Effect of Social Capital and Absorptive Capability on Innovation in Internet ...
Yi-Ching Tsai
International Journal of Management; Mar 2006; 23, 1; ABI/INFORM Global
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International Journal of Management
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Effect of Social Capital and Absorptive Capability on
Innovation in Internet Marketing
Yi-ChingTsai
National Taipei University, Taiwan
This study explores how website structure and customer relationships affect customer
knowledge flow and innovation in Internet marketing in Taiwan. This investigation
assumes that the website is a center of information flow and that visiting customers are
network members. These two elements thus form the Internet marketing network. This
study also uses the concept of 'social capital' frequently used in network study and
discusses the effect of structure and relationship on innovation performance. Meanwhile,
each website is assumed to differ in 'absorptive capability' of customer knowledge
owing to differences in its design. The analytical results show that a website with
abundant social capital will have higher 'absorptive capability' and 'innovation
performance' than a website that lacks social capital. Furthermore, if a website structure
has higher centrality, equivalence and density, it will successfully transfer more customer
knowledge. Such a website can provide more creative information and service, meet
customer needs and satisfy customers.
Introduc tion
The Internet has become a key marketing channel in Taiwan, just as in other developed
economies. As estimated by the Institute for Information Industry (III) in 2002, the size
of the Taiwanese e-business market will grow to approximately USD 12.3 billion in
2004, compared to USD 1.1 billion in 2000. Internet marketing can rapidly create large
market economies at high speed, and Internet marketing is clearly crucial to the
development of modern economies. However, according to some e-business research,
the critical factor in obtaining business opportunities and encouraging consumption in
the present era of rapid change is to appreciate customer needs (Hoffman et al., 1999).
When customers trust a website, they are likely to buy products or seek product
information through that website.
Previous studies often stress that customer interaction is helpful for absorbing customer
knowledge. However, compared to traditional 'one-to-many' marketing media, internet
is a media with 'many-to-many' characteristic. Thus, if we use traditional measurement
of interaction to study the internet, the explanation is not strong enough. Internet
characteristics formed in many-to-many environment should also be considered.
Therefore, this work applies the 'social capital' theory of networks, and uses network
structure characteristics to represent the structural factors of social capital. Those
characteristics include centrality, structural equivalence, and network density.
Additionally, the constructs of website-customer relationship and customer-customer
relationship were used to represent network member relationship quality. Finally, this
study uses absorptive capability to measure the effect of customer knowledge flow and
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adopts the concepts of 'social capital' and 'absorptive capability' to discuss the influences
of the concepts of 'social capital' and 'absorptive capability' on website innovation
performance.
Literature Review
Previously, most researchers considered economic behavior to be constrained by
continuing social connections. From the perspective of social structure, Burt (1992),
Nahapiet and Ghoshal (1988) think all people should participate in a society in which
there are shared norms and established social structures, relational and institutional
embeddedness. Under such conditions, they can create common social wealth and values.
Individuals intending to break or exit the connections would affect the productivity of
others to create value. Furthermore, those objects that are embedded in social structure,
institution and relationships are termed 'social capital'.
Nahapiet and Ghoshal defined the structural dimension of social capital as the 'holistic
connection pattern among members'. In this dimension, important constructs used in
previous researches including network connections among members, network structure
and morphology. The criteria used for measuring the connection pattern include density,
connectivity and level.
Nahapiet and Ghoshal also integrated previous studies and pointed out that social capital
should include structural and relational dimensions. Granovetter (1985) divided social
capital into structural embeddedness and relational embeddedness dimensions.
Granovetter also argued that website structure will improve relationships among
members with better structures. Therefore, structural embeddedness positively affects
relational embeddedness. On the basis of the above considerations, the following
hypothesis is proposed:
H1: Structural embeddedness positively affects relational embeddedness.
Structural Embeddedness
Granovetter (1992) noted that structural embeddedness includes social system and overall
relational network characteristics. Structural embeddedness could be defined as the
impersonal connection structure among people or units.
This study defines structural embeddedness in accordance with the proposals of Davi
and Ravindranath (2001). The measurement of structural embeddedness includes
centrality, structural equivalence and network density. Structural embeddedness provides
network members with more efficient information flow (Jones et al., 1997).
Centrality of structural embeddedness refers to individual positioning in the Internet,
and also ensures that the connection is meaningful (Wasserman and Faust, 1994). Higher
centrality implies more important status and power (Wasserman and Faust, 1994), more
resources (Brass and Burkhardt, 1992) and more rapid resource flow (Gnyawali and
Madhavan, 2001), as well as easy information receipt and update. This investigation
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uses the ability to control information flow in a website environment and customer
trust in the website for measuring centrality.
Structural equivalence measures partnership among network members. Information
exchange among members becomes closer with increasing structural equivalence. A
website manager can build equivalence among network members, to make the status of
members more equal, and also to control the information exchange among network
members (Roger, 1995).
Additionally, network managers with higher centrality can increase network member
numbers (Gulati, 1995), namely, enhance network density. In this study, network density
means the numbers of customers in a website, and also describes the percentage of
customers who really provide information, compared to those who do not give any
information.
Previous structural embeddedness-related papers pointed out that structural
embeddedness affects organizational absorptive and innovative capability (Chen and
MacMillan, 1992; Ferrier et al., 1999). On the basis of the above considerations, the
following hypotheses are proposed:
H2: Structural embeddedness positively affects absorptive capability.
H3: Structural embeddedness positively affects innovation performance.
Relational Embeddedness
The concept of relational embeddedness was originally used in communication studies.
This concept was used to describe the phenomenon of one-to-one resource distribution.
Subsequently, this concept was gradually applied in intra-organization or betweenorganization studies (Burt, 1992). Some authors also pointed out that relational
embeddedness significantly affects competitive advantages (Dyer, 1998).
'Relational embeddedness' describes interpersonal relationship developed by
interpersonal interactions during a specific period (Granovetter, 1992). Nahapiet and
Ghoshal (1998) defined the relational dimension of social capital as 'the asset created
and used through relationship.' In this dimension, previous studies have used important
constructs like trust, trustworthiness, norm, sanction, obligation and expectation, identity
and identification to study relational embeddedness.
This study defines customer network connection as a connection among customers
who provide a website with information or knowledge (McEvily and Zaheer, 1999;
Uzzi, 1997). Gulati (1998) also mentioned that website participants are inclined to
cultivate their shared and mutual understanding behaviors to make such social
relationships the consensus. This one-to-one connection is a key for knowledge sharing
(Cohen and Levinthal, 1990). Uzzi (1997) noted that under one-to-one relationship,
members share their information and suggestions more when the connection is stronger.
Therefore, under a strong connection relationship, it is easier to achieve better effects in
terms of mutual network learning, adapting to uncertain environments, knowledge flow
and innovation.
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This work divides relational embeddedness into 'website-customer relationships' and
'customer-customer relationships'. Based on the above literature review, the
establishment of those two relationships will assist knowledge absorption. First, from
the perspective of website-customer relationships, websites with better relationships
with customers will attract customer visits and make customers willing to provide
varieties of knowledge. Second, from the perspective of customer-customer relationship,
customers with better mutual relationships will exchange their opinions easily and
extensively. Through group discussions, customers will give opinions related to products
or service improvement to the service provider. These feedbacks benefit absorptive
capability and innovation performance.
Previous papers have observed that relational embeddedness affects organizational
absorptive and innovative capability. On the basis of the above considerations, the
following hypotheses are proposed:
H4: Relational embeddedness positively affects absorptive capability. H5:
Relational embeddedness positively affects innovation performance.
Absorptive Capability and Innovation Performance
Absorptive capability refers to the capability of a business to manage knowledge for
customers, that is, the ability to acquire, transfer, update, renew and apply customer
knowledge. Absorptive capability is extremely helpful for innovation (Wong, 1995).
Cohen and Levinthal (1990) defined absorptive capability as the capability of 'a business'
to understand external information value, and to apply it for business innovation.'
In this study, website innovation performance measures website innovation in providing
service and information. The measurement proposed by Olson et al. (1995), which
includes speed of providing information, degree of goal achievement, service quality,
customer satisfaction and degree of service success is used to measure website
innovation.
Absorptive capability not only assists the performance of organizational innovation
(Chanaron and Perrin, 1987), but also as a source of sustainable competitive advantage.
The influence of absorptive capability is more prominent in the information or
technological industries (Bettis and Hitt, 1995; Tushman and Anderson, 1986). On the
basis of the above considerations, the following hypotheses are proposed:
H6: Absorptive capability positively affects innovation performance.
Research Method
This study surveyed Internet marketing stores in Taiwan. Items for each concept were
developed or borrowed from previous research and modified. The questionnaire can be
divided into three parts. The first part includes 15 items and measures social capital.
Meanwhile, the second part includes 12 items and measures absorptive capability. Finally,
the third part includes five items and measures innovation performance. Respondents
rated their perceptions of the items using seven-point Likert-type scales, which range
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from 'strongly agree' to 'strongly disagree'. Developed from the previous literature,
items have content validity. Additionally, items also have reliability owing to the result
of Cronbach's alpha (all results exceed 0.8). Finally, this research uses LISREL to analyze
the data to determine whether the hypotheses are supported.
Sampling
This survey studies Internet marketing stores in Taiwan. From the book "2003 List of eStores in Taiwan" published by the government, 'Direct transaction with customer'
section was selected. The electronic questionnaires were then distributed to 1067 stores.
Two hundred and twenty stores returned completed questionnaires. After deleting eight
unusable questionnaires, 212 (19.87%) responses were deemed usable.
Research Results
The relationships between constructs were examined using LISREL, and their results
are presented in Fig. 1 and summarized below, with the implications being discussed in
the following section. Evidently in Fig. 1, this model fits the data closely: X2 /df =2.422,
GFI=0.94, AGFI=0.90, IFI=0.91, CFI=0.96, RMR=0.042. The result demonstrates that
the proposed model is supported by empirical data .
Figure 1. LISREL Analysis Model for Research Framework
(Figures are factor loadings; t > 1.96, *p < 0.05; t > 2.58, **p < 0.01; t > 3.29, ***p < 0.001)
X2
73.26
df
30
AVdf GFI
2.422 QM
AGFI
IFI
Q_%
CFI RMR
a% 0.042
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This investigation then more closely examined the relationship between latent
independent variables and latent dependent variables in the LISREL model. From the
perspective of structural embeddedness, as shown in Fig. 1, structural embeddedness
positively affects absorptive capability and innovation performance. The factor loading
of structural embeddedness and absorptive capability is 0.8, compared to 0.82 between
structural embeddedness and relationship embeddedness. The result shows that network
structure significantly influences absorptive capability. Additionally, the factor loading
of structural embeddedness and innovation performance is 0.35, which suggests that
improved network structure significantly helps innovation.
Relational embeddedness also positively affects absorptive capability, but the factor
loading isjustO.01. Relational embeddedness negatively affects innovation performance,
but the factor loading is also only -0.01. Obviously, even if relational embeddedness
affects absorptive capability and innovation performance, the influence appears to be
weak. Compared to structural embeddedness, relational embeddedness appears not to
be very helpful for customer knowledge flow and innovation.
According to the empirical result, only H5 is not supported; that is, the hypothesis that
'relational embeddedness positively affects innovation performance' is not supported.
Table 1 lists the results. Because the whole model includes both measurement and
structural models, all parameters are in their standardized form, which ranges between
-1 and +1.
As shown in Table 1, most hypotheses are supported except H5. The original hypothesis
suggested that relational embeddedness positively affects innovation performance, but
the result of empirical analysis indicates that the effect is negative. However, if relational
embeddedness influences innovation performance through absorptive capability, the
effect becomes positive. The explanation could be that relational embeddedness has a
more positive effect if it is through the transformation mechanism of absorptive
capability.
Table 1. Path Analysis of Latent Variables
Independent Variables
Dependent Variables
Dynamic Capability
Innovation Performance
Effect
t
Effect
t
Structural Embeddedness
Direct effect
0.80
g -75***
0.35
3.50***
Indirect effect
0.26
3 39***
Overall effect
0.80
g75***
0.77
11.66***
Relational Embeddedness
Direct effect
0.01
1.97*
-0.01
2.59*
Indirect effect
0.01
2.71*
Overall effect
0.01
1.97*
-0.01
2.99*
Dynamic Capability
Direct effect
0.54
5.89***
Indirect effect
Overall effect
0.54
5.89***
(Figures are factor loadings; t>1.96,
*p
< 0.05; t> 2.58, **p<0.01;t>3.29, ***p< 0.001)
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Based on the above statistical analysis, this study finds that structural and relational
embeddedness affects absorptive capability and innovation performance differently. To
explain the interactive relationship between social capital and absorptive capability, this
investigation applies regression analysis and draws the model relationship as illustrated in
Fig.2. Innovation performance increases with increasing structural embeddedness of a website,
accompanied by increased absorptive capability. As for relational embeddedness, websites
with the higher relational embeddedness and lower absorptive capability will reduce
innovation performance.
Discussion and Conclusion
The question of how a website uses customer manage to innovate and achieve good
performance is a crucial one. This study explores the social capital that resides in websites and
discusses its influence on customer knowledge flow in the context of Taiwanese Internet
stores. The best answer to the above question appears to be 'to ensure a good structural
network and absorptive capability'.
First, in the dimension of structural network, this study assumes the website to be the center of
the network of information flows between customers. The empirical data demonstrates that
websites with higher centrality will acquire more customer knowledge. In conclusion, the
website should have the power to control customer knowledge. Second, this work examines
the composition characteristics of the network, namely, the equivalence between members.
This study surveys how websites recognize customer loyalty. Based on the previous literature
and this study, it is found that websites dealing with each customer equally will have higher
equivalence; therefore, customers will easily have chances to exchange knowledge and
information they have. Nowadays, numerous websites divide their members by classifying
them into different levels and grades. This policy would limit customer Internet use, reduce the
interchange space of some customers and lower the effect of customer knowledge flow.
Figure 2. Results of Interaction Effect
Innovation
Performance
▲
High Structural
Embeddedness
Low Structural
Embeddedness
Innovation
Performance
A
High Structural
Embeddedness
Low Structural
Embeddedness
Absorptive
Capability
Absorptive
Capability
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With regard to structural embeddedness, this study discusses network density, which
means the percentage of customers who really provide knowledge. The result of empirical
analysis demonstrates that the absorptive capability and innovation performance of a
website increase with increasing network density. Rapidly increasing the number of
customers in a network is difficult. However, a website should do its best to ensure that
a mechanism exists through which customers can offer different knowledge. Therefore,
if a website could provide appropriate feedback or build up interesting communication
interfaces, it would be helpful for visiting customers to keep their knowledge on the
website.
In respect of the relational embeddedness of social capital, according to the result of
LISREL, as shown in Fig. 1, maintaining good relationships with customers does not
guarantee higher absorptive capability and innovation performance. However, a website
that has higher absorptive capability, with a better relationship between website and
customers, will have higher innovation performance. This conclusion means that a
website should give priority to establishing the absorptive capability mechanism for
building good customer relationships and achieving improved performance.
This study is based on the Internet marketing environment. Network structure is found
to be able to improve customer knowledge absorption compared to relational structure.
The explanation could be attributed to the difficulty of maintaining relationships and
controlling customer loyalty in Internet marketing environments. Under such conditions,
more attention should be paid to establishing a network structure. If a mechanism and
good interactive interface can be built through which customers can provide personal
information and knowledge, this would help to enhance the absorption capability of,
and customer knowledge in, the Internet.
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