什麼因素讓使用者參與並推廣專業虛擬社群

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：95

、訪客IP：18.118.184.102

姓名

陳映璇(Ying-Hsuan Chen) 查詢紙本館藏

畢業系所

資訊管理學系

論文名稱

什麼因素讓使用者參與並推廣專業虛擬社群
(What Factors Keep Users Participating in and Promoting a Professional Virtual Community)

相關論文

★ 影響ERP導入過程及成效因素之研究 - 單一公司兩次導入SAP系統之比較分析	★ 運用資料倉儲技術建置物力動員資訊系統之開發
★ 買方採用自有電子市集之個案研究─以台塑企業為例	★ DEA模型評估經營效率之研究—以某綜合證券商為例
★ 尋求卓越：中小企業資訊部門的管理之個案研究	★ 「證券商共同網路交易平台」之可行性分析
★ 產業競合模式策略探討－以自行車產業為例	★ RFID導入航空貨運站出口作業流程應用之研究
★ 綠色供應鏈活動建構之個案研究-以筆記型電腦製造業為例	★ 導入資訊科技服務管理之評估-以遠東銀行為例
★ 資訊系統導入歷程中專案團隊決策衝突之探討	★ 應用資源基礎理論探討持久競爭優勢-以智慧型手機H公司為例
★ 服務導向架構為基礎的企業流程管理之探討 - 以瀚宇博德股份有限公司為例	★ 沙賓法案實施與企業遵循個案研究--以K公司為例
★ 資訊服務委外之個案分析－以銀行簡訊為例	★ 有線電視業者經營IPTV之競爭優勢分析—以個案公司為例

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 ( 永不開放)

摘要(中)

近年，越來越多人樂於參與在專業虛擬社群中。然而，社群中缺乏回饋機制是非常難促使使用者投資他們寶貴的時間和成本。要創造成功的社群，有兩項非常重要的因素。其中一項，是什麼樣的因素吸引使用者投入並持續地參與在社群中。另外一項因素則是，什麼樣的原因使他們想要推廣社群。本研究專注於探討哪些內外部誘因使個人感到滿意並願意持續參與社群中的開源專案。本研究模型主要在探討，提高名聲、互惠規範以及技術知識的因素影響參與者的滿意度，和滿意度對持續參與意圖及社群推廣的影響。透過本研究的研究方法是線上問卷的收集與分析來驗證本研究的實徵模型，本研究選擇兩種方式收集樣本來源。一種是從GitHub網站。另一種則是由台灣人所組成並參與在Facebook的技術議題討論群組中的成員。本研究總共收集116份樣本並使用SmartPLS做資料分析。研究結果顯示，互惠規範、技術知識品質、技術知識使用會正向影響滿意度，且滿意度會正向影響持續意圖及社群推廣。

摘要(英)

In recent years, more and more people enjoy participating in a professional virtual community (PVC). However, without any compensation is hard to facilitate individuals to invest their treasure time and effort in the PVC. The benefits are the key point to motivate individuals’ participation intention but not forced. To make a successful community, it is important to aim at two factors. One factor is that what incentives attract individuals to engage and continue participating in the PVC. The other is that what factors make them promote the PVC. This study focused on intrinsic, extrinsic and technical knowledge incentives, which effect individuals’ satisfaction and continuance intention participating in open source projects of the PVC. The model discussed reputation enhancement, norm of reciprocity and technical knowledge factors to effect participants’ satisfaction, and satisfaction effects the continuance intention and community promotion. The hypotheses of this model were empirically validated by using an online survey. We chose two sources to collect our sample. One is “GitHub” (https://github.com/). The other source is groups on Facebook that discuss technical issues and consists of Taiwanese. This research collects empirical data of the 116 respondents in total and analyzes the data with SmartPLS. The result shows that norm of reciprocity, technical knowledge quality and technical knowledge utilization have positive impact on satisfaction, and satisfaction is positively associated with continuance intention and community promotion.

關鍵字(中)

★ 專業虛擬社群
★ 滿意度
★ 持續意圖
★ 技術知識品質
★ 技術知識使用

關鍵字(英)

★ professional virtual community
★ satisfaction
★ continuance intention
★ technical knowledge quality
★ technical knowledge utilization

論文目次

中文摘要 i
Abstract ii
致謝 iii
Contents iv
List of Tables vi
List of Figures vii
Chapter 1 Introduction 1
1.1 Research Background and Motivation 1
1.2 Research Objectives and Questions 3
Chapter 2 Literature Review 4
2.1 Professional Virtual Communities 4
2.2 Knowledge Sharing and Influence Factors 5
2.3 Continued Participation in Professional Virtual Communities 6
Chapter 3 Research Model and Hypotheses 8
3.1 Research Model 8
3.2 Reputation Enhancement 10
3.3 Norm of Reciprocity 11
3.4 Technical Knowledge Quality 12
3.5 Technical Knowledge Utilization 13
3.6 Knowledge-sharing Activity 14
3.6.1 Continuance Intention 14
3.6.2 Community Promotion 15
Chapter 4 Research Methodology 16
4.1 Sample Selection and Data Collection 16
4.2 Measurement 17
4.2.1 Reputation Enhancement 17
4.2.2 Norm of Reciprocity 18
4.2.3 Technical Knowledge Quality 19
4.2.4 Technical Knowledge Utilization 19
4.2.5 Satisfaction 20
4.2.6 Continuance Intention 21
4.2.7 Community Promotion 22
Chapter 5 Data Analysis and Results 23
5.1 Sample Characteristics 24
5.2 Measurement Model 27
5.2.1 Item Reliability 27
5.2.2 Convergent Validity 28
5.2.3 Discriminant Validity 28
5.3 Structural Model 32
Chapter 6 Conclusion 35
6.1 Findings and Discussion 35
6.1.1 Effect of Reputation Enhancement on Satisfaction 35
6.1.2 Effect of Norm of Reciprocity on Satisfaction 36
6.1.3 Effect of Technical Knowledge Factors on Satisfaction 36
6.1.4 Effect of Technical Knowledge Quality on Technical Knowledge Utilization 37
6.1.5 Effect of Satisfaction on Continuance Intention 37
6.1.6 Effect of Satisfaction on Community Promotion 37
6.2 Implications 38
6.3 Limitations 40
Reference 41
Appendix 46
Questionnaire A 46
Questionnaire B 51

參考文獻

Ajzen, I., and Fishbein, M. (1980). Understanding attitudes and predicting social behavior. New Jersey: Prentice-Hall.
Ba, S., Stallaert, J., and Whinston, A. B. (2001). Research commentary: Introducing a third dimension in information systems design—The case for incentive alignment. Information Systems Research, 12(3), 225-239.
Bagozzi, R. P., and Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74-94.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
Blau, P. M. (1964). Exchange and power in social life. New York: Wiley.
Bock, G. W., Sabherwal, R., and Qian, Z. (2008). The effect of social context on the success of knowledge repository systems. IEEE Transactions on Engineering Management, 55(4), 536-551.
Casaló, L. V., FlaviáN, C., and GuinalíU, M. (2010). Relationship quality, community promotion and brand loyalty in virtual communities: Evidence from free software communities. International Journal of Information Management, 30(4), 357-367.
Chang, A. M., Kannan, P. K., and Whinston, A. B. (1999). Electronic communities as intermediaries: The issues and economics. in Proceedings of the 32ndHawaii International Conference on System Sciences, R. Sprague Jr. (ed.), Washington, DC: IEEE Computer Society Press.
Chang, H. H., and Chuang, S. S. (2011). Social capital and individual motivations on knowledge sharing: Participant involvement as a moderator. Information & Management, 48(1), 9-18.
Chen, C. J., and Hung, S. W. (2010). To give or to receive? Factors influencing members’ knowledge sharing and community promotion in professional virtual communities. Information & Management, 47(4), 226-236.
Chen, I. Y. (2007). The factors influencing members′ continuance intentions in professional virtual communities—A longitudinal study. Journal of Information Science, 33(4), 451-467.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern Methods for Business Research, 295(2), 295-336.
Chin, W. W., Marcolin, B. L., and 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), 189-217.
Chiu, C. M., Hsu, M. H., and Wang, E. T. (2006). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888.
Collier, J. E., and Bienstock, C. C. (2006). Measuring service quality in e-retailing. Journal of Service Research, 8(3), 260-275.
Connolly, T., and Thorn, B. K. (1990). Discretionary databases: Theory, data, and implications. in Organizations and Communication technology, J. Fulk and C. Steinfield (Eds.), Newbury Park, CA: Sage Publications, 219-233.
Constant, D., Sproull, L., and Kiesler, S. (1996). The kindness of strangers: The usefulness of electronic weak ties for technical advice. Organization Science, 7(2), 119-135.
Fang, Y. H., Chiu, C. M., and Wang, E. T. (2011). Understanding customers′ satisfaction and repurchase intentions: An integration of IS success model, trust, and justice. Internet Research, 21(4), 479-503.
Fernback, J., and Thompson, B. (1995). Computer-mediated communication and the American collectivity: The dimensions of community within cyberspace. Annual Convention of the International Communication Association, Albuquerque, New Mexico.
Fornell, C., and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3), 382-388.
Goodhue, D., Lewis, W., and Thompson, R. (2006). PLS, small sample size, and statistical power in MIS research. in Proceedings of the 39th Hawaii International Conference on System Sciences, R. Sprague Jr. (ed.), Los Alamitos, CA: IEEE Computer Society Press.
Goodman, P. S., and Darr, E. D. (1998). Computer-aided systems and communities: Mechanisms for organizational learning in distributed environments. MIS Quarterly, 22(4), 417-440.
Gray, P. H. (2001). The impact of knowledge repositories on power and control in the workplace. Information Technology & People, 14(4), 368-384.
Hair, J. F., Sarstedt, M., Ringle, C. M., and 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.

He, W., and Wei, K. K. (2009). What drives continued knowledge sharing? An investigation of knowledge-contribution and -seeking beliefs. Decision Support Systems, 46(4), 826-838.
Hsu, M. H., Chiu, C. M., and Ju, T. L. (2004). Determinants of continued use of the WWW: An integration of two theoretical models. Industrial Management & Data Systems, 104(9), 766-775.
Hsu, M. H., Ju, T. L., Yen, C. H., and Chang, C. M. (2007). Knowledge sharing behavior in virtual communities: The relationship between trust, self-efficacy, and outcome expectations. International Journal of Human-Computer Studies, 65(2), 153-169.
Jin, S. A. A. (2013). Peeling back the multiple layers of Twitter’s private disclosure onion: The roles of virtual identity discrepancy and personality traits in communication privacy management on Twitter. New Media and Society, 15(6), 813-833.
Jin, X. L., Zhou, Z., Lee, M. K., and Cheung, C. M. (2013). Why users keep answering questions in online question answering communities: A theoretical and empirical investigation. International Journal of Information Management, 33(1), 93-104.
Kankanhalli, A., Tan, B. C., and Wei, K. K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. MIS Quarterly, 29(1), 113-143.
Kollock, P. (1999). The economies of online cooperation: Gifts, and public goods in Cyberspace. in Communities in Cyberspace, M. A. Smith and P. Kollock (Eds.), Routledge, New York, 220-239.
Lakhani, K. R., and Von Hippel, E. (2003). How open source software works: “Free” user-to-user assistance. Research Policy, 32(6), 923-943.
Limayem, M., Hirt, S. G., and Cheung, C. M. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.
Lin, H. F. (2008). Determinants of successful virtual communities: Contributions from system characteristics and social factors. Information & Management, 45(8), 522-527.
Lin, H. F. (2007). Effects of extrinsic and intrinsic motivation on employee knowledge sharing intentions. Journal of Information Science, 33(2), 135-149.
Lin, M. J. J., Hung, S. W., and Chen, C. J. (2009). Fostering the determinants of knowledge sharing in professional virtual communities. Computers in Human Behavior, 25(4), 929-939.
Lu, Y., and Yang, D. (2011). Information exchange in virtual communities under extreme disaster conditions. Decision Support Systems, 50(2), 529-538.
Marett, K., and Joshi, K. D. (2009). The decision to share information and rumors: Examining the role of motivation in an online discussion forum. Communications of the Association for Information Systems, 24(1), 47-68.
McKinney, V., Yoon, K., and Zahedi, F. M. (2002). The measurement of web-customer satisfaction: An expectation and disconfirmation approach. Information Systems Research, 13(3), 296-315.
Molm, L. D. (1997). Coercive power in social exchange. New York: Cambridge University Press.
Rheingold, H. (2000). The virtual community: Homesteading on the electronic frontier. MA: MIT Press.
Songini, M.L. (2003). SAP pushes to increase use of its middleware, Computerworld, 37(36), 10.
Teo, H. H., Chan, H. C., Wei, K. K., and Zhang, Z. (2003). Evaluating information accessibility and community adaptivity features for sustaining virtual learning communities. International Journal of Human-Computer Studies, 59(5), 671-697.
Thibaut, J. W., and Kelley, H. H. (1959). The social psychology of groups. New York: John Wiley.
Tiwana, A., and Bush, A. A. (2005). Continuance in expertise-sharing networks: A social perspective. IEEE Transactions on Engineering Management, 52(1), 85-101.
Tseng, F. C., and Kuo, F. Y. (2010). The way we share and learn: An exploratory study of the self-regulatory mechanisms in the professional online learning community. Computers in Human Behavior, 26(5), 1043-1053.
Wachter, R. M., Gupta, J. N., and Quaddus, M. A. (2000). IT takes a village: Virtual communities in support of education. International Journal of Information Management, 20(6), 473-489.
Wasko, M. M., and Faraj, S. (2000). “It is what one does”: Why people participate and help others in electronic communities of practice. The Journal of Strategic Information Systems, 9(2), 155-173.
Wasko, M. M., and Faraj, S. (2005). Why should I share? Examining social capital and knowledge contribution in electronic networks of practice. MIS Quarterly, 29(1), 35-57.
Wenger, E. (1998). Communities of practice: Learning, meaning, and identity. New York: Cambridge university press.
Werts, C. E., Linn, R. L., and Jöreskog, K. G. (1974). Intraclass reliability estimates: Testing structural assumptions. Educational and Psychological Measurement, 34(1), 25-33.

指導教授

王存國

審核日期

2017-7-10

推文