International Journal of Management, Knowledge and Learning, 2(2), 165–184
Linking Resource-Based Strategies
to Customer-Focused Performance
for Professional Services:
A Structural Equation
Modelling Approach
Ming-Lu Wu
United International College, Beijing Normal University –
Hong Kong Baptist University, China
This paper links professional service firms’ resource-based strategies to their
customer-focused performance for formulating service quality improvement
priorities. The research applies the structural equation modelling approach
to survey data from Hong Kong construction consultants to test some hy-
potheses. The study validates the various measures of firms’ resource-based
strategies and customer-focused performance and bridges the gaps in firms’
organizational learning, core competences and customer-focused perfor-
mance mediated by their strategic flexibility. The research results have prac-
tical implications for professional service firms to deploy resources appro-
priately to first enhance different competences and then improve customer-
focused performance using their different competences.
Keywords: organizational learning; core competences; strategic flexibility;
customer satisfaction; structural equation model; professional services
Introduction
Worldwide developed economies have been dominated by services for
decades, and Hong Kong is not an exception. However, Hong Kong is also
well known for its energetic real estate market and the related construction
industry, evidenced by the high density of well-functioned commercial and
residential buildings. In fact, of Hong Kong’s limited non-service sectors,
construction industry has been a major business with a share of about 35
percent in recent years.
In the construction industry, the consulting part of a project is tradition-
ally awarded to an outsourcing consultant (architect, surveyor, etc.) who can
complete it with the minimum tendering price, and commission for the con-
sultant’s professional services is agreed on a mandatory fee scale based
on a certain percentage of the project’s construction cost (Carr, 1982). As
recent as late 1990s, the Hong Kong Housing Authority still engaged con-
struction consultants for their housing projects based on the mandatory fee
www.issbs.si/press/ISSN/2232-5697/2_165-184.pdf
166 Ming-Lu Wu
scale. However, competitive fee tendering is rapidly gaining popularity in the
construction industry as a mechanism for distributing consultancy projects
to willing professional service providers, and the awarding decision is based
on the consultants’ tendering fees and quality scores assessed from their
technical submissions by the clients (i.e., government agencies or private
firms). For example, a study by Drew, Li, and Shen (2000) identified that 89
percent of quantity surveying consultancy projects in Hong Kong is allocated
through the competitive fee tendering mechanism.
The special feature of the competitive fee tendering system, as com-
pared to the traditional price bidding, is its use of a quality score in addition
to the fee score in evaluating professional service providers’ submissions.
It is therefore important for professional consultants in the construction
industry to measure and improve their service quality. However, service
quality, although often ‘created’ by the service provider, is eventually per-
ceived by the customers. Just as Drucker (1973) noted four decades ago,
business success is not determined by the provider, but by the customer
and the customer-focused dimension should be the priority of managerial
attention. In today’s turbulent environment, customers are playing an even
more important role in business competition and, accordingly, customer-
focused performance represents a decisive source of firms’ competitive
advantage. Taking the competitive fee tendering system for example, supe-
rior client-perceived consulting quality can help a construction consultant
submit relatively higher bidding prices, while still maintaining his overall
competitiveness, for higher and long-term profits.
Although customer-focused performance is important, it can only be
achieved by translating into measures or actions of what a firm should do to
meet customers’ requirements. However, there have been few studies effec-
tively addressing the linkage between customer-focused performance and
firms’ operational or resource-based strategies. Noticeable exceptions are
the recent works of Wang and Lo (2003, 2004) who identify the key compo-
nents and resource-based determinants of customer-focused performance
and propose a conceptual framework of cause-effect paths to link firm’s
resource-based strategies to customer-focused performance. This provides
a meaningful approach for construction consultants to identify measures,
antecedents, and consequences of their client- or customer-focused service
quality for successfully bidding in the competitive fee tendering system.
The current study aims to apply the conceptual framework of Wang and
Lo (2003, 2004) to construction consulting services in Hong Kong. It was
originated from a Hong Kong government-funded project to model compet-
itive fee tendering in the local construction industry. An important objec-
tive of the project was to examine how service quality and customer satis-
faction are linked to the strategies and core competences of professional
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 167
consultants, so as to help them formulate service quality improvement pri-
orities and develop appropriate bidding strategies. For that purpose, this
paper first reviews the conceptual framework with developed detail con-
structs and proposed relationships. Then sampling method, measurement
scales and survey data are described and the structural equation modelling
(SEM) results are analysed, such as validating the measures and testing
the SEM’s goodness-of-fit and the expected relationships. Detail discus-
sions of the modelling results are presented next, which reveal a number of
relationships unique to knowledge-intensive services, such as professional
consulting in this study. Finally, concluding remarks are provided, includ-
ing managerial implications for service firms in general, and construction
consultants in particular, to improve their customer-focused performance,
as well as limitations of the current research and suggestions for future
studies.
The Conceptual Framework
This section will present a conceptual framework to link a firm’s resource-
based strategies to its customer-focused performance based on literature
review with a number of research hypotheses implicitly proposed. Resource-
based strategies include organizational learning, core competences and
strategic flexibility, while customer-focused performance is composed of
customer-perceived service quality and value, as well as customer satis-
faction.
Key Components of Customer-Focused Performance
As widely accepted in the marketing literature (Chan et al., 2003; For-
nell, Johnson, Anderson, Cha, & Bryant, 1996), especially due to their di-
rect relations to customer’s purchasing decisions, customer-perceived ser-
vice quality, customer-perceived service value, and customer satisfaction
can be regarded as the three comprehensive and effective dimensions of
customer-focused performance. It is noticed that the three dimensions of
customer-focused performance interact positively with one another. For ex-
ample, Oliver (1993) suggests that service quality should be antecedent to
customer satisfaction, and Fornell et al. (1996) further identify customer-
perceived value as another key driver of customer satisfaction. It is also
evident that enhanced service quality should increase service value (Chan
et al., 2003; Fornell et al., 1996).
Resource-Based Determinants of Customer-Focused Performance
Superior customer-focused performance can only be achieved through a
firm’s resource-based strategies, which interact with one another and are
combined to lay a solid foundation for the firm’s distinctive competences.
Volume 2, Issue 2, 2013
168 Ming-Lu Wu
The resource-based view allows each strategy or action to be referenced
to the delivery of quality services of high value, which in turn lead to the
satisfaction of customer requirements (Chmielewski & Paladino, 2007).
The firm must build and upgrade its own competences through organi-
zational learning and strategic flexibility to help identify business trends,
track customer-focused performance, and facilitate quick market response
(Akroush, 2012).
Core competences can be viewed as firm-specific skills and cognitive
traits directed towards the attainment of higher customer satisfaction in
comparison with the competitors (Hamel & Heene, 1994). These compe-
tences can be leveraged directly to satisfy the existing customer needs or
indirectly to develop a range of core services, based on which a stream of
final services of higher quality and value is delivered. According to the in-
tensive literature reviews by Bani-Hani and AlHawary (2009) and Wang and
Lo (2003, 2004), two distinct types of core competences can be identi-
fied: marketing competence that determines the target customers and mar-
ket demand of the firm’s service offerings, and technological competence
that determines the offerings’ technical contents. This is in line with the
three components of dynamic capabilities, a similar concept to core com-
petences, as summarized by Wang and Ahmed (2007): adaptive capability,
absorptive capability, and innovative capability. Largely, marketing compe-
tence corresponds to adaptive capability, and technological competence
relates to absorptive capability and innovative capability.
Integrative competence, although suggested by Wang and Lo (2003,
2004) as another type of core competences, is roughly a combination of
marketing and technological competences and hence will not be included
in this study for simplicity. It is expected that a firm’s core competences
positively affect its customer-perceived quality and value, which in turn help
the firm achieve higher customer satisfaction (Wang & Ahmed, 2007; Wang
& Lo, 2003, 2004).
Strategic flexibility is the ability of a firm to respond to the changes in the
environment in a timely and appropriate manner with due regard to the com-
petitive forces in the marketplace (Golden & Powel, 2000; Shimizu & Hitt,
2004). In modern economy, strategic, organizational, and marketing vari-
ables have to be adapted for the firms to be efficient (Milgrom & Roberts,
1995). As Kak (2004) argues, no matter how you understand the sources
or contents of strategic flexibility, core competences of a firm always exert
great influence on its strategic flexibility. For example, a firm’s marketing
competence determines its speed and cost to detect any changes in the
customer requirements or market demand, and its technological compe-
tence enables its provision of technologically new services to respond to
the market changes. That is, a firm’s core competences constitute the ma-
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 169
jor sources of its strategic flexibility and determine the level of its strategic
flexibility to a great extent.
It is also appropriate to assume positive impacts of a firm’s strategic
flexibility on its customer-focused performance (Matthyssens, Pauwels, &
Vandenbempt, 2005). Hence it can be expected that a firm’s strategic flex-
ibility mediates the impacts of its core competences on customer-focused
performance. Just as Wang and Ahmed (2007) propose, firm’s capabilities
or competences are ‘more likely to lead to better firm performance when
particular capabilities are developed in line with the firm’s strategic choice.’
This sounds appealing, since a firm’s strategic flexibility may be more di-
rectly felt by customers than its competences, which are built by the firm in
a longer process.
Organizational Learning. Addressed by Cyert & March (1963) over 50
years ago as a process by which organizations learn through interaction
with their environments, organizational learning acts as an important an-
tecedent of organizational competences (Murray & Donegan, 2003; Hung,
Yang, Lien, McLean, & Kuo, 2010). That is, firms must learn in practice how
to acquire, generate or explore as well as how to access, apply or exploit
relevant knowledge effectively and efficiently to remain competitive and up-
grade their core competences (Grant & Baden-Fuller, 2004; Kang, Morris,
& Snell, 2007). As performed in Wang and Lo (2003, 2004), this empiri-
cal study will measure and test organizational learning in a narrower sense
of learning orientation with three dimensions of straightforward meanings:
commitment to learning, shared vision, and open-mindedness. Indeed, as
Kang et al. (2007) and Murray and Donegan (2003) argue, it is the learning
environment, orientation or culture that fundamentally determines a firm’s
learning propensity and process, and hence its competence upgrading and
leveraging process.
All of the above expected relationships between the research constructs
lead to a path model as shown in Figure 1, which, after detail measures
for each construct are developed, forms a typical structural equation model
(SEM).
Sampling, Measurements and Data
Sampling Population
This study aims to examine how service quality and customer/client sat-
isfaction are related to the strategies and core competences of the out-
sourcing consultants in the Hong Kong construction industry, which gener-
ally requires data from two sources. On one hand, data from different con-
struction consultancy firms are needed to test the interactive relationships
among firms’ key resource-based strategies. On the other hand, data from
different customers are needed to test the interactive relationships among
Volume 2, Issue 2, 2013
170 Ming-Lu Wu
ζ1
Commitment to
Learning
ζ2
Shared
Vision
ζ3
Open
-Mindedness
η1
Marketing
Competence
η2
Technological
Competence
η3
Strategic
Flexibility
η4
Customer-
Perceived Quality
η5
Customer-
Perceived Value
η6
Customer
Satisfaction
0.128
(0.139)
0.223 (0.058)
0.
06
1
(0
.3
74
) 0.7
39
(0.0
01)
0.
24
5
(0
.1
46
)0.327
(0.064)
0.
14
4
(0
.1
69
)0.130
(0.124) 0
.3
1
2
(0
.0
3
1
)
0.767
(0.001)
0
.0
0
3
(0
.4
8
9
–0
.1
18
(0
.1
22
)
0.
31
9
(0
.0
11
)
0.176
(0.080)
0.705
(0.001)
0.
26
2
(0
.0
24
)
0.704
(0.001)
Figure 1 The conceptual model and estimated standardised path coefficients with one-tail
p-values (in brackets)
the key components of customer-focused performance. More importantly,
all of the surveyed customers should be the customers of the surveyed
firms in order to link and test the relationships between the two parts, i.e.,
firm’s resource-based strategies and customer-focused performance.
Ideally, the sampling procedure would be to first survey a number of
consultancy firms in order to get their self-evaluated resource-based perfor-
mance data, and then to interview a sufficient number of the customers
for each firm, whose responses are averaged to get a set of customer-
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 171
focused performance data for the particular firm. A firm’s resource-based
performance data and its corresponding customer-focused performance
data make up a complete data point or observation. For each firm, tens
of, if not hundreds of, its customers should be successfully surveyed to
make the customer-focused performance data representative and reliable.
In doing so, thousands of customers should be clearly identified and
successfully surveyed. This can only be done with full involvement of each
firm and is a heavy burden for the study. To be simple, customer-focused
performance data were collected indirectly from the firms surveyed and not
directly from the firms’ customers, i.e. only firms were surveyed. Each sur-
veyed firm not only supplied a set of its resource-based performance data
as usual, but also provided a set of its customer-focused performance data
as perceived by the firm itself, not by its customers as done in some simi-
lar studies (Salomann, Dous, Kolbe, & Brenner 2005; Nasution & Mavondo,
2008).
It is felt that professional service firms included in our study should
understand the quality of their services in general and the perceptions of
their customers in particular. Hence, the obtained customer-focused perfor-
mance data, although potentially over- or under-estimated, could be viewed
as an initial alternative in this exploratory study for the sake of simplic-
ity and cost-saving. Otherwise, similar to many empirical studies that are
primarily related to firms’ resource-based strategies (Murray & Donegan,
2003; Hung et al., 2010) or their customer-focused performance (Fink,
James, Hatten, & Bakstran, 2008; Hall, 2007), it is operationally and finan-
cially difficult for this research to link the two important parts. Furthermore,
due to their professionalism or ethics standards, these consulting firms are
also less likely to over-estimate their customers’ evaluations. In case of
possible over-estimations it should be noted that if all firms over-estimate
their customers’ perceptions in the same manner, the directions and sig-
nificance levels of the links from resource-based strategies to customer-
focused performance would be the same as using actual customer percep-
tions in a linear model as in this paper, which provides additional support
for our simplified approach.
Measurement Scales
The current research developed the measurement scales according to the
key ideas suggested by Churchill (1979), i.e. first mapping out the do-
main of each construct and then establishing the scale items to represent
the domain. The first issue of specifying the domains of the constructs in
this study has been addressed above where the components of customer-
focused performance and its key resource-based determinants have been
appropriately defined. As for the second issue, multi-item measures are
Volume 2, Issue 2, 2013
172 Ming-Lu Wu
strongly recommended to represent the domain of a construct to reduce
the measurement errors or increase the measurement reliability. Actually,
the use of multi-item measures is almost a must for a well-developed survey
instrument in practice.
Hence, a multi-item approach was adopted in this study with each con-
struct measured by several items to capture its domain reliably. In particu-
lar, resource-based strategies were directly evaluated by the firms accord-
ing to their actual performance, and customer-focused performance was
indirectly evaluated by the surveyed firms in relation to their established
goals, their major rivals in the marketplace, and their customers’ desires in
certain areas (Beard & Dess, 1981). Based on the previous discussions,
and especially on the reviews and suggestions of Wang and Lo (2003,
2004), multiple measurement items were developed to reflect each of the
three customer-focused performance constructs and the six resource-based
strategies constructs as shown in Table 1.
Each measurement item in Table 1 corresponded to a survey question,
which was answered using the popular 7-point Likert scale. For example,
the third survey question for the commitment to learning construct (denoted
as x13) was: ‘Learning in our firm is seen as a key to organizational survival.’
Respondents were asked to show, from ‘strongly disagree’ (coded as 1) to
‘strongly agree’ (coded as 7), their degrees of agreement with this positive
statement for the measurement item.
Survey and Data
Based on the above-proposed measurement scales, a questionnaire was
developed and mailed with a cover letter to a population of 355 Hong Kong
construction consultancy firms. These firms provided construction consult-
ing services in architecture, building surveying, etc. to local developers,
contractors, private clients and government departments. The names, ad-
dresses and persons in charge of these consulting firms were obtained
from local business trade directories and professional societies and asso-
ciations. Finally, 122 firms returned usable questionnaires, representing a
quite high response rate of 34.4 percent as compared to many similar sur-
veys (Salomann et al., 2005; Velcu, 2010). The corresponding data formed
the basis for this study, which, due to the high response rate, can be viewed
well representative of the professional consultants in the Hong Kong con-
struction industry.
Among the 122 construction consulting firms successfully surveyed,
45.9 percent were smaller with no more than 50 employees while 41.8
percent were relatively large with more than 200 employees, and 83.6 per-
cent had offered construction consulting services for more than 10 years.
In particular, 88.5 percent of the surveyed firms used the competitive fee
tendering system, of which 65.7 percent and 19.4 percent had positive and
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 173
Table 1 Constructs, Survey Items, Reliability Measures, and R-Squares
Constructs (ζi, ηj), survey items (xik, yjn), reliability measures and R-squares (R2) SFL
ζ1 Commitment to Learning (AVE = 0.770, Cronbach’s α = 0.903)
x11 The basic values of our firm include learning and knowledge sharing as
keys to improvement.
0.796
x12 Our firm sees ‘employee learning’ an investment, not an expense. 0.927
x13 Learning in our firm is seen as a key to organizational survival. 0.904
ζ2 Shared Vision (AVE = 0.768, Cronbach’s α = 0.907)
x21 There is a common goal in our firm (for example, to provide clients with
quality service).
0.831
x22 There is total agreement on our firm’s vision across all levels, functions
and divisions.
0.873
x23 All employees are committed to the goals of our firm. 0.923
ζ3 Open-Mindedness (AVE = 0.601, Cronbach’s α = 0.810)
x31 We are not afraid to review critically the assumptions we have made about
our clients.
0.877
x32 Colleagues realize that they must continually review and discuss the way
they perceive the market, in terms of the opportunities and threats in the
competitive market environment.
0.780
x33 We often collectively question the way we interpret clients’ information. 0.653
η1 Marketing Competence (AVE = 0.568, Cronbach’s α = 0.835, R2 = 0.801)
y11 Our capability in obtaining real time information about changes of clients’
needs is very strong.
0.728
y12 Our capability in communicating with clients about their potential and
current demands is very strong.
0.816
y13 We have strong capability in benchmarking our services to our major
competitors.
0.729
y14 We have strong capability of managing effectively long-term, close
relationships with clients.
0.737
η2 Technological Competence (AVE = 0.507, Cronbach’s α = 0.780, R2 = 0.550)
y21 Our firm always makes relatively heavy investment in R&D activities. 0.585
y22 We have accumulated a broad spectrum of strong professional knowledge
and skills.
0.665
y23 We are skillful in applying new technology, knowledge or practice to
problem-solving.
0.854
y24 We always lead the innovation of technology or practice in the construction
industry.
0.717
Continued on the next page
natural assessments of the system respectively, demonstrating the popu-
larity and effectiveness of the new project bidding system.
Modelling Results and Analyses
The covariance-based SEM approach was used to estimate and evaluate the
proposed model using the Amos package and the survey data. Following the
two steps recommended by Anderson and Gerbing (1988), the various mea-
Volume 2, Issue 2, 2013
174 Ming-Lu Wu
Table 1 Continued from the previous page
Constructs (ζi, ηj), survey items (xik, yjn), reliability measures and R-squares (R2) SFL
η3 Strategic Flexibility (AVE = 0.624, Cronbach’s α = 0.889, R2 = 0.591)
y31 We have strong capability to redirect the strategic positioning of our
services quickly and effectively.
0.793
y32 We have strong capability to respond quickly to the actions taken by our
competitors.
0.822
y33 We have strong capability to respond quickly to rapidly changing clients’
needs.
0.829
y34 We have strong capability to redeploy strategic resources quickly
according to environmental changes.
0.791
y35 Strategic resources in our firm can be used in many different areas. 0.709
η4 Customer-Perceived Quality (AVE = 0.833, Cronbach’s α = 0.936, R2 = 0.464)
y41 Our clients always get services of high quality from our firm. 0.866
y42 Our clients consider the quality of our services good. 0.918
y43 Our clients are confident of the quality of our services. 0.952
η5 Customer-Perceived Value (AVE = 0.582, Cronbach’s α = 0.775, R2 = 0.760)
y51 Overall, our services are value for money. 0.799
y52 Considering expenses and quality they get, clients believe that it is a right
decision to use our services.
0.848
y53 Our firm always tries to reduce the time and effort clients have to spend in
the process of obtaining and consuming our services.
0.624
η6 Customer Satisfaction (AVE = 0.684, Cronbach’s α = 0.865, R2 = 0.878)
y61 Our firm can provide services that meet client’s expectation. 0.775
y62 Comparing with the desirable level, our services always make clients
satisfied.
0.894
y63 Taking the major competitors’ services into consideration, clients are very
pleased with us.
0.808
Notes SFL – standardized factor loadings.
sures were first validated and then the proposed hypotheses or structural
relationships were tested.
Validating the Measures
To validate the measures of the constructs, the proposed model was first
estimated with all paths deleted, but all constructs assumed to be corre-
lated to each other. The estimated reliability results are summarized in Table
1. It can be seen that, firstly, the Cronbach’s coefficient α of each construct
is greater than the conventional threshold of 0.700, with a maximum of
0.936 for customer-perceived quality. This demonstrates each construct’s
composite reliability for internal consistency.
Secondly, the standardized factor loadings for all but one measurement
items are above the conventional cut-off of 0.6. In fact, among all of the
31 measurement items, 27 have factor loadings greater than 0.7. It is also
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 175
noticed that all factor loadings are highly significant (p < 0.001), showing
strong evidence of convergent validity of the measures. At the same time,
the average variance extracted (AVE) of each construct in the model is more
than 50 percent, with a maximum of 83.3 percent for customer-perceived
quality, guaranteeing that more valid variance than error is explained for
each construct (Fornell & Larcker, 1981).
Thirdly, the constructs should also show high discriminant validity which,
according to Fornell and Larcker (1981), can be demonstrated if the square
root of AVE of each construct is higher than the correlation coefficients be-
tween it and any other constructs in the model. Most AVEs and correlations
from the modelling results meet this criterion, largely showing that the con-
structs are both conceptually and empirically distinct from each other.
Evaluating the Model’s Fit
The full model estimation results provide various measures to evaluate the
model’s goodness-of-fit. Firstly, the estimated covariances and variances of
the model’s three exogenous organizational learning constructs, i.e. com-
mitment to learning, shared vision, and open-mindedness, are highly signif-
icant (p < 0.001). The estimated variances for the regression errors of the
model’s six endogenous constructs are also highly significant (p < 0.01).
These provide a good basis for correctly estimating the model.
Secondly, R-square (R2) for the regression equation to predict each of
the model’s six endogenous constructs is from 0.464 to 0.878 as shown
in Table 1, quite high as compared to many SEM studies. This indicates a
strong predictive power of the proposed model.
Thirdly, although the estimation results show a significant chi-square
(R2 = 748.47, df = 414, p < 0.001), other overall fit indexes are relatively
satisfactory given the smaller sample size in this study. Especially, the
model has a low χ2/df of 1.808, a reasonably high non-normed fit index of
0.874 and comparative fit index of 0.888, and a reasonably low root mean
square error of approximation of 0.082. These suggest an acceptably good
fit of the model to the data, providing a reliability support for testing the
cause-effect relationships between the model’s constructs.
Testing the Expected Impacts
The estimated standardized regression coefficient (b) for each path of the
model and the associated one-tail p-value are shown in Figure 1, which can
be used to test the expected impacts. It is noticed that the impact of tech-
nological competence on strategic flexibility and shared vision on marketing
competence is highly insignificant (p > 0.30) and cannot be verified. Also,
the impact of marketing competence on customer-perceived value, open-
mindedness on technological competence, commitment to learning on mar-
Volume 2, Issue 2, 2013
176 Ming-Lu Wu
keting competence, technological competence on customer-perceived qual-
ity and value is insignificant at the p<0.10 level, although four of them are
positive as expected.
Other expected impacts can be verified with significantly (p < 0.10) pos-
itive path coefficients, including the impact of commitment to learning
and shared vision on technological competence and strategic flexibility on
customer-perceived value. Especially, the impact of market competence and
strategic flexibility on customer-perceived quality and customer-perceived
value on customer satisfaction is significant at the p<0.05 level. Most no-
ticeable are the highly significant (p< 0.001) paths from open-mindedness
to marketing competence, from marketing competence to strategic flexibil-
ity, and from customer-perceived quality to customer-perceived value and
customer satisfaction.
Discussions of Modelling Results
Impact of Organizational Learning on Core Competences
In the current era of knowledge economy, it is not enough for firms to only
possess certain competences. To succeed, they must be able to develop
new competitive advantages through organizational learning to meet the
changing market conditions and customer needs. This is especially true
for construction consulting services, which are knowledge-intensive (but
not technology-intensive) and hence continuous organizational learning of
new knowledge is necessary for them to be technologically competitive.
Furthermore, these services are faced with different client needs for bud-
gets and project styles and hence continuous organizational learning of
changing market conditions is necessary for them to be marketing compet-
itive. That is, organizational learning is expected to enhance a firm’s core
competences. This study largely validates the hypothesis, evidenced by the
positive influences of the three components of organizational learning on
both technological and marketing competences as shown in Figure 1. In
detail, the modelling results reveal that:
1. A firm’s commitment to learning has a more significant impact on
its technological competence (b = 0.223, p = 0.058) than on its mar-
keting competence (b = 0.128, p = 0.139). This seems natural since
technological competence, as opposed to marketing competence, is
indeed based more on acquiring, processing and applying new infor-
mation and knowledge – all reflected in commitment to learning.
2. Shared vision has a much more significant impact on the techno-
logical competence (b = 0.327, p = 0.064) than on the marketing
competence (b = 0.061, p = 0.374), implying that a higher degree
of shared vision can improve the technological competence, but may
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 177
not improve the marketing competence. This possibly suggests that
marketing competence – building closer relationships with customers
– requires more flexibility or open-mindedness than shared vision or
uniformity. Another point to support this result is that shared vision
is more important than flexibility for harmonious communication be-
tween experts and employees in acquiring and sharing new knowledge
and skills to improve the technological competence.
3. Unlike commitment to learning and shared vision, which have more
significant influences on the technological competence than on the
marketing competence, open-mindedness has a much more signif-
icant impact on the marketing competence (b = 0.739, p < 0.001)
than on the technological competence (b = 0.245, p = 0.146). This
is understandable, since, among the three dimensions of organiza-
tional learning, open-mindedness requires the firm to continuously
and critically review market conditions and customer requirements to
the greatest extent, which associates more with marketing compe-
tence than with technological competence.
Impact of Core Competences on Customer Perceptions
The modelling results reveal a much more significant impact of marketing
competence on customer-perceived quality (b = 0.312, p = 0.031) than on
value (b = 0.144, p = 0.169). This implies that, for construction consult-
ing services, a firm’s marketing competence may be viewed more from the
quality perspective than from the value side to create higher customer sat-
isfaction. Since service quality can be perceived more easily and objectively
than service value, firms tend to build their competences, including mar-
keting competence, mainly for improving their service quality. In this study,
construction consultancy firms are engaged in competitive fee tendering,
which will specifically assess the firms’ quality scores in addition to their
bidding prices. Hence firms’ endeavours or competences should indeed be
devoted to the service quality side, which in fact is also the major objective
– measuring and managing service quality – of this research.
This study fails to demonstrate a significant impact of the technological
competence on both customer-perceived quality and value. As construction
consulting services are not technology-intensive, this implies that techno-
logical competence may not considerably help a construction consulting firm
in improving its customer-perceived quality and value, hence it may not be
particularly necessary to be technologically competitive.
The Mediating Roles of Strategic Flexibility
Strategic flexibility plays a mediating role in the proposed model to link a
firm’s competences to its customer-focused performance. On one hand, the
Volume 2, Issue 2, 2013
178 Ming-Lu Wu
model shows that market competence exerts a substantially more signifi-
cant impact (b = 0.767, p<0.001) on strategic flexibility than technological
competence (b = 0.003, p = 0.489). This is not unexpected. A firm’s market
competence is based on a profound understanding of customers’ current
and future needs and competitors’ possible actions, which will help the
firm to respond quickly to market changes and hence enhance its strategic
flexibility. But a firm’s technological competence is unique in some sense,
and hence is usually difficult to replace by substitute processes, difficult for
competitors to imitate, and immobile across firm boundaries (Grant, 1991),
which may not enhance its strategic flexibility.
On the other hand, the modelling results reveal that strategic flexibility
has a more significant impact on customer-perceived quality (b = 0.319,
p = 0.011) than on customer-perceived value (b = 0.176, p = 0.080). This
could again be understood from the reasoning that construction consulting
firms’ endeavours are likely to focus more on their professional service qual-
ity, which can be more easily perceived by the clients. Combining with the
previous results, this study also reveals a leading role of strategic flexibil-
ity in enhancing the customer-focused performance – among the resource-
based determinants (i.e. technological competence, marketing competence
and strategic flexibility) of customer-perceived quality and value, strategic
flexibility is the most important with the largest and most significant impact
coefficients.
Finally, it is interesting to examine the strategic flexibility’s mediating role
in linking a firm’s competences to its customer-focused performance. Since
the direct impact of technological competence on customer-perceived qual-
ity and value and on strategic flexibility is insignificant, strategic flexibility
does not mediate the impact of technological competence on customer-
focused performance at all. However, the mediating role of strategic flexi-
bility in linking a firm’s marketing competence to its customer-focused per-
formance is obvious, evidenced by considerable direct impact of market-
ing competence on customer-focused performance and also indirect impact
through its significant influence on strategic flexibility. This again shows that
marketing competence is more important than technological competence in
improving customer-focused performance for consulting services.
In detail, strategic flexibility has a strong mediating role in linking a firm’s
marketing competence to its customer-perceived quality, as implied by sig-
nificant direct impact of marketing competence on customer-perceived qual-
ity and its significant indirect impact via strategic flexibility. But its mediat-
ing role is much weaker in linking a firm’s marketing competence to its
customer-perceived value, as evidenced by a much less significant direct
impact of marketing competence on customer-perceived value and its less
significant indirect impact via strategic flexibility. This once again demon-
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 179
strates that a consulting service firm’s marketing competence has more to
do with customer-perceived quality than with customer-perceived value, with
or without the mediation role of its strategic flexibility.
Customer-Perceived Quality and Value
As well established in the marketing literature, this study confirms that
customer-perceived quality helps enhance customer-perceived value and
that both customer perceived quality and value increase the customer sat-
isfaction. In the study it is noticed that these customer perceptions are not
really from the clients themselves, but are ascertained by the consultancy
firms. The confirmed significant relationships among these ‘customer’ per-
ceptions prove the quality of the existing measures of structural relations
among the customer-focused performance constructs. This shows the ap-
propriateness of letting firms (indirectly) reveal customer perceptions, as
performed in this study, since it is reasonable to assume that firms should
be able to know, at least partly, their customers’ perceptions.
The positive path coefficients relating customer-perceived quality to value
and satisfaction are highly significant (p < 0.001), showing the strong pre-
dictive power of quality on value and satisfaction. A positive impact of
customer-perceived value on satisfaction is also significant (p < 0.05), but
weaker than the impact of quality. This is in line with the marketing notion
that value may be more essential for customers’ initial choices, but quality
is much more fundamental for their consumption experiences (Fornell et
al., 1996). In fact, the above modelling results demonstrate much stronger
impacts of core competences and strategic flexibility on customer-perceived
quality than on customer-perceived value, logically suggesting a higher im-
portance of quality than value. The dominating role of quality over value
in forming customer satisfaction also supports the previous results that a
service firm should associate its competences and strategic flexibility more
with quality than with value.
Summary and Concluding Remarks
Originated from a Hong Kong government-funded project to model compet-
itive fee tendering in the local construction industry, this study aims to
examine how customer-focused performance relates to professional con-
sultants’ core competences, and hence to help them formulate service
quality improvement priorities for developing appropriate bidding strategies.
By establishing a structural equation model (SEM) with the help of survey
data collected from local construction consultants, the current paper largely
validates the conceptual framework of Wang and Lo (2003, 2004), which
links a firm’s resource-based strategies to its customer-focus performance
and hence accomplishes the proposed research objective. In general, the
Volume 2, Issue 2, 2013
180 Ming-Lu Wu
modelling results support the positive impacts of organizational learning
on a firm’s core competences, which in turn positively influence customer-
focused performance directly and indirectly through its strategic flexibility.
In particular, a number of hypothesized impacts are verified at the one-tail
10 percent significant level, including the positive impact of commitment to
learning and shared vision on technological competence, open-mindedness
on marketing competence, marketing competence on strategic flexibility and
customer-perceived quality, and strategic flexibility on customer-perceived
quality and value.
Managerial Implications
This study also reveals several relationships unique to the construction con-
sulting businesses that are not technology-intensive, which have managerial
implications for professional services. Firstly, a firm’s degree of shared vi-
sion exerts much bigger influence on its technological competence than on
its marketing competence, while its open-mindedness has just the reverse
pattern of effects. This implies that, if technological competence is consid-
ered more important, the firm should maintain a higher degree of shared
vision or uniformity to promote harmonious communications between its
experts and employees in acquiring and sharing new knowledge and in-
formation. However, if marketing competence is deemed more influential,
which is usually the case for services, the firm needs more flexibility or
open-mindedness to continuously review the market conditions in order to
build closer relationships with customers.
Secondly, a firm’s marketing competence has much stronger impact on
its strategic flexibility and customer-perceived quality and value than its
technological competence. This shows that the higher cost and lower pro-
vision rates of technological competence make it less influential than mar-
keting competence for the strategic flexibility and customer-focused perfor-
mance of professional service firms, which are not technology-intensive.
Such service firms are better off to deploy their resources more on building
marketing competences, such as actively understanding customers’ current
and future needs and competitors’ possible actions, and quickly responding
to market changes and providing operational solutions.
Thirdly, a firm’s competences and strategic flexibility have greater impact
on customer-perceived quality than on customer-perceived value, leading
to somewhat unusual conclusion that quality is much more important than
value in forming customer satisfaction for professional services. This im-
plies the dominating role of quality over price in professional services, which
are highly knowledge-intensive (but not necessarily technology-intensive)
and whose clients are usually highly knowledgeable. Hence, firms should
pay more attention to their service quality than offering prices by not only
International Journal of Management, Knowledge and Learning
Linking Resource-Based Strategies to Customer-Focused Performance 181
maintaining their technological competences, but continuously improving
their marketing competences and strategic flexibilities as well.
Research Limitations and Future Directions
This paper demonstrates the influential links from resource-based strate-
gies to customer-focused performance for professional services using a
conceptual framework and survey data from 122 construction consulting
firms in Hong Kong. As reported above, the research findings are interesting
and have certain managerial implications. However, since the constituents
of organizational learning, core competences and strategic flexibility and
their differentiated effects on customer-focused performance have only re-
cently emerged as an important subject for empirical research (Duysters
& Hagedoorn, 2000; Wang & Lo, 2003, 2004), limitations do exist in this
paper, and future studies should attempt to overcome them.
Firstly, although many relationships in the conceptual framework are vali-
dated in the study, some are found to be insignificant at the one-tail 10 per-
cent level, including the links from shared-vision to marketing competence
and from technological competence to strategic flexibility. Similar studies
are thus needed to verify all relevant relationships expected from the con-
ceptual framework. Especially, more samples from not technology-intensive
services are required to verify the dominating role of marketing competence
over technological competence in achieving superior customer-focused per-
formance. Studies of services with more technological requirements are
also called for to distinguish the different roles of marketing and techno-
logical competences of different firms in enhancing their customer-focused
performance.
Secondly, this study is based on an admittedly small sample of 122 con-
struction consulting firms in Hong Kong, which may be the major reason
for the SEM’s not-so-good fitting, including a number of insignificant paths.
Given the small economic scale of Hong Kong and the highly knowledge-
intensive nature of the construction consulting services, the sample size
of 122 is actually not unacceptably small. However, corresponding to the
model’s 9 constructs and 31 measurement items, the sample size is in-
deed small. In this regard, the current research with the limited survey data
has little room to improve, and future researches are required to conduct
larger scale of surveys of firms in different service settings to present more
complete and reliable studies into the important cause-effect chain from
organizational learning to core competences and then to customer-focused
performance.
Thirdly, due to the difficulty in identifying and surveying each firm’s cus-
tomers, customer-focused performance data were simply obtained from the
firms, not directly from the customers. Although difficult, it is still hoped
Volume 2, Issue 2, 2013
182 Ming-Lu Wu
that future studies can obtain data from the firms for their resource-based
strategies and data from each firm’s customers for their perceptions of the
firm’s performance, and hence more reliably examine the conceptual frame-
work linking a firm’s resource-based strategies to its customer-focused per-
formance.
Acknowledgements
This research was partly supported by a College Research Grant (CRG11-
12/B/06) from BNU-HKBU’s United International College. The author thanks
Dr. Hing-Po Lo for initial discussions of the research idea.
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Ming-Lu Wu received his Ph.D. degree in mathematical statistics from the Chi-
nese Academy of Sciences in 1994. He has more than 25 years of research
and teaching experiences in actuarial mathematics, consumer satisfaction,
decision science, economic analysis, performance assessment, quality man-
agement and structural equation modelling in Australia, China, and Hong
Kong. He has published three books and hundreds of papers and articles,
some of which have been frequently cited in the academic circles, and has
also been on the Editorial Board of Environmental Modelling and Assessment
since 2009. mlwu@uic.edu.hk
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International Journal of Management, Knowledge and Learning