The role of organizational capabilities in successful e-business implementation
Lee, Chih-Ping; Lee, Gwo-Guang; Lin, Hsiu-Fen.
Business Process Management Journal
13. 5 (2007): 677-693.
13. 5 (2007): 677-693.
Abstract (summary)
Based on organizational capabilities and information technology implementation literature, this study seeks to propose a research model to examine the influence of organizational capabilities on e-business implementation success. Data collected from 202 information systems executives in large Taiwanese organizations were employed to test the relationships between the research model constructs. The results from the structural equation modeling approach provide quite a strong support for the hypothesized relations. The results showed that certain factors related to organizational learning and knowledge management capabilities are important antecedents of e-business value. This study did not test all organizational factors, and focused particularly on learning capacity and knowledge capability factors. A knowledge asset must be rare and inimitable to become a source of competitive advantage. Without secure processes, knowledge loses the key qualities of being rare and inimitable. Knowledge management means recognizing and managing all of an organization's intellectual and social capital to meet its e-business objectives. An organization needs a well-designed knowledge management infrastructure to create and maintain the e-business knowledge required to improve back-office efficiency, customer intimacy and efficiency of coordination with business partners.
Full Text
Proactively managing radically changing external environments, organizational capability and technological innovation are crucial to business success ([56] Veliyath and Fitzgerald, 2000; [59] Yam et al. , 2004). E-business (electronic business) is critical to technological innovation strategy, since it integrates internet-based systems with core business potentially affecting the whole business ([34] Kim and Ramkaran, 2004; [58] Xie and Johnston, 2004). E-business is defined as any commercial or administrative transaction or information exchange made available over the internet ([44] Moodley, 2003; [57] Wang and Cheung, 2004). Based on various types of trading partners, e-business can be categorized into business-to-business (B2B) and business-to-consumer (B2C) environments ([35] Koh and Maguire, 2004). The B2B activities include online purchase or procurement between customer and supplier, such as supply chain management (SCM) and enterprise resource planning (ERP) systems. They are comprised of back-office systems. The B2C activities include consumer's online inventory tracking before ordering a product. An example of the B2C e-business application is customer relationship management (CRM) and it is comprised of the front-office system. E-business enables firms to use the internet to share information, facilitate transactions, improve customer services and strengthen supplier integration ([62] Zhu and Kraemer, 2002).
Although e-business has technical components, management issues must be addressed regarding changes in organizational processes and interaction both within a firm and among firms ([3] Ash and Burn, 2003). For example, [45] Raman et al. (2006) argued that organizational capabilities are playing important roles in successful CRM implementation. [51] Saini and Johnson (2005) also examined that firm capabilities (such as information technology (IT) capability, strategic flexibility, and trust-building capability) are critical for superior firm performance in electronic commerce (e-commerce). Moreover, developing organizational learning and knowledge management strategies has been considered an effective and efficient means of successful IT implementation ([38] Lin and Lee, 2005). This perspective has been strengthened by several recent studies ([49] Raymond and Blili, 2000; [40] Malhotra et al. , 2005; [47] Ravichandran, 2005). However, empirical studies have seldom addressed the organizational capabilities (such as organizational learning and knowledge management capabilities) influencing e-business contribution to firm performance.
Based on organizational capabilities and IT implementation literature ([36] Lee, 2001; [38] Lin and Lee, 2005; [51] Saini and Johnson, 2005; [45] Raman et al. , 2006), this study proposes a research model to examine the influence of organizational capabilities on e-business implementation success. In the proposed model, the organizational capabilities construct is decomposed into organizational learning capabilities (training available, technical expertise and knowledge level) and knowledge management capabilities (knowledge acquisition, knowledge application and knowledge sharing). The research model and hypothesized relationships are empirically tested using the structural equation modeling (SEM) approach, supported by LISREL software. This study is significant for at least two reasons:
it determines the key antecedents to successful e-business implementation based on organizational learning and knowledge management perspectives; and
it helps to understand the effects of organizational capabilities and e-business contribution on a firm's performance.
Finally, this study has implications for e-business managers or policy-makers in formulating policies and targeting appropriate organizational capabilities to ensure effective e-business implementation.
E-business and e-business implementation success
E-business
E-business, more than just establishing an internet presence or conducting e-commerce transactions, concerns redefining old business models and maximizing business value ([33] Kalakota and Robinson, 1999). E-business is complex to use involving business process changes and significant financial investments in areas such as computing and networking infrastructure and human resource management ([1] Aldin et al. , 2004; [57] Wang and Cheung, 2004). E-business includes e-commerce, as well as both front and back-office systems that constitute the engine of modern business ([33] Kalakota and Robinson, 1999).
E-business applies packaged software applications that link and manage information flows within and across complex organizations, enabling managers to make decisions using information that truly reflects the current state of their business. Furthermore, e-business represents a new way to manage businesses and relationships with trading partners and reflects a firm's strategic intention to use the internet to share information, facilitate transactions, improve customer service and strengthen back-office integration ([61] Zhu, 2004).
E-business implementation success
E-business enables firms to conduct electronic transactions with any business partners along the value chain, and creates opportunities for companies to establish interactive relationships with business partners (such as suppliers, logistics providers, wholesalers, distributors, service providers and end customers), improve operating efficiency, and extend their reach, all at a very low cost ([3] Ash and Burn, 2003). E-business implementation success refers to the impact of e-business application on firm performance in term of downstream markets, internal operations and upstream procurement ([61] Zhu, 2004). Abundant information about downstream markets enables firms to expand sales channels and enhance customer relationships ([37] Lederer et al. , 2001). E-business can to improve business efficiency and staff productivity within organizations when complementary resources exist ([14] Chircu and Kauffman, 2000). The broad interactivity and connectivity of the internet upstream can decrease transaction costs and facilitate firms' coordination with business partners ([41] Malone et al. , 1987).
Recently, many researchers have studied e-commerce or e-business implementation success. For instance, [10] Bradford and Florin (2003) integrated innovation and information systems (IS) theories to develop and test a model of ERP implementation success. The analytical results revealed that top management support, training, perceived complexity of ERP and competitive pressure significantly influence the ERP implementation success. [53] Stylianou et al. (2003) examined the effect of various environmental, organizational and personal factors on management attitudes to e-commerce. [46] Ranganathan et al. (2004) investigated the assimilation of web technology systems into internal supply-chain functions and their external diffusion into inter-organizational supply-chain networks, and explored the relevant environmental determinants. These findings indicate that the internal assimilation and external diffusion of web technologies both significantly affect the benefits of SCM. A more recently survey by [64] Zhu et al. (2004) adapted the technology-organization-environment framework to investigate six factors (technology readiness, firm size, global scope, financial resources, competition intensity and regulatory environment) affecting value creation of e-business. Although these studies have provided significant insights into the relationship between various factors and the benefit of e-business, exactly how factors related to organizational learning and knowledge management affect the impact of e-business on firm performance has received little empirical attention.
Research model and hypotheses
Previous studies discussed features of organizational capabilities corresponding to different mechanisms that facilitate IT diffusion and firm performance ([12] Caloghirou et al. , 2004; [45] Raman et al. , 2006). Part of these organizational capabilities result from organizational learning culture and knowledge accumulation within firms, and form what has been described as the firm "absorptive capacity" ([15] Cohen and Levinthal, 1990; [28] Jantunen, 2005). Therefore, this study discusses the organizational capabilities construct of the research model in terms of organizational learning and knowledge management capabilities. The research model investigated in this study is shown in Figure 1 [Figure omitted. See Article Image.], which hypothesized that organizational learning capabilities (training available, technical expertise and knowledge level) and knowledge management capabilities (knowledge acquisition, knowledge application and knowledge sharing) affect e-business implementation success. Each construct involved in the research model and hypotheses are discussed below.
Organizational learning capabilities
Recent studies have found organizational learning capacity to be a key factor in influencing IS deployment ([27] Hult, 1998; [60] Zahay and Handfield, 2004). Despite the pervasiveness of IT in modern workplaces, evidence is growing of failure to optimize organizational effectiveness because of poor employee acceptance new technologies ([30] Johnson, 1997). Training availability and strong technical expertise have been identified as necessary in a firm using IT to improve core competencies ([48] Ravichandran and Lertwongsatien, 2005).
Training availability refers to quantity of education available technology adopters or users. Previous research has shown that education and training are important factors for technology implementation ([10] Bradford and Florin, 2003). Utilizing e-business necessitates investment in IT infrastructure and employee training. Provision of sufficient training helps companies to obtain the required IT human resources and develop them into superior e-business functionalities to realize the potential e-business value ([63] Zhu and Kraemer, 2005). Hence, firms that devote significant training resources to IT are more likely to implement e-business and realize its value successfully. Hence, the following hypothesis is formulated:
H1. Training availability is positively associated with e-business implementation success.
Technical expertise describes firm level of specialized technical expertise. [43] Melville et al. (2004) identified lack of technical expertise as a key factor inhibiting IS evolution and sophistication. Technical expertise refers to the skills to create internet-enabled capabilities, such as front-office customer services and back-office systems integration, which determine a firm's overall e-business success ([62] Zhu and Kraemer, 2002). Moreover, whether e-business can create value in terms of resources depends heavily on level of expertise in implementing internet technologies, and more importantly, on the ability to use Internet technologies successfully ([7] Bharadwaj, 2000; [61] Zhu, 2004). Firms with high levels of technical expertise can be expected to master the technical aspects of e-business and achieve e-business contribution to firm performance more completely than firms with lower levels of technical expertise. Hence, the following hypothesis is formulated:
H2. Technical expertise is positively associated with e-business implementation success.
Knowledge level refers to the familiarity of firm employee with a technology. If employees understand internet technologies, they are likely to be able to interact with their customers and business partners and conduct business over the internet ([62] Zhu and Kraemer, 2002). [20] Gibbs and Kraemer (2004) found that e-business know-how provides the business and management skills to use e-business successfully. Consequently, a firm with employees who understand e-business is likely to realize the most success in e-business implementation. The following hypothesis is formulated:
H3. The knowledge level is positively associated with e-business implementation success.
Knowledge management capabilities
Absorptive capacity has been shown to be a critical component in understanding IT management practice and IT use, as well as enhancing the ability to effectively implement new IT ([9] Boynton et al. , 1994; [24] Harrington and Guimaraes, 2005). The absorptive capacity represents the set of organizational routines and processes involved in acquiring, applying and sharing knowledge to produce dynamic organizational capabilities. Efficient knowledge management processes, such as knowledge acquisition, application and sharing, are important for IT implementation success.
Knowledge acquisition is defined as the business processes that use existing knowledge and capture new knowledge. E-commerce development requires concerted effort and experience in recognizing and capturing new knowledge ([17] Etemad, 2004). Organizations generally have to acquire the know-what, know-how and know-why to assimilate any complex technology successfully ([4] Attewell, 1992). Know-what is factual knowledge about a technological innovation and its features, know-how is knowledge about how to apply a technological innovation in an organization, and know-why is knowledge required to meaningfully measure the cost, benefits and risks of applying a technological innovation ([47] Ravichandran, 2005). Furthermore, [44] Moodley (2003) indicated that e-business infrastructure involves not only e-commerce initiatives but also is driven by acquisition knowledge and skills. Relationships between knowledge acquisitions capabilities thus are expect to be positively related to e-business implementation success. The following hypothesis is formulated:
H4. Knowledge acquisition is positively associated with e-business implementation success.
Knowledge application is defined as the business processes through which effective storage and retrieval mechanisms enable a firm to access knowledge easily. From the technological innovation perspectives, knowledge transfer, knowledge integration and practical application of knowledge are the main elements for developing technological capabilities ([21] Gilbert and Cordey-Hayes, 1996; [54] Sveiby, 1997; [29] Johannessen et al. , 1999). Firms that stimulate and improve organizational application of knowledge are more likely to achieve successful e-business implementation. Therefore, the following hypothesis is formulated:
H5. Knowledge application is positively associated with e-business implementation success.
Knowledge sharing is defined as the business processes that distribute knowledge among all individuals participating in process activities. The literature on the organizational effectiveness of IS emphasizes that a knowledge sharing culture is the main organizational condition for successful knowledge management and exploitation ([16] Damodaran and Olpher, 2000). [39] Liu et al. (2004) found that openness towards knowledge sharing is important to increase organizational competitiveness. Previous studies also indicated that knowledge sharing is important for utilizing e-business ([31] Jones and Price, 2004; [18] Fiala, 2005). Thus, knowledge-sharing capabilities are expected to be positively associated with e-business implementation success. The following hypothesis is formulated:
H6. Knowledge sharing is positively associated with e-business implementation success.
Research methodology
Sample and data collection
The study population comprised IS executives in Taiwanese firms. [25] Heijden (2001) used IS executives as informants because of their ability to answer questions related to e-business implementation. A draft questionnaire was pilot tested by three MIS professors to ensure that the content and wording were free of problems. Five IS executives then examined the revised questionnaire. These IS executives were given the questionnaire and asked to examine it for meaningfulness, relevance, and clarity.
The sample frame was selected based on the 2003 Common Wealth directory of the 1,000 largest firms in Taiwan. However, this list did not contain information on IS department. Consequently, to ensure that IS executives received the questionnaire and maximize response rate, two research assistants spent two weeks telephoning these 1,000 firms. The research assistants asked the target firms whether they had formal IS departments. Additionally, the research assistants sought the name of the IS executives to whom a questionnaire should be mailed. Firms with no formal IS departments were removed from the sample. This process produced a sample of 820 firms from various industries. Moreover, the final questionnaires were mailed to the 820 IS executives of large organizations in Taiwan. A cover letter explaining the study objectives and a stamped return envelope were enclosed. Follow-up letters were sent approximately three weeks after the initial mailing.
Measures
To adequately build the constructs for testing the hypotheses, this study mainly adapted from previous studies and modified for use in e-business context. For all perceptual measures, a five-point Likert type scales was employed, typically anchored by 1-strongly disagree and 5-strongly agree. The operationalizations of the measures are noted in the Appendix. The measurement approach for each theoretical construct in the model is described briefly below.
Organizational learning capabilities were using three constructs: training available, technical expertise and knowledge level. Training available was measured with two items adapted from [10] Bradford and Florin's (2003) model of assessing the level of education available to e-business users. Technical expertise was measured with a two-item scale that adapted from [42] McGowan and Madey (1998). These items were used to assess the level of specialized technical expertise within the firm. The knowledge level was defined as the familiarity of the employees in the firm with e-business knowledge. Level of knowledge was assessed by a three-item measure modified from [55] Thong (1999).
Knowledge management capabilities were measured by three constructs with a total of 13 items, knowledge acquisition, knowledge application and knowledge sharing, derived from those proposed by [22] Gold et al. (2001). First, knowledge acquisition was defined as the extent to which business processes use existing knowledge and capture new knowledge. Second, knowledge application was defined as the ability to access knowledge by business processes involving storage and retrieval. Finally, knowledge sharing was defined as the extent to which individual participation in business processes involving knowledge distribution.
This study based on [64] Zhu et al. 's (2004) work, defines e-business implementation success as a second-order construct in terms of impact on commerce, internal efficacy, and coordination. Three-item measures were used to assess the impact on commerce, indicated by increased market share, improved customer service and enhanced products or services. The impact on internal efficacy was measured in terms of business efficiency and staff productivity. Finally, impact on coordination was measured in terms of reduction in transaction costs with business partners and improved coordination with business partners.
Statistical analysis
The SEM approach was used to validate the research model. This approach was chosen because of its ability to test casual relationships between constructs with multiple measurement items ([32] Joreskog and Sorbom, 1996). Numerous researchers have proposed a two-stage model-building process for applying SEM ([26] Hoyle, 1995; [32] Joreskog and Sorbom, 1996; [23] Hair et al. , 1998). Confirmatory factor analysis (CFA) was conducted to examine the reliability and validity of the measurement model, and the structural model also was analyzed to test the associations hypothesized in the research model.
Data analysis and results
Sample characteristics
Of the 820 questionnaires distributed, 202 completed and usable questionnaires were returned, representing a response rate of 24.6 percent. All respondents were IS executives, and had worked in the IS field for an average 13.1 years. Table I [Figure omitted. See Article Image.] lists the respondent company characteristics, including industry type, number of IS employees and e-business experience.
Measure reliability and validity
The research instrument used CFA to examine construct reliability, convergent validity and discriminant validity. The composite reliability assessed the internal consistency of the measurement model. The composite reliability is similar to that of Cronbach's α , except that it also takes into account the actual factor loadings rather than assuming that each item is equally weighted in the composite load determination. From Table II [Figure omitted. See Article Image.], the composite reliability of all constructs exceeded the benchmark of 0.6 recommended by [5] Bagozzi and Yi (1988). Convergent validity, the degree to which multiple attempts to measure the same concept are in agreement, was evaluated by examining the factor loading within each construct and composite reliability ([2] Anderson and Gerbing, 1998). From Table II [Figure omitted. See Article Image.], the items of factor loadings significantly (i.e. t >1.96) on their corresponding construct, with the lowest t -value being 7.82 ([6] Bagozzi et al. , 1991). Moreover, Table III [Figure omitted. See Article Image.] shows the estimation of the second-order construct, e-business implementation success. The paths from the second-order construct to the three first-order factors are significant and of high magnitude, greater than the suggested cutoff of 0.7 ([13] Chin, 1998). Thus, on both theoretical and empirical grounds, the conceptualization of e-business implementation success as a higher-order, multidimensional construct seems justified.
Discriminant validity is the degree to which the measures of different concepts are distinct. Discriminant validity can be examined by comparing the squared correlations between constructs and variance extracted for a construct ([19] Fornell and Larcker, 1981). The analysis results showed that the square correlations for each construct is less than the variance extracted by the indicators measuring that construct, as shown in Table IV [Figure omitted. See Article Image.], indicating the measure has adequately discriminant validity. In summary, the measurement model demonstrated adequate reliability, convergent validity and discriminant validity.
Testing the structural model
Standardized paths and various model-fit indices are shown in Figure 2 [Figure omitted. See Article Image.]. The observed normed χ2 (the ratio between χ2 and the degree of freedom) was 1.96 (χ2 =532.09, df = 272), which is smaller than three recommended by [5] Bagozzi and Yi (1988). Other fit indices also show good fit for the structural model. The goodness-of-fit index is 0.87, which exceed the recommended cut-off level of 0.8 ([11] Browne and Cudeck, 1993). The comparative fit index is 0.94 and normed fit index is 0.91, which also exceed the recommended cut-off level of 0.9 ([32] Joreskog and Sorbom, 1996). Additionally, the root mean square error of approximation is 0.069, which is below the cut-off level of 0.08 recommended by [11] Browne and Cudeck (1993). In summary, the hypothesized research model exhibited a fairly good fit with the data collected.
Training available, technical expertise, knowledge level, knowledge acquisition, knowledge application and knowledge sharing have positive and significant paths (p <0.01 for training available, knowledge level and knowledge application; p <0.05 for technical expertise, knowledge application and knowledge sharing) leading to e-business implementation success. Hence, all hypotheses are supported. Moreover, altogether the three organizational learning capabilities (training available, technical expertise and knowledge level) and three knowledge management capabilities (knowledge acquisition, knowledge application and knowledge sharing) explained 64 percent of the variance in e-business implementation success. Hence, the results indicate that organizational learning and knowledge management capabilities have significantly explained data variations for e-business implementation success.
Discussion
Organizational learning and e-business implementation success
Organizational learning capabilities, such as training available, technical expertise and knowledge level, were found to significantly determine successful e-business implementation. Firms that provide e-business training are more likely to realize the potential e-business contribution to firm performance. Owing to the inherent complexity of e-business systems, training methods must enable employees to scale initial hurdles to acceptance and usage, realizing more from e-business.
Firms with strong technical expertise and e-business knowledge are most likely to realize e-business implementation success. These findings are consistent with previous studies that have reported that spending on IT human capital (e.g. technical skills and firm-specific knowledge) was more strongly correlated than spending on computer capital with firm performance ([52] Segars and Grover, 1998; [48] Ravichandran and Lertwongsatien, 2005). Firms that can afford to hire e-business specialists and maintain significant technical expertise are better positioned than other firms to facilitate value creation in e-business. Moreover, firms that increase their knowledge of e-business are better able than other firms to use e-business. Consequently, adequate technical and e-business knowledge is a necessary first step to utilizing e-business to support and enhance firm performance.
Knowledge management and e-business implementation success
The results of this study support the hypotheses that knowledge acquisition, application and sharing positively impact e-business implementation success. This finding is consistent with [8] Bose's (2003) view that knowledge management capabilities help improves e-business competitiveness. Specifically, e-businesses differ from other previously studied areas of IT applications because they integrate intra- and inter-organizational business processes. Knowledge accumulation enables employees to both use existing knowledge and create new knowledge, both of which are crucial for e-business implementation. Furthermore, knowledge-sharing e-business activities occur not only within firms, but also between firms and their business partners. Knowledge sharing enables employees to understand integration and management of intra- and inter-organizational business processes, and develop novel solutions to problems that significantly improve on current practices. Consequently, knowledge management is an emerging capability that can find critical information more efficiently, utilize staff more effectively, organize knowledge for rapid retrieval and reuse, and improve interactions with trading partners. That is, successful e-business implementation increasingly depends on the ability to acquire, develop and share knowledge.
Conclusions
This study developed a research model to examine the influence of organizational learning and knowledge management capabilities on successful e-business implementation. The results confirm that e-business implementation is expected to understanding the training support and technical knowledge available, while also understanding the knowledge-intensive practices required to create, apply, deploy and share knowledge. The implications for practitioners and researchers and the limitations of this study are discussed below.
Implications for practitioners
The results of this study have several important implications for management. First, this study stresses the importance considerations for practitioners who are initiating or currently conducting e-business applications. Managers who wish exploit e-business investment should emphasize both social and technical factors and their interaction within and beyond the organization, instead of focusing exclusively on technological considerations. The development of organizational learning and knowledge management strategies would be useful for e-business implementation and enhance firm performance. Second, the firms that provide e-business training for their employees and increase their knowledge of e-business can expect to achieve higher levels of e-business implementation success. Third, knowledge management means recognizing and managing all of an organization's intellectual and social capital to meet its e-business objectives. An organization needs a well-designed knowledge management infrastructure to create and maintain the e-business knowledge required to improve back-office efficiency, customer intimacy and efficiency of coordination with business partners. Hence, firms with enhance and accurate leveraging of the strategic relevance of knowledge and knowledge management practices is more likely to achieve e-business contribution to firm performance.
Limitations and future research
There are several limitations to this study, requiring further examination and additional research. First, the sample was drawn from Taiwanese IS executives. Hence, the research model should be tested further using samples from other countries, since cultural differences may be influenced by cultural differences between Taiwan and other countries, and further testing thus would provide a more robust test of the hypotheses. Second, some IS literature has also indicated differences between large organizations and small- and medium-sized enterprises (SMEs) in internet-based system applications ([50] Riquelme, 2002). Similar studies of SMEs therefore should be conducted to examine these differences. Finally, besides the factors proposed here, organizational capabilities related to benefits of e-business are many and varied, and can change over time. This study did not test all organizational factors, and focused particularly on learning capacity and knowledge capability factors. For example, a knowledge asset must be rare and inimitable to become a source of competitive advantage. Without secure processes, knowledge loses the key qualities of being rare and inimitable ([22] Gold et al. , 2001). Therefore, future research could assess the influence of knowledge protection processes on e-business implementation success. Moreover, although the scales used for measuring organizational learning and knowledge management capabilities similarities with existing scales, further research might consider developing more elaborate measures to allow for a richer coverage of these antecedents of e-business implementation success.
The authors would like to thank the National Science Council of the People's Republic of China, Taiwan for financially supporting this research under Contract No. NSC92-2416-H-011-004.
References
1. Aldin, N., Brehmer, P. and Johansson, A. (2004), "Business
development with electronic commerce: refinement and repositioning",
Business Process Management Journal, Vol. 10 No. 1, pp. 44-62.
2. Anderson, J.C. and Gerbing, D.W. (1998), "Structural equation modeling in practice: a review and recommended two-step approach", Psychological Bulletin, Vol. 103 No. 3, pp. 411-23.
3. Ash, C.G. and Burn, J.M. (2003), "A strategic framework for the management of ERP enabled e-business change", European Journal of Operational Research, Vol. 146 No. 2, pp. 374-87.
4. Attewell, P. (1992), "Technology diffusion and organizational learning: the case of business computing", Organization Science, Vol. 3 No. 1, pp. 1-19.
5. Bagozzi, R.P. and Yi, Y. (1988), "On the evaluation of structural equation model", Journal of Academy of Marketing Science, Vol. 16 No. 1, pp. 74-94.
6. Bagozzi, R.P., Yi, Y. and Phillips, L.W. (1991), "Assessing construct validity in organizational research", Administrative Science Quarterly, Vol. 36 No. 3, pp. 421-58.
7. Bharadwaj, A.S. (2000), "A resource-based perspective on information technology capability and firm performance: an empirical investigation", MIS Quarterly, Vol. 24 No. 1, pp. 169-96.
8. Bose, R. (2003), "Knowledge management-enabled health care management systems: capabilities, infrastructure, and decision-support", Expert Systems with Applications, Vol. 24 No. 1, pp. 59-71.
9. Boynton, A.C., Zmud, R.W. and Jacobs, G.C. (1994), "The influence of IT management practice on IT use in large organizations", MIS Quarterly, Vol. 18 No. 3, pp. 299-318.
10. Bradford, M. and Florin, J. (2003), "Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems", International Journal of Accounting Information Systems, Vol. 4 No. 3, pp. 205-25.
11. Browne, M.W. and Cudeck, R. (1993), Alternative Ways of Assessing Model Fit, Sage, Newbury Park, CA.
12. Caloghirou, Y., Kastelli, I. and Tsakanikas, A. (2004), "Internal capabilities and external knowledge sources: complements or substitutes for innovation performance", Technovation, Vol. 24 No. 1, pp. 29-39.
13. Chin, W.W. (1998), "Issues and opinion on structure equation modeling", MIS Quarterly, Vol. 22 No. 1, pp. vii-xvi.
14. Chircu, A.M. and Kauffman, R.J. (2000), "Limits to value in electronic commerce-related IT investments", Journal of Management of Information Systems, Vol. 17 No. 2, pp. 59-80.
15. Cohen, W. and Levinthal, D. (1990), "Absorptive capacity: a new perspective on learning and innovation", Administrative Science Quarterly, Vol. 35 No. 1, pp. 128-52.
16. Damodaran, L. and Olpher, W. (2000), "Barriers and facilitators to the use of knowledge management systems", Behaviour and Information Technology, Vol. 19 No. 6, pp. 405-13.
17. Etemad, H. (2004), "E-commerce: the emergence of a field and its knowledge network", International Journal of Technology Management, Vol. 28 No. 7, pp. 776-800.
18. Fiala, P. (2005), "Information sharing in supply chains", OMEGA: International Journal of Management Science, Vol. 33 No. 5, pp. 419-23.
19. Fornell, C. and Larcker, D.F. (1981), "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
20. Gibbs, J.L. and Kraemer, K. (2004), "Cross-country investigation of the determinants of scope of e-commerce use: an institutional approach", Electronic Markets, Vol. 14 No. 2, pp. 124-37.
21. Gilbert, M. and Cordey-Hayes, M. (1996), "Understanding the process of knowledge transfer to achieve successful technological innovation", Technovation, Vol. 16 No. 6, pp. 301-12.
22. Gold, A.H., Malhotra, A. and Segars, A.H. (2001), "Knowledge management: an organizational capabilities perspective", Journal of Management Information Systems, Vol. 18 No. 1, pp. 185-214.
23. Hair, J.F., Anderson, R.L. and Tatham, W.C. (1998), Multivariate Data Analysis with Reading, Prentice-Hall, Upper Saddle River, NJ.
24. Harrington, S.J. and Guimaraes, T. (2005), "Corporate culture, absorptive capacity and IT success", Information and Organization, Vol. 15 No. 1, pp. 39-63.
25. Heijden, H.V.D. (2001), "Measuring IT core capabilities for electronic commerce", Journal of Information Technology, Vol. 16 No. 1, pp. 13-22.
26. Hoyle, R.H. (1995), Structuring Equation Modeling: Concepts, Issues and Applications, Sage, London.
27. Hult, G.T. (1998), "Managing the international strategic sourcing process as market-driven organizational learning system", Decision Sciences, Vol. 29 No. 1, pp. 193-216.
28. Jantunen, A. (2005), "Knowledge-processing capabilities and innovative performance: an empirical study", European Journal of Innovation Management, Vol. 8 No. 3, pp. 336-49.
29. Johannessen, J.A., Olsen, B. and Olaisen, J. (1999), "Aspects of innovation theory based on knowledge-management", International Journal of Information Management, Vol. 19 No. 2, pp. 121-39.
30. Johnson, M. (1997), Teleworking in Brief, Butterworth-Heinemann, Oxford.
31. Jones, M.C. and Price, R.L. (2004), "Organizational knowledge sharing in ERP implementation: lessons from industry", Journal of Organizational and End User Computing, Vol. 16 No. 1, pp. 21-40.
32. Joreskog, K.G. and Sorbom, D. (1996), LISREL 8: Structural Equation Modeling, Scientific Software International Cop., Chicago, IL.
33. Kalakota, R. and Robinson, M. (1999), E-business Roadmap for Success, Addison-Wesley, Reading, MA.
34. Kim, H.M. and Ramkaran, R. (2004), "Best practices in e-business process management: extending a re-engineering framework", Business Process Management Journal, Vol. 10 No. 1, pp. 27-43.
35. Koh, S.C.L. and Maguire, S. (2004), "Identifying the adoption of e-business and knowledge management within SMEs", Journal of Small and Enterprise Development, Vol. 11 No. 3, pp. 338-48.
36. Lee, J.N. (2001), "The impact of knowledge sharing, organizational capability and partnership quality on IS outsourcing success", Information and Management, Vol. 38 No. 5, pp. 323-35.
37. Lederer, A.L., Mirchandami, D.A. and Sims, K. (2001), "The search for strategic advantage from the world wide web", International Journal of Electronic Commerce, Vol. 5 No. 4, pp. 117-33.
38. Lin, H.F. and Lee, G.G. (2005), "Impact of organizational learning and knowledge management factors on e-business adoption", Management Decision, Vol. 43 No. 2, pp. 171-88.
39. Liu, P.L., Chen, W.C. and Tsai, C.H. (2004), "An empirical study on the correlation between knowledge management capability and competitiveness in Taiwan's industries", Technovation, Vol. 24 No. 12, pp. 971-7.
40. Malhotra, A., Gosain, S. and EI Sawy, O.A. (2005), "Absorptive capacity configurations in supply chain: gearing for partner-enabled market knowledge creation", MIS Quarterly, Vol. 29 No. 1, pp. 145-87.
41. Malone, T.W., Yates, J. and Benjamin, R.I. (1987), "Electronic markets and electronic hierarchies", Communications of the ACM, Vol. 30 No. 6, pp. 484-97.
42. McGowan, M.K. and Madey, G.R. (1998), "The influence of organizational structure and organizational learning factors on the extent of EDI implementation in US firms", Information Resource Management Journal, Vol. 11 No. 3, pp. 17-27.
43. Melville, N., Kraemer, K. and Gurbaxani, V. (2004), "Information technology and organizational performance: an integrative model of IT business value", MIS Quarterly, Vol. 28 No. 2, pp. 283-322.
44. Moodley, S. (2003), "The challenge of e-business for South African apparel sector", Technovation, Vol. 23 No. 7, pp. 557-70.
45. Raman, P., Wittmann, C.M. and Rauseo, N.A. (2006), "The role of organizational capabilities in successful CRM implementation", The Journal of Personal Selling and Sales Management, Vol. 26 No. 1, pp. 39-54.
46. Ranganathan, C., Dhaliwal, J.S. and Teo, T.S.H. (2004), "Assimilation and diffusion of web technologies in supply-chain management: an examination of key drivers and performance impact", International Journal of Electronic Commerce, Vol. 9 No. 1, pp. 127-61.
47. Ravichandran, T. (2005), "Organizational assimilation of complex technologies: an empirical study of component-based software development", IEEE Transactions on Engineering Management, Vol. 52 No. 2, pp. 249-68.
48. Ravichandran, T. and Lertwongsatien, C. (2005), "Effect of information systems resources and capabilities on firm performance: a resource-based perspective", Journal of Management Information Systems, Vol. 21 No. 4, pp. 237-76.
49. Raymond, L. and Blili, S. (2000), "Organizational learning as a foundation of electronic commerce in the network organization", International Journal of Electronic Commerce, Vol. 5 No. 2, pp. 29-45.
50. Riquelme, H. (2002), "Commercial internet adopting in China: comparing the experience of small medium and large businesses", Internet Research: Electronic Networking Applications and Policy, Vol. 12 No. 3, pp. 276-86.
51. Saini, A. and Johnson, J.L. (2005), "Organizational capabilities in e-commerce: an empirical investigation of e-brokerage service providers", Journal of Academy of Marketing Science, Vol. 33 No. 3, pp. 360-75.
52. Segars, A.H. and Grover, V. (1998), "Strategic information systems planning: an investigation of the constructs and its measurement", MIS Quarterly, Vol. 22 No. 2, pp. 139-63.
53. Stylianou, A.C., Robbins, S.S. and Jackson, P. (2003), "Perceptions and attitudes about eCommerce development in China: an exploratory study", Journal of Global Information Management, Vol. 11 No. 2, pp. 31-47.
54. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-based Assets, Berrett-Koehler, San Francisco, CA.
55. Thong, J.Y.L. (1999), "An integrated model of information systems adoption in small business", Journal of Management Information Systems, Vol. 15 No. 4, pp. 187-214.
56. Veliyath, R. and Fitzgerald, E. (2000), "Firm capabilities, business strategies, customer preference, and hypercompetitive areas: the sustainability of competitive advantages with implications for firm competitiveness", Competitiveness Review, Vol. 10 No. 1, pp. 56-82.
57. Wang, S. and Cheung, W. (2004), "E-business adoption by travel agencies: prime candidates for mobile e-business", International Journal of Electronic Commerce, Vol. 8 No. 3, pp. 43-63.
58. Xie, F.T. and Johnston, W.J. (2004), "Strategic alliances: incorporation the impact of e-business technological innovations", Journal of Business and Industrial Management, Vol. 19 No. 3, pp. 208-22.
59. Yam, R.C.M., Guan, J.C., Pun, K.F. and Tang, E.P.Y. (2004), "An audit of technological innovation capabilities in Chinese firms: some empirical findings in Beijing, China", Research Policy, Vol. 33 No. 8, pp. 1123-40.
60. Zahay, D.L. and Handfield, R.B. (2004), "The role of learning and technical capabilities in predicting adoption B2B technologies", Industrial Marketing and Management, Vol. 33 No. 7, pp. 627-41.
61. Zhu, K. (2004), "The complementarily of information technology infrastructure and e-commerce capability: a resource-based assessment of their business value", Journal of Management Information Systems, Vol. 21 No. 1, pp. 167-202.
62. Zhu, K. and Kraemer, K.L. (2002), "E-commerce metrics for net-enhanced organizations: assessing the value of e-commerce to firm performance in the manufacturing sector", Information Systems Research, Vol. 13 No. 3, pp. 275-95.
63. Zhu, K. and Kraemer, K.L. (2005), "Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry", Information Systems Research, Vol. 16 No. 1, pp. 61-84.
64. Zhu, K., Kraemer, K.L., Xu, S. and Dedrick, J. (2004), "Information technology payoff in e-business environment: an international perspective on value creation of e-business in the financial services industry", Journal of Management Information Systems, Vol. 21 No. 1, pp. 17-54.
2. Anderson, J.C. and Gerbing, D.W. (1998), "Structural equation modeling in practice: a review and recommended two-step approach", Psychological Bulletin, Vol. 103 No. 3, pp. 411-23.
3. Ash, C.G. and Burn, J.M. (2003), "A strategic framework for the management of ERP enabled e-business change", European Journal of Operational Research, Vol. 146 No. 2, pp. 374-87.
4. Attewell, P. (1992), "Technology diffusion and organizational learning: the case of business computing", Organization Science, Vol. 3 No. 1, pp. 1-19.
5. Bagozzi, R.P. and Yi, Y. (1988), "On the evaluation of structural equation model", Journal of Academy of Marketing Science, Vol. 16 No. 1, pp. 74-94.
6. Bagozzi, R.P., Yi, Y. and Phillips, L.W. (1991), "Assessing construct validity in organizational research", Administrative Science Quarterly, Vol. 36 No. 3, pp. 421-58.
7. Bharadwaj, A.S. (2000), "A resource-based perspective on information technology capability and firm performance: an empirical investigation", MIS Quarterly, Vol. 24 No. 1, pp. 169-96.
8. Bose, R. (2003), "Knowledge management-enabled health care management systems: capabilities, infrastructure, and decision-support", Expert Systems with Applications, Vol. 24 No. 1, pp. 59-71.
9. Boynton, A.C., Zmud, R.W. and Jacobs, G.C. (1994), "The influence of IT management practice on IT use in large organizations", MIS Quarterly, Vol. 18 No. 3, pp. 299-318.
10. Bradford, M. and Florin, J. (2003), "Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems", International Journal of Accounting Information Systems, Vol. 4 No. 3, pp. 205-25.
11. Browne, M.W. and Cudeck, R. (1993), Alternative Ways of Assessing Model Fit, Sage, Newbury Park, CA.
12. Caloghirou, Y., Kastelli, I. and Tsakanikas, A. (2004), "Internal capabilities and external knowledge sources: complements or substitutes for innovation performance", Technovation, Vol. 24 No. 1, pp. 29-39.
13. Chin, W.W. (1998), "Issues and opinion on structure equation modeling", MIS Quarterly, Vol. 22 No. 1, pp. vii-xvi.
14. Chircu, A.M. and Kauffman, R.J. (2000), "Limits to value in electronic commerce-related IT investments", Journal of Management of Information Systems, Vol. 17 No. 2, pp. 59-80.
15. Cohen, W. and Levinthal, D. (1990), "Absorptive capacity: a new perspective on learning and innovation", Administrative Science Quarterly, Vol. 35 No. 1, pp. 128-52.
16. Damodaran, L. and Olpher, W. (2000), "Barriers and facilitators to the use of knowledge management systems", Behaviour and Information Technology, Vol. 19 No. 6, pp. 405-13.
17. Etemad, H. (2004), "E-commerce: the emergence of a field and its knowledge network", International Journal of Technology Management, Vol. 28 No. 7, pp. 776-800.
18. Fiala, P. (2005), "Information sharing in supply chains", OMEGA: International Journal of Management Science, Vol. 33 No. 5, pp. 419-23.
19. Fornell, C. and Larcker, D.F. (1981), "Evaluating structural equation models with unobservable variables and measurement error", Journal of Marketing Research, Vol. 18 No. 1, pp. 39-50.
20. Gibbs, J.L. and Kraemer, K. (2004), "Cross-country investigation of the determinants of scope of e-commerce use: an institutional approach", Electronic Markets, Vol. 14 No. 2, pp. 124-37.
21. Gilbert, M. and Cordey-Hayes, M. (1996), "Understanding the process of knowledge transfer to achieve successful technological innovation", Technovation, Vol. 16 No. 6, pp. 301-12.
22. Gold, A.H., Malhotra, A. and Segars, A.H. (2001), "Knowledge management: an organizational capabilities perspective", Journal of Management Information Systems, Vol. 18 No. 1, pp. 185-214.
23. Hair, J.F., Anderson, R.L. and Tatham, W.C. (1998), Multivariate Data Analysis with Reading, Prentice-Hall, Upper Saddle River, NJ.
24. Harrington, S.J. and Guimaraes, T. (2005), "Corporate culture, absorptive capacity and IT success", Information and Organization, Vol. 15 No. 1, pp. 39-63.
25. Heijden, H.V.D. (2001), "Measuring IT core capabilities for electronic commerce", Journal of Information Technology, Vol. 16 No. 1, pp. 13-22.
26. Hoyle, R.H. (1995), Structuring Equation Modeling: Concepts, Issues and Applications, Sage, London.
27. Hult, G.T. (1998), "Managing the international strategic sourcing process as market-driven organizational learning system", Decision Sciences, Vol. 29 No. 1, pp. 193-216.
28. Jantunen, A. (2005), "Knowledge-processing capabilities and innovative performance: an empirical study", European Journal of Innovation Management, Vol. 8 No. 3, pp. 336-49.
29. Johannessen, J.A., Olsen, B. and Olaisen, J. (1999), "Aspects of innovation theory based on knowledge-management", International Journal of Information Management, Vol. 19 No. 2, pp. 121-39.
30. Johnson, M. (1997), Teleworking in Brief, Butterworth-Heinemann, Oxford.
31. Jones, M.C. and Price, R.L. (2004), "Organizational knowledge sharing in ERP implementation: lessons from industry", Journal of Organizational and End User Computing, Vol. 16 No. 1, pp. 21-40.
32. Joreskog, K.G. and Sorbom, D. (1996), LISREL 8: Structural Equation Modeling, Scientific Software International Cop., Chicago, IL.
33. Kalakota, R. and Robinson, M. (1999), E-business Roadmap for Success, Addison-Wesley, Reading, MA.
34. Kim, H.M. and Ramkaran, R. (2004), "Best practices in e-business process management: extending a re-engineering framework", Business Process Management Journal, Vol. 10 No. 1, pp. 27-43.
35. Koh, S.C.L. and Maguire, S. (2004), "Identifying the adoption of e-business and knowledge management within SMEs", Journal of Small and Enterprise Development, Vol. 11 No. 3, pp. 338-48.
36. Lee, J.N. (2001), "The impact of knowledge sharing, organizational capability and partnership quality on IS outsourcing success", Information and Management, Vol. 38 No. 5, pp. 323-35.
37. Lederer, A.L., Mirchandami, D.A. and Sims, K. (2001), "The search for strategic advantage from the world wide web", International Journal of Electronic Commerce, Vol. 5 No. 4, pp. 117-33.
38. Lin, H.F. and Lee, G.G. (2005), "Impact of organizational learning and knowledge management factors on e-business adoption", Management Decision, Vol. 43 No. 2, pp. 171-88.
39. Liu, P.L., Chen, W.C. and Tsai, C.H. (2004), "An empirical study on the correlation between knowledge management capability and competitiveness in Taiwan's industries", Technovation, Vol. 24 No. 12, pp. 971-7.
40. Malhotra, A., Gosain, S. and EI Sawy, O.A. (2005), "Absorptive capacity configurations in supply chain: gearing for partner-enabled market knowledge creation", MIS Quarterly, Vol. 29 No. 1, pp. 145-87.
41. Malone, T.W., Yates, J. and Benjamin, R.I. (1987), "Electronic markets and electronic hierarchies", Communications of the ACM, Vol. 30 No. 6, pp. 484-97.
42. McGowan, M.K. and Madey, G.R. (1998), "The influence of organizational structure and organizational learning factors on the extent of EDI implementation in US firms", Information Resource Management Journal, Vol. 11 No. 3, pp. 17-27.
43. Melville, N., Kraemer, K. and Gurbaxani, V. (2004), "Information technology and organizational performance: an integrative model of IT business value", MIS Quarterly, Vol. 28 No. 2, pp. 283-322.
44. Moodley, S. (2003), "The challenge of e-business for South African apparel sector", Technovation, Vol. 23 No. 7, pp. 557-70.
45. Raman, P., Wittmann, C.M. and Rauseo, N.A. (2006), "The role of organizational capabilities in successful CRM implementation", The Journal of Personal Selling and Sales Management, Vol. 26 No. 1, pp. 39-54.
46. Ranganathan, C., Dhaliwal, J.S. and Teo, T.S.H. (2004), "Assimilation and diffusion of web technologies in supply-chain management: an examination of key drivers and performance impact", International Journal of Electronic Commerce, Vol. 9 No. 1, pp. 127-61.
47. Ravichandran, T. (2005), "Organizational assimilation of complex technologies: an empirical study of component-based software development", IEEE Transactions on Engineering Management, Vol. 52 No. 2, pp. 249-68.
48. Ravichandran, T. and Lertwongsatien, C. (2005), "Effect of information systems resources and capabilities on firm performance: a resource-based perspective", Journal of Management Information Systems, Vol. 21 No. 4, pp. 237-76.
49. Raymond, L. and Blili, S. (2000), "Organizational learning as a foundation of electronic commerce in the network organization", International Journal of Electronic Commerce, Vol. 5 No. 2, pp. 29-45.
50. Riquelme, H. (2002), "Commercial internet adopting in China: comparing the experience of small medium and large businesses", Internet Research: Electronic Networking Applications and Policy, Vol. 12 No. 3, pp. 276-86.
51. Saini, A. and Johnson, J.L. (2005), "Organizational capabilities in e-commerce: an empirical investigation of e-brokerage service providers", Journal of Academy of Marketing Science, Vol. 33 No. 3, pp. 360-75.
52. Segars, A.H. and Grover, V. (1998), "Strategic information systems planning: an investigation of the constructs and its measurement", MIS Quarterly, Vol. 22 No. 2, pp. 139-63.
53. Stylianou, A.C., Robbins, S.S. and Jackson, P. (2003), "Perceptions and attitudes about eCommerce development in China: an exploratory study", Journal of Global Information Management, Vol. 11 No. 2, pp. 31-47.
54. Sveiby, K.E. (1997), The New Organizational Wealth: Managing and Measuring Knowledge-based Assets, Berrett-Koehler, San Francisco, CA.
55. Thong, J.Y.L. (1999), "An integrated model of information systems adoption in small business", Journal of Management Information Systems, Vol. 15 No. 4, pp. 187-214.
56. Veliyath, R. and Fitzgerald, E. (2000), "Firm capabilities, business strategies, customer preference, and hypercompetitive areas: the sustainability of competitive advantages with implications for firm competitiveness", Competitiveness Review, Vol. 10 No. 1, pp. 56-82.
57. Wang, S. and Cheung, W. (2004), "E-business adoption by travel agencies: prime candidates for mobile e-business", International Journal of Electronic Commerce, Vol. 8 No. 3, pp. 43-63.
58. Xie, F.T. and Johnston, W.J. (2004), "Strategic alliances: incorporation the impact of e-business technological innovations", Journal of Business and Industrial Management, Vol. 19 No. 3, pp. 208-22.
59. Yam, R.C.M., Guan, J.C., Pun, K.F. and Tang, E.P.Y. (2004), "An audit of technological innovation capabilities in Chinese firms: some empirical findings in Beijing, China", Research Policy, Vol. 33 No. 8, pp. 1123-40.
60. Zahay, D.L. and Handfield, R.B. (2004), "The role of learning and technical capabilities in predicting adoption B2B technologies", Industrial Marketing and Management, Vol. 33 No. 7, pp. 627-41.
61. Zhu, K. (2004), "The complementarily of information technology infrastructure and e-commerce capability: a resource-based assessment of their business value", Journal of Management Information Systems, Vol. 21 No. 1, pp. 167-202.
62. Zhu, K. and Kraemer, K.L. (2002), "E-commerce metrics for net-enhanced organizations: assessing the value of e-commerce to firm performance in the manufacturing sector", Information Systems Research, Vol. 13 No. 3, pp. 275-95.
63. Zhu, K. and Kraemer, K.L. (2005), "Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry", Information Systems Research, Vol. 16 No. 1, pp. 61-84.
64. Zhu, K., Kraemer, K.L., Xu, S. and Dedrick, J. (2004), "Information technology payoff in e-business environment: an international perspective on value creation of e-business in the financial services industry", Journal of Management Information Systems, Vol. 21 No. 1, pp. 17-54.
Appendix
Appendix. Questionnaire items
Training availability
TA1. My organization views employee training as an investment, not an expense.
TA2. My organization provided extensive training in e-business.
Technical expertise
TE1. IS employees are generally very knowledgeable regarding technical matters.
TE2. My organization contains considerable technical expertise.
Knowledge level
KL1. The organization contains a high level of e-business knowledge.
KL2. My organization hires highly specialized or knowledgeable personnel for e-business.
KL3. My organization is dedicated to ensuring that employees are very familiar with e-business.
Knowledge acquisition
My organization ...
KA1 . Has processes for acquiring supplier knowledge.
KA2 . Has processes for generating new knowledge based on existing knowledge.
KA3 . Has processes for acquiring customer knowledge.
KA4 . Has processes for acquiring knowledge on developing new products/services.
Knowledge application
My organization ...
KAP1 . Has processes for integrating different sources and types of knowledge.
KAP2 . Has processes for transferring organizational knowledge to employees.
KAP3 . Has processes for filtering knowledge.
KAP4 . Has processes for applying experiential knowledge.
KAP5 . Has processes for applying knowledge to solve new problems.
Knowledge sharing
My organization ...
KS1 . Has processes for distributing knowledge throughout the organization.
KS2 . Has processes for distributing knowledge among our business partners.
KS3 . Has a standardized reward system for sharing knowledge.
KS4 . Designs processes to facilitate knowledge sharing across functional boundaries.
E-business implementation success
Impact on commerce
Implication of e-business, my organization ...
IC1. Increase market share.
IC2. Improve customer service.
IC3. Provide better products or services.
Impact on internal efficacy
Implication of e-business, my organization ...
IIE1. Enhance business efficiency.
IIE2. Enhance staff productivity.
Impact on coordination
Implication of e-business, my organization ...
ICO1. Reduce transaction costs with business partners.
ICO2. Improve coordination with business partners or suppliers.
Corresponding author
Hsiu-Fen Lin can be contacted at: hflin@mail.ntou.edu.tw
Training availability
TA1. My organization views employee training as an investment, not an expense.
TA2. My organization provided extensive training in e-business.
Technical expertise
TE1. IS employees are generally very knowledgeable regarding technical matters.
TE2. My organization contains considerable technical expertise.
Knowledge level
KL1. The organization contains a high level of e-business knowledge.
KL2. My organization hires highly specialized or knowledgeable personnel for e-business.
KL3. My organization is dedicated to ensuring that employees are very familiar with e-business.
Knowledge acquisition
My organization ...
KA1 . Has processes for acquiring supplier knowledge.
KA2 . Has processes for generating new knowledge based on existing knowledge.
KA3 . Has processes for acquiring customer knowledge.
KA4 . Has processes for acquiring knowledge on developing new products/services.
Knowledge application
My organization ...
KAP1 . Has processes for integrating different sources and types of knowledge.
KAP2 . Has processes for transferring organizational knowledge to employees.
KAP3 . Has processes for filtering knowledge.
KAP4 . Has processes for applying experiential knowledge.
KAP5 . Has processes for applying knowledge to solve new problems.
Knowledge sharing
My organization ...
KS1 . Has processes for distributing knowledge throughout the organization.
KS2 . Has processes for distributing knowledge among our business partners.
KS3 . Has a standardized reward system for sharing knowledge.
KS4 . Designs processes to facilitate knowledge sharing across functional boundaries.
E-business implementation success
Impact on commerce
Implication of e-business, my organization ...
IC1. Increase market share.
IC2. Improve customer service.
IC3. Provide better products or services.
Impact on internal efficacy
Implication of e-business, my organization ...
IIE1. Enhance business efficiency.
IIE2. Enhance staff productivity.
Impact on coordination
Implication of e-business, my organization ...
ICO1. Reduce transaction costs with business partners.
ICO2. Improve coordination with business partners or suppliers.
Corresponding author
Hsiu-Fen Lin can be contacted at: hflin@mail.ntou.edu.tw
AuthorAffiliation
Chih-Ping Lee, Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan
Gwo-Guang Lee, Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan
Hsiu-Fen Lin, Department of Shipping and Transportation Management, National Taiwan Ocean University, Keelung, Taiwan
Gwo-Guang Lee, Department of Information Management, National Taiwan University of Science and Technology, Taipei, Taiwan
Hsiu-Fen Lin, Department of Shipping and Transportation Management, National Taiwan Ocean University, Keelung, Taiwan
Illustration
Figure 1: The research model
Figure 2: Results of structural model
Table I: Sample characteristics (n =202)
Table II: Measurement model: loadings, convergent validity, and reliability
Table III: Second-order construct of e-business implementation success
Table IV: Discriminant validity
Figure 2: Results of structural model
Table I: Sample characteristics (n =202)
Table II: Measurement model: loadings, convergent validity, and reliability
Table III: Second-order construct of e-business implementation success
Table IV: Discriminant validity
Appears to be copied from a paper from China.
ReplyDelete