進階搜尋


   電子論文尚未授權公開,紙本請查館藏目錄
(※如查詢不到或館藏狀況顯示「閉架不公開」,表示該本論文不在書庫,無法取用。)
系統識別號 U0026-0409201815070400
論文名稱(中文) 以沉浸理論觀點探討使用者對運動型手機遊戲的持續使用意願
論文名稱(英文) Examining Users’ Continuance Usage Intention of Sports Mobile Game: A Flow Theory Perspective
校院名稱 成功大學
系所名稱(中) 電信管理研究所
系所名稱(英) Institute of Telecommunications and Management
學年度 106
學期 2
出版年 107
研究生(中文) 李柏霆
研究生(英文) Bo-Ting Li
學號 R96041057
學位類別 碩士
語文別 英文
論文頁數 74頁
口試委員 指導教授-廖俊雄
口試委員-林珮珺
口試委員-呂錦山
口試委員-汪志堅
口試委員-楊忠山
中文關鍵字 手機遊戲  沉浸理論  享樂價值  功利價值  持續使用意願 
英文關鍵字 Flow theory  hedonic value  utilitarian value  continuance usage intention  mobile game  structural equation modeling 
學科別分類
中文摘要 隨著智慧型手機的普及以及行動網路的發展,人們可以隨時隨地使用網路與世界各個地方連結,根據國際電信聯盟的統計,全世界大約有接近一半的人口使用過行動上網,許多新興的產品和服務也伴隨日漸普及的智慧型手機和行動上網而來,而成長幅度最為巨大的產業當屬手機遊戲,無論是在通勤時間、午休時間都能看到人們在玩手機遊戲,這種手機使用習慣的轉變也給遊戲營運商帶來巨大的商機,而使用者的持續使用意願更是影響手機遊戲營運商收入最重要的因素之一。
本次研究透過沉浸理論、消費者價值來探討使用者的技巧與遊戲的挑戰性如何帶來沉浸經驗,而沉浸經驗又是如何帶來享樂價值與功利價值,進而提高他們的持續使用意願。本研究問卷透過網路張貼於BBS 與Reddit,最終蒐集的樣本數為403 份,分析流程依序為單因子變異數分析、探索性因素分析、驗證性因素分析與結構方程模型。研究的結果顯示使用者的技巧與遊戲的挑戰性與進入沉浸狀態有顯著的正向關係,沉浸狀態會正向影響享樂價值、功利價值,而享樂價值與功利價值會正向影響使用者的持續使用意願。透過中介效果分析發現沉浸狀態也會直接影響使用者的持續使用意願。研究結果顯示如果遊戲能夠讓玩家技巧與遇到的挑戰互相平衡則可讓使用者更快進入沉浸,且這種醉心於遊戲帶來的愉快與完成目標的成就感會提高使用者的持續使用意願。一個能夠留住使用者的遊戲必須要讓技巧與遊戲挑戰性互相平衡,如果使用者技巧太高而挑戰性太低會讓遊戲顯得無趣,相反的,技巧太低而挑戰性太高會讓使用者感到焦慮。本研究的結果可提供給遊戲開發商做為如何提高使用者的持續使用意願之參考。
英文摘要 Universal internet connections and advanced smartphones have made mobile games widely accepted by the public. People enjoy sports mobile game during commuting, lunch breaks, or leisure time, and they provide huge business opportunities for game operators. In particular, continuance usage intention is one of the most influential factors for revenue drivers. The aim of this study is, based on flow theory and consumer value, to understand how users immerse in sports mobile game and continue playing them. The constructs of skill, challenge, and flow are considered as flow experiences, and the constructs of perceived hedonic value and perceived utilitarian value are considered as consumer value. In the theoretical framework, the levels of the constructs are measured, and the causal relationships among flow experiences, consumer value, and sports mobile game continuance usage intention are investigated. Further, the mediating roles of perceived hedonic value and perceived utilitarian value on the linkage of flow to continuance usage intention are examined. Questionnaires are posted to sports mobile game forums on the Bulletin Board System and Reddit from March 2018 to April 2018, and a total of 403 effective responses are collected. A descriptive statistics analysis is conducted to understand the demographics of the respondents, game usage experience, and the characteristics of each variable. The ANOVA results reveal that there are significant differences in characteristics among the three study groups: light users, moderate users, and heavy users. Exploratory factor analysis (EFA) indicates that six factors in this model are extracted with eigenvalues of 1.0 or greater and that the total cumulative variance is 64.059%. In the confirmatory factor analysis (CFA), the criteria for measurement model fit, chi-square/df (2.027), GFI (0.892), AGFI (0.867), CFI (0.931), and RMSEA (0.051) demonstrate good model fit with the data. The structural equation modeling (SEM) analysis reveals that all the paths are found to be significant, with t-values higher than 1.96, indicating that user ability and the difficulty level of NBA 2K18 both have a positive effect on flow; flow is positively related to perceived hedonic value, perceived
utilitarian value, and sports mobile game continuance usage intention, and perceived hedonic value and perceived utilitarian value are positively related to sports mobile
game continuance usage intention. In addition, both perceived hedonic value and perceived utilitarian value are found to partially mediate flow and sports mobile game
continuance usage intention. Finally, practical strategies drawn from the results are provided for mobile game operators when developing new games.
論文目次 Table of Contents
Table of Contents ..........................................................................................................i
List of Tables.................................................................................................................ii
List of Figures............................................................................................................. iii
Chapter One Introduction...........................................................................................1
1.1 Background and Motivation ............................................................................1
1.2 Research Objectives.........................................................................................4
Chapter Two Theoretical Background.......................................................................5
2.1 Flow Theory.....................................................................................................5
2.2 Consumer Value ...............................................................................................7
Chapter Three Hypothesis Development .................................................................10
3.1 Skill and Challenge ........................................................................................10
3.2 Flow ...............................................................................................................11
3.3 Perceived Hedonic Value and Perceived Utilitarian Value ............................14
3.4 Sports Mobile Game Continuance Usage Intention.......................................16
Chapter Four Research Model and Design .............................................................21
4.1 Research Model .............................................................................................21
4.2 Measurement Development ...........................................................................21
4.3 Data Collection and Sampling .......................................................................25
4.4 Analysis Method ............................................................................................25
Chapter Five Empirical Results ...............................................................................30
5.1 Descriptive Statistics Analysis.......................................................................30
5.2 Exploratory Factor Analysis ..........................................................................36
5.3 Confirmatory Factor Analysis........................................................................40
5.4 Structural Equation Modeling........................................................................43
Chapter Six Conclusion and Discussion ..................................................................51
6.1 Summary of the Results .................................................................................51
6.2 Managerial Implication..................................................................................52
6.3 Limitations and Future Research ...................................................................53
References ...................................................................................................................55
Appendix A: Items in Questionnaire........................................................................69
Appendix B: Items in Chinese Questionnaire .........................................................71
參考文獻 Agarwal, R., & Karahanna, E. (2000). Time flies when you’re having fun: Cognitive
absorption and beliefs about information technology usage. MIS Quarterly,
24(4), 665-694.
Al-Maghrabi, T., & Dennis, C. (2011). What drives consumers’ continuance intention
to e-shopping? Conceptual framework and managerial implications in the case
of Saudi Arabia. International Journal of Retail & Distribution
Management, 39(12), 899-926.
Al-Maghrabi, T., Dennis, C., & Vaux Halliday, S. (2011). Antecedents of continuance
intentions towards e-shopping: The case of Saudi Arabia. Journal of Enterprise
Information Management, 24(1), 85-111.
Android Police (2016). Pokémon GO Passes 100 Million Play Store Downloads in Just
a Month. Retrieved from https:// www. androidpolice. Com / 2016 /08 /
08/%20pokmon-go-passes-100-million-play-store-downloads-just-month
Babin, B. J., Lee, Y. K., Kim, E. J., & Griffin, M. (2005). Modeling consumer
satisfaction and word-of-mouth: Restaurant patronage in Korea. Journal of
Services Marketing, 19(3), 133-139.
Babin, B., Darden, W., & Griffin, M. (1994). Work and/or Fun: Measuring hedonic and
utilitarian shopping value. Journal of Consumer Research, 20(4), 644-656.
Bacon, D. R., Sauer, P. L., & Young, M. (1995). Composite reliability in structural
equations modeling. Educational and Psychological Measurement, 55(3), 394-
406.
Barnes, S. J. (2011). Understanding use continuance in virtual worlds: Empirical test of
a research model. Information & Management, 48(8), 313-319.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic, and statistical
considerations. Journal of Personality and Social Psychology, 51(6), 1173-
1179.
Barrett, P. (2007). Structural equation modelling: Adjudging model fit. Personality and
Individual Differences, 42(5), 815-824.
Bearden, W. O., Sharma, S., & Teel, J. E. (1982). Sample size effects on Chi Square
and other statistics used in evaluating causal models. Journal of Marketing
Research, 19(4), 425-430.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological
Bulletin, 107(2), 238-246.
Bhattacherjee, A. (2001). Understanding information systems continuance: An
56
expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
Blanchard, R. F., & Galloway, R. L. (1994). Quality in retail banking. International
Journal of Service Industry Management, 5(4), 5-23.
Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: John
Wiley & Sons.
Broadband Commission for Sustainable Development (2017). The State of Broadband:
Broadband Catalyzing Sustainable Development. Retrieved from
https://www.itu.int/dms_pub/itu-s/opb/pol/S-POL-BROADBAND.18-2017-
PDF-E.pdf
Calvo-Porral, C., Faíña-Medín, A., & Nieto-Mengotti, M. (2017). Exploring
technology satisfaction: An approach through the flow experience. Computers
in Human Behavior, 66(1), 400-408.
Carpenter, J. M., & Fairhurst, A. (2005). Consumer shopping value, satisfaction, and
loyalty for retail apparel brands. Journal of Fashion Marketing and
Management: An International Journal, 9(3), 256-269.
Cazalla, O., Sebastián, E., Cultrone, G., Nechar, M., & Bagur, M. G. (1999). Threeway
ANOVA interaction analysis and ultrasonic testing to evaluate air lime
mortars used in cultural heritage conservation projects. Cement and Concrete
Research, 29(11), 1749-1752.
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. C., & Chen, K. (2014). The effects of hedonic/utilitarian
expectations and social influence on continuance intention to play online
games. Internet Research, 24(1), 21-45.
Chang, K. C. (2014). Examining the effect of tour guide performance, tourist trust,
tourist satisfaction, and flow experience on tourists’ shopping behavior. Asia
Pacific Journal of Tourism Research, 19(2), 219-247.
Chang, Y. P., & Zhu, D. H. (2012). The role of perceived social capital and flow
experience in building users’ continuance intention to social networking sites in
China. Computers in Human Behavior, 28(3), 995-1001
Chen, S. C., Chen, H. H., & Chen, M. F. (2009). Determinants of satisfaction and
continuance intention towards self-service technologies. Industrial
Management & Data Systems, 109(9), 1248-1263.
Chiu, C. M., Chiu, C. S., & Chang, H. C. (2007). Examining the integrated influence
of fairness and quality on learners’ satisfaction and Web‐based learning
continuance intention. Information Systems Journal, 17(3), 271-287.
57
Chiu, C. M., Hsu, M. H., Sun, S. Y., Lin, T. C., & Sun, P. C. (2005). Usability, quality,
value and e-learning continuance decisions. Computers & Education, 45(4),
399-416.
Chiu, C. M., & Wang, E. T. (2008). Understanding Web-based learning continuance
intention: The role of subjective task value. Information & Management, 45(3),
194-201.
Chiu, C. M., Wang, E. T., Fang, Y. H., & Huang, H. Y. (2014). Understanding
customers’ repeat purchase intentions in B2C e‐commerce: The roles of
utilitarian value, hedonic value and perceived risk. Information Systems
Journal, 24(1), 85-114.
Choi, Y., Pae, A., Park, E. J., & Wright, R. F. (2010). The effect of surface treatment
of fiber-reinforced posts on adhesion of a resin-based luting agent. The Journal
of Prosthetic Dentistry, 103(6), 362-368.
Chuang, Y. H., Lin, C. S., & Shu, W. (2011). Continuance of Social Network Services
Games. International Journal of Global Management Studies, 3(1), 1-16.
Costello, A. B., & Osborne, J. W. (2005). Best practices in exploratory factor analysis:
Four recommendations for getting the most from your analysis. Practical
Assessment, Research & Evaluation, 10(7), 1-9.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests.
Psychometrika, 16(3), 297-334.
Cronin, J. J., Brady, M. K., & Hult, G. T. M. (2000). Assessing the effects of quality,
value, and customer satisfaction on consumer behavioral intentions in service
environments. Journal of Retailing, 76(2), 193-218.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco, CA: Jossey
& Bass.
Csikszentmihalyi, M. (1997). Happiness and creativity: Going with the flow. The
Futurist, 31(5), 8-12.
Custodero, L. A. (2002). Seeking challenge, finding skill: Flow experience and music
education. Arts Education Policy Review, 103(3), 3-9.
Dağhan, G., & Akkoyunlu, B. (2016). Modeling the continuance usage intention of
online learning environments. Computers in Human Behavior, 60(1), 198-211.
Davis, S., & Wiedenbeck, S. (2001). The mediating effects of intrinsic motivation, ease
of use and usefulness perceptions on performance in first-time and subsequent
computer users. Interacting with Computers, 13(5), 549-580.
De Croon, E. M., Sluiter, J. K., Blonk, R. W., Broersen, J. P., & Frings-Dresen, M. H.
(2004). Stressful work, psychological job strain, and turnover: A 2-year
prospective cohort study of truck drivers. Journal of Applied Psychology, 89(3),
58
442-453
Deng, L., Turner, D. E., Gehling, R., & Prince, B. (2010). User experience, satisfaction,
and continual usage intention of IT. European Journal of Information
Systems, 19(1), 60-75.
Detienne, K. B., Agle, B. R., Phillips, J. C., & Ingerson, M. C. (2012). The impact of
moral stress compared to other stressors on employee fatigue, job satisfaction,
and turnover: An empirical investigation. Journal of Business Ethics, 110(3),
377-391.
Dickson, P. R., & Sawyer, A. G. (1990). The price knowledge and search of
supermarket shoppers. The Journal of Marketing, 54(3), 42-53.
Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store
information on buyers’ product evaluations. Journal of Marketing Research,
28(3), 307-319.
Dubrovski, D. (2001). The role of customer satisfaction in achieving business
excellence. Total Quality Management, 12(7), 920-925.
Fabrigar, L. R., Wegener, D. T., MacCallum, R. C., & Strahan, E. J. (1999). Evaluating
the use of exploratory factor analysis in psychological research. Psychological
Methods, 4(3), 272-284.
Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods,
and model specification on structural equation modeling fit indexes. Structural
Equation Modeling: A Multidisciplinary Journal, 6(1), 56-83.
Fiore, A. M., Jin, H. J., & Kim, J. (2005). For fun and profit: Hedonic value from image
interactivity and responses toward an online store. Psychology & Marketing,
22(8), 669-694.
Ford, J. K., MacCallum, R. C., & Tait, M. (1986). The application of exploratory factor
analysis in applied psychology: A critical review and analysis. Personnel
Psychology, 39(2), 291-314.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with
unobservable variables and measurement error. Journal of Marketing Research,
18(1), 39-50.
Fullagar, C. J., Knight, P. A., & Sovern, H. S. (2013). Challenge/skill balance, flow,
and performance anxiety. Applied Psychology, 62(2), 236-259.
Gagne, P., & Hancock, G. R. (2006). Measurement model quality, sample size, and
solution propriety in confirmatory factor models. Multivariate Behavioral
Research, 41(1), 65-83.
Gallarza, M. G., & Saura, I. G. (2006). Value dimensions, perceived value, satisfaction
and loyalty: An investigation of university students’ travel behaviour. Tourism
59
Management, 27(3), 437-452.
Gamespot (2016). Pokémon Go Reaches $600 Million, Faster than Any Mobile Game
in History. Retrieved from https://www.gamespot.com/articles/pokemon-goreaches-
600-million-faster-than-any-mob/1100-6444687/
Gao, L., & Bai, X. (2014). An empirical study on continuance intention of mobile social
networking services: Integrating the IS success model, network externalities and
flow theory. Asia Pacific Journal of Marketing and Logistics, 26(2), 168-189.
Gartner (2017). Gartner Says Worldwide PC Shipments Declined 4.3 Percent in Second
Quarter of 2017. Retrieved from https://www.gartner.com/%20newsroom
/id/3759964
Gartner (2017). Gartner Says Worldwide Sales of Smartphones Grew 9 Percent in First
Quarter of 2017. Retrieved from https://www.gartner.com/%20newsro
om/id/3725117
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph:
Tutorial and annotated example. Communications of the Association for
Information ystems, 16(1), 91-109.
Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and
regression: Guidelines for research practice. Communications of the Association
for Information Systems, 4(7), 152-167.
Ghani, J. A., Supnick, R., & Rooney, P. (1991). The Experience of Flow in Computermediated
and in face-to-face Groups. Information Systems, 91(3), 229-237.
Ghani, J. A., & Deshpande, S. P. (1994). Task characteristics and the experience of
optimal flow in human-computer interaction. Journal of Psychology, 128(4),
381-391.
Gogin, G. (2006). Cell phone culture. London, England: Routledge.
Gruen, T. W., Osmonbekov, T., & Czaplewski, A. J. (2006). eWOM: The impact of
customer-to-customer online know-how exchange on customer value and
loyalty. Journal of Business Research, 59(4), 449-456.
Grüsser, S. M., Thalemann, R., & Griffiths, M. D. (2006). Excessive computer game
playing: Evidence for addiction and aggression?. CyberPsychology &
Behavior, 10(2), 290-292.
Guo, Z., Xiao, L., Chanyoung, S., & Lai, Y. (2012). Flow experience and continuance
intention toward online learning: An integrated framework. IS Curriculum &
Education, 13(4)1-21.
Guo, Y. M., & Poole, M. S. (2009). Antecedents of flow in online shopping: A test of
alternative models. Information Systems Journal, 19(4), 369-390.
Gursoy, D., Spangenberg, E. R., & Rutherford, D. G. (2006). The hedonic and
60
utilitarian dimensions of attendees’ attitudes toward festivals. Journal of
Hospitality & Tourism Research, 30(3), 279-294.
Hair, J. F., Jr, Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data
analysis (7th ed.). London, England: Pearson.
Hamari, J., Shernoff, D. J., Rowe, E., Coller, B., Asbell-Clarke, J., & Edwards, T.
(2016). Challenging games help students learn: An empirical study on
engagement, flow and immersion in game-based learning. Computers in Human
Behavior, 54(1), 170-179.
Hancock, G. R., & Freeman, M. J. (2001). Power and sample size for the root mean
square error of approximation test of not close fit in structural equation
modeling. Educational and Psychological Measurement, 61(5), 741-758.
Hayashi, A., Chen, C., Ryan, T., & Wu, J. (2004). The role of social presence and
moderating role of computer self-efficacy in predicting the continuance usage
of e-learning systems. Journal of Information Systems Education, 15(2), 139-
154.
Heskett, J. L., Sasser, W. E., & Hart, C. W. L. (1990). Breakthrough service. New York,
NY: Mcgraw Hill.
Hoffman, D. L., & Novak, T. P. (1996). Marketing in hypermedia computer-mediated
environments: Conceptual Foundations. Journal of Marketing, 60(3), 50-68.
Holbrook, M. B. (2002). Consumer value: a framework for analysis and research (2nd
ed.). London, England: Routledge.
Hong, F. Y., Chiu, S. I., & Huang, D. H. (2012). A model of the relationship between
psychological characteristics, mobile phone addiction and use of mobile phones
by Taiwanese university female students. Computers in Human Behavior, 28(6),
2152-2159.
Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling:
Guidelines for determining model fit. Electronic Journal of Buisness Research
Methods, 6(1), 53-60.
Hsiao, C. H., Chang, J. J., & Tang, K. Y. (2016). Exploring the influential factors in
continuance usage of mobile social Apps: Satisfaction, habit, and customer
value perspectives. Telematics and Informatics, 33(2), 342-355.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM
with social influences and flow experience. Information & Management, 41(7),
853-868.
Hu, 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.
61
Huang, H. C., Huang, L. S., Chou, Y. J., & Teng, C. I. (2017). Influence of temperament
and character on online gamer loyalty: Perspectives from personality and flow
theories. Computers in Human Behavior, 70(1), 398-406.
Huang, M. H. (2003). Designing website attributes to induce experiential
encounters. Computers in Human Behavior, 19(4), 425-442.
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.
Hume, M., & Sullivan Mort, G. (2010). The consequence of appraisal emotion, service
quality, perceived value and customer satisfaction on repurchase intent in the
performing arts. Journal of Services Marketing, 24(2), 170-182.
Ilsever, J., Cyr, D., & Parent, M. (2007). Extending models of flow and eloyalty.
Journal of Information Science and Technology, 4(2), 3-22.
International Telecommunication Union (2017). ICT Facts and Figures. Retrieved
from https://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFacts
Figures2017.pdf
Internet World Stats (2017). Internet Usage Statistics. Retrieved from: http://www.
internetworldstats.com/stats.htm
Jackson, S. A., Ford, S. K., Kimiecik, J. C., & Marsh, H. W. (1998). Psychological
correlates of flow in sport. Journal of Sport and Exercise Psychology, 20(4),
358-378.
Jin, S. A. A. (2012). “Toward integrative models of flow”: Effects of performance, skill,
challenge, playfulness, and presence on flow in video games. Journal of
Broadcasting & Electronic Media, 56(2), 169-186.
Jöreskog, K. G., & Sörbom, D. (1984). LISREL VI: Analysis of linear structural
relationships: By the method of maximum likelihood. Chicago, IL: National
Educational Resources.
Kaiser, H. F. (1960). The application of electronic computers to factor analysis.
Educational and Psychological Measurement, 20(1), 141-151.
Khang, H., Kim, J. K., & Kim, Y. (2013). Self-traits and motivations as antecedents of
digital media flow and addiction: The Internet, mobile phones, and video
games. Computers in Human Behavior, 29(6), 2416-2424.
Kim, B. (2010). An empirical investigation of mobile data service continuance:
Incorporating the theory of planned behavior into the expectation-confirmation
model. Expert Systems with Applications, 37(10), 7033-7039.
Kim, C., Galliers, R. D., Shin, N., Ryoo, J. H., & Kim, J. (2012). Factors influencing
Internet shopping value and customer repurchase intention. Electronic
Commerce Research and Applications, 11(4), 374-387.
62
Kim, H. J. (2008). Common factor analysis versus principal component analysis:
Choice for symptom cluster research. Asian Nursing Research, 2(1), 17-24.
Kim, H. W., Chan, H. C., & Chan, Y. P. (2007). A balanced thinking-feelings model of
information systems continuance. International Journal of Human Computer
Studies, 65(6), 511-525.
Kim, H., & Niehm, L. S. (2009). The impact of website quality on information quality,
value, and loyalty intentions in apparel retailing. Journal of Interactive
Marketing, 23(3), 221-233.
Kim, Y. H., Kim, D. J., & Wachter, K. (2013). A study of mobile user engagement
(MoEN): Engagement motivations, perceived value, satisfaction, and continued
engagement intention. Decision Support Systems, 56(1), 361-370.
Koufaris, M., Kambil, A., & LaBarbera, P. A. (2001). Consumer behavior in web-based
commerce: An empirical study. International Journal of Electronic
Commerce, 6(2), 115-138.
Krejcie, R. V., & Morgan, D. W. (1970). Determining sample size for research activities.
Educational and Psychological Measurement, 30(1), 607-610.
Larsen, T. J., Sørebø, A. M., & Sørebø, Ø . (2009). The role of task-technology fit as
users’ motivation to continue information system use. Computers in Human
Behavior, 25(3), 778-784.
Lee, C. H., & Wu, J. J. (2017). Consumer online flow experience: The relationship
between utilitarian and hedonic value, satisfaction and unplanned
purchase. Industrial Management & Data Systems, 117(10), 2452-2467.
Lee, K. C., Kang, I., & McKnight, D. H. (2007). Transfer from offline trust to key
online perceptions: An empirical study. IEEE Transactions on Engineering
Management, 54(4), 729-741.
Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward elearning:
An extension of the expectation–confirmation model. Computers &
Education, 54(2), 506-516.
Lessiter, J., Freeman, J., Keogh, E., & Davidoff, J. (2001). A cross-media presence
questionnaire: The ITC-Sense of Presence Inventory. Presence: Teleoperators
& Virtual Environments, 10(3), 282-297.
Liao, C., Palvia, P., & Lin, H. N. (2006). The roles of habit and web site quality in ecommerce.
International Journal of Information Management, 26(6), 469-483.
Lim, T. S., & Loh, W. Y. (1996). A comparison of tests of equality of variances.
Computational Statistics & Data Analysis, 22(3), 287-301.
63
Limayem, M., & Cheung, C. M. (2008). Understanding information systems
continuance: The case of Internet-based learning technologies. Information &
Management, 45(4), 227-232.
Limayem, M., Hirt, S. G., & 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, C. S., Wu, S., & Tsai, R. J. (2005). Integrating perceived playfulness into
expectation-confirmation model for web portal context. Information &
Management, 42(5), 683-693.
Lin, T. C., Wu, S., Hsu, J. S. C., & Chou, Y. C. (2012). The integration of value-based
adoption and expectation–confirmation models: An example of IPTV
continuance intention. Decision Support Systems, 54(1), 63-75.
Lin, W. S. (2012). Perceived fit and satisfaction on web learning performance: IS
continuance intention and task-technology fit perspectives. International
Journal of Human Computer Studies, 70(7), 498-507.
Mallat, N., Rossi, M., Tuunainen, V. K., & Ö örni, A. (2009). The impact of use context
on mobile services acceptance: The case of mobile ticketing. Information &
Management, 46(3), 190-195.
Mathwick, C., & Rigdon, E. (2004). Play, Flow, and the Online Search
Experience. Journal of Consumer Research, 31(2), 324-332.
Marlatt, G. A., Baer, J. S., Donovan, D. M., & Kivlahan, D. R. (1988). Addictive
behaviors: Etiology and treatment. Annual Review of Psychology, 39(1), 223-
252.
Maytum, J. C., Heiman, M. B., & Garwick, A. W. (2004). Compassion fatigue and
burnout in nurses who work with children with chronic conditions and their
families. Journal of Pediatric Health Care, 18(4), 171-179
Merikivi, J., Tuunainen, V., & Nguyen, D. (2017). What makes continued mobile
gaming enjoyable? Computers in Human Behavior, 68(1), 411-421.
Mouakket, S. (2015). Factors influencing continuance intention to use social network
sites: The Facebook case. Computers in Human Behavior, 53(1),102-110.
Naidoo, R., & Leonard, A. (2007). Perceived usefulness, service quality and loyalty
incentives: Effects on electronic service continuance. South African Journal of
Business Management, 38(3), 39-48.
Newzoo (2017). The Global Games Market Will Reach $108.9 Billion in 2017 with
Mobile Taking 42%. Retrieved from https://newzoo.com/insights/articles
/%20the-global-games-market-will-reach-108-9-billion-in-2017-with-mobiletaking-
42/
64
Nordam, A., Torjuul, K., & Sørlie, V. (2005). Ethical challenges in the care of older
people and risk of being burned out among male nurses. Journal of Clinical
Nursing, 14(10), 1248-1256.
Novak, T. P., Hoffman, D. L., & Duhachek, A. (2003). The influence of goal-directed
and experiential activities on online flow experiences. Journal of Consumer
Psychology, 13(1), 3-16.
Novak, T., Hoffman, D., & Yung, Y. (2000). Measuring the Customer Experience in
Online Environments: A Structural Modeling Approach. Marketing
Science, 19(1), 22-42.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw Hill.
Oghuma, A. P., Libaque-Saenz, C. F., Wong, S. F., & Chang, Y. (2016). An
expectation-confirmation model of continuance intention to use mobile instant
messaging. Telematics and Informatics, 33(1), 34-47.
Overby, J. W., & Lee, E. J. (2006). The effects of utilitarian and hedonic online
shopping value on consumer preference and intentions. Journal of Business
Research, 59(10), 1160-1166.
Ozturk, A. B., Nusair, K., Okumus, F., & Hua, N. (2016). The role of utilitarian and
hedonic values on users’ continued usage intention in a mobile hotel booking
environment. International Journal of Hospitality Management, 57(1), 106-115.
Pace, S. (2004). A grounded theory of the flow experiences of Web users. International
Journal of Human Computer Studies, 60(3), 327-363.
Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-valueloyalty
chain: A research agenda. Journal of the Academy of Marketing Science,
28(1), 168-174.
Patterson, P. G., & Spreng, R. A. (1997). Modelling the relationship between perceived
value, satisfaction and repurchase intentions in a business-to-business, services
context: An empirical examination. International Journal of Service Industry
Management, 8(5), 414-434.
Perry, S. D., & Lee, K. C. (2007). Mobile phone text messaging overuse among
developing world university students. Communicatio, 33(2), 63-79.
Roca, J. C., Chiu, C. M., & Martínez, F. J. (2006). Understanding e-learning
continuance intention: An extension of the Technology Acceptance
Model. International Journal of Human Computer Studies, 64(8), 683-696.
Ruxton, G. D., & Beauchamp, G. (2008). Time for some a priori thinking about post
hoc testing. Behavioral Ecology, 19(3), 690-693.
Ryu, K., Han, H., & Jang, S. (2010). Relationships among hedonic and utilitarian values,
satisfaction and behavioral intentions in the fast-casual restaurant industry.
65
International Journal of Contemporary Hospitality Management, 22(3), 416-
432.
Salanova, M., Bakker, A. B., & Llorens, S. (2006). Flow at work: Evidence for an
upward spiral of personal and organizational resources. Journal of Happiness
Studies, 7(1), 1-22.
Satorra, A., & Bentler, P. M. (2001). A scaled difference chi-square test statistic for
moment structure analysis. Psychometrika, 66(4), 507-514.
Sensor Tower (2016). Pokémon GO Passes $160 Million Worldwide Revenue, Usage
Remains Strong. Retrieved from https://sensortower.com/blog/%20pokemongo-
160-million-dollars-usage-still-strong
Sensor Tower (2106). Pokémon GO Revenue Skyrockets to More Than $440 Million
Since Release. Retrieved from https://sensortower.com/blog/pokemon% 20-go-
160-million-dollars-usage-still-strong
Seyal, A. H., Rahman, M. N. A., & Rahim, M. M. (2002). Determinants of academic
use of the Internet: A structural equation model. Behaviour & Information
Technology, 21(1), 71-86.
Sharma, S. (1996). Applied multivariate techniques (1st ed.). New York, NY: John
Wiley & Sons.
Sherry, J. L. (2004). Flow and media enjoyment. Communication Theory, 14(4), 328-
347.
Shevlin, M., & Miles, J. N. (1998). Effects of sample size, model specification and
factor loadings on the GFI in confirmatory factor analysis. Personality and
Individual Differences, 25(1), 85-90.
Shiau, W. L., Huang, L. C., & Shih, C. H. (2011). Understanding continuance intention
of blog users: A perspective of flow and expectation confirmation theory.
Journal of Convergence Information Technology, 6(4), 306-317.
Shim, S. I., Forsythe, S., & Kwon, W. S. (2015). Impact of online flow on brand
experience and loyalty. Journal of Electronic Commerce Research, 16(1), 56-
71.
Shin, N. (2006). Online learner’s “flow” experience: An empirical study. British
Journal of Educational Technology, 37(5), 705-720.
Skadberg, Y. X., & Kimmel, J. R. (2004). Visitors’ flow experience while browsing a
Web site: Its measurement, contributing factors and consequences. Computers
in Human Behavior, 20(3), 403-422.
Sørebø, Ø ., Halvari, H., Gulli, V. F., & Kristiansen, R. (2009). The role of selfdetermination
theory in explaining teachers’ motivation to continue to use elearning
technology. Computers & Education, 53(4), 1177-1187.
66
Statista (2016). Number of Newly Developed Applications/Games Submitted for
Release to the iTunes App Store from 2012 to 2016. Retrieved from
https://www.statista.com/statistics/258160/number-of-new-apps-submitted-tothe-
itunes-store-per-month/
Statista (2017). Leading iPhone Gaming App Titles Worldwide in September 2017, by
Number of Downloads. Retrieved from https:// www. statista. com/%
20statistics/697688/leading-iphone-mobile-games-global-downloads/
Statista (2017). Number of Active Mobile Broadband Subscriptions Worldwide from
2007 to 2017. Retrieved from https://www.statista.com/%20statistics
/273016/number-of-mobile-broadband-subscriptions-worldwide-since-2007/
Statista (2017). Smartphone Shipments by Vendor Worldwide from 4th Quarter 2009 to
2nd Quarter 2017. Retrieved from https://www.statista.com/statistics/
271490/quarterly-global-smartphone-shipments-by-vendor/
Stone, R. W., & Baker-Eveleth, L. (2013). Students’ expectation, confirmation, and
continuance intention to use electronic textbooks. Computers in Human
Behavior, 29(3), 984-990.
Su, Y. S., Chiang, W. L., Lee, C. T. J., & Chang, H. C. (2016). The effect of flow
experience on player loyalty in mobile game application. Computers in Human
Behavior, 63(1), 240-248.
Sung, K., Seo, Y., & Kim, J. H. (2012). Relationships between compassion fatigue,
burnout, and turnover intention in Korean hospital nurses. Journal of Korean
Academy of Nursing, 42(7), 1087-1094.
Teng, C. I., & Huang, H. C. (2012). More than flow: Revisiting the theory of four
channels of flow. International Journal of Computer Games Technology, 20(4),
1-9.
Thompson, B. (2004). Exploratory and confirmatory factor analysis: Understanding
concepts and applications (1st ed.). Washington, WA: American Psychological
Association.
Thompson, B. M., Kirk, A., & Brown, D. F. (2005). Work based support, emotional
exhaustion, and spillover of work stress to the family environment: A study of
policewomen. Stress and Health, 21(3), 199-207.
Thong, J. Y., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on
the expectation-confirmation model for information technology
continuance. International Journal of Human Computer Studies, 64(9), 799-
810.
Tinsley, H. E., & Tinsley, D. J. (1987). Uses of factor analysis in counseling psychology
research. Journal of Counseling Psychology, 34(4), 414-427.
67
USA Today (2016). Pokémon Go Beating Facebook, Tinder and Snapchat. Retrieved
from https://www.usatoday.com/story/tech/gaming/2016/07/12/chart-moretime-
spent-pokmon-go-than-instagram-snapchat/86982096/
USA Today (2016). Pokémon Go Fastest Mobile Game to 10M Downloads. Retrieved
from https://www.usatoday.com/story/tech/gaming/2016/07/20/pokemon-gofastest-
mobile-game-10m-downloads/87338366/
Venkatesh, V., & Davis, F. D. (2000). Theoretical extension of the technology
acceptance model: Four longitudinal field studies. Management Science, 46(2),
186-204.
Venture Beat (2017). Mobile Game Revenue Grew 53% to $11.9 Billion in Q1 2017.
Retrieved from https://venturebeat.com/2017/04/13/worldwide-mobile-
%20game-revenue-grew-53-to-11-9-billion-in-q1/
Venture Beat (2017). Pokémon Go Passes $1.2 Billion in Revenue and 752 Million
Downloads. Retrieved from https://venturebeat.com/2017/06/30/pokemon-
%20go-passes-1-2-billion-in-revenue-and-752-million-downloads/
Watson, D., Clark, L. A., Weber, K., Assenheimer, J. S., Strauss, M. E., & McCormick,
R. A. (1995). Testing a tripartite model: Exploring the symptom structure of
anxiety and depression in student, adult, and patient samples. Journal of
Abnormal Psychology, 104(1), 15-25.
Wu, J. J., & Chang, Y. S. (2005). Towards understanding members’ interactivity, trust,
and flow in online travel community. Industrial Management & Data
Systems, 105(7), 937-954.
Wu, Z., Ann, T. W., & Shen, L. (2017). Investigating the determinants of contractor’s
construction and demolition waste management behavior in Mainland China.
Waste Management, 60(1), 290-300.
Yang, K., & Lee, H. J. (2010). Gender differences in using mobile data services:
Utilitarian and hedonic value approaches. Journal of Research in Interactive
Marketing, 4(2), 142-156.
Yang, S., Lu, Y., Wang, B., & Zhao, L. (2014). The benefits and dangers of flow
experience in high school students’ internet usage: The role of parental
support. Computers in Human Behavior, 41(1), 504-513.
Yao, X., Phang, C. W., & Ling, H. (2015). Understanding the influences of trend and
fatigue in individuals’ SNS switching intention. System Sciences, 48(6), 324-
334.
Young, K. S. (1998). Internet addiction: The emergence of a new clinical
disorder. Cyberpsychology & Behavior, 1(3), 237-244.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means68
end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22.
Zhang, K., Min, Q., Liu, Z., & Liu, Z. (2016). Understanding microblog continuance
usage intention: An integrated model. Aslib Journal of Information Management,
68(6), 772-792.
Zhao, L., Lu, Y., Zhang, L., & Chau, P. Y. (2012). Assessing the effects of service
quality and justice on customer satisfaction and the continuance intention of
mobile value-added services: An empirical test of a multidimensional
model. Decision Support Systems, 52(3), 645-656.
Zhou, T. (2013a). An empirical examination of continuance intention of mobile
payment services. Decision Support Systems, 54(2), 1085-1091.
Zhou, T. (2013b). The effect of flow experience on user adoption of mobile
TV. Behaviour & Information Technology, 32(3), 263-272.
Zhou, T. (2014). Understanding the determinants of mobile payment continuance
usage. Industrial Management & Data Systems, 114(6), 936-948.
Zhou, T., & Li, H. (2014). Understanding mobile SNS continuance usage in China from
the perspectives of social influence and privacy concern. Computers in Human
Behavior, 37(1), 283-289.
Zhou, T., & Lu, Y. (2011). Examining mobile instant messaging user loyalty from the
perspectives of network externalities and flow experience. Computers in Human
Behavior, 27(2), 883-889.
Zhou, T., Li, H., & Liu, Y. (2010). The effect of flow experience on mobile SNS users’
loyalty. Industrial Management & Data Systems, 110(6), 930-946.
論文全文使用權限
  • 同意授權校內瀏覽/列印電子全文服務,於2023-09-05起公開。
  • 同意授權校外瀏覽/列印電子全文服務,於2023-09-05起公開。


  • 如您有疑問,請聯絡圖書館
    聯絡電話:(06)2757575#65773
    聯絡E-mail:etds@email.ncku.edu.tw