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BEYOND COMPLIANCE: AN
EXPLORATORY INVESTIGATION OF
PROACTIVE SAFETY BEHAVIOURS WITHIN
THE CONTEXT OF WORK DRIVING
Klaire Somoray
Bachelor of Behavioural Science (Psychology Honours I)
Submitted in fulfilment of the requirements for the degree of
Doctor of Philosophy
Centre for Accident Research and Road Safety - Queensland
Faculty of Health, School of Psychology
Queensland University of Technology
2019
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving i
Keywords
Driving for work, educate, feedback inquiry, fixing safety issues, fleet safety,
intervene, leadership, meta-analysis, motivation, occupational health and safety,
organisational psychology, proactive safety behaviour, safety citizenship, safety
climate, safety compliance, safety participation, safety proactivity, structural equation
modelling, vehicle maintenance, voice, work drivers, work driving context, work
proactivity.
ii Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
Abstract
Road trauma is the main cause of work-related death in Australia. From 2002 to
2013, two-thirds of work-related deaths in the Australian workforce were attributed to
vehicle incidents on public roads and worksites. Similar trends were also found
overseas, suggesting that work-related road trauma is a significant public health issue
that needs to be addressed. However, organisations often fail to manage the risks
associated with work driving. Furthermore, current research on work driving safety
often focus on employees’ risky driving behaviours, placing a strong emphasis on
crashes and traffic violations as measures of work drivers’ safety performance. Yet,
researchers within the general occupational health and safety field (OHS) are already
focusing on proactive approaches to work safety management. For instance, the
concept of Proactive safety behaviours is currently being used as a leading safety
performance indicator within the OHS area of research.
The current program of research provides an exploratory investigation of
proactive safety behaviours within the context of work driving (PSB-WD). PSB-WD
is defined as: 1) behaviours that improve the context of the work environment to be
more supportive of safety – these behaviours that may not directly contribute to
workplace safety, but facilitate an environment that supports safety (i.e., behaviours
that create a positive environment for safety); 2) behaviours that aim to improve
workplace safety that cannot be forced (i.e., self-starting); and 3) behaviours that are
change-oriented which aim to improve the current workplace safety practices.
Using the available research on proactive safety behaviours and related
constructs, this research program developed a measurement and model of PSB-WD.
The current program of research comprises one meta-analysis and three quantitative
studies, which are briefly outlined below:
Study 1: Meta-analytic review of the current literature that identified the
contextual and cognitive mechanisms as antecedents of proactive safety
behaviours and related constructs. Data was extracted from 71 studies. This
review helped informed the research model that was proposed and utilised
for the current program of research.
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving iii
Study 2: A self-report measure for PSB-WD was developed using a
deductive approach to scale development. First, an item pool was generated
and later assessed by an expert panel (n = 5). This process forms the first part
of Study Two (Study 2a). Then the scale was pilot tested using N = 43
employees who drive for work (Study 2b). This study initially assessed the
reliability and dimensionality of the scale. Principal component analysis
(PCA) was used for this initial assessment. Then, the dimensionality of the
PSB-WD scale was further tested using a survey (via online and hardcopy)
with a sample of N = 300 employees who drive for work (Study 2c).
Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA)
were utilised for this further assessment.
Study 3: Using the same sample from Study 2c, the proposed PSB-WD
model was examined using structural equation modelling (SEM).
For Study 1, existing studies on proactive safety behaviours and related
constructs were reviewed. The review specifically focused on the contextual and
proximal antecedents of proactive safety behaviours using the safety proactivity model
by Curcuruto and Griffin (2017). The calculations for the meta-analysis were
conducted using the metafor package in R. More specifically, the H&S-type method
within the metafor package, which is based on Hunter and Schmidt’s (2014) meta-
analysis approach, was specifically used to calculate the pooled effect size estimates.
The meta-analytic calculations were conducted on 71 studies. Within the
identified contextual antecedents, safety climate, leadership, perceived organisational
support, trust, work autonomy showed significant effects on proactive safety
behaviours. Within the identified proximal antecedents, safety knowledge, safety
motivation, self-efficacy, perceived control and promotion focus also showed
significant effects on proactive safety behaviours. Out of the 71 studies reviewed, one
study examined workers’ participation in road safety practices, and another study
investigated safety voice using a sample of work drivers.
For Study 2, a deductive approach to scale development was conducted. The
scale development involved 3 phases: 1) item pool generation, 2) expert panel, and 3)
pilot testing of the scale. First, an item pool for the PSB-WD scale was generated using
the current measures on proactive safety behaviours and related constructs. Existing
iv Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
measures on general work proactivity were also consulted. These items were then
adapted to suit the work safety driving context. Using a nominal group technique, the
research candidate along with her supervisory team ranked and categorised the items
into possible dimensions of proactive safety behaviours. Second, an expert panel (N =
5) was approached to give further assessment on the content validity and clarity of the
items. These two-step process (item generation and expert panel) forms the first part
of Study 2 (Study 2a). The second phase of Study 2 involved the pilot testing of the
scale using a sample of employees who drive for work (N = 43). PCA was utilised for
the initial assessment of the scale and found eight potential dimensions of PSB-WD
scale, which included: feedback inquiry, helping / volunteerism, fixing responsibility,
vehicle maintenance, protection, intervene, knowledge sharing and voice.
For Study 2c, the dimensions of the PSB-WD scale were further assessed using
EFA and CFA using a sample of N = 300 employees who drive for work. The sample
completed the survey either online or via a hardcopy. The psychometric properties of
the scale were also examined. The results of the EFA demonstrated six dimensions of
PSB-WD and were confirmed using CFA. The final dimensions comprised feedback
inquiry, fixing responsibility, vehicle maintenance, intervene, educate, and voice. The
PSB-WD scale also showed good internal reliabilities, convergent validity and
divergent validity.
For Study 3, SEM was conducted to assess the proposed research model using
the same sample from Study 2c. It was hypothesised that safety climate
(organisational-level and group-level) and leader-member exchange (LMX) would
have significant relationships with employees’ proactive safety behaviours when
driving for work. Safety climate and LMX formed the contextual antecedents of the
research model. Furthermore, it was also hypothesised that anticipation focus,
perceived control and felt responsibility would also have significant relationships with
employees’ proactive safety behaviours when driving for work. These variables
formed the proximal antecedents of the model. To test the divergent validity of the
model, safety compliance and its associated proximal antecedent, preventative focus,
was added to the proposed research model.
The findings revealed that group-level safety climate, LMX, anticipation focus,
perceived control and felt responsibility demonstrated significant relationships with
work drivers’ proactive safety behaviours. More specifically, the results showed that
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving v
group-level safety climate has a significant indirect effect on work drivers’ proactive
safety behaviours via anticipation focus, perceived control and felt responsibility,
while LMX showed a significant direct effect on work drivers’ proactive safety
behaviours. Anticipation focus, perceived control and felt responsibility also showed
significant direct effects on work drivers’ proactive safety behaviours.
On the other hand, organisational-level safety climate did not demonstrate any
significant effects on proactive safety behaviours, but it showed a significant direct
effect on safety compliance behaviours. Preventative focus also showed a direct effect
on safety compliance behaviours, but not on proactive safety behaviours.
The current program of research appealed for a proactive measure of safety
performance within the work driving context, taking insights from research on
proactive safety behaviours from the fields of traffic safety, general organisational
psychology and OHS. The PSB-WD measure that was developed could be used as a
complementary measure of behaviour-based safety performance within the context of
work driving. Furthermore, this research program also provided a model on how
organisations can engage their work drivers and management to be more proactive in
managing risks while driving for work. More specifically, the current program of
research showed that group-level safety climate, the quality of leader’s relationship
with employees, as well as employee’s propensity to anticipate risk, perceived control
and felt responsibility towards work driving safety is critical to work drivers’
engagement with proactive safety behaviours. The program of research has made
significant theoretical and practical contributions by exploring the possible application
of the proactive safety behaviour construct within the context of work driving.
vi Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
Table of Contents
Keywords .............................................................................................................................. i Abstract ................................................................................................................................ ii Table of Contents ................................................................................................................ vi List of Figures ..................................................................................................................... ix List of Tables ....................................................................................................................... x List of Abbreviations .......................................................................................................... xi List of Publications Resulting from the PhD Research Program ....................................... xii List of Publications Outside of the PhD Program ............................................................. xiii Statement of Original Authorship ...................................................................................... xv Acknowledgements ........................................................................................................... xvi
Chapter 1: Introduction .................................................................................................... 1 1.1 Introductory Statement ............................................................................................ 1 1.2 Study Background and Rationale ............................................................................ 1
1.2.1 The Issue of Work Driving ................................................................................. 1 1.2.2 Current Work Driving Safety Management ....................................................... 4
1.3 A Need for an Alternative Framework ................................................................... 7 1.3.1 Older Models of Safety Management AKA Safety-I ......................................... 9 1.3.2 Newer Models of Safety Management AKA Safety-II ...................................... 9
1.4 A Proactive Measure of Safety Performance Within the Work Driving Context . 12 1.5 Chapter Summary and Key Learnings .................................................................. 15
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions ......... 16 2.1 Introductory Statement .......................................................................................... 16 2.2 Background and Origins of Proactive Safety Behaviour ...................................... 16
2.2.1 Contextual Performance ................................................................................... 18 2.2.2 Organisational Citizenship Behaviour .............................................................. 19 2.2.3 Proactivity ......................................................................................................... 21 2.2.4 Bringing it all together ...................................................................................... 23
2.3 Similar Concepts in Traffic Safety Research ........................................................ 24 2.4 Chapter Summary and Key Learnings .................................................................. 27
Chapter 3: Overview of Research Program ................................................................... 29 3.1 Introductory Statement .......................................................................................... 29 3.2 Research Questions, Aim and Objectives ............................................................. 30 3.3 Demarcation of Scope ........................................................................................... 31 3.4 Thesis Outline ....................................................................................................... 32
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours .............................................................................................................. 34 4.1 Introductory Statement .......................................................................................... 34
4.1.1 Purpose of the Study ......................................................................................... 34 4.1.2 Scope of the Study ............................................................................................ 35
4.2 Framework for Modelling Proactive Safety Behaviours ...................................... 36 4.2.1 Contextual Antecedents .................................................................................... 37
Safety Climate ........................................................................................................... 37 Leadership, Perceived Organisational Support and Organisational Trust ................. 40 Work Demands and Work Autonomy ....................................................................... 45
4.2.2 Proximal Antecedents ....................................................................................... 47 Safety Knowledge and Safety Motivation ................................................................. 48 Regulatory Focus, Self-efficacy and Perceived Control ........................................... 49
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving vii
Relevance to work driving safety ............................................................................. 50 4.2.3 Summary of the Literature ............................................................................... 51
4.3 Method .................................................................................................................. 51 4.3.1 Search Strategy ................................................................................................. 51 4.3.2 Inclusion and Exclusion Criteria ...................................................................... 53 4.3.3 Coding .............................................................................................................. 55 4.3.4 Meta-analysis calculations ............................................................................... 55
4.4 Results .................................................................................................................. 57 4.4.1 Study Characteristics ........................................................................................ 57 4.4.2 Meta-analytic Correlations ............................................................................... 58 4.4.3 Contextual Antecedents ................................................................................... 66 4.4.4 Proximal Antecedent ........................................................................................ 67 4.4.5 Selected Studies Relevant to Work Driving Safety .......................................... 67
4.5 Discussion ............................................................................................................. 68 4.5.1 Practical Implications ....................................................................................... 71 4.5.2 Limitations and Future Directions .................................................................... 72 4.5.3 Chapter Summary and Key Learnings ............................................................. 72
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context ....................................................................................................... 74 5.1 Introductory Statement ......................................................................................... 74 5.2 Purpose of the Study ............................................................................................. 76 5.3 Method and Results of Study 2a – Item Generation and Expert Panel ................. 76
Item Pool Generation ................................................................................................ 77 Expert Panel .............................................................................................................. 79
5.4 Method and results of Study 2b – Pilot Study ...................................................... 81 Method ...................................................................................................................... 81 Results ....................................................................................................................... 81
5.5 Summary of Study 2a and 2b ............................................................................... 86 5.6 Method and Results of Study 2c ........................................................................... 88
5.6.1 Method ............................................................................................................. 88 5.6.2 Results of Study 2c ........................................................................................... 88
Overview of Data Analysis ....................................................................................... 88 Assessment of Missing Data ..................................................................................... 89 Participant Demographics and Work Driving Exposure ........................................... 89
5.6.3 Exploratory Factor Analysis ............................................................................. 91 Assumption Checking ............................................................................................... 91 Initial Exploratory Faction Analysis ......................................................................... 91 Final Exploratory Factor Analysis ............................................................................ 94
5.6.4 Confirmatory Factor Analysis .......................................................................... 96 Overview of Confirmatory Factor Analysis .............................................................. 96 Results of the Confirmatory Factor Analysis ............................................................ 97 Validity Assessment.................................................................................................. 99
5.7 Overall Discussion of Study 2 ............................................................................ 100 5.7.1 Theoretical and Practical Implications ........................................................... 103 5.7.2 Limitations and Future Studies ...................................................................... 104 5.7.3 Concluding Remarks ...................................................................................... 105
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)............................................................................................................. 106 6.1 Introductory Statement ....................................................................................... 106
6.1.1 Contextual Antecedents ................................................................................. 107 Safety Climate ......................................................................................................... 107 Leader-Member Exchange. ..................................................................................... 109
6.1.2 Proximal Antecedents .................................................................................... 111 Proactive Future Orientation – Anticipation-Focus ................................................ 111
viii Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
Proactive Motivational States – Can Do and Reason To ........................................ 112 6.2 Non-Proactive Antecedent, Mediators and Safety Compliance .......................... 114 6.3 Study Hypotheses ................................................................................................ 117 6.4 Method ................................................................................................................ 118 6.5 Measures ............................................................................................................. 118
6.5.1 Proactive Safety Behaviours within the Work Driving Context (PSB-WD). . 118 6.5.2 Safety Climate Survey – Short Form. ............................................................. 119 6.5.3 Leader-Member Exchange (LMX). ................................................................ 119 6.5.4 Anticipation Focus, Perceived Control and Felt Responsibility. .................... 119 6.5.5 Prevention Focus and Safety Compliance. ..................................................... 120
6.6 Data Analysis ...................................................................................................... 121 6.6.1 Overview of Data Analysis ............................................................................. 121
6.7 Results ................................................................................................................. 121 6.7.1 Treatment of Missing Data ............................................................................. 121 6.7.2 Aggregation of Items ...................................................................................... 122 6.7.3 Assumption Checking ..................................................................................... 122
Common Method Variance Test ............................................................................. 123 6.7.4 Description of Data ......................................................................................... 124 6.7.5 Who are more likely to engage in Proactive Safety Behaviours? ................... 126 6.7.6 Hypothesis Testing using Structural Equation Modelling .............................. 128
Test of Direct and Indirect Effects .......................................................................... 128 Hypothesis on the Non-Proactive States, Motivation and Outcomes ...................... 130
6.8 Discussion ........................................................................................................... 131 6.8.1 Limitations and Future Research .................................................................... 134 6.8.2 Chapter Summary and Key Learnings ............................................................ 135
Chapter 7: Discussion and Conclusions ....................................................................... 137 7.1 Introductory Statement ........................................................................................ 137
7.1.1 Overall Findings in Relation to RQ1 .............................................................. 138 7.1.2 Overall Findings in Relation to RQ2 .............................................................. 142 7.1.3 Overall Findings in Relation to RQ3 .............................................................. 143 7.1.4 Theoretical Implications and Contributions ................................................... 144 7.1.5 Strengths and Practical Implications .............................................................. 147 7.1.6 Limitations and Suggestions for Future Research .......................................... 150 7.1.7 Concluding Remarks ...................................................................................... 152
Bibliography .................................................................................................................... 153
Appendices ....................................................................................................................... 175
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving ix
List of Figures
FIGURE 2.1 OVERVIEW OF THE HISTORICAL ORIGINS OF PROACTIVE SAFETY RESEARCH ....................... 18 FIGURE 2.2 FIELDS OF RESEARCH THAT HELPED INFORM THE PROACTIVE SAFETY BEHAVIOUR
CONSTRUCT WITHIN THE WORK DRIVING CONTEXT AND THE FOUNDATION OF THE CURRENT
PROGRAM OF RESEARCH .............................................................................................................. 27 FIGURE 3.1 OUTLINE OF THE PROGRAM OF RESEARCH AND ITS PRESENTATION IN THIS THESIS ............. 33 FIGURE 4.1 CURCURUTO AND GRIFFIN’S (2018) MODEL OF ANTECEDENTS OF SAFETY PROACTIVITY. THE
GRAY SHADED BOXES WERE THE FOCUS OF THE CURRENT META-ANALYSIS. ............................... 36 FIGURE 4.2 SEARCH STRATEGY FOR THE SYSTEMATIC REVIEW AND META-ANALYSIS .......................... 53 FIGURE 5.1 HYPOTHESISED DIMENSIONS OF PROACTIVE SAFETY BEHAVIOURS WITHIN THE WORK
DRIVING CONTEXT (PSB-WD; LEFT) AND THE DIMENSIONS EXTRACTED FROM PCA USING THE
PILOT STUDY DATA (RIGHT). ........................................................................................................ 87 FIGURE 5.2 RE-SPECIFIED MEASUREMENT MODEL OF PSB-WD SCALE ................................................. 99 FIGURE 5.3 HYPOTHESISED DIMENSIONS OF PROACTIVE SAFETY BEHAVIOURS WITHIN THE WORK
DRIVING CONTEXT FROM THE ITEM GENERATION (PSB-WD; LEFT) AND THE DIMENSIONS
EXTRACTED FROM PCA USING THE PILOT STUDY DATA (MIDDLE) AND DIMENSIONS EXTRACTED
FROM THE EFA AND CFA (LEFT)............................................................................................... 102 FIGURE 6.1 RESEARCH MODEL ............................................................................................................ 106 FIGURE 6.2 RESEARCH MODEL WITH HYPOTHESES .............................................................................. 117 FIGURE 6.3 RESPECIFIED MODEL AFTER CONSULTING THE MODIFICATION INDICES ............................ 129 FIGURE 6.4 RESPECIFIED MODEL WITH STANDARDISED REGRESSION ESTIMATES, ONLY SHOWING THE
SIGNIFICANT PATHS. .................................................................................................................. 130 FIGURE 6.5 RESEARCH MODEL WITH PREVENTION FOCUS AND SAFETY COMPLIANCE TO TEST THE
DISCRIMINANT VALIDITY ........................................................................................................... 131
x Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
List of Tables
TABLE 1.1 TRADITIONAL MODELS OF SAFETY VERSUS HRO AND RESILIENCE ENGINEERING. THIS
TABLE WAS ADAPTED FROM HOLLNAGEL ET AL. (2013, P. 26). .................................................... 11 TABLE 4.1 SEARCH TERMS USED FOR EACH DATABASE ......................................................................... 52 TABLE 4.2 TERMINOLOGIES AND MEASURES USED FOR THE CURRENT STUDY ....................................... 54 TABLE 4.3 STUDIES INCLUDED IN THE DATA-ANALYSIS ......................................................................... 59 TABLE 4.4 RESULTS OF THE META-ANALYSIS ........................................................................................ 65 TABLE 5.1 CHAPTER SECTION, PHASES, METHODOLOGY AND PURPOSES OF STUDY 2A, 2B AND 2C ....... 76 TABLE 5.2 FINAL PCA FOR THE PILOT STUDY SURVEY PSB-WD ......................................................... 84 TABLE 5.3 REVISED AND ADDED ITEMS ................................................................................................. 86 TABLE 5.4 DEMOGRAPHIC AND WORK INFORMATION OF PARTICIPANTS ................................................ 90 TABLE 5.5 INITIAL PAF WITH PROMAX ROTATION ................................................................................ 93 TABLE 5.6 FINAL PAF WITH PROMAX ROTATION .................................................................................. 95 TABLE 5.7 ASSESSMENT OF MODEL FIT ................................................................................................. 97 TABLE 5.8 DISCRIMINANT AND CONVERGENT VALIDITY ..................................................................... 100 TABLE 6.1 MEANS, STANDARD DEVIATIONS, CRONBACH ALPHA AND INTER-CORRELATIONS BETWEEN
THE VARIABLES .......................................................................................................................... 125 TABLE 6.2 BIVARIATE CORRELATIONS BETWEEN PROACTIVE SAFETY BEHAVIOUR VARIABLES AND
WORK DRIVING EXPOSURE AND RISK .......................................................................................... 127 TABLE 6.3 STANDARDISED REGRESSION WEIGHTS AND 95% BIAS-CORRECTED CONFIDENCE INTERVALS
WITH 10,000 BOOTSTRAP SAMPLING .......................................................................................... 129 TABLE 7.1 OVERVIEW OF DESIGN AND METHODOLOGY STRUCTURED BY THE RESEARCH QUESTIONS .. 137
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving xi
List of Abbreviations
Abbreviation / Symbol Definition
α Cronbach’s alpha
β Beta
χ2 Chi-square
BCa Bias-corrected and accelerated bootstrap
CI Confidence Intervals
CFA Confirmatory Factor Analysis
CMB Common Method Bias
EFA Exploratory Factor Analysis
HRO High Risk Organisation
LMX Leader-Member Exchange
MVA Missing Value Analysis
OHS Occupational Health and Safety
PCA Principal Component Analysis
PAF Principal Axis Factoring
PSB-WD Proactive Safety Behaviours within the Work Driving
Context
SEM Structural Equation Modelling
xii Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
List of Publications Resulting from the PhD Research Program
Conference Paper:
Somoray K., Newton C., Lewis I., Wishart D. (2019). Development of proactive safety behaviour scale within the work driving context. In P Arezes (Eds.), Advances in Safety Management and Human Factors (pp. 470-479) Switzerland: Springer. doi: https://doi.org/10.1007/978-3-319-94589-7_46
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving xiii
List of Publications Outside of the PhD Program
Academic Journals:
Street, T. D., Somoray, K., Richards, G. C., & Lacey, S. J. (2019). Continuity of care for patients with chronic conditions from rural or remote Australia: A systematic review. Australian Journal of Rural Health. doi: 10.1111/ajr.12511 Street, T., Lacey, S., & Somoray, K. (2019). Employee stress, reduced productivity, and interest in a workplace health program: a case study from the Australian mining industry. International journal of environmental research and public health, 16(1), 94. doi: /10.3390/ijerph16010094
Debnath, A.K., Haworth, N., Schramm, A., Heesch, K.C., Somoray, K. (2018). Factors influencing noncompliance with bicycle passing distance laws. Accident Analysis and Prevention, 115, 137-142. doi: 10.1016/j.aap.2018.03.016c
Wishart, D., Somoray, K., & Evenhuis, A. (2017). Thrill and adventure seeking in risky driving at work: The moderating role of safety climate. Journal of Safety Research, 63, 83-89. doi: 10.1016/j.jsr.2017.08.007
Wishart, D., Somoray, K., & Rowland, B. (2017). Role of thrill and adventure seeking in risky work-related driving behaviours. Personality and Individual Differences, 104, 362-367. doi:10.1016/j.paid.2016.08.033
Somoray, K., Shakespeare-Finch, J., & Armstrong, D. (2017). The impact of personality and workplace belongingness on mental health workers’ professional quality of life. Australian Psychologist, 52, 52-60. doi: 10.1111/ap.12182
Book Chapters:
Wishart, D., Rowland, B., & Somoray, K. (2019). Safety citizenship behaviour: A complimentary paradigm to improving safety culture within the organisational driving setting. In N. J. Ward, B. Watson & T. Özkan (Eds.), Traffic Safety Culture: Theory, Measurement and Application, Howard House, Bingley: Emerald Publishing Ltd.
Conference Papers:
Licina, P., Johnston, E., Somoray, K., Rakotonirainy, A., & King, M. (2017). Fitness to drive after lumbar discectomy – A pilot study using an advanced driving simulator. In 2017 Spine Society of Australia 28th Annual Scientific Meeting, 7-9 April, 2017, Hobart, Tasmania.
xiv Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
Somoray, K. & Wishart, D. (2016). Review of research methodologies in investigating work-related driving behaviour. In 2016 Australasian Road Safety Conference, 6-8 September 2016, Canberra, A.C.T.
Wishart, D., Somoray, K., & Rowland, B. (2016). Reducing reversing vehicle incidents in Australian fleet settings – A case study. In Stanton, Neville A., Landry, Steve, Di Bucchaianico, Giuseppe, & Vallicelli, Andrea (Eds.) Advances in Human Aspects of Transportation. Springer, 733-744.
Wishart, D., Somoray, K., & Rowland, B. (2016). A longitudinal study evaluating work driving safety interventions implemented by a number of organisations. In 2016 Australasian Road Safety Conference, 6-8 September 2016, National Convention Centre, Canberra, A.C.T.
Rowland, B., Wishart, D., & Somoray, K. (2015). Organisational driving safety systems analysis: fleet safety situational issues and system gaps. In 2015 Australasian Road Safety Conference, 14-16 October 2015, Gold Coast, QLD.
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving xv
Statement of Original Authorship
The work contained in this thesis has not been previously submitted to meet
requirements for an award at this or any other higher education institution. To the best
of my knowledge and belief, the thesis contains no material previously published or
written by another person except where due reference is made.
Signature: QUT Verified Signature
Date: 14 June 2019
xvi Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving
Acknowledgements
The past three years have flown so fast. My journey in work driving safety
research started four years ago, when Darren asked me to work for him as a Research
Assistant at CARRS-Q. Since then, I have been fortunate to be part of various research
projects, within and outside the area of work driving safety. My passion for research,
and especially for statistics and data analysis, has flourished over the years.
This passion for research continues to grow. For a large part, I have my
supervisors, Darren, Cameron and Ioni, to thank for that. I always look forward to our
fun meetings and email chats. Cam and Ioni, you were not in the original supervisory
team, but you took me on, and provided support as if you were there from the start.
Thank you Darren for always believing in me, thank you Cam for the statistical advice
(and crude jokes), and thank you Ioni for the swift feedback, constructive comments
and constant encouragement. I could not have asked for better supervisors. I also
would like to acknowledge QUT scholarship for the financial support.
To my wonderful friends. Thank you for the continuous support and encouraging
messages, even if I've been hiding in my cave or forget to reply. Special thanks to
John, Kai, Jaggy, Evie and Ada for helping me de-stress. John, you've been there from
the beginning. You've always listened, and continue to listen, to my nerdy discussions.
To the friends I made during my PhD journey - especially Sep, Mahrokh, Wahi
and Raniya. You have been my constant rock. The laughter, the late night chats, the
pep talks, the frequent "why are we doing this again?" discussions, the dinners, the
picnics, the way we celebrate each other's small wins - I am finishing my thesis with a
big smile because of you guys. Thank you.
To Michelle. You've been my source of comfort and stability, especially in the
past few months. You always listen to my stress rants – cheering me on and brightening
up my day. Thank you for the continuous love, patience, encouragement and support.
I am so grateful to have you in my life and I look forward to our future travels.
And lastly to my family, especially to my Mom and Dad. You always
encouraged me in everything that I do. You always celebrate my achievements,
however small. Your love and guidance have kept me going and your hard work has
Beyond Compliance: An Exploratory investigation of proactive safety behaviours within the context of work driving xvii
always been my source of inspiration. I truly appreciate everything you do for me, but
I know that I can never thank you enough. Ma and Pa, I dedicate my work and
achievements to both of you.
Chapter 1: Introduction 1
Chapter 1: Introduction
1.1 INTRODUCTORY STATEMENT
The current program of research aims to explore the concept of proactive safety
behaviour as a possible indicator of safety performance within the work driving
context. This research is important because work-related road trauma is a significant
public health issue. Organisations also have the legal responsibility to ensure the safety
of their employees while driving for work. Using theoretical frameworks and
constructs from organisational psychology, occupational health and safety (OHS) and
traffic safety, the overarching aim of this program of research was to examine the
concept of proactive safety behaviours and its possible application within the work
driving context.
This chapter begins by providing the background and rationale for the research
program. Relevant literature on work driving safety is critically reviewed and
summarised, with a specific focus on the significant impact of work-related road
trauma on the public’s health and safety. The gaps within the management of work
driving safety, from a practitioner and research point of view, are also highlighted.
A need for an alternative framework for managing work driving safety is
essential. High Reliability Organisation (HRO) Theory and Resilience Engineering,
also known as Safety-II models, are specifically used as the theoretical lens to guide
the progression of the program of research. Before the discourse on these models, the
traditional models of occupational safety (Safety-I) and the shift towards the more
recent models are discussed. Then, a need for a proactive measure of safety behaviour
within the work driving context is proposed.
1.2 STUDY BACKGROUND AND RATIONALE
1.2.1 The Issue of Work Driving
Deaths and injuries resulting from a vehicle crash is a significant public health
issue that needs to be addressed (Robb, Sultana, Ameratunga, & Jackson, 2008).
Globally, road trauma is associated with 1.3 million deaths and up to 50 million non-
fatal injuries each year, costing governments an estimated 3% of their gross domestic
2 Chapter 1: Introduction
product annually (World Health Organization, 2015). In Australia, road crashes result
in an average of 1,400 deaths and 32,500 serious injuries annually with an estimated
cost of $27 billion to the economy (Department of Infrastructure Regional
Development and Cities, 2018).
These human and societal costs are tragic and unnecessary, given that the
majority of road traffic incidents are preventable (National Safety Council, 2014;
World Health Organization, 2015). However, despite the overwhelming number of
deaths and injuries resulting from a road crash, there seems to be a general sense of
complacency and acceptance towards road traffic risks (National Safety Council,
2014). It is possible that due to the repeated exposure to driving, a large majority of
people see driving as an everyday task and the associated risks of injury and fatality
are often overlooked (Banks, 2008; National Safety Council, 2014).
This complacency towards driving risks is also observed within organisations
(Banks, 2008). For instance, most organisations in high risk industries (e.g., mining
and constructions) often have zero harm policies for central work processes but often
do not have any comprehensive safety policies for driving during working hours
(Newnam, Wishart, & Newton, 2014). This lack of attention on workers’ safety while
driving is problematic, given that work-related driving incidents present the majority
of casualties and financial costs to society (Australian Transport Council, 2011).
According to the Australian Transport Council (2011), fifteen percent of the
national road toll in Australia are a result of work-related crashes. This proportion is
even higher if commuting to and from work is considered as work-related travel. On a
more concerning note, while the total number of work fatalities and serious injuries is
decreasing, the proportion of vehicle-related incidents at work has remained relatively
stable between 2003 and 2016 (Safe Work Australia, 2018b). A recent report by Safe
Work Australia (2018b) demonstrated that the proportion of vehicle crashes as a
mechanism of fatality and serious injury at work has been between 35% and 43% for
13 years1. These figures suggest that, each year, over one-third of worker fatalities are
attributed to the result of a road crash. In addition, analysis of worker fatalities from
2007 to 2016 revealed that nearly two-thirds (64%) of deaths in the Australian
1 This proportion remained relatively stable between 2003 and 2016, aside from year 2015 when the proportion was at its lowest at 28%.
Chapter 1: Introduction 3
workforce involved a vehicle (Safe Work Australia, 2018a). Of these vehicle-related
deaths, over 45% occurred due to a vehicle collision on public roads (Safe Work
Australia, 2018a). It is important to note that, while these data examined crashes from
both light and heavy vehicle fleets, it is likely that the majority of the crash data is
derived from heavy vehicle industries as these organisations are governed under
federal laws and regulations. Therefore, the available data may be underestimating the
extent of the issue as crashes from light vehicle fleets are not always recorded
(Stuckey, Pratt & Murray, 2013).
Other industrialised countries also face similar issues. Data analysis conducted
by the European Agency for Safety and Health at Work (2010) revealed that road
trauma accounts for 29% of worker fatalities throughout Europe. In the United
Kingdom, it was reported that 7% of the national traffic fatalities were work-related
and this number increases to 23% when commercial vehicles were involved (Murray,
2007). Road crash is also the leading cause of work-related deaths in the United States
(Pratt, 2003). In 2014, nearly a quarter of fatal work-related injuries suffered by
American employees occurred on the road (Bureau of Labor Statistics, 2014). From
these reports, it is clear that driving is one of the most hazardous job activities for
workers to undertake (Haworth, Greig, & Wishart, 2008; Wishart, 2015).
In addition to the tragic loss of lives, Wheatley (1997) reported that occupational
driving incidents also cost the Australian government approximately 1 billion to $1.5
billion annually, while a study by Davey and Banks (2005) estimated an average of
$28,000 per reported work-related vehicle incident in total insurance costs for
companies. Motor vehicle incidents are also over-represented in Australian workers’
compensation claims. From 2010 to 2011, vehicle incidents were the most common
cause of Australian compensated fatalities, accounting for almost one-third of all
compensated deaths (Safe Work Australia, 2013).
Clearly, there are notable benefits to conducting research within the work-related
road safety domain. Many lives and financial costs could be saved if risks related to
work driving were properly managed and adequate measures were put in place
(Wishart, 2015). In order to achieve high levels of safety while driving for work,
management and workers must be proactive in addressing the risks related to work
driving. Research should focus on investigating the leading indicators of safety
performance that aim to improve safety in the work driving domain instead of reacting
4 Chapter 1: Introduction
to past events (Newnam et al., 2014). While research over the past decade is starting
to focus on leadership practices and system-based approaches to understanding work
driving safety (e.g., Newnam & Goode, 2015; Newnam & Oxley, 2016), the majority
of the research and practice in this field still tend to focus on employees’ involvement
in crashes and traffic violations as measures of safety performance when driving for
work (Newnam et al., 2014). Furthermore, these incidents are often used by
organisations to inform their risk management process which, in turn, provides a
superficial antidote to a problem without fully understanding the cause (Wishart,
2015). For example, a crash is attributed to speeding, but the contributing factors (such
as speeding to meet clients on time) may not often be investigated. Arguably, there is
a need to shift from the reactive perspective that currently dominates the field of work
driving safety to that of a more proactive risk management approach.
While research and practice in the work driving safety field are still primarily
focused on lagging indicators of safety (Newnam et al., 2014), the general OHS field
is already placing greater emphasis on concepts that go beyond accidents, injuries and
minimum safety compliance to further improve safety at work (Curcuruto & Griffin,
2017). In order to adequately address work driving safety, there is a clear need for a
perspective shift in the way that researchers and organisations currently examine risk
management when driving for work (Wishart, 2015).
1.2.2 Current Work Driving Safety Management
Workplace health and safety legislation in Australia also requires organisations
to be responsible for the safety of their employees, and this includes driving for work
(Robb et al., 2008; Safe Work Australia, 2016a). Within this legislation, vehicles used
for work are defined as part of a workplace and driving for work is considered a work-
related task (Austroads, 2018). Recently, the industrial manslaughter provisions in the
Work Health and Safety Act (2011) makes it a criminal offence for employers and
senior officers in Queensland to negligently cause the death of a worker while
undertaking work-related tasks or during working hours (including a work break;
Queensland Government, 2018). Since work-related travel is considered a job task,
employers can also be held liable for not implementing their legal obligations and
ensuring a safe system of work when employees use motor vehicles for work (Wishart,
2015).
Chapter 1: Introduction 5
Furthermore, a large proportion of road commute within Australia is work-
related. In 2012, 20% of the registered vehicles in Australia include commercial
vehicles, trucks and buses and 33.5% of the annual mileage travelled by Australians
are for business purposes (Australian Bureau of Statistics, 2012). However,
organisations often fail to mitigate the risks associated with work driving with the same
level of diligence as other work-related hazards (Wishart, 2015).
There is a significant contrast in the management of risks between general work
tasks and work driving. For example, risk management within mining or construction
industries operate under the ‘zero harm’ framework (Wishart, 2015). Within this
framework, any activity that compromises safety is not tolerated and unacceptable.
Furthermore, these industries allocate appropriate resources in building workplace
health and safety management teams, training and awareness programs, and safety
consultations to ensure compliance with safety procedures and policies (Wishart,
2015). However, when managing employees’ safety when driving for work,
organisations often lack policies and procedures on this particular work activity
(Haworth et al., 2008; Murray, 2007; Murray, Newnam, Watson, Davey, & Schonfeld,
2003; Wishart, 2015). Wishart (2015) further argued that risk management on work
driving often is inadequately resourced (e.g., lack of personnel and education
programs) and often attract lower levels of diligence. Indeed, it is not surprising that
safe driving practices are usually compromised and employees who drive for work
suffer from more severe and frequent crashes at work (Stuckey, Lamontagne, Glass,
& Sim, 2010).
If organisations do implement risk management for work driving, they often take
precautions following a crash or violation, and the efficacy of this approach is limited
by the analysis of incidents that happened in the past (Wishart & Davey, 2004). In a
project that evaluated work-related driving safety practices in Australia, Murray et al.
(2003, p. 10) stated that senior managers “tend to focus on fleet safety as a reactive
response to a range of negative events such as being involved in a fatality or very
expensive crash” (p. 10). Murray et al. (2003) also found that management of work-
related crashes typically centre on the employee – usually putting the blame on the
work driver when an incident occurs (Murray et al., 2003). Wishart and Davey (2004,
p. 2) also reported that organisations often take a “silver bullet approach aimed at
developing and implementing a single countermeasure or intervention strategy to
6 Chapter 1: Introduction
encompass and address all fleet related road safety issues” (p. 2). This reactive
approach to safety often emphasises the fault of those involved, instead of encouraging
a deeper examination of the organisational processes that may have played a major
role in the occurrence of the incident (Hudson, 2003).
Recently, work led by Newnam (e.g., Newnam & Goode, 2015; Newnam,
Goode, Salmon & Stevenson, 2017; Warmerdam, Newnam, Sheppard, Griffin &
Stevenson, 2017; Newnam & Oxley, 2016; Newnam, Lewis & Watson, 2012), Salmon
(e.g., Salmon, McClure & Stanton, 2012; Salmon and Lenne, 2015) and has been
applying a systems-based approach to road safety. This systems-based approach
challenges the reductionist approach of ‘blaming the driver’ that focuses on unsafe
driving behaviours and instead examines the road transportation system as a whole
(Newnam and Goode, 2015). For instance, Newnam and Goode (2015) stated that the
road freight system has the characteristics of a complex sociotechnical system.
Consequently, a crash caused by fatigue may indicate the driver’s disregard of fatigue
management policies and/or could indicate the supervisor’s lack of involvement on
journey management or the company’s policies on production over safety (Newnam
and Goode, 2015). While these recent studies look at the complexity of the road
transportation systems as factors of road incidents (rather than just ‘blaming the
driver’), these studies still look at crashes as a performance indicator.
Furthermore, current risk management in work driving promotes a strong focus
on compliance with standard rules and regulations rather than promoting a proactive
approach to safety (Murray et al., 2003). This approach is based on the premise that
safe driving is mostly reliant on workers’ compliance with traffic laws and
organisations’ safety policies and procedures (if available). While compliance with
safety policies reduces the risk of accidents and injuries at work (Christian, Bradley,
Wallace, & Burke, 2009), research suggests that such incidents continue to occur even
when workers comply with rules and regulations (Hu, Yeo, & Griffin, 2018). These
incidents occur because workers comply with safety procedures in different manners,
and not all standards and procedures in place are appropriate to work activities (Hu et
al., 2018). Hu et al. (2018) argued that blindly following rules instead of doing the task
safely can be as dangerous as non-compliance behaviours. Thus, it is important to
examine a proactive approach in managing risks while driving for work, not only for
Chapter 1: Introduction 7
the safe and successful operations of organisations, but also for the safety of the
community.
1.3 A NEED FOR AN ALTERNATIVE FRAMEWORK
While research on proactive safety management approaches within the general
OHS) field is readily available, there is very limited research on this topic within the
work driving area (Mooren, 2016). Research on work driving safety is already limited
in the first place (Wishart, 2015) and Mooren (2016) argued that there seemed to be
little crossover between the general OHS research and fleet safety. For instance, the
earliest accounts of driver management programs in the literature appeared to be
conducted in 1995 by Adams-Guppy and Guppy (1995) and Kedjidjian (1995)2. Using
a sample of British company car drivers, Adams-Guppy and Guppy (1995) found that
the participants who reported to exceed speeding limits placed more importance on
getting to appointments on time. Therefore, they recommended for organisations to
apply realistic scheduling to reduce time-urgency factors and to reduce employees’
speeding behaviours. Kedjidjian (1995), on the other hand, recommended defensive
driver techniques, driver education and installation of vehicle safety features to
manage employees’ safety while driving for work.
Aside from these studies, it was only around the turn of the century (2000’s) that
interest piqued on driver management programs that target other factors, apart from
driving error, as potential causes of work driving incidents (Haworth et al., 2008).
Previously, management of work driving were based on the ‘carrots-and-stick’
approach. These programs usually involved giving rewards for the absence of traffic
violations and applying punishments when workers get into road incidents. On the
other hand, more recent studies within the OHS field is moving away from the ‘carrots-
and-stick approach’, and human errors and violations are being seen as the
consequence of organisational shortcomings rather than the cause of safety incidents.
Findings from the OHS field are, however, not being implemented within the area of
work driving safety (Mooren, 2016).
2 These findings are based on Haworth, Tingvall and Kowadlo’s (2000) review of best practices in fleet safety.
8 Chapter 1: Introduction
There is a clear need for an alternative framework for managing work driving
risks. This framework should place less focus on lagging indicators3 and more focus
on identifying and recognising leading indicators (Lofquist, 2010). Lofquist (2010)
argued that this framework would require a new set of soft metrics (i.e., attitudes and
behaviours) captured and reported by work drivers which could help anticipate risks
before incidents occur. To guide the current program of research, the frameworks of
HRO and Resilience Engineering (also known as Safety-II) had been utilised.
Before starting the discussion on these frameworks, however, it is important to
note that several safety models exist within the general road safety context (e.g.,
Haddon Matrix; Safety Systems Model). Still, given the occupational nature of the
current program of research, it is arguably more appropriate to examine the theoretical
developments within the general OHS field in identifying and conceptualising leading
indicators that could be used within the work driving setting.
Several researchers have also proposed frameworks for improving work driving
safety (e.g., Stuckey et al.’s [2010] Occupational Light Vehicle Systems Model;
Murray, Watson, King, Pratt & Darby’s [2014] Haddon Matrix for work driving).
While these models are useful in identifying the different factors that could influence
work drivers’ safety from the individual (e.g., drivers’ characteristics) and broader
level (e.g., organisational, community) perspectives, these models do not provide
descriptions on what indicators could be measured to assess the work drivers’ safety
performance before a crash occurs. These models are still focused on lagging
indicators, rather than leading indicators. On the other hand, Safety-II models offer an
alternative approach to understanding safety and provide a basis on what these leading
indicators could be. Therefore, these safety frameworks were utilised as the theoretical
lens which guided the progression of the current research program. The purpose of
applying these frameworks is to explore the possible ways to measure leading
indicators of safety performance within the work driving context. Furthermore, these
frameworks would provide further rationale on the importance of the current program
of research.
3 Lagging indicators measure the safety performance of an organisation based on past incidents (e.g., frequency and severity of injuries) while leading indicators measure safety events that may happen in the future (O’Neill, Martinov-Bennie, Cheung, & Wolfe, 2013).
Chapter 1: Introduction 9
To fully understand the concept of Safety-II, a discussion of older safety models
or Safety-I is first required.
1.3.1 Older Models of Safety Management AKA Safety-I
Traditional models of safety are rationalist and prescriptive, often attributing the
cause of work accidents to human failure and putting little emphasis on the role of
broader organisational structures and social contexts in accident causation (e.g.,
Heinrich’s Domino Theory; Toft, Dell, Klockner, & Hutton, 2012). Within the
traditional models of safety management, the main objective is to keep accidents and
risks to a minimum level, with rules seen as “essentially static and in a sense linear”
(Hale & Borys, 2013, p. 211). Hale and Borys (2013) argued that this approach to
safety is based on major accidents where rule violation is identified as the cause. As a
response, management calls for more stringent and extensive rules to prevent
recurrence of such events. Close supervision, safety rules and regulation, employee
education and accident analysis are encouraged to limit the “unsafe acts” performed
by employees (Safe Work Australia, 1996).
These models of safety have persisted over a number of decades (from early
1930s to 1980s) and some of its influence is still evident in the way that OHS is
managed in organisations (Hale & Borys, 2013). However, these models are
problematic as they paint a simplistic approach to accident causation.
In the 1990s, Reason (1990) proposed the Swiss-cheese model of accident
causation, which is influential in shifting the view on occupational safety. Reason
(1990) argued that, in a complex system, hazards are prevented by a series of barriers.
However, each barrier has its own unintended weakness or “holes” (like a stack of
Swiss cheese). According to this model, accidents occur due to the failure of
recognising these weaknesses and failure to put up defences to stop hazards and errors
from passing through. While the Swiss-cheese model has its critics, it was influential
in changing the perspective of humans as the main cause of accidents to recognising
the role of systems and the work environment (as well as its interaction with human
behaviour) in accident causation and prevention (Toft et al., 2012).
1.3.2 Newer Models of Safety Management AKA Safety-II
Since then, the study of work environment, organisational culture and safety
management system have dominated the literature (Pillay, Borys, Else, & Tuck, 2010).
10 Chapter 1: Introduction
Instead of focusing on why things go wrong, safety researchers are starting to look at
how things go right. Recently, most OHS research has begun investigating how
organisations still manage to be safe and productive in the face of economic challenges
and ongoing disruptions to production. The High Reliability Organisations (HRO)
theory provides a comprehensive description on how high risk organisations maintain
safety for long periods even when operating in complex and hazardous environments
(Glendon, 2011; Lekka, 2011). Developed by researchers from the University of
California, the HRO theory maintains a positive view on the nature of accidents in
complex systems by arguing that organisations can become more reliable by creating
a ‘just safety culture’ that focuses on identifying system failures rather than blaming
the individuals. Within this perspective, errors could still occur, but can be prevented
through a combination of organisational design, culture, management and human
decision making.
Organisations that operate within the HRO framework are constantly pre-
occupied with failure so that they can anticipate areas of potential failure and cope
effectively when errors do occur (Glendon, 2011). This feature of HRO is often
described as “collective mindfulness”. Other characteristics of HRO include a strong
learning orientation, where workers are continuously trained to recognise and manage
errors and willingness to learn from mistakes (Glendon, 2011). In Weick and Roberts’s
(1993) observational study, they found that operators in aircraft carriers tackle risk and
eliminate errors by relying on their past training and comprehension of the situation.
There was also an emphasis on checks and procedures to ensure that workers could
correct errors before they escalate into crisis (Glendon, 2011).
Resilience engineering, on the other hand, was coined by Hollnagel, Woods,
and Leveson (2007) to describe a safety management approach where organisations
are able to operate under pressure while being productive and still achieving high-
levels of safety. Resilience engineering seeks to enhance the ability of organisations
by creating proactive risk models at all levels of management, promote processes that
are robust and flexible and direct resources proactively despite disruptions to
production and economic pressures (Dekker, Hollnagel, Woods, & Cook, 2008). The
HRO theory shares similar concepts and principles with resilience engineering, where
resilient organisations have the capacity to bounce back after experiencing safety
challenges and mishaps.
Chapter 1: Introduction 11
For an organisation to be safe, reliable and resilient, management should
discourage a blind following of rules and instead foster proactive safety behaviours
and safety awareness among their workers (Hale & Borys, 2013). Workers are
encouraged to recognise critical situations and have the ability to identify a safe action
beyond safety regulations (Dekker et al., 2008). Various OHS researchers have argued
that the framework of HRO and resilience engineering should be applied in other
transportation modes, such as vehicle fleets, when managing risks (Glendon, 2011;
Lofquist, 2017; Naveh & Marcus, 2002). For instance, Naveh and Marcus (2002)
argued that a high percentage of traffic crashes can be attributed to drivers’ error and
lack of attention. In nuclear power plants and commercial aviation, the operators’
‘errors’ are thoroughly scrutinised and analysed to determine how disasters can be
prevented. This information is then fed back to operators and system designers to
optimise the safety system networks. Similar systems should be in place within the
work driving contexts, where both the work drivers and their supervisors need to be
more aware of road hazards and what decisions to take to avoid these risks.
Therefore, these frameworks were utilised as the ‘conceptual lens’ that guided
the progression of this research4. Table 1.1 shows the differences between the
traditional models of safety compared to Safety-II models. As shown in Table 1.1, the
current program of research defined safety as “many things as possible go right” and
safety is managed by constant anticipation of possible errors and issues. Rather than a
liability, workers are also considered as a resource, who are “necessary for system
flexibility and resilience” (Hollnagel et al, 2013, p. 26). From these Safety-II concepts,
the current research program proposed proactive safety behaviours as a metric of
leading safety indicators within the work driving context.
Table 1.1 Traditional Models of Safety versus HRO and Resilience Engineering. This table was adapted from Hollnagel et al. (2013, p. 26).
Traditional Models of Safety aka
Safety-I
HRO and Resilience Engineering aka
Safety-II
Definition of Safety That as few things as possible go wrong.
That as many things as possible go right.
4 It is important to acknowledge that while the focus of the current program of research was on the behaviours of the work drivers (and Resilience Engineering and HRO tend to focus on the wider system), the program also considered the other factors within the work environment (leadership and safety climate) that could impact on proactive safety behaviours.
12 Chapter 1: Introduction
Safety management principles
Reactive, respond when something happens or is categorised as an unacceptable risk.
Proactive, continuously trying to anticipate developments and events.
View of human factor in safety management
Humans are predominantly seen as a liability or hazard.
Humans are seen as a resource necessary for system flexibility and resilience.
Accident investigation
Accidents are caused by failures and malfunctions. The purpose of an investigation is to identify the causes.
Things basically happen in the same way, regardless of the outcome. The purpose of an investigation is to understand how things usually go right as a basis for explaining how things occasionally go wrong.
Risk Assessment
Accidents are caused by failures and malfunctions. The purpose of an investigation is to identify causes and contributory factors.
To understand the conditions where performance variability can become difficult or impossible to monitor and control.
1.4 A PROACTIVE MEASURE OF SAFETY PERFORMANCE WITHIN THE WORK DRIVING CONTEXT
Research and practice within work driving safety, however, is lagging behind
other work hazard risk management (Wishart, Bevan, & Somoray, 2019)5. As
mentioned previously, there is currently a strong emphasis on managing work driving
after an incident has occurred or only focusing on meeting the minimum requirements
for safety. Within the work driving context, safety performance is still viewed using
traditional models, with greater emphasis on frequency and severity of crashes and
traffic violations (Wishart et al., 2019). These measures are ineffective indicators of
safety performance because accidents and injuries only reflect occurrences of failure.
In addition, there are difficulties with assessing on-road behaviours,
organisational crashes and traffic offences. For instance, research on driving behaviour
typically utilise self-report measures of crash involvement, which are susceptible to
biases (e.g., comprehension, memory selection; Arthur, Bell, Edwards, Day, Tubre &
Tubre, 2005). It could be argued that work drivers are even more likely to under report
crashes and traffic violations during working hours due to fear of negative
repercussions from their organisations. Archival records of crash involvement can be
5 This book chapter is not part of the current program of research but was written during my work as a research assistant for Darren Wishart (external supervisor).
Chapter 1: Introduction 13
difficult to obtain, may breach anonymity and can be resource intensive (Arthur et al.,
2005). Some organisations may also be unwilling to share crash data to researchers.
These events are also relatively infrequent and, most times, the information gathered
from these events is retrospective and sensitive (Newnam et al., 2014). Therefore, there
should be a focus beyond crashes and traffic violations as measures of safety
performance within the work driving field.
Yet, researchers and practitioners within the general OHS domain are already
placing emphasis on concepts such as proactive safety behaviour to progress beyond
these traditional models of safety and to further improve safety at work. Instead of
focusing on lagging indicators of safety, OHS researchers are using proactive safety
behaviours as a measure of safety performance and as a leading safety indicator in high
risk occupations (Curcuruto & Griffin, 2017). Proactive safety behaviours are usually
described in contrast with safety compliance. Safety compliance refers to the
compulsory behaviours that individuals must perform in order to meet the minimum
requirements of safety in the workplace (e.g., wearing protective clothing and adhering
to safety procedures).
In contrast, proactive safety behaviour refers to behaviours that go beyond these
minimal safety requirements. These behaviours may not directly contribute to the
worker’s personal safety, but instead assist in developing an environment that supports
safety (Griffin & Neal, 2000). A way to have a proactive role in safety is to engage in
proactive safety behaviours, such as voicing concerns when safety issues arise, giving
suggestions during meetings, correcting unsafe procedures and reporting unsafe and
risky situations to management. These actions are also usually voluntary in nature
(Griffin & Neal, 2000).
It is important to acknowledge that while organisations have the legal duty to
provide a safe and healthy work environment for their employees, workers must also
actively contribute to the management of their workplace’s health and safety issues
(European Agency for Safety and Health at Work, 2012; Safe Work Australia, 2016b).
Various legislations on occupational and health safety in industrialised nations such as
Europe, United States and Australia require employers to consult and involve their
workers when addressing issues relating to the workplace’s health and safety. In turn,
workers are required to proactively participate and cooperate with their employers in
the management of their own and their co-workers’ safety while at work (e.g., Bureau
14 Chapter 1: Introduction
of Labor Statistics, 2014; European Agency for Safety and Health at Work, 2012;
Queensland Government, 2011). Within OHS legislations and governing bodies (such
as European Agency for Safety and Health at Work and Safe Work Australia), worker
participation often takes the form of safety consultations and formation of safety
committee and unions to represent workers regarding safety matters (Arrigo & Casale,
2010).
However, occupational health and safety researchers argued that workers could
proactively participate in resolving safety issues and improving their workplace health
and safety without such formal requirements (Curcuruto & Griffin, 2017).
Furthermore, these legislations usually require worker representatives to carry out
these consultations (European Agency for Safety and Health at Work, 2012). These
consultations and other representative tasks require additional hours to complete
besides their regular job duties. Therefore, support is usually needed, not only from
their employers, but from the workers they represent (European Agency for Safety and
Health at Work, 2012).
Curcuruto and Griffin (2017) argued that workers need to have a proactive role
in safety promotion, and they must work together with their co-workers and managers
in order to make meaningful improvements in workplace safety. Proactive safety
behaviours have been associated with reduced workplace accidents, injuries, work
accidents, lost work days and better reporting attitudes (e.g., Griffin & Neal, 2000;
Neal & Griffin, 2006). Research has also found that engaging in proactive safety
behaviour is more effective at improving safety outcomes in the longer-term
(measured by reduced accidents and workplace injuries) compared to merely
complying with safety rules and regulations (e.g., Christian et al., 2009; Neal &
Griffin, 2006; Neal et al., 2000). In Christian et al.’s (2009) meta-analysis on work
safety performance, they found that participating in safety activities has a slightly
stronger correlation and tighter confident intervals with reduced accidents and injuries
(Mp = -.15; 95% CI [-.18, -.13])6 compared to safety compliance (Mp = -.14; 95% CI
[-.20, -.08]). Furthermore, proactive safety behaviour has also been associated with
non-safety related outcomes such as better customer service and improved employees’
health (e.g., reduced blood pressure; Haslam, O’Hara, Kazi, Twumasi, & Haslam,
6 Mp = mean corrected pooled correlation
Chapter 1: Introduction 15
2016). These studies suggest that, for organisations to thrive and be successful in
achieving the desired high levels workplace safety, workers and management have to
work proactively towards risk reduction, transcending mere compliance with safety
standards and procedures (Curcuruto & Griffin, 2017).
Following this view, there is some merit in investigating proactive safety
behaviour as a measure of safety performance when employees drive for work. This
research aim is driven by the premise that, to improve safety while driving for work,
employees and management need to be proactive in addressing safety issues as
opposed to just simply following rules and regulations and reacting to crashes,
violations and injuries. Proactive safety behaviour as a measure of safety performance
in the work driving context could provide an alternative or complementary paradigm
to current risk management strategies. If work has less routine and predictability, such
as driving for work (due to other drivers on the road, road conditions, weather, etc.),
proactive safety behaviours may be required to guide safe practices where compliance
to rules and procedures may fall short (Zohar, 2008).
1.5 CHAPTER SUMMARY AND KEY LEARNINGS
This chapter summarised the literature on the issues of work driving and the
current practices and research on work driving safety management. Injuries and
fatalities resulting from work driving incidents is a significant public health issue. Due
to the costs of human lives and economic loss. However, current research on work
driving safety mostly focus on lagging indicators. Furthermore, management of risks
is often reactive, only conducting safety checks once an incident has already occurred.
While government regulations in Australia and other industrialised countries require
organisations to ensure their employees’ safety while driving for work, vehicle-related
incidents are still the cause of most work-related fatalities and injuries. This chapter
also highlighted the need for an alternative framework on work driving safety
management, with a particular focus on using HRO theory and Resilience Engineering
as theoretical lens to guide how work driving safety could be managed. The chapter
concluded with an appeal for a proactive measure of safety performance within the
work driving context, taking insights from research on proactive safety behaviours
from the OHS field.
16 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
2.1 INTRODUCTORY STATEMENT
A broad range of behaviours, concepts and terminologies is associated with the
construct of proactive safety behaviours. Thus, a comprehensive investigation of
proactive safety behaviours is required to gain a full understanding of this construct
before applying it to the work driving context. This chapter assists in placing the
foundation for the current program of research and critical to the background
information necessary for the subsequent chapters.
It is important to note that this taxonomy of behaviours has not been fully
examined within the work driving context and, therefore, most of the literature
reviewed within this chapter is derived from the areas of OHS and organisational
psychology. In particular, concepts of contextual performance, organisational
citizenship behaviours and work proactivity were reviewed in this chapter. Similar
concepts of these behaviours within the traffic safety research are also discussed.
2.2 BACKGROUND AND ORIGINS OF PROACTIVE SAFETY BEHAVIOUR
According to Griffin and Neal (2000), safety performance has two behavioural
components: safety compliance and safety participation. Safety compliance refers to
the compulsory behaviours that individuals must perform in order to meet the
minimum requirements of safety in the workplace (e.g., wearing protective clothing
and adhering to safety procedures). On the other hand, safety participation refers to
behaviours that go beyond these minimal safety requirements. These behaviours may
not directly contribute to the worker’s personal safety, but instead assist in developing
an environment that supports safety (Griffin & Neal, 2000). Safety participation is
voluntary in nature and usually involves helping co-workers, promoting safety
programs within the workplace, demonstrating initiative, and putting effort into
improving safety in the workplace (Griffin & Neal, 2000).
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 17
Griffin and Neal’s model was an important study within the OHS field as it
provided a theoretical framework on safety performance, and identified its potential
organisational and individual antecedents (e.g., safety climate) and outcomes (e.g.,
injuries, accidents). Their seminal work also extended the dialogue on safety
performance as a multi-dimensional construct (Burke, Sarpy, Tesluk, & Smith-Crowe,
2002). Burke et al. (2002) argued that, prior to Griffin and Neal’s model, the literature
on OHS was mostly focused on safety compliance. In the past, interventions were
focused on increasing compliance with safety regulations and there was a common
assumption that compliance problems were the source of poor safety attitudes (Neal &
Griffin, 2002). Griffin and Neal’s (2000) research encouraged researchers and
practitioners to consider behaviours that go beyond safety compliance, and identify the
antecedents and determinants of such behaviours.
It is important to note, however, that while Griffin and Neal (2000)
conceptualised their model of safety performance, other researchers had already
examined safety behaviours that go beyond the minimal safety requirements. One of
the first studies that formally recorded such behaviours was conducted by Andriessen
(1978). While studying the safety behaviours of Dutch construction workers,
Andriessen (1978) noticed that, in addition to complying with safety rules and
regulations, construction workers also engaged in voluntary behaviours that improved
the safety of their work environment (e.g., voicing safety concerns to their
supervisors). Andriessen (1978) called these behaviours, ‘safety initiatives’.
Other notable early studies include Simard and Marchand’s (1995) investigation
of safety initiative behaviours within the manufacturing industry, and Cree and
Kelloway’s (1997) examination of willingness to participate in safety programs using
a sample of production employees. In both studies, safety initiatives and willingness
to participate in safety programs referred to workers’ readiness to engage in behaviours
that aimed to improve the safety of their working environment beyond the minimal
requirements of their jobs. Similarly, Roberts and Geller (2001) also proposed the
actively caring hypothesis, which refers to the “ultimate goal in occupational safety -
that employees care enough about the safety of their co-workers to act accordingly”
(p. 97). Workers who exhibit active caring behaviours are constantly looking for
organisational hazards, and when faced with unsafe behaviours and practices, these
workers intervene with corrective procedures (Roberts & Geller, 2001).
18 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
However, Griffin and Neal (2000) were the first to conduct a comprehensive
investigation of safety performance and to provide a model that differentiated between
compliant and participative safety behaviours, as well as to conduct an investigation
regarding their antecedents and possible safety outcomes. The current chapter utilises
Griffin and Neal’s (2000) research on safety participation as a starting point to
investigate the construct of proactive safety behaviour. Figure 2.1 provides the
overview of research on proactive safety behaviours, its related constructs and its
origins. To fully gain a comprehensive understanding of proactive safety behaviours
and its related constructs, it is imperative to discuss their origins, which are usually
derived from research in organisational psychology. These constructs are further
discussed in the following sections.
2.2.1 Contextual Performance
Safety participation as a component of safety performance is based on Borman
and Motowidlo’s (1993) theory of work performance. In this original theory, Borman
and Motowidlo (1993) proposed two major components of performance: task
performance and contextual performance. Task performance describes the extent to
which a worker effectively contributes to the organisation’s operations and processes
by directly providing the required services and products (e.g., firefighters performing
rescue operations). On the other hand, contextual performance describes the extent to
which a worker contributes to the organisation’s success by influencing the broader
psychological and social environment (i.e., context) in which the core tasks must
operate (e.g., firefighters picking up a shift when their co-workers are unwell; Borman
& Motowidlo, 1997). In this theory, contextual performance involves activities
Figure 2.1 Overview of the historical origins of proactive safety research
Organisational Citizenship Behaviour
(Organ, 1988)
Contextual Performance (Borman and Motowidlo,
1997)
Proactive Behaviours (Bateman and Crant, 1993)
Safety Citizenship Behaviours
(Hofmann et al., 2003)
Safety Participation (Griffin and Neal,
2000)
Proactive Safety Behaviours
(Curcuruto et al., 2015)
Prosocial Safety Behaviours
(Curcuruto et al., 2015)
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 19
directed at maintaining a work environment that allows the core task activities to be
effective. The taxonomy of contextual performance includes five categories of
behaviours (Borman & Motowidlo, 1997, p. 102):
1) persisting with extra effort and enthusiasm to successfully complete task
activities (e.g., perseverance and conscientiousness);
2) volunteering to carry out activities that are not formally part of their job
(e.g., suggesting organisational improvements);
3) helping and cooperating with others (e.g., assisting or helping co-workers);
4) following rules and procedures (e.g, meeting deadlines); and
5) endorsing, supporting, and defending organisational objectives (e.g.,
organisational loyalty).
Borman and Motowidlo (1997) argued that contextual performance is, in some
ways, more important than task performance especially when increased competition
and economic challenges (e.g., downsizing) demand companies to perform better.
Team members’ adaptability and willingness to exhibit extra effort contribute to the
success of the organisation in the longer term.
In a similar manner, safety participation describes behaviours that may not
necessarily directly contribute to workplace safety, but that may help develop an
environment or ‘context’ that supports safety (Griffin & Neal, 2000). Using the
conceptualisation of contextual performance, Neal and Griffin (2000) argued that
behaviours such as attending safety meetings and engaging in voluntary safety
activities promote a work context that is supportive of safety.
2.2.2 Organisational Citizenship Behaviour
Borman and Motowidlo’s (1993) operationalisation of contextual performance
is derived from the organisational citizenship behaviour research and, by extension,
safety participation shares several theoretical elements with organisational citizenship
behaviour as well. Organisational citizenship behaviour is defined as, “behaviours that
are discretionary, not directly or explicitly recognised by the formal reward system,
and that in the aggregate promote the effective functioning of the organisation”
(Organ, 1988, p. 4). Examples of organisational citizenship behaviours include helping
a co-worker finish a task and participating in various professional development
programs to benefit the organisation. Research shows that, although these behaviours
are not formally defined in one’s role, they are crucial to the survival, performance and
20 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
effectiveness of the organisation (Organ, Podsakoff, & MacKenzie, 2006). Employees
exhibiting high levels of organisational citizenship behaviours are often referred to as
‘good corporate citizens’ or ‘good soldiers’, in part due to the extra productive
activities undertaken for the advancement of the organisation and for the extra effort
beyond what is normally acknowledged, expected or rewarded (Organ, 1988).
Similar to Borman and Motowidlo’s (1993) taxonomy of behaviours that relates
to contextual performance, Organ’s (1988) original research on organisational
citizenship behaviour also had five dimensions: altruism, conscientiousness,
sportsmanship, courtesy and civic virtue behaviour. More recent research, however,
has indicated seven dimensions, which expanded and revised the taxonomy of
behaviours related to organisational citizenship behaviours to include a more
comprehensive taxonomy of behaviours (Organ et al., 2006), and which are: helping,
individual initiative, organisational loyalty, self-development and organisational
compliance. Sportsmanship and civic virtues were the only two dimensions that
remained from the original research.
Using the dimensions studied within the organisational citizenship research,
Hofmann, Morgeson, and Gerras (2003) coined the term ‘safety citizenship
behaviours’ to describe the extra-role behaviours that workers carry out to improve the
safety of their work environment. Hofmann et al.’s (2003) research on safety
citizenship behaviours expanded the construct of safety participation. Safety
participation is unidimensional in nature, and is usually measured with these three
behaviours: “I promote the safety program within the organization”, “I put in extra
effort to improve the safety of the workplace” and “I voluntarily carry out tasks or
activities that help to improve workplace safety” (Neal and Griffin, 2006, p. 953). On
the other hand, Hofmann et al.’s (2003) research on safety citizenship behaviours
provided a higher-order construct consisting of six dimensions of proactive safety
behaviours. These six dimensions are derived from the organisational citizenship
behaviour research, and include (Hofmann et al., 2003, p. 178):
Helping – behaviours that help out the organisation and its members to ensure
that everyone is working safely
Safety Civic Virtue (Keeping Informed) – behaviours that are related to
maintaining an up-to-date knowledge on the safety issues in the organisation.
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 21
Initiating Safety-Related Change (Improving Safety) – behaviours that try to
improve the overall safety of the organisation that are self-initiated
Voice – voicing out safety-related recommendations and opinions on safety
matters even if others may disagree
Stewardship – taking action to prevent safety violations and protect the well-
being of their co-workers
Whistleblowing – similar to the voice dimension but behaviours that are
specific to reporting and monitoring of other members’ unsafe behaviours and
potential safety violations
Workers who exhibit safety citizenship behaviours tend to be more compliant
with safety management policies and are involved in fewer work related safety
incidents (Hofmann et al., 2003). Hofmann et al. (2003) suggested that safety
citizenship behaviours are associated with the promotion and improvement of safety
within the workplace. Such behaviours can enhance individual commitment and
personal responsibility, which may translate into improvements in tangible risk
management and consequently improved safety outcomes (Wishart et al., 2019).
2.2.3 Proactivity
Another source of research when investigating proactive safety behaviours is the
literature on proactivity (e.g., Crant, 2000; Parker, Williams, & Turner, 2006).
Research on work proactivity began with the construct of proactive personality, where
Bateman and Crant (1993) argued that some individuals have the disposition to initiate
change in their immediate work environment, while some individuals have no self-
initiative and are merely reacting to their work situations. However, recent studies in
the work proactivity literature place emphasis on the behaviour aspect of proactivity
instead of the dispositional characteristics (e.g., Crant, 2000; Parker et al., 2006). By
conceptualising work proactivity as a behaviour, proactivity is seen as something that
leaders can facilitate and shape within the organisation, rather than seeing it as a fixed
individual attribute that someone may or may not have (Crant, 2000). This way, leaders
are encouraged to promote and shape proactive behaviours among the workforce.
Proactive behaviours in the workplace are conceptualised as self-stating, change-
oriented and future-focused. These elements suggest that proactive behaviours are self-
initiated rather than enforced (Parker et al., 2006). Employees who exhibit high levels
22 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
of proactive behaviours enact and drive change within the organisation rather than
adapting to their situation (Parker & Collins, 2010). Being future-focused suggests that
proactive behaviours involves anticipating and thinking ahead, rather than reacting to
the current situation (Grant & Ashford, 2008; Parker & Collins, 2010).
Similar to Borman and Motowidlo’s (1997) research on contextual performance,
research on proactivity took concepts from the organisational citizenship behaviour
literature. However, while there are similarities between organisational citizenship
behaviour and proactive behaviours, researchers have argued for differences between
the two constructs. Parker, Bindl, and Strauss (2010) contested that proactivity is
different from organisational citizenship behaviour because proactivity can be
conceptualised as a stable personality trait, a behaviour or a process, whereas
organisational citizenship behaviours only describes extra-role behaviours in the
workplace. For instance, an employee may carry out an in-role behaviour
‘proactively’. Additionally, there are some behaviours under the organisational
citizenship behaviour construct which can be seen as passive or compliant (e.g.,
following rules and being loyal), instead of being ‘proactive’ (Belschak & Hartog,
2010). Therefore, Parker et al. (2010) argued that the proactivity literature investigates
the active, taking-charge and change-oriented aspect of citizenship behaviours.
Recently, research by Curcuruto and colleagues have incorporated the
proactivity literature in their investigation of proactive safety behaviours (Curcuruto,
Conchie, Mariani, & Violante, 2015; Curcuruto, Mearns, & Mariani, 2016). Curcuruto
et al. (2015) suggested that these previous constructs of proactive safety behaviour,
safety participation and safety citizenship could be distinguished into two categories:
proactive and prosocial behaviours. Curcuruto et al. (2015) argued that proactive
safety behaviours should be action-oriented, change-oriented and future-focused, as
opposed to passively reacting to the events that have already occurred and simply
complying with rules and regulations. Prosocial safety behaviours, on the other hand,
are affiliative in nature, and mostly reflect the helping and stewardship dimensions of
organisational citizenship behaviours (Curcuruto et al., 2015). With this
conceptualisation, Curcuruto et al. (2015) argued that the dimensions of whistle-
blowing, safety voice, safety initiative and keeping-informed identified within the
safety citizenship research are proactive safety behaviours, while helping and
stewardship dimensions are prosocial safety behaviours.
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 23
However, it could be argued that helping co-workers be safe and protecting
colleagues from hazards still have aspects of proactivity given that these behaviours
are usually discretionary and not expected from one’s roles. Furthermore, protecting
co-workers from hazards require an initiative to act. Therefore, the current program of
research argues that prosocial behaviours (e.g., stewardship, helping) are still change-
oriented and action-focused behaviours that seek out to bring positive change in safety
practices within organisations through the process of fostering co-operation and social
relationships with co-workers. Consequently, these behaviours are still regarded as an
aspect of safety proactivity.
2.2.4 Bringing it all together
Due to the different concepts that inform the research on proactive safety
behaviours, various terminologies and definitions of proactive safety behaviours have
been used interchangeably within the literature (see Table 2.1).
Table 2.1 Different terminologies associated with the construct of Proactive Safety Behaviours adapted and extended from Curcuruto and Griffin (2017, pp 109-110).
Terminology / Construct Definition Behaviours measured Safety Initiative (Andressien, 1997; Simard & Marchard, 1995)
Employees’ attempts to create a safer work environment.
Employees take initiatives in order to work more safely Make suggestions in order to improve safety at work environment Put pressure on the supervisor to improve safety at work
Actively caring about safety (Geller, Johnson, Redmon, & Mawhinney, 2001; Geller, Roberts, & Gilmore, 1996)
Employees acting to benefit the safety of other employees.
Observing and recording the safe and unsafe behaviours of coworkers, and then provide constructive behavioral feedback
Willingness to participate in health and management programs (Cree & Kelloway, 1997)
By participating in health and safety programs, employees have the opportunity to have a "voice" in the management of workplace health and safety.
Participation in various programs (e.g., attending safety meetings, attending safety training).
Safety Participation (Griffin & Neal, 2000)
Safety behaviours that may not necessarily directly contribute to workplace safety, but help develop an environment that supports safety.
Promoting safety program Extra effort to improve safety Voluntarily carry out tasks to improve safety
Safety Citizenship (Hofmann et al., 2003)
Safety behaviours that are not formally rewarded by the organisation, but plays a strong role in accident prevention due to its facilitation in improving the safety and learning within the workplace.
Whistle-blowing Safety voice Helping Safety initiative
24 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
Proactive safety behaviours (Curcuruto et al., 2015)
Safety behaviours that are challenging in nature and seek to bring out positive change in the safety practices within the organisation.
Whistle-blowing Safety voice Safety initiative Keeping informed
Prosocial safety behaviours (Curcuruto et al., 2015)
Safety behaviours that are affiliative in nature. This behaviour generally manifest itself as helping co-workers and looking out for their welfare and safety. Often seen as a way to foster good relationships.
Helping Stewardship
Using the origins of contextual performance, organisational citizenship
behaviour and proactivity research, the overarching conceptualisation of proactive
safety behaviours that is utilised in the current program of research has the following
distinct, yet related, components:
1) behaviours that improve the context of the work environment to be more
supportive of safety – these behaviours may not directly contribute to
workplace safety, but may facilitate an environment that supports safety
(i.e., behaviours that create a positive environment for safety);
2) behaviours that aim to improve workplace safety that cannot be forced (i.e.,
self-starting); and
3) behaviours that are change-oriented and which aim to improve the current
workplace safety practices.
Taking the current knowledge on proactive safety behaviours, a more specific
definition of proactive safety behaviours within the work driving safety context could
be defined as: behaviours that work drivers perform that create a work environment
that promotes work driving safety. These behaviours must be 1) self-starting (in other
words, cannot be forced), and/or 2) change-oriented (with an aim to improve the
current work driving safety practices). Coming from the perspectives of safety
citizenship and safety proactivity research, arguably this construct is multi-
dimensional, which may include: voicing out, intervening, problem prevention and
changing the organisation's policies and procedures.
2.3 SIMILAR CONCEPTS IN TRAFFIC SAFETY RESEARCH
While the concept of proactive safety behaviours had not been studied in the
work driving context, similar constructs have been investigated in the general road
safety research. For instance, prosocial driving behaviours have been studied in the
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 25
literature. Prosocial driving has been referred to as, “a pattern of safe driving
behaviours that potentially protect the well-being of passengers, other drivers, and
pedestrians, and that promotes effective cooperation with others in the driving
environment” (Harris et al., 2014, p. 2). Ross and Antonowicz (2004) argued that most
people characterised driving as an individual activity, whereas in reality, driving
occurs in a ‘social vacuum’. The social feedback drivers receive from other road users
can, implicitly and explicitly, influence the driver’s decision-making and behaviour on
the road. Being a safe and courteous driver requires adequately developed social
cognitive skills and positive values that show concern to the safety of oneself and
others (Ross & Antonowicz, 2004).
However, prosocial driving behaviours describe general driving behaviours on
the road (e.g., “decreasing speed to accommodate poor road conditions”, p. 3) rather
than specific behaviours within the work context. Furthermore, prosocial driving
behaviours often reflect compliance with traffic laws (e.g., “obey traffic signs” and
“come to a complete stop at a stop sign”; Harris et al., 2014, p. 3) instead of personal
initiatives and change-oriented behaviours.
The concept of traffic safety citizenship was also developed by Ward and
colleagues (Otto, Finley, & Ward, 2016; Finley, Riggs, Otto, & Ward, 2015). Based
on the concept of safety citizenship behaviours, traffic safety citizenship focused on
the prosocial aspects of traffic behaviours across different levels of society (e.g.,
individual family, workplace and community). Examples of such behaviours include:
asking others not to speed, intervening to prevent others from drink driving and
advocating for stronger traffic laws. This concept is based on the premise that, often,
it is only a small number of public road users who engage in risky behaviours.
Therefore, it is important to foster more active engagement from the larger majority of
safe road users to influence the behaviours of the risky drivers.
In a survey of 1,954 adult drivers in the United States, Otto et al. (2016) found
that around half of the respondents indicated being in a situation in the past 12 months
when a passenger was not wearing a seat belt or a driver was using a mobile phone
while driving. Participants were more likely to intervene if the person who conducted
the unsafe behaviour was part of their close social circle (e.g., family or friends)
compared to more socially distant circle (e.g., acquaintances or strangers).
Furthermore, Otto et al. (2016) found that the participants were most likely to report
26 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
intervening if they perceived that other people would also intervene. When group
differences were assessed between individuals who reported higher frequency of
intervening compared to those who rarely or never intervened, participants who
intervened more were more likely to have a higher sense of comfort and confidence in
performing such behaviours.
A similar study on these intervening behaviours were demonstrated in a study
by Buckley, Sheehan and Chapman (2009) on a school-based behaviour change
program that targets friendship groups for risk driving prevention. In their study, they
examined the idea of ‘mateship’ in encouraging adolescents to intervene when their
friends engage (or are thinking of engaging) in risky driving behaviours such as drink
driving and speeding (Buckley et al., 2009). Another school-based road safety program
by Kennedy, Cullen, Firman, Fleiter and Lewis (2018) examined how the program
could influence young people’s intention to speak up when a driver engages in a risky
behaviour. These interventions include voicing concerns, taking away their friend’s
keys or offering a lift to prevent their friends from engaging in risky driving
behaviours.
This concept of engaging bystanders to reduce risky driving behaviours were
also examined within the workplace context. Otto, Ward, Swinford and Linkenbach
(2014) studied employees’ intention to prevent their co-workers from engaging in
risky driving behaviours (e.g., not wearing a seatbelt, texting while driving, using a
mobile phone while driving, aggressive driving or speeding). Their findings revealed
that, individuals with higher intentions to intervene were associated with stronger
perceived norms that intervening behaviours were supported or approved of within the
workplace.
These intervening behaviours tap into the concepts of safety stewardship
dimension of safety citizenship behaviours. While these studies present a starting point
for the current program of research, there may be other proactive safety behaviours
that employees could engage in while driving for work. More specifically, these
studies (e.g., Buckley, Sheehan, & Chapman, 2009; Kennedy et al., 2018; Otto et al.,
2016; Otto et al., 2014; Ward, 2015) only examined the aspect of intervening when
someone is engaging in a risky driving behaviours. Other aspects of proactive safety
behaviours (e.g., safety voice, safety civic virtue) were not yet investigated within the
context of work-related driving. Therefore, a significant gap exists within the research
Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions 27
of proactive safety behaviours and in terms of understanding its nature and
multidimensionality within the context of work driving safety. Due to the specific
context of work driving, there may be other factors that previous research has not
examined, that could influence one’s engagement with proactive safety behaviours.
The current program of research sought to address this gap.
2.4 CHAPTER SUMMARY AND KEY LEARNINGS
This chapter has critically reviewed and discussed the origins and definitions of
proactive safety behaviours using studies from organisational psychology and general
occupational safety research (Figure 2.1). The chapter also examined similar
constructs within traffic safety research. The review informed the definition of
proactive safety behaviours used by the current research program. This definition
comprises three key components: behaviours that may not directly contribute to
workplace safety but they facilitate an environment that supports safety (in other
words, behaviours that create a positive environment for safety); behaviours that aim
to improve workplace safety that cannot be forced (self-starting); and, behaviours that
are change-oriented which aim to improve the current workplace safety practices
(change-oriented behaviours). The literature reviewed in this chapter helped to identify
the gaps in the literature and to inform the background research that was necessary to
develop the research aims, objectives and questions of the current program of research.
Figure 2.2 Fields of research that helped inform the proactive safety behaviour construct within the
work driving context and the foundation of the current program of research
Proactive Safety Behaviours within the work driving context
Occupational Health and Safety research
Organisational psychology research
Road traffic safety research
28 Chapter 2: Proactive Safety Behaviours – A Review on Origins and Definitions
Chapter 3: Overview of Research Program 29
Chapter 3: Overview of Research Program
3.1 INTRODUCTORY STATEMENT
The work driving context is complex and dynamic, involving different entities
and decision makers (Stuckey et al., 2010). Not only do work drivers have to safely
operate within the road environment (which is typically the domain of road
authorities), they also have to perform within the occupational context (Stuckey et al.,
2010). However, work driving safety management typically focuses on on-road
context, with little to no regard on the influence that organisations could do to manage
risks related to work driving. Driving for work also has unusual characteristics that
may affect safety management such as irregular work driving times, unrealistic work
demands, driving seen as secondary or not part of one’s job and may involve remote
work without direct supervision (Newnam, Greenslade, Newton, & Watson, 2011).
Within the general OHS field, a substantial amount of work has been conducted
on the development of safety management systems that have yet to be applied within
the work driving context (Mooren, 2016). Some risk management models
acknowledge the dynamic and multi-dimensional nature of work and increasingly
recognises the complex processes involved in managing risks. Some approaches
require organisations to continually anticipate risks and be responsive and proactive in
eliminating risks. The nature of road transport tasks involves exposure to a relatively
uncontrolled work environment (e.g., public roads). It is therefore important for work
drivers and managers to continually anticipate risks and adapt the process to avoid
injury crashes (Newnam, Sheppard, et al., 2014). Currently, there is little research on
this proactive approach to safety management within the work driving context.
However, current studies in other occupational settings could provide some foundation
research in the necessary management and organisational characteristics that might
influence safety performance. Newnam et al. (2014) aptly described the need for
proactive safety behaviours in the work driving setting with this statement:
“To achieve reductions in work-related road traffic injury, it will be necessary
to extend the focus beyond the individual’s compliance with safety procedures, as safe
30 Chapter 3: Overview of Research Program
work environments depend on individuals anticipating threats to safety, showing
concern for the safety of others (team supervisor) and contributing to safety” (p. 4)
The previous two chapters discussed the background and rationale of the
program of research, focusing on the issues of work driving and the current
management and research on work driving risks. The previous chapters also identified
the gaps in research and presented the current literature on proactive safety behaviours.
The current chapter is an extension of the previous chapters and provides an overview
of the research program. The current chapter presents the research aim and objectives
as well as the demarcation of scope that describes the context and constraints in which
the program of research were conducted. Finally, the structure of the thesis document
is also presented.
3.2 RESEARCH QUESTIONS, AIM AND OBJECTIVES
While proactive safety behaviours have been studied in various work settings,
proactive safety behaviours have not been fully examined within the work driving
context. This presents a significant gap in the current work driving literature.
Therefore, the following questions had been developed and formed the foundation of
the current program of research:
RQ1: What do we currently know about the construct of proactive safety
behaviours?
RQ2: What are the proactive safety behaviours that work drivers perform to
ensure and improve safety (and that of their co-workers) while driving for
work?
RQ3: What are the individual and organisational factors that promote and
inhibit proactive safety behaviours in work drivers?
Relating to these questions, this research program has an overarching aim, with
three-related objectives:
Overarching Research Aim: To develop a research model and measure of proactive
safety behaviour that could be utilised within the context of work driving.
Research objective 1: To investigate the current literature in order to better
understand the proactive safety behaviour construct and identify the factors that
influence employees’ engagement in proactive safety behaviours. This
Chapter 3: Overview of Research Program 31
investigation will inform the development of the research model and
measurement.
Research objective 2: To develop an instrument to measure proactive safety
behaviours within the work driving context.
Research objective 3: To investigate the suitability of the proposed model by
conducting a quantitative study in a sample of work drivers.
3.3 DEMARCATION OF SCOPE
Work drivers in this program of research were defined as employees who drive
as a requirement in order to perform important aspects of their jobs. The target
population were required to drive for work at least once a week, including the commute
to and from work7. The target population spans a range of industries including remote
and mobile workers who travel to different locations throughout the day (e.g., utility
workers, teleworkers, community nurses, emergency services and couriers; Huang et
al., 2013; Newnam & Watson, 2011b).
The context of work driving offers a unique perspective on the study of
occupational safety performance. Work drivers could range from having traditional
(e.g., office desk job) to precarious (e.g., field work) employment arrangements. In
addition, their work involves the use of the public road system, thus operating within
both occupational health and safety and road safety policy contexts (Fort et al., 2016).
Where some workers may only have to comply with occupational health and safety
policies specific to their jobs, driving for work also requires compliance with traffic
laws and regulations. Work drivers are also usually on the road alone without
supervision, making it is more difficult to monitor their behaviour compared with
employees within a single physical setting (e.g., factory workers; Huang et al., 2013;
Newnam, Lewis & Watson, 2012). Supervisor absence could also mean increased
reliance on themselves to drive safely for work (Huang et al., 2013; Newnam et al.,
7 Although some researchers regarded commuting to and from work as distinct from work-related travel (Fort, Ndagire, Gadegbeku, Hours, & Charbotel, 2016; Health and Safety Executive, 2014; Salminen, 2000), it is important to acknowledge that commuting to and from work is considered as ‘work-related’ travel within the work health and safety legislation and work insurance claims (especially within Queensland; WorkCover Queensland, 2016). Other researchers have also argued that commuting to and from work should be considered a work-related driving activity (e.g., Newnam & Watson, 2011a, 2011b).
32 Chapter 3: Overview of Research Program
2012). Therefore, there are specific factors within the work driving context that could
influence one’s engagement with proactive safety behaviours.
3.4 THESIS OUTLINE
This thesis has four chapters that document the program of research together
with two introductory chapters, and one general discussion and concluding chapter
(see Figure 3.1 for the thesis outline). Chapter 1 provided the introductory discourse
on the research topic, outlining the background and rationale of the program of
research. Chapter 1 specifically discussed the current research on work driving safety,
detailing the issues of work driving, the shortcomings of current work driving safety
management and the need for an alternative framework for managing risks related to
work driving safety. Chapter 1 also presented the theoretical framework that guided
the the current program of research. Chapter 2 discussed the topic of proactive safety
behaviours, its background and origins on organisational psychology, its application
on the OHS field and its possible role in traffic psychology and specifically within
work driving context. The current chapter (Chapter 3) provides an overview of the
research context, questions and aim of the research program. Chapters 4 to 6 document
the three studies that constitute the program of research. Chapter 7 discusses the overall
findings of the program of research and concluding statements.
Chapter 3: Overview of Research Program 33
Figure 3.1 Outline of the program of research and its presentation in this thesis
Research Question 1: What do we currently know about the construct of proactive safety behaviours? Related research objective: To investigate the current literature in order to better understand the proactive safety behaviour construct and identify the factors that influence employees’ engagement in proactive safety behaviours. (RO1) Method: Literature review and meta-analysis
Overarching Research Aim: To develop a new model and measure of proactive safety behaviours within the work driving context.
Chapter 2 – Proactive Safety Behaviours – A Review on Origins and Definitions (Literature review)
Chapter 4 – Meta-analytic Review of Antecedents to Proactive Safety Behaviours (Study 1)
Research Question 2: What are the proactive safety behaviours that work drivers perform to improve safety (and of their co-workers) while driving for work? Related research objective: To develop an instrument to measure proactive safety behaviours within the work driving context. (RO2) Method: Item pool generation with the research team and expert panel for the scale development (Study 2a). Online survey with sample of work drivers to test the developed scale (Study 2b and Study 2c).
Study 2a – Item Generation and Expert Panel
Chapter 5 – Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
Study 2b – Pilot Study
Study 2c – Main Survey
Research Question 3: What are the individual and organisational factors that promote and inhibit proactive safety behaviours in work drivers? Related research objective: To investigate the suitability of the proposed model by conducting a quantitative study in a sample of work drivers. (RO3) Method: Online survey with sample of work drivers.
Chapter 6 – Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
34 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
4.1 INTRODUCTORY STATEMENT
Behaviours that go beyond one’s expected roles “do not exist in a vacuum”
(Gyekye & Salminen, 2005, p. 815). Organisational factors, individual differences,
cognitive mechanisms, and the dynamic relationship between these variables, promote
or inhibit proactive safety behaviours (Curcuruto & Griffin, 2017). Using Curcuruto
and Griffin’s (2017) framework, the current chapter appraises and synthesises studies
that have examined the distal and proximal antecedents of proactive safety behaviours.
Proximal antecedents refer to factors that are directly responsible for the differences
in proactive safety behaviours (Griffin & Neal, 2000). On the other hand, distal
antecedents (which may include variables within the work environment) may also
directly influence proactive safety behaviours, but the effect is usually smaller
compared to proximal antecedents. Distal antecedents may also influence proactive
safety behaviours via the proximal antecedents (Griffin & Neal, 2000). Griffin and
Neal (2000, p. 347) argued that distinguishing distal from proximal antecedents is
important in order to “allow a systematic assessment of conceptually distinct
perceptions that may have different causes and consequences within organisations”. In
other words, it is critical to identify these factors as it will facilitate a better
understanding on how management can encourage and promote these behaviours in
the workplace. This chapter forms the first study of the current program of research
(Study 1) and aims to answer RQ1: “What do we currently know about the construct
of proactive safety behaviours?”
4.1.1 Purpose of the Study
Compared to previous reviews that examined other safety behaviours (Christian
et al., 2009; Nahrgang, Morgeson, & Hofmann, 2011), the current review focused on
the antecedents of proactive safety behaviours and its associated constructs. The meta-
analytic component of the review also extends upon Curcuruto and Griffin’s (2017)
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 35
literature review on safety proactivity. While Curcuruto and Griffin (2017) provided a
comprehensive account of safety proactivity, this current meta-analysis presents an
opportunity to quantify the relationships of the different contextual and proximal
variables that they proposed within the model. In addition, the meta-analytic
calculations allowed the pooling of available quantitative data from individual studies
for a more precise estimate of the effect size of each relationship (Schmidt & Hunter,
2014). The current review also informs the development of a theoretical model of
proactive safety behaviour that would be applied within the work driving context.
Therefore, general discussions of the antecedents in relation to work driving safety are
conducted, particularly if similar constructs had been studied within the work driving
safety field. Studies that were found during the database search that may relate to work
driving safety were also specifically examined as part of the meta-analysis.
4.1.2 Scope of the Study
While previous studies have examined the role of individual differences and
dispositional characteristics on proactive safety behaviours, the current review will not
examine these variables. Within the general safety literature, various studies have
investigated a vast array of personality characteristics that predispose individuals to
errors, accidents and injuries. The search for reliable individual difference variables
that strongly relate to safety performance is characterised by inconsistent and
inconclusive findings (Hogan & Foster, 2013). Several reviews that have examined
the role of personalities and dispositional characteristics often show weak or non-
significant effects on safety behaviours (Beus, Dhanani, & McCord, 2015; Christian
et al., 2009). In addition, this perspective is influenced by traditional models of safety
which are based on the premise that “error-prone” individuals contribute the most
towards workplace accidents and injuries (Hogan & Foster, 2013). Therefore, this
review only focused on the contextual and proximal antecedents of proactive safety
behaviours.
36 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
4.2 FRAMEWORK FOR MODELLING PROACTIVE SAFETY BEHAVIOURS
Despite the importance of proactive safety behaviours in improving workplace
health and safety, it is only recently that a conceptual model of safety proactivity has
been proposed. According to Curcuruto and Griffin (2017), aiming for an injury-free
workplace requires improvement in the work environment, the person and the
behaviour. These domains are interdependent and dynamic – a change in one domain
impacts on the others. Curcuruto and Griffin’s (2017) model proposes that there are
distal and proximal antecedents of proactive safety behaviours. Curcuruto and Griffin
(2017) argued that distal antecedents comprise contextual and individual factors that
impact on cognitive-motivational mechanisms (i.e., proximal antecedents) which, in
turn influence whether one performs a proactive safety behaviour (See Figure 4.1).
However, it is important to acknowledge that this framework is influenced by previous
models on safety performance by Griffin and Neal (2000) and work proactivity by
Parker and colleagues (Parker & Wang, 2015; Parker, Williams, & Turner, 2006).
While the specific factors studied within these three frameworks differ, there are
several notable commonalities. For instance, among these three frameworks, the
researchers have recognised the importance of dispositional characteristics that may
predispose individuals to act proactively, the role of work environment in cultivating
these behaviours and the potential cognitive mechanisms that have a direct impact on
these behaviours.
Contextual Antecedents (climate, support, job
design)
Individual Antecedents (competency, affective
states and role definition)
Motivational - Capability Drivers
(control perception; self-efficacy)
Motivational -
Commitment Drivers (psychological ownership;
felt responsibility)
Future Oriented States (prevention orientation;
improvement orientation)
Proactive Safety Behaviours
Distal Antecedents Proximal Antecedents
Figure 4.1 Curcuruto and Griffin’s (2018) model of antecedents of safety proactivity. The grey shaded boxes were the focus of the current meta-analysis.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 37
The current review utilised this framework for the purpose of organising both
the literature and the results of the meta-analysis. Within the review, the antecedents
were classified as either contextual (i.e., organisation-related) or proximal (i.e.,
cognitive-psychological mechanisms). Contextual antecedents were considered to be
more distal compared to proximal antecedents and, therefore, it was anticipated that
proximal antecedents would yield larger relationships with proactive safety behaviours
compared to the distal contextual factors.
4.2.1 Contextual Antecedents
To engage in proactive safety behaviours, workers must perceive that such
behaviours are valued and important within their work environment (Curcuruto &
Griffin, 2017; Griffin & Curcuruto, 2016; Griffin & Neal, 2000). In this review,
contextual antecedents refer to variables specific to the organisational environment
that have been found to affect employees’ proactive safety behaviours. In Curcuruto
and Griffin’s (2017) safety proactivity framework, the contextual antecedents were
obtained from the paradigms of: 1) organisational climate and culture, 2)
organisational support and social exchange theories, and 3) work design. Similar to
their framework, the current review presents three categories of contextual antecedents
of proactive safety behaviours: 1) safety climate, 2) leadership, perceived
organisational support and trust, and 3) work demands and work autonomy.
Safety Climate
Researchers often look at the organisation’s safety culture and/or safety climate
when investigating the organisational factors that influence safety behaviours in the
workplace. Safety climate represents the inferences that the employees make towards
their organisation’s safety practices (Zohar, 1980). Safety climate is also often used as
an interchangeable term for safety culture (Mearns & Flin, 1999). While there are some
conceptual differences between safety climate and safety culture, both concepts
represent the importance and value that the organisation and its members place on
workplace safety (Guldenmund, 2000)8.
8 The discussion on the conceptual differences between safety culture and safety climate is beyond the scope of this study. However, it is generally accepted that safety climate provides a ‘snapshot’ of safety culture, and that it reflects the ‘overt manifestations’ of safety culture, such as attitudes, policies and practices of safety within the organisation. Safety culture refers to the shared values, norms, beliefs and ideas of safety within an organisation (Guldenmund, 2000) and it is crucial in shaping and defining how
38 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
According to Zohar (2010), organisations have complex rules and policies across
competing domains. Employees must then sort through these complexities to discern
which behaviours are expected, supported and rewarded. How managers and
supervisors trade-off the need for productivity, while ensuring safety policies and
procedures are still being implemented, presents a message to employees on which
behaviours are most important. If productivity is favoured over safety, employees are
more likely to prioritise production and usually to the detriment of safety (Zohar,
2010). On the other hand, a positive safety climate prioritises safety over the
organisation’s productivity levels. Thus, a positive safety climate would encourage
safety compliant and enhancing behaviours especially if these behaviours are
supported and rewarded.
Safety climate is often seen as a meaningful antecedent to safety behaviour and,
in particular, proactive safety behaviours. The original conceptualisation and
operationalisation of safety climate was conducted at the organisational level (e.g.,
Zohar, 1980), meaning that the shared perceptions of safety practices are coming from
the policy and procedural actions of top management and practices of the supervisors
(Brondino, Silva, & Pasini, 2012). However, Zohar and Luria (2005) proposed that
employees examine their work environment from dual perspectives of being members
of both the organisation and of a particular sub-unit within that organisation. While
safety climate was originally conceptualised as established safety policies and
procedures from the top-level management, sub-unit managers and supervisors
execute these policies and procedures through direct interaction with subordinates
(Zohar & Luria, 2005). Thus, potential discrepancies may occur between the top-level
safety is presented and integrated in the organisation’s daily processes, functions and management. Safety culture is complex as it is comprises the underlying and enduring structure of the fundamental values, norms and assumptions towards safety in an organisation, some of which may not be observable by its own members (Mearns & Flin, 1999). Several researchers argued that qualitative and ethnographic methods should be used when investigating an organisation’s safety culture (Weigmann et al., 2002). The deeper structure of an organisation’s culture is often not immediately accessible to outsiders, therefore, in-depth and extensive measures should be used to gain a full understanding of an organisation’s safety culture (Weigmann et al., 2002).
Since safety climate is easier to measure using quantitative methods (Guldenmund, 2000), the majority of survey studies used the construct of safety climate. Further, the current study utilised meta-analysis to quantify the effects of the observed relationships, therefore, the review (and the current program of research) utilised the construct of safety climate to provide a ‘snapshot’ of an organisation's safety culture.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 39
(i.e., organisation-level) established policies and procedures and the sub-unit (i.e.,
group-level) execution of these policies and procedures.
This multi-level analysis of safety climate only gained research attention within
the last 10 to 15 years and, previously, safety climate was primarily measured from an
individual perspective. Thus, distinction between organisational-level and group-level
safety climate has tended to be poorly specified (Zohar & Luria, 2005). While safety
climate is continuously being measured from the individual level, there is growing
evidence for the predictive and informative nature of safety climate at various levels
of aggregation (Griffin & Curcuruto, 2016; Zohar, 2008, 2014). For instance, Clarke’s
(2006) review showed that an overall measure of safety climate has a stronger effect
with safety participation (Mp = 0.50) compared to safety compliance (Mp = 0.43).
However, when Christian et al. (2009) distinguished the measurement of safety climate
between psychological (i.e., individual-level) and group-level, the differential
influence of the two levels were more pronounced – with individual-level safety
climate having a stronger relationship with safety compliance (Mp = 0.49) compared
with the relationship between group-level safety climate and safety compliance (Mp =
0.40). On the other hand, the effect size found between individual-level safety climate
and safety participation (Mp = 0.59) was the same with the effect size found between
group-level safety climate and safety participation (Mp = 0.59).
The current study primarily built on previous meta-analyses by studying the
effect of different levels of safety climate (e.g., individual, work group-level, and
organisational-level) on proactive safety behaviours. Clarke’s (2006) meta-analysis
did not distinguish between the different levels of safety climate. Christian et al.’s
(2009) meta-analysis only examined the psychological and group-levels of safety
climate on safety participation, but did not examine the impact on organisational-level
safety climate on safety participation9.
In the current study, the definitions used for individual and group-level safety
climate were based on Christian et al.’s (2009) review to maintain consistency and
9 Christian et al. (2009) only looked the relationship between organisational-level safety climate and safety performance (i.e., a combination of safety compliance and safety participation). This could be due to the small number of studies in their review that utilised the organisational-level analysis. The current review found enough studies for the organisational-level to enable that factor to be included in the analysis.
40 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
direct comparison to their results. Individual-level climate is defined as: “individual
perceptions of safety-related policies, practices, and procedures pertaining to safety
matters that affect personal well-being at work” (Christian et al., 2009, p. 1106). When
these perceptions are shared among individuals in a particular work group
environment, a group-level climate emerges. Therefore, group level safety climate is
defined as, “shared perceptions of work environment characteristics as they pertain to
safety matters that affect a group of individuals” (Christian et al., 2009, p. 1106). Since
Christian et al. (2009) did not specifically examine organisational-level safety climate
and no definitions were provided, Zohar et al.’s (2008) definition of organisational-
level safety climate was utilised: “shared perceptions among members of an
organisation with regard to its fundamental properties, i.e., policies, procedures, and
practices” (p. 376).
Relevance to work driving safety
While safety climate research within the work driving setting is limited,
available research suggests that safety climate has a role discouraging risky driving
behaviour in workers ( Newnam et al. 2008; Wills, Watson, & Biggs, 2006, 2009). For
instance, in a survey of 323 employees working in Australian fleet settings, Wills et
al. (2009) found that employee’s perception of safety climate was a significant
predictor of unsafe driving behaviours and driving intentions over and above
demographic characteristics (age and gender) and driving exposure (annual mileage
and weekly driving hours). Safety climate explained the largest amount of unique
variance in the driver’s reported behaviours compared to other factors (i.e., safety
attitudes, perceived behavioural control and driving experience; Wills et al., 2009).
These results provide evidence of the importance of having policies and rules
regarding safe driving and of the importance of safety climate on work driving safety.
While previous research has demonstrated the role of safety climate on driving
behaviours, it is possible that it may also have an influence on work drivers’ proactive
safety behaviours.
Leadership, Perceived Organisational Support and Organisational Trust
Leadership has also been shown to play a critical role in encouraging workers to
perform safety behaviours (Hofmann & Morgeson, 1999; Griffin & Talati, 2014; Neal
& Griffin, 2002). Leaders are in the position to motivate their teams to work safely
and help create a safety culture within the organisation by encouraging and rewarding
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 41
safety behaviours among employees (Hofmann & Morgeson, 2004; Griffin & Talati,
2014).
Within the field of occupational safety, transactional and transformational
leadership is often used to examine the effect of leadership on safety behaviours
(Clarke, 2013a). Transactional leadership emphasises the exchange process between
leaders and members, where rewards are given to the members when an acceptable
level of effort and performance are displayed, and sanctions are imposed when an
expected level of performance is not met or if undesired behaviours are performed
(Bass, 1997). In contrast, transformational leaders are less focused on the exchange
process with their followers, but instead act as a role model and encourage members
to align their value systems with the overall organisational goals (Bass, 1997).
Previous research has shown that transformational leaders were more effective in
motivating employees to behave safely especially if safety was considered as a core
value promoted by leaders (Barling, Loughlin, & Kelloway, 2002).
More recently, however, researchers have distinguished between the impact of
active transactional leaders and passive leadership (Clarke, 2013a; Jiang & Probst,
2016). A meta-analysis by Clarke (2013) differentiated transactional leadership styles
into active versus passive, arguing that “active leaders monitor subordinate’s
behaviour, anticipate problems and take proactive steps to implement corrective
actions. In contrast, passive leaders wait until the behaviour has created problems
before taking any action” (p. 25). Passive leaders take a more laissez-fare approach,
avoiding responsibilities and making decisions and are usually absent when needed by
subordinates (Jiang & Probst, 2016). Available research on passive leadership showed
that this leadership style is related to poor safety climate and higher frequency of
workplace incidents (Kelloway, Mullen, & Francis, 2006; Zohar, 2002).
Clarke’s (2013) meta-analysis demonstrated that while active transactional
leadership is important in ensuring compliance to safety rules and regulations in
employees, transformational leadership is more essential in encouraging employees to
go beyond the rules and regulations and be proactive about safety issues at work.
However, Clarke’s (2013) review did not study the meta-analytic effect of passive
leadership on safety behaviours. Therefore, the current review built on Clarke’s (2013)
review by examining the impact of passive leadership on proactive safety behaviours,
in addition to transformational and active transactional styles of leadership.
42 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
In addition to leadership styles, the role of perceived organisational support and
organisational trust in workplace health and safety are gaining interest in recent years
(e.g., Conchie & Donald, 2009; Conchie, Donald, & Taylor, 2006; Tucker, Chmiel,
Turner, Hershcovis, & Stride, 2008). Perceived organisational support is based on the
organisational support theory, which proposes that, “employees develop global beliefs
concerning the extent to which the organisational values their contributions and cares
about their well-being” (Rhoades and Eisenberger, 2002, p. 698). Thus, perceived
organisational support is the perception that aid will be available from the organisation
when it is needed (Eisenberger, Huntington, Hutchison, & Sowa, 1986; Rhoades &
Eisenberger, 2002). Perceived organisational support had been examined widely
within the organisational psychology literature due to its strong associations with job
satisfaction, wellbeing and job performance (Kurtessis et al., 2017; Rhoades &
Eisenberger, 2002). However, its application within the OHS field has only been
examined sporadically. Initial interest on the role of perceived organisational support
within OHS were introduced by Geller and colleagues in the mid 1990s (Geller et al.,
1996; Roberts & Geller, 1995). They demonstrated that having a caring work
environment promoted safety within the workplace. Geller et al. (2001) found that
employees who felt supported within their organisations were more likely to take
responsibility in ensuring their co-workers safety due to their perceived sense of
camaraderie. From their work, Geller and colleagues argued that actively caring about
employees could act as a supplement or even an alternative approach to monitoring
safety within the workplace (Geller et al., 1996; Roberts & Geller, 1995).
On the other hand, organisational trust describes a more specific interpersonal
process that occurs within the work environment compared to perceived organisational
support. While organisational trust is a complex topic and disagreements exist in
regards to its conceptualisation, it has been defined as a willingness to depend on
another party as well as an expectation of reciprocity (Mayer, Davis, & Schoorman,
1995). The role of trust on safety had been widely recognised by practitioners and
researchers and it is usually seen as an important aspect of safety culture and
transformational leadership (Conchie et al., 2006). For instance, the most widely
accepted and comprehensive definition of safety culture as defined by the Advisory
Committee on the Safety of Nuclear Installations (ACSNI) suggests that mutual trust
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 43
is important to develop an effective safety culture10. In addition, Bass’ (1997) model
of transformational leadership posits that this leadership style is effective, in part,
through its facilitation of building trust in others who follow the leader. However,
currently, empirical investigation of trust as its own concept and its influence on OHS
is lacking. Recent works by Conchie and colleagues (Conchie, 2013; Conchie &
Donald, 2009) examined trust towards leaders, workers and organisation, as its own
concept. They found that trust is an important factor in promoting safety behaviour,
especially if such behaviours were not expected in one’s formal role. Trust in
supervisors and co-workers was shown to be important in safety voice and safety
initiatives as workers would be more confident that they would not be “blamed” for
speaking up about safety issues (Conchie et al., 2006). The available evidence thus
suggests that trust is important in fostering open communication within the workplace
and, in particular, with respect to the open reporting of safety incidents (Conchie et al.,
2006).
Safety climate describes the employees’ shared perceptions of safety policies
and procedures and how safety is valued within the organisation. On the other hand,
leadership, perceived organisational support and organisational trust tap into the
impact of interpersonal processes or social exchanges within the organisation and its
potential influence on safety. Social exchange theory is often utilised to explain the
interpersonal processes that occur within the organisation. Social exchange theory
suggests that if one party acts in ways that are beneficial to another party, this creates
an implicit obligation for future reciprocity (Cropanzano & Mitchell, 2005). In
essence, social exchange theory describes the reciprocal relationship between two
parties (Xerri, 2013). Within the workplace, reciprocity refers to the cooperative
exchange between employees or between the organisation and employees (Dabos &
Rousseau, 2004). Social exchange theory has also been previously utilised as the
theoretical framework for addressing safety citizenship behaviours (Hofmann &
Morgeson, 1999; Hofmann, Morgeson, & Gerras, 2003). Hofmann and Morgeson
10 The full definition of safety culture as proposed by the ACSNI is as follows,“…the product of individual and group values, attitudes, perceptions, competencies, and patterns of behaviour that determine commitment to, and the style and proficiency of, an organisation’s health and safety management. Organisations with a positive safety culture are characterised by communications founded on mutual trust, by shared perceptions of the importance of safety and by the efficacy of preventative measures” (Health and Safety Executive, 2005, p. 3).
44 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
(1999) argued that if organisations actively demonstrate that they care and value their
employees, then employees would perceive that management is open and accepting of
employees’ safety concerns.
From the organisational climate paradigm, a positive safety climate may
encourage employees to act proactively towards safety due to the shared perception
that safety is valued within the organisation. However, from the social exchange
perspective, proactive safety behaviours could be encouraged via an implied obligation
for workers to act in a safe manner especially if the employees receive support and
trust from their organisations. In other words, if employees feel supported, cared for,
inspired by their leaders and have trust towards their managers, they are more likely
to take initiative in safety matters, especially if their wellbeing and safety is valued
within the organisation.
The current study extends previous reviews on safety behaviours by examining
the role of leadership styles, perceived organisational support and organisational trust
on proactive safety behaviours. Previous meta-analyses have tended to focus only on
the role of safety climate and leadership (Christian et al., 2009; Clarke, 2006, 2013a)
without looking at other organisational factors that may influence employees’ safety
behaviours.
Relevance to work driving safety
It is only in recent years that interpersonal processes and relationships within
organisations have gained research attention in the work driving safety context (e.g.,
Newnam, Warmerdam, Sheppard, Griffin, & Stevenson, 2017; Peretz & Luria, 2017;
Warmerdam et al., 2018). Available research in work driving safety has identified that
leaders play a critical role in creating a context in which safety is valued and prioritised
within his or her team (Newnam et al., 2012). Although there is very limited research
that has examined the role of leadership styles on work driving safety, available
evidence suggests that having a collaborative relationship between leaders and drivers
is associated with safer driving performance (Newnam et al., 2012). Furthermore,
research on the role of perceived organisational support and organisational trust on
OHS is currently limited, therefore, their role within the specific domain of work
driving safety remains unclear. Peretz and Luria (2017) did not directly examined the
impact of perceived organisational support and trust in work drivers, but they found
that having low quality friendships at work is associated with unsafe driving
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 45
behaviours (e.g., sharper turns). Therefore, it is possible that these interpersonal
processes may also influence employees’ engagement on proactive safety behaviours
when driving for work.
Work Demands and Work Autonomy
Work design is also an important aspect of Curcuruto and Griffin’s (2017) model
on safety proactivity. Work design describes “how jobs, tasks, and roles are structured,
enacted, and modified, as well as the impact of these structures, enactments, and
modifications on individual, group, and organizational outcomes” (Grant & Parker,
2009, p. 5). Although the previously discussed antecedents of proactive safety
behaviours examines the role of shared perception of safety and interpersonal
processes within the organisation, work design examines the variables inherent within
the job that may encourage or inhibit one’s engagement in safety behaviours. In other
words, work design could have an impact on whether an employee acts in a proactive
manner towards safety. Studies that examine work design and its influence on safety
performance typically use the job demands and resources model and/or the high
performance systems model11 to explain the relationships between work tasks and
safety behaviour (Parker et al., 2001; Zacharatos, Barling, & Iverson, 2005). These
models usually focus on the role of work demands and work autonomy on safety
behaviours.
Work demands within the OHS literature include risks and hazards, physical
demands and work complexity that employees may experience at work (Nahrgang et
al., 2011). It is possible that the strain and exhaustion that an individual may
experience due to these work demands may reduce their engagement in safety
behaviours (Nahrgang et al., 2011). In Nahrgang et al.’s (2011) meta-analysis of safety
outcomes, they found that high work demands (e.g., risk, hazards, physical demands
and work complexity) explained 20% of the variance in adverse events and unsafe
behaviour. Conversely, having job resources, which may involve work autonomy,
could reduce the associated physiological and psychological strains associated with
work demands (Nahrgang et al., 2011). Having autonomy encourages workers to feel
freedom regarding their work and enables them to achieve their goals (Parker et al.,
11 Parker, Axtell, and Turner (2001) defined high performance work systems as: “autonomous job designs with reasonable role demands supported by adequate training, effective leaders, the flow of information, and employment security are fundamental components” (p. 215).
46 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
2001). Autonomy allows employees to feel agency and provide input when necessary.
Indeed, research has found autonomy to be positively related to higher levels of
reporting safety incidents (Parker et al., 2001).
The aforementioned research shows when other demanding tasks require the
focus of workers, and if resources are stretched, safety is often ignored. In these
situations, employees will often narrow their roles to exclude responsibilities outside
their jobs and, therefore, may be less likely to proactively participate in addressing
safety issues at work (Turner, Chmiel, & Walls, 2005; Turner, Stride, Carter,
McCaughey, & Carroll, 2012). Previous meta-analyses have inclined to only examine
the role of perceived work risk on safety compliance (Christian et al., 2009) and the
role of work demands and autonomy on unsafe work outcomes (e.g., unsafe
behaviours, accidents, injuries; Nahrgang et al., 2011). The current meta-analysis
extended the literature by examining the effect of work demands and autonomy on
proactive safety behaviours.
Relevance to work driving safety
Studies on the role of work demands and work autonomy on proactive safety
behaviours of work drivers are limited. However, available research shows that driving
for work can be highly demanding (e.g., physical workload from extended driving
periods, mental stress from traffic congestion, getting to appointments on time;
Useche, Ortiz, & Cendales, 2017). These work demands have been found to be
associated with aggressive driving when commuting to and from work (Li, Wang, Li,
& Zhou, 2017), poor physical health (e.g., neck and back pains; Krause, Ragland,
Greiner, Syme, & Fisher, 1997) and stress in work drivers (Raggatt, 1991).
While it is clear the driving for work can be highly demanding, employee’s
perceived level of autonomy when driving for work is unclear. Some researchers have
argued that work driving is associated with high levels of autonomy (e.g., work drivers
performing their work tasks at geographically remote locations and outside the
physical constraints of a workplace; Newnam et al., 2017; Zohar, Huang, Lee, &
Robertson, 2015). However, other researchers have suggested that work drivers’
autonomy could be limited by their organisation’s policies and procedures (e.g.,
constraints in job scheduling; Morrow & Crum, 2004). Thus, work demands and work
autonomy could have an impact on work drivers’ safety behaviours but their influence
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 47
has yet to be empirically investigated in regards to their impact on one’s engagement
with proactive safety behaviours while driving for work.
4.2.2 Proximal Antecedents
As shown in Figure 4.1, motivational factors and future oriented states are
central to Curcuruto and Griffin’s (2017) model of safety proactivity and act as
proximal antecedents to proactive safety behaviours. Curucuto and Griffin (2017)
argued that several cognitive-mechanisms may impact directly on one’s motivation to
act in a proactive manner. These motivational drivers were referred to as: capability
and commitment drivers. Based on Vroom’s (1964) expectancy-valence theory12,
capability drivers was conceptualised as the ‘can-do’ motivational processes that
explains why individuals may perform proactive safety behaviours (e.g., self-efficacy
and their perceived control). In contrast, commitment drivers tap into individuals’
‘reason-to’ perform these behaviours (e.g., felt responsibility and psychological
ownership of safety within the workplace).
Future oriented states were not conceptualised as motivational factors, but
instead, as an individual’s tendency to look towards future possibilities. In Curcuruto
and Griffin’s (2017) safety proactivity framework, they argued that individuals who
have the propensity to anticipate risks and those who strive to improve safety in the
workplace beyond the minimal standards are more likely to behave proactively for
safety. These individuals have the future orientation of ‘anticipation-orientation’ and
‘improvement-orientation’. Anticipation-oriented and improvement-oriented
individuals are more likely to suggest new or different ways to do things more safely.
These individuals are also more willing to think about ways to improve safety at work
12 In its simplest form, expectancy-valence theory argues that the individual carries out a behaviour depending on (a) the perceived value of the outcome (valence) and (b) the perceived probability of achieving that outcome (expectancy; Pinder, 2008). Curcuruto and Griffin’s (2017) model of safety proactivity argues that the ‘can-do’ motivation to conduct proactive safety behaviours is based on the ‘expectancy’ aspect of Vroom’s expectancy-valence theory, while the ‘reason-to’ motivation to conduct such behaviours taps into the aspect of ‘valence’.
However, the majority of research within the OHS field did not conceptualised safety motivation as a multidimensional construct. It is also recently that the concepts of ‘can-do’ and ‘reason-to’ motivations to act safely have been proposed (Curcuruto et al., 2016; Curcuruto et al. 2017). Therefore, the current review conceptualised safety motivation as a unidimensional construct. Furthermore, concepts that may be associated with safety motivation, such as self-efficacy and perceived control, were conceptualised as its own constructs.
48 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
even if activities are running smoothly and there is no evidence of apparent threat
(Curcuruto et al., 2016).
Using Curcuruto and Griffin’s (2017) safety proactivity model as a guide, the
discussions of proximal antecedents within the review examines the role of safety
motivation, regulatory focus, self-efficacy and perceived control on proactive safety
behaviours. Safety knowledge was not originally conceptualised as a proximal factor
of the safety proactivity model, however, previous frameworks (e.g., Griffin and Neal,
2000) considered safety knowledge as a proximal antecedent of safety behaviours.
Therefore, the current review also examined safety knowledge as a proximal
antecedent of proactive safety behaviours.
Safety Knowledge and Safety Motivation
Safety knowledge and safety motivation are usually considered as proximal
antecedents of safety behaviours. Safety knowledge is defined as employees’
understanding of the safety procedures in the workplace (Griffin and Neal, 2000).
Griffin and Neal (2000) argued that individuals must understand how to perform their
work safely and must also have the necessary skills to comply with safety procedures.
Safety motivation, on the other hand, refers to the person’s willingness to put effort in
behaving safely and the value that the person puts on ‘being safe’. Employees may
work in an environment that has a positive safety climate, but they must also be
motivated to participate in safety activities.
The role of safety knowledge and safety motivation on safety behaviours had
been extensively examined in the literature. Both safety knowledge and safety
motivation have been shown to have a direct influence on proactive safety behaviours
(Christian et al., 2009; Curcuruto & Griffin, 2017). In their meta-analysis, Christian et
al. (2009) sought to examine such relationships; however, due to a lack of studies, they
were able to only examine the relationship between safety knowledge and safety
participation. Their review found a large effect between safety knowledge and safety
participation (Mp = .61). The current review extended Christian et al.’s (2009) research
by calculating the meta-analytic effect size between safety motivation and proactive
safety behaviours.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 49
Regulatory Focus, Self-efficacy and Perceived Control
Although the majority of research currently has focused on safety knowledge
and motivation as proximal antecedents of safety behaviours, recent studies have
begun to investigate other possible proximal antecedents, such has employees’
regulatory focus. The self-regulation focus theory describes the two cognitive
approaches that individuals engage in when deciding which behaviours to perform
during a goal pursuit (Higgins, 1997; Henning et al., 2009). These two cognitive
approaches are promotion focused or prevention focused (Higgins, 1997). Promotion
focused individuals seek out ways to accomplish tasks, often engaging in strategies
that maximise rewards (Henning et al., 2009); while, prevention focused individuals
tend to avoid activities that may deter a successful accomplishment of tasks.
Prevention focused individuals mostly engage in strategies that avoid punishment
(Henning et al., 2009) while promotion focused individuals are more likely to take
initiative to change aspects of their immediate work environment (Aryee & Hsiung,
2016). Promotion focus and prevention focus are considered as complementary goal-
oriented states of safety proactivity in Curcuruto and Griffin’s (2017) model in
addition to safety motivation. Curcuruto and Griffin (2017) argued that these
regulatory states enable people to direct attention to future possibilities and the
potential for unexpected events to impinge on current operations adopting more
proactive strategies for a safer environment. At the time of writing, this is the first
study meta-analytic review that examined the role of regulatory focus on proactive
safety behaviours.
Curcuruto and Griffin’s (2017) model also argued that self-efficacy and
perceived control are essential in safety proactivity. Self-efficacy is a person’s level of
confidence in their ability to perform tasks successfully under a range of conditions.
On the other hand, perceived control refers to a person’s belief that their actions
directly influence their immediate surroundings. As mentioned previously, self-
efficacy and perceived control are examples of commitment drivers under Curcuruto
and Griffin’s (2017) model which they describe as the ‘can-do’ motivational processes
that explain why individuals may perform proactive safety behaviours. In other words,
when individuals have the confidence in their ability to be proactive in regards to their
safety and they believe that they have control over their work tasks, they are more
likely to perform proactive safety behaviours. In a study of employees from the
50 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
construction and transport industries, Fugas and colleagues (Fugas, Melia, & Silva,
2011; Fugas, Silva, & Melia, 2012, 2013) found that perceived control and self-
efficacy had direct effects on proactive safety behaviours.
Relevance to work driving safety
Only some of the aforementioned proximal antecedents have been studied within
the work driving context. For instance, while research is limited, studies exist on the
role of safety motivation, safety knowledge, perceived control and self-efficacy on
work driving behaviours. Available studies have suggested that high safety motivation
was associated with lower self-reported crashes (Newnam, Griffin, & Mason, 2008).
Newnam et al. (2008) also found that the safety motivation of drivers was stronger if
the fleet managers and supervisors highly valued driving safety. In the same study,
Newnam et al. (2008) found that self-efficacy was not a significant predictor of work
drivers’ self-reported crashes but it demonstrated a significant association with their
safety motivation. Furthermore, a report by the European Agency for Safety and
Health at Work reviewed several case studies conducted in Europe regarding the
management of risks in road transport drivers (Copsey et al., 2011). The report found
that increasing knowledge of the risks, policies and procedures via training, driver
manuals and information knowledge-sharing, helped to reduce risks when transporting
goods. However, these studies did not examine the influence of safety motivation and
knowledge on work drivers’ proactive safety behaviours.
The evidence regarding the role of perceived control on work driving safety is
mixed. Although Wills et al. (2009) demonstrated that perceived control was not a
significant predictor of unsafe driving behaviours and driving violations in work
drivers (e.g., self-reported crashes and traffic offences), Poulter, Chapman, Bibby,
Clarke, and Crundall (2008) found that perceived control showed a significant direct
effect on work drivers’ adherence with road traffic laws. The difference on the results
between these two studies could be due to the different outcome variables. More
specifically, in Will et al.’s (2009) study, it could be argued that work drivers had less
perceived control of unsafe driving behaviours, especially if their organisation's
climate encourage unsafe practices (i.e., driving while fatigued to meet production
goals). Indeed, in Will et al.’s (2009) study, safety climate showed a stronger effect on
driving behaviours compared to perceived control. Nevertheless, these studies
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 51
examined the influence of perceived control on driving behaviours, but not on the
proactive safety behaviours of work drivers.
4.2.3 Summary of the Literature
The previous sections critically synthesised the contextual and proximal
antecedents of proactive safety behaviours and its related constructs, based on
Curcuruto and Griffin’s (2017) framework. It is important to examine these
antecedents as behaviours that go beyond one’s expected roles “do not exist in a
vacuum” (Gyekye & Salminen, 2005, p. 815). The literature specifically focused on
safety climate, organisation-based social exchange and interpersonal processes
(specifically, leadership, perceived organisational support and trust), and work design
(specifically, work demands and autonomy) as contextual antecedents of proactive
safety behaviours. Safety knowledge, safety motivation, regulatory focus (specifically,
promotion focus and prevention focus), self-efficacy and perceived control were
considered as the proximal antecedents. The relevance of these antecedents on work
driving safety were also examined as the review would inform the development of a
research model of the current program of research. Furthermore, since contextual
antecedents were considered to be more distal compared to proximal antecedents, it
was anticipated that proximal antecedents would yield larger relationships with
proactive safety behaviours compared to the distal contextual factors.
4.3 METHOD
4.3.1 Search Strategy
A literature search was conducted to identify empirical studies that had examined
factors that influenced proactive safety behaviours. The first component of the
literature search was the use of electronic databases for any relevant studies that were
written in English and with no restriction imposed on the year of publication. The
databases of PsychINFO (via Ebscohost), Web of Science and Scopus were utilised to
conduct the search. These databases give wide access to literature in behavioural
science (PsychINFO) and cross-disciplinary research (Web of Science and Scopus).
The following keywords for the search were used: “safety citizenship”, “safety
participation”, “extra-role”, “actively caring” and “proactive safety”. The AND search
strategy was used for “extra-role” and “actively caring” with “safety” (e.g., “extra-
role” AND “safety”) to denote that the initial keyword search was specific on safety
52 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
issues (see Table 4.1). The AND search strategy was also used for Scopus as the initial
search for the “proactive safety” keyword produced more than 200 results.
Table 4.1 Search Terms used for each database
Database Search Term
PsychINFO (via Ebscohost) “proactive safety AND behavi*”, “safety citizenship”
(abstract), “safety participation”, “actively caring AND
safety”, “extra role AND safety”
Web of Science “proactive safety”, “safety citizenship”, “safety participation”,
“actively caring AND safety”, “extra role AND safety”
Scopus “proactive safety AND behavi*”, “safety citizenship”
(abstract), “safety participation”, “actively caring AND
safety”, “extra role AND safety”
A second component of the literature search was a manual search of journals that
targeted organisational psychology and safety to ensure all relevant articles are
included. The journals that were included in the search were: Journal of Applied
Psychology, Personnel Psychology, Journal of Organizational Behavior, Journal of
Occupational Health Psychology, Safety Science, Journal of Safety Research and
Accident Analysis and Prevention. Furthermore, the reference lists of the retrieved
articles and previous meta-analyses on safety behaviours and safety performance (e.g.,
Christian et al., 2009; Clarke, 2006, 2013) were reviewed for additional studies. Figure
4.2 shows the search strategy that was utilised for this study.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 53
4.3.2 Inclusion and Exclusion Criteria
To be included in the review, studies were required to meet three criteria:
1. Studies had to have included a measure of proactive safety behaviour (Table
4.2). Studies were excluded if they only used an overall measure of safety
performance without proving a distinction between proactive safety
behaviour and safety compliance.
Papers excluded: Duplicates n = 246
Papers for full-text review n = 130
Studies included in the data extraction
n = 78
Papers excluded: Did not explicitly study proactive behaviours n = 37 Did not provide correlations or statistics to calculate an effect size n = 9
Cannot access full-text n = 6
Papers for title and abstract review
n = 253
Manual search n = 52 Database search n = 447
Papers excluded: Inclusion criteria not met n = 123
Total papers n = 499
Figure 4.2 Search strategy for the systematic review and meta-analysis
Studies included in the meta-analysis calculation
n = 71
Papers excluded in the meta-analytic coding n = 7
54 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Table 4.2 Terminologies and measures used for the current study
Terminology / Construct Definition Behaviours measured Safety Initiative (Andressien, 1997; Simard & Marchard, 1995)
Employees’ attempts to create a safer work environment.
Employees take initiatives in order to work more safely Make suggestions in order to improve safety at work environment Put pressure on the supervisor to improve safety at work
Actively caring about safety (Geller, Johnson, Redmon, & Mawhinney, 2001; Geller, Roberts, & Gilmore, 1996)
Employees acting to benefit the safety of other employees.
Observing and recording the safe and unsafe behaviours of coworkers, and then provide constructive behavioral feedback
Willingness to participate in health and management programs (Cree & Kelloway, 1997)
By participating in health and safety programs, employees have the opportunity to have a "voice" in the management of workplace health and safety.
Participation in various programs (e.g., attending safety meetings, attending safety training).
Safety Participation (Griffin & Neal, 2000)
Safety behaviours that may not necessarily directly contribute to workplace safety, but help develop an environment that supports safety.
Promoting safety program Extra effort to improve safety Voluntarily carry out tasks to improve safety
Safety Citizenship (Hofmann et al., 2003)
Safety behaviours that are not formally rewarded by the organisation, but plays a strong role in accident prevention due to its facilitation in improving the safety and learning within the workplace.
Whistle-blowing Safety voice Helping Safety initiative
Proactive safety behaviours (Curcuruto et al., 2015)
Safety behaviours that are challenging in nature and seek to bring out positive change in the safety practices within the organisation.
Whistle-blowing Safety voice Safety initiative Keeping informed
Prosocial safety behaviours (Curcuruto et al., 2015)
Safety behaviours that are affiliative in nature. This behaviour generally manifest itself as helping co-workers and looking out for their welfare and safety. Often seen as a way to foster good relationships.
Helping Stewardship
2. Studies had to have been conducted within an organisational setting. Thus,
studies that utilised a student population as the study sample were excluded.
3. Studies were required to have reported sample sizes and correlations (or
statistics that could be transformed into correlations) between proactive
safety behaviour and an antecedent variable. Qualitative studies and case
studies were excluded in the meta-analysis.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 55
After the data extraction, some studies were not added to the calculations of the
meta-analytic correlations due to the small number of studies examining the same
antecedent. For instance, the study by Zhang and Wu (2014) on mindfulness and
general mental ability were excluded in the meta-analytic calculations. Furthermore,
some studies examined proactive safety behaviours and related constructs without a
discussion of any antecedents. From this process, a total of 7 studies that were
extracted for full-text review were not included in the meta-analytic calculations.
Therefore, a total of 71 studies were included for the meta-analytic calculations.
4.3.3 Coding
Sample size, the country where the study was performed, industry from which
drivers were from, study design, measure and definition of proactive safety behaviour,
and the antecedents were coded. The coding of the antecedents is available in
Appendix A. Effect sizes were recorded for all possible statistical relations among the
antecedents and proactive safety behaviour variables in order to calculate the pooled
estimate effect size. Accurate coding is essential for meta-analysis. Once the coding
was finished, 15% of the sample were randomly selected, cross-checked with the
original sources for inaccuracies by the same author (the PhD candidate). Inaccurate
input were subsequently revised.
4.3.4 Meta-analysis calculations
Meta-analytic calculations were carried out using Hunter and Schmidt’s random-
effects model (Schmidt & Hunter, 2014). This model was applied due to the different
measurements used for the antecedent and the outcome variable (e.g., safety
participation measure, safety citizenship measures, actively caring measures, see Table
4.2 for the measures coded within the meta-analysis). Data was analysed using the
metafor package in R, with the H&S-estimator (Viechtbauer, 2010). Hunter and
Schmidt’s approach is an appropriate method when estimating pooled effect sizes on
studies that use continuous measures (e.g., correlation coefficient or standardized
mean differences; Borenstein, Hedges, Higgins, & Rothstein, 2009). This approach is
also often used when conducting meta-analysis in the field of the organisational
sciences (Kepes et al., 2013).
Using Hunter and Schmidt’s meta-analytic approach, the effect size between
variables were represented by the observed correlation coefficients (i.e., Pearson’s r)
56 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
and weighted by the sample size (Borenstein et al., 2009). These effect sizes were then
corrected with the study’s imperfections or ‘artefacts’ to provide a better estimate of
the effect (Borenstein et al., 2009). Measurement errors tend to attenuate (i.e., lower
or dilute) the observed correlation coefficients.
When using Hunter and Schmidt’s (2004) method, the observed effect sizes are
usually corrected using the measurement errors for the antecedent and outcome
variables by giving more weight when calculating the pooled effect size estimates.
Since the majority of the studies reported the measures’ Cronbach α, these reliability
estimates were used for the corrections using equation 4.1. For studies that did not
report the Cronbach alpha’s for the measures used, the average of the reported
reliability estimates were utilised, an approach recommended by Hunter and Schmidt
(2004).
∙ ∙ Equation
4.1
rcor = corrected r; robv = observed r; rxx = Cronbach α of antecedent variable; ryy = Cronbach α of outcome variable
Other corrections were also applied. Within the dataset, there were studies that
reported multiple estimates of the same relationship. For instance, estimates for several
dimensions of safety climate (e.g., management commitment, safety over production)
were reported instead of providing the overall correlation estimate between safety
climate and proactive safety behaviour13. For these cases, the observed effect sizes
were combined into a single correlation using the average mean of the reported
estimates. This approach prevented a study from being double-counted in the meta-
analytic calculations. While using the composite formula is the preferred method for
calculating a single correlation for interdependent effect sizes (Geyskens et al., 2009),
some calculations for the composite scores were not possible14. For consistency in
13 For example, a study may provide an effect size for management commitment and safety participation, r = .30 and another effect size for safety over production r = 40, which are dimensions of safety climate. If the study did not provide an overall effect size for safety climate, the average of the available effect sizes that measure the same construct (which is safety climate for this example) was utilised (e.g., average of r = .30 and r = .40 is .35). 14 According to Geyskens, Krishnan, Steenkamp, and Cunha (2009), calculating a single composite score formula is the preferred approach, which follows the formula: composite score = Σrxy/SQRT(k + k*(k -1)*(ΣrY1Y2/k))
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 57
reporting, average of estimates was calculated. In contrast, studies that included
multiple independent samples were separately coded.
The following information was collected for the meta-analytic calculations: the
observed correlations, robv, the sample size (N), and the Cronbach’s α of the
antecedents (rxx) and outcome variables (ryy) to correct for the observed Pearson’s r
correlations. Once all information were collected and coded in Microsoft Excel, the
metafor package in R was used to calculate the corrected correlations, rcor, the pooled
observed and corrected correlations estimates and the corresponding standard errors
for the pooled corrected estimates (SE) and the 95% confidence intervals (CI). A 95%
CI excluding zero indicates that one can be 95% confident that the average true
correlation is larger than zero. Therefore, an exclusion of zero within the confidence
intervals suggest a significant result. Confidence intervals provide an estimate of the
variability around the estimated pooled corrected meta-analytic correlations. The total
sample size and the number of studies (k) included in the pooled correlations were
presented. Finally, the heterogeneity of the studies were assessed.
4.4 RESULTS
4.4.1 Study Characteristics
The studies that were analysed for the current meta-analysis are presented in
Table 4.3. The studies were conducted in various industries: agriculture, construction,
healthcare, manufacturing, mining, transport, and the utility, petroleum and energy
sector. The most common industry where the studies were conducted was the utility,
petroleum and energy sector (n = 16; 22.5%). Ten studies used employees from various
industries, retail, military or firefighting (14.1%). Around two-thirds of these studies
were conducted in Europe (n = 22; 31%) and Northern America (n = 25; n = 35%).
The majority of the studies were cross-sectional (n = 65; 95%) and two of these
studies were carried out in two waves. Only 3 studies used a longitudinal design. Just
over half of the studies used the Neal and Griffin’s (2000) safety participation (n = 36;
51%) and 15 (21%) of the studies used Hofmann et al.’s (2003) safety citizenship
where k = no. of correlations and rY1Y2 are the inter-correlations of the composite. While this method is the preferred approach (Geyskens et al., 2009), some data required for the formula were still missing, therefore, available effect sizes were averaged so as to be dealt with in a consistent manner.
58 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
behaviours to measure proactive safety behaviours. The remainder of the studies either
developed their own measures (n = 6; 8%) or relied upon a mixture of items adapted
from safety participation and safety citizenship measures (n = 12; 17%).
4.4.2 Meta-analytic Correlations
Table 4.4 demonstrates the pooled meta-analytic correlations between the
perceived work environment, individual differences and the proximal antecedents of
proactive safety behaviours. The Cochran’s Q-Statistics demonstrate heterogeneity in
all extracted relationships between the antecedents and proactive safety behaviours
except for group-level safety climate and passive leadership. Its corresponding I2
denotes the extent of the heterogeneity within the dataset. These results suggest that
the use of a random-effects estimation was appropriate for the calculations of the
pooled estimate effect size. The Egger’s regression tests were conducted to provide an
objective measure for potential publication bias. Egger’s test was used due to its better
suitability for smaller meta-analysis sample sizes (k < 25; Quintana, 2015). From this
test, only the effect size for perceived control showed apparent publication bias (i.e.,
stronger effect sizes being published; Quintana, 2015) due to the significant Egger’s
test.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 59
Table 4.3 Studies included in the data-analysis
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
1 Agnew, Flin, and Mearns (2013)
Healthcare UK Europe 1866 clinical staff Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
2 Andriessen (1978) Construction Netherlands Europe 207 construction workers
Cross-sectional
Safety initiative Original Safety Motivation
3 Aryee and Hsiung (2016)
Others Taiwan Asia 235 firefighters; 91 supervisors
Longitudinal (6m duration)
Safety initiative Hofmann et al.'s Safety Citizenship
Regulatory Focus
4 Barbaranelli, Petitta, and Probst (2015)
Others US and Italy Mixed Various workers Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Safety Knowledge, Safety Motivation
5 Boughaba, Hassane, and Roukia (2014)
Utility, Petroleum and Energy
Algeria Middle East
300 workers from an oil company (Company A); 208 workers from an oil company (Company B)
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
6 Brondino, Silva, and Pasini (2012)
Manufacturing Italy Europe 991 blue collar workers from a metal and mechanical sector
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
7 Burke, Sarpy, Tesluk, and Smith-Crowe (2002)
Utility, Petroleum and Energy
US North America
132 hazardous waste workers
Cross-sectional
Engaging in work practices to reduce risk
Original Safety Knowledge
8 Burt, Sepie, and McFadden (2008)
Construction New Zealand Oceana 80 workers from forestry and construction industries
Cross-sectional
Care scale Geller's Actively Caring
Perceived Organisational Support
9 Chen and Chen (2014)
Transport Taiwan Asia 339 flight attendants Cross-sectional
Extra-role safety behaviour; Upward communication
Others or Mixture Job Autonomy
10 Chughtai (2015) Healthcare Pakistan Asia 179 doctors Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership; Self-efficacy
11 Clarke and Ward (2006)
Manufacturing UK Europe
83 team members; 22 supervisors from a glassware manufacturing company
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Leadership, Job Autonomy
12 Conchie and Donald (2009)
Construction UK Europe 139 workers and 33 supervisors from a construction company
Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Leadership, Trust
13 Conchie, Taylor, and Donald (2012)
Utility, Petroleum and Energy
UK Europe 150 employees; 79 supervisors from an oil company
Cross-sectional
Safety voice Hofmann et al.'s Safety Citizenship
Leadership, Trust, Safety Motivation
60 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
14 Conchie (2013) Construction UK Europe 251 employees from a construction company
Cross-sectional
Challenge and Affiliative
Hofmann et al.'s Safety Citizenship
Leadership, Trust, Safety Motivation, Regulatory Focus
15 Cree and Kelloway (1997)
Manufacturing Canada North America
130 production employees
Cross-sectional
Willingness to participate
Others or Mixture Work demands
16 Cullen and Hammer (2007)
Healthcare US North America
243 nurses and health care workers
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Work demands
17 Curcuruto, Mearns, and Mariani (2016)
Manufacturing Italy Europe 523 chemical and manufacturing
Exploratory and Validation
Proactive safety Hofmann et al.'s Safety Citizenship
Leadership
18 Eklöf (2002) Agriculture Sweden Europe 92 fishermen Pilot of survey
Activity in safety work Others or Mixture Safety Knowledge; Perceived Control
19 Ford and Tetrick (2011)
Healthcare US North America
171 hospital workers Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate, Perceived Control
20 Fugas, Melia, Silvia (2011)
Transport Italy Europe
129 operational workers in a transportation company
T1 and T2 cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate
21 Fugas, Silva, and Melia (2012)
Construction Italy Europe
356 operational workers in a transportation company
Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate, Perceived Control
22 Geller, Roberts, and Gilmore (1996)
Manufacturing US North America
374 workers from a plastic manufacturing plant; 218 workers from a textile manufacturing plant
T1 and T2 cross-sectional
Willingness to actively care
Geller's Actively Caring
Perceived Organisational Support, Perceived Control, Work Demands
23 Griffin and Neal (2000)
Manufacturing AUS Oceana 1264 workers from a construction and mining company
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Safety Knowledge, Safety Motivation
24 Griffin and Hu (2013)
Others AUS Oceana 267 workers from various industries
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership
25 Guo, Yiu, and Gonzalez (2016)
Construction NZ Oceana 213 construction workers
Cross-sectional
Safety participation Original Safety Climate, Safety Knowledge, Safety Motivation
26 Hoffmeister et al. (2014)
Utility, Petroleum and Energy
US North America
1167 pipefitters and plumbers
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Leadership
27 Hofmann and Adam (1996)
Utility, Petroleum and Energy
US North America
222 workers from a chemical processing plant
Cross-sectional
Approach intention Original Perceived Organisational Support
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 61
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
28 Hofmann, Morgeson, and Gerras (2003)
Others US North America
101 workers from a military unit
Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate, Leadership
29 Hon, Chan, and Yam (2014)
Utility, Petroleum and Energy
HK Asia
396 repair, maintenance, minor alternation and addition employees
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
30 Hsu, Lee, Wu, and Takano (2008)
Utility, Petroleum and Energy Taiwan and
Japan Asia
295 oil refinery workers from Taiwan; 256 oil refinery workers from Japan
Cross-sectional
Willingness to report Original
Safety Climate, Perceived Organisational Support, Work Demands, Regulatory Focus; Self-efficacy
31 Inness, Turner, Barling, and Stride (2010)
Others US North America
159 moonlighters Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership, Work Demands
32 Jiang, Yu, Li, and Li (2010)
Utility, Petroleum and Energy
China Asia 631 workers from petroleum and chemical industries
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
33 Jiang and Probst (2016)
Transport US North America
389 workers from a public transit agency
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership, Safety Knowledge, Safety Motivation
34 Kark, Katz-Navon, and Delegach (2015)
Others Israel Middle East
99 employees from an online survey firm with access to workers; 789 workers and 49 managers in teams of technician and mechanics
Cross-sectional
Safety initiative Others or Mixture Leadership
35 Kath, Marks, Raney (2010)
Transport US North America
548 railway workers Cross-sectional
Upward safety communication
Hofmann et al.'s Safety Citizenship
Safety Climate, Leadership, Perceived Organisational Support
36 Keffane (2015) Others France Europe 165 workers; 135 managers
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Safety Knowledge, Safety Motivation
37 Krauss and Casey (2014)
Utility, Petroleum and Energy
Australia Oceana 254 workers from a utilities company
Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate, Leadership
38 Lievens and Vlerick (2014)
Healthcare Belgium Europe 152 nurses Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership, Safety Knowledge
39 Lu and Yang (2010) Transport Taiwan Asia 336 passenger ferry operators
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership
62 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
40 Lu and Yang (2011) Transport Taiwan Asia 155 passenger ferry operators
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
41
Martinez-Corcoles, Schobel, Gracia, Tomas, and Peiro (2012)
Utility, Petroleum and Energy Spain Europe
495 workers from a nuclear power plant
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership
42
Martinez-Corcoles, Gracia, Tomas, Peiro, and Schobel (2013)
Utility, Petroleum and Energy
Spain Europe 479 workers from a nuclear power plant
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Leadership
43 McGonagle, Childress, Walsh, and Bauerle (2016)
Construction USA North America
290 workers in physical labour jobs - taken with some university students but also field recruitment
Cross-sectional
Safety participation Others or Mixture Safety Climate, Safety Motivation
44 Mearns and Reader (2008)
Utility, Petroleum and Energy
UK Europe 703 workers from an installation company
Cross-sectional
Safety citizenship Others or Mixture Perceived Organisational Support
45 Mullen (2005) Manufacturing Canada North America
103 workers from manufacturing company; 75 students from service industries
Cross-sectional
Willingness to participate
Others or Mixture Perceived Organisational Support
46 Mullen and Kelloway (2009)
Healthcare Canada North America
54 leaders; 115 healthcare workers
Longitudinal; Pre-post
Safety participation Neal and Griffin's Safety Participation
Self-efficacy; Perceived Organisational Support
47 Mullen, Kelloway, and Teed (2011)
Healthcare Canada North America
241 workers taken from a university sample; 491 healthcare employees from Sample B
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Leadership
48 Neal, Griffin, and Hart (2000)
Healthcare Australia Oceana 525 healthcare workers
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Safety Knowledge, Safety Motivation
49 Neal and Griffin (2006)
Healthcare Australia Oceana
430 healthcare workers in T1; 490 healthcare workers in T2; 301 healthcare workers in T3
Longitudinal Safety participation Neal and Griffin's Safety Participation
Safety Climate, Safety Motivation
50 Paolillo, Silva, and Pasini (2016)
Manufacturing Italy Europe 481 workers from a metal-mechanical industry
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Motivation
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 63
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
51 Parboteeah and Kapp (2008)
Manufacturing US North America
237 workers from an automotive manufacturing company
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Motivation
52 Probst, Graso, Estrada, and Greer (2013)
Manufacturing US North America
128 workers from pulp and paper mill company
Two-Wave Safety citizenship behaviours
Neal and Griffin's Safety Participation
Safety Motivation, Regulatory Focus
53 Sampson, DeArmond, and Chen (2014)
Utility, Petroleum and Energy
US North America
120 pipefitters belonging in a union local
Cross-sectional
Safety participation Hofmann et al.'s Safety Citizenship
Perceived Organisational Support, Job Autonomy
54 Shea, De Cieri, Donohue, Cooper, and Sheehan (2016)
Others Australia Oceana 3605 workers from various organisations
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Motivation; Perceived Control
55 Simard and Marchand (1994)
Manufacturing Canada North America
2169 various workers from manufacturing plants
Cross-sectional
Safety initiatives Others or Mixture Safety Climate
56 Simard and Marchand (1995)
Manufacturing Canada North America
23615 workers from manufacturing plants
Cross-sectional
Safety initiatives Others or Mixture
Safety Climate, Perceived Organisational Support, Job Demands
57 Sinclair, Martin, and Sears (2010)
Others US North America
535 retail employees Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Work Demands, Safety Knowledge, Safety Motivation
58 Smith and DeJoy (2014)
Others US North America
398 full time professional fire-fighters
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
59 Smith, Eldridge, and DeJoy (2016)
Transport US North America
398 full time professional fire-fighters
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate, Leadership
60
Subramaniam, Mohd Shamsudin, Mohd Zin, Sri Ramalu, and Hassan (2016)
Manufacturing Malaysia Asia 120 workers from manufacturing industries
Cross-sectional
Safety participation Others or Mixture Safety Climate
61 Tharaldsen, Mearns, and Knudsen (2010)
Utility, Petroleum and Energy
UK and Norway
Europe
170 workers from a drilling company in the UK; 621 workers from a drilling company in Norway
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Trust
64 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Study No.
Author (Year) Industry Country Area Sample Characteristics
Study Design Terminology Used Measure Used Predictors
62 Toderi, Gaggia, Mariani, Mancini, and Broccoli (2015)
Construction Italy Europe 277 workers in construction industry
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Knowledge, Safety Motivation
63 Tucker, Chmiel, Turner, Hershcovis, and Stride (2008)
Transport UK Europe 213 bus drivers Cross-sectional
Employee safety voice Hofmann et al.'s Safety Citizenship
Perceived Organisational Support
64 Turner, Chmiel, and Walls (2005)
Transport UK Europe 334 railway workers Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Perceived Organisational Support, Job Autonomy
65 Turner, Stride, Carter, McCaughey, and Carroll (2012)
Healthcare UK Europe 280 healthcare workers
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Job Autonomy
66 Vinodkumar and Bhasi (2010)
Agriculture India Asia 1566 fertilizer companies
Cross-sectional
Safety participation Original Safety Climate, Safety Knowledge, Safety Motivation
67 Willis, Brown, and Prussia (2012)
Utility, Petroleum and Energy
US North America
821 employees from an electric utility company
Cross-sectional
Safety citizenship behaviours
Others or Mixture Safety Climate
68 Xuesheng and Xintao (2011)
Mining China Asia 450 workers from a coal mine
Cross-sectional
Safety citizenship behaviours
Hofmann et al.'s Safety Citizenship
Safety Climate
69 Yuan, Li, and Lin (2014)
Mining China Asia 271 workers from a coal mine
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Safety Climate
70 Yuan, Li, and Tetrick (2015)
Mining China Asia 250 workers from a coal mine
Cross-sectional
Safety participation Neal and Griffin's Safety Participation
Perceived Organisational Support; Self-efficacy
71 Zacharatos, Barling, and Iverson (2005)
Utility, Petroleum and Energy
Canada North America
191 workers from telecoms and petroleum companies
Cross-sectional
Safety initiative Others or Mixture Safety Climate, Trust, Safety Knowledge, Safety Motivation
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 65
Table 4.4 Results of the meta-analysis
Construct N k robv rcor SE (rcor) 95%
CIlower 95%
CIupper Q I2
Egger’s Test
Contextual Antecedents Safety climate 20,886 47 0.35 0.43 0.03 0.37 0.49 454.67** 89.5% p = 0.913
Psychological safety climate 17,368 38 0.35 0.43 0.04 0.36 0.51 428.07** 90.9% p = 0.895 Group-level safety climate 2,170 6 0.39 0.47 0.03 0.42 0.52 7.64 16.0% p = 0.990 Organisational-level safety climate 1,348 3 0.30 0.37 0.07 0.23 0.50 10.59** 64.3% p = 0.85
Leadership Transformational leadership 8,518 28 0.33 0.37 0.04 0.30 0.44 163.04** 82.3% p = 0.936 Transactional leadership 3,534 9 0.18 0.22 0.08 0.06 0.38 64.37** 83.3% p = 0.932 Passive leadership 1,011 3 -0.18 -0.23 0.04 -0.31 -0.16 2.37 0.0% p = 0.136
Perceived organisational support 4,865 15 0.27 0.33 0.04 0.25 0.41 52.29** 70.2% p = 0.924 Organisational trust 1,518 9 0.28 0.32 0.06 0.21 0.43 42.08** 78.3% p = 0.063 Work autonomy 1,115 4 0.38 0.44 0.13 0.19 0.69 67.26** 93.9% p = 0.815 Work demands 3,315 12 0.01 -0.00 0.07 -0.14 0.14 80.28** 84.1% p = 0.872
Proximal Antecedents Perceived knowledge and skill 7,498 16 0.51 0.64 0.04 0.57 0.71 106.95** 84.2% p = 0.147 Safety motivation 11,764 21 0.44 0.53 0.05 0.42 0.63 265.04** 91.2% p = 0.460 Self-efficacy 1,179 5 0.33 0.42 0.53 0.32 0.53 12.84* 61.0% p = 0.475 Perceived control 4,754 6 0.60 0.75 0.12 0.50 0.99 188.02** 93.1% p < .001 Regulatory focus
Promotion focus 2,37
3 9 0.32 0.38 0.07 0.24 0.51 50.43** 80.5% p = 0.512
Prevention focus 1,482 4 0.03 0.03 0.07 -0.12 0.18 20.45** 72.2% p = 0.664 Notes. k = number of studies; robv = Mean pooled observed correlation coefficients; rcor = Mean pooled corrected correlation coefficients; SE
(rcor) = Standard Error of the Mean pooled corrected correlation coefficients; CI = Confidence Intervals; Q = Cochran’s Q-Statistics; I2 = I2 statistics.
66 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
4.4.3 Contextual Antecedents
Given that the studies included in the analysis generally featured safety climate
and leadership when examining safety behaviours, it is not surprising that these two
factors were the two most studied antecedents of proactive safety behaviour within the
current review. Safety climate was the most studied antecedent of proactive safety
behaviour with individually coded effect sizes of k = 47 and while there were k = 40
individually coded effect sizes for leadership styles.
In line with previous reviews (Christian et al., 2009; Clarke, 2006), the current
findings showed a moderate and positive relationship between safety climate and
proactive safety behaviours (rcor = 0.43; 95% CI [0.37, 0.49]) and this effect was
significant. When the different levels of safety climate were examined, all levels
showed significant and moderate relationships with proactive safety behaviours,
however, group-level safety climate showed the strongest effect (rcor = 0.47; 95% CI
[0.42, 0.52]).
The current study also examined the effects of three different leadership styles
(transformational, transactional and passive) on proactive safety behaviours.
Transformational leadership was positively related to proactive safety behaviour (rcor
= 0.37; 95% CI [0.30, 0.44]), while transactional was significantly related to proactive
safety behaviours (rcor = 0.22; 95% CI [0.06, 0.38]) but its effect was weaker compared
to transformational leadership. The analysis revealed that passive leadership was
significantly and negatively related to proactive safety behaviours (rcor = -0.23; 95%
CI [-0.31, -0.16]).
Overall, both perceived organisational support (rcor = 0.33; 95% CI [0.25, 0.41])
and trust (rcor = 0.32; 95% CI [0.21, 0.43]) were positively related to proactive safety
behaviours, with similar effect sizes. When aspects of work design were analysed,
work autonomy showed a moderate and positive relationship with proactive safety
behaviours (rcor = 0.44; 95% CI [0.19, 0.69]). The pooled estimate effect was
significant. On the other hand, work demands showed a very low and negative
relationship with proactive safety behaviours (rcor = -0.00; 95% CI [-0.06, 0.14]), and
the effect was not significant.
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 67
4.4.4 Proximal Antecedent
The current meta-analysis revealed positive effect sizes among the extracted
proximal antecedents and proactive safety behaviours. Most effects were significant,
except for prevention focus. Perceived control showed the strongest effect (rcor = 0.75;
95% CI [0.50, 0.99]). However, the strength of the pooled estimate effect size for
perceived control should be interpreted with caution due to the significant Egger’s test.
Safety motivation also showed a strong effect with proactive safety behaviours (rcor =
0.53; 95% CI [0.42, 0.63]) as well as perceived knowledge and skills (rcor = 0.64; 95%
CI [0.57, 0.71]). Self-efficacy showed a moderate to strong effect size (rcor = 0.42;
95% CI [0.32, 0.53]).
When the differential effect of regulatory focus was analysed, the results
revealed that promotion focus showed a moderate and significant pooled estimate
effect (rcor = 0.38; 95% CI [0.24, 0.51]) while prevention focus showed a very weak
and non-significant effect (rcor = 0.03; 95% CI [-0.12, 0.18]).
4.4.5 Selected Studies Relevant to Work Driving Safety
Out of the 71 empirical studies that were extracted and analysed in the current
meta-analysis, one study explored workplace safety in terms of participating in road
safety practices (Keffane, 2015) and another study examined safety voice using a
sample of urban bus drivers (Tucker et al., 2008). Keffane (2015) examined the role
of safety climate in management of road safety practices using a sample of employees
who drive for work in France. Keffane’s study (2015) utilised established measures
from safety literature which were adapted to suit the work driving context. The path
analysis revealed that safety communication and feedback was the only dimension of
safety climate that demonstrated a significant positive effect on participation in road
safety practices. Other dimensions that were examined (e.g., safety commitment,
safety training) were not significant predictors of safety participation.
While Tucker et al.’s (2008) study did not specifically examine the context of
work driving safety, they looked at safety voice behaviours in bus drivers. They found
that perceived co-worker and organisational support for safety were significant
predictors of employee voice. Bus drivers spoke out more about safety issues when
they perceived that their organisation supported safety and this relationship was
mediated by employees’ perceptions of their co-workers’ supporting workplace safety.
68 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
Co-workers support for workplace safety also showed a stronger effect on drivers’
safety voice compared to organisation-level support for safety.
4.5 DISCUSSION
Utilising Curcuruto and Griffin’s (2017) model of safety proactivity, the current
study undertook a meta-analytic investigation of factors that facilitate and inhibit
proactive safety behaviours. Specifically, it examined the contextual antecedents (i.e.,
safety climate, leadership, perceived organisational support, trust, work autonomy and
work demands) and proximal antecedents (safety knowledge, safety motivation, self-
efficacy, perceived control and regulatory focus) of proactive safety behaviours. The
purpose of the current review was to inform the development of a research model of
proactive safety behaviour that would be applied within the work driving context
(which is detailed in Chapter 6).
The present study has a number of theoretical implications. First, the current
meta-analysis further confirms the relationship between safety climate and proactive
safety behaviour. This finding is in line with previous reviews that have also
demonstrated that a positive safety climate is associated with higher levels of active
participation in workplace safety practices (Christian et al., 2009; Clarke, 2006).
Employees’ perceptions of their workplace safety climate influence their behaviour.
Therefore, in a positive safety climate, employees are encouraged to proactively
participate in safety activities and are likely to suggest safety initiatives within the
workplace.
Didla, Mearn and Flin (2007) argued that when a work environment place
emphasis on safety over production and the importance of safety values are
incorporated in all levels of the organisation (e.g., top-level, sub-units), employees are
encouraged to take more initiatives in ensuring workplace safety. The current study
extended the literature by segregating the different levels of safety climate (i.e.,
psychological-level, group-level or organisation-level) and their influence on
proactive safety behaviours. The current findings clearly demonstrated that, when the
shared perception of safety is analysed within the work-group or direct supervisor level
(i.e., group-level), the effect of safety climate on proactive safety behaviours were
stronger compared to shared perception of safety among the top organisational level.
The current meta-analysis provides further evidence to the multi-level nature of safety
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 69
climate (Zohar, 2008; Zohar & Luria, 2005) and that supervisors’ safety practices may
have a stronger impact on employees’ initiatives to promote safety at work.
In regards to the effect of leadership styles, the current meta-analysis revealed
that transformational leadership has a moderate and positive relationship with
proactive safety behaviours while transactional leadership showed a positive but
weaker effect. On the other hand, passive leadership demonstrated a negative effect on
proactive safety behaviours. These findings provide further support that leadership is
an important antecedent to proactive safety behaviours. More specifically,
transformational leadership style has the strongest effect in ensuring proactive safety
behaviours in the workplace out of the three leadership styles. This finding is inline
with previous reviews (Clarke, 2006, 2013a).
The current meta-analysis also provided further support on the distinctiveness
between the three types of leadership and the differential effects that they have on
proactive safety behaviours. It can be argued that although transactional leadership
style was associated with a smaller effect on proactive safety behaviours compared to
transformational leadership, its significant positive effect suggests that transactional
leadership is still a critical factor in safety promotion initiatives in the workplace –
providing that the leader is active (e.g., one who monitors and provides feedback on
errors). The current meta-analysis extends previous reviews on leadership and safety
behaviours, by demonstrating that passive leadership showed a negative effect on
proactive safety behaviours. It is possible that previous studies that found a weak effect
between transactional leadership and safety behaviours (e.g., Kark, Katz-Navon, &
Delegach, 2015) did not differentiate active transactional leaders from passive leaders.
The current findings further clarified that active transactional leaders still play a
positive role in employees’ proactive safety behaviours. However, the passive
leadership style may actually have detrimental effects on workers’ safety behaviours,
with employees having diminished proactivity towards safety.
Furthermore, the current meta-analysis demonstrated that perceived
organisational support, organisational trust and work autonomy have moderate and
positive effects on proactive safety behaviours. While there is currently limited
research on these concepts and their impact on occupational safety, emerging evidence
suggests that individuals must feel supported within their workplace, must trust their
organisations, and must feel autonomous regarding their work in order to be proactive
70 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
towards occupational safety (e.g., Mearns et al., 2008; Parker et al., 2001; Turner et
al., 2005; Zacharatos et al., 2005). Having a supportive environment could create a
sense of group cohesion within the workplace and contribute to employees ‘feeling
safe’ to take safety initiatives at work (Geller et al., 1996). Furthermore, being
supported at work could encourage employees to care about the wellbeing and safety
of their co-workers and may encourage their engagement in safety behaviours that
ensure the safety of their co-workers, even when it is not expected (Burt, Sepie, &
McFadden, 2008; Geller et al., 1996). Organisational trust, on the other hand, could
foster open communication and enhanced cooperation, which could then encourage
employees to engage in proactive safety behaviours (Conchie & Donald, 2008;
Conchie et al., 2006).
The results also revealed that work autonomy is a critical factor for employees’
proactive safety behaviours. Among the contextual antecedents, work autonomy had
the highest meta-analytic effect on proactive safety behaviours. Curcuruto and Griffin
(2017) argued that employees with higher autonomy may present more opportunities
and motivation to get involved in safety tasks that fall outside their job description.
This could explain the high meta-analytic effect found in the current study. On the
other hand, work demands showed a non-significant effect on proactive safety
behaviours. It is possible that the finding is due to the majority of the studies showing
very low correlations between work demands and proactive safety behaviours.
Employees may feel overwhelmed by the demands they experienced at work and, as
such, they are not motivated or have less energy, to take safety initiatives at work
(Sampson, DeArmond, & Chen, 2014).
Within the proximal antecedents, the current meta-analysis provided further
evidence that safety knowledge and safety motivation are critical proximal antecedents
to proactive safety behaviours. However, the study has also extended current
knowledge by demonstrating that self-efficacy, perceived control and promotion focus
can also act as additional proximal antecedents to proactive safety behaviours. The
previous meta-analysis by Christian et al. (2009) showed that employees need to be
motivated and have the knowledge to engage in proactive behaviours but the current
review extended the literature by demonstrating that having high self-efficacy and
perceived control and being promotion focused also encourage individuals to engage
in such behaviours. Perceived control showed the strongest pooled correlation estimate
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 71
on proactive safety behaviours, however, due to the significant publication bias test,
this meta-analytic strength should be interpreted with caution.
The findings of the current study also extended Curcuruto and Griffin’s (2017)
safety proactivity model by providing meta-analytic evidence on their proposed
antecedents of proactive safety behaviours. In addition, the effect sizes of the proximal
antecedents generally showed higher pooled correlation strengths with proactive safety
behaviours compared to the contextual antecedents. This observation gave further
evidence to the suitability of the variables’ groupings within the distal and proximal
categories and the relative ‘distance’ of effect of the antecedents to the outcome
variable as proposed by the model. Furthermore, Curcuruto and Griffin (2017) have
argued that safety knowledge is a distal antecedent of safety proactivity. However, the
high correlation found between safety knowledge and proactive safety behaviours in
the current study showed that it is possible that safety knowledge may act as a proximal
antecedent to proactive safety behaviours.
4.5.1 Practical Implications
The findings of the current meta-analysis provide practical value to
organisations. Specifically, the findings demonstrate that various organisational
antecedents have significant influences on one’s engagement with proactive safety
behaviours. Organisations are in the position to make changes within the workplace in
order to provide a space for their employees to feel safe in engaging in such
behaviours. The specific focus on organisational antecedents demonstrate that while a
selection process could distinguish workers who may have a disposition to act in a
proactive manner (e.g., promotion-focused), they can also be trained and encouraged
to take safety initiatives by cultivating a positive safety climate, supportive and caring
workplace, and designing a workplace that fosters autonomy.
The current review also highlighted that while safety climate is a critical factor
for safety proactivity, a variation exists depending on which level of safety climate is
being examined. The differentiation between the levels of safety climate allows for
more specific feedback to relevant parties (Zohar, 2005). In other words, by
distinguishing the levels of safety climate, organisations could have a specific focus
on which level to target for intervention. The current findings demonstrated that while
organisational-level safety climate is still a critical factor of proactive safety
behaviours, group-level safety climate is of particular importance as direct supervisors
72 Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours
and work groups may have more influence on proactive safety behaviours compared
to company-level safety procedures and policies. For instance, while Huang et al.
(2013) did not specifically studied proactive safety behaviours in work drivers, they
found that group-level safety climate has a stronger relationship with near-miss
incident reporting compared to organisational-level safety climate.
The current study also highlighted the different leadership styles that are critical
in encouraging proactive safety behaviours. A particularly unique contribution of this
study is demonstrating that having a passive leadership style could have a detrimental
impact on these behaviours. Therefore, leaders should take particular consideration of
not taking a passive approach when managing workers, as employees may be less
likely to be proactive towards workplace safety.
4.5.2 Limitations and Future Directions
Although the current meta-analysis may inform theory and practice, it is
important to mention its limitations. The measurement of proactive safety behaviours
was exclusively carried out with self-report measures and the majority were cross-
sectional studies. The use of self-report measures could introduce potential method
bias (Lindell & Whitney, 2001; Podsakoff, MacKenzie, Lee, & Podsakoff, 2003).
Furthermore, there is a limited number of peer-reviewed literature focused on work
driving safety, particularly on the topic of proactive safety behaviours. This limitation
prevented a comprehensive review of proactive safety behaviours within the context
of work driving.
Due to the small number of studies that both concurrently examined the
contextual and proximal antecedents within the same study, the current meta-analysis
could also not test a path analysis to model the extracted variables in order to determine
the possible mediating effects of the proximal antecedents. Future studies could apply
path modelling when more research becomes available on the topic of proactive safety
behaviours. The path analysis could further investigate the direction of the relationship
between the distal and proximal antecedents.
4.5.3 Chapter Summary and Key Learnings
The current chapter critically synthesised the contextual and proximal
antecedents of proactive safety behaviours and its related constructs. The review
specifically focused on safety climate, organisation-based social exchange and
Chapter 4: Meta-analytic Review of Contextual and Proximal Antecedents to Proactive Safety Behaviours 73
interpersonal processes, and work design as contextual antecedents of proactive safety
behaviours while safety knowledge, regulatory focus, self-efficacy and perceived
control were considered as the proximal antecedents. The meta-analytic component of
the review extended upon Curcuruto and Griffin’s (2017) literature review on safety
proactivity and proposed model of safety proactivity. While Curcuruto and Griffin
(2017) provided a comprehensive account of the antecedents associated with safety
proactivity, the meta-analytic calculations allowed the pooling of available
quantitative data from individual studies for a more precise estimate of the effect size
of each relationship (Schmidt & Hunter, 2014). The current review was utilised to
inform the development of a research model of proactive safety behaviour that would
be applied within the work driving context.
74 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
5.1 INTRODUCTORY STATEMENT
The previous chapter discussed the terminologies, measures and concepts that
relate to proactive safety behaviours. Proactive safety behaviour is established as a
leading indicator of safety performance within the general OHS literature. However,
this concept is not yet examined within the work driving research despite several
researchers already indicating that this is an important concept to apply within the
work driving field (Otto et al., 2014; Newnam, et al., 2014; Wishart et al., 2019).
Furthermore, previous research on proactive safety behaviours (e.g., Curcuruto and
Griffin, 2016; Curcuruto et al., 2016) does not consider the unique challenges that
involved in work-related driving tasks (e.g., working alone, not being consistently
monitored by supervisors).
Within the OHS field, several measures exist that assess employees’ engagement
with proactive safety behaviours. However, as mentioned in the previous chapters,
most of these measures are unidimensional. Aside from Hoffman et al.’s (2003)
measure of safety citizenship, proactive safety behaviours are usually measured using
Neal and Griffin’s (2003) measure of safety participation which utilises 3 items. Other
versions of this survey include more items (e.g., Zacharantos et al., Subramaniam et
al., 2016) but these measures are still unidimensional in nature.
Similar concepts to proactive safety behaviours had been studied within the field
of road safety (e.g., traffic safety citizenship; Finley et al., 2015), as discussed in
Chapter 2. However, these studies only examined stewardship-type behaviours of
intervening when a driver is conducting an unsafe behaviour (e.g., using mobile phone
while driving or not wearing a seat belt; Buckley et al., 2009; Otto et al., 2016).
Thus, a research gap exists. There is a need to develop a measure that is specific
to the context of work driving as there might be certain elements within work driving
itself that may impact one’s proactivity to be safe. For instance, Newnam et al. (2011)
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 75
developed the driving behaviour questionnaire scale within the occupational context
(O-DBQ) based on the commonly used general driving behaviour questionnaire
(DBQ). Newnam et al. (2011) argued that a specific scale was critical due to the
context of the workplace environment and its potential impact on employees’ driving
behaviours. They further argued that the scale could help in identifying unsafe driving
behaviours that are specific to the workplace context and could help organisations
monitor safe driving practices among their employees. Once the scale was developed,
Newnam and VonSchuckmann (2012) compared the predictive value of safety climate
and role overload between O-DBQ and DBQ and found that the organisational factors
accounted for a greater variance in the specifically tailored questionnaire compared to
the general DBQ.
Based on the similar premise, the current research program developed a measure
of proactive safety behaviours within the context of work driving (PSB-WD) to
consider the specific elements that are inherent in driving for work. For instance, it
was decided that items such as “trying to improve safety procedures” from Hofmann
et al.'s (2003) measure of safety citizenship should be altered to include “work driving
safety procedures” to indicate that the item specifically measures work driving safety.
Doing so improved the conceptual clarity and relevance of these items to suit the work
driving context rather than general occupational safety behaviours. It was also decided
that several items should be added to suit the scale within the work driving context.
For example, items specific to taking initiative with vehicle maintenance were added
to the measure to investigate proactive work driving practices.
The current chapter details the three studies that were conducted to develop a
multi-dimensional PSB-WD scale. This chapter has two sections: 1) the methods,
results, and discussion of Study 2a and 2b, which represents the scale development
and initial testing of the dimensionality of the scale, and 2) the methods, results, and
discussion of Study 2c which represents further testing of the scale. Table 5.1 shows
the overview of the current chapter. These studies aim to answer the second research
question: “What are the proactive safety behaviours that work drivers perform to
ensure and improve safety (and that of their co-workers) while driving for work?”
76 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
Table 5.1 Chapter section, phases, methodology and purposes of Study 2a, 2b and 2c
Chapter Section
Phase Method and Sample Purpose
Section 1: Scale development and initial testing of the scale dimensionality and reliability
Phase 1a: Item generation
(Study 2a)
Literature review
Research Team (N = 3)
Process akin to Group Nominal Technique
Generate an item pool for the survey
Phase 1b: Expert Panel
(Study 2a)
Expert Panel Survey
Sample of work drivers’ supervisors and managers and road safety experts (N = 5)
Assessment of content validity and clarity
Phase 2: Pilot testing of the items
(Study 2b)
Pilot Testing Survey; Principal Component Analysis
Sample of work drivers (N = 43)
Assessment of dimensionality and reliability, as well as item reduction
Section 2: Further scale testing
Phase 3: Testing of Survey Validity
(Study 2c)
Main Survey – Part A
Exploratory Factor Analysis
Confirmatory Factor Analysis (N = 300)
Further assessment of dimensionality and reliability, as well as construct validity, convergent validity and discriminant validity
5.2 PURPOSE OF THE STUDY
Careful consideration of specific aspects of work driving safety were taken into
account during the development process. A rigorous process was conducted to ensure
that the newly developed scale captured a variety of proactive safety behaviour
dimensions within the work driving context and to develop a psychometrically sound
scale. The following section details that process that was taken to develop, pilot and
validate a new measurement tool for proactive safety behaviours within the work
driving context. The procedure followed Hinkin’s (1998) and DeVellis (2016)
approaches to scale development.
5.3 METHOD AND RESULTS OF STUDY 2A – ITEM GENERATION AND EXPERT PANEL
According to Hinkin (1998), scale development typically follows two
approaches: deductive development and inductive development. In the deductive
approach, the theory informs the development of the scale (top-down). This approach
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 77
requires a thorough and extensive understanding of the phenomenon being studied in
order to inform the initial generation of the survey items (Hinkin, 1998). The inductive
scale development, on the other hand, does not follow a theoretical foundation and
requires researchers to use qualitative approaches in order to generate items for the
survey (Hinkin, 1998). For the current research, the deductive approach was utilised
due to the existing knowledge on proactive safety behaviours. The findings from the
literature review of the theoretical construct and assisted with the item generation.
Item Pool Generation
A literature review was conducted to inform the development of the theoretical
construct and to assist in developing the items for the survey. Part of this literature
review is evident in Chapter 2 of the thesis, which detailed the concepts, terminologies,
definitions and measures related to proactive safety behaviours. Various databases
were utilised to search for relevant literature and measures of safety citizenship, safety
participation, extra-role safety behaviours and safety proactivity. Other measures of
work contextual performance, organisational citizenship behaviours and work
proactivity were also reviewed due to the constructs origins in organisational
psychology research.
Items from existing measures were collected and reviewed (e.g., Geller et al.,
1996; Hofmann et al., 2003; Mearns & Reader, 2008; Neal et al., 2000; Parker &
Wang, 2015; Simard & Marchand, 1994; Willis, Brown, & Prussia, 2012). A total of
84 items were generated with 70 items derived from existing measures that were
modified to suit the work driving context and 14 items were originally developed.
Since the construct of proactive safety behaviour is multi-dimensional in nature,
the candidate, along with her supervisory team, utilised the Nominal Group
Technique15 to rank, revise, remove and categorise the pooled items into possible
dimensions of proactive safety behaviours. The research team were provided their own
15 Nominal Group Technique is a strategy used when a group is involved in a process of problem identification solution generation and decision making (Delbecq, Van de Ven, & Gustafson, 1975). When utilising this technique, group members provide their view of the solution with a short explanation. When duplicate solutions exist, these solutions are moved to the next phase of the solution generation and the members proceed to rank the remaining solutions (Delbecq et al., 1975). This technique encourages participation from all group members and results in a prioritised solution that represent the group’s preferences.
78 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
copies of the item pool and were given the task of assigning sub-dimensions for each
item, which included: whistle-blowing, stewardship, voice, improving safety,
problem-prevention, monitoring, feedback inquiry, taking charge, and safety civic
virtue. The dimensions were mostly based on Hofmann et al.’s (2003) research on
safety citizenship behaviours and dimensions of proactivity by Parker and colleagues
(Parker & Collins, 2010; Parker & Wang, 2015). Each researcher was also told to rank
the items from 0 (do not include) to 5 (include). Researchers were encouraged to
modify the item to improve its clarity and they were also encouraged to offer any
comments on each item.
If the research team could not provide a suitable category, they were instructed
to provide a new category for the item. If a disagreement between items occurred
(regarding the ranking or category), the research team had to provide reasons for their
ranking and assigned categories. Reasons for item modifications were also provided.
Disagreement in ranking and categories were discussed until consensus were reached
between the team members. For example, one of the team members suggested that
whistle-blowing may have harmful connotations as it may suggest aggressive
behaviours. All researchers agreed and this category was changed to voice, which was
considered as denoting a more neutral tone.
From this process, it was identified that proactive safety behaviours in the work
driving context could involve six key behavioural indicators, which are detailed below:
Problem prevention – acting to prevent the re-occurrence of challenges and
barriers to safety while driving for work.
Stewardship – helping co-workers to ensure their safety while driving for
work.
Voice – speaking up when employees have work driving safety concerns.
Helping / Volunteerism – volunteering to carry out activities that are not
formally part of their job as well as helping and cooperating with others to
ensure the safety of other employees while driving for work.
Feedback inquiry – explicit verbal requests for feedback regarding the
employees’ safety behaviours while driving for work.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 79
Changing organisation’s policies and procedures – Taking one’s initiative
to change the organisational policies and procedures with an aim to
improve the safety of work drivers.
From the initial 84 items, 47 items remained in the item pool, with 5 items for
feedback inquiry, 5 items for volunteerism, 13 items for problem prevention, 10 items
for stewardship and 5 items for voice and 9 items for changing organisation's policies
and procedures. The 47 items were reviewed by the candidate and the supervisory team
to ensure the clarity of the items, and that they were not repetitive and thus distinct to
its assigned category. The scaling method used for this survey was a 5-point Likert
type scale ranging from 1 (never) to 5 (always) to determine the likelihood that work
drivers would perform these behaviours. This scaling method was utilised as it has
been employed in other surveys within the work driving settings (e.g., Newnam et al.,
2012).
Expert Panel
After developing the items for the survey, experts in fleet safety and occupational
safety research, as well as managers and supervisors of work drivers, were approached
to take part in an expert panel. The panel members were required to have either, a)
experience in managing fleets or supervising work drivers, or b) have experience in
research regarding work driving safety and occupational safety research. Potential
panel members were recruited from the professional network of the external supervisor
(Darren Wishart). An anonymous survey was developed using Qualtrics (a survey
management website) and links were sent via email. Online recruitment was preferred
due to the geographic dispersion of the potential panel members. Fifteen participants
were approached to participate and five participants completed the anonymous survey
online to examine the survey items (33.3% response rate).
The items were checked for the clarity of wording 1 (not clear) to 5 (very clear)
and content 1 (low content validity) to 5 (high content validity). Experts were also
requested to provide comments on each item and a general comment regarding the
dimensions. These comments were considered and changes were applied to the
existing items (e.g., minor changes in wording and sentence structure). See Appendix
B for the survey used.
80 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
Most items received good ratings of content validity and clarity. Due to the very
small sample size (n = 5), descriptives statistics were only conducted on the rating
scores. Items were either deleted or further modified if the content validity and clarity
ratings were very low. Some experts suggested that some behaviours within the item
pool were not possible for work drivers to carry out without approval from supervisors.
For example, for the item “I volunteer to conduct journey planning”, several experts
commented that work drivers need approval from their supervisors to conduct journey
planning and therefore, it was not applicable for work drivers. These items were
subsequently deleted.
Some experts also provided comments to improve the items. For example, a
expert commented that one of the items may seem aggressive due to the use of the
word “confront”. Therefore, some items were revised to reflect the comments provided
by the experts. From this process, five items were deleted and six items were revised:
Items Deleted:
I try to change the way the job is done so that I feel safe when driving for work
I volunteer to conduct work driving risk assessments
I volunteer to conduct journey planning
I try to prevent other drivers from being injured on the job
I resolve potential safety issues that relate to driving for work
I try to implement solutions to solve urgent work driving safety issue
Items Revised (added or edited phrases or words are italicised):
“I actively seek feedback about my work driving” to “I actively seek feedback
from my co-workers and passengers about my work driving”
“When I experience a traffic incident or receive a traffic offence when driving
for work, I initiate a conversation with people at work” to “When I experience
a traffic incident or receive a traffic offence when driving for work, I initiate
the conversation to learn from my mistakes”
“I get involved in work driving safety programs and activities even if it is
outside my responsibilities” to “I get involved in work driving safety programs
and activities to help other workers drive safely”
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 81
“I confront other co-workers about their unsafe behaviours while driving for
work” to “I would intervene if I see a co-worker doing something unsafe while
driving for work”
“I warn other co-workers about the dangers of driving unsafely” to “I
encourage my co-workers to think about the dangers of driving unsafely”
“I inform new drivers that violations of safety procedures will not be tolerated”
to “I inform other drivers that violations of safety procedures will have
negative consequences”
A total of 42 items remained. Due to the anonymity of the survey, the expert
panel did not have the opportunity to review the final items. However, these items
went further testing. The items were piloted using a sample of work drivers to
determine its factorability and, in the attempt to further reduce the number of the items.
The results of the pilot study are outlined in the following section.
5.4 METHOD AND RESULTS OF STUDY 2B – PILOT STUDY
Method
To establish the validity and reliability of the newly developed measure of
proactive safety behaviour within the work driving context, the questionnaire was
piloted with a State Government organisation that manages vehicle fleets. Data was
collected online using the Qualtrics survey platform. The link to the survey was sent
to the email of the organisation contact. Initially, 67 participants started the survey but
only 43 participants fully completed the study. Two participants indicated that they
were not eligible for the study, four participants stopped at the 3rd question and the
remainder of the incomplete data ranged from 2% to 87% completion. It is likely that
the length of the survey may have deterred the participants. The following results only
report data from the completed surveys based on N = 43 respondents. See Appendix C
and D for the participant information sheet and survey used for the pilot study.
Results
Participant Demographics and Work Driving Exposure
The majority of respondents were male (n = 23; 53.5%), aged 40 years and above
(n = 30; 69.2%) and had been employed by the company for more than 7 years (59.5%).
More than half (64.9%) of participants reported having held their driving licence for
more than 20 years. The majority of participants in the sample reported driving for
82 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
work between 1 to 10 hours per week (n = 38; 88.4%) and was driving up to 10,000
kilometres per year (n = 35; 81.4%).
Principal Component Analysis
A series of principal component analyses (PCA) was conducted to determine the
factor structure of the survey and identify poor performing (e.g., cross loading) items.
PCA is a technique used for reducing items and assessing possible dimensionality to
increase the measures interpretability but also minimising information loss (Jolliffe &
Cadima, 2016).
There were 42 items in the PSB-WD survey during the pilot study and 43
participants. A review on current developments in PCA technique demonstrated that
in studies that apply PCA with small sample sizes, especially in cases were n < p
(where n denotes the sample size and p denotes the number of variables or items), PCA
is still possible (Jolliffe & Cadima, 2016).
Furthermore, a Varimax rotation was applied because orthogonal rotations are
more desirable as they simplify the applied criteria and make the rotated factors easier
to interpret (Jolliffe & Cadima, 2016). On the other hand, non-orthogonal rotations
assume that factors are correlated but minimise factor loadings (Jolliffe & Cadima,
2016). Varimax is the most popular orthogonal rotation technique and commonly used
in social sciences (Jolliffe & Cadima, 2016). Even though previous literature suggests
that dimensions of proactive safety behaviours were correlated (e.g., Curcuruto,
Conchie, Mariani, & Violante, 2015), an orthogonal rotation was chosen over non-
orthogonal for ease of interpretation of the factors. The current study was only an initial
pilot-testing of the items and, therefore, the ability to interpret the factors was essential.
Next, the Bartlett’s test of Sphericity and Kaiser–Meyer–Olkin (KMO) Measure
of Sampling Adequacy were assessed to determine whether sufficiently large
relationships existed within the sample data to perform PCA and the subsequent
Exploratory Factor Analysis (EFA) in Study 2c (Howard, 2016). Bartlett’s test of
sphericity evaluates whether the sample’s correlation matrix is an identity matrix –
identity matrix indicates that the variables are unrelated and, therefore, not suitable for
structure detection (Howard, 2016). Given that PCA determines the variables’
relationships, a lack of correlations within the observed data prevents the PCA from
being performed (Howard, 2016). A significant Bartlett’s test of sphericity indicates
that the observed data is not an identity matrix and that PCA is appropriate.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 83
However, several researchers have noted that the Bartlett’s test of sphericity is
usually significant as virtually most datasets are significantly different from an identity
matrix (Howard, 2016). Therefore, KMO Measure of Sampling Adequacy is usually
interpreted alongside Bartlett’s test of sphericity. KMO Measure of Sampling
Adequacy evaluates whether the proportion of variance within the observed data may
indicate latent factors. High values (close to 1) indicate higher inter-correlations within
the variables and values less than 0.50 are usually indicative that the EFA is not
suitable for the observed dataset.
For the initial PCA, a significant Bartlett’s test (2 (561) = 1535.30, p < .001)
was found and the KMO test of sampling adequacy was .38. While the KMO test of
sample adequacy was poor, the significant Bartlett’s test of sphericity suggested that
there may be significant inter-relationships between the variables and thus that the
factor model was appropriate (Hair, William, Babin, & Anderson, 2010; Tabachnick
& Fidell, 2007). The items for ‘volunteerism’ and the items for ‘changing of
organisational policies and procedures’ seemed to be converging into a single factor
structure. The research team decided to remove the items that had been created for
‘changing of organisational policies and procedure’ given that this factor may be more
likely to act as a higher factor structure that encompasses other sub-factors.
Initially, 8 factors were extracted from the initial PCA. After the removal of the
‘changing of organisational policies and procedure’ factor, items were deleted one by
one, removing highly-correlated items, high cross-loadings and low communalities.
Items were retained if they had strong factor loadings, small cross-loadings across all
factor structures and if the item provided a meaningful and useful contribution within
the factor. The final factor analysis still demonstrated 8 components with an
Eigenvalue of >1 (See Table 5.2). The KMO was .67, which is acceptable, and the
Bartlett’s test of sphericity was significant, 2 (325) = 1112.03, p < .001.
84 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
Table 5.2 Final PCA for the Pilot Study Survey PSB-WD
FACTOR LOADINGS
ITEM CODE
ITEM STATEMENT 1 2 3 4 5 6 7 8
Factor 1 – Helping / Volunteerism (4 items)
H/V5 I volunteer to help other drivers with their work safety driving responsibilities.
0.93
H/V4 I volunteer to help other workers learn more about safe work driving practices.
0.91
H/V3 I get involved in work driving safety programs and activities to help other workers drive safely.
0.86
H/V 1 I volunteer to educate work driving safety procedures to new drivers.
0.80
Factor 2 - Protecting Other Drivers and Fixing Safety Issues Outside of Responsibility (4 items)
S8 I go out of my way to look out for the safety of other drivers
0.85
S9 I take action to protect other drivers from risky situations.
0.84
PP6 If I see something unsafe, I go out of my way to take care of it.
0.72
PP7 I fix safety issues that relates to work driving even if it is not my responsibility.
0.60 0.45
Factor 3 - Intervening Other Drivers and Problem Prevention (5 items)
S3 I would intervene to stop safety violations of other drivers.
0.78
S2 I would intervene if I see a co-worker doing something unsafe while driving for work.
0.77 0.40
PP1 When driving for work, I plan extra journey time and breaks for bad weather, traffic congestion, etc.
0.75
PP3 I resolve problems in ways that reduce the risks associated with driving for work.
0.58 0.49
S1
If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I talk to them about the hazards of their risky behaviours.
0.43 0.54
Factor 4 - Voice (3 items)
V4 I speak up on work driving safety matters even if others might disagree.
0.88
V5 I communicate my views about work driving safety issue, even if others would disagree.
0.84
V3 I speak up about safety concerns during team meetings or toolbox talks.
0.81
Factor 5 - Vehicle Maintenance (2 items)
PP8 If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisors or completing paperwork.
0.90
PP9 When I see a vehicle that needs maintenance, I inform my supervisors or the appropriate person about it.
0.89
Factor 6 – Sharing Knowledge to Other Drivers (3 items)
S6 I encourage other drivers to follow safe work driving procedures.
0.85
S7 I encourage new drivers to follow safe working procedures.
0.40 0.78
S5 I inform other drivers that violations of safety procedures will have negative consequences.
0.76
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 85
FACTOR LOADINGS
ITEM CODE
ITEM STATEMENT 1 2 3 4 5 6 7 8
Factor 7 - Feedback Inquiry (3 items)
FI1 I actively seek feedback from my supervisor about my work driving.
0.87
FI2 I actively seek feedback from my co-workers and passengers about my work driving.
0.86
FI3 I actively seek feedback about my work driving with people at work.
0.76
Factor 8 - Fixing Safety Issues (2 items)
PP4 I implement solutions to solve safety issues that relate to driving for work.
0.87
PP5 When I see a potential work driving safety hazard, I do my best to fix it.
0.50 0.56
Total Variance Extracted 35.8 12.9 9.7 7.6 6.3 5.1 4.8 3.9
Internal Reliabilities .95 .89 .81 .95 .98 .94 .80 .74
Notes. Extraction Method: Principal Component Analysis; Rotation Method: Varimax with Kaiser Normalisation; Rotation converged in 13 iterations; N = 43. H/V = Helping/Volunteer Items; PP = Problem Prevention Items; FI = Feedback Inquiry; Stewardship; V = Voice.
As shown in Table 5.2, all extracted factors had reliability scores above
Cronbach’s α of 0.70, which is an acceptable measure for a scale’s internal consistency
(Kline, 2000). Cumulatively, the overall factor structure accounted for 86.1% of the
total variance. However, the results revealed that some items still loaded highly across
more than one factor. In order to maintain a minimum of three items per factor, these
items were still retained but were later modified to more clearly represent their primary
factor (Hinkin, 1998).
It was also noted that some of the factor structure seemed to represent two
different sub-factors. For instance, the items in Factor 2 seemed to represent
“Protecting Other Drivers” and “Fixing Safety Issues Outside of Responsibility” while
Factor 3 seemed to represent “Intervening Other Drivers” and “Problem Prevention”.
These factors were considered as representing two different categories of proactive
safety behaviours.
In order to maintain at least three items per factor (to maximise reliability),
several additional items were written for factors that had less than three items. Another
item that represented protecting other drivers was added as well as an item reflecting
fixing safety issues outside of one’s responsibility. Similarly, another item was
developed for Factor 5 (Vehicle Maintenance). In addition, the items for the remaining
volunteering dimension were further revised to denote a more proactive stance on the
behaviour. More specifically, instead of “I volunteer…”, the items were revised to: “I
86 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
go out of my way…” The following table presents the revised and additional items to
the survey.
Table 5.3 Revised and added items
Revised Items
If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I talk to them about the hazards of their risky behaviours. Revised to: If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I would intervene. I resolve problems in ways that reduce the risks associated with driving for work.
Revised to: When I experience safety issues while driving for work, I resolve these problems. When I see a potential work driving safety hazard, I do my best to fix it. Revised to: When I see a potential safety hazard while driving for work, I resolve it by finding a solution. Helping/Volunteer items were revised to: I go out of my way to educate new employees about work driving safety procedures. I go above my duties to help other drivers with their work driving safety responsibilities. I go out of my way to help other drivers learn more about safe work driving practices. I go above my duties to help my co-workers drive safely.
Additional Items
I go above my duties to resolve driving safety issues at work for Fixing Safety Issues I make sure that vehicle defects are attended to quickly for Vehicle Maintenance I look after the safety of other drivers in my organisation for Stewardship Protection
5.5 SUMMARY OF STUDY 2A AND 2B
Study 2a and 2b presented the scale development process for the PSB-WD
measure. Study 2a involved the item pool generation and expert panel review of the
items, while Study 2b involved the pilot testing of the measure. From the item
generation phase, the process generated 84 items that were reduced to 47 items using
the Nominal Group Technique decision process applied by the research team. The
generated item pool was categorised into six dimensions of proactive safety behaviours
within the work driving context, namely: feedback inquiry, helping/volunteerism,
problem prevention, stewardship, voice and changing organisational policies and
procedures. Then, an expert panel was consulted to further review and give feedback
on the items. From this process, the measure was further reduced to 42 items (with six
revised items).
Although the pilot study had a small sample size and the results from the PCA
should be interpreted cautiously, the findings were able to provide important insights
into the dimensionality and reliability of the PSB-WD scale as well as potential
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 87
improvements. It was hypothesised that the proactive safety behaviours scale within
the work driving context (PSB-WD) may have six factors (see Figure 5.1). The results
from the initial PCA indicated that changing of organisational policies and procedures
may be indicating a higher-order factor and, therefore, this dimension was removed
from subsequent PCA. The final PCA suggested that, generally, most items remained
within the hypothesised factors. For instance, the items developed for
volunteerism/helping, voice and feedback inquiry were originally written for these
factors.
However, the findings from the pilot study also revealed that some of the
extracted factors could be further divided into sub-dimensions. In particular, it is
possible that problem prevention could be divided into fixing responsibilities and
vehicle maintenance, while stewardship could be divided into protection, intervention
and knowledge-sharing. Several new items were developed to ensure that all
hypothesised sub-factors had three items, as recommended by Bollen (1989, p. 244),
so as to ensure stability of each factor. Therefore, the revised PSB-WD resulting from
Study 2 had 29 items. The following section will discuss the evaluation of the validity
of the factors and the overall measure.
PSB-WD
Study 2b
Feedback Inquiry
Helping / Volunteerism
Problem Prevention
Fixing safety issues
Fixing safety issues outside of
responsibility
Vehicle maintenance
Stewardship
Protection
Intervene
Sharing KnowledgeVoice
PSB-WD
Study 2a
Feedback Inquiry
Helping / Volunteerism
Problem Prevention
Stewardship
Voice
Changing of organisations policies
and procedures
Figure 5.1 Hypothesised dimensions of proactive safety behaviours within the work driving context (PSB-WD; left) and the dimensions extracted from PCA using the pilot study data (right).
88 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
5.6 METHOD AND RESULTS OF STUDY 2C
5.6.1 Method
Study 2c was conducted to further assess the dimensionality of the PSB-WD
scale, as well as further assess its reliability and validity. An online survey was
primarily used to access a wider range of employees who drive for work. Potential
participants for Study 2c were informed that the current study was interested in
understanding the proactive behaviours that work drivers and their supervisors perform
to ensure employees’ safety while driving for work. The anonymous questionnaire,
developed using Qualtrics, took 25 to 30 minutes to complete. The recruitment
methods included: convenience sampling via snowballing, a social media campaign
via Facebook, accessing members of various fleet management associations (where
members manage small to large vehicle fleets from 10 to 10,000 fleets) and email
advertisements. The online recruitment yielded N = 219 usable surveys (with less than
10% missing data). See Appendix E and F for the participant information sheet and
survey used for Study 2c.
In addition, hardcopies of the survey were distributed during a series of
workshops delivered among work drivers who were employed within the State
Government and the workshops were run by the external supervisor (Darren Wishart).
There were 119 participants who attempted the hardcopy version of the survey.
However, 38 of the hardcopy surveys showed substantial missing data. Therefore, only
81 surveys were used. Input of hardcopy data were validated by a random selection
(30%) of the hardcopy surveys and were crosschecked with the entered data. Data
entries that were found to be inaccurate were subsequently corrected.
To maximise the participation rate, participants who completed the survey had
the chance to go into a random prize draw to win one of ten $100 gift vouchers. After
completing the survey, participants who wanted to be included in the prize draw were
provided with a separate link to enter their personal details so as to keep such details
separate from their survey responses and thus ensured their anonymity.
5.6.2 Results of Study 2c
Overview of Data Analysis
To assess the validity and reliability of the newly developed scale, EFA and
Confirmatory Factor Analysis (CFA) were performed. EFA was conducted in order to
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 89
identify the underlying dimensions among the set of variables and to assess whether
the resulting factors corresponded to the hypothesised dimensions (Hair et al., 2010).
CFA, on the other hand, quantifies the scale validity and the goodness-of-fit of the
resulting model from the EFA (Hair et al., 2010). The goodness-of-fit is the extent to
which the sample data matches the expected values from the hypothesised model. All
data analyses were conducted in IBM SPSS Statistics version 23 and IBM AMOS
version 25.
Assessment of Missing Data
Data analyses were carried out on usable surveys where cases had missing data
on less than 10% of their responses. There were 300 usable cases in the dataset. There
were 219 surveys completed online and 81 on paper.16 As recommended by Hair et al.
(2010), missing data under 10% for individual cases can generally be ignored (p. 55).
From the remaining surveys, analysis of the raw data revealed that there were minimal
missing information across variables (0.3% to 2.0%). the Missing Value Analysis
(MVA) was carried out and the non-significant Little’s MCAR test, χ2 (2353) =
2164.68, p = .997 suggesting that the data were missing completely at random.
Participant Demographics and Work Driving Exposure
Table 5.4 presents the information on the demographic and work characteristics
of the sample. The majority of respondents were work drivers who did not have a
supervision role, had an average age of 36 years (SD = 14.21; Range = 17 to 74), and
who had held their driving licence for an average of 18 years (SD = 14.07; Range =
less than one year to 56 years). The participants had been working within their current
organisation for an average of 7 years (SD = 8.24; Range = 0 to 40 years). More than
half (55.7%) of the participants reported driving for work between 1 to 10 hours per
week and almost half (42.7%) reported to drive between 1 to 10,000 kilometres for
work annually. Most participants reported driving a car, sedan or a wagon type of
vehicle for work (59.7%) and that they drove on asphalt or bitumen roads (84.3%).
The majority of the sample (87%) also reported not having previously been involved
in a crash and 83.3% reported that they had not received a traffic offence in the past
16 EFA for both the online and hardcopy version of the survey were assessed and no significant differences were found regarding factor structures and item loadings for each structure.
90 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
year. However, around 62.3% reported having experienced at least one near-miss in
the past year.
Table 5.4 Demographic and work information of participants
Frequency Percent Data Collection Method Online Survey 219 73.0 Hardcopy Survey 81 27.0 Supervision Role Yes 32 10.7 No 268 89.4 Work driving hours per week 1 – 10 hours 167 55.7 11 – 20 hours 75 25.0 21 – 30 hours 28 9.3 31 – 40 hours 16 5.3 41 – 50 hours 6 2.0 51 – 60 hours 5 1.7 61 hours or more 3 1.0 Annual kilometres driven for work 1 – 10,000 kms 128 42.7 10,001 - 20,000 kms 68 22.7 20,001 - 30,000 kms 38 12.7 30,001 - 40,000 kms 22 7.3 40,001 - 50,000 kms 17 5.7 50,001 - 60,000 kms 10 3.3 60,001 kms or more 17 5.7 Gender Male 148 49.3 Female 152 50.7 Type of vehicle for work Car / Sedan / Wagon 179 59.7 SUV / 4WD 83 27.7 Heavy Vehicle 20 6.7 Other 18 6.0 Type of road Asphalt / Bitumen roads 253 84.3 Dirt roads 3 1.0
Combination of Asphalt / Bitumen roads and Dirt roads
41 13.7
Other 2 0.7 Missing 1 0.3 Self-reported crash in the past 12 months
None 261 87.0 One crash 29 9.7 Two crashes 6 2.0 Three or more crashes 4 1.3 Self-reported near misses in the past 12 months
None 113 37.7 One near-miss 73 24.3 Two near-misses 48 16.0 Three or more near-misses 66 22.0 Self-reported traffic offences in the past 12 months
None 250 83.3 One traffic offence 29 9.7 Two traffic offences 10 3.3 Three or more traffic
offences 11 3.7
Notes. N = 300.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 91
5.6.3 Exploratory Factor Analysis
Assumption Checking
Several assumptions were checked to ensure that the data was suitable for the
factor analysis. First, the current sample size of N = 300 was an appropriate number
for factor analysis, as recommended by several authors such as Hair et al. (2010) and
Tabachnick and Fidell (2007). Next, the Bartlett’s test of Sphericity and Kaiser–
Meyer–Olkin (KMO) Measure of Sampling Adequacy were assessed to determine
whether there were sufficiently large inter-relationships within the sample data to
perform EFA (Howard, 2016).
Factorability of the correlation matrix was also examined. A correlation matrix
should be used in the EFA process to display the relationships between individual
variables. Tabachnick, Fidell, and Osterlind (2007) recommended inspecting the
correlation matrix for correlation coefficients over 0.30. Hair et al. (2010), on the other
hand, suggested that if the loadings of ±0.30 is considered minimal, while ±0.40 is
important and ±.50 is significant.
Initial Exploratory Faction Analysis
For the EFA, a series of Principal Axis Factoring (PAF) analyses was conducted
to determine the factor structure of the scale. While the previous pilot testing of the
survey used an orthogonal rotation to simplify the rotations for the PCA, an oblique
(correlated) rotation was carried out for PAF as it allows the factors to be correlated.
For the current study, Promax Rotation, which is an oblique rotation, was chosen as it
has the advantage of being conceptually simple and offers fast calculations (Lewis-
Beck, Bryman & Liao, 2003). Furthermore, the pilot study that was previously
conducted utilised PCA with a Varimax Rotation. Using Promax allowed for
continuity with previous analysis, given that Promax utilises a target matrix usually
obtained from a Varimax Rotation for the factor rotation (Abdi, 2003).
Examining the items’ correlation matrix, almost all items had significant inter-
item correlations. Only two inter-item correlations were non-significant: volunteer
item 4 with vehicle maintenance item 1, r = 0.06, p = .135 and volunteer item 4 with
vehicle maintenance item 2, r = 0.05, p = .220. All other inter-item correlations were
significant, ranging from r = 0.10 to r = .85. An initial PAF with Promax Rotation was
conducted and factorability of the overall set of variables was assessed. The KMO
measure of sampling adequacy was .93 and a significant Bartlett’s Test of Sphericity,
92 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
2 (406) = 6673.98, p < .001. The large inter-item correlations, the high KMO and
significant Barlett’s Test of Sphericity suggested that the data were suitable for EFA.
Having assessed the assumptions of the EFA and established the suitability of
the observed sample data for the analysis, the 29 item PSB-WD scale was subjected to
a PAF with Promax Rotation. The initial PAF revealed six factors with eigenvalues
exceeding 1, explaining 66.13% of the total variance (See Table 5.5). The
communalities and pattern matrix were examined to assess the factor loadings and to
identify any items that have low communalities and/or which had cross-loadings with
multiple factors. From these examinations, the initial PAF results demonstrated that
there were items with a) low communality (n = 1) and b) high cross-factor loadings (n
= 4). Items with high cross-factor loadings and low communalities were removed and
the factor model was re-specified to improve the simplicity of the factor structure.
Furthermore, inter-item correlations were also assessed for highly correlated items as
it may indicate item redundancy. These items were deleted one-by-one to assess how
the deletion would impact on the overall factor structure.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 93
Table 5.5 Initial PAF with Promax Rotation
FACTOR LOADINGS ITEM CODE ITEM STATEMENT 1 2 3 4 5 6 V 3 I go out of my way to help other drivers learn more about safe work
driving practices. 0.97
V 2 I go above my duties to help other drivers with their work driving safety responsibilities.
0.88
V 4 I go above my duties to help my co-workers drive safely. 0.82
SK 1 I encourage new drivers to follow safe working procedures. 0.82
V 1 I go out of my way to educate new employees about work driving safety procedures.
0.78
SK 3 I encourage other drivers to follow safe working procedures. 0.76
SK 2 I inform other drivers that violations of safety procedures will have negative consequences.
0.57
SP 3 I look after the safety of other drivers in my organisation.e 0.47
SP 1 I take action to protect other drivers from risky situations.b 0.30 0.29 0.24 0.27 -0.20 PP-G 2
I implement solutions to solve safety issues that relate to driving for work.
0.90
FIS 1 I fix safety issues that relate to work driving even if it is not my responsibility.
0.86
PP-G 3
When I see a potential safety hazard while driving for work, I resolve it by finding a solution.
0.79
PP-G 1
When I experience safety issues while driving for work, I resolve these problems.
0.67
FIS 3 I go above my duties to resolve driving safety issues at work.c 0.30 0.67
FIS 2 If I see something unsafe, I go out of my way to take care of it.f 0.54
PP-G 4
When driving for work, I plan extra journey time and breaks for bad weather, traffic congestion, etc.a
-0.26 0.53
SP 2 I go out of my way to look out for the safety of other drivers.d 0.22 0.27 0.25
SI 2 If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I would intervene.
0.98
SI 1 I would intervene if I saw a co-worker doing something unsafe while driving for work.
0.87
SI 3 I would intervene to stop safety violations of other drivers. 0.69
FI 2 I actively seek feedback from my co-workers and passengers about my work driving.
0.91
FI 3 I ask people at work for feedback about my driving. 0.85
FI 1 I actively seek feedback from my supervisor about my work driving. 0.73
VM 2 When I see a vehicle that needs maintenance, I inform my supervisors or the appropriate person about it.
1.00
VM 1 If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisors or completing the paperwork.
0.91
VM 3 I make sure that vehicle defects are attended to quickly. 0.57
V 2 I speak up about work driving safety issues that affect work drivers even if it makes me unpopular.
0.83
V 3 I communicate my views about work driving safety issue, even if others would disagree.
0.69
V 1 I speak up about safety concerns during team meetings or toolbox talks. 0.69 Total Variance Explained 42.45 8.79 4.48 3.95 3.59 2.87 Notes. Extraction Method: Principal Axis Factoring with Promax Rotation; Rotation converged into 7 iterations. a Problem prevention item 4 was deleted due to low communality (.27) b Steward protection item 1 was deleted due to high cross-factor loadings. c Fixing responsibility item 3 was deleted due to high cross-factor loadings. d Steward protection item 2 was deleted due to high cross-factor loadings. e Steward protection item 3 was deleted due to high cross-factor loadings. The initial factor analysis did not show cross-factor loadings, but cross-loadings were visible once the items were deleted one-by-one. f Fixing responsibility item 2 was deleted due to high cross-factor loadings. The initial factor analysis did not show cross-factor loadings, but cross-loadings were visible once the items were deleted one-by-one. SK = Steward Knowledge; V = Volunteer; V = Voice; VM = Vehicle Maintenance; FI = Feedback Inquiry; SI = Steward Intervene; PP = Problem Prevention - General; Fixing Safety Issues = FSI
94 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
The initial PAF showed that Problem Prevention General item 4 had a low
communality score of .27 after rotation. This item was deleted first and the PAF was
re-run. Steward Protection item 1 showed high cross-loadings with multiple factors
and was removed from the analysis. Fixing Safety Issues item 3 also demonstrated
high cross-factor loadings. The initial PAF did not indicate that Steward Protection
item 3 and Fixing Safety Issues item 2 had high-cross factor loadings, but the cross-
loadings were visible on the 4th and 5th re-run of the analysis. All items for Steward
Protection were removed. Overall, 6 items were removed from the EFA procedure.
Final Exploratory Factor Analysis
The final PAF revealed the same 6 factors, with a total of 70.2% variance
explained. Inspection of the item statements for each factor inferred that the first factor
represented “education”, factor two represented “feedback inquiry”, factor three
represented “intervene”, factor four represented vehicle maintenance, factor 5
represented “fixing safety issues” and lastly, factor 6 represented “voice”. Examination
of the Cronbach’s alpha for the internal consistency of the items showed that all factors
were above 0.80 which indicates an acceptable reliability (Kline, 2000) and well above
the minimum acceptable guidelines of 0.70 for newly developed scales (DeVellis,
2016).
Inspection of the factor correlation matrix showed that the strength of the
relationships between the factors was generally medium, ranging between r = 0.25 to
r = 0.68, except for the low correlation between feedback inquiry and vehicle
maintenance (r = 0.13). Thus, using Promax, which is an oblique factor rotation, was
appropriate for the analysis.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 95
Table 5.6 Final PAF with Promax Rotation
FACTOR LOADINGS ITEM CODE ITEM STATEMENT 1 2 3 4 5 6 Factor 1 - Educate
Volunteer Q3 I go out of my way to help other drivers learn more about safe work driving practices.
0.93
Volunteer Q2 I go above my duties to help other drivers with their work driving safety responsibilities.
0.84
Steward Knowledge Q1
I encourage new drivers to follow safe working procedures. 0.80
Volunteer Q4 I go above my duties to help my co-workers drive safely. 0.80
Steward Knowledge Q3
I encourage other drivers to follow safe working procedures.
0.75
Volunteer Q1 I go out of my way to educate new employees about work driving safety procedures.
0.75
Steward Knowledge Q2
I inform other drivers that violations of safety procedures will have negative consequences.
0.61
Factor 2 – Fixing Safety Issues Problem Prevention 2
I implement solutions to solve safety issues that relate to driving for work.
0.84
Problem Prevention 3
When I see a potential safety hazard while driving for work, I resolve it by finding a solution.
0.80
Problem Prevention 1
When I experience safety issues while driving for work, I resolve these problems.
0.73
Fixing Responsibility Q1
I fix safety issues that relate to work driving even if it is not my responsibility.
0.67
Factor 3 – Feedback Inquiry
Feedback Q2 I actively seek feedback from my co-workers and passengers about my work driving.
0.94
Feedback Q3 I ask people at work for feedback about my driving. 0.87
Feedback Q1 I actively seek feedback from my supervisor about my work driving.
0.76
Factor 4 – Intervene
Steward Intervene Q2
If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I would intervene.
0.95
Steward Intervene Q1
I would intervene if I saw a co-worker doing something unsafe while driving for work.
0.81
Steward Intervene Q3
I would intervene to stop safety violations of other drivers. 0.65
Factor 5 –Voice
Voice 2 I speak up about work driving safety issues that affect work drivers even if it makes me unpopular.
0.94
Voice 3 I communicate my views about work driving safety issue, even if others would disagree.
0.81
Voice 1 I speak up about safety concerns during team meetings or toolbox talks.
0.79
Factor 6 – Vehicle Maintenance
Vehicle Maintenance Q2
When I see a vehicle that needs maintenance, I inform my supervisors or the appropriate person about it.
0.99
Vehicle Maintenance Q1
If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisors or completing the paperwork.
0.84
Vehicle Maintenance Q3
I make sure that vehicle defects are attended to quickly. 0.51
Total Variance Explained % 42.9 9.6 5.4 4.9 4.0 3.3 Cronbach Alpha 0.93 0.90 0.87 0.92 0.86 0.84 Notes. Extraction Method: Principal Axis Factoring; Rotation Method: Promax with Kaiser Normalisation. Rotation converged in 7 iterations.
96 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
5.6.4 Confirmatory Factor Analysis
Overview of Confirmatory Factor Analysis
For the CFA, the model’s goodness of fit was assessed using three indices:
absolute fit, incremental fit and parsimony fit. Absolute fit indices determine the extent
that a proposed model fits the observed sample data and identified which of
hypothesised model provided the most superior fit (Byrne, 2016). The calculation for
these absolute fit indices does not rely on a comparison with a baseline model, instead
it measures how well the observed model compares to a non-existent model (Byrne,
2016). Examples of absolute fit indices include: Chi-square test, Goodness of Fit Index
(GFI), Adjusted Goodness of Fit Index (AGFI), Root Mean Square Error of
Approximation (RMSEA) and the Standardised Root Mean Square Residual (SRMR).
Incremental fit indices, on the other hand, compare the hypothesised model to a
baseline model (Brown, 2014). Also known as comparative or relative fit indices, the
baseline model or the “null hypothesis” rests on the premise that covariances or
correlations among the indicators are fixed to zero (Brown, 2014). Comparative Fit
Index (CFI) and Tucker-Lewis Index (TLI) belong to this fit indices category.
Lastly, parsimony fit indices favour the models that are simple and have a better
model parsimony (i.e., number of freely estimated parameters expressed by model
degrees of freedom; Brown, 2014). Models that are less parsimonious and quite
complex are penalised – the more complex the model is, the lower the fit index.
Parsimony Goodness-of-Fit Index (PGFI), the Parsimonious Normed Fit Index (PNFI)
and CMIN/DF or Minimum Discrepancy divided by Degrees of Freedom are some
examples of parsimony fit indices (Byrne, 2016).
Table 5.7 shows the recommended threshold for each index. The ideal model
should not only be theoretically sensible, but must also fit the sample data. There is an
on-going discussion as to which indices are the most appropriate to report and what
the recommended thresholds should be (Brown, 2014; Byrne, 2016). For instance, the
conventional overall test of fit in covariance structure analysis is the chi-square (χ2)
test, which measures the extent of the discrepancy between the fitted covariance matrix
with the sample data (Hu & Bentler, 1995). A good model fit provides a non-
significant result at a 0.05 threshold (Brown, 2014). However, the χ2 test is quite
restrictive as it assumes multivariate normality and is quite sensitive to sample size. If
the sample size is large, the χ2 test usually rejects the model but a small sample size
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 97
could lead to a lack of power. Therefore, it is difficult to discriminate between good-
fitting from bad-fitting models using the χ2 test. The χ2 statistic should always be
interpreted in conjunction with other model fit indices (Hair et al., 2010). To assess
the model of the PSB-WD scale, the goodness of fit were assessed using Chi-square,
RMSEA (absolute fit indices), CFI (incremental fit indices) and CMIN/DF
(parsimonious fit indices). The SRMR was not calculated due to some missing data.
Table 5.7 Assessment of Model Fit
Criterion Excellent Threshold
Acceptable Threshold
Absolute Fit Indices
χ2 p 0.05 p 0.05 RMSEA < . 05 < . 08 SRMR < . 05 < . 08 GFI > .95 > .90 Incremental Fit Indices
NFI > .95 > .90 TLI > .95 > .90 RNI > .95 > .90 CFI > .95 > .90 Parsimony Fit Indices
AGFI > .95 > .90 CMIN/DF > .95 > .90 PNFI > .95 > .90
Notes. χ2 = Discrepancy Chi-square, CMIN/DF = Minimum Discrepancy/Degree of Freedom, RMSEA = Root Mean Square Error of Approximation, SRMR = Standardised Root Mean Residual, GFI = Goodness-of-Fit-Index, TLI = Tucker-Lewis Index.
Results of the Confirmatory Factor Analysis
Overall, the EFA analysis revealed that the PSB-WD scale had six factors:
Education, Feedback Inquiry, Intervene, Vehicle Maintenance, Fixing Safety Issues
and Voice. In order to confirm the measurement model and to assess its construct
validity, CFA was applied (Hair et al., 2010).
The initial model’s goodness of fit was 2 (215) 559.65, p < .001, CMIN/DF =
2.60, CFI = .93, RMSEA = 0.07. Although the 2 was significant, the other indices
suggested that the model was an acceptable fit to the data. Inspection of the results
revealed that the standardised loading estimates of all items were .60 or greater and
significant at p <.001, confirming the factor structure specified in the EFA.
The modification indices with complete data were checked to see if the model
could be re-specified to improve the model fit. The modification indices demonstrated
98 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
that the model could be improved by co-varying the error terms between steward
knowledge item 3 and item 1 which would reduce the largest modification in the model
(MI = 109.87). In addition, error terms for volunteer item 2 covaried with steward
knowledge item 1 (MI = 20.49), item 2 (MI = 17.03) and item 3 (MI = 19.26). While
various researchers have suggested the need to exercise caution if using the
modification indices for model re-specification, if the change is based on conceptual
terms, then the modification indices could be a useful tool (Byrne, 2016). For the
proposed change, the two items were conceptually belonging within the same factor
and, on reading the items description suggested that the two items were very similar
to each other, which could indicate a redundancy between the two items. Therefore,
instead of co-varying the two error terms, steward knowledge item 1 was deleted and
the model produced a better goodness-of-fit indices. Steward knowledge item 1 was
deleted as it reduced the reliability estimates and this item had referred to new drivers
while item 3 had referred to other drivers. Thus, the term “other drivers” may seem
more general and have broader appeal. Volunteer item 2 was also removed from the
analysis due to potential item redundancy with other volunteer items.
Figure 5.2 shows the re-specified measurement model of PSB-WD scale after
the removal of steward knowledge item 1 and volunteer item 2. The goodness-of-fit of
the specified model was 2(174) = 348.75, p < .001, CMIN/DF = 2.00, CFI = .96,
RMSEA = 0.06. The 2 test was still significant, but the other indices demonstrate a
better fit compared to the previous model.
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 99
Figure 5.2 Re-specified measurement model of PSB-WD scale
Validity Assessment
Validity of the measure was further explored by examining its construct,
convergent and discriminant validity (Hair et al., 2010). Convergent validity is a
function of the association between two different measurement scales, which are
supposed to measure the same concept and is achieved when multiple indicators
operate in a consistent manner (Hair et al., 2010). The composite reliability (CR) and
average variance extracted (AVE) were used to measure the convergent validity of the
constructs. The constructs are said to have convergent validity when the composite
reliability exceeds the criterion of 0.07 and the AVE 0.05. AMOS does not produce
100 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
the AVE and composite reliability for each factor, therefore, they were calculated
manually using an excel tool developed by Gaskin (2011) .
Discriminant validity is the extent to which the scales reflect their suggested
construct different from the relationship with all the other scales in the research model
(Hair et al., 2010). To test discriminant validity, the square root of AVE should be
higher than the correlations between the factors in order to satisfy the discriminant
validity requirement. As shown in Table 5.8, all square roots of the AVEs (in diagonal
cells) are higher than the correlations between the factors and demonstrating support
for discriminant validity.
Table 5.8 Discriminant and convergent validity
CR AVE Voice Educate Feedback Intervene
Vehicle Mainte- nance
Fixing Safety Issues
Voice 0.92 0.80 0.89
Educate 0.90 0.65 0.70 0.81
Feedback 0.90 0.76 0.39 0.61 0.87
Intervene 0.86 0.68 0.45 0.49 0.25 0.82
Vehicle Maintenance 0.85 0.66 0.45 0.37 0.16 0.42 0.81
Fixing Safety Issues 0.87 0.62 0.63 0.66 0.35 0.50 0.55 0.79 Notes. CR = Composite Reliability; AVE = Average Variance Extracted; Diagonal numbers in bold are square root of AVE
5.7 OVERALL DISCUSSION OF STUDY 2
The current chapter detailed the development and testing of the PSB-WD scale.
The development of the PSB-WD scale involved three phases: 1) item generation and
expert panel review, 2) piloting the survey, and 3) testing the scale’s dimensionality,
reliability and validity. First, the item generation phase pooled 84 items that were
reduced to 47 items through a group decision making technique conducted by the
research team. An expert panel was consulted to further give feedback on the items
and the item pool were further reduced to 42 items. Five items with low clarity and
low content validity were removed and six items were revised based on the feedback
by the expert panel. The initial PSB-WD scale with 42 items were categorised into six
dimensions: feedback inquiry, helping/volunteerism, problem prevention,
stewardship, voice and changing organisational policies and procedures.
The pilot testing of the 42 item PSB-WD scale revealed that, generally, most
items remained within the expected factors. For instance, the items for
volunteerism/helping, voice and feedback inquiry were originally written for these
factors. However, items written for some dimensions revealed mixed results,
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 101
particularly for the stewardship and problem prevention dimensions. For instance, it
was evident that problem prevention could be divided into fixing safety issues and
vehicle maintenance, while stewardship could be divided into protection, intervene
and knowledge-sharing.
Nevertheless, the results of the pilot study demonstrated the dimensionality of
the scale and assessment of the internal reliability of the extracted factors was
acceptable (all factors had a Cronbach α above 0.70). The PSB-WD scale was also
further reduced to 29 items, removing the items with poor communalities and high
cross-factor loadings.
The last phase of the scale development process involved an EFA to further
explore the factorability of the PSB-WD scale and confirmation of its factor structure
via CFA. The EFA demonstrated six factors: educate, feedback inquiry, voice,
intervene, fixing safety issues and vehicle maintenance (See Figure 5.3). The results
further clarified the factors found from the pilot studies, suggesting that vehicle
maintenance and fixing safety issues were indeed separate factors (which included
items originally written for the problem prevention dimension). Educate and intervene
were also separate factors (which included items originally written for the stewardship
and helping/ volunteering dimensions). Feedback inquiry and voice were the only
factors that stayed relatively stable between the three processes. From this process,
the psychometric properties of the scale demonstrated sound reliability and validity
(e.g., construct, convergent, divergent validities). The final version of the PSB-WD
scale had 21 items.
102Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
PSB-WD
Study 2b
Feedback Inquiry
Helping / Volunteerism
Problem Prevention
Fixing safety issues
Vehicle Maintenance
Stewardship
Protection
Intervention
Knowledge Sharing Voice
PSB-WD
Study 2c
Feedback Inquiry
Educate
Fixing safety Issues
Vehicle Maintenance
Intervene
Voice
Figure 5.3 Hypothesised dimensions of proactive safety behaviours within the work driving context from the item generation (PSB-WD; left) and the dimensions extracted from PCA using the pilot study data (middle) and dimensions extracted from the EFA and CFA (left).
PSB-WD
Study 2a
Feedback Inquiry
Helping / Volunteerism
Problem Prevention
Stewardship
Voice
Changing of organisations policies and procedures
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 103
5.7.1 Theoretical and Practical Implications
The purpose of the current study was to identify proactive safety behaviours that
are prevalent to the context of work driving and to develop a measure for these
behaviours. Adapting existing measures on proactive safety behaviours and proactivity
originally developed for general work settings, the PSB-WD scale provided a clearer
picture on the proactive safety behaviours that employees may undertake while driving
for work.
While this scale was developed specifically for the work driving context, the
current study provided further evidence that proactive safety behaviours is a multi-
dimensional construct, even when applied in a new context (i.e., work driving).
However, the PSB-WD scale also demonstrated possible new dimensions of proactive
safety behaviours, which included: feedback inquiry, fixing safety issues and vehicle
maintenance. These dimensions were specifically developed from the work proactivity
measures by Parker and colleagues (Parker & Collins, 2010; Parker & Wang; 2015) -
measures that previous studies on proactive safety behaviours have not examined.
Although these dimensions were specifically developed for work driving safety, it is
possible that these dimensions could also be applied within the general safety field.
In addition, previous studies that examined similar constructs to proactive safety
behaviours within the road safety research (e.g., traffic safety citizenship by Finley et
al. [2015]) only examined the passengers’ role in intervening when a driver engages
in a risky behaviour (e.g., using a mobile phone while driving). The current study has
contributed to the work driving literature by providing a larger set of behaviours that
employees may engage in when taking initiatives in work driving safety (e.g., asking
feedback about their driving; educating other drivers of safety policies and
procedures).
Furthermore, the newly developed PSB-WD scale could be used as a diagnostic
tool for work driving safety performance. Inspection of the internal reliability and
validity of the scale also indicated that the developed scale has sound psychometric
properties. This psychometrically sound scale could be used as a complementary tool
alongside current measures of work driving safety (e.g., occupational driving safety
behaviours, self-reporting of crashes, safety incidents, traffic violations and near
misses). More specifically, instead of just looking at lagging indicators (e.g., crashes
104 Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context
and traffic violations), organisations could use this scale to measure other indicators
of safety performance among work drivers.
The scale could also be used as an education tool to cultivate these behaviours
in organisations. The PSB-WD scale identified various behavioural indicators of
proactive safety within the work driving context. Companies could use the current
research findings to develop workshops on various ways that employees could be
proactive about safety while driving for work.
5.7.2 Limitations and Future Studies
There were a number of limitations that should be noted and directions for future
research. First, the low response rate from the pilot study represented a limitation to
the current study. It could be argued that the low response rate could reflect the time
constraints and the length of the survey. However, it was necessary to initially retain
all questions given that the studies were testing the stability and structure of a new
measure. Furthermore, this limitation was addressed in third phase of the study with a
larger sample size of work drivers.
In addition, further studies are needed to examine the test-retest reliability of the
new measure. While the current scale has shown excellent internal reliability and
validity (e.g., construct and content), further testing should be conducted to ensure its
stability over time. For instance, test-retest reliability analyses could be carried out
over several time-points to ensure the scale’s consistency. In addition, further evidence
of the external validity of the scale could be assessed based on supervisors’ rating of
work drivers’ proactivity levels towards safety issues and critical events. While this
testing could be resource intensive, it would likely offer further insights in regards to
assessing the quality of the scale.
Next, the study utilised self-report measures to assess the proactive safety
behaviours among work drivers. Although self-report measures are often used in traffic
research, these measures are subjected to participant response biases (Newnam et al.,
2011). For instance, the recruitment procedure of seeking voluntary participation for
the survey may have contributed to selection bias, whereby employees self-selecting
into completing the survey may be already engaging in proactive work driving safety
behaviours. Those who may not be performing such behaviours may be less likely to
volunteer for participation. Future studies could attempt to utilise other methods of
Chapter 5: Development and Testing of Proactive Safety Behaviour Measure within the Work Driving Context 105
measuring proactive work driving safety behaviours to reduce these biases, such as
observation or diary studies.
5.7.3 Concluding Remarks
The current study is motivated by the significant issue of work-related road
crashes which result in fatalities and serious injuries. Furthermore, there is currently a
lack of evidence regarding the identification of leading indicators for safety
performance among the work driving population. The current study aimed to make a
practical contribution in the work driving safety field by developing a measurement
tool that could examine these behaviours in the workplace and by investigating how
organisations can engage their work drivers and management to be more proactive in
managing risks while driving for work.
This study suggests that the newly developed PSB-WD scale is a
psychometrically sound scale for assessing proactive safety behaviours among work
drivers. At present, no research has captured the proactive safety behaviours prevalent
in the work driving population. Therefore, this new instrument has the potential to
further inform work driving safety research. For instance, research could use the newly
developed scale to develop better understanding of the relationships between the
antecedents and outcomes specific to this behaviour. In addition, the scale could be
used as a diagnostic tool to identify target behaviours and conditions for interventions.
Further discussion of this suggestion appears in the general discussion chapter
(Chapter 7).
106 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
6.1 INTRODUCTORY STATEMENT
Study 1 summarised and synthesized the contextual and individual factors that
influence proactive safety behaviours, using studies conducted within the general
occupational safety field. As shown from the findings of the meta-analysis conducted
within the current program of research (Chapter 4, section 4.4), employees’ proactive
safety behaviour is influenced by a wide range of contextual factors and cognitive
mechanisms. In conjunction with the findings from the meta-analysis and the current
literature on the work driving safety field, the current study proposes a new model for
proactive safety behaviours that could be applied within the work driving context (see
Figure 6.1). The proposed model is guided by the framework established by Curcuruto
and Griffin (2017) on safety proactivity and tested using a sample of work drivers (N
= 300).
Can-do Motivation: Perceived Control
Reason-to Motivation: Felt Responsibility
Proactive Future Orientation & Motivational States
PROACTIVE WORK DRIVING SAFETY BEHAVIOURS
Proactive Safety Behaviours
CONTEXTUAL ANTECEDENTS PROXIMAL ANTECEDENTS SAFETY BEHAVIOUR
Perceived Work Environment
Safety Climate
Leader-Member Exchange
Future Orientation: Anticipation Focus
Figure 6.1 Research model
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 107
This chapter presents the results of this model testing, which represents the third
and final study of the current program of research. This chapter also aims to answer
RQ3: “What are the individual and organisational factors that promote and inhibit
proactive safety behaviours in work drivers?”
It is also expected that a myriad of factors would influence the proactive safety
behaviours performed by work drivers. The current program of research only
specifically examined the potential influence of safety climate, leader-membership
exchange (LMX) as context antecedents of proactive safety behaviours among work
drivers. The current program of research also specifically examined future orientation
and motivational states as the proximal factors of these behaviours. The arguments for
choosing these factors are discussed in the following sections of the current chapter.
6.1.1 Contextual Antecedents
Safety Climate
As mentioned in Study 1 (meta-analytic review), researchers within the general
occupational field have often examined safety climate to investigate safety behaviours
in the workplace. To engage in proactive safety behaviours, employees must perceive
that such behaviours are valued and important within their work environment (Griffin
and Neal, 2000). The organisation’s climate often sets the expectations on which
behaviours are valued and rewarded. A positive safety climate sets the expectation that
safety is critical within the organisation. Therefore, positive safety climate encourage
workers to conduct safety behaviours and practices in the workplace because working
safely is valued within their organisation (Griffin & Neal, 2000).
An extensive body of literature exists on the role of safety climate in
occupational safety and, as demonstrated in Study 1, safety climate has a significant
effect on proactive safety behaviours. Safety climate has also been studied in the work
driving literature and seen as an integral factor in work drivers’ safe driving
performance (Newnam et al., 2011; Wills, Watson & Biggs, 2009). Safety climate
within the work driving literature has been defined as, “the mental framework or set
of perceptions that drivers hold about fleet safety policies and practices in their
organisations” (Husband, 2011, p. 17). Using work drivers from various Australian
organisations that operate vehicle fleets, Wills et al. (2009) found that employees’
perceptions of safety climate significantly predicted current driving behaviours and
108 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
future driving intentions over and above demographic characteristics (age and gender)
and driving exposure (annual mileage and weekly driving hours). Safety climate
explained the largest unique variance of the driving behaviours compared to other
factors (i.e., safety attitudes, perceived behavioural control and driving experience;
Wills et al., 2009). In Will et al.’s (2009) study, employees’ perception of the
importance and practicality of safety rules, how safety issues are communicated within
the organisation and management’s commitment to safety were found to be the most
influential safety climate elements on work-related driving behaviours (Wills et al.,
2009). However, safety climate within the work driving literature is usually examined
as a predictor of risky driving behaviours in work drivers. Safety climate as an
antecedent to proactive safety behaviours within the work driving context has not been
previously examined.
Furthermore, current research on safety climate within the work driving context
tend to focus on the factor structure of safety climate and which safety climate factor
is most important in predicting employees’ driving behaviours (e.g., Wills et al., 2006,
2009). However, recent studies by Huang and colleagues have started to examine the
perceptions of safety climate from different levels of the organisation (e.g., group
versus organisation)17 using different samples of work drivers of heavy and light
vehicles (Huang, Ho, Smith, & Chen, 2006; Huang, Lee, McFadden, Rineer, &
Robertson, 2017; Zohar, Huang, Lee, & Robertson, 2014; Huang et al., 2013). Huang
et al. (2013) developed a multi-level safety climate measure that could be used within
the work driving setting. Using their multi-level measure of safety climate, Huang et
al. (2013) demonstrated that higher levels of organisational and group safety climate
were associated with lower involvement in their work driver’s near miss events and
work-related injury and illness. Huang et al. (2013) found that group-level safety
climate has a stronger relationship with near-miss incident reporting compared to
organisational-level safety climate. Furthermore, the level of safety climate showed a
17 As mentioned in Chapter 4, Zohar and colleagues (Zohar, 2008; Zohar and Luria, 2005) proposed a multi-level framework for safety climate which differentiates between the organisation and group-level as employees’ perception may change depending on the referent group (i.e., top management or direct supervisors). In particular, safety climate from the organisation-level perspective may involve policies and procedures established by the company, while the top management ensures that these policies and procedures are implemented and safety is promoted. Group-level safety climate is more focused on the direct supervisory and workgroup safety practices. However, the top management’s priorities (organisational-level) may not always align with the priorities of the unit-level supervisors and the workgroup (group-level).
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 109
differential effect on the outcome variables. For instance, higher group safety climate
is a significant predictor of lower absenteeism due to illness, organisational safety
climate did not show a significant relationship with absenteeism. From these studies
and findings of Study 1, it is possible that different levels of safety climate
(organisational versus group) could also have a potential differential effect on work
drivers’ proactive safety behaviours.
Leader-Member Exchange.
In addition to safety climate, the impact of leaders is usually examined within
occupational safety. Leaders play a critical role in encouraging workers to perform
safety behaviours and in shaping the safety climate within an organisation (Hofmann
& Morgeson, 1999; Neal & Griffin, 2002). Various leadership theories exist in the
literature, however, the current chapter focuses on the social exchange relationship
between leaders and subordinates and its influence on proactive work driving
behaviour. Specifically, the current study used the leader-member exchange (LMX)
theory for the proposed research model.
The LMX theory describes the quality of the relationship between leaders and
their followers. This theory offers a unique perspective on leadership due to its focus
on the ‘dyadic relationship’ between the leader and the subordinate (Graen & Uhl-
Bien, 1995). High quality LMX is characterised by trust, mutual respect, fairness and
support between leaders and their followers (Graen & Uhl-Bien, 1995). Within the
safety literature, research shows that having a high quality LMX is associated with
more open communication and increased value congruence (Hofmann & Morgeson,
2004). As a result, workers are encouraged to raise safety concerns and become more
committed to safety in their workplace (Hofmann & Morgeson, 2004). Hofmann and
Morgeson (2004) also found that employees with high quality relationships with their
leaders are more likely to perceive safety as a job responsibility and more likely to
engage in more safety citizenship behaviours. Didla et al. (2009) suggested that the
concept of safety citizenship behaviour is based on the principle of reciprocity and the
social exchange between members and leaders. If the reciprocal supervisor-employee
relationship is built upon mutual trust, support and fairness, workers will reciprocate
positively to his/her leader and engage in behaviours that they perceive their leaders
find important (Didla et al., 2009). Therefore, leaders who place a strong emphasis on
safety in the workplace are more likely to encourage safety behaviours in their workers
110 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
if they have a high quality relationship with their subordinates (Didla et al., 2009).
Hoffmeister et al. (2014) also argued that when leaders consider their employees
individually, employees are more open to generating ideas and solutions to safety-
related problems (i.e., active promotion of safety practices).
The results of Study 1 demonstrated that transformational leadership showed a
significant and moderate relationship with proactive safety behaviours. While
transformational and LMX taps into different aspects of leadership, with the former
describing leadership traits while the latter explaining the social exchange relationship
between leaders and subordinates, Clarke (2013b) argued that transformational
leadership also encompasses aspects of LMX. In particular, Clarke (2013b) suggested
that transformational leaders demonstrate individualised consideration, whereby a
leader is said to show interest in subordinates’ personal and professional development
and listens to their needs and concerns (which is an aspect of LMX).
Furthermore, research within the work driving field has previously examined the
role of LMX on safety driving behaviours and found that the quality of leader and
member exchange is a significant factor of safety driving performance (Newnam et al.,
2012). Newnam et al. (2012) argued that “participation in safe driving practices is
likely to be promoted through reciprocation of those behaviours valued by the
supervisor” (p. 32). Using a sample of healthcare employees who drive for work,
Newnam et al. (2012) studied the role of LMX on the safety information exchange
between supervisors and work drivers and driving performance. Safety information
exchange measures the frequency of discussions on driver safety with direct
supervisors within a two-week period. Their study found that high quality relationship
with leaders is associated with more frequent exchange of safety information and safer
driving performance (Newnam et al., 2012). In other words, LMX not only promoted
safety communication between supervisors and work drivers, but it also promoted
engagement in safe driving behaviours.
Therefore, instead of examining the influence of leadership traits on proactive
safety behaviours, LMX was used in the model as an antecedent to work drivers’
proactive safety behaviours. The current program of research proposed that the
relationship between the leaders and subordinates would have an impact on work
drivers’ engagement in proactive safety behaviours.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 111
6.1.2 Proximal Antecedents
Future orientation and motivational states are the central aspects of Curcuruto
and Griffin’s (2017) model of safety proactivity. As discussed in Chapter 4, Curucuto
and Griffin (2017) argued that several cognitive-mechanisms may impact directly on
one’s motivation to act in a proactive manner, capability and commitment drivers and
future orientation. The capability and commitment mechanisms were based on the
expectancy-valence theory of motivation, while future orientation states were based
on the regulatory focus theory. Since these concepts were already discussed in Chapter
4, only a brief overview and their relation to the research model are provided in the
following sections.
Proactive Future Orientation – Anticipation-Focus
Recently, Curcuruto et al. (2016) proposed the framework of future orientation
and its relationship with safety management. Curcuruto et al. (2016) argued that
individuals who have the propensity to anticipate risks and those who strive to improve
safety in the workplace beyond the minimal standards are more likely to behave
proactively for safety. These individuals have the future orientation of ‘anticipation’
or ‘improvement’.
The construct of future orientation taps into the promotion-focused concept
within the self-regulation focus theory (Curcuruto et al., 2016). The self-regulation
focus theory describes the two cognitive approaches that individuals engage in when
deciding which behaviours to perform during a goal pursuit (Higgins, 1997; Henning
et al., 2009). These two cognitive approaches are promotion-focused or prevention-
focused (Higgins, 1997). Curcuruto et al. (2016) applied this concept of promotion-
focus in occupational safety contexts. They suggested that individuals who are
promotion-focused are more likely to anticipate risks and to continuously improve
safety within the workplace (Curcuruto et al., 2016).
Anticipation-focused and improvement-focused individuals are more likely to
suggest new or different ways to do things more safely (Curcuruto et al., 2016). These
individuals are also more willing to think about ways to improve safety at work even
if activities are running smoothly and there is no evidence of apparent threat
(Curcuruto et al., 2016). Using a sample of chemical and manufacturing operators,
Curcuruto et al. (2016) found that individuals who anticipated risks and who had the
propensity to improve the safety of their work environment were more likely to engage
112 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
in proactive safety behaviours. More specifically, individuals with anticipation
orientation and improvement orientation were more likely to voice safety concerns and
suggest safety improvements, and were less likely to engage in risk-taking behaviours
The concepts of anticipation and future orientation have not yet been applied in
the work driving context, however, similar constructs had been studied in the general
road safety research, particularly with risk anticipation (e.g., McKenna, Horswill, &
Alexander, 2006; Kinnear, Kelly, Stradling, Thompson; 2013). For instance, McKenna
et al. (2006) found that training individuals in anticipating hazards on the road were
associated with reduced risk driving. They argued that risk taking behaviour, while
deliberate, could also reflect failure to appreciate the danger within the immediate
environment. In line with this argument, anticipation focused individuals may pre-
empt risks and hazards when driving for work. Research on improvement orientation
within driving safety is still unclear. Therefore, the current study focused on the role
of anticipation orientation on proactive safety behaviours within the context of work
driving.
Proactive Motivational States – Can Do and Reason To
While safety climate and high-quality relationship with leaders create an
environment that encourages individuals to engage in proactive safety behaviours,
individuals must actually be motivated to perform these behaviours (Andriessen, 1978;
Griffin and Neal, 2000). Individuals’ motivation to proactively engage in safety
practices is central to Curcuruto and Griffin (2017) model of safety proactivity.
Curcuruto and Griffin (2017) argued that motivation directly influence proactive safety
behaviours and act as proximal antecedents for such behaviours.
As mentioned in Chapter 4, Curcuruto and Griffin (2017) argued that several
cognitive-mechanisms may directly impact on one’s motivation to act in a proactive
manner. These motivational states were referred to as: capability and commitment
drivers. These motivational states were based on Vroom’s (1964) expectancy-valence
theory. In its simplest form, the expectancy-valence theory proposes that an individual
carries out a behaviour depending on (a) the perceived value of the outcome (valence)
and (b) the perceived probability of achieving that outcome (expectancy; Pinder,
2008). For instance, a worker will engage in a work behaviour (e.g., staying late at
work) if they believe that this behaviour is likely to result in valued rewards and
outcomes (e.g., getting a promotion; Pinder, 2008).
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 113
In line with the expectancy-valence theory, Curcuruto and Griffin (2017)
conceptualised the capability drivers as the ‘can-do’ motivational processes which
relates to one’s self-efficacy and belief that they can actually carry out the behaviour
(similar to the expectancy). On the other hand, commitment drivers refer to the
‘reasons’ why individuals should carry out the proactive behaviour (similar to valence
and instrumentality). Within these two broad categories of ‘can-do’ and ‘reason-to’
motivational drivers, Curcuruto and Griffin (2017) argued that there are 4 dimensions
of motivational states. The capability ‘can-do’ drivers include the components of:
1) role-breadth self-efficacy – which describes the extent in which an individual
is confident that they are able to carry out proactive safety activities and
perform safety initiatives, and
2) perceived control – which describes the extent in which individuals believe
they have “control” or are influential in shaping the safety systems and
procedures within their organisation.
On the other hand, the commitment ‘reason-to’ drivers include:
1) psychological ownership – which refers to the feeling of possession to an
‘object’ (material or immaterial) within an organisation. Within the safety literature,
psychological ownership of safety relates to the individual’s belief that their safety at
work is ‘their own’, and
2) felt responsibility – which refers to one’s perceived responsibility of safety
within the workplace.
While these dimensions of motivational states have been examined in the general
proactivity literature (e.g., Bindl, 2010; Parker et al., 2010; Parker et al., 2006), these
concepts have not been fully examined in the general occupational safety research and
especially within the work driving context. Available evidence suggests that these
motivational states were positively correlated with safety initiative, safety voice and
safety stewardship and with negative relationships with risk-taking behaviours
(Curcuruto et al., 2016). The meta-analysis conducted as part of this program of
research also showed that self-efficacy and perceived control were significant
proximal indicators of proactive safety behaviours, with perceived control showing a
stronger effect (rcor = 0.75) compared to self-efficacy (rcor = 0.42).
114 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
Although these motivational states have not been extensively examined within
the work driving context, similar concepts have been studied. For example, Banks,
Davey, and Biggs (2010) studied the perceived shared responsibility with road safety
outcomes using a sample of work drivers in Australia. They found that work drivers
who felt that responsibility in achieving work-related road safety is shared within the
organisation, were more likely to engage in safe driving behaviours. Specifically, these
individuals were less likely to drive while fatigued or to drive while multi-tasking
(Banks et al., 2010).
Perceived control had also been examined within the general road safety
research, but usually as an aspect of the Theory of Planned Behaviour, rather than as
a motivational state. In Otto et al.’s (2016) research on traffic safety citizenship, they
found that individuals who felt more confident and comfortable in speaking up were
more likely to intervene when a driver is conducting a risky behaviour (e.g., using their
phone while driving or not wearing a seatbelt).
The current study specifically studied the effect of felt responsibility and
perceived control on work drivers’ proactive safety behaviours. In addition, an indirect
effect between safety climate and proactive safety behaviours, via anticipation focus,
perceived control and felt responsibility, was proposed as previous studies have
demonstrated that safety climate has a direct and indirect influence on safety
behaviours via safety motivation and regulatory focus (Wallace et al., 2016; Christian
et al., 2009).
6.2 NON-PROACTIVE ANTECEDENT, MEDIATORS AND SAFETY COMPLIANCE
Although proactive safety behaviour is the focus of the current research, a
discussion of safety compliance is required so as to have a comprehensive
understanding of proactive safety behaviours. Violation of rules and procedures is
often seen as a major cause of workplace accidents and injuries (Zohar, 2008).
Therefore, complying with safety policies and procedures are integral in the
functioning of organisations and ensuring the safety and wellbeing of everyone at
work. As mentioned earlier, safety compliance (along with safety participation) is an
important dimension of Griffin and Neal's (2000) safety performance framework.
Safety compliance consists of behaviours synonymous with adhering to rules,
regulations, policies, and procedures relating to safety many of which are typical in
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 115
traditional safety strategies (e.g., wearing personal protective equipment and
conducting risk assessment strategies according to policies and regulations). Safety
compliant behaviours are essential in the work driving context because of the inherent
risks associated with driving for work. For example, various regulatory procedures are
in place to manage work driving fatigue (e.g., limiting hours of driving, providing
minimum hours of rest; Gander et al., 2011). These regulations ensure the safety of the
driver and the community and failure to comply with these regulations could have
devastating consequences in terms of contributing to road crashes.
Indeed, safety compliance is vital and often seen as an important prerequisite for
safe commercial vehicle operations. However, simply focusing on these behaviours as
a measure of safety performance is limited and unlikely to be sustainable in the long
run (Wishart et al., 2019). If the safety operation of an organisation simply relies on
workers complying with rules and regulations, engagement with safety would be
minimal and would not encourage desire for improvement (Curcuruto et al., 2015). In
routine and predictable work, complying with safety rules and regulations could be
adequate for maintaining safe practices (Wishart et al., 2019). However, if work has
less routine and predictability, such as driving for work (due to various road
conditions, weather, other drivers on the road, etc.), complying with safety procedures
may not be sufficient (Zohar, 2008). Proactive safety behaviours may be necessary to
guide safe practices where compliance to rules and procedures may fall short (Zohar,
2008). By including proactive safety behaviours in addition to safety compliance as
key safety performance indicators in the workplace, organisations are providing a more
comprehensive management of safety in routine work practices as well as ensuring
workers’ safety in less predictable circumstances such as a sudden adverse weather
conditions while driving or noticing a vehicle defect during a delivery (Zohar, 2008).
Furthermore, since the current program of research used a recently developed
scale to measure proactive work driving safety behaviours, safety compliance was
added to the research model to test for discriminant validity. While proactive safety
behaviours and safety compliance are closely related (Christian et al. 2009), different
mechanisms are involved in these two constructs. For instance, Griffin and Hu (2013)
found that leadership styles differ on their impact on employees’ safety compliance
and safety participation behaviours. Leaders who monitored workers’ mistakes and
safety violations were more likely to promote safety compliant behaviours among their
116 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
subordinates. On the other hand, leaders who encouraged members to learn from
mistakes and place high value on team members’ safety were more likely to promote
safety participation among employees. It could be argued that different situational,
individual and cognitive mechanisms are involved in safety compliance and proactive
safety behaviours.
Therefore, to examine the discriminant validity of the model and to provide a
comprehensive account of safety performance in work drivers, the current research
also examined the different mechanisms involved in safety compliant behaviours along
with proactive safety behaviours. From the literature, it was expected that safety
climate and the quality of the relationship between leaders and members will be
associated with safety compliance, but the strength of the relationship may be weaker
(as was demonstrated by Christian et al.’s [2009] meta-analysis). Furthermore, the
cognitive mechanisms involved in engaging with safety compliant behaviours were
also expected to be different from cognitive mechanisms involved with proactive
safety behaviours. For instance, instead of having an anticipation focus orientation,
safety compliance may be promoted by a preventative orientation. Individuals with
preventative orientation may comply with the rules and regulations to avoid being
penalised when caught and may comply with rules and regulations are fear of negative
repercussions instead of feeling responsible for their safety and the safety of others
(Aryee & Hsiung, 2016; Curcuruto & Griffin, 2017).
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 117
6.3 STUDY HYPOTHESES
The following hypotheses were developed from the aforementioned evidence
base model of the current program of research (See Figure 6.2):
Direct Effects. Having a positive organisational and group safety climate (H1)
and high quality leadership-member relationship (H2) will have a direct positive
relationship with work drivers’ proactive safety behaviours. Anticipation focus,
perceived control and felt-responsibility will also have a positive relationship with
proactive work driving safety behaviours (H3).
Indirect Effects. Future orientation and motivational states will act as mediating
variables between the safety climate and proactive safety behaviours. In other words,
safety climate (group and organisational level) will also have a positive relationship
with work drivers’ proactive safety behaviours via anticipation focus, perceived
control and felt responsibility (H4).
Non-proactive orientation, motivation and outcomes. Although not a core
focus of the program of research, it is important to demonstrate that the concept of
proactive safety behaviours is different from safety compliance. Therefore, an
additional outcome variable, safety compliance, along with its proposed antecedent
Figure 6.2 Research model with hypotheses
118 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
variable, preventative focus was added to the model. Therefore, it was hypothesised
that preventative focus and safety compliance will show a differential effect towards
the proposed model of proactive safety behaviour. Specifically, it was expected that
preventative focus will have a positive relationship with safety compliance but will
have a negative relationship with proactive safety behaviours. It was also expected that
safety climate will have a direct relationship, and an indirect relationship, with safety
compliance via preventative focus. LMX will also have a direct positive relationship
with safety compliance.
6.4 METHOD
The data used for Study 3 was the same data collected Study 2c, therefore, the
methodology, data cleaning and participant demographics and work characteristics for
Study 3 can be found in the Chapter 5. However, the measures that relate to the data
analysis of the current chapter were discussed in the following section. See Appendix
E and F for the participant information sheet and survey used for Study 3.
6.5 MEASURES
Participants were asked to indicate their demographics (i.e., age and gender),
years of having had a driving licence and work-driving related activities such as:
number of hours driven to work per week; kilometres driven to work annually; amount
of time worked in the organisation; type of vehicle driven for work; and, typical type
of road driven for work. Participants were also questioned on how many crashes and
near-misses they had experienced and traffic offences they had received while driving
for work in the past year. The following measures were used in the survey:
6.5.1 Proactive Safety Behaviours within the Work Driving Context (PSB-WD).
Proactive safety behaviours were assessed using the newly developed 21-item
proactive safety behaviour scale within the work driving context (PSB-WD). The
results from the analysis underpinning this measure are presented in Study 2c and
revealed a six-factor scale of PSB-WD: Education, Voice, Fixing Safety Issues,
Vehicle Maintenance, Feedback Inquiry and Intervene. Participants rated the extent to
which they performed these behaviours on a 5-point Likert-type scale of 1 (never) to
5 (always).
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 119
6.5.2 Safety Climate Survey – Short Form.
A scale of safety climate specifically developed for work drivers by Huang et al.
(2013) was used in this study. This scale measures safety climate at the organisational-
and group-levels within the work driving context. Zohar (2008) argued that perception
of safety climate changes depending on the referent group (i.e., organisational level
versus group-level). Organisation-level safety climate refers to the workers’
perception of the safety procedures and policies established by the company and top
management (and was assessed by 6 items). Group-level safety climate describes the
perceptions that workers have of their direct supervisor and workgroup safety practices
(and was assessed by 6 items). Participants rated the extent they agreed with each
statement on a 5-point Likert-type scale of 1 (strongly disagree) to 5 (strongly agree).
Higher scores indicate a more positive perception of organisational and group safety
climate.
6.5.3 Leader-Member Exchange (LMX).
The Leader-Member exchange (LMX) scale developed by Graen and Uhl-Bien
(1995) was used to measure the quality of the relationship between work drivers and
their supervisors. LMX was measured using seven items (e.g., “My supervisor
understands my job problems and needs” / “I understand the problems and needs of
my work drivers”). Participants rated the extent they agreed with each statement on a
5-point Likert-type scale of 1 (strongly disagree) to 5 (strongly agree). Higher scores
indicated a more positive exchange relationship. Previous research showed good
internal consistency and validity scores for the scale and this measure had been
previously applied within the general safety research (Hofmann et al., 2003) and work
driving context (Newnam et al., 2012).
6.5.4 Anticipation Focus, Perceived Control and Felt Responsibility.
Anticipation focus, perceived control and felt responsibility were measured
using the proactive safety (PRO-SAFE) scale developed by Curcuruto et al. (2016).
The PRO-SAFE scale measures the cognitive and psychological mechanisms (i.e.,
future orientation and motivation) of proactive management of safety and incident
prevention in the workplace. For the current study, the dimensions of anticipation
focus, perceived control and felt responsibility were utilised. Previous research has
120 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
demonstrated solid psychometrics for the PRO-SAFE scale using samples from high
risk industries (e.g., chemical and manufacturing; Curcuruto et al., 2016).
The scale was adapted to suit the work driving context, therefore confirmatory
factor analysis (CFA) was conducted to assess the validity of the adapted scale. The
model showed an acceptable fit, χ2(51) = 170.06, p < .001; CMIN/DF = 3.34, CFI =
0.94, TLI = 0.92, NFI = 0.91, RMSEA = 0.09, SRMR = .09). All items demonstrated
significant loadings to the hypothesised factors; however, some had low factor
loadings (less than 0.06). These items were deleted (n = 2) and the second model
showed a better fit, χ2(32) = 76.50, p < .001; CMIN/DF = 2.39, CFI = 0.97, TLI = 0.96,
NFI = 0.96; RMSEA = 0.07; SRMR = 0.06). The final version of the scale used with
the current analysis had 4 items measuring anticipation focus (e.g., “I anticipate risks
or safety problems when driving for work, thinking of the possible alternative
scenarios if problem arises”), 3 items measuring perceived control (e.g., “I recognise
that I am able to make significant contributions to the work driving safety within my
department”) and 3 items measuring felt responsibility (e.g., “I feel that it's my
responsibility to discuss work driving safety issues with my co-workers”). Participants
rated their agreement with each statement on a 5-point Likert-type scale of 1 (strongly
disagree) to 5 (strongly agree). Higher scores indicate higher levels of proactive safety
motivation and future safety orientation.
6.5.5 Prevention Focus and Safety Compliance.
The measure for prevention orientation that was utilised in the current study was
adapted from several existing measures on prevention focus (Wallace & Chen, 2006;
Neubert, Kacmar, Carlson, Chonko, & Roberts, 2008). In addition, the safety
compliance measure used for the current study was adapted from Neal and Griffin’s
(2006) study. Both measures were adapted to suit the work driving context. Four items
were utilised for safety compliance (e.g., “I follow the work driving safety policies and
procedures”) and three items for prevention focus (e.g., “I try to avoid making mistakes
or violating rules when driving for work because I do not want to get in trouble”). The
items for prevention focus and safety compliance were subjected to a CFA due to the
applied changes. The results of the CFA a good model fit, χ2(6) = 9.78 p < .001;
CMIN/DF = 1.63, CFI = 0.96, TLI = 0.99, NFI = 0.99, RMSEA = 0.47; SRMR = .03).
For preventative focus, participants rated the extent they agreed to each statement on
a 5-point Likert-type scale of 1 (strongly disagree) to 5 (strongly agree). For safety
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 121
compliance, participants rated the extent they performed these behaviours on a 5-point
Likert-type scale of 1 (never) to 5 (always). Higher scores indicate higher levels of
preventative focus and safety compliance.
6.6 DATA ANALYSIS
6.6.1 Overview of Data Analysis
Data was cleaned and relevant assumptions for Structural Equation Modelling
(SEM) were checked. To assess interrelationships between the variables and the
complete structural model, SEM was used for the analysis. The current data analysis
followed the two-step modelling approach (Anderson & Gerbing, 1988). Using the
two-step modelling approach, the measurement model was initially assessed using
exploratory factor analysis (EFA) and CFA, where the measurement model is adjusted
and fitted to the data prior to testing the structural model (see Chapter 5). Once the
developed scale had been assessed, the testing of the structural model was conducted
– where the structural relationship between the measured variables and latent
constructs was analysed. SEM is a powerful multivariate analysis technique that has
the capacity to estimate multiple and interrelated relationship within a single analysis,
while addressing the issues of measure-specific errors (Hair et al., 2010). Therefore,
this statistical technique was chosen over regression mediation modelling. For the
current analysis presented herein, the potential causal relationship between the
variables were assessed using a latent mediation model via path diagrams with
Maximum Likelihood estimation method to fit the model. Regression estimates and
modification indices were examined to improve the model fit if necessary.
6.7 RESULTS
6.7.1 Treatment of Missing Data
As mentioned in Study 2c (see Chapter 5), there was minimal missing
information across variables and data were missing completely at random, as
demonstrated by a non-significant Little’s MCAR test. To preserve power, subscale
mean imputation was used to deal with the missing values on the variables of interest.
Missing data was replaced by calculating the participant’s mean score on each
subscale. Subscale mean imputation is a reliable method for preserving power, when
missing data is minimal, which is the case in this study (Schafer & Graham, 2002).
Schafer and Graham (2002) demonstrated that this method does not create bias in
122 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
preliminary data. Thus, the mean substitution should not have impacted the main
analyses of the current study. There were variables that did not have enough
information (e.g., no response or only 1 response to a variable item) and, therefore,
mean imputation was not possible. Since bootstrapping and use of modification indices
for SEM require full data information, cases with missing data, where mean imputation
was not possible, were deleted (n = 6).
6.7.2 Aggregation of Items
Although several authors have suggested that N = 200 is a sufficient sample size
to achieve statistical power when conducting a SEM analysis, it is acknowledged that
the sample size is still restricted in terms of testing a full measurement and structural
model due to the large number of variable items (e.g., Little, Cunningham, Shahar, &
Widaman, 2002; Matsunaga, 2008). As such, the measured observed variables were
aggregated to form a mean for each latent construct. The structural path analysis was
conducted using the aggregated scores. While this reduces the complexity of the model
(Little et al., 2002), it is still possible to assess the relationships among the variables.
Using the aggregated scores as indicators of the latent construct, a power analysis was
carried out to ensure that the current sample size (N = 294) was of sufficient statistical
power to detect significant effects. Using the G*Power program, computation of
achieved power was 0.99, revealing sufficient power.
6.7.3 Assumption Checking
Following the assessment and treatment of missing data, the scales were assessed
for non-normal distribution of data as SEM requires variables to be normally
distributed (Hair et al., 1995; Kline, 2000). Therefore, prior to the hypothesis testing,
the raw data were examined for univariate outliers and assumptions of normality.
Visual inspection of histograms and box-plots revealed univariate outliers on some of
the variables (i.e., PSB-WD feedback, vehicle maintenance, preventative focus,
anticipation focus, perceived control and felt responsibility). However, no extreme
outliers were observed in any of these variables (none with a z score of more than 3.29;
Field, 2013). Kolmogorov-Smirnov test of normality was examined and the results
revealed non-normality across all variables. Inspection of the histograms and statistics
for skewness and kurtosis also confirmed breaches of normality. When assumptions
of residual’s normality and homoscedasticity are not met, the standard errors are
usually biased, which could inflate the confidence intervals of the regression
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 123
coefficients (Field, 2013). Therefore, due to these violations in normality, bootstrap
analysis of 10,000 samples was carried out on all analysis. Bootstrap analysis does not
rely on the traditional central limit theorem and its assumptions (Efron & Tibshirani,
1986; Field, 2013).
Checks were also conducted to determine whether any differences on proactive
behaviours existed depending on the where the data was collected (online survey
versus hard-copy; See Appendix G). A series of independent t-tests were conducted
comparing the differences between PSB-WD scores from the online and hardcopy
collection methods. Significant differences were only found in regards to vehicle
maintenance, t(238.76) = 3.67, p = .001, BCa 95% CI [-1.89, 0.55], feedback inquiry
scores, t(191.52) = 2.98, p = .003, BCa 95% CI [0.33, 1.64], and intervene, t(289.00)
= -1.91, p = .037, BCa 95% CI [-1.51, -1.04] and the effect sizes were small (i.e.,
Cohen’s d = 0.29, Cohen’s d = 0.33, and Cohen’s d = 0.29, respectively). The sample
who completed the survey online were less likely to report vehicle maintenance and to
intervene but more likely to ask for feedback about their driving. The other proactive
safety behaviours did not show a significant difference between the data collection
method. Due to the small effect sizes, it is assumed that the data collection method had
no substantial influences on the results. Furthermore, using all of the sample ensured
the statistical power of the analysis and, therefore, the overall sample was used.
Common Method Variance Test
Due to the cross-sectional nature of the data, common method bias (CMB) is a
potential problem (Lindell & Whitney, 2001). CMB generally refers to the situation
when the correlations between constructs are due to the method used not the constructs
themselves (Podsakoff, Mackenzie, Lee, & Podsakoff, 2003). To examine if CMB was
a threat in this study, Harman's single-factor test was used (Podsakoff, et al., 2003).
An EFA was conducted with the number of factors fixed to one, using the items
retained from the CFA. Inspection of the unrotated factor solution showed that the first
factor only accounted for 29.1% of the total variance. CMB is considered to exist if
one factor explains more than half of the variance in all the items. Using this test, CMB
was not considered a problem within the study.
124 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
6.7.4 Description of Data
The descriptive statistics and reliabilities of the subscales are presented in Table
6.1. All subscales were associated with reliability scores of Cronbach’s α above 0.70,
thus indicating internal consistency was acceptable (Kline, 2000).
Examining the patterns of proactive safety behaviours, Table 6.1 demonstrates
that the sample were more likely to report vehicle maintenance behaviours as indicated
by the higher average scores and negative skew compared to the other proactive safety
behaviours. Participants were also less likely to engage in feedback inquiry as
demonstrated by the low average scores and positive skew.
As shown in Table 6.1, most of the variables were positively and significantly
correlated with proactive safety behaviours. Generally, the safety climate variables
showed a range of positive and moderate correlations between the proactive safety
behaviour variables, with organisational safety climate having the strongest positive
correlation with vehicle maintenance (r = .35), and group safety climate having the
strongest positive correlation with educate (r = .38). The correlations between LMX
and the proactive safety behaviour variables ranged between low to moderate (r = .18
to r = .29).
Anticipation focus was shown to have moderate strength correlations with the
proactive safety behaviours. Perceived control and felt responsibility also
demonstrated moderate to high correlations with proactive safety behaviours. The
highest correlation observed was between educate and felt responsibility, r = .52.
Compared with the work environment variables, the proximal variables were
generally more highly correlated with proactive safety behaviours. This difference in
correlation strength could indicate the temporal ordering assumption that is required
in mediation analysis. Within mediation analysis, it is assumed that the mediating
variables (i.e. focus and motivation variables) are more highly related to the outcome
variable (i.e., proactive safety behaviours). Therefore, temporal ordering can be
assumed.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 125
Table 6.1 Means, Standard Deviations, Cronbach Alpha and Inter-correlations between the variables
PSB-WD Variables
M SD
Skew α SC-Org
SC-Group LMX
Anticipation Focus
Perceived
Control
Felt Responsibility
Prevention
Focus
Safety Compliance Educate Voice
Fixing Issues VM
Feedback
Intervene
PSB-WD Total
SC-Org 20.34 6.00 -.30 0.93 -
SC-Group 17.74 6.55 -.11 0.94 .74** -
LMX 27.51 5.74 -.92 0.94 .44** .41** -
Anticipation Focus
15.76 2.68 -.78 0.87 .26** .27** 0.10 -
Perceived Control 10.65 2.44 -.45 0.84 .43** .49** .27** .39** -
Felt Responsibility
9.99 2.64 -.45 0.87 .32** .41** .25** .31** .61** -
Prevention Focus 7.53 1.81 -.66 0.81 .14* 0.05 0.02 .20** 0.06 0.05 -
Safety Compliance
16.39 4.04 -1.20 0.83 .35** .24** .28** .24** .25** .25** .17** -
PSB-WD Variables
Educate 14.08 5.63 .06 0.90 .29** .38** .21** .40** .48** .52** 0.01 .36** -
Voice 9.01 3.56 .01 0.92 .20** .23** .22** .39** .45** .32** -0.01 .35** .65** -
Fixing Issues
13.50 4.24 -.38 0.87 .26** .21** .22** .40** .40** .38** -0.01 .42** .61** .56** -
Vehicle Maintenance
12.19 3.30 -1.25 0.84 .35** .18** .29** .32** .36** .27** 0.10 .47** .40** .42** .51** -
Feedback Inquiry 5.50 3.08 1.33 0.90 .24** .36** .18** .28** .31** .36** 0.10 .19** .56** .37** .33** .16** -
Intervene 10.86 3.05 -.58 0.86 .28** .25** .24** .34** .42** .41** 0.04 .48** .48** .42** .46** .39** .24** -
PSB-WD Total 65.14 17.08 -.30 - .36** .37** .30** .48** .55** .52** 0.06 .51** .88** .78** .80** .64** .60** .66** -
Notes. N = 294; ** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed); M = Mean; SD = Standard Deviation; α = Cronbach’s alpha; SC-Org = Organisational Safety Climate; SC-Group = Group Safety Climate; LMX = Leader-member exchange; PSB-WD = Proactive Safety Behaviours within the Work Driving Context; VM = Vehicle Maintenance; Highlighted cells demonstrate significant bivariate inter-correlations between the antecedents and PSB-WD variables
126 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
6.7.5 Who are more likely to engage in Proactive Safety Behaviours?
Before going on to the hypothesis testing, several tests were conducted to assess
demographic and work variables and its potential relationships with proactive safety
behaviours. The relationships between the continuous and ordinal variables (i.e., hours
of driven to work each week, annual kilometres of driving to work, employed time in
the current organisation, crashes in the past year, near misses in the past year and traffic
offences in the past year) and the proactive safety behaviour variables were carried out
using bivariate correlation analyses. For the categorical variables (e.g., gender, work
vehicle used, work road), a series of independent t-tests (gender and work road) and
One-way ANOVAs were conducted (vehicle used).
As seen in Table 6.2, hours per week, annual kilometres, employed years were
significantly correlated with most of the proactive safety behaviours. Generally, the
hours driven per week and annual kilometres driven to work had positive and
significant relationships with most of the proactive safety behaviours, except for
intervene and voice. Furthermore, positive and significant relationships were found
between years of employment with voice, fixing safety issues, vehicle maintenance
and intervene.
Only a small number of participants who self-reported to having experienced
these events in the past year. More specifically, only n = 39 (13.7%) has reported to
have experienced a crash and n = 50 (17.0%) has reported committing traffic
violations. More participants reported having experienced a near-miss n = 183
(62.2%). Self-reported crashes, near misses and traffic offences in the past year did not
demonstrate any significant relationships with proactive safety behaviours, except for
a significant negative correlation between vehicle maintenance and self-reported
traffic offences.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 127
Table 6.2 Bivariate correlations between Proactive Safety Behaviour variables and work driving exposure and risk
Hours per
week Annual
Kilometers Employed
years Crashes in
the past year
Near misses in the past
year
Traffic offences in
the past year
Educate .20** .18** 0.10 0.02 0.07 0.02
Voice .22** 0.11 .18** 0.04 -0.01 -0.08
Fixing Safety Issues .19** .18** .13* 0.08 -0.07 0.02 Vehicle Maintenance .17** .14* .19** 0.05 -0.03 -.13*
Feedback Inquiry .13* .13* 0.03 0.10 0.06 0.03
Intervene 0.04 -0.01 .15** -0.10 -0.11 -0.05 Notes. N = 294; ** Correlation is significant at the 0.01 level (2-tailed); * Correlation is significant at the 0.05 level (2-tailed); PSB-WD = Proactive Safety Behaviours within the Work Driving Context; Crashes, near misses and traffic offences are self-reported.
When assessing the potential influence of gender on proactive safety
behaviours, the only significant difference found was on feedback inquiry (see
Appendix H). Males were more likely to ask for feedback about their work driving
compared to females, t(279.41) = 2.43, p = .011, 95% BCa 95% CI [0.11, 1.51]. No
significant differences were found between male and female in their likelihood of
performing other proactive safety behaviours.
Furthermore, differences in proactive safety behaviours were compared
between employees who have a supervisory role compared to those with no
supervisory role (Appendix I). Significant differences between these two groups were
significant for all types of proactive safety behaviours. In general, participants with a
supervisory role were more likely to report engaging in proactive safety behaviours
compared to those without a supervisory role.
Differences on the type of road that the current sample usually drive on were
also considered. Due to the small sample size of drivers who reported to primarily
drive on dirt roads (n = 3), the independent samples t-tests were only conducted
between work drivers who reported driving on asphalt or bitumen roads compared to
a combination of asphalt and dirt roads. Drivers who reported driving on the
combination of asphalt and bitumen roads were more likely to perform most of the
proactive safety behaviours compared to those who drive on asphalt or bitumen roads
only (See Appendix J). The only exception to this finding was that, there were no
significant group differences found on the intervene variable.
Differences in proactive safety behaviour performance as a function of vehicle
type were also assessed. Overall group differences were only found for voice, F(3,
128 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
291) = 8.79, p =.001, and vehicle maintenance, F (3, 291) = 8.79, p =.001. Games-
Howell Post-hoc analysis was used due to the unequal sample sizes and breaches in
normality assumptions. The results showed that those who drive heavy vehicles (Mdiff =
2.29, BCa 95% CI [0.84, 3.75]) and SUV or 4WD (Mdiff = 1.52, BCa 95% CI [0.44,
2.59]) were more likely to voice safety issues compared to those who reported driving
a smaller car. Similarly, those who drive heavy vehicles (Mdiff = 1.74, BCa 95% CI
[0.22, 3.25]) and SUV or 4WD (Mdiff = 1.53, BCa 95% CI [0.64, 2.41]) were more
likely to perform vehicle maintenance compared to those who drive a smaller car.
6.7.6 Hypothesis Testing using Structural Equation Modelling
Test of Direct and Indirect Effects
The hypothesised model was analysed in AMOS, and the results returned a poor
fit, 2 (45) 272.87 p < .001, CMIN/DF = 6.06, CFI = 0.84, TLI = 0.77; NFI = 0.82,
RMSEA = 0.13, SRMR = 0.09. Therefore, the modification indices (MI) were
consulted to examine how the model’s fit could be improved. Covarying the error
terms between the focus and motivation variables would decrease the model
discrepancy by a total of MI = 120.04, while covarying the error terms between educate
and feedback showed a potential reduction of MI = 23.36. Given that these constructs
were conceptually related, covarying the error terms is acceptable. Therefore, these
error terms were covaried and the respecified model fit was improved, 2(41) = 122.69,
p < .001, CMIN/DF = 2.99, NFI = 0.92, TLI = 0.91, CFI = .94, RMSEA = 0.08, SRMR
= .05. The goodness-of-fit indices showed an acceptable fit, and therefore, no other
modifications were conducted. The respecified model is shown in Figure 6.3.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 129
Figure 6.3 Respecified Model after consulting the modification indices
Next, the standardised estimates were examined to see the predictive abilities of
the antecedents and to assess whether the hypotheses were met. As shown in Table
6.3, LMX, anticipation focus, perceived control and felt responsibility were the only
antecedents that showed significant relationships with proactive safety behaviours.
The relationships were positive, indicating that higher levels of LMX, anticipation
focus, perceived control and felt responsibility were associated with higher levels of
proactive safety behaviours. Organisational and group safety climates and LMX did
not demonstrate significant direct effects with proactive safety behaviours.
Table 6.3 Standardised regression weights and 95% Bias-corrected Confidence Intervals with 10,000 Bootstrap sampling
Estimate p-value
BCa 95% CI Lower Interval
BCa 95% CI Upper
Interval SC-Org → Anticipation Focus 0.12 0.120 -0.04 0.28 SC-Group → Anticipation Focus 0.18 0.019 0.03 0.34 SC-Org → Perceived Control 0.16 0.041 0.01 0.31 SC-Group → Perceived Control 0.37 *** 0.21 0.51 SC-Org → Felt Responsibility 0.04 0.621 -0.12 0.20 SC-Group → Felt Responsibility 0.38 *** 0.22 0.52 SC-Org → PSBWD 0.08 0.290 -0.07 0.22 SC-Group → PSBWD -0.07 0.387 -0.23 0.09 LMX → PSBWD 0.14 0.010 0.03 0.25 Anticipation Focus → PSBWD 0.32 *** 0.22 0.42 Perceived Control → PSBWD 0.27 *** 0.13 0.41 Felt Responsibility → PSBWD 0.26 *** 0.13 0.38
Notes. N = 294; *** p = <.001; Bias-corrected.
130 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
To test the hypothesised mediation effect of safety climate on proactive safety
behaviours via the focus and motivation variables, the indirect effects were assessed.
The findings showed that a significant indirect effect was only observed for group
safety climate (β = 0.25, BCa 95% CI [.15, .37]; shown as the dotted line in Figure
6.4). This indirect effect was observed via anticipation focus, perceived control and
felt responsibility. No other significant indirect effects were observed.
Figure 6.4 Respecified model with standardised regression estimates, only showing the significant paths.
Hypothesis on the Non-Proactive States, Motivation and Outcomes
Although not the core focus of the current study within the program of research,
it is important to demonstrate that proactive safety behaviours were distinct from safety
compliance behaviour so as to assess the discriminant validity between the two
constructs. Therefore, an additional outcome variable, safety compliance, along with
its proposed antecedent variable, preventative focus, were added to the model to
examine its differential effect on proactive safety behaviours.
When prevention focus and safety compliance were added to the model, the
goodness of fit indices indicated a relatively acceptable fit, 2 (58) 173.56, p < .001,
CMIN/DF = 2.99, NFI = 0.90, TLI = .88, CFI = .93, RMSEA = .08, SRMR = .06.
However, the original model without preventative focus and safety compliance, still
showed the better model fit.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 131
Within this model, prevention focus showed a significant direct effect β = .13,
BCa 95% CI [.02, .24] with safety compliance. It also showed a negative direct effect
with proactive safety behaviours, but the effect was not significant, β = -.03, BCa 95%
CI [-.13, .07]. Significant direct effects were also found between LMX β =. 17, BCa
95% CI [.04, .30] and safety compliance as well as organisational safety climate β =.
29, BCa 95% CI [.14, .43] and safety compliance. When the indirect effects were
examined, no significant effects were found.
6.8 DISCUSSION
The current study (Study 3) examined the hypothesised model of proactive safety
behaviours within the work driving context (PSB-WD) using a large sample of
employees who drive for work. Specifically, it measured the influence of safety
climate, LMX as contextual antecedents, as well as anticipation focus, felt
responsibility and perceived control as proximal antecedents of proactive safety
behaviours. It was hypothesised that safety climate would have a positive direct effect
on proactive work driving safety behaviours and an indirect effect via the proximal
variables. This hypothesis was only partially supported. The findings revealed that
group and organisational safety climate did not show significant direct effects on
proactive behaviours. Only a significant indirect effect was found between group
Figure 6.5 Research model with prevention focus and safety compliance to test the discriminant validity
132 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
safety climate and proactive safety behaviours (via anticipation focus, perceived
control and felt responsibility). These results suggest that group safety climate could
influence employees’ perceived control of safety and risk anticipation while driving
for work as well as felt responsibility for work driving safety issues, which in turn,
encourages them to take safety initiatives towards work driving.
On the other hand, organisational safety climate did not show any significant
effect (whether direct or indirect) on work drivers’ proactive safety behaviours, but
showed a significant direct effect on safety climate. The differential effect between
these two levels of safety climate could indicate that, organisational policies and
procedures on work driving safety influence employees’ compliance behaviours. To
go beyond these compliance behaviours, however, employees must perceive that these
organisational policies and procedures on work driving safety are practiced by their
supervisors and group-unit. In other words, even though company policies and
procedures may set the boundaries of the permissible safety practices within the
organisation, the implementation of these practices that take place within the
supervisory teams are more influential among work drivers (Zohar, 2008; Zohar &
Luria, 2005). Organisations may have policies and procedures regarding work driving
safety, but if this is not implemented by supervisors, work drivers may not necessarily
perceive driving safety as important and, therefore, not be proactive about work
driving safety.
It was also hypothesised that LMX would have a positive direct effect on work
drivers’ proactive safety behaviours, which was supported by the findings. This result
is in line with previous research (e.g., Hofmann et al., 2003; Newnam et al., 2012).
Hofmann et al. (2003) found that LMX was significantly related to safety citizenship
behaviours using a military sample. They argued that having high quality relationships
between leaders and members encourage active collaboration on potential safety
issues. Furthermore, Newnam et al. (2012) found a significant relationship between
LMX and safety driving performance on work drivers. Newnam et al. (2012) argued
that a leadership style that promote concern for workers’ well-being are more likely to
engage employees to practice safer work driving behaviours. The current study extends
the knowledge on the role of LMX within occupational safety by demonstrating that,
high quality exchanges between leaders and team members could also encourage
employees to take initiatives towards work driving safety.
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 133
Risk anticipation, perceived control and felt responsibility also showed
significant direct effects on proactive safety behaviours. Compared to the contextual
antecedents, these variables also showed the strongest effects, suggesting a more
proximal influence on proactive safety behaviours. The current results provide further
evidence to the role of future orientation and motivational states on proactive safety
behaviours.
More specifically, the findings revealed that anticipation focus has a positive
direct effect on proactive safety behaviours. This result suggests that work drivers who
anticipate risks are more likely to be proactive in managing driving safety. This result
is consistent with previous research by Curcuruto et al. (2015) where they found
anticipation orientation to have positive correlations with safety initiative, voice and
stewardship behaviours. However, their research only examined the bivariate
correlations between these constructs. The current study extends this knowledge by
showing that, using structural modelling technique, anticipation orientation may also
have a possible predictive role on proactive safety behaviours.
Furthermore, the majority of previous studies have conceptualised motivation as
a single construct (see Study 1 in Chapter 4). The current study extends the existing
literature by studying the multi-dimensionality of motivation on work drivers’
proactive safety behaviours. The current findings suggest that employees are
motivated to take initiatives on work driving safety if they perceive themselves as
having influence on the organisation’s safety processes and procedures. In other
words, employees could be proactive regarding work driving safety if they ‘can’ have
a significant impact on current safety practices (i.e., perceived control represents the
‘can-do’ motivational mechanisms; Curcuruto et al., 2016). In addition, employees are
also likely to take initiatives if they feel responsible for their safety (and of their co-
workers’) while driving for work. In other words, work drivers engage in proactive
safety behaviours because they have a ‘reason’ to engage in such behaviours (i.e., felt
responsibility represents the ‘reason-to’ motivational mechanisms; Curcuruto et al.,
2016). The current results extended the work driving literature by demonstrating that,
felt responsibility is not only related to safe driving behaviours (Banks, Davey, &
Biggs, 2010) but also on work drivers’ proactivity towards work driving safety.
134 Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3)
6.8.1 Limitations and Future Research
There were a number of limitations that should be noted and directions for future
research. First, while the cross-sectional design employed in the current study is an
important first step toward the understanding of work drivers’ proactive safety
behaviours, longitudinal studies are required to investigate the causal relationships that
were proposed in the model.
Furthermore, the current study did not focus on crashes, near misses and traffic
offences as they are seen as lagging indicators of work driving safety, however, it is
important to acknowledge the non-significant relationships found between these safety
incidents and proactive safety behaviours. These non-significant results could be due
to the small number of participants who reported experiencing crashes, near misses
and traffic offences during working hours. In addition, the crashes and traffic offences
reported by the participant are self-reported which are susceptible to biases (e.g.,
memory recall), in contrast to actual crashes. Future research could further assess the
relationship between proactive safety behaviours and on-road behaviour using other
options such as organisational crash data and naturalistic driving data.
Different organisational levels of analysis (e.g., individual, work teams, top-
management) could also provide a better understanding of how different factors impact
on proactive safety behaviours. For instance, future studies may utilise a multi-level
modelling to further explore the impact of safety climate on different levels of safety
proactivity, within the individual-, team- or organisational-level.
Next, the study utilised self-report measures to assess the proactive safety
behaviours among work drivers. Although self-report measures are often used in traffic
research, these measures are subject to participant biases (Newnam et al., 2012). For
instance, the recruitment procedure of seeking voluntary participation for the survey
may have contributed to selection bias, whereby employees self-selecting into
completing the survey may be already engaging in proactive work driving safety
behaviours. Those who may not be performing such behaviours may be less likely to
volunteer for participation. On a similar note, it is also possible that participants may
respond inaccurately due to social desirability bias, which refers to an individual’s
tendency to portray himself/herself in a favourable light (Nederhof, 1985). Due to
nature of the topic, participants may tailor their answers to demonstrate positive self-
representation. Future studies could attempt to utilise other methods of measuring
Chapter 6: Model Testing of Proactive Safety Behaviours within the Work Driving Context (Study 3) 135
proactive work driving safety behaviours to reduce these biases, such as observation
or diary studies.
6.8.2 Chapter Summary and Key Learnings
The current chapter proposed a new model for proactive safety behaviours that
could be applied within the work driving context. This proposed model was then tested
using a sample of work drivers (N = 300) with structural question modelling. The
findings revealed that group safety climate, LMX, anticipation focus, perceived
control and felt responsibility demonstrated significant relationships with work
drivers’ proactive safety behaviours. More specifically, the results revealed that group
safety climate has an indirect effect on work drivers’ proactive safety behaviours via
anticipation focus, perceived control and felt responsibility, while LMX showed a
direct effect on work drivers’ proactive safety behaviours. Anticipation focus,
perceived control and felt responsibility also showed direct effects on work drivers’
proactive safety behaviours. Organisational-level safety climate did not demonstrate
any significant effects on proactive safety behaviours in work driving, but it showed a
significant direct effect on safety compliance behaviours. Preventative focus also
showed a direct effect on safety compliance behaviours, but not on proactive safety
behaviours.
Overall, the current study suggests that when cultivating proactive safety
behaviours in the work driving settings, group safety climate is more important than
organisational safety climate. Relationship between leaders and members is also
crucial in cultivating these behaviours. Furthermore, employees who have high levels
of anticipation risk, perceived control and felt responsibility towards driving safety
may also engage in more proactive safety behaviours while driving for work.
Chapter 7: Discussion and Conclusions 137
Chapter 7: Discussion and Conclusions
7.1 INTRODUCTORY STATEMENT
The previous chapters presented the program of research that developed and
tested a new measure and a model of proactive safety behaviours within the work
driving context (PSB-WD). This final chapter provides a synthesis of the research
methodology and findings using the research questions as the structure (see Table 7.1).
This chapter also presents the theoretical and practical contributions of the current
program of research, especially within the area of OHS and work driving safety.
Strengths of the research program as well as the limitations and suggestions for future
research are also discussed.
Table 7.1 Overview of design and methodology structured by the research questions
Overarching aim To develop a model and measure of proactive safety behaviours within the work driving context.
RQ1 What do we currently know about the construct of proactive safety behaviour? Study design and methodology:
Literature review Using research from areas of organisational psychology and occupational safety, the concept of proactive safety behaviours and similar constructs were reviewed. Meta-analysis
Review of the current literature on the antecedents of proactive safety behaviours and using meta-analysis to explore the effect of the factors based on the results of 71 studies.
RQ2 What are the proactive safety behaviours that work drivers perform to improve safety (and safety of their co-workers) while driving for work?
Study design and methodology
Item Generation and Expert Panel
Research team for the item generation (n = 3) and road safety experts and supervisors and managers of work drivers for the expert panel (n = 5).
Literature review and nominal group technique process between the research team to identify items for the measure. Online survey for the expert panel to assess content validity and item clarity.
Pilot Testing
Online survey to assess the dimensionality of the PSB-WD scale and to reduce the number of items with 43 work drivers using PCA for the analysis.
Measurement Testing
Online survey to assess the validity of the PSB-WD scale with N = 300 work drivers using EFA and CFA for the analysis.
138 Chapter 7: Discussion and Conclusions
RQ3 What are the individual and organisational factors that promote and inhibit proactive safety behaviours in work drivers?
Study design and methodology
Model Testing
Online survey to assess the hypothesised model with N = 300 work drivers using SEM for the analysis.
7.1.1 Overall Findings in Relation to RQ1
Two reviews were conducted in order to answer the first research question,
“What do we currently know about the construct of proactive safety behaviours?” The
first review critically synthesised and discussed the origins and definitions of proactive
safety behaviours using studies from organisational psychology and general
occupational safety research. The second review involved a meta-analysis conducted
as a research component within the overall program of research. This review explored
the distal and proximal antecedents of proactive safety behaviours that have been
studied within the OHS literature. The overall findings of these two reviews (i.e., the
literature review and the meta-analytical review) are discussed below.
The literature review discussed the existing literature on proactive safety
behaviours. The first account of this construct was found in Andriessen’s (1978) study
on safety behaviours using a sample of construction workers. In addition to complying
with safety rules and regulations, Andriessen (1978) noted that the participants also
engaged in ‘safety initiatives’, which were voluntary behaviours that improved the
safety of their work environment (e.g., voicing safety concerns to their supervisors).
Since then, a plethora of studies have examined these behaviours within the field of
OHS. However, Neal and Griffin’s (2002) research on safety participation, Hoffman
et al.’s (2003) work on safety citizenship and Curcuruto and colleagues’ studies on
safety proactivity (Curcuruto et al., 2015; Curcuruto & Griffin, 2017; Curcuruto,
Mearns, & Mariani, 2016) have provided a more comprehensive understanding of
these behaviours. These evidence-base studies drew upon concepts from the area of
organisational psychology which, in turn, provided theoretical underpinnings for these
behaviours. Specifically, the theoretical underpinnings of proactive safety behaviours
were based on the concepts of contextual performance (Borman & Motowidlo, 1993),
organisational citizenship behaviours (Organ, 1988) and work proactivity (Bateman &
Crant, 1993; Parker et al., 2006).
Chapter 7: Discussion and Conclusions 139
Several key findings were obtained from the literature review. First, individuals
who engage in more proactive safety behaviours were associated with fewer safety
incidents at work (Hofmann et al., 2003; Neal & Griffin, 2006). These behaviours were
found to be associated with the promotion and improvement of safety within the
workplace, better attitudes towards safety reporting and lower absence rates (e.g.,
Curcuruto & Griffin, 2017; Hofmann et al., 2003). In particular, proactive safety
behaviour was more effective at improving safety outcomes in the longer-term
(measured by reduced accidents and workplace injuries) compared to merely
complying with safety rules and regulations (e.g., Christian et al., 2009; Neal &
Griffin, 2006; Neal et al., 2000).
Second, these behaviours were initially conceptualised as a unidimensional
construct, with most research using Neal and Griffin’s (2000) measure of safety
participation. However, Hofmann et al.’s (2003) research on safety citizenship
expanded the construct of safety participation which provided a broader range of
behaviours. Their research revealed a higher-order construct of safety citizenship
consisting of six dimensions: helping, safety civic virtue (keeping informed), initiating
safety-related change (improving safety), voice, stewardship and whistle-blowing.
More recently, Curcuruto and colleagues (Curcuruto et al. 2015; Curcuruto & Griffin,
2017) built upon Hofmann et al.’s (2003) research. They argued that safety citizenship
could be further distinguished into two categories: prosocial and proactive behaviours.
Curcuruto et al. (2015) argued that proactive safety behaviours should be action-
oriented, change-oriented and future-focused. Prosocial safety behaviours, on the other
hand, are affiliative in nature, and mostly reflect the helping and stewardship
dimensions of organisational citizenship behaviours (Curcuruto et al., 2015).
The synthesis of the literature helped to inform the definition of proactive safety
behaviours, which was then utilised in the current program of research. Specifically,
proactive safety behaviour within the work driving was defined as: 1) behaviours that
improve the context of the work environment to be more supportive of safety -
behaviours that may not directly contribute to workplace safety, but facilitate an
environment that supports safety (i.e., behaviours that create a positive environment
for safety); 2) behaviours that aim to improve workplace safety that cannot be forced
(i.e., self-starting); and 3) behaviours that are change-oriented which aim to improve
the current workplace safety practices.
140 Chapter 7: Discussion and Conclusions
The review also examined similar concepts of proactive safety behaviours within
the field of general road traffic safety (i.e., outside of the organisational context). From
the review, research on prosocial driving behaviours (Harris et al., 2014) and traffic
safety citizenship (Otto et al., 2016; Finley et al., 2015) tapped into similar constructs
underlying the proposed proactive work driving safety behaviours. Specifically, the
conceptual underpinning of prosocial driving behaviours and traffic safety citizenship
is that these behaviours foster a safer culture within the general road environment. This
conceptual underpinning is similar to an aspect of proactive safety behaviours - to
improve the context of the work environment to be more supportive of safety.
However, prosocial driving behaviour and traffic safety citizenship were missing
critical aspects of proactive safety behaviours (e.g., change-oriented behaviours). For
instance, prosocial driving behaviours often reflect compliance with traffic laws (e.g.,
“obey traffic signs” and “come to a complete stop at a stop sign”; Harris et al., 2014,
p. 3) while traffic safety citizenship behaviours only measure passenger intervening
behaviours (e.g., speaking up when a driver conduct risky behaviours).
In addition to the literature review of proactive safety behaviours and its related
concepts, a meta-analysis was conducted to critically appraise and synthesise the
antecedents of proactive safety behaviours based on 71 studies. Following Curcuruto
and Griffin’s (2017) framework on safety proactivity, this review explored the distal
and proximal factors that could facilitate or inhibit one’s engagement with proactive
safety behaviours. This framework recognised the importance of the work
environment in cultivating these behaviours and the cognitive mechanisms that may
underlie these discretionary behaviours.
Then, the meta-analytical review (i.e., Study 1 of the research program) provided
further evidence that safety climate and leadership styles were important contextual
(i.e., organisational) variables of proactive safety behaviours. Study 1 also further
confirmed that safety knowledge and safety motivation were significant antecedents
of proactive safety behaviours. The effect sizes found for safety knowledge and safety
motivation demonstrated stronger effects, which may indicate a more proximal
relationship with the outcome variable. These findings were consistent with previously
established reviews (Christian et al., 2009; Clarke, 2006, 2013a). However, Study 1
extended the present knowledge by examining the influence of passive leadership,
perceived organisational support, trust, and work design variables on proactive safety
Chapter 7: Discussion and Conclusions 141
behaviours. More specifically, the findings of the meta-analysis revealed that passive
leadership style could inhibit one’s engagement with proactive safety behaviours as
demonstrated by the significant and negative effect size, while perceived
organisational support, trust and work autonomy were significantly and positively
related to proactive safety behaviours.
Compared with prior reviews which only examined safety knowledge and safety
motivation as proximal antecedents of proactive safety behaviours, the current meta-
analysis investigated a wider range of proximal factors. The findings revealed that
employees’ self-efficacy, perceived control and having a promotion focus showed
significant positive relationships with proactive safety behaviours. When observing
the pattern of the effects, it was evident that the proximal antecedents demonstrated
stronger effects sizes compared to the contextual antecedents. This pattern provided
possible evidence that contextual antecedents are distal in their relationships with
proactive safety behaviours, while the examined cognitive mechanisms could present
a more direct (i.e., proximal) relationship with proactive safety behaviours.
The literature search within the meta-analysis also revealed that, out of the 71
empirical studies that were examined, two studies were found to have some relevance
to the context of proactive work driving safety. Of these two studies, one was
specifically conducted with an aim to improve work driving safety by examining road
safety participation (Keffane, 2015) and another study examined safety voice using a
sample of urban bus drivers (Tucker et al., 2008). These studies, however, only looked
at the unidimensional nature of proactive safety behaviours (road safety participation
and safety voice).
Overall, the findings from the literature review and meta-analysis provided a
comprehensive understanding of proactive safety behaviours and its related concepts.
Both reviews informed the theoretical underpinnings of the model used for the current
program of research. The evidence base also informed the development of the
measurement tool, by adapting established current measures from previous studies to
suit the work driving context. This process resulted in the development of the research
model and the measurement scale of proactive safety behaviours within the work
driving context.
142 Chapter 7: Discussion and Conclusions
7.1.2 Overall Findings in Relation to RQ2
The concept of proactive safety behaviours and its dimensions have not been
extensively studied within the work driving safety context. Thus, the current program
of research developed a new scale to measure work drivers’ proactive safety behaviour
(PSB-WD) and to answer the second research question, “What are the proactive safety
behaviours that work drivers perform to improve safety (and of their co-workers) while
driving for work?”
The process of developing the PSB-WD scale was guided by Hinkin et al.'s
(1997) and DeVellis' (2016) approaches to scale development. Several studies were
conducted to develop the PSB-WD scale. First, an item generation process pooled
existing items from the literature that measured proactive safety behaviours and related
constructs as well as measures of general work proactivity behaviours (Study 2a).
These items were then adapted to suit the work driving safety context. The candidate,
along with her supervisory team, ranked, revised, removed and categorised the pooled
items into possible dimensions of proactive safety behaviours (e.g., feedback inquiry,
helping/volunteerism, changing organisation’s policies and procedures, problem
prevention, stewardship and safety voice). Then, an expert panel comprising road
safety experts, fleet safety managers and supervisors (n = 5) were contacted to provide
further feedback on the newly developed items and the hypothesised categories. Once
the expert panel’s feedback was applied, the scale was piloted with a small sample of
work drivers (n = 43) to assess its dimensionality.
The results of the pilot test (Study 2b) revealed eight possible dimensions of
proactive work driving safety behaviours based on a principal component analysis
(PCA). The results of the PCA also revealed that, generally, most items remained
within the expected factors. For instance, the items for volunteerism/helping, voice
and feedback inquiry were originally written for these factors. However, items written
for the stewardship and problem prevention subscales were mixed. A larger sample of
work drivers (n = 300) was used to further examine the scale by using exploratory and
confirmatory factor analysis (Study 2c). The final dimensions of this construct were
identified as: education, safety voice, fixing safety issues, vehicle maintenance,
intervene, and feedback inquiry. The final PSB-WD scale had 21 items and the
psychometric properties of the PSB-WD scale were demonstrated as having sound
reliability and validity (e.g., discriminant and convergent).
Chapter 7: Discussion and Conclusions 143
Several key findings were obtained from the scale development process. First,
Study 2 revealed that proactive work driving safety driving behaviour is a multi-
dimensional construct. Next, although the majority of the dimensions resulting from
the scale development have been supported by previous research (e.g., education,
fixing safety issues, feedback inquiry), the newly developed scale provided a specific
dimension that may be unique to work driving context; namely, ‘vehicle maintenance’.
Previous research that examined work drivers’ pre-trip vehicle maintenance
behaviours usually measured this behaviour using two items: “check the tyre pressure
of your work vehicle” and “check the oil and water levels of your work vehicle” (Wills
et al., 2006, p. 377). However, Wills et al. (2006) did not specifically examined the
proactive behaviours of work drivers. Checking the tyre pressure as well as checking
the oil and water levels of work vehicles could only denote safety compliance
behaviours. On the other hand, the vehicle maintenance dimension in the current
program of research provides a specific example of how employees could engage in
behaviours that relate to proactive problem prevention while driving for work. The
items for the vehicle maintenance dimensions also explored the aspect of consulting
another person (e.g., supervisor) when a possible defect occurs.
Last, findings from Study 3 suggested that the current sample of work drivers
reported high levels of engagement in vehicle maintenance behaviours as indicated by
the high average and negative skewed distribution scores within this dimension. On
the other hand, the current sample of work drivers reported low levels of feedback
inquiry as indicated by the low average and positively skewed distribution scores
within this dimension.
7.1.3 Overall Findings in Relation to RQ3
The third research question was: “What are the individual and organisational
factors that promote and inhibit proactive safety behaviours in work drivers?” To
answer this research question, a quantitative analysis was conducted to test the
hypothesised model of proactive safety behaviours within the work driving context.
The hypothesised model proposed multi-level safety climate (i.e., organisation-level
and group-level) and leader-member exchange (LMX) as contextual antecedents of
proactive safety behaviours in work drivers; while anticipation focus, perceived
control and felt responsibility were identified as the proximal antecedents. The
findings revealed that organisational and group safety climate were differentially
144 Chapter 7: Discussion and Conclusions
related to work drivers’ proactive safety behaviours. More specifically, group safety
climate showed a significant indirect effect on proactive safety behaviours, via
anticipation focus, perceived control and felt responsibility. However, organisational
safety climate did not show any significant effect, whether directly or indirectly, on
proactive safety behaviours. These results suggested that group safety climate may be
a more important antecedent of work drivers’ proactive safety behaviours compared
to organisational safety climate.
Furthermore, the relationship between leaders and work drivers (as measured by
LMX) showed a significant positive direct effect on proactive work driving safety
behaviours. Examining the bivariate correlations, LMX demonstrated the strongest
correlation with vehicle maintenance. This finding suggests that high quality
relationships with supervisors could encourage employees to be proactive about their
safety while driving for work, especially when maintaining vehicles. In a practical
manner, these findings suggest that leaders and management could facilitate work
drivers’ safety proactivity by conducting daily or weekly toolbox talks with a specific
focus on work driving safety.
The findings also revealed other factors that significantly related to proactive
safety behaviours and these included anticipation focus, perceived control and felt
responsibility. The current findings suggest that work drivers who anticipate risks, who
perceive that they have control of work driving situations and who feel responsible for
work driving safety, were more likely to be proactive in managing driving safety.
7.1.4 Theoretical Implications and Contributions
The current program of research, while exploratory in nature, presents several
theoretical implications and contributions. First, the development and testing of the
PSB-WD model and scale presents an advancement in knowledge within the OHS and
work driving safety fields. More specifically, even though the construct of proactive
safety behaviours was initially conceptualised within the field of OHS, this concept
has been effectively applied within the field of work driving safety. Furthermore, the
PSB-WD model is the first theoretical framework that considered the organisational
factors and cognitive mechanisms (and the interaction between the two) on proactive
safety behaviours within the work driving context.
Chapter 7: Discussion and Conclusions 145
On a broad level, the findings of the research program imply that the
management of work driving safety could be advanced by applying the current
knowledge on the fields of OHS and organisational psychology. Since work drivers
operate within the organisational environment (Stuckey et al., 2010), there is an
impetus to examine the role of the work environment in managing the risks related to
work driving. The current program of research also demonstrated that there is a merit
in examining behaviours (other than driving behaviours, and involvement in crashes
and traffic violations) as potential safety performance indicators within the work
driving context.
Another theoretical implication of the current research program is the extension
of safety proactivity within the field of work driving safety. There is an increasing
interest in the role of proactive management of safety within the OHS field (e.g.,
Curcuruto et al., 2015). The current program of research provides a significant
contribution by demonstrating that proactive safety behaviours could be applied within
a specific area of work driving safety.
Put simply, while organisations ensure their employees’ safety by managing
risks and hazards in the workplace, risks related to work driving maybe relatively less
likely to be of focus. For instance, employees in utility industries may undertake
compulsory training to ensure safety while operating maintenance equipment and
machinery. However, utility workers may also drive between different worksites. This
work-related driving activity, which is associated with high risks, is often ignored in
general OHS research (Wishart et al., 2019).
The current research program suggests that the risks associated with these work-
related driving activities should also be managed by organisations, especially given
that driving for work is one of the most hazardous work activities that an employee
could undertake. Future research could also examine the differences in proactive safety
behaviours in both general work activities and when employees must drive for work.
Second, the meta-analysis reported in Study 1 extended the current literature on
proactive safety behaviours. Extending Curcuruto and Griffin's (2017) literature
review and model of safety proactivity, the present study advanced the current
understanding of the contextual and proximal antecedents of safety proactivity by
providing a meta-analytic investigation of various organisational factors and cognitive
mechanisms and their influence on proactive safety behaviours. The meta-analytic
146 Chapter 7: Discussion and Conclusions
results provide quantitative evidence to support Curcuruto and Griffin’s (2017)
proposed framework for safety proactivity. More specifically, the findings of the meta-
analysis provide further evidence on the importance of examining the multi-level
framework of safety climate, different styles of leadership, social exchanges and
interpersonal processes within the organisation and work design as facilitators of
proactive safety behaviours. The meta-analysis also demonstrated other possible
proximal antecedents of proactive safety behaviours other than safety knowledge and
safety motivation (which has been the focus of previous research). In particular, the
meta-analysis showed that perceived control demonstrated the strongest meta-analytic
effect with proactive safety behaviours, even more than the effects found for safety
knowledge and safety motivation.
Furthermore, the development of the PSB-WD scale provided further evidence
relating to the multi-dimensionality of proactive safety behaviours. The current
program of research also revealed new dimensions which had not been previously
examined. The PSB-WD scale shares similar dimensions to prior measures of
proactive safety behaviours. For instance, voicing driving safety concerns relates to
the voice dimension of Hofmann et al.’s (2002) safety citizenship measure. However,
the PSB-WD scale also demonstrated dimensions of feedback inquiry, fixing safety
issues and vehicle maintenance. These dimensions were specifically developed from
the work proactivity measures by Parker and colleagues (Parker & Collins, 2010;
Parker & Wang; 2015), measures that previous studies on proactive safety behaviours
have not examined. Although these dimensions were specifically developed for work
driving safety, it is possible that these dimensions could also be applied within the
general work safety field.
In addition, the PSB-WD model further confirms the importance of examining
the multi-level framework of safety climate in the work driving setting. The majority
of research within the work driving field does not utilise the multi-level framework of
safety climate (Wills et al., 2006, 2009). It is only recently that Huang and colleagues
(e.g., Huang et al., 2013; Huang et al., 2017) have examined the group- and
organisational-level of safety climate within the work driving context. The current
research program provides further evidence that employees have different perceptions
of safety climate depending on the referent level. For instance, results of Study 3
showed that group safety climate had a significant indirect effect on proactive safety
Chapter 7: Discussion and Conclusions 147
behaviours (via anticipation orientation, perceived control and felt responsibility).
However, group-level safety climate did not show any significant effects on safety
compliance.
On the other hand, organisational-level safety climate showed a significant direct
effect on safety compliance, but not on proactive safety behaviours. While safety
compliance was not the focus of the current research program, the findings provide
further evidence that different levels of safety climate may have a distinct influence on
different behaviours performed by the work driver (safety compliance versus proactive
safety behaviours). The findings of Study 3 also provided further evidence relating to
the role of leaders on work driving safety, and extended the current literature by
demonstrating that having high quality relationship between leaders and members
could also encourage proactive safety behaviours within the work driving context.
Lastly, the current program of research contributes to the existing literature by
providing more evidence on the utility of examining the cognitive mechanisms that
underlie proactive safety behaviours. Previous research of Curcuruto et al.’s (2015)
only examined the bivariate correlations between future orientation and motivational
states on safety proactivity. Using SEM, the current research program extends this
knowledge by showing that anticipation orientation, perceived control and felt
responsibility demonstrated direct effects on proactive safety behaviours.
7.1.5 Strengths and Practical Implications
Several strengths and practical implications are evident from the research
program, especially relating to the management of work driving safety. Driving for
work is one of the riskiest activity that an employee could undertake during working
hours. It is critical to address the risks associated with work-related driving given that
a high percentage of injuries and fatalities that occur in the work place are vehicle-
related incidents. Although risk management processes relating to high risk industries
are underpinned by the ‘zero harm’ approach, organisations lack policies relating to
driving safety when managing work driving risks. This lack of appropriate risk
management strategies and diligence toward work-related road safety can severely
compromise safe driving practices and subsequently increase the risk, severity and
frequency of work-related crashes (Stuckey et al., 2010). Findings from this program
of research provide significant contributions to the current knowledge within the fields
of OHS and work driving safety by exploring the proactive safety behaviours of
148 Chapter 7: Discussion and Conclusions
employees who drive for work. Previous research on proactive safety behaviours using
work drivers (e.g., Keffane, 2015 and Tucker et al., 2008) have only examined the
unidimensional nature of proactive safety behaviours (i.e., road safety participation;
Keffane, 2015, and safety voice; Tucker et al., 2008). This is the first research program
that has explored the multi-dimensional concept of proactive safety behaviours within
the work driving field.
The core strength of the current program of research is the comprehensive
understanding of proactive safety behaviours from the literature review and meta-
analysis. Unlike the traditional narrative (unsystematic) reviews in organisational
sciences that only include studies selected by the author, conducting a meta-analytic
review limits this selection bias by thoroughly assembling and critically appraising all
relevant research on the specified topic (Denyer & Tranfield, 2009). The results of the
meta-analysis also further informed the safety proactivity framework that was
developed by Curcuruto and Griffin (2017). Another key strength of the research
program is developing a measurement tool that has psychometrically sound properties.
While there are problems within self-report questionnaires, surveys are still the most
commonly used method in organisational and OHS research as it is cost-efficient and
easy to administer (DeVellis, 2016).
The current program of research also provides significant practical contributions
in the field of work driving safety by 1) investigating how organisations can engage
their work drivers to be more proactive in managing risks while driving for work, and
by 2) providing a potential indicator of work driving safety performance that does not
rely on lagging indicators (e.g., crashes and traffic violations).
The proposed PSB-WD model demonstrated the importance of organisational
factors, particularly group safety climate and LMX, on work drivers’ proactive safety
behaviours. These findings suggest that organisations could encourage these
behaviours among work drivers by ensuring that safety policies and procedures on
work driving are implemented. Direct supervisors’ commitment to safety is especially
important as the current findings revealed that group safety climate may influence
employees’ anticipation of risks when driving for work as well as their perceived
control and felt responsibility in work driving safety. These cognitive mechanisms, in
turn, encourage work drivers to act proactively about safety matters related to work-
related driving. On the other hand, the influence of LMX on work drivers’ proactive
Chapter 7: Discussion and Conclusions 149
safety behaviours suggests that if supervisors and managers actively demonstrate that
they care and value their employees within the organisation, then employees could
perceive that management as accepting of employees’ work driving safety concerns.
From these results, the following practical suggestions for workplace safety
interventions are discussed. Training could be implemented within organisations to
raise awareness on the influence of safety climate on workers’ safety behaviours while
driving as well as creating leadership programs that promote safety. The current
program of research demonstrated the critical role that supervisors play, suggesting
that leaders need to have high quality relationships with their team members in order
to encourage workers to engage in proactive safety behaviours while driving. These
training programs may include a leadership-based intervention designed to improve
managers’ and supervisors’ interpersonal skills in order to enrich their communication
and relationships with work drivers (Newnam et al., 2012). In addition, organisations
should openly demonstrate that they are committed to the safety of employees when
they drive for work. Organisations must also ensure that work driving safety rules and
procedures do not conflict with requirements of other work tasks to demonstrate
commitment to a strong and positive work driving safety climate.
The results of the Study 3 also showed that employees were motivated to engage
in proactive safety behaviours if they continuously anticipated risks, felt responsible
for their organisation’s work driving issues, and perceived that they have control of
these issues. In a practical manner, these findings suggest that leaders and management
could facilitate work drivers’ safety proactivity by conducting daily or weekly tool-
box talks. Within these meetings, workers and supervisors could be encouraged to
openly communicate possible risks, dangers and hazards that workers may experience
on the road. These meetings could increase employee’s perceived responsibility and
control towards work driving issues, which in turn could motivate them to engage in
proactive safety behaviours. Managers could ask team members one-to-one or in team
meetings to provide feedback or ideas for fleet safety improvement where open
dialogue is encouraged and supported.
Furthermore, the newly developed PSB-WD scale could be used as a diagnostic
tool for work driving safety performance. This psychometrically sound scale could be
used as a complementary tool to current measures of work driving safety (e.g.,
occupational driving safety behaviours, self-reporting of crashes, safety incidents,
150 Chapter 7: Discussion and Conclusions
traffic violations and near misses). More specifically, instead of just looking at lagging
indicators (e.g., crashes and traffic violations), organisations could use this scale to
measure other indicators of safety performance among work drivers.
The scale could also be used as an education tool to cultivate these behaviours
in organisations. The PSB-WD scale identified various behavioural indicators of
proactive safety within the work driving context. Companies could use the current
research findings to develop workshops which could outline the various ways that
employees could be proactive about safety while driving for work. For instance,
training materials could be developed clearly stating that proactive safety behaviours
are encouraged in the workplace (e.g., “in our company, we ensure workplace safety
by encouraging other drivers to follow safety working procedures”, or “to reduce work
driving incidents, speak up when you see a co-worker using a model phone while
driving”). These statements could also be reiterated by supervisors and could be
incorporated in employee orientations. These trainings should also be conducted on a
regular basis to demonstrate that these behaviours are critical to the organisation.
However, it is important to acknowledge that these training programs may only
be effective if the organisations already operate within a certain level of positive safety
culture regarding work driving (Wishart et al., 2019). In other words, employees must
perceive that these behaviours are valued and encouraged in the workplace. These
behaviours do not occur in a vacuum (Didla et al., 2007; Didla, Mearns, & Flin, 2009),
and the current research showed that safety climate is a critical factor for proactive
safety behaviours within the work driving context. In addition, any training materials
developed based on the results of the current research would need to be evaluated and,
as such, further research would be required to evaluate such interventions.
7.1.6 Limitations and Suggestions for Future Research
The significant theoretical and practical contributions notwithstanding, this
program of research also had limitations which need to be acknowledged. Overall, it
is important to acknowledge that the current program of research was exploratory in
nature given that this was the first study to extensively examine the application of
proactive safety behaviours within the work driving context. Future research directions
are discussed in the following sections.
Chapter 7: Discussion and Conclusions 151
First, the main survey (Study 2c and Study 3) utilised a convenience sampling
recruitment and, therefore, the results may not be generalised to the whole work
driving population. In addition, the use of self-report measures may be subjected to
self-reporting bias. It is possible that employees who volunteered to complete the
survey were more conscientious about driving safety. Given that the current program
of research is largely exploratory, future research could attempt to utilise other
methods of measuring proactive work driving safety behaviours to reduce these biases,
such as observation method or diary studies. Further, supervisor rates of work team’s
safety proactivity level could offer further evidence of the external validity of the
measure. Future studies could also investigate whether the results found in the current
sample are consistent with employees from other organisations.
Second, due to the cross-sectional design of the main survey that informed the
model testing, data was only collected at a single time-point using one questionnaire.
Single time-point questionnaires have been previously criticised due to their increased
potential for common method variance (e.g., Podsakoff et al. 2003). Although the
current program of research assessed the potential common method bias within dataset,
longitudinal studies are required to minimise the bias that may result from common
method variance. In addition, longitudinal studies could further clarify the
relationships between the hypothesised variables of the PSB-WD model and allow
causality to be inferred. For example, previous research suggests that there is a
reciprocal relationship between safety motivation and safety participation (Neal &
Griffin, 2006). While safety climate is an important antecedent of proactive safety
behaviours, it is also possible that engagement in these behaviours could further
improve the workplace safety climate. Future research could assess the possible
reciprocal relationships. Further re-test reliability of the final PSB-WD scale should
also be conducted.
In addition, while the current program of research did not focus on crashes,
future research could further assess the relationship between proactive safety
behaviours and on-road behaviour using other options such as organisational crash
data and naturalistic driving data. Recently, OHS researchers have begun examining
the influence of proactive safety behaviours on other safety outcome measures such as
lost-time injuries, micro-accidents and property damage (e.g., Curcuruto et al, 2015).
Furthermore, future studies could examine the influence of proactive safety behaviours
152 Chapter 7: Discussion and Conclusions
on other performance measures that go beyond safety outcomes, such as company
reputation, job satisfaction, increased work engagement (Huang, Lee, McFadden,
Murphy, Robertson, Cheung & Zohar, 2016).
Lastly, the current program of research was primarily conducted using
quantitative methods. For instance, the item pool generation using the current literature
review, nominal group technique and the use of expert panel provided a deductive
approach to the development of the PSB-WD scale. However, using qualitative
methods to obtain opinions gathered from the target population could offer other
insights to the current findings. For instance, future studies could examine other
potential facilitators and barriers to engaging in proactive safety behaviours within the
work driving safety context through an in-depth qualitative investigation.
7.1.7 Concluding Remarks
Existing research and practice on work driving safety mostly focus on lagging
indicators and management of risks is often reactive, only conducting safety checks
once an incident has already occurred. The current program of research made
significant contributions to the current knowledge and industry practice within the
field of OHS by exploring the possible application of the proactive safety behaviour
construct within the context of work driving. This program of research is driven with
the proposition that, to improve safety while driving for work, employees and
management need to be proactive in addressing safety issues as opposed to just simply
following rules and regulations and reacting to crashes, violations and injuries.
Proactive safety behaviour as a measure of safety performance in the work driving
context could provide an alternative or complementary paradigm to current risk
management strategies.
The current exploratory investigation has provided theoretical and practical
contributions to the field of work driving safety by providing a model on how
organisations can engage their work drivers and management to be more proactive in
managing risks while driving for work. Furthermore, the research program also
provided a possible complementary measure that measure behaviour-based leading
indicators of safety for employees who drive for work. Driving for work involves high
risks, thus proactive safety behaviours may be necessary to encourage employees to
engage in activities going beyond compliance. Consequently, engaging in proactive
safety behaviours may vastly improve work driving safety.
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Research Part F: Traffic Psychology and Behaviour, 30, 84-96. doi:
https://doi.org/10.1016/j.trf.2015.01.014
Appendices 175
Appendices
Appendix A: Coding of Contextual and Proximal Antecedents
Antecedent Variable coded
Safety climate Safety climate, safety culture, perceived safety norms
Psychological safety climate No mentioned level
Group-level Group, co-worker, supervisor, employee, leaders
Organisational-level Organisational
Leadership
Transformational Transformational, LMX, motivate, concern, empowering, safety-specific transformational, ethical
Active transactional
Transactional, monitoring, instructing, safety-specific transformational
Passive Passive leadership
Perceived organisational support
Perceived organisational support, group process, interpersonal, teamwork, organisational concern for employees, supervisor support, positive and non-related job communication, social support, co-worker support
Organisational trust Trust, trust in management
Work Demands Risk, work overload, role overload, work hazards, hazard exposure, emotional demands, job demands
Work Autonomy Job autonomy, job control (but used autonomy as a definition)
Safety Motivation Safety motivation, expectation motivation, motivation, participation motivation, motivation to participate, intrinsic motivation
Safety Knowledge Safety knowledge, knowledge-related job characteristics, sufficiency of technical skills, knowledge
Regulatory focus
Promotion-focused Promotion focus, identified regulation, consideration of future consequences
Prevention-focused Prevention focus, external regulation
Self-efficacy Self-efficacy, perceived probability of success, core self-evaluation
Perceived control Perceived manageability of risks, empowerment, perceived behavioural control, safety control
176 Appendices
Appendix B: Proactive safety behaviours of work drivers item development
Definition of proactive safety behaviours:
1) Behaviours that create a work environment that promotes safety 2) Behaviours that aim to improve workplace safety that is self-starting (in
other words, cannot be forced). 3) Behaviours that are change-oriented which aims to improve the current
workplace safety practices Definition of work drivers: employees who drive for work at least once a week, including commute to and from work. Proactive safety behaviours within the work driving safety context: Behaviours that work drivers perform that create a work environment that promotes work driving safety. These behaviours must be self-starting (in other words, cannot be forced) and/or change-oriented (with an aim to improve the current work driving safety practices). The research team (Klaire Somoray, Darren Wishart and Cameron Newton) have identified SIX subscales that reflect this definition of proactive safety behaviours. These dimensions are: feedback inquiry, helping/volunteerism, changing the organisations’ policies and procedures, problem prevention, stewardship and voice (See figure below). The items that we have generated or revised from previous studies should reflect these dimensions.
Proactive Safety
Behaviours
Feedback Inquiry
Helping / Volunteerism
Changing Organisation's
Policies and Procedures
Problem Prevention
Stewardship
Voice
Appendices 177
INSTRUCTIONS FOR THE EXPERT PANEL: The following items were developed from previous research on proactive safety behaviours and similar constructs. The items have been revised to suit the work-driving context. We would like to ask you to evaluate these items depending on their content validity and the clarity of meaning. Please rate the content validity of each item, on the scale of 1 (low content validity) to 5 (high content validity) under the heading CV. Please also rate the clarity of each item on the scale of 1 (not clear) to 5 (very clear) under the heading Clarity. If you would like to add some comments regarding each item, please write them within the comments column. If you would like to add general comments, a wider comment section is provided at the end of each subscale (e.g., if there’s an additional item you can think of that fit this subscale, how the items should be re-worded, etc)
SUBSCALE: FEEDBACK INQUIRY Feedback Inquiry involves explicit verbal requests for feedback regarding the employees’ safety behaviours while driving for work. CV Clarity Comments 1 I actively seek feedback from my supervisor
about my work driving
2 I actively seek feedback from my co-workers about my work driving
3 I actively seek feedback about my work driving 4 When I experience a traffic incident or receive a
traffic offence when driving for work, I initiate the conversation to learn from my mistakes
5 I ask people at work about my driving General comments:
SUBSCALE: VOLUNTEERISM/HELPING Volunteering to carry out activities that are not formally part of their job as well as helping and cooperating with others to ensure the safety of other employees while driving for work. CV Clarity Comments 1 I volunteer to educate work driving safety
procedures to new drivers
2 I assist my co-workers to help them drive safely 3 I get involved in work driving safety activities to
help other workers drive safely
4 I volunteer to help other drivers learn more about safe work driving practices
178 Appendices
5 I volunteer to help other drivers with their work safety driving responsibilities
General comments:
SUBSCALE: CHANGING ORGANISATION’S POLICIES AND PROCEDURES Taking one’s initiative to change the organisational policies and procedures with an aim to improve the safety of work drivers. CV Clarity Comments 1 I take the initiative in improving work driving
safety procedures and policies
2 I take the initiative in setting up work driving safety objectives and/or improvement plans
3 I take the initiative in bringing about improved work driving safety procedures within my organisation
4 I try to change the way the job is done to make driving for work safer
5 I try to change work driving safety policies and procedures to make them safer
6 I provide suggestions to my supervisors to improve the safety of the employees while driving for work
7 I make suggestions to improve how work driving safety is handled in our organisation
8 I try to introduce new work driving safety policies that are more effective
9 I provide suggestions to improve employees' safety while driving for work
General comments:
SUBSCALE: PROBLEM PREVENTION Acting to prevent the re-occurrence of challenges and barriers to safety while driving for work CV Clarity Comments 1 When driving for work, I plan extra journey time
and breaks for bad weather, traffic congestion, etc.
2 When driving for work, I plan ahead to make sure I do not feel stressed when driving for work
3 I try to solve problems in ways that reduce risks associated with driving for work
Appendices 179
4 I solve potential issues that relate to driving for work
5 I try to implement solutions to solve urgent work driving safety issues
6 When I see a potential work driving safety hazard, I correct it myself if possible
7 If I see something unsafe, I go out of my way to take care of it
8 I fix safety issues that relates to work driving even if it is not my responsibility
9 If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisor or complete paperwork
10 When I see a vehicle that needs maintenance, I inform my supervisors about it
11 I volunteer to conduct work driving risk assessments
12 I volunteer to conduct journey planning 13 When I experience a near-miss event, I talk to
people at work to learn from the incident
General comments:
SUBSCALE: STEWARDSHIP Helping co-workers to ensure their safety while driving for work CV Clarity Comments 1 If I see my co-workers doing something risky
while driving for work (e.g., using their mobile phone or speeding), I talk to them about the hazards of their risky behaviours
2 I confront other coworkers about their unsafe behaviours while driving for work
3 I take action to stop safety violations of other drivers to improve work driving safety
4 I warn other coworkers about the dangers of driving unsafely
5 I inform new drivers that violations of safety procedures will not be tolerated
6 I talk to other drivers to follow safe work driving procedures
7 I encourage new drivers to follow safe working procedures
8 I go out of my way to look out for the safety of other drivers
9 I take action to protect other drivers from risky situations
10 I try to prevent other drivers from being injured on the job
General comments:
180 Appendices
SUBSCALE: VOICE Speaking up when you have work driving safety concerns CV Clarity Comments 1 I speak up with new ideas or changes in work
driving safety
2 I speak up and get involved with work driving safety issues that affect work drivers
3 I speak up about safety concerns during team meetings or toolbox talks
4 I speak up on work driving safety matters even if others disagree
5 I communicate my views about work driving safety issue, even if others would disagree
General comments:
Appendices 181
Appendix C: Participant Information Sheet for Pilot Study
PARTICIPANT INFORMATION FOR QUT RESEARCH PROJECT – Pilot Survey –
Beyond Compliance: The investigation of Proactive Safety Behaviours in the Work Driving
Context
QUT Ethics Approval Number 1600000824
RESEARCH TEAM Principal Researcher: Ms Klaire Somoray PhD student Associate Researchers: Dr Darren Wishart Principal Supervisor
Centre for Accident Research and Road Safety – Queensland (CARRS-Q)
Professor Cameron Newton Associate Supervisor School of Management, QUT Business School
Queensland University of Technology (QUT) DESCRIPTION This project is being undertaken as part of a PhD study investigating the proactive safety behaviours performed by workers in organisations that operate vehicle fleets. The purpose of this project is to examine the proactive safety behaviours within the work-related driving setting. Proactive safety behaviours are behaviours that individuals perform to ensure and/or to improve their safety and their coworkers’ while driving for work. These behaviours are above and beyond the employees’ official job’s description and organisational policies and procedures. The project aims: To understand what are the proactive safety behaviours and initiatives that workers engage in to improve their safety and of their co-workers’ while driving for work, that are beyond their formal role. To understand the factors that motivate and hinder proactive safety behaviours at work. To understand the consequences of engaging in proactive safety behaviours at work. You are invited to participate in this project because: Driving is an essential part of your job duties and You drive for work at least once a week. Supervisors, managers and work health and safety officers who also deals with work drivers as part of their jobs are also invited to participate in this project. PARTICIPATION Participation will involve completing an anonymous survey that will take approximately 20 to 30 minutes of your time.
182 Appendices
Questions will include: I get involved in work driving safety activities to help other workers drive safely I take the initiative in improving work driving safety procedures and policies I make suggestions to improve how work driving safety is handled in our organisation Your participation in this project is entirely voluntary. If you agree to participate, you do not have to complete any question(s) you are uncomfortable answering. Your decision to participate or not participate will not impact upon your current or future relationship with QUT, CARRS-Q or your organisation. If you do agree to participate, you can withdraw from the project without comment or penalty. However, as the survey is anonymous once it has been submitted it will not be possible to withdraw. EXPECTED BENEFITS It is expected that this project may not directly benefit you, but it may benefit the general community. The overall aim of the project is to improve employees’ safety while driving for work by understanding the proactive safety behaviours that work drivers may engage in and how we can encourage these behaviours in the workplace. RISKS There are minimal risks associated beyond normal day-to-day living associated with your participation in this project. The questions on this survey will focus on positive and proactive behaviours in the workplace as well as questions about your organisations’ safety climate, safety leadership, motivation and risk perception. If there are items that you are not comfortable in answering, you have the option to skip them. All information you provide will be treated as confidential and will not be shared. Any reports, findings or papers produced using data collected during this research project will only contain aggregate data (i.e. participants grouped together) in order to ensure no individual or identifying details are included. QUT provides for limited free psychology, family therapy or counselling services (face-to-face only) for research participants of QUT projects who may experience discomfort or distress as a result of their participation in the research. Should you wish to access this service please call the Clinic Receptionist on 07 3138 0999 (Monday–Friday only 9am–5pm), QUT Psychology and Counselling Clinic, 44 Musk Avenue, Kelvin Grove, and indicate that you are a research participant. Alternatively, Lifeline provides access to online, phone or face-to-face support, call 13 11 14 for 24 hour telephone crisis support. PRIVACY AND CONFIDENTIALITY All comments and responses are anonymous and will be treated confidentially unless required by law. The names of individual persons are not required in any of the responses. Any data collected as part of this project will be stored securely as per QUT’s Management of research data policy. Please note that non-identifiable data from this project may be used as comparative data in future projects or stored on an open access database for secondary analysis. CONSENT TO PARTICIPATE The return of the completed survey via mail or online is accepted as an indication of your consent to participate in this project.
Appendices 183
QUESTIONS / FURTHER INFORMATION ABOUT THE PROJECT If you have any questions or require further information please contact one of the listed researchers. Klaire Somoray k.somoray@qut.edu.au 07 3138 4909 Darren Wishart d.wishart@qut.edu.au 07 3138 4885 Cameron Newton cj.newton@qut.edu.au 07 3138 2523 CONCERNS / COMPLAINTS REGARDING THE CONDUCT OF THE PROJECT QUT is committed to research integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Advisory Team on 07 3138 5123 or email humanethics@qut.edu.au. The QUT Research Ethics Advisory Team is not connected with the research project and can facilitate a resolution to your concern in an impartial manner. THANK YOU FOR HELPING WITH THIS RESEARCH PROJECT. PLEASE PRINT THIS SHEET FOR YOUR INFORMATION.
184 Appendices
Appendix D: Proactive Safety Behaviours Pilot Survey
PROACTIVE SAFETY BEHAVIOURS AND WORK-RELATED DRIVING SAFETY
In partnership with your organisation, the Centre for Accident Research and Road Safety Queensland (CARRS-Q) at Queensland University of Technology (QUT) is currently doing a research project on work-related driving safety. The major component of the project is to understand the positive and proactive behaviours that work drivers and their supervisors perform to prevent accidents and unsafe practice while driving for work. The survey is strictly confidential and the research team will combine all the collected responses from the survey, therefore, your specific response will be anonymous. The survey should only take 20 to 30 minutes to complete. THANK YOU FOR YOUR ASSISTANCE. If you would like to participate in the study, consent is required. Please click the button below whether you would like to provide your consent to participate in this study. I would like to provide my conset to participate in this study (1) I do not want to participate in the study (2) INSTRUCTIONS For the following questions, please select the answer which BEST reflect your views and/or experiences. THE SURVEY WILL BE OPEN FOR 2 WEEKS, please complete the survey within this timeframe. Thank you.
Appendices 185
PLEASE NOTE: "Driving for work" includes driving for the purposes of work-related tasks (e.g., going to meetings, driving to see a client or a customer, driving to a work site for a job). This also INCLUDES commuting between work and home. Approximately, how many hours PER WEEK do you normally drive for work?
o 1 – 10 hours (1)
o 11 – 20 hours (2)
o 21 – 30 hours (3)
o 31 – 40 hours (4)
o 41 – 50 hours (5)
o 51 – 60 hours (6)
o 61 hours or more (7)
o I do not drive for work (8) Approximately, how many kilometres do you drive EACH YEAR for work?
o 1 – 10,000 kms (1)
o 10,001 - 20,000 kms (2)
o 20,001 - 30,000 kms (3)
o 30,001 - 40,000 kms (4)
o 40,001 - 50,000 kms (5)
o 50,001 - 60,000 kms (6)
o 60,001 kms or more (7)
o I do not drive for work (8)
186 Appendices
The following questions will ask some information about you and your work vehicle use. Are you?
o Male (1)
o Female (2) What is your age?
o Under 18 years old (1)
o 19 – 24 years old (2)
o 25 – 29 years old (3)
o 30 – 34 years old (4)
o 35 – 39 years old (5)
o 40 – 44 years old (6)
o 45 – 49 years old (7)
o 50 and above (8) How long have you had your driver’s licence?
o Less than 1 year (1)
o 1 – 5 years (2)
o 6 – 10 years (3)
o 11 – 15 years (4)
o 15 – 20 years (5)
o More than 20 years (6)
Appendices 187
How long have you been working for this organisation?
o Less than 1 year (1)
o 1 to 3 years (2)
o 4 to 6 years (3)
o More than 7 years (4) Which department of your organisation do you work for? What type of vehicle do you mainly drive for work?
o Car / Sedan / Wagon (1)
o SUV / 4WD (2)
o Heavy Vehicle (3)
o Other (please specify) (4) ________________________________________________
When driving for work, what type of road do you usually drive on?
o Asphalt / Bitumen roads (1)
o Dirt roads (2)
o Combination of Asphalt / Bitumen roads and Dirt roads (3)
o Other (please specify) (4) ________________________________________________
188 Appendices
The following questions will ask about your exposure to work-related driving risks. Before answering the questions, please read the definitions below: ‘Driving for work’ - includes driving for the purposes of work-related tasks. This INCLUDES commuting between work and home. ‘Crashes’ - any incident involving a motor vehicle that resulted in an injury or any damage to a vehicle or property. 'Near-miss' - any incident involving a motor vehicle where you narrowly avoided a collision with another vehicle or property. ‘Offences’ - any incident for which you were fined or incurred a loss of demerit points. This DOES NOT INCLUDE parking offences. In the last 12 months, how many crashes have you experienced while driving for work?
o None (1)
o One crash (2)
o Two crashes (3)
o Three or more crashes (4) In the last 12 months, how many near-misses have you experienced while driving for work?
o None (1)
o One near-miss (2)
o Two near-misses (3)
o Three or more near-misses (4) In the last 12 months, how many traffic offences have you experienced while driving for work?
o None (1)
o One traffic offence (2)
o Two traffic offences (3)
o Three or more traffic offences (4)
Appendices 189
The following questions will ask you about some behaviours that you may perform at work.
Nev
er
So
met
imes
Ab
ou
t h
alf
of
the
tim
e
Mo
st o
f th
e
tim
e
Alw
ays
I actively seek feedback from my supervisor about my work driving. 1 2 3 4 5
I actively seek feedback from my co-workers and passengers about my work driving. 1 2 3 4 5
I actively seek feedback about my work driving with people at work. 1 2 3 4 5
When I experience a traffic incident or receive a traffic offence when driving for work, I initiate the conversation to learn from my mistakes. 1 2 3 4 5
I ask people at work about my driving. 1 2 3 4 5
I volunteer to educate work driving safety procedures to new drivers. 1 2 3 4 5
I assist my co-workers to help them drive safely. 1 2 3 4 5
I get involved in work driving safety programs and activities to help other workers drive safely. 1 2 3 4 5
I volunteer to help other workers learn more about safe work driving practices. 1 2 3 4 5
I volunteer to help other drivers with their work safety driving responsibilities. 1 2 3 4 5
I take the initiative in improving work driving safety policies and procedures. 1 2 3 4 5
I take the initiative in setting up work driving safety objectives and/or improvement plans within my organisation. 1 2 3 4 5
190 Appendices
I take the initiative in bringing about improved work driving safety procedures within my organisation. 1 2 3 4 5
I provide suggestions to my supervisors to improve the safety of the employees while driving for work. 1 2 3 4 5
I change work driving safety policies and procedures to make them safer. 1 2 3 4 5
I make suggestions to improve how work driving safety is handled in our organisation. 1 2 3 4 5
I introduce new work driving safety policies that are more effective. 1 2 3 4 5
I provide suggestions to improve employees' safety while driving for work. 1 2 3 4 5
When driving for work, I plan extra journey time and breaks for bad weather, traffic congestion, etc. 1 2 3 4 5
I plan ahead to make sure I do not feel stressed when driving for work. 1 2 3 4 5
I resolve problems in ways that reduce the risks associated with driving for work. 1 2 3 4 5
I implement solutions to solve safety issues that relate to driving for work. 1 2 3 4 5
When I see a potential work driving safety hazard, I do my best to fix it. 1 2 3 4 5
If I see something unsafe, I go out of my way to take care of it. 1 2 3 4 5
I fix safety issues that relates to work driving even if it is not my responsibility. 1 2 3 4 5
If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisors or completing paperwork. 1 2 3 4 5
When I see a vehicle that needs maintenance, I inform my supervisors or the appropriate person about it. 1 2 3 4 5
When I experience a near-miss event, I talk to people at work to learn from the incident. 1 2 3 4 5
Appendices 191
If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I talk to them about the hazards of their risky behaviours. 1 2 3 4 5
I would intervene if I see a co-worker doing something unsafe while driving for work. 1 2 3 4 5
I would intervene to stop safety violations of other drivers. 1 2 3 4 5
I encourage my co-workers to think about the dangers of driving unsafely. 1 2 3 4 5
I inform other drivers that violations of safety procedures will have negative consequences. 1 2 3 4 5
I encourage other drivers to follow safe work driving procedures. 1 2 3 4 5
I encourage new drivers to follow safe working procedures. 1 2 3 4 5
I go out of my way to look out for the safety of other drivers. 1 2 3 4 5
I take action to protect other drivers from risky situations. 1 2 3 4 5
I speak up with new ideas or changes in work driving safety. 1 2 3 4 5
I speak up about work driving safety issues that affect work drivers. 1 2 3 4 5
I speak up about safety concerns during team meetings or toolbox talks. 1 2 3 4 5
I speak up on work driving safety matters even if others might disagree. 1 2 3 4 5
I communicate my views about work driving safety issue, even if others would disagree. 1 2 3 4 5
192 Appendices
Appendix E: Participant Information Sheet for the Main Survey
PARTICIPANT INFORMATION FOR QUT RESEARCH PROJECT – Main Survey –
Beyond Compliance:
The investigation of Proactive Safety Behaviours in the Work Driving Context
QUT Ethics Approval Number 1600000824
RESEARCH TEAM
Principal Researcher: Ms Klaire Somoray PhD student Associate Researchers: Dr Ioni Lewis Principal Supervisor
Centre for Accident Research and Road Safety – Queensland (CARRS-Q)
Professor Cameron Newton Associate Supervisor School of Management, QUT Business School
Queensland University of Technology (QUT) Dr Darren Wishart External Supervisor
DESCRIPTION This project is being undertaken as part of a PhD study investigating the proactive safety behaviours performed out by workers in organisations that operate vehicle fleets. The purpose of this project is to examine the proactive safety behaviours within the work-related driving setting. Proactive safety behaviours are behaviours that individuals perform to ensure and/or to improve their safety and their coworkers’ while driving for work. These behaviours are above and beyond the employees’ official job’s description and organisational policies and procedures. You are invited to participate in this project because: i) driving is an essential part of your job duties and ii) you drive for work at least once a week. Supervisors, managers and work health and safety officers who also deals with work drivers as part of their jobs are also invited to participate in this project. PARTICIPATION Participation will involve completing an anonymous survey with Likert scale answers that will take approximately 25 – 30 minutes of your time. Questions will include: I encourage other drivers to follow safe working procedures. I fix safety issues that relates to work driving even if it is not my responsibility. I communicate my views about work driving safety issue, even if others would disagree. Your participation in this project is entirely voluntary. If you agree to participate, you do not have to complete any question(s) you are uncomfortable answering. Your decision to participate or not participate will in no way impact upon your current or future relationship with QUT, CARRS-Q or your organisation. If you do agree to participate, you can withdraw from the project without comment or penalty. However, as the survey is anonymous once it has been submitted it will not be possible to withdraw.
Appendices 193
EXPECTED BENEFITS It is expected that this project may not directly benefit you, but it may benefit the general community. The overall aim of the project is to improve employees’ safety while driving for work by understanding the proactive safety behaviours that work drivers may engage in and how we can encourage these behaviours in the workplace. To recognise your contribution the research team is offering the chance to win one of ten $100 Coles/Myer gift vouchers for completing the survey. Please note the opening date for entries for the first survey is 27th November 2017, the closing date for entries is 27th of February 2018. The Terms and Conditions of the prize draw can be located at: https://survey.qut.edu.au/survey-data/67/67667/media/62/6254.pdf RISKS There are minimal risks associated beyond normal day-to-day living associated with your participation in this project. The questions on this survey will focus on positive and proactive behaviours in the workplace as well as questions about your organisations’ safety climate, safety leadership, motivation and risk perception. If there are items that you are not comfortable in answering, you have the option to skip them. All information you provide will be treated as confidential and will not be shared. Any reports, findings or papers produced using data collected during this research project will only contain aggregate data (i.e. participants grouped together) in order to ensure no individual or identifying details are included. QUT provides for limited free psychology, family therapy or counselling services (face-to-face only) for research participants of QUT projects who may experience discomfort or distress as a result of their participation in the research. Should you wish to access this service please call the Clinic Receptionist on 07 3138 0999 (Monday–Friday only 9am–5pm), QUT Psychology and Counselling Clinic, 44 Musk Avenue, Kelvin Grove, and indicate that you are a research participant. Alternatively, Lifeline provides access to online, phone or face-to-face support, call 13 11 14 for 24 hour telephone crisis support. PRIVACY AND CONFIDENTIALITY All comments and responses are anonymous and will be treated confidentially unless required by law. The names of individual persons are not required in any of the responses. Any data collected as part of this project will be stored securely as per QUT’s Management of research data policy. Please note that non-identifiable data from this project may be used as comparative data in future projects or stored on an open access database for secondary analysis. CONSENT TO PARTICIPATE The return of the completed survey via mail or online is accepted as an indication of your consent to participate in this project. QUESTIONS / FURTHER INFORMATION ABOUT THE PROJECT If you have any questions or require further information please contact one of the listed researchers. Klaire Somoray k.somoray@qut.edu.au 07 3138 4909 Ioni Lewis i.lewis@qut.edu.au 07 3138 4966
194 Appendices
Cameron Newton cj.newton@qut.edu.au 07 3138 2523 CONCERNS / COMPLAINTS REGARDING THE CONDUCT OF THE PROJECT QUT is committed to research integrity and the ethical conduct of research projects. However, if you do have any concerns or complaints about the ethical conduct of the project you may contact the QUT Research Ethics Advisory Team on 07 3138 5123 or email humanethics@qut.edu.au. The QUT Research Ethics Advisory Team is not connected with the research project and can facilitate a resolution to your concern in an impartial manner. THANK YOU FOR HELPING WITH THIS RESEARCH PROJECT. PLEASE PRINT THIS SHEET FOR YOUR INFORMATION.
Appendices 195
Appendix F: Main Survey
PROACTIVE SAFETY BEHAVIOURS AND WORK-RELATED
DRIVING The Centre for Accident Research and Road Safety Queensland (CARRS-Q) at Queensland University of Technology (QUT) is currently doing a research project on work driving safety. A major component of the project is to understand the positive and proactive behaviours that work drivers and their supervisors perform in order to ensure employees' safety while driving for work. The questionnaire is strictly confidential and the research team will combine all the collected responses, therefore, your specific response will be anonymous. The questionnaire should only take 25 to 30 minutes to complete. THANK YOU FOR YOUR ASSISTANCE. If you would like to participate in the study, consent is required. Please indicate whether you are providing your consent to participate in this study:
Yes, I would like to provide my consent to participate in the study
No, I do not want to participate in the study
INSTRUCTIONS For each of the following questions, please select the answer which BEST reflects your views and/or experiences. Please indicate your answer by circling the best choice that corresponds with your opinions or by writing your answer in the space provided. Thank you.
196 Appendices
PLEASE NOTE: "Driving for work" includes driving for the purposes of work-related tasks (e.g., going to meetings, driving to see a client or a customer, driving to a work site for a job). This also INCLUDES commuting between work and home.
1. The following questions will ask about your work driving exposure. Please circle one number from 1 to 8: Approximately, how many hours PER WEEK do you normally drive for work?
1 – 10 hours ........................ 11 – 20 hours ...................... 21 – 30 hours ...................... 31 – 40 hours ...................... 41 – 50 hours ...................... 51 – 60 hours ...................... 61 hours or more ................. I do not drive for work ..........
1 2 3 4 5 6 7 8
Approximately, how many kilometres do you drive EACH YEAR for work?
1 – 10,000 kms .................... 10,001 - 20,000 kms ........... 20,001 - 30,000 kms ........... 30,001 - 40,000 kms ........... 40,001 - 50,000 kms ........... 50,001 - 60,000 kms ........... 60,001 kms or more ............ I do not drive for work ..........
1 2 3 4 5 6 7 8
If choose “I do not drive for work”, we thank you for your interest in the survey; however, at the present time, we are looking for participants who currently drive for work purposes. As such, we ask that you please do not continue with the survey. Thank you.
Appendices 197
2. The following questions will ask some information about you and your
work vehicle use
Are you? Male ......................................................................... Female .....................................................................
1 2
What is your age (in years)?
____________________ (years old)
How long have you held your driver’s licence (in years)?
____________________ (years)
How long have you been working for this organisation (in years)?
____________________ (years)
What type of vehicle do you mainly drive for work?
Car/ Sedan/Wagon .................................................. 4WD/SUV ................................................................ Heavy Vehicle .......................................................... Other (please specify____________________)
1 2
3
4
When driving for work, in a typical week, where do you do most of this driving?
Asphalt/Bitumen Roads ........................................... Dirt Roads ................................................................ Combination of Asphalt/Bitumen Roads and Dirt Roads ...................................................................... Other (please specify____________________)
1 2
3
4
5
198 Appendices
3. The following questions will ask about your exposure to work-related driving risks. Before answering the questions, please read the definitions below:
‘Driving for work’ - includes driving for the purposes of work-related
tasks. This INCLUDES commuting between work and home.
‘Crashes’ - any incident involving a motor vehicle that resulted in an injury or any damage to a vehicle, property or person (pedestrian).
'Near-miss' - any incident involving a motor vehicle where you narrowly avoided a collision with a vehicle, property or person (pedestrian).
‘Offences’ - any incident for which you were fined or incurred a loss of demerit points. This DOES NOT INCLUDE parking offences.
In the past 12 months, how many crashes have you experienced while driving for work?
None ....................................................................... One crash ............................................................... Two crashes ........................................................... Three or more crashes ...........................................
1 2
3
4
In the last 12 months, how many near-misses have you experienced while driving for work?
None ....................................................................... One near-miss ........................................................ Two near-misses .................................................... Three or more near-misses ....................................
1 2
3
4
In the last 12 months, how many traffic offences have you experienced while driving for work?
None ....................................................................... One traffic offence .................................................. Two traffic offences ................................................ Three or more traffic offences ................................
1 2
3
4
Appendices 199
4. The following questions will ask you about some behaviours that you may perform at work.
Please circle one number for each item from 1 = “Never” to 5 = “Always” N
ever
Rar
ely
So
met
imes
Mo
st o
f th
e
tim
e
Alw
ays
I speak up about safety concerns during team meetings or toolbox talks.
1 2 3 4 5
I speak up about work driving safety issues that affect work drivers even if it makes me unpopular.
1 2 3 4 5
I communicate my views about work driving safety issue, even if others would disagree.
1 2 3 4 5
I go out of my way to educate new employees about work driving safety procedures.
1 2 3 4 5
I go above my duties to help other drivers with their work driving safety responsibilities.
1 2 3 4 5
I go out of my way to help other drivers learn more about safe work driving practices.
1 2 3 4 5
I go above my duties to help my co-workers drive safely.
1 2 3 4 5
I actively seek feedback from my supervisor about my work driving.
1 2 3 4 5
I actively seek feedback from my co-workers and passengers about my work driving.
1 2 3 4 5
I ask people at work for feedback about my driving.
1 2 3 4 5
I encourage new drivers to follow safe working procedures.
1 2 3 4 5
I inform other drivers that violations of safety procedures will have negative consequences.
1 2 3 4 5
I encourage other drivers to follow safe working procedures.
1 2 3 4 5
When I experience safety issues while driving for work, I resolve these problems.
1 2 3 4 5
I implement solutions to solve safety issues that relate to driving for work.
1 2 3 4 5
When I see a potential safety hazard while driving for work, I resolve it by finding a solution.
1 2 3 4 5
When driving for work, I plan extra journey time and breaks for bad weather, traffic congestion, etc.
1 2 3 4 5
I fix safety issues that relate to work driving even if it is not my responsibility.
1 2 3 4 5
If I see something unsafe, I go out of my way to take care of it.
1 2 3 4 5
I go above my duties to resolve driving safety issues at work.
1 2 3 4 5
200 Appendices
If I notice a defect in the vehicle I am driving, I take an appropriate action by notifying my supervisors or completing the paperwork.
1 2 3 4 5
When I see a vehicle that needs maintenance, I inform my supervisors or the appropriate person about it.
1 2 3 4 5
I make sure that vehicle defects are attended to quickly.
1 2 3 4 5
I take action to protect other drivers from risky situations.
1 2 3 4 5
I go out of my way to look out for the safety of other drivers.
1 2 3 4 5
I look after the safety of other drivers in my organisation.
1 2 3 4 5
I would intervene if I saw a co-worker doing something unsafe while driving for work.
1 2 3 4 5
If I see my co-workers doing something risky while driving for work (e.g., using their mobile phone or speeding), I would intervene.
1 2 3 4 5
I would intervene to stop safety violations of other drivers.
1 2 3 4 5
I follow the work driving safety policies and procedures.
1 2 3 4 5
I attend mandatory meetings or toolbox talks for work driving safety.
1 2 3 4 5
I comply with the organisation’s rules and regulations on work driving safety.
1 2 3 4 5
I go to the required training and education programs on driving safety provided by my organisation. 1 2 3 4 5
Appendices 201
In your job role, do you supervise a work driver? Yes No If you answered YES, please complete the questions on the next page under the section named SUPERVISORS. If you answered NO, please stay on this page and answer the questions under the section named WORK DRIVERS.
WORK DRIVERS
5a. The following questions will ask about your relationship with your supervisors. When answering the following questions, think about the supervisor who is responsible for the daily management of your work driving (e.g., the one who you report to regarding your driving for work).
Please indicate how strongly do you agree or disagree with the following statements. S
tro
ng
Dis
agre
e
Dis
agre
e
Neu
tral
Ag
ree
Str
on
gly
Ag
ree
I usually know where I stand with my supervisor.
1 2 3 4 5
My supervisor understands my job problems and needs.
1 2 3 4 5
My supervisor recognises my potential.
1 2 3 4 5
Regardless of how much formal authority my supervisor has, he or she would personally help me solve problems in my work.
1 2 3 4 5
I can count on my supervisor to help me out even at his or her own expense, when I really need it.
1 2 3 4 5
My supervisor has enough confidence in me that he or she would defend and justify my decisions even if I am not present to do so.
1 2 3 4 5
My working relationship with my supervisor is effective.
1 2 3 4 5
202 Appendices
SUPERVISORS
5b. The following questions will ask about your relationship with work drivers that you supervise. When answering the following questions, think about the work drivers whom you are responsible for.
Please indicate how strongly do you agree or disagree with the following statements. S
tro
ng
Dis
agre
e
Dis
agre
e
Neu
tral
Ag
ree
Str
on
gly
Ag
ree
The work drivers that I supervise usually know where they stand with me.
1 2 3 4 5
I understand the problems and needs of my work drivers.
1 2 3 4 5
I recognise the potential of my work drivers.
1 2 3 4 5
Regardless of how much formal authority I have, I would personally help my work drivers with their work problems.
1 2 3 4 5
I would use my formal authority to help my work drivers, even at my own expense.
1 2 3 4 5
I have enough confidence in my work drivers that I would support their decisions.
1 2 3 4 5
I have an effective relationship with the work drivers that I supervise.
1 2 3 4 5
Halfway there!
6. The following questions will ask you about your organisation's views on safety while driving for work. The first part will ask about your company as a whole and the next part will ask questions about the supervisors who you report to regarding your work driving.
Please indicate how often you experience the following situations. N
ever
Rar
ely
So
met
imes
Mo
st o
f th
e t
ime
Alw
ays
My company….
…reacts quickly to solve the problem when told about work driving safety concerns.
1 2 3 4 5
…is strict about driving safely even when work tasks fall behind schedule.
1 2 3 4 5
Appendices 203
…listens carefully to workers’ ideas about improving work driving safety.
1 2 3 4 5
...invests a lot in work driving safety training for workers.
1 2 3 4 5
…uses any available information to improve existing work driving safety rules.
1 2 3 4 5
…tries to continually improve driving safety levels in each department.
1 2 3 4 5
If you are a work driver, think about your direct supervisors (who are responsible for your work driving) and answer how often they do the following. If you are a supervisor for a work driver, think about the management-level and answer how often they do the following. N
ever
Rar
ely
So
met
imes
Mo
st o
f th
e t
ime
Alw
ays
My supervisors or the supervisors in my company…
...have discussions with employees on how to improve safety while driving for work.
1 2 3 4 5
…compliment employees who pay special attention to work driving safety.
1 2 3 4 5
…are strict about driving safely even when workers are tired or stressed.
1 2 3 4 5
…frequently talk about work driving safety issues throughout the work week.
1 2 3 4 5
…are strict with driving safety rules even when work falls behind schedule.
1 2 3 4 5
…uses explanations (not just compliance) to get employees to act safely while driving for work.
1 2 3 4 5
7. The following questions will ask you about your general feelings towards safety while driving for work.
Please indicate how strongly do you agree or disagree with the following statements. S
tro
ng
Dis
agre
e
Dis
agre
e
Neu
tral
Ag
ree
Str
on
gly
Ag
ree
I anticipate risks or safety problems when driving for work, thinking of the possible alternative scenarios if problems arise.
1 2 3 4 5
I look at work driving safety issues from different perspectives to find appropriate solutions.
1 2 3 4 5
204 Appendices
Please indicate how strongly do you agree or disagree with the following statements. S
tro
ng
Dis
agre
e
Dis
agre
e
Neu
tral
Ag
ree
Str
on
gly
Ag
ree
Even before crashes happen, I think about various risky situations that may compromise safety when driving for work.
1 2 3 4 5
I look ahead to ensure that safety issues relating to driving for work are addressed.
1 2 3 4 5
I recognise that I am able to make significant contributions to the work driving safety within my department.
1 2 3 4 5
I recognise that I have an influence on matters that relate to work driving safety.
1 2 3 4 5
I recognise that my own actions have great importance for the driving safety of the work team.
1 2 3 4 5
I recognise that most of the safety problems that occurs while driving for work are under one’s own control.
1 2 3 4 5
I strive hard to be an example of someone who has strong commitment to work driving safety.
1 2 3 4 5
I feel that it's my responsibility to discuss work driving safety issues with my co-workers.
1 2 3 4 5
I feel responsible for taking the initiative in suggesting improvements to workers' safety while driving for work.
1 2 3 4 5
I depend on me to make improvements to my organisation's work driving safety.
1 2 3 4 5
I follow the work driving safety rules and regulations set by my organisation to avoid getting in trouble.
1 2 3 4 5
I try to avoid making mistakes or violating rules when driving for work because I do not want to get in trouble.
1 2 3 4 5
I follow the rules when driving for work because I do not want to get caught.
1 2 3 4 5
Appendices 205
Appendix G: Collection Method - Online versus Hardcopies
Online (n =
219) Hardcopy (n =
75)
BCa 95% Confidence
Interval M SD M SD t df p-value Lower Upper
Educate 14.36 5.79 13.27 5.07 1.67 142.16 0.107 -0.33 2.52
Voice 8.84 3.60 9.52 3.39 -1.31 289.00 0.181 -1.55 0.33
Fixing Safety
Issues 13.43 4.46 13.71 3.54 -0.53 156.95 0.617 -1.26 0.78
Vehicle
Maintenance 11.88 3.60 13.11 1.91 -3.67 238.76 0.001 -1.84 -0.55
Feedback Inquiry 5.73 3.29 4.81 2.25 2.98 191.52 0.003 0.33 1.64
Intervene 10.65 3.18 11.47 2.53 -1.91 289.00 0.037 -1.51 -0.04
Notes. N = 294; Analysis was conducted using independent sample t-test; df = degrees of freedom; BCa = Bootstrap Confidence Intervals based on 10,000 samples; highlighted cells indicate statistically significant differences based on exclusion of zero between the lower and upper intervals
206 Appendices
Appendix H: Gender differences (male versus female) on proactive safety
behaviours
Male Female
BCa 95% Confidence
Interval M SD M SD t df p-value Lower Upper
Educate 14.71 5.67 13.48 5.54 1.92 291.00 0.041 -0.09 2.57
Voice 9.06 3.46 8.97 3.66 0.28 291.00 0.755 -0.69 0.88
Fixing Safety
Issues 13.52 4.31 13.48 4.18 0.10 291.00 0.914 -0.86 0.94
Vehicle
Maintenance 12.41 3.28 11.98 3.30 1.17 291.00 0.202 -0.33 1.16
Feedback
Inquiry 5.92 3.30 5.09 2.80 2.43 279.41 0.011 0.11 1.51
Intervene 10.77 3.13 10.95 2.97 -0.47 291.00 0.623 -0.78 0.44
Notes. N = 294; Analysis was conducted using independent sample t-test; df = degrees of freedom; BCa = Bootstrap Confidence Intervals based on 10,000 samples; highlighted cells indicate statistically significant differences based on exclusion of zero between the lower and upper intervals
Appendices 207
Appendix I: Supervisory role differences on proactive safety behaviours
Has a supervisor
role (n = 31) No supervisor role
(n = 263)
BCa 95% Confidence
Interval M SD M SD t df p-value Lower Upper
Educate 17.58 5.41 13.67 5.52 3.74 292.00 0.001 1.73 6.00
Voice 11.10 3.11 8.76 3.53 3.52 292.00 0.001 1.16 3.44
Fixing Safety
Issues 15.45 3.95 13.27 4.22 2.74 292.00 0.002 0.64 3.68
Vehicle
Maintenance 13.42 2.78 12.05 3.33 2.21 292.00 0.014 0.10 2.43
Feedback Inquiry 7.23 3.80 5.29 2.93 3.36 292.00 0.009 0.55 3.39
Intervene 12.81 2.26 10.63 3.05 4.87 44.04 0.001 1.25 3.04
Notes. N = 294; Analysis was conducted using independent sample t-test; df = degrees of freedom; BCa = Bootstrap Confidence Intervals based on 10,000 samples; highlighted cells indicate statistically significant differences based on exclusion of zero between the lower and upper intervals
208 Appendices
Appendix J: Differences on proactive safety behaviour scores based on the
frequently used road type when driving for work
Asphalt / Bitumen roads
(n = 249) Combination
(n = 39)
BCa 95% Confidence
Intervals
M SD M SD t df p-value Lower Upper
Educate 13.68 5.60 16.28 5.17 4.74 286 0.006 -4.42 -0.79
Voice 8.71 3.57 10.74 2.94 6.03 286 0.001 -3.00 -0.97
Fixing Safety
Issues 13.30 4.29 14.67 3.86 1.79 286 0.036 -2.70 -0.10
Vehicle
Maintenance 12.03 3.44 13.26 1.98 3.02 79.51 0.002 -2.03 -0.46
Feedback
Inquiry 5.30 2.97 6.41 3.41 5.61 286 0.051 -2.33 -0.01
Intervene 10.84 3.00 11.18 3.26 0.26 286 0.550 -1.41 0.83
Notes. N = 294; Analysis was conducted using independent sample t-test; df = degrees of freedom; BCa = Bootstrap Confidence Intervals based on 10,000 samples; highlighted cells indicate statistically significant differences based on exclusion of zero between the lower and upper intervals
Appendices 209
Appendix K: Differences on proactive safety behaviour scores based on the
frequently used vehicle when driving for work
Car / Sedan /
Wagon (n = 178) SUV / 4WD
(n = 79) Heavy Vehicle
(n = 20)
M SD M SD M SD F df p-value
Educate 13.49 5.74 14.38 5.66 16.15 3.48 2.69 3 0.05
Voice 8.26 3.62 9.77 3.24 10.55 2.35 8.79 3 0.00
Fixing Safety Issues 13.08 4.39 14.03 4.05 14.80 3.58 1.68 3 0.17
Vehicle Maintenance 11.53 3.71 13.04 2.24 13.25 2.45 6.95 3 0.00
Feedback Inquiry 5.48 3.19 5.29 2.77 5.70 2.89 0.66 3 0.58
Intervene 10.74 3.19 11.18 2.91 10.50 3.05 0.53 3 0.67
Notes. N = 294; Analysis is conducted using one-way ANOVA; df = degrees of freedom; highlighted cells indicate statistically significant differences between groups
210 Appendices
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