在競爭激烈的環境下，資訊科技對於公司來說是不可或缺的。企業投資資訊科技能夠替公司增加組織績效和利益等，相反來說，不適當的採用資訊科技可能會造成企業失敗。過去學者研究組織採用資訊科技，大多是認為基於功能性的需求來探討，然而，企業採用資訊科技的目的有時並不是為了資訊科技帶來的功能效益，有可能是因為外在環境壓力的影響，像是受到同業壓力的影響、政府的規範和環境趨勢的影響等而採用某樣資訊科技。因為不同的採用目的，對於企業的採用結果會有不同的影響。因此本研究的目的在於了解組織採用與使用資訊科技的影響因素為何，並探討不同的採用目的(功能性和象徵性)對於組織的影響。
本研究基於Fit-Viability Model建構出研究模型，納入企業採用資訊科技之內在因素和外在因素，並透過問卷調查的方式進行實證研究，結果顯示本研究之模型能夠有效的解釋資訊科技的採用與使用。對於組織的採用動機而言，外在環境壓力對於科技的象徵性採用會有較大的影響。因為象徵性而採用資訊科技，組織會有較少的實際使用，配適度和組織可行性對於組織績效都有顯著的影響。說明象徵性採用目的也能夠為組織帶來績效。

In a competitive environment, Information Technology (IT) is necessary for companies to boost performance. Adoption of proper IT is very important because inappropriate use of IT can lead to the failure of organizations. In the past, many researchers have investigated the issue of business adoption of information technology from their functional needs. In many cases, however, technology adoption is not due to functional needs, but due to environmental pressures or other reasons, such as peer pressure, normative pressure and surrounding changes. Different purposes for adoption may lead to different outcomes. Hence, the purpose of this research is to investigate what factors affect an organization’s adoption of information technology, and how different purposes (symbolic value vs. function value) can affect organizational adoption.
The framework of this paper is based on the Fit-Viability Model to study both internal organizational factors and external environmental factors. A questionnaire survey of Taiwanese firms was conducted and PLS was used to analyze the collected data. Results show that the model used in the paper can interpret organizational IT adoption and IT usage. We find that different factors come into play between symbolic and functional adoption. Environmental pressures have greater effects on symbolic adoption which often lead to less usage and less enhancement to organizational performance.

論文審定書 i
致謝 ii
摘要 iii
abstract iv
目錄 v
圖次 vii
表次 viii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第三節 研究流程 5
第二章 文獻探討 6
第一節 企業之資訊科技採用 6
第二節 影響企業採用資訊科技之因素 7
第三節 資訊科技採用後之績效 11
第四節 認知利益 12
第五節 任務科技配適度 14
第六節 配適-可行性模式 17
第三章 研究架構與方法 22
第一節 研究架構 22
第二節 研究假說 23
第三節 操作型定義與問項 26
第四節 問卷設計 36
第四章 資料分析 41
第一節 樣本基本資料 41
第二節 衡量模型 44
第三節 結構模型及假說驗證 50
第五章 結論與建議 61
第一節 研究結果及討論 61
第二節 理論及實務意涵 63
第三節 研究限制及未來方向 64
參考文獻 65
附錄一、問卷內容 73

中文文獻
王宏仁. (2016). 【iThome 2016年CIO大調查｜企業IT投資規模分析】雲端和行動需求持續發威，大資料投資降溫回穩. from http://www.ithome.com.tw/article/103723
孫思源, & 林東清. (1999). 企業採用資訊科技影響構面因素之彙總研究. 中華管理評論, 第二卷，第五期, 133~144頁.

英文文獻

Abreu Novais, M., & Arcodia, C. (2013). Measuring the effects of event sponsorship: Theoretical frameworks and image transfer models. Journal of Travel & Tourism Marketing, 30(4), 308-334.
Ahituv, N., & Giladi, R. (1993). Business success and information technology: Are they really related? : Tel Aviv University, Faculty of Management, The Leon Recanati Graduate School of Business Administration.
Altinkemer, K., Ozcelik, Y., & Ozdemir, Z. D. (2011). Productivity and performance effects of business process reengineering: A firm-level analysis. Journal of Management Information Systems, 27(4), 129-162.
Anderson, E. W., Fornell, C., & Mazvancheryl, S. K. (2004). Customer satisfaction and shareholder value. Journal of marketing, 68(4), 172-185.
Ashforth, B. E. (1985). Climate formation: Issues and extensions. Academy of management review, 10(4), 837-847.
Bagozzi, R. P. (1982). A field investigation of causal relations among cognitions, affect, intentions, and behavior. Journal of marketing research, 562-583.
Banker, R. D., Chang, H., Janakiraman, S. N., & Konstans, C. (2004). A balanced scorecard analysis of performance metrics. European journal of operational research, 154(2), 423-436.
Baroudi, J. J., Olson, M. H., & Ives, B. (1986). An empirical study of the impact of user involvement on system usage and information satisfaction. Communications of the ACM, 29(3), 232-238.
Barua, A., Kriebel, C. H., & Mukhopadhyay, T. (1995). Information technologies and business value: An analytic and empirical investigation. Information systems research, 6(1), 3-23.
Beatty, R. C., Shim, J. P., & Jones, M. C. (2001). Factors influencing corporate web site adoption: a time-based assessment. Information & management, 38(6), 337-354.
Benbasat, I., Dexter, A. S., & Todd, P. (1986). An experimental program investigating color-enhanced and graphical information presentation: an integration of the findings. Communications of the ACM, 29(11), 1094-1105.
Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: an empirical investigation. Mis Quarterly, 169-196.
Bhattacherjee, A., & Premkumar, G. (2004). Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. Mis Quarterly, 229-254.
Bohlen, J. M. (1964). The adoption and diffusion of ideas in agriculture: Iowa State University Press.
Bohlen, J. M. (1968). Research needed on adoption models. The Processes and Effects of Mass Communication, 798-815.
Bouchard, L. (1993). Decision criteria in the adoption of EDI: Direction de la recherche, Faculté des sciences de l'administration, Université Laval.
Brynjolfsson, E. (1993). The productivity paradox of information technology: review and assessment. Communications of the ACM, 36(12).
Brynjolfsson, E., & Hitt, L. (1996). Paradox lost? Firm-level evidence on the returns to information systems spending. Management science, 42(4), 541-558.
Carr, N. G. (2003). IT doesn't matter. Educause Review, 38, 24-38.
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.
Cheney, P. H., Mann, R. I., & Amoroso, D. L. (1986). Organizational factors affecting the success of end-user computing. Journal of Management Information Systems, 3(1), 65-80.
Chin, W. W. (2000). Frequently asked questions–partial least squares & PLS-graph. Home Page.[On-line]. Retrieved October, 15, 2006.
Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: a technological diffusion approach. Management science, 36(2), 123-139.
D'Ambra, J., & Wilson, C. S. (2004). Use of the World Wide Web for international travel: Integrating the construct of uncertainty in information seeking and the task‐technology fit (TTF) model. Journal of the Association for Information Science and Technology, 55(8), 731-742.
Damanpour, F., & Schneider, M. (2006). Phases of the adoption of innovation in organizations: Effects of environment, organization and top managers. British journal of Management, 17(3), 215-236.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. Mis Quarterly, 319-340.
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.
Dehning, B., Richardson, V. J., & Zmud, R. W. (2007). The financial performance effects of IT-based supply chain management systems in manufacturing firms. Journal of Operations Management, 25(4), 806-824.
Devaraj, S., & Kohli, R. (2003). Performance impacts of information technology: Is actual usage the missing link? Management science, 49(3), 273-289.
Dewan, S., & Min, C.-k. (1997). The substitution of information technology for other factors of production: A firm level analysis. Management science, 43(12), 1660-1675.
Dickson, G. W., DeSanctis, G., & McBride, D. J. (1986). Understanding the effectiveness of computer graphics for decision support: a cumulative experimental approach. Communications of the ACM, 29(1), 40-47.
Diewert, W. E., & Smith, A. M. (1994). Productivity measurement for a distribution firm: National Bureau of Economic Research.
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task–technology fit constructs. Information & management, 36(1), 9-21.
Doll, W. J., & Torkzadeh, G. (1991). The measurement of end-user computing satisfaction: theoretical and methodological issues. Mis Quarterly, 5-10.
Festinger, L. (1954). A theory of social comparison processes. Human relations, 7(2), 117-140.
Fishbein, M., & Ajzen, I. (1977). Belief, attitude, intention, and behavior: An introduction to theory and research.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of marketing research, 382-388.
Forsythe, S., Liu, C., Shannon, D., & Gardner, L. C. (2006). Development of a scale to measure the perceived benefits and risks of online shopping. Journal of interactive marketing, 20(2), 55-75.
Foskett, J. (2016). Adaption of the Fit-Viability Theory to Assess Technology in the Hospital Laboratory. Northcentral University.
Gebauer, J., & Shaw, M. J. (2004). Success factors and impacts of mobile business applications: results from a mobile e-procurement study. International Journal of Electronic Commerce, 8(3), 19-41.
Goodhue, D. (1988). I/S attitudes: toward theoretical and definitional clarity. ACM SIGMIS Database, 19(3-4), 6-15.
Goodhue, D. L. (1995). Understanding user evaluations of information systems. Management science, 41(12), 1827-1844.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. Mis Quarterly, 213-236.
Goodyear, M. (1993). Reviewing the concept of brands and branding. Marketing and Research Today, 21(2), 75-75.
Grandon, E. E., & Pearson, J. M. (2004). Electronic commerce adoption: an empirical study of small and medium US businesses. Information & management, 42(1), 197-216.
Guler, I., Guillén, M. F., & Macpherson, J. M. (2002). Global competition, institutions, and the diffusion of organizational practices: The international spread of ISO 9000 quality certificates. Administrative science quarterly, 47(2), 207-232.
Gutierrez, A., Boukrami, E., & Lumsden, R. (2015). Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of Enterprise Information Management, 28(6), 788-807.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2009). Multivariate data analysis (Vol. 5): Prentice hall Upper Saddle River, NJ.
Hair, J. F., Sarstedt, M., Ringle, C. M., & Mena, J. A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the academy of marketing science, 40(3), 414-433.
Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358-390.
Hartwick, J., & Barki, H. (1994). Explaining the role of user participation in information system use. Management science, 40(4), 440-465.
Hitt, L. M., & Brynjolfsson, E. (1996). Productivity, business profitability, and consumer surplus: three different measures of information technology value. Mis Quarterly, 121-142.
Hsu, P.-F., Ray, S., & Li-Hsieh, Y.-Y. (2014). Examining cloud computing adoption intention, pricing mechanism, and deployment model. International Journal of Information Management, 34(4), 474-488.
Hwang, Y., & Leitch, R. A. (2005). Balanced scorecard: evening the odds of successful BPR. IT professional, 7(6), 24-30.
Iacovou, C. L., Benbasat, I., & Dexter, A. S. (1995). Electronic data interchange and small organizations: Adoption and impact of technology. Mis Quarterly, 465-485.
Ifinedo, P. (2011). Internet/e-business technologies acceptance in Canada's SMEs: an exploratory investigation. Internet Research, 21(3), 255-281.
Jasperson, J. S., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. Mis Quarterly, 29(3), 525-557.
Junglas, I., & Watson, R. (2003). U-commerce: an experimental investigation of ubiquity and uniqueness. ICIS 2003 Proceedings, 35.
Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. Mis Quarterly, 781-804.
Kim, H.-W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.
Kim, H.-W., & Kankanhalli, A. (2009). Investigating user resistance to information systems implementation: A status quo bias perspective. Mis Quarterly, 567-582.
King, W. R., & Teo, T. S. (1996). Key dimensions of facilitators and inhibitors for the strategic use of information technology. Journal of Management Information Systems, 12(4), 35-53.
Klonglan, G. E., & Coward, E. W. (1970). The concept of symbolic adoption: A suggested interpretation. Rural Sociology, 35(1), 77.
Kollmann, T., HäSel, M., & Breugst, N. (2009). Competence of IT professionals in e-business venture teams: the effect of experience and expertise on preference structure. Journal of Management Information Systems, 25(4), 51-80.
Kuan, K. K., & Chau, P. Y. (2001). A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Information & management, 38(8), 507-521.
Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems implementation. Paper presented at the Critical issues in information systems research.
Lai, V. S., & Guynes, J. L. (1997). An assessment of the influence of organizational characteristics on information technology adoption decision: a discriminative approach. IEEE Transactions on Engineering Management, 44(2), 146-157.
Larosiliere, G. D., & Carter, L. D. (2013). An Empirical Study On The Determinants Of E-Government Maturity: A Fit-Viability Perspective. Paper presented at the ECIS.
Lee, C.-P., & Shim, J. P. (2007). An exploratory study of radio frequency identification (RFID) adoption in the healthcare industry. European Journal of Information Systems, 16(6), 712-724.
Liang, H., Saraf, N., Hu, Q., & Xue, Y. (2007). Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. Mis Quarterly, 59-87.
Liang, T.-P., Huang, C.-W., Yeh, Y.-H., & Lin, B. (2007). Adoption of mobile technology in business: a fit-viability model. Industrial management & data systems, 107(8), 1154-1169.
Liang, T.-P., & Wei, C.-P. (2004). Introduction to the special issue: mobile commerce applications. International Journal of Electronic Commerce, 8(3), 7-17.
Lin, W.-S., & Wang, C.-H. (2012). Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Computers & Education, 58(1), 88-99.
Loveman, G. W. (1994). An assessment of the productivity impact of information technologies. Information technology and the corporation of the 1990s: Research studies, 84-110.
Lucas Jr, H. C. (1975). Performance and the use of an information system. Management science, 21(8), 908-919.
Lucas Jr, H. C. (1981). Analysis, Design and Implementation of Information Systems: McGraw-Hill, Inc.
Mettler, T. (2016). Anticipating mismatches of HIT investments: Developing a viability-fit model for e-health services. International journal of medical informatics, 85(1), 104-115.
Moore, G., & Benbasat, I. (1992). An empirical examination of a model of the factors affecting utilization of information technology by end-users. University of British Columbia, Vancouver, working paper.
O’brien, R. M. (2007). A caution regarding rules of thumb for variance inflation factors. Quality & Quantity, 41(5), 673-690.
Oliveira, T., Thomas, M., & Espadanal, M. (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & management, 51(5), 497-510.
Oliver, C. (1991). Strategic responses to institutional processes. Academy of management review, 16(1), 145-179.
Olson, M. H., & Ives, B. (1982). Chargeback systems and user involvement in information systems-An empirical investigation. Mis Quarterly, 47-60.
Park, C. W., Jaworski, B. J., & Maclnnis, D. J. (1986). Strategic brand concept-image management. The Journal of Marketing, 135-145.
Petter, S., Straub, D., & Rai, A. (2007). Specifying formative constructs in information systems research. Mis Quarterly, 623-656.
Pettey, C. (2016). Gartner Says Global IT Spending to Reach $3.5 Trillion in 2017. from http://www.gartner.com/newsroom/id/3482917
Pierce, J. L., & Delbecq, A. L. (1977). Organization structure, individual attitudes and innovation. Academy of management review, 2(1), 27-37.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. Journal of applied psychology, 88(5), 879.
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., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467-484.
Quaddus, M., & Hofmeyer, G. (2007). An investigation into the factors influencing the adoption of B2B trading exchanges in small businesses. European Journal of Information Systems, 16(3), 202-215.
Ramamurthy, K., & Premkumar, G. (1995). Determinants and outcomes of electronic data interchange diffusion. IEEE Transactions on Engineering Management, 42(4), 332-351.
Ramamurthy, K. R., Sen, A., & Sinha, A. P. (2008). An empirical investigation of the key determinants of data warehouse adoption. Decision support systems, 44(4), 817-841.
Ravichandran, T., Lertwongsatien, C., & LERTWONGSATIEN, C. (2005). Effect of information systems resources and capabilities on firm performance: A resource-based perspective. Journal of Management Information Systems, 21(4), 237-276.
Ray, G., Barney, J., & Muhanna, W. (2001). Capabilities, Business Processes, and Competitive Advantage: The Impact of Information Technology on Customer Satisfaction in North American Insurance Industry,“: Working paper, university of Texas at Austin.
Richard, S. W. (1992). Organizations: Rational, natural, and open systems. Aufl., Englewood Cliffs (NJ).
Robbins, S. P. (1992). Essentials of organizational behavior. New Jersey: Prentice Hall.
Robey, D. (1979). User attitudes and management information system use. Academy of Management Journal, 22(3), 527-538.
Robins, J., & Wiersema, M. F. (1995). A resource‐based approach to the multibusiness firm: Empirical analysis of portfolio interrelationships and corporate financial performance. Strategic Management Journal, 16(4), 277-299.
Rogers, E. M. (1968). A communication research approach to the diffusion of innovations. Diffusion Research Needs, Columbia: Missouri Agricultural Experiment Station, North Central Regional Research Bulletin, 186, 27-30.
San Martín, S., López-Catalán, B., & Ramón-Jerónimo, M. A. (2012). Factors determining firms' perceived performance of mobile commerce. Industrial management & data systems, 112(6), 946-963.
Santhanam, R., & Hartono, E. (2003). Issues in linking information technology capability to firm performance. Mis Quarterly, 125-153.
Saunders, C. S., & Clark, S. (1992). EDI adoption and implementation: A focus on interorganizational linkages. Information Resources Management Journal (IRMJ), 5(1), 9-20.
Seyal, A. H., Awais, M. M., Shamail, S., & Abbas, A. (2004). Determinants of electronic commerce in Pakistan: Preliminary evidence from small and medium enterprises. Electronic Markets, 14(4), 372-387.
Seyal, A. H., Noah Abd Rahman, M., & Awg Yussof Hj Awg Mohammad, H. (2007). A quantitative analysis of factors contributing electronic data interchange adoption among Bruneian SMEs: A pilot study. Business Process Management Journal, 13(5), 728-746.
Shah Alam, S. (2009). Adoption of internet in Malaysian SMEs. Journal of Small Business and Enterprise Development, 16(2), 240-255.
Sheth, S. (1983). An integrative theory of patronage preference and behavior. InW. R. DardenandR. F. Lusch (Eds.), Patronage behaviorand retail management (pp. 9-28): Amsterdam: North-Holland.
Sitkin, S. B., & Pablo, A. L. (1992). Reconceptualizing the determinants of risk behavior. Academy of management review, 17(1), 9-38.
Sivakumar, K., & Raj, S. (1997). Quality tier competition: How price change influences brand choice and category choice. The Journal of Marketing, 71-84.
Steers, R. M. (1977). Organizational effectiveness: A behavioral view: Goodyear Pub. Co.
Subramanian, A., & Nilakanta, S. (1996). Organizational innovativeness: Exploring the relationship between organizational determinants of innovation, types of innovations, and measures of organizational performance. Omega, 24(6), 631-647.
Swanson, E. B. (1987). Information channel disposition and use. Decision Sciences, 18(1), 131-145.
Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of retailing, 77(2), 203-220.
Tanriverdi, H. (2006). Performance effects of information technology synergies in multibusiness firms. Mis Quarterly, 57-77.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: toward a conceptual model of utilization. Mis Quarterly, 125-143.
Tjan, A. K. (2001). Finally, a way to put your Internet portfolio in order. Harvard Business Review, 79(2), 76-85, 156.
Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation: Lexington Books.
Tornatzky, L. G., & Klein, K. J. (1982). Innovation characteristics and innovation adoption-implementation: A meta-analysis of findings. IEEE Transactions on Engineering Management(1), 28-45.
Triandis, H. C. (1979). Values, attitudes, and interpersonal behavior. Paper presented at the Nebraska symposium on motivation.
Turban, E., Liang, T.-P., & Wu, S. P. (2011). A framework for adopting collaboration 2.0 tools for virtual group decision making. Group decision and negotiation, 20(2), 137-154.
Wade, M., & Hulland, J. (2004). Review: The resource-based view and information systems research: Review, extension, and suggestions for future research. Mis Quarterly, 28(1), 107-142.
Wang, E. T., Klein, G., & Jiang, J. J. (2006). ERP misfit: country of origin and organizational factors. Journal of Management Information Systems, 23(1), 263-292.
Wang, J., & Wang, X. (2012). Structural equation modeling: Applications using Mplus: John Wiley & Sons.
Wu, S. P.-J., Straub, D. W., & Liang, T.-P. (2015). How information technology governance mechanisms and strategic alignment influence organizational performance: Insights from a matched survey of business and it managers. Mis Quarterly, 39(2), 497-518.
Yeh, Y.-H. (2011). Organizational Adoption of Information Technologies–An Extended Fit-Viability Model. Doctorate Dissertation. National Sun Yat-sen University.
Zahra, S. A. (1993). Environment, corporate entrepreneurship, and financial performance: A taxonomic approach. Journal of business venturing, 8(4), 319-340.
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.
Zott, C., & Huy, Q. N. (2007). How entrepreneurs use symbolic management to acquire resources. Administrative science quarterly, 52(1), 70-105.
Zwick, T. (2002). Employee resistance against innovations. International journal of Manpower, 23(6), 542-552.


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Gartner, http://www.gartner.com/newsroom/id/3482917
iThome, http://www.ithome.com.tw/article/103723