本研究提供幾個可能延伸之研究建議,作為後續研究學者之參考,相關研究 有待後續再做進一步的驗證與討論:
(一)、線上遊戲類型之玩家類型在使用差異性之探討
本研究所回收之樣本雖僅以網路線上遊戲玩家為主,但於內容之分析與探討 上尚未針對不同遊戲類型的線上遊戲玩家使用之差異性進行分類與探討。因此,
建議未來相關研究者,可嘗試以不同遊戲類型線上遊戲玩家作為分析之對象,並 於研究模式之構面中加入新變數如「沉迷」者與重度「沉迷」者之區別、性別上 之區分,增加研究結果之多樣性,提升研究結果之參考實用性,更具一般性與代 表性。
(二)、增加中介變數模式檢測
本研究未使用單因子中介模型檢測本研究之中介效果。因而,建議可於未來 之研究中嘗試探討單因子中介模型之相關中介效果。
(三)、檢驗共同方法變異
本研究為自陳式問卷,可能存在共同方法變異(Common method variance, CMV)之可能性。為了解決問題,因此本研究根據 Podsakoff et al.(2003)之 建議,在本研究之問卷設計過程中進行程序控制,已邀請二位相關研究領域之教 授及兩位長期熟悉之網路線上遊戲專家級玩家給予問卷修訂建議,並施行前測與 修正問卷之語意。此外,本研究並未使用檢驗共同方法變異是否顯著存在。因此,
建議未來相關研究者應用更細膩之 CMV 檢測法探討共同方法變異之存在與否。
(四)、在研究模式中再額外增加外生變數
本研究建議可在原有研究模式中加入外生變數,此舉可使得研究模式更加完 整,有利於研究模式本身的解釋力,也將會產生不同之研究結果。
90
(五)、建議增加質性研究
傅仰止(2001)認為,如僅憑藉著單一研究途徑是無法有效且深入地解釋所與 探討之議題(傅仰止, 2001)。因此,本研究建議後續之研究可再增加質性研究分 析,在研究過程中可提供更加深入客觀之剖析,可用以幫助研究者更加清楚瞭解 線上遊戲玩家之持續使用意向背後的真實影響因素,以期能為網路遊戲經營者提 供更多有益之訊息,提昇線上遊戲整體人氣、服務品質及使用者滿意度,藉此吸 引更多玩家的加入線上遊戲,期能共創雙贏局面。
91
參考文獻
Ahituv, N. (1980). A systematic approach toward assessing the value of an information system. MIS quarterly, 4(4), 61-75.
Al-Debei, M. M., Jalal, D., & Al-Lozi, E. (2013). Measuring web portals success: a respecification and validation of the DeLone and McLean information systems success model. International Journal of Business Information Systems.
Alloway, R. M. (1980). Defining success for data processing: a practical approach to strategic planning for the DP department.
Anderson, E. W., Fornell, C., & Lehmann, D. R. (1994). Customer satisfaction, market share, and profitability: findings from Sweden. The Journal of Marketing, 58(3), 53-66.
Astrachan, C. B., Patel, V. K., & Wanzenried, G. (2014). A comparative study of
CB-SEM and PLS-SEM for theory development in family firm research. Journal of Family Business Strategy, 5(1), 116-128.
doi: http://dx.doi.org/10.1016/j.jfbs.2013.12.002
Awad, N. F., & Krishnan, M. (2006). The Personalization Privacy Paradox: An Empirical Evaluation of Information Transparency and the Willingness to be Profiled Online for Personalization. MIS quarterly, 30(1), 53-66.
Badrinarayanan, V. A., Sierra, J. J., & Martin, K. M. A dual identification framework of online multiplayer video games: The case of massively multiplayer online role playing games (MMORPGs). Journal of Business Research, 68(5), 1045-1052.
doi: http://dx.doi.org/10.1016/j.jbusres.2014.10.006
Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models.
Journal of the academy of marketing science, 16(1), 74-94.
Bailey, J. E., & Pearson, S. W. (1983). Development of a tool for measuring and analyzing computer user satisfaction. Management Science, 29(5), 530-545.
Bakos, J. Y. (1987). Dependent variables for the study of firm and industry-level impacts of information technology.
Baraka, I. A., Baraka, I. A., & El-Gamily, I. I. (2013). Assessing call centers’ success:
A validation of the DeLone and Mclean model for information system.
Egyptian Informatics Journal, 14(2), 99-108.
doi: http://dx.doi.org/10.1016/j.eij.2013.03.001
Barnett, J., & Coulson, M. (2010). Virtually real: A psychological perspective on massively multiplayer online games. Review of General Psychology, 14(2), 167.
Bentler, P. M. (1992). On the fit of models to covariances and methodology to the<
92
em> Bulletin.</em>. Psychological bulletin, 112(3), 400.
Bharati, P., & Chaudhury, A. (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems, 37(2), 187-197.
Bhattacherjee, A. (2001). Understanding information systems continuance: an expectation-confirmation model. MIS quarterly, 25(3), 351-370.
Bhattacherjee, A., Perols, J., & Sanford, C. (2008). Information technology
continuance: A theoretical extension and empirical test. Journal of Computer Information Systems, 49(1), 17-26.
Billieux, J., Thorens, G., Khazaal, Y., Zullino, D., Achab, S., & Van der Linden, M. (2015).
Problematic involvement in online games: A cluster analytic approach.
Computers in Human Behavior, 43(0), 242-250.
doi: http://dx.doi.org/10.1016/j.chb.2014.10.055
Bollen, K. A. (1990). Overall fit in covariance structure models: Two types of sample size effects. Psychological bulletin, 107(2), 256.
Bossen, C., Jensen, L. G., & Udsen, F. W. (2013). Evaluation of a comprehensive EIR based on the DeLone and McLean model for IS success: Approach, results, and success factors. International journal of medical informatics, 82(10), 940-953.
Brown, T. A. (2003). Confirmatory factor analysis of the Penn State Worry
Questionnaire: Multiple factors or method effects? Behaviour Research and Therapy, 41(12), 1411-1426.
Browne, M. W., Cudeck, R., & Bollen, K. A. (1993). Alternative ways of assessing model fit. Sage Focus Editions, 154, 136-136.
Campbell, J. P. (1976). Psychometric theory. Handbook of industrial and organizational psychology, 185, 222.
Carlson, M., & Mulaik, S. A. (1993). Trait ratings from descriptions of behavior as mediated by components of meaning. Multivariate Behavioral Research, 28(1), 111-159.
Cerullo, M. J. (1980). INFORMATION-SYSTEMS SUCCESS FACTORS. Journal of Systems Management, 31(12), 10-19.
Chang, C.-C. (2012). Examining users’ intention to continue using social network games: A flow experience perspective. Telematics and Informatics.
Chang, C.-C. (2013). Examining users′ intention to continue using social network games: A flow experience perspective. Telematics and Informatics, 30(4), 311-321.
Chang, I.-C., Liu, C.-F., & Iwang, I.-G. (2011). Exploring nursing e-learning systems success based on information system success model. Computers Informatics
93
Nursing, 29(12), 741-747.
Chang, T.-S., Ku, C.-Y., & Fu, I.-P. (2013). Grey theory analysis of online population and online game industry revenue in Taiwan. Technological Forecasting and Social Change, 80(1), 175-185.
doi: http://dx.doi.org/10.1016/j.techfore.2012.06.009
Chatterjee, S., Chakraborty, S., Sarker, S., Sarker, S., & Lau, F. Y. (2009). Examining the success factors for mobile work in healthcare: A deductive study. Decision Support Systems, 46(3), 620-633.
doi: http://dx.doi.org/10.1016/j.dss.2008.11.003
Chen, C.-h. (2011). The Effect of Flow Experience, Perceived Usefulness, Perceived Ease of Use and Perceived Playfulness on Online Game Players' Continuance Intention.
Chen, C.-W. D., & Cheng, C.-Y. J. (2009). Understanding consumer intention in online shopping: a respecification and validation of the DeLone and McLean model.
Behaviour & Information Technology, 28(4), 335-345.
Chen, F., Curran, P. J., Bollen, K. A., Kirby, J., & Paxton, P. (2008). An empirical
evaluation of the use of fixed cutoff points in RMSEA test statistic in structural equation models. Sociological Methods & Research, 36(4), 462-494.
Chen, P., & El Zarki, M. (2011). Perceptual view inconsistency: an objective evaluation framework for online game quality of experience (QoE). Paper presented at the Proceedings of the 10th Annual Workshop on Network and Systems Support for Games.
Chen, S.-C., Yen, D. C., & Iwang, M. I. (2012). Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. Computers in Human Behavior, 28(3), 933-941. doi: http://dx.doi.org/10.1016/j.chb.2011.12.014 Chena, R., & Sharma, S. K. (2013). Understanding Member Use of Social Networking
Sites from a Risk Perspective. Procedia Technology, 9, 331-339.
doi: http://dx.doi.org/10.1016/j.protcy.2013.12.037
Chenoweth, T., Minch, R., & Gattiker, T. (2009). Application of protection motivation theory to adoption of protective technologies. Paper presented at the System Sciences, 2009. IICSS'09. 42nd Iawaii International Conference on.
Chervany, N. L., Dickson, G. W., & Kozar, K. A. (1972). An experimental gaming framework for investigating the influence of management information systems on decision effectiveness: Management Information Systems Research Center, Graduate School of Business Administration, University of Minnesota.
Chinomona, R. (2013). Mobile Gaming Perceived Enjoyment and Ease of Play as Predictors of Student Attitude and Mobile Gaming Continuance Intention.
94
Mediterranean Journal of Social Sciences, 4(14), 237.
Chismar, W. G., & Kriebel, C. I. (1985). A method for assessing the economic impact of information systems technology on organizations. Paper presented at the Proceedings of the Sixth International Conference on Information Systems.
Chiu, C.-M., Cheng, I.-L., Iuang, I.-Y., & Chen, C.-F. (2013). Exploring individuals’
subjective well-being and loyalty towards social network sites from the perspective of network externalities: The Facebook case. International Journal of Information Management, 33(3), 539-552.
Chiu, C.-M., Isu, M.-I., & Wang, E. T. (2006a). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888.
Chiu, C.-M., Isu, M.-I., & Wang, E. T. G. (2006b). Understanding knowledge sharing in virtual communities: An integration of social capital and social cognitive theories. Decision Support Systems, 42(3), 1872-1888.
doi: http://dx.doi.org/10.1016/j.dss.2006.04.001
Chiu, C.-M., Wang, E. T., Shih, F.-J., & Fan, Y.-W. (2011). Understanding knowledge sharing in virtual communities: an integration of expectancy disconfirmation and justice theories. Online Information Review, 35(1), 134-153.
Choi, D., & Kim, J. (2004). Why people continue to play online games: In search of critical design factors to increase customer loyalty to online contents.
CyberPsychology & behavior, 7(1), 11-24.
Clemons, E. K., & Kimbrough, S. O. (1986). Information systems, telecommunications, and their effects on industrial organization: Reginald I. Jones Center,
Wharton School, University of Pennsylvania.
Costikyan, G. (1994). I have no words and I must design. Interactive Fantasy# 2.
British roleplaying journal.
Couger, J. D., & Wergin, L. M. (1974). Systems management: small company MIS.
Infosystems, 21(10), 30-33.
Crossler, R. E. (2010). Protection motivation theory: Understanding determinants to backing up personal data. Paper presented at the System Sciences (IICSS), 2010 43rd Iawaii International Conference on.
Culnan, M. J. (1983). Chauffeured versus end user access to commerical databases:
The effects of task and individual differences. MIS quarterly, 7(1), 55-67.
Danziger, J. N. (1979). Technology and Productivity A Contingency Analysis of Computers in Local Government. Administration & Society, 11(2), 144-171.
Debatin, B., Lovejoy, J. P., Iorn, A. K., & Iughes, B. N. (2009). Facebook and online privacy: Attitudes, behaviors, and unintended consequences. Journal of Computer‐Mediated Communication, 15(1), 83-108.
95
DeLone, W. I. (1988). Determinants of success for computer usage in small business.
MIS quarterly, 12(1), 51-61.
Delone, W. I. (2003). The DeLone and McLean model of information systems success:
a ten-year update. Journal of management information systems, 19(4), 9-30.
DeLone, W. I., & McLean, E. R. (1992). Information systems success: the quest for the dependent variable. Information Systems Research, 3(1), 60-95.
DeLone, W. I., & McLean, E. R. (2002). Information systems success revisited. Paper presented at the System Sciences, 2002. IICSS. Proceedings of the 35th Annual Iawaii International Conference on.
Delone, W. I., & Mclean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of Electronic Commerce, 9(1), 31-47.
DeVellis, R. (1991). Scale development. Applications and theory: Newbury Park, CA:
Sage.
DeVellis, R. F. (2011). Scale development: Theory and applications (Vol. 26): Sage.
Doll, W. J., & Torkzadeh, G. (1988). The measurement of end-user computing satisfaction. MIS quarterly, 259-274.
Domahidi, E., Festl, R., & Quandt, T. (2014). To dwell among gamers: Investigating the relationship between social online game use and gaming-related friendships.
Computers in Human Behavior, 35(0), 107-115.
doi: http://dx.doi.org/10.1016/j.chb.2014.02.023
Domahidi, E., Scharkow, M., & Quandt, T. (2012). Real friends and virtual life?
Computer games as foci of activity for social community building.
Dong, T.-P., Cheng, N.-C., & Wu, Y.-C. J. (2014). A study of the social networking website service in digital content industries: The Facebook case in Taiwan.
Computers in Human Behavior, 30, 708-714.
Dwyer, C., Iiltz, S., & Passerini, K. (2007). Trust and privacy concern within social networking sites: A comparison of Facebook and MySpace. AMCIS 2007 Proceedings, 339.
Ein-Dor, P., & Segev, E. (1978). Organizational context and the success of
management information systems. Management Science, 24(10), 1064-1077.
Elliot, S., Li, G., & Choi, C. (2013). Understanding service quality in a virtual travel community environment. Journal of Business Research, 66(8), 1153-1160.
Ellison, N. B., Steinfield, C., & Lampe, C. (2007). The benefits of Facebook “friends:”
Social capital and college students’ use of online social network sites. Journal of Computer‐Mediated Communication, 12(4), 1143-1168.
Emery, J. C. (1971). Cost/benefit analysis of information systems: Society for Management Information Systems.
96
Eom, S. (2013). Testing the Seddon Model of Information System Success in an E-Learning Context: Implications for Evaluating DSS Decision Support Systems II‐Recent Developments Applied to DSS Network Environments (pp. 19-33):
Springer.
Ferguson, R. L., & Jones, C. I. (1969). A computer aided decision system.
Management Science, 15(10), B-550-B-561.
Floropoulos, J., Spathis, C., Ialvatzis, D., & Tsipouridou, M. (2010). Measuring the success of the Greek taxation information system. International Journal of Information Management, 30(1), 47-56.
Fogel, J., & Nehmad, E. (2009). Internet social network communities: Risk taking, trust, and privacy concerns. Computers in Human Behavior, 25(1), 153-160.
Freeze, R. D., Alshare, K. A., Lane, P. L., & Joseph Wen, I. (2010). IS success model in e-learning context based on students' perceptions. Journal of Information Systems Education, 21(2), 173.
Fuerst, W. L., & Cheney, P. I. (1982). Concepts, Theory, and Techniques: FACTORS AFFECTING TIE PERCEIVED UTILIZATION OF COMPUTER-BASED DECISION SUPPORT SYSTEMS IN TIE OIL INDUSTRY. Decision Sciences, 13(4), 554-569.
Gallagher, C. A. (1974). Perceptions of the value of a management information system. Academy of Management Journal, 17(1), 46-55.
Garrity, J. T. (1963). Top management and computer profits. Harvard Business Review, 41(4), 6-12.
Geer, D. (2003). Risk management is still where the money is. Computer, 36(12), 129-131.
Ginzberg, M. J. (1978a). Behavioral Science-Finding an Adequate Measure of OR/MS Effectiveness. Interfaces, 8(4), 59-62.
Ginzberg, M. J. (1978b). Finding an Adequate Measure of OR/MS Effectiveness.
Interfaces, 8(4), 59-62.
Ginzberg, M. J. (1981). Early diagnosis of MIS implementation failure: promising results and unanswered questions. Management Science, 27(4), 459-478.
Gremillion, L. L. (1984). Organization size and information system use: An empirical study. Journal of management information systems, 1(2), 4-17.
Iair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate analysis.
Englewood: Prentice Hall International.
Iair, J. F., Anderson, R. E., Tatham, R. L., & William, C. (1998). Black (1998), Multivariate data analysis: Upper Saddle River, NJ: Prentice Iall.
Iamilton, S., & Chervany, N. L. (1981). Evaluating information system
effectiveness-Part I: Comparing evaluation approaches. MIS quarterly, 5(3), 55-69.
97
Iertz, D. B. (1968). Unlocking The Computer's Profit Potential. McKinsey and Company, New York, 38.
Iilton, R. W., & Swieringa, R. J. (1982). DECISION FLEXIBILITY AND PERCEIVED INFORMATION VALUE*. Decision Sciences, 13(3), 357-379.
Iinton, D. E., Nickerson, A., & Bryant, R. A. (2011). Worry, worry attacks, and PTSD among Cambodian refugees: A path analysis investigation. Social science &
medicine, 72(11), 1817-1825.
Io, S.-I., & Iuang, C.-I. (2009). Exploring success factors of video game
communities in hierarchical linear modeling: The perspectives of members and leaders. Computers in Human Behavior, 25(3), 761-769.
doi: http://dx.doi.org/10.1016/j.chb.2009.02.004
Iong, S., You, S., Kim, E., & No, U. (2014). A group-based modeling approach to estimating longitudinal trajectories of Korean adolescents’ on-line game time.
Personality and Individual Differences, 59(0), 9-15.
doi: http://dx.doi.org/10.1016/j.paid.2013.10.018
Isiao, C.-C., & Chiou, J.-S. (2012a). The effects of a player’s network centrality on resource accessibility, game enjoyment, and continuance intention: A study on online gaming communities. Electronic Commerce Research and
Applications, 11(1), 75-84.
Isiao, C.-C., & Chiou, J.-S. (2012b). The impact of online community position on online game continuance intention: Do game knowledge and community size matter? Information & Management, 49(6), 292-300.
doi: http://dx.doi.org/10.1016/j.im.2012.09.002
Isu, C.-L., & Lu, I.-P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information & Management, 41(7), 853-868.
Iu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6(1), 1-55.
Iuang, L.-Y., Isieh, Y.-J., & Wu, Y.-C. J. (2014). Gratifications and social network service usage: The mediating role of online experience. Information &
Management, 51(6), 774-782.
doi: http://dx.doi.org/10.1016/j.im.2014.05.004
Iuysmans, J. I. (1970). implementation of operations research.
Igersheim, R. I. (1976). Managerial response to an information system. Paper presented at the Proceedings of the June 7-10, 1976, national computer conference and exposition.
Ives, B., Olson, M. I., & Baroudi, J. J. (1983). The measurement of user information
98
satisfaction. Communications of the ACM, 26(10), 785-793.
Jöreskog, K. G., & Sörbom, D. (1996). LISREL 8: User's reference guide: Scientific Software International.
Jackson, D. L., Gillaspy Jr, J. A., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: an overview and some recommendations.
Psychological methods, 14(1), 6.
Jansz, J. (2005). The emotional appeal of violent video games for adolescent males.
Communication Theory, 15(3), 219-241.
Jen, W.-Y., & Chao, C.-C. (2008). Measuring mobile patient safety information system success: an empirical study. International journal of medical informatics, 77(10), 689-697.
Johnston, I. R., & Vitale, M. R. (1988). Creating competitive advantage with interorganizational information systems. MIS quarterly, 12(2), 153-165.
Joinson, A. N., Reips, U.-D., Buchanan, T., & Schofield, C. B. P. (2010). Privacy, trust, and self-disclosure online. Human–Computer Interaction, 25(1), 1-24.
Kim, E., & Lee, J. (1986). An exploratory contingency model of user participation and MIS use. Information & Management, 11(2), 87-97.
Kim, E. J., Namkoong, K., Ku, T., & Kim, S. J. (2008). The relationship between online game addiction and aggression, self-control and narcissistic personality traits.
European Psychiatry, 23(3), 212-218.
Kim, Y.-Y., Kim, M.-I., & Oh, S. (2014). Emerging factors affecting the continuance of online gaming: the roles of bridging and bonding social factors. Cluster Computing, 17(3), 849-859.
King, W. R., & Epstein, B. J. (1983). Assessing information system value: An experimental study. Decision Sciences, 14(1), 34-45.
King, W. R., & Rodriguez, J. I. (1978). Evaluating management information systems.
MIS quarterly, 2(3), 43-51.
King, W. R., & Rodriguez, J. I. (1981). Note—Participative Design of Strategic Decision Support Systems: An Empirical Assessment. Management Science, 27(6), 717-726.
Koo, D.-M. (2009). The moderating role of locus of control on the links between experiential motives and intention to play online games. Computers in Human Behavior, 25(2), 466-474.
Kriebei, C. I., & Raviv, A. (1980). An economics approach to modeling the
productivity of computer systems. Management Science, 26(3), 297-311.
Kriebel, C. A., & Raviv, A. (1982). APPLICATION OF A PRODUCTIVITY MODEL FOR COMPUTER SYSTEMS*. Decision Sciences, 13(2), 266-284.
Ku, C.-Y., Sung, P.-C., & Isieh, W.-I. (2014). Policy satisfaction for separation of
99
dispensing from medical practices in Taiwan: Success of the
prescription-release information system. Telematics and Informatics, 31(2), 334-343.
Kulkarni, U. R., Ravindran, S., & Freeze, R. (2007). A knowledge management success model: theoretical development and empirical validation. Journal of
management information systems, 23(3), 309-347.
Lai, J.-Y., & Yang, C.-C. (2009). Effects of employees' perceived dependability on success of enterprise applications in e-business. Industrial Marketing Management, 38(3), 263-274.
Larcker, D. F., & Lessig, V. P. (1980). Perceived Usefulness of Information: A Psychometric Examination*. Decision Sciences, 11(1), 121-134.
Lascu, D.-N., & Zinkhan, G. (1999). Consumer conformity: review and applications for marketing theory and practice. Journal of Marketing Theory and Practice, 7(3), 1-12.
Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and
satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with computers, 21(5), 385-392.
Lee, M.-C. (2009). Understanding the behavioural intention to play online games: an extension of the theory of planned behaviour. Online Information Review, 33(5), 849-872.
Lee, M.-C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation–confirmation model. Computers
& Education, 54(2), 506-516.
Lee, S.-Y., Poon, W.-Y., & Bentler, P. (1990). A three-stage estimation procedure for structural equation models with polytomous variables. Psychometrika, 55(1), 45-51.
Lee, S.-Y. T., Kim, I.-W., & Gupta, S. (2009). Measuring open source software success.
Omega, 37(2), 426-438.
Lee, S., & Quan, C. f. (2013). Factors affecting Chinese Ubiquitous Game Service usage intention. International Journal of Mobile Communications, 11(2), 194-212.
Lee, S. Y. (2015). Interpersonal influence on online game choices. Computers in Human Behavior, 45(0), 129-136.
doi: http://dx.doi.org/10.1016/j.chb.2014.11.086
doi: http://dx.doi.org/10.1016/j.chb.2014.11.086