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The relationship among organisationallearning, continuous improvementand performance improvement: Anevolutionary perspectiveWenbin Ni a & Hongyi Sun ba School of Business Administration , Zhejiang University ofFinance & Economics , Hang Zhou, Chinab Department of Manufacturing Engineering and EngineeringManagement , City University of Hong Kong , 83 Tat Chee Avenue,Kowloon, Hong Kong, ChinaPublished online: 03 Nov 2009.
To cite this article: Wenbin Ni & Hongyi Sun (2009) The relationship among organisational learning,continuous improvement and performance improvement: An evolutionary perspective, Total QualityManagement & Business Excellence, 20:10, 1041-1054, DOI: 10.1080/14783360903247312
To link to this article: http://dx.doi.org/10.1080/14783360903247312
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The relationship among organisational learning, continuousimprovement and performance improvement:An evolutionary perspective
Wenbin Nia and Hongyi Sunb�
aSchool of Business Administration, Zhejiang University of Finance & Economics, Hang Zhou,China; bDepartment of Manufacturing Engineering and Engineering Management,City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China
This paper records the research on the relationship between organisational learning(OL), continuous improvement (CI) and performance improvement from anevolutionary perspective. The research may contribute to the literature by providingnew explanations to the questions such as whether OL and CI are equal and how OLand CI influence each other. The research is based on the survey data from about500 companies in 15 countries/regions. Data analysis is based on structural equationmodelling (SEM). OL is treated as an evolutionary process and measured separatelyby previous learning and current learning. The results can be summarised as follows.First, CI directly contributes to performance, while OL does not contribute directly.Second, CI and OL do enhance each other, but there is a time lag. Well-establishedlearning capability contributes to CI, and CI in return supports current OL. Therelationship is evolutionary like rolling a snowball. The result suggests thatcompanies have to be patient when implementing OL and also incorporate OL withCI or other problem-oriented programmes.
Keywords: organisational learning (OL); continuous improvement (CI); performanceimprovement
Introduction
Organisational learning (OL) has been widely regarded as an important approach by which
organisations can survive and grow in this dynamic and turbulent competitive environ-
ment. Several researchers argue that the only sustainable competitive advantage may be
the capability of learning faster than competitors (e.g. Nonaka, 1991; Senge, 1990a).
Under such circumstances, Senge’s (1990a, 1990b) advocacy of the learning organisation
soon provokes a management upsurge to building organisations that commit to learning.
However, academia and practitioners are not very clear of what a learning organisation is
and how to build it. Kofman and Senge (1993) even argue that there is no such thing as a
learning organisation, but just a linguistic creation. Even how an organisation learns is
ambiguous regarding such issues as learning subject, learning context and learning
process (Lahteenmaki et al., 2001).
In exploring effective means to cultivate organisational learning capability and viable
approaches to build what is called a learning organisation, a stream of research in total
quality management (TQM) and continuous improvement (CI) provides the link
between CI and OL. Barrow (1993) argues that TQM and organisational learning are
ISSN 1478-3363 print/ISSN 1478-3371 online
# 2009 Taylor & Francis
DOI: 10.1080/14783360903247312
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�Corresponding author. Email: [email protected]
Total Quality Management
Vol. 20, No. 10, October 2009, 1041–1054
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inextricably connected for the reason that learning is an intended effect of TQM and that
process improvement and organisational learning are operating in a concurrent integrated
way. Terziovski et al. (2000) establishes a mutual dependency between TQM and the
learning organisation by field studies. Other authors such as Garvin (1993), Locke and
Jain (1995) and Mukherjee et al. (1998) highlight the role of learning in continuous
improvement, arguing that the culture of learning as well as technologies for learning
will contribute to an organisation’s continuous improvement programmes.
Notwithstanding insightful propositions about the linkage, the above-mentioned and
other similar researches thus far (for example, Hill, 1996; Love et al., 2000; Luthans
et al., 1995) are almost conceptual in nature. Though several researches use an empirical
approach, they are just based on case studies. There is a call for quantitative testing by
cross-sectional studies to further rectify and refine this proposed linkage and its impact
on organisational performance (Terziovski et al., 2000). The main focus of these
researches is to ascertain the contribution of CI to cultivating organisational learning capa-
bility and how organisational learning capability can foster the successful implementation
of continuous improvement programmes, namely, the linkage between CI and OL and the
effect of this linkage on organisational renewal (Ferguson-Amores et al., 2005) and
performance (Mitki et al., 1997).
In this research, the relationship between OL, CI and performance improvement will
be tested. The OL is treated as an evolutionary process and measured at previous and
current time points, respectively. It aims to portray the mutually enhancing relationship
between OL and CI as well as their contribution to performance improvement. The
research may contribute to the literature by answering the questions such as whether
OL and CI are equal and how OL and CI influence each other.
Hypotheses formulation and model development
CI as an evolutionary learning process
Continuous improvement (CI) is a traditional concept in organisational improvement. The
early examples could be dated back to the nineteenth century in the UK and the USA
(Schroeder & Robinson, 1991), while the Japanese fully exploited the potentials of this
approach in the middle and latter part of the twentieth century in the form of Kaizen
(Imai, 1986; Nonaka, 1991; Schroeder & Robinson, 1991). So many efforts have been
poured into the research and application of CI that it becomes the core instrument of incre-
mental organisational change afterwards. However, in its inception of prevalence, CI is
considered only as a suggestion box for incremental organisational change (Boer et al.,
2000). Its strategic importance as a core and dynamic capability and its place as the
most important competency for companies have been ignored (Bessant & Francis, 1999).
The concept of CI comes into the field of manufacturing for the purpose of reducing
costs and improving quality (Tersine, 2004). It takes its initial shape as a suggestion
scheme in its early beginnings. A CI programme is traditionally initiated by top manage-
ment. Leadership’s commitment for CI is regarded as the requisite and key factor of a suc-
cessful CI programme (Kaye & Anderson, 1999). The suggestion scheme also contains a
corresponding incentive and reward plan. In such a programme, employees are treated as
individuals that have the ability to ‘think’, not just to ‘execute’ (Ishikure, 1988), though in
the Japanese form individuals act collectively in organisations, e.g. by means of a quality
circle team. The philosophy that employees are able to think is a deviation from the tra-
ditional Taylorism approach. Consequently, the launch of CI implies a culture transform-
ation from centralisation to decentralisation, from expert governance to high involvement
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management (Savolainen, 1999). This is accomplished through training, empowerment,
job rotation, teamwork, and other human resource management approaches (Imai, 1986).
Thus, the process of CI, best presented by endless churning of Deming’s PDCA (plan,
do, check and act) cycles, implies a process of incremental organisational change (Choi,
1995) and leads to remarkable and continuous improvement of organisational performance.
CI is organisation-specific in nature and path-dependent during acquisition (Teece et al.,
1997). The process of CI is evolutionary and developmental. A suggestion scheme will
ultimately transform the organisation in aspects of structure, leadership, culture, and so
on by accumulative effect, acting as an approach of incremental organisational change
and development. Its ultimate outcomes shift from operational objectives (productivity,
quality) to strategic competitive advantage (sustainable dynamic capability).
In summary, CI involves a process of organisational change/transformation and the
successful CI definitely needs and will consequently induce a complete change in
pattern of behaviour and culture. The transforming process evolves gradually and incre-
mentally in a relatively long period of time. For example, Boer et al. (2000) describes
CI as a planned, organised and systematic process of ongoing, incremental and
company-wide change of existing practices aimed at improving company performance.
Bessant and Francis (1999) attribute CI’s strategic advantage to a cluster of behavioural
routines that require time to learn and institutionalise, and are hard to copy or transfer.
Hereby, Garvin (1993) argues that CI requires a commitment to learning; otherwise organ-
isations can only repeat old practices and the changes obtained from CI remain cosmetic
and short-lived. Learning is a mechanism to understand how CI can lead to organisational
change; that is, how, in an evolutionary process, the behavioural routines obtained from CI
can be internalised into the organisation’s day-to-day operations.
OL as an evolutionary process
A few authors (e.g. Huysman, 1999) criticise the propensity to regard OL as organisational
achievement that implies organisational change or improvement. However, the compari-
son of OL definitions by Dixon (1994) reveals that most authors agree that learning
increases knowledge orienting to action improvement. For example, Argyris and
Schon’s (1978) learning concept refers to error detection and correction. Fiol and Lyles
(1985) define OL as the process of improving actions through better knowledge and under-
standing. It is especially manifest in the ideal form of learning organisation that links
learning to competitive advantage of firms. OL is a process by which an organisation
sustains and develops its dynamic capability through cognitive and behavioural change
or improvement (Zollo & Winter, 2002).
The next question is how organisations learn to improve and to sustain competitive
advantage. Two related concepts and their relationship to dynamic capability are relevant
here. One is so-called tacit knowledge, and the other is organisational routines. By tacit
knowledge, Nonaka (1991, p. 97) refers to ‘subjective insights, intuitions and hunches
of individual employees’. It is highly personal and contextual dependent, and not so
easy to articulate and transfer. In the perspective of the resource-based view of the firm,
tacit knowledge is in a central position for developing sustainable competitive advantage
(Ambrosini & Bowman, 2001). Organisational routines can be defined as stable yet flex-
ible patterns of organisational behaviours by which an organisation reacts to internal or
external stimuli (Zollo & Winter, 2002). They also have the characteristics of being con-
textual specific, and path dependent (Becker, 2004). Gavetti and Levinthal (2000, p. 113)
suggest that ‘routines reflect experiential wisdom in that they are the outcome of trial and
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error learning and the selection and retention of prior behaviors’. By this point, organis-
ational routines are regarded as storage of tacit knowledge, and are attributed by strategic
theorists as the source of dynamic capabilities (Teece et al., 1997).
The central learning process by which an organisation routinises behaviour patterns
and stores tacit knowledge (procedural memory) is experience accumulation (Zollo &
Winter, 2002). For behaviour patterns to embed and reside in a specific context, to
diffuse all over the organisation, to the extent that they are taken for granted by organis-
ation members, learning occurs through a trial and error process, experiment, evaluation
and feedback, which in its nature is experiential learning and develops evolutionarily.
Other forms, such as visiting a benchmarking organisation, or reading a reference docu-
ment, will not contribute to this process until the information gained is transformed into
contextual-dependent knowledge and ingrained in everyday operational activities.
Nonaka (1991), in his spiral model of knowledge for developing tacit knowledge,
describes this process as socialisation, which refers to creating knowledge from tacit to
tacit, and internalisation, which refers to enriching a tacit knowledge base from explicit
knowledge. In the organisational routines literature, it is well recognised that routines
evolve in a path-dependent manner and history matters in its evolution (Becker, 2004).
Other important issues include the distinction between individual and organisation
learning, and the attempt to integrate individual level learning with the organisational
level one (Lahteenmaki et al., 2001). It is commonly agreed that, on the one hand, organ-
isational learning is not simply the sum of individual learning (Fiol & Lyles, 1985), on the
other hand, organisations cannot learn without individual learning (Argyris, 1992; Argyris
& Schon, 1978). This involves a process of transforming individual level learning to
organisational level learning. This process is complex and involves dynamic and sophis-
ticated interaction between the members of the organisation. From the routines perspec-
tive, this process involves transformation of individual habits to collective habits,
namely organisational routines (Becker, 2004). For example, Dixon’s (1994) organis-
ational learning cycle (i.e. generating, integrating, interpreting and acting) is a continuous
process to transform the organisation at the individual, group and system levels in order to
engage all members of the organisation in all the steps.
Having in mind the nature of the learning process that contributes to dynamic capability,
one may propose that a programme of continuous improvement may facilitate this process.
Several CI attributes can contribute to it. First, CI can lead to continuous change and
improvement of the organisation. Successful behaviours can be routinised through a
cycle of PDCA. Secondly, high-involvement characteristics of CI allow organisation
members to interact dynamically in the changing process, enhancing knowledge diffusion
and transfer. Thirdly, CI changes and improves the organisation in an incremental way,
which matches the evolutionary manner of routines development. Fourthly, many aspects
of CI, such as leadership’s commitment, employee involvement, and suggestion schemes
will undoubtedly direct the organisational culture to one that facilitates learning. In fact,
the development of dynamic capability is in an incremental manner according to Teece
et al. (1997, p. 523), as they argue that ‘if many aspects of a firm’s learning environment
change simultaneously, the ability to ascertain cause–effect relationships is confounded
because cognitive structures will not be formed and rates of learning diminish as a result’.
The linkage between CI and OL
Organisational learning develops along an evolutionary and experiential process. In fact,
researchers on learning organisations (e.g. DiBella et al., 1996; Jerez-Gomez et al., 2005;
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Marsick & Watkins, 2003) are attempting to investigate the stages for building a learning
organisation as well as the knowledge learned (Nonaka, 1991). In this paper, we separate
previous learning and current learning. Previous learning refers to learning activities
already undertaken, and such learning has produced knowledge or routines that have
been mastered by the organisation. Organisation members have mastered the learned
knowledge and can use it successfully for continuous improvement. Current learning
refers to ongoing learning activities; such learning has not produced routinised behaviour-
al patterns in the organisation, which leads to knowledge and routines in the process of
being digested by the organisation members and will eventually add into the repertoire
of previous learning capability.
The previous and current learning concepts reflect the evolutionary process and the
stages of learning. More important, the relationships between OL and CI are different at
the two stages. The mutual dependency between the two is recognised by previous
researchers such as Barrow (1993) and Terziovski et al. (2000). In the first place, learning
is the prerequisite of CI. In this stage, it is reasonable to claim that learning will deter-
minedly affect the achievements of CI implementation, as Garvin (1993, p. 78) argues
‘how can an organization improve without first learning something new?’ Then, the learn-
ing capability evolves along with the progress of CI implementation. CI is a vehicle or
driving force for learning more. Bessant et al. (2001) argue that CI involves the evolution
and aggregation of a set of key behavioural routines within the firm. They develop
six levels of CI capability and associated behaviours. These clusters of behaviours are
organisational routines that are evolving along with the CI development, which, in our
term, is current learning. Therefore, two hypotheses on the relationship between CI and
OL are formulated as below:
H1: Previous learning has a positive effect on the implementation of CI.
H2: CI activities have a positive effect on the current learning.
It is quite obvious that there is a relationship between previous and current learning.
The learning process is like rolling a snowball. Current learning is based on previous learn-
ing. People learn from previous learning experiences. Previous learning will be a basis for
new learning activities and is a facilitator to start to learn new things. In other words, if a
company has a long history of learning, it will be easier for its members to learn new
things. The discussion leads to the third hypothesis.
H3: Previous learning enhances new and current learning.
Contributions of CI and OL to performance
Previous literature widely supports the conclusions that CI and/or OL bring about
performance improvement. The research from the perspective of a resource-based view
links CI and OL to sustainable competitive advantage of the company. Most CI literature
agrees that sustained CI has a major impact on performance improvement while requiring
little capital investment (e.g. Boer et al., 2000; Imai, 1986; Schroeder & Robinson, 1991).
In OL literature, besides conventional conceptual research and case studies, there are
emerging rigid theoretical studies regarding the linkage between OL, performance and
other relative variables. For example, Lopez et al. (2005) find that OL is a determining
factor of business performance. Tippins and Sohi (2003) find that OL is a mediator
between information technology competence and performance.
However, there is little empirical research on the interrelationships between CI, OL and
performance. Gieskes et al. (1999) argue that the contribution of CI to performance
Total Quality Management 1045
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improvement is ‘taken for granted’ by almost all researchers in this field. There is a
similar gap in the OL field. OL is studied from various perspectives, such as sociology, phil-
osophy, economics and management science at large (Easterby-Smith, 1997); and
production management, organisational change, innovation management and strategy
management in business specifically. Although there are deviations, there is some
consensus among these perspectives that conceptually value OL as a predictor of organis-
ational improvement, which Huysman (1999) terms as improvement bias. The point is that
OL is too frequently treated as an achievement verb, rather than a process verb. Some (e.g.
Miner & Mezias, 1996) even argue that learning does not consequentially link with
improvement; organisations can learn good and bad things simultaneously. Additionally,
there is a learning effect in learning. Time is another factor that should be considered.
It is theoretically and practically imperative to study the contributions of CI and OL to
performance simultaneously, as the two variables are interrelated as discussed before. If
there is a linkage between CI and OL, will this relationship affect the contributions of CI
and OL to performance, and if so how? Separating previous learning from current learning,
there will be three hypotheses regarding the contributions of CI and OL to performance.
H4: The adoption of continuous improvement activities has a positive effect on organisationalperformance improvement.
H5: Previous learning has a positive effect on performance improvement.
H6: Current learning has a positive effect on performance improvement.
The relationships between previous learning, current learning, CI and performance
improvement are illustrated by the above six hypotheses, as shown in Figure 1.
Methodology and data collection
Survey and data
The data for this research are from the project of Continuous Improvement Survey, carried
out by Continuous Innovation Network (CINet), a global network set up to bring together
researchers and industrialists working in the field of continuous innovation. The survey
aimed to examine the motives, targets and means of the organisations chosen to promote,
support and sustain continuous improvement activities. For details regarding CINet and
the survey, please refer to the book by Boer et al. (2000) and the website of CINet
(www.continuous-innovation.com).
The survey was conducted in Australia, the Netherlands, Sweden, Ireland, the United
Kingdom, Spain and Norway, respectively by local cooperative universities. The total
Figure 1. The proposed model and hypotheses.
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sample size is 513. The sample profiles of the participating countries are presented in
Table 1. Out of the 513 respondents, 108 are deleted for missing data using the listwise
method. It is tested by dimensions of employee size, annual turnover, business unit
type, and production system type that there is no bias between the deleted and total respon-
dents. All the companies are manufacturing firms.
Construct measurement
In this session, the measurement scales, reliability and validity tests for OL, CI and per-
formance will be presented. The data are shown in the Appendix.
The concept that continuous improvement (CI) activities involve a suite of behaviours
and are clustered around several core themes is a prevalent cognition among the CI
researchers (Bessant et al., 2001). Terziovski and Sohal (2000) also attempt to classify
the tools of CI utilising factor analysis, and link these core themes to organisational
performance. But the activities of CI vary in the literature. We tried to identify
common activities that appear in most researches, and match these activities with the
long list of improvement activities and quality tools in the survey. This led to six activities
that are common among most CI papers and books, and included in the survey. See the
Appendix for the items. Factor analysis with principal components extraction shows
that the items can be converged into one factor. The Cronbach’s coefficient (0.72) also
shows an acceptable internal reliability of the construct.
Measuring organisational learning (OL) has developed recently as a promising research
theme (Marsick & Watkins, 2003). Jerez-Gomez et al. (2005) propose a four-dimensional
measurement of organisational learning capability, namely managerial commitment,
systems perspectives, openness and experimentation, knowledge transfer and integration.
Another more rigorously tested measurement is developed by Marsick and Watkins (2003)
with seven dimensions. Though the items in the CINet survey cannot meet Marsick and
Watkins’s 43-items version of ‘dimensions of the learning organization questionnaire’, a
version of seven items that can be used separately to create a scale of learning organisation
is adopted by this paper. OL is measured on a scale from 1 to 5, representing very low to
very high learning. Factor analysis with principal components extraction shows that the
items for both previous and current learning can be converged to one factor. Cronbach’s
coefficient is 0.88 for current learning, reaching acceptable internal reliability.
Performance measure covers productivity, delivery reliability, cost, lead time and
production volume. Performance achievement is measured as perceived degree of
Table 1. Sample distribution among countries.
Country Frequency
Australia 89Netherlands 51Sweden 77Ireland 81UK 69Spain 105Switzerland 27Norway 14
Total 513
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improvement over the last three years. It is measured on a 1 to 5 scale with 1 representing
great improvement and 5 no improvement. Factor analysis with principal components
extraction shows that the items can be reduced to one factor. Cronbach’s coefficient
(0.77) shows an acceptable internal reliability.
Structural equation modelling
The proposed six hypotheses are tested simultaneously using structural equation model-
ling (SEM). The initial proposed model will be modified by deleting insignificant paths
if the model does not fit data well and then tested again. This process ends when the
model fits well evaluated by a two-step procedure. The first step is to examine the signifi-
cance of path and measurement coefficients. The second is to examine the whole model fit
by using multiple criteria, as recommended by previous scholars (Hu & Bentler, 1999).
Because x2 is sensitive to sample size, due to our large sample size, an alternative of
normed chi-square (x2/df) is used to assess the model fit. In addition, goodness of fit
index (GFI), and comparative fit index (CFI) are used, as well as root mean square
error of approximation (RMSEA). Generally, according to rule of thumb recommended
by previous authors, GFI and CFI values above 0.9, and RMSEA value below 0.05 are
regarded as good fit. RMSEA between 0.05 and 0.08 (Browne & Cudeck, 1993) is also
acceptable. For normed chi-square, Carmines and McIver (1981) recommended the
value be below 3.
The results
The proposed model as shown in Figure 1 was tested by SEM software AMOS (Byrne,
2001). According to the test, two path coefficients are not significant at the significance
level of 0.05. These two paths (previous learning to performance improvement and
current learning to performance improvement) are deleted and the model is tested
again. After the modification, all coefficients in the measurement model and structural
model are significant at the level of 0.05. The ultimate accepted model is shown in
Figure 2 and the results of the whole model fit indexes are shown in Table 2.
The standardised weight of path from previous learning to continuous improvement is
0.494, significant at the level of 0.01. The squared multiple correlation of continuous
improvement is 0.24, implying that 24% variance of continuous improvement is explained
by the model. This result implies that Hypothesis 1 is supported by the data. The standar-
dised path weight of continuous improvement to current learning is 0.524, and significant
at the level of 0.01, implying that the adoption of a continuous improvement programme
has a positive effect on learning capability acquisition, supporting Hypothesis 2. Also,
there is a positive effect of previous learning on current learning shown by the significant
path from previous learning to current learning, showing that organisational experience
will influence later organisational behaviours. The total effect of previous learning on
current learning is 0.499 by adding direct effect (0.241) and indirect effect (0.258)
through continuous improvement; and 46% of the variance is explained by the model.
It is noticeable that the indirect effect via continuous improvement is greater than the
direct effect of previous learning on current learning; this suggests that CI has an
influential effect on enhancing organisational learning capability.
With respect to the effect on performance improvement, only one path (from continu-
ous improvement to performance improvement) is significant. The standardised weight is
0.566. Paths from two learning capability variables are excluded in the final accepted
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model as their path weights are not significant at the level of 0.05. Thirty-two per cent
variance of performance improvement is explained by the model.
The results from SEM support H1, H2, H3 and H4, but reject H5 and H6. Detailed
discussions of the results and implications will be elaborated in the next section.
Discussion
In previous studies, the relationship between OL and performance has been studied either
directly or indirectly with moderating or mediating factors. There are studies reporting that
OL did not contribute to performance directly. For example, Tippins and Sohi (2003)
studied how IT affects organisation performance and found that organisational learning
mediates the effect of IT competency on firm performance. Other studies such as Lopez
et al. (2005) empirically study the direct effects of OL on innovation, competitiveness
and financial performance. The research investigates both the direct (H5) and mediating
effect of OL on performance improvement (H1 and H4). It is found that OL contributes
to CI, which then contributes to performance improvement. According to this result,
OL is the means to enhance CI, not the end!
Figure 2. The accepted model.
Table 2. The fitness results for the accepted model.
Fit results Accepted model Accepted range
x2/df 1.879 ,3GFI 0.918 .0.9CFI 0.958 .0.9RMSEA 0.045 ,0.05
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Adopting the evolutionary perspective of learning, this study distinguishes previous
from current learning, which makes the relationship more convoluted than previous
research has shown. Previous research had tried to identify the precondition and the
driver of CI (Mukherjee et al., 1998). In our model, it is the previous learning capability
that enhances CI activities. This implies that organisations with well-established learning
capability will perform better than an organisation that has just started OL. The result
implies that there is a learning effect in learning. It takes time before OL can contribute
to CI. Companies should not expect OL to show benefits in a short time period.
The acceptance of Hypothesis 2 implies that CI activities in turn facilitate learning,
more precisely, the current learning. The parallel learning mechanism in Mitki et al.’s
(1997) case study is one example where a CI programme contributes to OL. Garvin’s
(1993) learning organisation building block of systematic problem solving relying on
the PDCA (plan, do, check and act) cycle, fact-based management and statistical tools
(histograms, Pareto charts, cause–effect diagrams) is another good example. Bessant
and Francis (1999) develop a framework from no CI activity at all to full CI capability
for a learning organisation. They explain that the move towards full CI capability involves
a process of acquiring and embedding key behaviours and is essentially a learning process.
The research confirms that OL and CI enhance each other, but it is CI which contrib-
utes to performance improvement. How to explain this and what are the implications? The
goal of OL is to learn and apply the knowledge and skills. However, in some cases of OL,
it is not easy to define why to learn and where to apply. CI is more objective oriented and
focusing on a problem. When the CI group members learn, it is for the purpose of solving a
particular problem. CI is a very practical environment for employees to learn for a
common objective. OL is very often regarded as a process of gaining information and
knowledge for qualification and skills. The application part is not obvious. OL should
be aligned, at least finally, with organisational objectives. The implication is that when
companies implement OL, it must be aligned with a practical objective such as new
product development, continuous improvement, or reducing delivery time, etc.
The relationship between CI and OL can be summarised as follows. First, CI directly
contributes to performance, while OL does not contribute directly. Second, CI and OL do
enhance each other, but there is a time lag. Well-established learning capability contrib-
utes to CI, and CI in return supports current OL. The relationship is evolutionary like
rolling a snowball. The evolutionary relationship is illustrated in Figure 3. The result
suggests that companies have to be patient when implementing OL and also incorporate
OL with CI or other problem-oriented programmes.
Figure 3. The dynamic relationship between organisational learning (OL), continuous improvement(CI) and performance improvement (P).
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Conclusions and future research
The paper investigates the relationships between OL, CI and performance improvement
from an evolutionary perspective. The result shows that OL enhances CI, and CI contrib-
utes to performance improvement. It clears up doubts in previous research as to whether
OL contributes to performance improvement directly or indirectly. This may be a mean-
ingful and new input to existing literature in the OL field. The research also reveals the
mutually enhancing relationship between OL and CI. The finding on the mutual depen-
dency echoes and supports propositions by previous research. However, this research
reveals that the mutually enhancing relationship between OL and CI is not simultaneous.
There is a time lag. The result is found out due to the evolutionary perspective which
distinguishes previous learning from current learning. In a summary, there is a learning
effect in learning in terms of enhancing CI. Also there is a rolling snowball effect in
terms of establishing learning capability.
The results of this paper support the proposition of building a learning organisation
through CI, or quality improvement at large. This proposition is of great meaning to com-
panies that are lagging behind in quality management but are still keen on becoming a
learning organisation to build competitive capability, especially in emerging markets
such as China. The suggestion from this study is that they should not be fickle in affection
such as loving the new and loathing the old. On the contrary, as proposed by this study and
others (e.g. Bessant & Francis, 1999; Hill, 1996; Love et al., 2000), CI is the beginning of
the journey towards a learning organisation, and an effective way through which organis-
ations can develop dynamic capabilities in the turbulent competitive environment (Bessant
et al., 2001; Escrig-Tena & Bou-Llusar, 2005; Jha et al., 1996).
Some authors (e.g. Ferguson-Amores et al., 2005) relate the learning mechanism in CI
to Argyris’s (1992) single-loop learning, suggesting that persistence in developing current
capabilities will lead to a capability trap that endangers the organisation in a high-velocity
environment (Levitt & March, 1988). But no evidence or fact has proved this claim
empirically. So, more variables need to be included in the research model, such as organ-
isational life cycle, environmental variance to deeply examine the relationship between CI
and OL.
Another promising direction for future research is to empirically test the role of
performance feedback in building organisational learning capability. Traditionally, per-
formance is seen as the result of strategy management. Particularly, empirical studies in
management always treat performance as a dependent variable. However, performance
feedback theory already tackles how an organisation re-posits its strategy by comparing
aspiration level and performance achievement (Greve, 2003). Researches on CI and
TQM reveal the importance of performance measurement in achieving continuous
improvement. However, the significance of performance feedback in building OL capa-
bility is just beginning to catch the eyes of researchers and empirical studies are needed
to understand the mechanism.
Finally, future research is also needed to investigate how OL and CI can be integrated.
The questions may include: shall a company implement OL first or CI first? Longitudinal
case studies are needed to answer these questions.
Acknowledgement
The research reported in this paper is fully supported by a Strategic Research Grant (SRG
70001715) from City University of Hong Kong, Hong Kong, P. R. China.
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Appendix. Reliability and validity tests of the four constructs
Continuous improvement activities ( factor loadings)
CI1 Training of personnel in problem solving tools (0.719)CI2 Monitoring the improvement activities (measures, follows-up) (0.677)CI3 Supportive leadership for improvement (0.758)CI4 Work in teams/work groups (0.706)CI5 A suggestion scheme for improvement (0.362)CI6 A general problem solving format (e.g. PDCA) (0.658)
(Eigenvalue ¼ 2.614, Variance explained ¼ 43.537%, Cronbach’s alpha ¼ 0.72)
Previous organisational leaning ( factor loadings)
OL1a Appropriate organisational mechanisms are used to deploy what has beenlearned across the organisation (0.741)
OL2a Everyone learns from their experiences, both good and bad (0.651)OL3a Individuals and groups at all levels share (make available) their learning
from all work and improvement experiences (0.800)OL4a Individuals seek out opportunities for learning/personal development
(e.g. active experimentation, setting own learning objectives) (0.747)OL5a Managers accept and, where necessary, act on all the learning that takes
place (0.773)OL6a People and teams ensure that their learning is incorporated into the organ-
isation by making use of the mechanisms provided for that (0.826)OL7a The organisation articulates and consolidates (captures and shares) the
learning of individuals and groups (0.791)
(Eigenvalue ¼ 4.077, Variance explained ¼ 58.236%, Cronbach’s alpha ¼ 0.88)
Current organisational leaning ( factor loadings)
OL1b Appropriate organisational mechanisms are used to deploy what has beenlearned across the organisation (0.741)
OL2b Everyone learns from their experiences, both good and bad (0.613)OL3b Individuals and groups at all levels share (make available) their learning
from all work and improvement experiences (0.802)OL4b Individuals seek out opportunities for learning/personal development
(e.g. active experimentation, setting own learning objectives) (0.751)OL5b Managers accept and, where necessary, act on all the learning that takes
place (0.804)OL6b People and teams ensure that their learning is incorporated into the organ-
isation by making use of the mechanisms provided for that (0.806)OL7b The organisation articulates and consolidates (captures and shares) the
learning of individuals and groups (0.808)
(Eigenvalue ¼ 4.081, Variance explained ¼ 58.297%, Cronbach’s alpha ¼ 0.88)
Performance improvement in the past three years ( factor loadings)
PI1 Increased production volume (0.714)PI2 Increased productivity (0.817)PI3 Improved delivery reliability (0.725)PI4 Reduced lead times (0.783)PI5 Reduced cost (0.753)
(Eigenvalue ¼ 2.886, Variance explained ¼ 57.713%, Cronbach’s alpha ¼ 0.77)
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