Modelling The Resilience Capability In E-government

Using Human Centric Approach

A Case Study In Malaysia Public Sector

Nurul Aisyah Sim Binti Abdullah

CS990

Supervisor : Prof. Dr. Noor Laila Mohd Noor

Co Supervisor : Dr. Emma Nuraihan Mior Ibrahim

Service availability

and accessibility

High speed, can

access anytime any

whereProvide services Use the service

Service

Continuity

Issue

Research Outline

1. Research Roadmap

2. Background Study

3. Problem Statement

4. Preliminary Study Result

5. Research Questions and Objectives

6. Research Scope & Limitations

7. Research Methodology

8. Findings and Discussions

9. Contributions

10. Future Works

11. Publications

Review the literature

Conduct preliminary

study

Research Framework

and hypothesis

development

Research design

Measurement and

question- questionnaire

development

Study 2 Study 3

Problem Formulation

Research Approach

(Creswell, 1994, 2003,

Sekaran, 2013)

Research Roadmap

Data collection

Study 1

Understanding research background, issue,

gap, problem and establishing research

domain

Confirmation of the actual issue and the

problems in the domains studied

Identify the theory to refer to determine the

exogenous, endogenous variable,

independent, dependent variable and Identify

the hypothesis statements

Conference paper, ICRIIS, 2013

Conference paper

(PACIS 2014),

Conference paper

(CONF-IRM 2016)

Develop measurements attribute of variables, pilot

study, identify the goodness of measures, identify

the internal consistency and stability of measures

Formulate the research problem Identify

research objectives, scope and produce

research proposal

Determine the most suitable research design and

paradigm

Publications

Identify sampling strategy

Identify respondent

Data analysis Testing

and Evaluation

Identify the character, relationship and patterns of

the phenomena under studies

Identified Model

GeneralizationValidate model

Interpretation of the findings

Discussion on the implication of the findings

Journal (TGPPP 2016)

Definition of Terms

E-government

• the delivery of government information and services via the Internet or other digital means to citizens or businesses or other governmental agencies (Palvia & Sharma, 2007)

Business Continuity Management (BCM)

• is a holistic management process that is used to ensure that operations continue and services are delivered at predefined levels (ISO 22301, 2012)

Resilience

• refers to the maintenance of positive adjustments under challenging conditions (Karl E Weick, Sutcliffe, & Obstfeld, 1999). Introduce by Holling (1973).

• is a growing area of interest within BCM (Burnard & Bhamra, 2011).

• is emerging as a new paradigm where “success” is based on the ability of human to anticipate the changing shape of risk before, during, and after failures (Hollnagel & Woods, 2006)

• Literature perceived resilience as a human-centric approach where it is based on ability of an individual when aggregated to organizational level, which could define the organization resilience capability (Cynthia a. Lengnick-Hall et al., 2011).

• The theoretical and practical knowledge on resilience is still being researched (Wukich, 2013) and empirical literature on resilience is scarce(Barasa, Mbau, & Gilson, 2018)

Resilience capability

• The ability to absorb, ability to adapt and ability to recover in response to unintended event, change or disaster (Abdullah et al., 2013)

Background Study

Background Study

Approach toward service availability & continuity:

Risk Management

Business Continuity Management

Resilience as new safety paradigm based on human ability to organize and adapt

Preliminary study

Prevention/Mitigation Strategy

Theory of Plan Behaviour (TPB)

understanding human

behaviour - triadic reciprocal

determinism explain why

people engage in certain conduct

Resilience Capability Model

resilience element (organizational factor, personal quality, capability factor and person-environment setting factor) antecendant of intention-to-organize (Self

organize, process organize and technology organize) which acts as the main predictor to resilience capability (ability to absorb, adapt and recover)

provide a conceptual

frameworks for the study of

human action for predictionCapability for resilience -Resilience Construct

Resilience Theory (RT)Social Cognitive Theory

(SCT)

E-government Service Continuity & Availability

Risk Management Resilience OrganizationBusiness Continuity Management

Proses Identify threat and manage risk to be within its

risk appetite by installing mitigation action (Hiles,

2010). The goal - to reduce the impact of risk. Focus on

what going wrong

Framework for identifying an organization's risk of

exposure and prepare a strategy for recovery to

survive. The goal – ensure the ability to effectively

respond to threats. Focus on what going wrong

Recovery Strategy

The ability to organize and adapt to maintenance of

positive adjustments under challenging conditions and

respond to environmental change and uncertainty.

Focus on what Going right.

success” is based on the ability of human to anticipate

the changing shape of risk before, during, and after

failures occur (Hollnagel & Woods, 2006)

Basic Concept of Resilience - Resilience Definition

Element Of resilience -derived from a complex interplay of personal

quality, person-environment setting and environmental factors .

Problem Statement

“the number of disaster events is increasing and Asia recorded the highest and widest

technological disaster in the region”, (The OFDA/CRED - International Disaster Database

(2012).

• Focused on

Process and

technology-based

solutions limiting

the spectrum to

process and

technological

approach, and the

lack attention

given to the

human factor (Pitt

& Goyal, 2004,

Business

Continuity

Institute, 2010,

Hollnagel, 2009;

Hollnagel,

Leonhardt, Licu,

& Shorrock,

2013).

• the current RM

and BCM

approach is not

sufficient to

ensure the

survival of an

organization

(Sawalha, 2011;

Erik Hollnagel &

Woods, 2006;

Boehmer, 2009)

Vulnerable

and

Focus on

Risk Management and Busines Continuity -

Develop policy, standard and guideline in

related to IT security and service continuity

Install Alternatif Site, prevention,

avoidance, detection and prediction

mechanism

CURRENT APPROACH

RESILIENCE THEORY

Leads to

Reorganize

Adapt

The absence of human-approach and the emerging of

resilient concept for coping with disruption in dynamic,

unpredictable and complex environment suggests that

there is an impending need for a study to produce a

Resilience Capability Model that outlines the

underlying concept which will allow the organization to

develop capacity for resilience. This Resilience

capability model is targeted to be used by government

to build an organization resilient through strategic

human management.

Preliminary Study

Critical service disrupted

Total Yes No

Fully implement E-

government

Count 128 39 167

% of Total 65.6 20.0 85.6

Partially implement E-

government

Count 11 17 28

% of Total 5.6 8.7 14.4

Total Count 139 56 195

% of Total 71.3 28.7 100.0

• 85.6% fully utilized IT & 14.4% utilize IT in the delivery of certain services

• Out of the 85.6% agencies that fully utilized IT, 65.6% of the agencies indicated

that the critical service had disrupted compare to 14.4% of the agencies partially

utilized IT in deliver their critical service, only 5.6% indicate that their critical

service had disrupted

Frequency Percent

Always 3 1.5

Very Often 27 13.8

Sometimes 107 54.9

Rare 46 23.6

Never 12 6.2

Total 195 100.0

• Respondents indicated that the cumulative frequency of E-government disruptions

is 70% which is alarming

• The respondents indicated that the causes of disruptions are due to human error

(53.8%), process (50.8%), technology failure (42.15) and natural disaster (7.7%

• Further analysis showed an interesting situation where the respondents agreed

that the main contribution to E-government disruptions were due to the human

component, but the most attention on E-government implementation was given to

the technology component.

• The result is consistent with other related study that generally believe that

between 30% and 80% of incidents are due to human failure (Whittingham, 2008;

Reason, 2013).

Research Questions and Objectives

Research Questions Research Objectives

1. How to model the resilience capability in

e-government using human centric

approach in Malaysian public sector?

1. To identify the human centric antecedent

factor that would influence the formation of

resilience E-government

2. To model the resilience capability in E-

government;

3. To validate the E-Government resilience

capability model.

Research Scope and limitationIntention-to-organize

• This research limit the focus of the source of resilience to only human factor which

refer to people and the organization environment because they are the most important

element in developing capacity for resilience

• Others factor were not included in the study due to their minimal influence on the

consolidation of resilience

• To be generalize, this research will not cover the elements that hinder or limit the

resilience capability.

Demand model

Technology ProcessPeople (Self)

3 critical dimensions information

security framework

Resilience is derived

from a complex interplay

of personal and

environmental factors

(Allan et al., 2012)

Element Of Resilience

Resilience

Research Methodology

Research Question Research

Objectives

Research Method Research Outcome Research

Contribution1. How to model the

resilience

capability in e-

government using

human-centric

approach in

Malaysian public

sector?

1. To identify the

human-centric

antecedent factor

that would

influence the

formation of

resilient e-

government

Literature review

Survey & Data Analysis

(Study 1)

Recommendations on key

antecedent factor for e-

government to develop

resilience capability

Recommendations on

key antecedent factor

for e-government to

develop resilience

capability

2. To model the

resilience

capability in e-

government

Survey & data analysis

(Study 2)

Relationship between

human-centric antecedent

factor and the resilience

capability

Theory of relationship

between human-

centric antecedent

factor and resilience

capability behaviour

model3. To validate the e-

government

resilience

capability model.

Statistical validation used

Structural Equation

Modelling (SEM) analysis

using Smart PLS

(Study 3)

Relationship between

human-centric antecedent

factor and the resilience

capability

Mapping of research questions, objectives, methods, outcomes and contribution

Exploratory phase Confirmatory Phase

EXPLORATORY PHASE

Study 1

Conce

ptual

Model

Study 2

Refine

d

Model

Constructs

Constructs

Refined Constructs

Study 1

• Explore and collect literatures in the research area using keywords

– 3 related theory identified

• Resilience theory (Holling1973, Hollnagel 2006, Lengnick-Hall,2011, Erol et al., 2010, Folke et al., 2002,Vogus

2007, Connor 2003, Kumpfer, 2002) - explained the basic concept, element and capability of resilience

• SCT (Bandura, 1986,1999,2002) - explain why people engage in certain conduct and identifies human behavior

as an interaction of personal factors, behavior and the environment factor (Triadic Reciprocal Determinism).

• TPB (Ajzen, 1991,2001)- provide a conceptual frameworks for the study of human action for prediction

• Develop research framework based on TPB

Resilience elements are integrated into the existing TPB model

EXPLORATORY PHASE

Study 1

Conce

ptual

Model

Study 2

Refine

d

Model

Themes / Constructs

Themes / Constructs

Refined Constructs

Study 1

First Variable Second Variable Third Variable Fourth Variable

= The Proposed model variables; = TPBs Variables

= Posit to influence intention determinant; = Posit to form intention;

= Posit to predict organization adaptation behaviour

HYPOTHESES

In total fifty seven (57) hypothesized relationships are tested in this research. Involve 21 constructs

Study 1

Study 1

Concep

tual

Model

Study 2

Refined

Model

Themes / Constructs

Themes / Constructs

Refined Constructs

Intention Determinant

IntentionBehavior

No. Constructs Number of Items Source

Organization Factor

1 Culture 4 Items (Chatman & Jehn, 1994; O’Reilly, Chatman, & Caldwell,

1991) (Li & Shani, 1991) (Harland et al., 2005)2 Structure 5 Items

3 Leadership style 5 Items

Personal Quality

4 Social competence 4 Items (Earvolino-Ramirez, 2007; Ewart, Jorgensen, Suchday, Chen,

& Matthews, 2002)

(Bronk, 2014) (Herl et al., 1999; Zauszniewski & Bekhet,

2011) (Connor & Davidson, 2003) (Ho, Lee, & Hu, 2012;

Pavlou & Fygenson, 2006)

5 Sense of purpose 4 Items

6 Problem-solving 3 Items

7 Autonomy 3 Items

8 Self-efficacy 3 Items

Person-environment factor

9 Caring-supporting relationship 3 Items (Earvolino-Ramirez, 2007) (Ho et al., 2012) (Jaaron &

Backhouse, 2014)

(Hofstra, 2009; Karreman & Vingerhoets, 2012; Polek,

Wohrle, & Pieter van Oudenhoven, 2010; Westhuizen, 2010)

10 High expectation 4 Items

11 Commitment 3 Items

12 Involvement 3 Items

Capability-to-react

13 High technological competence 3 Items

(Mcmanus & Brunsdon, 2007; Stephenson, 2010b)14 Process Readiness 3 Items

15 Technological readiness 3 Items

Intention to organizing for resilience

16 Self-organize 3 Items (Patil, 2008; Haron et al., 2013; Caralli, 2010; Iii, 2010; Goble

et al., 2002; Vorisek et al., 2011)17 Process-organize 3 Items

18 Technology-organize 3 Items

Resilience behaviour

19 Ability to absorb 3 Items (Erol, Henry, et al., 2010; Erol et al., 2009; Erol, Sauser, et al.,

2010)20 Ability to adapt 3 Items

21 Ability to recover 3 Items

71 item

-reliability

-Validity

-Theoretical

judgement

Study 1

Study 1

Concep

tual

Model

Study 2

Refined

Model

Constructs

Constructs

Refined

Constructs

Study 2

STEP 4Structural model assessment

STEP 3Measurement model assessment

STEP 2Data Screening

STEP 1Data collection phase

Study 1

Concep

tual

Model

Study 2

Refined

Model

Constructs

Constructs

Refined

Constructs

• Convenience sampling

involve 35 Malaysian

public sector Frontline

agencies

• Self-administered

questionnaire

• 700 questionnaires

distributed, 335

completed, 33 uunusable

and only 302 usable

(43.14%)

• the response rate within

the common range of

27.0 to 82.8% public

sector research (Baruch

& C. Holtom, 2008)

• the rate higher then

research by Sakri &

Sembok, (2012)

1. respondents answered at

least 75% of the

questionnaire(Sekaran,

2010),

2. Missing data (less than

5%) - Replaced used

mean substitution (Cohen

& Cohen,1983)

3. Outlier none exceed z >

4(Hair et al., 1998)

4. Eliminated suspicious

response patterns-

straight 4 or 7

5. skewness and kurtosis

values < absolute value

of 2 and 7 respectively.

6. Non-response bias

test(Armstrong &

Overton, 1977)

A quantitative method was applied to confirm the findings of this study.

PLS-SEM evaluation stages adopted

from (Sarstedt et al., 2014)

1. Item reliability – each item loadings

>0.7

2. Internal consistency reliability

evaluated using composite

reliability (Jöreskog, (1971), Hair et

al., 2014). Proposed value > 0.70

<0.95 (Nunally (1978) indicate

measurement model is reliable.

Values > 0.95 indicate items

redundant.

3. Convergent validity examines

whether the measures of the same

construct are highly correlated.

Assessed by the average variance

extracted (AVE) for all items

associated with each construct.

Acceptable AVE is =>0.50.

4. Discriminant validity determines the

extent to which a construct is

empirically distinct from other

constructs in the path model. Two

measures have been put forward—

the Fornell– Larcker criterion &

cross-loadings

1. Collinearity Assess. VIF > 10

=multicollinearity problem

(Nishishiba, et al.2013).

2. Path Coefficient by evaluated

sign, t-value >1.96 (sign. level

= 95%),

3. Model’s predictive accuracy

level of R2 - Values range from

0 to 1. R2 values of 0.67, 0.33,

or 0.19 are described as

substantial, moderate, or weak

by Chin (1998). The impact of

a specific Exogenous on a

Endogenous construct - effect

sizes f2-measures. Values

0.02, 0.15, and 0.35 described

respectively as small,

moderate, and large.

4. Out of sample prediction

(predictive relevance q2) -

(Sarstedt et al., 2014). Values

of 0.02, 0.15, and 0.35 indicate

small, medium, or large

predictive relevance.

CONFIRMATORY PHASE

The investigated factor consisted of all factors stated in the research framework.

CONFIRMATORY PHASE

Study 1

Concep

tual

Model

Study 2

Refined

Model

Constructs

Constructs

Refined Constructs

Study 2

Demographic Profile of Personal

• 55% of the respondent are male and the remaining 45% female.

•Majority of the respondents are under 40 years old (83.1%) and only 16.8 percent aged 40 and above.

•Most of the respondents hold a bachelor degree (54.35%).

•More than half of the respondents (52.3%) claimed that they have experienced a level of proficiency in their work based on Garis Panduan Kepakaran ICT).

Demographic profile of Professional

•high % work at operating agencies (64.5%), central agencies (35.5%).

•Majority has a level of experienced ICT proficiency (39.3%) and a very small level of expertise (13.1%).

•Most hold a bachelor’s degree and most of them are at professional level

•Similar the characteristics of respondents in a previous study (Sakri & Sembok, 2012).

•Therefore, is believed to be representative of the wider population of IT practitioners working in the Malaysian public sector.

Demographic Profile of ICT Service Continuity Practice

•Risk management, prevention and prediction

mechanisms were most widely used (> 80%)

•97.7% admitted they have service continuity

policy in place.

•the majority (77%) respondents, carry out plan

review according to the best practical

recommendation.

•94.4% respondents has gone into the

awareness program.

•The cumulative percentage of service disruption

from always to sometimes is 69.6%) is found to

be more or less the same with the frequency in

preliminary studies (Abdullah, Noor, et al., 2016),

which is 70.2%.

Descriptive analysis of the

investigated construct

•All agencies are hierarchical and bureaucratic organizations (mechanistic structure), that encourage and practice innovative culture. All mean =>5.00

•The mean value for all variable of the personal quality, the person-environments setting, re-organize intention-, the capability-to-react - is above 5.0

•The mean value for all resilience ability variable is above 5.0 which represent the scale of “A day after impact” except for ability to recover had the mean value more than 4.0 which represent the scale of “Not Sure”. This indicates that on average, the public organization ability to absorb risk, adapt to the risk and recover day after impact

Resilient Capability Model developmentFrom the analysis of the empirical data based on the theoretical model, the resilient capability model is proposed for the

Malaysian public sector setting. The ICT Resilience capability model is drawn from the results of the path analysis that indicated:

Study 3

Study 1

Concep

tual

Model

Study 2

Refined

Model

Constructs

Constructs

Refined Constructs

Objective Revisited

Findings and Discussions

Objective Accomplishment

To identify the human-

centric antecedent factor

that would influence the

formation of resilient e-

government

• organizational setting (Inovative culture, mechanistic structure, TTLS) positively affect specific variable of identifying individual intention-

determinant (personal quality, person-environment setting, and capability-to-react).

• Innovative culture significantly affect all elements of personal quality (social competence, sense of purpose, autonomy, self-efficacy and problem-

solving skill), all elements of person-environment setting (caring support relationship, commitment, and involvement) except high expectation and

only one element of capability-to-react construct namely high technological competence.

• Mechanistic structure positively affects an individual sense of purpose, create high expectation, and contribute to develop process and technology

readiness

• TTLS significantly affect individual self-efficacy, and contribute to develop process and technology readiness.

• Personal quality, person-environment setting and the capability-to-react is perceived to be significant elements to predict IT person's intention-to-

organize.

• personal quality, namely self-efficacy and social competence to be the most significant predicting the formation of self-organize,

• person-environment setting, namely caring-supportive relationship, involvement and commitment, to be the most significant predicting the

formation of process-organize

• capability-to-react such as high technical competency, process and technical readiness to be the most significant predicting the formation of

technology-organize.

• three personality qualities (autonomy, sense of purpose and problem-solving skill) and one person-environment setting element (High expectation)

which represents resilience, personal factors in resilience theory were found to be not positively significantly related to intention-to-organize.

• The findings suggested that intention-to-organize perceived to be able to predict ICT resilience capability.

• Empirically, this research indicated that the intention-to-organize in different aspects, generate different resilience capability.

1. self-organize intention is perceived to produce the ability to adapt and ability to recover

2. process-organize intention is perceived to produce the ability to absorb and ability to recover

3. tech-organize intention will produce the ability to absorb and ability to adapt.

• This suggests that the intention of a person to organize is important in determining the resilience behaviour and it is consistent with previous

studies stating that the best way to predict and explain an actual behaviour is through that person’s behavioural intention (Ajzen, 1991; Miles,

Jeffrey, 2012; Roberts, Stout, & Halpern, 2012).

To model the resilience

capability in e-

government

The model indicates that 26% of the ability to absorb incoming risk related to ICT services, 25% of the ability to adapt to disruption or change in order

to maintain ICT services and 36% of the ability to recover from disruption or disaster in order to continuously provide ICT services in Malaysia

government agencies can be explained by the constructs in the proposed model.

To validate the e-

government resilience

capability model

The study has developed The Resilience Capability In E-government Model

The data analysis confirmed that the adjusted measurement model met all the requirements of convergent validity, discriminant validity, indicator

weight, and multicollinearity. The results also appeared to partly support the concept of triadic reciprocity in social cognitive theory (Bandura 1986).

ContributionsValidate resilience antecedent factorEmpirically validate resilience factor identified in the literature

Identified resilience relationship between external & internal factor

toward intention to organize Explore and validate external factor

(organizational setting ) toward Internal factor (intention determinant factor) and their effect

toward intention to organize.

Strengthen Azjen’s TPB model (1985, 1987, 1988, 1991)

The significant relationship between personal quality and self-organize intention,

person-environment setting and process-organize intention, and capability-to-react toward technology-organize intention, all

contribute to strengthening the formation of endogenous variables or intention factors as assumed by Ajzen’s TPB model (1985,

1987, 1988, 1991).

Organizational setting presenting situations in Malaysian public sectororganizational setting presenting clearest indication of external environment at the Malaysia Public sector workplace.

Choice of statistical analysisBy applying SEM, this research was able to demonstrate the joint impact of antecedent variables and the outcomes of organize-intention. The relationships between the factors in the hypothesized model are more accurate (Wan Afthanorhan, 2013).

The finding highlighted the importance resilience factoruseful for organizations to revisit their relevant policies and procedures specifically related to adoption of important factor identified and be strategize in strengthening the identified resilience capability

Resilience ability predictionThe research also contributes to the

theoretical body of knowledge through its uniqueness in predicting an organization's

resilience ability; namely the ability to absorb, ability to adapt and ability to recover.

The findings provide further evidence that intention-to-organize is a transformational

concept to be applied in justifying resilience acts.(Bandura 1996, Kumpfer 2000)

Establishment of ‘ICT Resilience Capability modelEmpirically validated Theory of Planned Behaviour based model and strengthening Ajzen’s Theory of Planned Behaviour model (1985,1987,1988,1991) and thus contribute to the body of knowledge by incorporating factors from different disciplines,

Th

eo

retica

l

• Only involved the given types of antecedent factors. Thus, future works need to explore

others factor as well, such as the BCM maturity, organizational characteristic,

organization core business or the other aspect that would influence the organizes-

intention behavior in the Malaysian public sector.

• Sampling limitations. future research should encompass a wider scope of organizations

may be in their category such as the federal government, state government, local

authority, federal statutory body, or could be private sector.

Limitations and Suggestions for Future Research

Publications

No Title Journal / Conference

1. Resilient Organization: Modelling The Capacity

for Resilience

3rd International Conference on Research and Innovation in

Information Systems – 2013 (ICRIIS’13), UNITEN, Selangor,

Malaysia 27-28 November 2013

(Scopus indexed)

2. Information Technology Service Management

(ITSM): Contributing Factors to IT Service

Disruptions – A Case of Malaysia Public Service

Agencies

The 19th Pacific Asia Conference on Information Systems (PACIS

2017) Chengdu, China, 24-28 Jun 2014

(Scopus indexed, Core rank A)

3. Contributing Factors To E-governments Service

Disruptions

Journal of Transforming Government: People, Process And Policy

Volume 10, Issue 1

(Scopus indexed, Q2)

4. Contributing Factor To Business Continuity

Management (BCM) Failure– A Case Of

Malaysia Public Sector

5th International Conference on Computing and Informatics, ICOCI

11-12 August, 2015 Istanbul, Turkey.

(Scopus indexed)

5. A Conceptual Model of Resilience Capability:

Human Centric Approach

International Conference On Information Resources Management

(Conf-irm) 2016: Digital Emancipation In A Networked Society

Cape Town, South Africa, 18-20 May, 2016

(Scopus indexed)

Thank you