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題名 組織採用資訊科技之彙整分析
Organizational Adoption of Information Technology: A Meta-Analysis作者 黃冠傑
Huang, Kuan-Chieh貢獻者 梁定澎<br>周彥君
Liang, Ting-Peng<br>Chou, Yen-Chun
黃冠傑
Huang, Kuan-Chieh關鍵詞 彙整分析
TOE模式
資訊科技
組織採用
Meta-analysis
TOE model
Information technology
Organization adoption日期 2018 上傳時間 2-May-2019 14:41:53 (UTC+8) 摘要 本文針對過去30年來，眾多學者對於組織採用資訊科技因素之初級研究進行彙整分析，並透過TOE模式，將原因以科技、組織、環境，等三構面進行歸納。本研究目的是希望能將過去結果迥異的研究進行客觀且具科學性的整合，得到一個彙整性之結論。本研究針對Web of Science資料庫中的31篇相關論文逐篇進行編碼，記錄每篇初級研究其自變量與依變量的相關係數，以及樣本數與各項資料，並透過彙整分析，將31篇論文的各項自變量與依變量關係進行整合與運算，進而為每種變數關係獲得一個整體的效果規模，以評估該變數之間的真實關聯程度。結果發現，影響力最大且最穩固的前五個因素依序為：預期效益、組織準備度、技術感知有用性、高層支持，以及IT基礎建設。總體來說，科技面與組織面的因素擁有較強的影響力，環境面的因素則較弱。不顯著的因素則包括：相對優勢、系統安全性、營運之地理範圍、廠商技術支援，以及政府支持。本研究針對文獻總數超過10篇的自變量設置三個調節變量，分別為：地區、組織規模、時間，並透過這三個調節變量將每個自變量切割成數個子集合，並再次進行彙整分析。結果發現IT基礎建設在「非亞洲」地區為顯著，且效果規模明顯強於「亞洲地區」；中小企業比大企業更容易因為自身組織規模的擴張，而更有意願去採用一項資訊科技，這與Hameed et al. (2012).的研究結果高度相符。除此之外，大企業相較於其他規模的企業，更容易因為競爭壓力、高層支持，以及預期效益的因素，而去採用一項創新的資訊科技；小企業則是更容易因為「組織內部的技術知識」，而左右其是否採用一項創新的資訊科技。
This research aims to do meta-analysis on the theses which were about finding the reasons for organizational IT adoption and were published during the last 30 years. TOE model is adopted in this thesis as research model due to the benefit from categorizing the reasons into 3 aspects: Technology, Organization and Environment. We hope to integrate the different results from the previous theses by a scientific methodology – Meta-Analysis and in order to get an overall result.31 studies from the database Web of Science are encoded. The correlation coefficients between independent and dependent variables are collected, as well as sample sizes and other data. These data are synthesized into Effect Size, which is able to indicate the overall and real extent to which each factor has through meta-analysis. The result shows that the top five significant and robust factors are Perceived Benefits, Organizational Readiness, Perceived Usefulness, Top Management Support and Technological Knowledge. Overall, Factors in the aspect of Technology and the aspect of Organization have stronger correlations than those in the aspect of Environment. Insignificant factors include Relative Advantages, System Security, Global Scope, Support from Technology Vendors and Government Support.Factors having at least 10 studies as samples are divided into several groups to analyze again by adding 3 moderators – Region, Organization Size and Time. The result shows that IT Infrastructure is significant in non-Asia area and has larger effect size than in Asia. SMEs are more willing to adopt a new information technology due to the increasing of its organization size than large firms, which is highly consistent with the findings from Hameed et al. (2012). Furthermore, large firms tend to adopt a new information technology due to Competitive Pressure, Top Management and Perceived Benefits while SMEs tend to do so due to the know-how in its organization.參考文獻 洪新原, 梁定澎, & 張嘉銘. (2005). 科技接受模式之彙總研究. 資訊管理學報, 12(4), 211-234.傅品甄. (2017). 組織採用資訊科技之彙整分析.Baker, J. (2012). The technology–organization–environment framework. In Information systems theory (pp. 231-245). Springer, New York, NY.Broadbent, M., Weill, P., & St. Clair, D. (1999). The implications of information technology infrastructure for business process redesign. MIS quarterly, 159-182.Buhalis, D. (1998). Strategic use of information technologies in the tourism industry. Tourism management, 19(5), 409-421.Card, N. A. (2015). Applied meta-analysis for social science research. Guilford Publications.Chong, J. L., & Olesen, K. (2017). A Technology-Organization-Environment perspective on eco-effectiveness: A Meta-analysis. Australasian Journal of Information Systems, 21.Cohen, J. (1977). Statistical power analysis for the behavioral sciences (Rev. ed.) New York: Academic. Google Scholar.Depietro, R., Wiarda, E., & Fleischer, M. (1990). The context for change: Organization, technology and environment. The processes of technological innovation, 199(0), 151-175.DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled clinical trials, 7(3), 177-188.Glass, G. V., Smith, M. L., & McGaw, B. (1981). Meta-analysis in social research. Sage Publications, Incorporated.Hage, J. (1980). Theories of organizations: Form, process, and transformation. John Wiley & Sons.Hameed, M. A., Counsell, S., & Swift, S. (2012). A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations. Information & management, 49(5), 218-232.Huang, P. Y. (2009). A Meta Analysis of Technology Adoption Intention Models.Hunter, J.E. & Schmidt, F.L. (1990). Methods of Meta Analysis, Sage Publications, Newbury Park, CA.Hunter, J.E., Schmidt, F.L. & Jackson, G.B. (1982). Meta-Analysis: Cumulating Research Findings Across Studies, Sage Publications, Beverly Hills, CA.Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological methods, 17(2), 137.Khandwalla, P. (1970) Environment and the organization structure of firms, McGill University, Montreal, Faculty of Management.Lee, G., & Xia, W. (2006). Organizational size and IT innovation adoption: A meta-analysis. Information & Management, 43(8), 975-985.Ma, Q., & Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End User Computing (JOEUC), 16(1), 59-72.Nie, J. (2007, September). A study of information technology adoption for small and medium sized enterprises strategic competitiveness. In Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on (pp. 4342-4346). IEEE.Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. The electronic journal information systems evaluation, 14(1), 110-121.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.Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. Journal of Applied Psychology, 90(1), 175.Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467-484.Racherla, P., & Hu, C. (2008). eCRM system adoption by hospitality organizations: A technology-organization-environment (TOE) framework. Journal of Hospitality & Leisure Marketing, 17(1-2), 30-58.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.Rosenthal, R. (1978). Combining results of independent studies. Psychological bulletin, 85(1), 185.Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological bulletin, 86(3), 638.Rosenthal, R. (1991). Meta-analytic procedures for social research (Vol. 6). Sage.Starbuck, W.H. (1976) Organizations and their environments, Chicago, Rand McNally.Thompson, J. D. (1967). Organizations in action: Social science bases of administration.Wang, Y. M., Wang, Y. S., & Yang, Y. F. (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological forecasting and social change, 77(5), 803-815.Wolf, F. M. (1986). Meta-analysis: Quantitative methods for research synthesis (Vol. 59). Sage.Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. Mis Quarterly, 419-432.Yeh, Y. H. (2011). Organizational Adoption of Information Technologies–An Extended Fit-Viability Model. Doctorate Dissertation. National Sun Yat-sen University. 描述 碩士
國立政治大學
資訊管理學系
105356022資料來源 http://thesis.lib.nccu.edu.tw/record/#G1053560223 資料類型 thesis dc.contributor.advisor 梁定澎<br>周彥君 zh_TW dc.contributor.advisor Liang, Ting-Peng<br>Chou, Yen-Chun en_US dc.contributor.author (Authors) 黃冠傑 zh_TW dc.contributor.author (Authors) Huang, Kuan-Chieh en_US dc.creator (作者) 黃冠傑 zh_TW dc.creator (作者) Huang, Kuan-Chieh en_US dc.date (日期) 2018 en_US dc.date.accessioned 2-May-2019 14:41:53 (UTC+8) - dc.date.available 2-May-2019 14:41:53 (UTC+8) - dc.date.issued (上傳時間) 2-May-2019 14:41:53 (UTC+8) - dc.identifier (Other Identifiers) G1053560223 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/123223 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理學系 zh_TW dc.description (描述) 105356022 zh_TW dc.description.abstract (摘要) 本文針對過去30年來，眾多學者對於組織採用資訊科技因素之初級研究進行彙整分析，並透過TOE模式，將原因以科技、組織、環境，等三構面進行歸納。本研究目的是希望能將過去結果迥異的研究進行客觀且具科學性的整合，得到一個彙整性之結論。本研究針對Web of Science資料庫中的31篇相關論文逐篇進行編碼，記錄每篇初級研究其自變量與依變量的相關係數，以及樣本數與各項資料，並透過彙整分析，將31篇論文的各項自變量與依變量關係進行整合與運算，進而為每種變數關係獲得一個整體的效果規模，以評估該變數之間的真實關聯程度。結果發現，影響力最大且最穩固的前五個因素依序為：預期效益、組織準備度、技術感知有用性、高層支持，以及IT基礎建設。總體來說，科技面與組織面的因素擁有較強的影響力，環境面的因素則較弱。不顯著的因素則包括：相對優勢、系統安全性、營運之地理範圍、廠商技術支援，以及政府支持。本研究針對文獻總數超過10篇的自變量設置三個調節變量，分別為：地區、組織規模、時間，並透過這三個調節變量將每個自變量切割成數個子集合，並再次進行彙整分析。結果發現IT基礎建設在「非亞洲」地區為顯著，且效果規模明顯強於「亞洲地區」；中小企業比大企業更容易因為自身組織規模的擴張，而更有意願去採用一項資訊科技，這與Hameed et al. (2012).的研究結果高度相符。除此之外，大企業相較於其他規模的企業，更容易因為競爭壓力、高層支持，以及預期效益的因素，而去採用一項創新的資訊科技；小企業則是更容易因為「組織內部的技術知識」，而左右其是否採用一項創新的資訊科技。 zh_TW dc.description.abstract (摘要) This research aims to do meta-analysis on the theses which were about finding the reasons for organizational IT adoption and were published during the last 30 years. TOE model is adopted in this thesis as research model due to the benefit from categorizing the reasons into 3 aspects: Technology, Organization and Environment. We hope to integrate the different results from the previous theses by a scientific methodology – Meta-Analysis and in order to get an overall result.31 studies from the database Web of Science are encoded. The correlation coefficients between independent and dependent variables are collected, as well as sample sizes and other data. These data are synthesized into Effect Size, which is able to indicate the overall and real extent to which each factor has through meta-analysis. The result shows that the top five significant and robust factors are Perceived Benefits, Organizational Readiness, Perceived Usefulness, Top Management Support and Technological Knowledge. Overall, Factors in the aspect of Technology and the aspect of Organization have stronger correlations than those in the aspect of Environment. Insignificant factors include Relative Advantages, System Security, Global Scope, Support from Technology Vendors and Government Support.Factors having at least 10 studies as samples are divided into several groups to analyze again by adding 3 moderators – Region, Organization Size and Time. The result shows that IT Infrastructure is significant in non-Asia area and has larger effect size than in Asia. SMEs are more willing to adopt a new information technology due to the increasing of its organization size than large firms, which is highly consistent with the findings from Hameed et al. (2012). Furthermore, large firms tend to adopt a new information technology due to Competitive Pressure, Top Management and Perceived Benefits while SMEs tend to do so due to the know-how in its organization. en_US dc.description.tableofcontents 第一章 緒論 11.1 研究背景 11.2 研究目的 2第二章 文獻探討 32.1 組織採用資訊科技之因素 32.2 TOE MODEL 42.3 針對IT ADOPTION 進行彙整分析之文獻 11第三章 研究架構與方法 123.1 研究架構 123.2 研究方法 123.2.1 蒐集與篩選文獻 133.2.2 資料編碼 163.2.3 資料分析 27第四章 研究結果 374.1 敘述研究法 374.2 彙整分析法 394.3 設置調節變量 45第五章 研究結論與限制 565.1 研究結論 565.2 研究貢獻 605.3 研究限制 60參考文獻 62附錄一 31篇彙整分析之文獻 66附錄二 31篇文獻之編碼資料 70附錄三 自變量來源文獻與名稱 73 zh_TW dc.format.extent 2619648 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G1053560223 en_US dc.subject (關鍵詞) 彙整分析 zh_TW dc.subject (關鍵詞) TOE模式 zh_TW dc.subject (關鍵詞) 資訊科技 zh_TW dc.subject (關鍵詞) 組織採用 zh_TW dc.subject (關鍵詞) Meta-analysis en_US dc.subject (關鍵詞) TOE model en_US dc.subject (關鍵詞) Information technology en_US dc.subject (關鍵詞) Organization adoption en_US dc.title (題名) 組織採用資訊科技之彙整分析 zh_TW dc.title (題名) Organizational Adoption of Information Technology: A Meta-Analysis en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 洪新原, 梁定澎, & 張嘉銘. (2005). 科技接受模式之彙總研究. 資訊管理學報, 12(4), 211-234.傅品甄. (2017). 組織採用資訊科技之彙整分析.Baker, J. (2012). The technology–organization–environment framework. In Information systems theory (pp. 231-245). Springer, New York, NY.Broadbent, M., Weill, P., & St. Clair, D. (1999). The implications of information technology infrastructure for business process redesign. MIS quarterly, 159-182.Buhalis, D. (1998). Strategic use of information technologies in the tourism industry. Tourism management, 19(5), 409-421.Card, N. A. (2015). Applied meta-analysis for social science research. Guilford Publications.Chong, J. L., & Olesen, K. (2017). A Technology-Organization-Environment perspective on eco-effectiveness: A Meta-analysis. Australasian Journal of Information Systems, 21.Cohen, J. (1977). Statistical power analysis for the behavioral sciences (Rev. ed.) New York: Academic. Google Scholar.Depietro, R., Wiarda, E., & Fleischer, M. (1990). The context for change: Organization, technology and environment. The processes of technological innovation, 199(0), 151-175.DerSimonian, R., & Laird, N. (1986). Meta-analysis in clinical trials. Controlled clinical trials, 7(3), 177-188.Glass, G. V., Smith, M. L., & McGaw, B. (1981). Meta-analysis in social research. Sage Publications, Incorporated.Hage, J. (1980). Theories of organizations: Form, process, and transformation. John Wiley & Sons.Hameed, M. A., Counsell, S., & Swift, S. (2012). A meta-analysis of relationships between organizational characteristics and IT innovation adoption in organizations. Information & management, 49(5), 218-232.Huang, P. Y. (2009). A Meta Analysis of Technology Adoption Intention Models.Hunter, J.E. & Schmidt, F.L. (1990). Methods of Meta Analysis, Sage Publications, Newbury Park, CA.Hunter, J.E., Schmidt, F.L. & Jackson, G.B. (1982). Meta-Analysis: Cumulating Research Findings Across Studies, Sage Publications, Beverly Hills, CA.Kelley, K., & Preacher, K. J. (2012). On effect size. Psychological methods, 17(2), 137.Khandwalla, P. (1970) Environment and the organization structure of firms, McGill University, Montreal, Faculty of Management.Lee, G., & Xia, W. (2006). Organizational size and IT innovation adoption: A meta-analysis. Information & Management, 43(8), 975-985.Ma, Q., & Liu, L. (2004). The technology acceptance model: A meta-analysis of empirical findings. Journal of Organizational and End User Computing (JOEUC), 16(1), 59-72.Nie, J. (2007, September). A study of information technology adoption for small and medium sized enterprises strategic competitiveness. In Wireless Communications, Networking and Mobile Computing, 2007. WiCom 2007. International Conference on (pp. 4342-4346). IEEE.Oliveira, T., & Martins, M. F. (2011). Literature review of information technology adoption models at firm level. The electronic journal information systems evaluation, 14(1), 110-121.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.Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. Journal of Applied Psychology, 90(1), 175.Premkumar, G., & Roberts, M. (1999). Adoption of new information technologies in rural small businesses. Omega, 27(4), 467-484.Racherla, P., & Hu, C. (2008). eCRM system adoption by hospitality organizations: A technology-organization-environment (TOE) framework. Journal of Hospitality & Leisure Marketing, 17(1-2), 30-58.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.Rosenthal, R. (1978). Combining results of independent studies. Psychological bulletin, 85(1), 185.Rosenthal, R. (1979). The file drawer problem and tolerance for null results. Psychological bulletin, 86(3), 638.Rosenthal, R. (1991). Meta-analytic procedures for social research (Vol. 6). Sage.Starbuck, W.H. (1976) Organizations and their environments, Chicago, Rand McNally.Thompson, J. D. (1967). Organizations in action: Social science bases of administration.Wang, Y. M., Wang, Y. S., & Yang, Y. F. (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological forecasting and social change, 77(5), 803-815.Wolf, F. M. (1986). Meta-analysis: Quantitative methods for research synthesis (Vol. 59). Sage.Wu, J., & Lederer, A. (2009). A meta-analysis of the role of environment-based voluntariness in information technology acceptance. Mis Quarterly, 419-432.Yeh, Y. H. (2011). Organizational Adoption of Information Technologies–An Extended Fit-Viability Model. Doctorate Dissertation. National Sun Yat-sen University. zh_TW dc.identifier.doi (DOI) 10.6814/THE.NCCU.MIS.004.2019.A05 en_US
