臺灣博碩士論文加值系統

近年來，遊戲化吸引行動裝置應用程式產業的矚目，遊戲化應用程式也如雨後春筍般在App Store和Google Play湧現。另外，學術界也不乏有關於遊戲化的研究，但卻鮮有研究探討遊戲化習慣養成行動應用程式與使用者行為意圖之間的相關性。我們整合科技受模型（Technology Acceptance Model；TAM）與心流理論（Flow Theory），利用新模型調查使用者對於遊戲化習慣養成行動裝置應用程式的使用意願，並且探索影響其持續使用或甚倡導應用程式的因素。透過問卷調查，我們蒐集來自不同背景的使用者對於此類應用程式的使用認知與使用經驗，共201份有效問卷。並利用偏最小平方法（PLS）進行迴歸分析，檢測內在動機，系統易用性，外在動機和行為意圖等之構面之間的關聯。經分析後確認模型內所有路徑都具顯著性。此外，群組分析的結果也呈現差異存在於不同性別間、不同習慣養成類型抑或不同持續使用時間。綜觀來說，遊戲化習慣養成行動應用程式中的系統優使性、外在動機以及內部動機正向影響使用者使用此類應用程式的行為意圖。

Gamification has been a focus of the mobile app industry in recent years. Researchers have also jumped on the bandwagon; however, few studies have ever been carried out to inspect the correlation between gamification and the users’ behavioral intention in the habit-formation context. With an integrated model of the Technology Acceptance Model and the Flow Theory, the objective of this study is to investigate people’s willingness to use a gamified habit-formation app and identify the factors which influence their decision to be a retainer or an advocator of the app. Through a questionnaire survey, we collect users' perceptions and experience of using such apps with a total of 201 valid samples collected. Regression analysis is conducted through Partial Least Squares (PLS) method, to measure the correlation between the dimensions of internal motivation, system ease of use, external motivation, and behavioral intention. All paths of the research model are significant. Moreover, multi-group analyses show the differences between female and male; among the genres of apps used; or among different duration of using apps. Generally, system ease of use, external motivation, and internal motivation brought by gamification may positively influence users’ behavioral intention of using habit-formation apps.

TABLE OF CONTENTS
指導教授推薦書
口試委員審定書
Acknowledgment iii
中文摘要 iv
Abstract v
TABLE OF CONTENTS vi
LIST OF TABLES ix
LIST OF FIGURES x
CHAPTER 1 INTRODUCTION - 1 -
1.1 Research Background and Motivation - 1 -
1.2 Research Objectives - 5 -
1.3 Research Process - 6 -
CHAPTER 2 LITERATURE REVIEW - 8 -
2.1 Gamification - 8 -
2.1.1 Concept of Gamification - 8 -
2.1.2 Game Design and Gamification Elements - 9 -
2.2 Technology Acceptance Model - 15 -
2.2.1 Origin: Theory of Reasoned Action (TRA) - 15 -
2.2.2 Introduction to Technology Acceptance Model (TAM) - 16 -
2.2.3 Application of TAM - 20 -
2.2.4 Perceived Enjoyment as External Variable in TAM - 21 -
2.3 Perceived Playfulness in Flow Theory - 22 -
2.3.1 Flow Theory - 22 -
2.3.2 Perceived Playfulness in Flow Experience - 24 -
2.4 Habit Formation - 25 -
CHAPTER 3 RESEARCH METHODOLOGY - 27 -
3.1 Research Model - 27 -
3.2 Research Hypotheses - 28 -
3.2.1 Perceived Enjoyment as Internal Motivation - 28 -
3.2.2 Perceived Ease of Use, Perceived Playfulness, and Behavioral Intention to Use in TAM…. - 29 -
3.2.3 Perceived Playfulness in Flow and Users’ Behavioral Intention - 30 -
3.3 Survey and Sampling - 30 -
3.3.1 Operational Definitions of Research Variables - 30 -
3.3.2 Questionnaire Design - 31 -
3.3.3 Sampling and Survey Deployment - 34 -
3.4 Data Analysis Method - 35 -
3.4.1 Analysis and Tools - 35 -
3.4.2 Pilot Test Result of Questionnaire and Amendment - 36 -
CHAPTER 4 RESULTS AND FINDINGS - 39 -
4.1 Descriptive Statistical Analyses - 39 -
4.1.1 Demographics - 39 -
4.1.2 Descriptive Statistics for Variable Dimensions - 42 -
4.2 Reliability and Validity Analyses - 45 -
4.2.1 Reliability Measurement - 45 -
4.2.2 Research Validity Measurement - 46 -
4.3 Research Hypotheses and SEM Examination - 47 -
4.4 Multi-Group Analyses - 50 -
4.4.1 Gender - 50 -
4.4.2 Genres of Apps Used - 52 -
4.4.3 Duration of Using App - 53 -
4.4.4 Description of Answering Situation for Open Question - 54 -
CHAPTER 5 DISCUSSION - 57 -
5.1 Habit-Formation Apps as IS - 57 -
5.2 Gamified Effect on Habit-Form Apps - 57 -
5.3 Deviation of Perceived Playfulness on Habit-Formation Apps - 58 -
5.4 Playfulness and Gender - 59 -
5.5 Genres of Habit-Formation Apps: Deviations of Internal Motivation and External Motivation - 61 -
5.6 Duration of App Use and Motivational Factors - 62 -
CHAPTER 6 CONCLUSIONS AND IMPLICATIONS - 63 -
6.1 Conclusions - 63 -
6.2 Implications for Practitioners - 65 -
6.2.1 Other Possible Factors Affecting Females Behavioral Intention - 65 -
6.2.2 Enhancing Functionality of Enjoyment and Playfulness - 66 -
6.2.3 Other than Concentration - 67 -
6.2.4 Keep Your App Updated Comprehensively - 68 -
6.3 Limitations of the Study - 70 -
6.4 Suggestions for Future Studies - 71 -
References - 72 -
Appendix A. Questionnaire (Chinese Version) - 86 -
APPENDIX B. Paired-Samples T-Test (PPFL) - 90 -
B.1 Paired-Samples Correlations (PPFLC, PPFLE & PPFLCU) - 90 -
B.2 Paired-Samples Test (PPFLC, PPFLE & PPFLCU) - 90 -
APPENDIX C. Independent-Samples T-Test (Gender) - 91 -
C.1 Group Statistics (Gender) - 91 -
C.2 Independent-Samples Test (Gender) - 91 -
APPENDIX D. Independent-Samples T-Test (Genre) - 92 -
D.1 Descriptives (Genre) - 92 -
D.2 Test of Homogeneity of Variances (Genre) - 93 -
D.4 Analysis of Variance (ANOVA) (Genre) - 93 -
APPENDIX E. Independent-Samples T-Test (Duration: L2M vs M2M)… - 94 -
E.1 Group Statistics (Duration: L2M vs M2M) - 94 -
E.3 Independent-Samples Test (Duration: L2M vs M2M) - 94 -
APPENDIX F. Independent-Samples T-Test (Duration: L2M vs M2M) …- 95 -
F.1 Group Statistics (Duration: L1W vs M1Y) - 95 -
F.2 Independent-Samples Test (Duration: L1W vs M1Y) - 95 -

LIST OF TABLES
CHAPTER 1
TABLE 1.1 LIST OF HABIT-FORMATION APPS EXAMPLES - 4 -
CHAPTER 2
TABLE 2.1 LITERATURE OF GAME DESIGN & GAMIFICATION ELEMENTS - 13 -
TABLE 2.2 APPLICATION OF TAM IN VARIOUS DOMAINS - 21 -
CHAPTER 3
TABLE 3.1 RESEARCH HYPOTHESES - 28 -
TABLE 3.2 OPERATIONAL DEFINITIONS OF VARIABLES - 31 -
TABLE 3.3 QUESTIONNAIRE ITEMS - 32 -
TABLE 3.4 FACTORS AND ITEMS FOR APP USE - 34 -
TABLE 3.5 DATA ANALYSIS METHODS - 37 -
TABLE 3.6 FACTOR LOADINGS AND CRONBACH’S Α (PILOT TEST) - 38 -
CHAPTER 4
TABLE 4.1 SAMPLE DEMOGRAPHICS - 40 -
TABLE 4.2 GENRES OF APP BEING USED & DURATION OF USING APP - 41 -
TABLE 4.3 MEANS & STANDARD DEV. OF PERCEIVED ENJOYMENT - 42 -
TABLE 4.4 MEANS & STANDARD DEV. OF PERCEIVED EASE OF USE - 42 -
TABLE 4.5 MEANS & STANDARD DEV. OF PERCEIVED USEFULNESS - 43 -
TABLE 4.6 MEANS & STANDARD DEV. OF PERCEIVED PLAYFULNESS - 43 -
TABLE 4. 7 MEANS & STANDARD DEV. OF BEHAVIORAL INTENTION TO USE - 44 -
TABLE 4.8 FACTOR LOADINGS OF DIMENSIONS - 45 -
TABLE 4.9 COMPOSITE RELIABILITY AND CRONBACH’S Α OF RESEARCH CONSTRUCTS - 46 -
TABLE 4.10 AVERAGE VARIANCE EXTRACTED AND CORRELATION MATRIX - 47 -
TABLE 4.11 HYPOTHESES TESTING RESULTS - 49 -
TABLE 4.12 GROUP STRUCTURAL MODEL ANALYSIS (GENDER) - 50 -
TABLE 4.13 COMPARISON OF R2 BETWEEN MALE & FEMALE - 51 -
TABLE 4.14 GROUP STRUCTURAL MODEL ANALYSIS (GENRE) - 52 -
TABLE 4.15 GROUP STRUCTURAL MODEL ANALYSIS (DURATION) - 54 -
TABLE 4.16 POSITIVE USER EXPERIENCE FEEDBACK - 55 -
TABLE 4.17 NEGATIVE USER EXPERIENCE FEEDBACK - 56 -
 
LIST OF FIGURES
CHAPTER 1
FIGURE 1.1 RESEARCH PROCESS - 7 -
CHAPTER 2
FIGURE 2.1 MDA FRAMEWORK - 11 -
FIGURE 2.2 MDE FRAMEWORK OF GAMIFICATION PRINCIPLES - 11 -
FIGURE 2.3 GAMIFICATION CONCEPT MAP - 14 -
FIGURE 2.4 THEORY OF REASONED ACTION MODEL - 15 -
FIGURE 2.5 TECHNOLOGY ACCEPTANCE MODEL - 17 -
FIGURE 2.6 HYBRID INTENTION MODELS - 19 -
FIGURE 2.7 REVISED TAM - 19 -
FIGURE 2.8 SIMPLIFIED TAM - 20 -
FIGURE 2.9 FLOW THEORY - 23 -
FIGURE 2.10 FLOW OF MENTAL STATES IN TERMS OF CHALLENGE LEVEL & SKILL LEVEL - 23 -
CHAPTER 3
FIGURE 3.1 RESEARCH MODEL - 27 -
CHAPTER 4
FIGURE 4.1 PATH COEFFICIENT OF RESEARCH MODEL - 48 -
FIGURE 4.2 COMPARISON OF R2 OF PPFL & BIU BETWEEN MALE & FEMALE - 51 -
CHAPTER 5
FIGURE 5.1 FOGG’S BEHAVIOR MODEL - 59 -

Accengage, (2018). 2018 Edition of the Push Notification Benchmark for Mobile Applications. Retrieved May 4, 2019, from, https://www.accengage.com/benchmark-opt-in-and-reaction-rates-of-push-notifications-and-in-app-messages-for-mobile-apps-2018-edition/
Adams, D. A., Nelson, R. R., & Todd, P. A. (1992). Perceived Usefulness, Ease of Use, and Usage of Information Technology: A Replication. MIS Quarterly, 16(2), 227. doi:10.2307/249577
Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behaviour. Englewood Cliffs NJ: Prentice Hall.
Atkinson, M., & Kydd, C. (1997). Individual Characteristics Associated with World-Wide-Web use: an Empirical Study of Playfulness and Motivation, The DATA BASE for Advances in Information Systems 28(2), 53-62.
Azar, K. M., Lesser, L. I., Laing, B. Y., Stephens, J., Aurora, M. S., Burke, L. E., & Palaniappan, L. P. (2013). Mobile Applications for Weight Management: Theory-Based Content Analysis. American Journal of Preventive Medicine, 45(5), 583-589.
Barnett, L. A. (1990). Playfulness: Definition, Design, and Measurement. Play and Culture, 3(4), 319-336.
Barnett, L. A. (1991). The Playful Child: Measurement of a Disposition to Play. Play and Culture, 4(1), 51-74.
Blohm, I., & Leimeister, J. M. (2013). Design of IT-Based Enhancing Services for Motivational Support and Behavioral Change. Business & Information Systems Engineering, 5(4), 275-278. doi:10.1007/s12599-013-0273-5
Blythe, M.A., Overbeeke, K., Monk, A.F., & Wright, P.C. Funology: from Usability to Enjoyment. Kluwer Academic Publishers, Norwell, MA, 2004.
Bonanno, P., & Kommers, P. A. M. (2008). Exploring the Influence of Gender and Gaming Competence on Attitudes towards Using Instructional Games. British Journal of Educational Technology, 39(1), 97-109.
Carroll, J. M., & Thomas, J. C. (1988). Fun. ACM SIGCHI Bulletin, 19(3), 21-24. doi: 10.1145/49108.1045604
Dale, S. (2014). Gamification: Making Work fun, or Making Fun of Work?. Business information review, 31(2), 82-90.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of use, and User Acceptance of Information Technology. MIS Quarterly, 319-340. doi: 10.2307/249008
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User Acceptance of Computer Technology: a Comparison of Two Theoretical Models. Management Science, 35(8), 982-1003. doi: doi.org/10.1287/mnsc.35.8.982
Deterding, S. (2012). Gamification: Designing for Motivation. Interactions, 19(4), 14-17. doi: 10.1145/2212877.2212883
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011, September). From Game Design Elements to Gamefulness: Defining Gamification. In the Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, Tampere, Finland (pp. 9-15). NY: ACM. doi: 10.1145/2181037.2181040
Dijkstra, T. K. (2013). Composites as Factors, Generalized Canonical Variables Revisited. Technical Report, Research Gate, doi: 10.13140/RG. 2.1. 3426.5449.
Dijkstra, T. K. (2015). All-Inclusive versus Single Block Composites. Technical Report, Research Gate, doi: 10.13140/RG.2.1.2917.8082
Fagan, M. H., Neill, S., & Wooldridge, B. R. (2008). Exploring the Intention to Use Computers: An Empirical Investigation of the Role of Intrinsic Motivation, Extrinsic Motivation, and Perceived Ease of Use. Journal of Computer Information Systems, 48(3), 31-37.
Fogg, B. J. (2009, April). A Behavior Model for Persuasive Design. In the Proceedings of the 4th International Conference on Persuasive Technology (p. 40). ACM.
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(3), 39-50.
Fourdesire (2019). FAQ for Version 2.9. Retrieved June 6, 2019, from https://fourdesire.helpshift.com/a/fortune-city/?l=en&s=faq-for-version-2-9
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research, MA: Addison-Wesley.
Gardner, B., & Lally, P. (2013). Does Intrinsic Motivation Strengthen Physical Activity Habit? Modeling Relationships between Self-Determination, Past Behaviour, and Habit Strength. Journal of behavioral medicine, 36(5), 488-497. doi: doi.org/10.1007/s10865-012-9442-0
Gefen, D., & Straub, D. W. (1997). Gender Differences in the Perception and Use of E-mail: An Extension to the Technology Acceptance Model. MIS Quarterly, 389-400.
Gentry, L., & Calantone, R. (2002). A Comparison of Three Models to Explain Shop-Bot Use on the Web. Psychology & Marketing, 19(11), 945-956.
Goodyear, M., & Nathan-Roberts, D. (2017, September). Gamification and The Design of Badges in Relation to Educational Achievement. In the Proceedings of the Human Factors and Ergonomics Society Annual Meeting (Vol. 61, No. 1, pp. 1229-1233). Sage CA: Los Angeles, CA: SAGE Publications.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2014). Multivariate data analysis. Harlow: Pearson Education Limited.
Hamari, J., Koivisto, J., & Sarsa, H. (2014, January). Does Gamification Work? -- A Literature Review of Empirical Studies on Gamification. In 2014 47th Hawaii International Conference on System Sciences (HICSS) (pp. 3025-3034). IEEE.
Hartley, S. (2018). The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World. Boston: Houghton Mifflin Harcourt.
Hartmann, T., & Klimmt, C. (2006). Gender and Computer Games: Exploring Females’ Dislikes. Journal of Computer-Mediated Communication, 11(4), 910–931.
Hendrickson, A. R., Massey, P. D., & Cronan, T. P. (1993). On the Test-Retest Reliability of Perceived Usefulness and Perceived Ease of Use Scales. MIS Quarterly, 17(2): 227-230. doi:10.2307/249803, JSTOR 249803
Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C. M., Diamantopoulos, A., Straub, D. W., ... & Calantone, R. J. (2014). Common Beliefs and Reality about PLS: Comments on Rönkkö and Evermann (2013). Organizational Research Methods, 17(2), 182-209. doi: 10.1177/1094428114526928
Hovis, K. (2018, September 26). Tech Companies Favor Social Scientists. Cornell Chronicle. Retrieved May 6, 2019, from https://news.cornell.edu/stories/2018/09/tech-companies-favor-social-scientists
Hunicke, R., LeBlanc, M., & Zubek, R. (2004, July). MDA: A Formal Approach to Game Design and Game Research. In the Proceedings of the AAAI Workshop on Challenges in Game AI (pp. 1-5). Menlo Park, CA: The AAAI Press.
Huotari, K., & Hamari, J. (2011, May). “Gamification” from the Perspective of Service Marketing. Presented at CHI’ 2011 Workshop Gamification: Using Game Design Elements in Non-Game Contexts, Vancouver, BC, Canada.
Hwang, Y., & Yi, M. (2002). Predicting The Use of Web-Based Information Systems: Intrinsic Motivation and Self-Efficacy. In the Proceedings of the 2002 AMCIS 149 (pp. 1076-1081). AIS Electronic Library. Retrieved February 4, 2019, form: http://aisel.aisnet.org/amcis2002/149
Jöreskog, K.G. and Wold, H. (1982) The ML and PLS Techniques for Modelling with Latent Variables: Historical and Comparative Aspects. In Jöreskog, K. G. & Wold H. (Eds.), Systems Under Indirect Observation: Causality, Structure, Prediction (Vol. 1, pp. 263-270). Amsterdam: North-Holland.
Kapp, K. M. (2012). The Gamification of Learning and Instruction: Game-Based Methods and Strategies for Training and Education. San Francisco, CA: Pfeiffer.
Kosmadoudi, Z., Lim, T., Ritchie, J. M., Louchart, S., Liu, Y., & Sung, R. (2012). Engineering Design Using Game-Enhanced CAD: The Potential to Augment the User Experience with Game Elements. Computer-Aided Design, 45(3), 777-795. doi: 10.1016/j.cad.2012.08.001
Knutas, A. (2018). Gamification. Encyclopedia of Computer Graphics and Games, 1-3. doi:10.1007/978-3-319-08234-9_219-1
Kuo, T., Tsai, G. Y., Lu, L. Y., & Wu, R. (2017). User’s Perceived Quality of Mobile Message App: Experience from Taiwan. Journal of Quality, 24(4), 235-250. doi: 10.6220/joq.2017.24(4).01
Lally, P., Chipperfield, A., & Wardle, J. (2008). Healthy Habits: Efficacy of Simple Advice on Weight Control Based on a Habit-Formation Model. International Journal of Obesity, 32, 700–707.
Lally, P., van Jaarsveld, C.H.M., Potts, H.W.W., & Wardle, J. (2010). How Are Habits Formed: Modelling Habit Formation in the Real World. European Journal of Social Psychology, 40, 998–1009. doi: 10.1002/ejsp.674
Lai, V. S., & Li, H. (2005). Technology Acceptance Model for Internet Banking: an Invariance Analysis. Information & Management, 42(2), 373-386.
Lieberman, J. N. (1977). Playfulness: Its Relationship to Imagination and Creativity. New York: Academic Press.
Lister, C., West, J. H., Cannon, B., Sax, T., & Brodegard, D. (2014). Just a Fad? Gamification in Health and Fitness Apps. JMIR Serious Games, 2(2), e9.
Lockheed, M. E. (1985). Women, Girls, and Computers: A First Look at the Evidence. Sex Roles, 13(3/4), 115–122.
López-Nicolás, C., Molina-Castillo, F. J., & Bouwman, H. (2008). An Assessment of Advanced Mobile Services Acceptance: Contributions from TAM and Diffusion Theory Models. Information & Management, 45(6), 359-364.
Lucas Jr, H. C., & Spitler, V. K. (1999). Technology Use and Performance: A Field Study of Broker Workstations. Decision Sciences, 30(2), 291-311.
Malone, T. W. (1980, September). What Makes Things Fun to Learn? Heuristics for Designing Instructional Computer Games. In the Proceedings of the 3rd ACM SIGSMALL Symposium and the First SIGPC Symposium on Small Systems (pp. 162-169). NY: ACM. doi: 10.1145/800088.802839
Martocchio, J. J., Webster, J. (1992). Effects of Feedback and Cognitive Playfulness on Performance in Microcomputer Software Training, Personnel Psychology 45, 553-578.
Malone, T. W. (1982, March). Heuristics for Designing Enjoyable User Interfaces: Lessons from Computer Games. In the Proceedings of the 1982 conference on Human Factors in Computing Systems (pp. 63-68). NY: ACM. doi: 10.1145/800049.801756
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38(4), 217-230. doi: doi.org/10.1016/S0378-7206(00)00061-6
National Communications Commission, Taiwan. (2017). 通訊傳播市場報告106 [Trans. Communications and Mass Media Report 2017]. Retrieved October 15, 2018, from https://www.ncc.gov.tw/chinese/files/18030/3923_38847_180301_1.pdf
Nation Development Council, Taiwan. (2017). 106年持有手機民眾數位機會調查報告 [Trans. 2017 Holding-Mobile-Phone Populace’s Digital Opportunity Survey Report]. Retrieved October 15, 2018 from https://www.ndc.gov.tw/Default.aspx
Nelson, M. J. (2012, October). Soviet and American Precursors to the Gamification of Work. In the Proceeding of the 16th International Academic MindTrek Conference (pp. 23-26). NY: ACM. doi: 10.1145/2393132.2393138
Newzoo (2018, June 14). 2018 Global Games Market Report. Retrieved October 15, 2018, from https://newzoo.com
Nevin, C. R., Westfall, A. O., Rodriguez, J. M., Dempsey, D. M., Cherrington, A., Roy, B., ... & Willig, J. H. (2014). Gamification as a Tool for Enhancing Graduate Medical Education. Postgraduate Medical Journal, 90(1070), 685-693. doi: 10.1136/postgradmedj-2013-132486.
Nunnally, J. C. (1980). Psychometric Theory. NY: McGraw-Hill.
O’Donovan, S. (2012). Gamification of the Games Course. Acessoem, 17, 1-8.
Padilla-MeléNdez, A., Del Aguila-Obra, A. R., & Garrido-Moreno, A. (2013). Perceived Playfulness, Gender differences and Technology Acceptance Model in a Blended Learning Scenario. Computers & Education, 63, 306-317.
Paunov, C., Planes-Satorra S., & Moriguchi, T. (2017), What Role for Social Sciences in Innovation?: Re-Assessing How Scientific Disciplines Contribute to Different Industries", OECD Science, Technology and Industry Policy Papers,45, OECD Publishing, Paris. doi:https://doi.org/10.1787/8a306011-en.
Pirouz, D. M. (2006). An Overview of Partial Least Squares. Business Publications, 24.
Ritterfeld, U., Cody, M., & Vorderer, P. (Eds.). (2009). Serious games: Mechanisms and effects. London, UK: Routledge.
Robson, K., Plangger, K., Kietzmann, J. H., McCarthy, I., & Pitt, L. (2015). Is It All a Game? Understanding the Principles of Gamification. Business Horizons, 58(4), 411-420.
Schrage, M. (2015, September 1). Why the Future of Social Science Is with Private Companies. Harvard Business Review. Retrieved May 6, 2019, from https://hbr.org/2015/09/why-the-future-of-social-science-is-with-private-companies
Seaborn, K., & Fels, D. I. (2015). Gamification in Theory and Action: A Survey. International Journal of human-computer studies, 74, 14-31.
SimilarWeb.com (2019). Features –App Analysis [online] Available at: https://pro.similarweb.com/#/apps/performance/0_com.fourdesire.fortunecity/158/1m/ [Accessed 16 Jun. 2019].
Simões, J., Redondo, R. D., & Vilas, A. F. (2013). A Social Gamification Framework for a K-6 Learning Platform. Computers in Human Behavior, 29(2), 345-353. doi:10.1016/j.chb.2012.06.007
Singh, S. P. (2012). Gamification: A Strategic Tool for Organizational Effectiveness. International Journal of Management, 1(1), 108-113.
Social Media Fact Sheet. (2018, February 05). Retrieved May 3, 2019, from https://www.pewinternet.org/fact-sheet/social-media/
Stavrou, N. A., Jackson, S. A., Zervas, Y., & Karteroliotis, K. (2007). Flow Experience and Athletes’ Performance with Reference to the Orthogonal Model of Flow. The Sport Psychologist, 21(4), 438-457.
Subramanian, G. H. (1994). A Replication of Perceived Usefulness and Perceived Ease of Use Measurement. Decision Sciences, 25(5-6), 863-874. doi:10.1111/j.1540-5915.1994.tb01873.x
Sun, A., Chen, J. F., & Chang, J. F. (2017) Exploring the Line Usage Intention by Flow Theory and Technology Acceptance Model. Journal of Internet Technology, 18(6), 1215-1222. doi: 10.6138/JIT.2017.18.6.20170303
Terzis, V., & Economides, A. A. (2011). Computer Based Assessment: Gender Differences in Perceptions and Acceptance. Computers in Human Behavior, 27(6), 2108-2122.
Venkatesh, V. (2000). Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model. Information Systems Research, 11(4), 342-365.
Venkatesh, V., Speier, C., & Morris, M. G. (2002). User Acceptance Enablers in Individual Decision Making about Technology: Toward an Integrated Model. Decision Sciences, 33(2), 297-316.
Venkatesh, V., & Davis, F. D. (1994) Modeling the Determinants of Perceived Ease of Use. In the Proceedings of the International Conference on Information Systems, Vancouver, Canada (pp. 213-227).
Venkatesh, V., & Davis, F. D. (1996). A Model of the Antecedents of Perceived Ease of Use: Development and Test. Decision Sciences, 27(3), 451-481.
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management Science, 46(2), 186-204.
Venkatesh, V., & Morris, M. G. (2000). Why Don’t Men Ever Stop to Ask for Directions? Gender, Social Influence, and Their Role in Technology Acceptance and Usage Behavior. MIS Quarterly,24(1), 115. doi:10.2307/3250981
Verplanken, B., & Orbell, S. (2003). Reflections on Past behavior: A Self-Report Index of Habit Strength. Journal of Applied Social Psychology, 33, 1313–1330. doi: 10.1111/j.1559-1816.2003.tb01951.x
Wang, Y.-S., Wu, M.-C., & Wang, H.-Y. (2009). Investigating the Determinants and Age and Gender Differences in the Acceptance of Mobile Learning. British Journal of Educational Technology, 40(1), 92–118.
Webster, J., & Martocchio, J. J. (1992). Microcomputer Playfulness: Development of a Measure with Workplace Implications. MIS Quarterly, 16(2), 201-226.
Webster, J., Trevino, L. K., & Ryan, L. (1993). The Dimensionality and Correlates of Flow in Human-Computer Interactions. Computers in Human Behavior, 9(4), 411-426.
Wiedemann, A. U., Gardner, B., Knoll, N., & Burkert, S. (2014). Intrinsic Rewards, Fruit and Vegetable Consumption, and Habit Strength: A Three‐Wave Study Testing the Associative‐Cybernetic Model. Applied Psychology: Health and Well‐Being, 6(1), 119-134.
Wixom, B. H., & Watson, H. J. (2001). An Empirical Investigation of the Factors Affecting Data Warehousing Success. MIS Quarterly, 25(1), 17-41.
Wood, W., Quinn, J. M., & Kashy, D. A. (2002). Habits in Everyday Life: Thought, Emotion, and Action. Journal of Personality and Social Psychology, 83(6), 1281-1297. doi:10.1037//0022-3514.83.6.1281
Wong A. M. K., Lin, C. C., Hsu, S. C., Chung, C. Y., Lin, Y. C., Huang, P. C., & Chen, C. K. (2015). Combining Eldercare Technology with Interactive Arts Environment. Taiwan Journal of Physical Medicine and Rehabilitation, 43(4):225-237. doi: 10.63S15/2015.43(4)03
Wong, T. S. (2012). The Effects of Students’ Information Ability and Adoption of Mobile Digital Learning to the Technology Acceptance. Tajen Journal, 41, 71-88. doi: 10.29707/TJ.201209.0005
Wu., D.Y. (2015). From Game to Gamification: Preliminary Research of Gamification Marketing Theory. Mass Communication Research, 124, 215-251.
Wu, L. L., Lee, L., Su, H. Y. (2008). Consumers’ Acceptance of Websites for Pre-Purchase Information Seeking. Journal of Information Management, 15(3), 227-250. doi: 10.6382/JIM.200807.0227
Yen, Y. S. & Lee, S. Y. (2012). A Study of the Technology Acceptance of Keyword Advertising to the Advertisers. Journal of Business Administration, 94, 69-92.
Yi, M. (2004, December 18). THEY GOT GAME/Stake of New Releases for Hunger Video Game Enthusiasts Mean It’s Boom Time for an Industry Now Even Bigger Than Hollywood. San Francisco Chronicles. Retrieved January 3, 2019, from https://www.sfgate.com
Zichermann, G., & Cunningham, C. (2011). Gamification by Design: Implementing Game Mechanics in Web and Mobile Apps. Sebastopol, CA: OReilly.
Zyda, M. (2005). From Visual Simulation to Virtual Reality to Games. Computer, 38(9), 25-32.