臺灣博碩士論文加值系統

利用跨組織資訊系統建構電子化供應鏈管理已成為企業改善績效與建立競爭優勢的一項重要策略。由於電子化供應鏈管理能加快供應鏈的速度與彈性，並且可降低成本以及提升顧客滿意度，會增進企業使用的意願。而擴散過程的相關議題有助於更進一步的瞭解企業最終是否有成功地應用電子化供應鏈管理。創新擴散理論運用了多階段的模型來解釋一項新事物的擴散過程。另外，在衡量資訊科技的價值時，過去的研究發現結果並不一致，主要的原因是使用了不恰當的績效衡量方式。平衡計分卡包含了財務與非財務量度，適用於考核資訊科技的績效。本研究主要根據創新擴散理論為基礎，並且依據過去相關文獻的探討之後，建構出本研究之架構模式，其中擴散過程分為，初始採用、組織內部擴散與外部擴散三階段，並根據平衡計分卡的四個構面，考核電子化供應鏈管理擴散對組織績效的影響。本研究是採用問卷調查法，以郵寄問卷的方式收集資料。統計分析的結果顯示，在擴散的前兩階段，初始採用與內部擴散階段對計分卡的四構面呈現正向顯著的影響。除了財務績效之外，在電子化供應鏈管理的外部擴散階段對學習與成長、企業流程與顧客三個構面呈現正向顯著的影響。

E-supply chain management (e-SCM), a specific form of interorganizational systems, has generally regarded as one of major strategies to improve organizational performance and create competitive advantage. In order to generate speed, agility, lower cost, and customer satisfaction in supply chain, organizations are willing to implement e-SCM. Besides, the diffusion issue for e-SCM is important for the final successful use. Innovation diffusion theory (IDT) is defined for exploring diffusion process with multiple stages. Moreover, empirical researches have found inconclusive results of IT values due to inadequacy measures. The balanced scorecard (BSC), including financial and non-financial measures, is an appropriate approach for accessing IT performance. Based on IDT and BSC, this study proposes a novel framework for exploring the relationship between the three-stage e-SCM diffusion and the four performance perspectives in BSC. A field survey method was adopted for this study. Results demonstrated that the two earlier stages, involving adoption and internal diffusion, had significant impacts on the four performance perspectives. At external diffusion stage, four perspectives except financial performance showed significant.

Abstract.............................................I
Contents...........................................III
Figure Contents......................................V
Table Contents......................................VI
1. Introduction......................................1
1.1 Research Background and Motivation...............1
1.2 Research Objectives and Questions................3
1.3 Research Procedure...............................5
2. Literature Review.................................7
2.1 SCM..............................................7
2.2 IDT and e-SCM Diffusion.........................12
2.3 BSC Concept and Measuring e-SCM Value...........17
2.3.1 BSC Concept...................................17
2.3.2 Measuring e-SCM Value.........................19
3. Research Methodology.............................26
3.1 Research Model..................................26
3.2 Hypotheses Development..........................28
3.2.1 Learning and Growth Perspective...............28
3.2.2 Business Process Perspective..................29
3.2.3 Customer Perspective..........................29
3.2.4 Financial Perspective.........................30
3.2.5 Control Variables.............................30
4. Research Design..................................32
4.1 Instrument......................................32
4.1.1 Basic Information.............................32
4.1.2 E-SCM diffusion...............................32
4.1.3 Organizational Performances...................33
4.1.4 Control Variables.............................34
4.2 Sample Organizations and Respondents............35
4.3 Scale Validation................................38
4.3.1 Analytic Techniques...........................38
4.3.2 Analysis of the Measurement Model.............39
5. Hypotheses Testing...............................45
6. Findings and Discussions.........................48
7. Conclusions, Implications, and Suggestions.......52
Reference...........................................56
Appendix: Questionnaire.............................64

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Balsmeier, P., & Voisin, W. (1996). Supply chain management: A time-based strategy. Industrial Management, 38(5), 24-27.
Banker, R. D., Chang, H., & Pizzini, M. J. (2004). The Balanced scorecard: Judgmental effects of performance measures linked to strategy. The Accounting Review, 79(1), 1-23.
Barber, N. F. (1993). EDI Ⅱ: The next generation. EDI World, 3(4), 18-20.
Barclay, D., Higgins, C., & Thompson, R. (1995). The partial least squares (PLS) approach to causal modeling: Personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
Beamon, B. M. (1999). Measuring supply chain performance. International Journal of Operations & Production Management, 19(3), 27-29.
Beechey, J., & Garlick, D. (1999). Using the balanced scorecard in banking. Journal of the Australian Institute of Bankers, 113(1), 28-31.
Brewer, P. C., & Speh, T. W. (2000). Using the balanced scorecard to measure supply chain performance. Journal of Business Logistics, 21(1), 75-94.
Chan, Y. E. (2000). IT value: The great divide between qualitative and quantitative and individual and organizational measures. Journal of Management Information Systems, 16(4), 225-261.
Chen, M. (2003). Factors affecting the adoption and diffusion of XML and Web services standards for E-business systems. International Journal of Human-Computer Studies, 58(3), 259-279.
Chin, W. W. (1998). Issues and opinion on structural equation modeling. MIS Quarterly, 22(1), 7-16.
Chin, W. W., Marcolin, B. L., & Newsted, P. R. (2003). A partial least squares latent variable modeling approach for measuring interaction effects: Results from a Monte Carlo simulation study and an electronic-mail emotion/adoption Study. Information Systems Research, 14(2), 189.
Cooper, M. C., Lambert, D. M., & Pagh, J. D. (1997). Supply chain management: More than a new name for logistics. International Journal of Logistics Management, 8(1), 1-14.
Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: A technological diffusion approach. Management Science, 36(2), 123-139.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.
Denton, G. A., & White, B. (2000). Implementing a balanced-scorecard approach to managing hotel operations: The case of white lodging services. Cornell Hotel and Restaurant Administration Quarterly, 41(1), 94.
Devaraj, S., & Kohli, R. (2000). Information technology payoff in the health-care industry: A longitudinal study. Journal of Information Management Systems, 16(4), 41-67.
Devaraj, S., & Kohli, R. (2003). Performance impacts of information technology: Is actual usage the missing link? Management Science, 49(3), 273-289.
Ellingson, D. A., & Wambsganss, J. R. (2001). Modifying the approach to planning and evaluation in governmental entities: A balanced scorecard approach. Journal of Public Budgeting Accounting and Financial Management, 13(1), 103-120.
Falk, R. F., & Miller, N. B. (1992). A Primer for Soft Modeling: Akron: University of Akron Press, OH.
Fichman, R. G. (2001). The role of aggregation in the measurement of IT-related organizational innovation. MIS Quarterly, 25(4), 427-456.
Fichman, R. G., & Kemerer, C. F. (1997). The assimilation of software process innovations: An organizational learning perspective. Management Science, 43(10), 1345-1363.
Fichman, R. G., & Kemerer, C. F. (1999). The illusory diffusion of innovation : An examination of assimilation gaps. Information Systems Research, 10(3), 255-275.
Fisher-Vanden, K. (2003). Management structure and technology diffusion in Chinese state-owned enterprises. Energy Policy, 31(3), 247-257.
Fisher, M. L. (1997). What is the right supply chain for your product? Harvard Business Review, 75(2), 105-117.
Fliedner, G. (2003). CPFR: An emerging supply chain tool. Industrial Management and Data Systems, 103(1), 14-21.
Forman, C., & Goldfarb, A. (2006). Diffusion of information and communication technologies to businesses In T. Hendershott (Ed.), Handbook of Economics and Information Systems: Elsevier.
Fornell, C., & Bookstein, F. L. (1982). Two structural equation models: LISREL and PLS applied to consumer exit-voice theory. Journal of Marketing Research, 19(4), 440-452.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Frohlich, M. T., & Westbrook, R. (2002). Demand chain management in manufacturing and services: Web-based integration, drivers and performance. Journal of Operations Management, 20(6), 729-745.
Gallivan, M. J. (2001). Organizational adoption and assimilation of complex technological innovations: Development and application of a new framework. Data Base, 32(3), 51-85.
Goode, S., & Stevens, K. (2000). An analysis of the business characteristics of adopters and non-adopters of World Wide Web technology. Information Technology and Management, 1(1), 129-154.
Grover, V., & Goslar, M. D. (1993). The initiation, adoption, and implementation of telecommunications technologies in US organizations. Journal of Management Information Systems, 10(1), 141-163.
Gumbus, A., & Lyons, B. (2002). The balanced scorecard at Philips Electronics. Strategic Finance, 84(5), 45-49.
Gunasekaran, A., & Ngai, E. W. T. (2004). Information systems in supply chain integration and management. European Journal of Operational Research, 159(2), 269-295.
Gunasekaran, A., Patel, C., & Tirtiroglu, E. (2001). Performance measures and metrics in a supply chain environment. International Journal of Operations & Production Management, 21(1/2), 71-87.
Hair, J. F., Anderson, R. E., Tatham, R., & Black, W. C. (2006). Multivariate data analysis: with readings: Prentice-Hall, Inc. Upper Saddle River, NJ, USA.
Hammer, M. (1990). Reengineering work: Don''t automate, obliterate. Harvard Business Review, 68(4), 104-112.
Handfield, R. B., & Nichols, E. L. (1999). Introduction to supply chain management. Englewood Cliffs, NJ: Prentice Hall.
Hong, W., & Zhu, K. (2006). Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level. Information & Management, 43(2), 204-221.
Hulland, J. (1999). Use of partial least squares (PLS) in strategic management research: A review of four recent studies. Strategic Management Journal, 20(2), 195-204.
Iacovou, C., Benbasat, I., & Dexter, A. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. MIS Quarterly, 19(1), 21.
Kaplan, R. S., & Norton, D. P. (1992). The balanced scorecard-measures that drive performance. Harvard Business Review, 70(1), 71-79.
Kaplan, R. S., & Norton, D. P. (1996a). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75-85.
Kaplan, R. S., & Norton, D. P. (1996b). Linking the balanced scorecard to strategy. California Management Review, 39(1), 53-79.
Kaplan, R. S., & Norton, D. P. (2001). Transforming the balanced scorecard from performance measurement to strategic management: Part I. Accounting Horizons, 15(1), 87-104.
Kaplan, R. S., & Norton, D. P. (2004a). Measuring the strategic readiness of intangible assets. Harvard Business Review, 82(2), 52-63.
Kaplan, R. S., & Norton, D. P. (2004b). The strategy map: guide to aligning intangible assets. Strategy & Leadership, 32(5), 10-17.
Kim, D., Cavusgil, S. T., & Calantone, R. J. (2006). Information system innovations and supply chain management: Channel relationships and firm performance. Journal of the Academy of Marketing Science, 34(1), 40-54.
Kim, J., Suh, E., & Hwang, H. (2003). A model for evaluating the effectiveness of CRM using the balanced scorecard. Journal of Interactive Marketing, 17(2), 5-19.
Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems implementation. In R. J. B. Jr. & R. A. Hirschheim (Eds.), Critical Issues in Information Systems Research (pp. 227-251). Chichester, UK: John Wiley and Sons Ltd.
Lambert, D. M., & Cooper, M. C. (2000). Issues in supply chain management. Industrial Marketing Management, 29(1), 65-83.
Lambert, D. M., Cooper, M. C., & Pagh, J. D. (1998). Supply chain management: Implementation issues and research opportunities. International Journal of Logistics Management, 9(2), 1-20.
Lancioni, R. A., Smith, M. F., & Oliva, T. A. (2000). The role of the Internet in supply chain management. Industrial Marketing Management, 29(1), 45-56.
Lapide, L. (2000). What about measuring supply chain performance? Achieving Supply Chain Excellence Through Technology, 2, 287-297.
Lavery, H. (1992). Getting a bigger EDI bang. EDI World, 7(2), 6-9.
Lee, H. L., & Billington, C. (1992). Managing supply chain inventory: Pitfalls and opportunities. Sloan Management Review, 33(3), 65-73.
Levy, D. L. (1997). Lean production in an international supply chain. Sloan Management Review, 38(2), 94-102.
Lewin, K. (1952). Group decision and social change. New York: Henry Holt
Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., & Subba Rao, S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), 107-124.
Libby, T., Salterio, S. E., & Webb, A. (2004). The balanced scorecard: The effects of assurance and process accountability on managerial judgment. The Accounting Review, 79(4), 1075-1094.
Maiga, A. S., & Jacobs, F. A. (2003). Balanced scorecard, activity-based costing and company performance: An empirical analysis. Journal of Managerial Issues, 15(3), 283-304.
Martinsons, M., Davison, R., & Tse, D. (1999). The balanced scorecard: a foundation for the strategic management of information systems. Decision Support Systems, 25(1), 71-88.
Melville, N., Kraemer, K., & Gurbaxani, V. (2004). Information technology and organizational performance: An integrative model of IT business value. MIS Quarterly, 28(2), 283-322.
Morgan, C. (2004). Structure, speed and salience: Performance measurement in the supply chain. Business Process Management Journal, 10(5), 522-536.
Nunnally, J. C. (1978). Psychometric Theory: McGraw-Hill, New York.
Park, J. H., Lee, J. K., & Yoo, J. S. (2005). A framework for designing the balanced supply chain scorecard. European Journal of Information Systems, 14(4), 335-346.
Patterson, K. A., Grimm, C. M., & Corsi, T. M. (2003). Adopting new technologies for supply chain management. Transportation Research Part E, 39(2), 95-121.
Patterson, K. A., Grimm, C. M., & Corsi, T. M. (2004). Diffusion of supply chain technologies. Transportation Journal, 43(3), 5-23.
Porter, M. E., & Millar, V. E. (1985). How information gives you competitive advantage. Harvard Business Review, 63(4), 149-160.
Premkumar, G., & Ramamurthy, K. (1995). The role of interorganizational and organizational factors on the decision mode for adoption of interorganizational systems. Decision Sciences, 26(3), 303-336.
Premkumar, G., Ramamurthy, K., & Nilakanta, S. (1994). Implementation of electronic data interchange: An innovation diffusion perspective. Journal of Management Information Systems, 11(2), 157-186.
Premkumar, G. P. (2000). Interorganization systems and supply chain management: An information processing perspective. Information Systems Management, 17(3), 56-69.
Rai, A., Patnayakuni, R., & Patnayakuni, N. (2006). Firm performance impacts of digitally enabled supply chain integration capabilities. MIS Quarterly, 30(2), 225-246.
Ramamurthy, K., & Premkumar, G. (1995). Determinants and outcomes of electronic data interchange diffusion. IEEE Transactions on Engineering Management, 42(4), 332-351.
Ramamurthy, K., Premkumar, G., & Crum, M. R. (1999). Organizational and interorganizational determinants of EDI diffusion and organizational performance: A causal model. Journal of Organizational Computing and Electronic Commerce, 9(4), 253-285.
Ranganathan, C., Dhaliwal, J. S., & Teo, T. S. H. (2004). Assimilation and diffusion of web technologies in supply-chain management: An examination of key drivers and performance impacts. International Journal of Electronic Commerce, 9(1), 127-161.
Rogers, E. M. (1995). Diffusion of Innovations (Fourth ed.). New York: The Free Press.
Sanchez, A. M., & Perez, M. P. (2005). Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681-700.
Shin, H., Collier, D. A., & Wilson, D. D. (2000). Supply management orientation and supplier/buyer performance. Journal of Operations Management, 18(3), 317-333.
Stank, T. P., Keller, S. B., & Daugherty, P. J. (2001). Supply chain collaboration and logistical service performance. Journal of Business Logistics, 22(1), 29-48.
Stewart, G. (1995). Supply chain performance benchmarking study reveals keys to supply chain excellence. Logistics Information Management, 8(2), 38-44.
Swamidass, P. M. (2003). Modeling the adoption rates of manufacturing technology innovations by small US manufacturers: A longitudinal investigation. Research Policy, 32(3), 351-366.
Swanson, E. B., & Ramiller, N. C. (1997). The organizing vision in information systems innovation. Organization Science, 8(5), 458-474.
Swanson, E. B., & Ramiller, N. C. (2004). Innovating mindfully with information technology. MIS Quarterly, 28(4), 553-583.
Tan, K. C., Kannan, V. R., & Handfield, R. B. (1998). Supply chain management: supplier performance and firm performance. International Journal of Purchasing and Materials Management, 34(3), 2-9.
Ullrich, M. J., & Tuttle, B. M. (2004). The effects of comprehensive information reporting systems and economic incentives on managers'' time-planning decisions. Behavioral Research in Accounting, 16(1), 89-105.
Van Der Zee, J. T. M., & De Jong, B. (1999). Alignment is not enough: Integrating business and information technology management with the balanced business scorecard. Journal of Management Information Systems, 16(2), 137-156.
Vickery, S., Calantone, R., & Droge, C. (1999). Supply chain flexibility: An empirical study. Journal of Supply Chain Management, 35(3), 16-24.
Wang, E., Tai, J., & Wei, H. L. (2006). A virtual integration theory of improved supply-chain performance. Journal of Management Information Systems, 23(2), 41-64.
Wang, Y. C., Chang, C. W., & Heng, M. S. H. (2004). The levels of information technology adoption, business network, and a strategic position model for evaluating supply chain integration. Journal of Electronic Commerce Research, 5(2), 85-98.
Yeniyurt, S. (2003). A literature review and integrative performance measurement framework for multinational companies. Marketing Intelligence and Planning, 21(3), 134-142.
Zhu, K., Kraemer, K., & Xu, S. (2003). Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 12(4), 251-268.
Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: A technology diffusion perspective on e-Business. Management Science, 52(10), 1557-1576.
Zmud, R. W., & Apple, L. E. (1992). Measuring technology incorporation/infusion. Journal of Product Innovation Management 9(2), 148-155.