User Modeling and User-Adapted Interaction

, Volume 28, Issue 1, pp 35–74 | Cite as

Gamification, quantified-self or social networking? Matching users’ goals with motivational technology

  • Juho HamariEmail author
  • Lobna Hassan
  • Antonio Dias


Systems and services we employ in our daily life have increasingly been augmented with motivational designs which fall under the classes of (1) gamification, (2) quantified-self and (3) social networking features that aim to help users reach their goals via motivational enforcement. However, users differ in terms of their orientation and focus toward goals and in terms of the attributes of their goals. Therefore, different classes of motivational design may have a differential fit for users. Being able to distinguish the goal profiles of users, motivational design could be better tailored. Therefore, in this study we investigate how different goal foci (outcome and focus), goals orientation (mastery, proving, and avoiding), and goal attributes (specificity and difficulty) are associated with perceived importance of gamification, social networking and quantified-self features. We employ survey data (\(\mathrm{N}=167\)) from users of HeiaHeia; a popular exercise encouragement app. Results indicate that goal-setting related factors of users and attributes of goals are connected with users’ preference over motivational design classes. In particular, the results reveal that being outcome-focused is associated with positive evaluations of gamification and quantified-self design classes. Users with higher proving-orientation perceived gamification and social networking design classes as more important, users with lower goal avoidance-orientation perceived social networking design as more important, whereas users with higher mastery-orientation perceived quantified-self design more important. Users with difficult goals were less likely to perceive gamification and social networking design important, whereas for users with high goal specificity quantified-self features were important. The findings provide insights for the automatic adaptation of motivational designs to users’ goals. However, more research is naturally needed to further investigate generalizability of the results.


Gamification Quantified-self Social networking Goal-setting Goal orientation Motivational information system 



This work was supported by the Finnish foundation for economic education (10-5562 and 12-6385), Hanken support foundation, the Finnish Funding Agency for Technology and Innovation TEKES (40111/14, 40107/14 and 40009/16) and participating partners, as well as Satakunnan korkeakoulusäätiö and its collaborators. The authors wish to also express their gratitude to the editors and reviewers for the fair, rigorous and meaningful review process.


  1. Agarwal, R., Karahanna, E.: Time, flies when you’re having fun: cognitive absorption and beliefs about information technology usage. Manag. Inf. Syst. MIS Q. 24(4), 665–694 (2000)CrossRefGoogle Scholar
  2. Alcivar, I., Abad, A.G.: Design and evaluation of a gamified system for ERP training. Comput. Hum. Behav. 58, 109–118 (2016)CrossRefGoogle Scholar
  3. Anderson, J.C., Gerbing, D.W.: The effect of sampling error on convergence, improper solutions, and goodness-of-fit indices for maximum likelihood confirmatory factor analysis. Psychometrika 49(2), 155–173 (1984)CrossRefGoogle Scholar
  4. Anderson, J.C., Gerbing, D.W.: Structural equation modeling in practice: a review and recommended two-step approach. Psychol. Bull. 103(3), 411–423 (1988)CrossRefGoogle Scholar
  5. Baard, P.P., Deci, E.L., Ryan, R.M.: Intrinsic need satisfaction: a motivational basis of performance and weil-being in two work settings1. J. Appl. Soc. Psychol. 34(10), 2045–2068 (2004)CrossRefGoogle Scholar
  6. Barker, C., Pistrang, N.: Research Methods in Clinical Psychology: An Introduction for Students and Practitioners. Wiley, New York (2015)CrossRefGoogle Scholar
  7. Barrett, M.A., Humblet, O., Hiatt, R.A., Adler, N.E.: Big data and disease prevention: from quantified self to quantified communities. Big Data 1(3), 168–175 (2013)CrossRefGoogle Scholar
  8. Bentler, P.M., Chou, C.P.: Practical issues in structural modeling. Sociol. Methods Res. 16(1), 78–117 (1987)CrossRefGoogle Scholar
  9. Bista, S.K., Nepal, S., Paris, C., Colineau, N.: Gamification for online communities: a case study for delivering government services. Int. J. Coop. Inf. Syst. 23(02), 1441002 (2014)CrossRefGoogle Scholar
  10. Bittner, J.V., Schipper, J.: Motivational effects and age differences of gamification in product advertising. J. Consum. Market. 31(5), 391–400 (2014)CrossRefGoogle Scholar
  11. Bogost, I.: Why Gamification is Bullshit 2, p. 65. In: Approaches, Issues, Applications, The Gameful World. Cambridge: MIT Press (2015)Google Scholar
  12. Bouvier, P., Sehaba, K., Lavoué, É.: A trace-based approach to identifying users’ engagement and qualifying their engaged-behaviours in interactive systems: application to a social game. User Model. User-Adap. Inter. 24(5), 413–451 (2014)CrossRefGoogle Scholar
  13. Boyd, D., Ellison, N.B.: Social network sites: definition, history, and scholarship. J. Comput. Mediat. Commun. 13(1), 210–230 (2007)CrossRefGoogle Scholar
  14. Burke, B.: Gamify: How Gamification Motivates People to Do Extraordinary Things. Bibliomotion Inc, Brookline (2014)Google Scholar
  15. Burnette, J.L., O’Boyle, E.H., VanEpps, E.M., Pollack, J.M., Finkel, E.J.: Mind-sets matter: a meta-analytic review of implicit theories and self-regulation. Psychol. Bull. 139(3), 655 (2013)CrossRefGoogle Scholar
  16. Butler, B.S.: Membership size, communication activity, and sustainability: a resource-based model of online social structures. Inf. Syst. Res. 12(4), 346–362 (2001)CrossRefGoogle Scholar
  17. Butler, B.S., Wang, X.: The cross-purposes of cross-posting: boundary reshaping behavior in online discussion communities. Inf. Syst. Res. 23(3–part–2), 993–1010 (2012)CrossRefGoogle Scholar
  18. Chan, K., Prendergast, G.: Materialism and social comparison among adolescents. Soc. Behav. Personal. Int. J. 35(2), 213–228 (2007)CrossRefGoogle Scholar
  19. Chen, A., Lu, Y., Chau, P.Y., Gupta, S.: Classifying, measuring, and predicting users’ overall active behavior on social networking sites. J. Manag. Inf. Syst. 31(3), 213–253 (2014)CrossRefGoogle Scholar
  20. Chin, W.W.: The partial least squares approach to structural equation modeling. Mod. Methods Bus. Res. 295(2), 295–336 (1998)Google Scholar
  21. Christy, K.R., Fox, J.: Leaderboards in a virtual classroom: a test of stereotype threat and social comparison explanations for women’s math performance. Comput. Educ. 78, 66–77 (2014)CrossRefGoogle Scholar
  22. Choe, E.K., Lee, N.B., Lee, B., Pratt, W., Kientz, J.A.: Understanding quantified-selfers’ practices in collecting and exploring personal data. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, pp. 1143–1152. ACM (2014)Google Scholar
  23. Cialdini, R.B., Goldstein, N.J.: Social influence: compliance and conformity. Annu. Rev. Psychol. 55, 591–621 (2004)CrossRefGoogle Scholar
  24. Cialdini, R.B., Trost, M.R.: Social influence: social norms, conformity, and compliance. In: Gilbert, D.T., Fiske, S.T., Lindzey, G. (eds.) The Handbook of Social Psychology, vol. 2, 4th edn., pp. 151–192. McGraw-Hill, Boston (1998)Google Scholar
  25. Cruz, C., Hanus, M.D., Fox, J.: The need to achieve: players’ perceptions and uses of extrinsic meta-game reward systems for video game consoles. Comput. Hum. Behav. 71, 1–9 (2015)Google Scholar
  26. Capa, R.L., Audiffren, M., Ragot, S.: The effects of achievement motivation, task difficulty, and goal difficulty on physiological, behavioral, and subjective effort. Psychophysiology 45(5), 859–868 (2008)Google Scholar
  27. Chin, W.W.: The partial least squares approach for structural equation modelling. In: Marcoulides, G.A. (ed.) Modern Methods for Business Research, pp. 295–336. Lawrence Erlbaum Associates, London (1998)Google Scholar
  28. Chin, W.W., Marcolin, B.L., Newsted, P.R.: 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. Inf. Syst. Res. 14(2), 189–217 (2003)CrossRefGoogle Scholar
  29. Corpus, J.H., McClintic-Gilbert, M.S., Hayenga, A.O.: Within-year changes in children’s intrinsic and extrinsic motivational orientations: contextual predictors and academic outcomes. Contemp. Educ. Psychol. 34(2), 154–166 (2009)CrossRefGoogle Scholar
  30. Csíkszentmihályi, M.: Beyond Boredom and Anxiety: Experiencing Flow in Work and Play. Jossey-Bass, San Francisco (1975)Google Scholar
  31. Cowley, B., Charles, D.: Behavlets: a method for practical player modeling using psychology-based player traits and domain specific features. User Model. User-Adap. Inter. 26(2–3), 257–306 (2016)CrossRefGoogle Scholar
  32. Davis, F.D.: Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Q. 13, 319–340 (1989)CrossRefGoogle Scholar
  33. Davis, F.D., Bagozzi, R.P., Warshaw, P.R.: Extrinsic and intrinsic motivation to use computers in the workplace. J. Appl. Soc. Psychol. 22(14), 1111–1132 (1992)CrossRefGoogle Scholar
  34. Deci, E.L., Koestner, R., Ryan, R.M.: A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychol. Bull. 125(6), 627 (1999)CrossRefGoogle Scholar
  35. Deci, E.L., Ryan, R.M.: The “what” and “why” of goal pursuits: human needs and the self-determination of behavior. Psychol. Inq. 11(4), 227–268 (2000)CrossRefGoogle Scholar
  36. Deterding, S.: The lens of intrinsic skill atoms: a method for gameful design. Hum. Comput. Interact. 30(3–4), 294–335 (2015)CrossRefGoogle Scholar
  37. Deterding, S., Dixon, D., Khaled, R., Nacke, L.: From game design elements to gamefulness: Defining gamification. In: Proceedings of the 15th International Academic MindTrek Conference: Envisioning Future Media Environments, pp. 9–15. ACM (2011)Google Scholar
  38. Dijkstra, A.: The persuasive effects of personalization through: name mentioning in a smoking cessation message. User Model. User-Adap. Inter. 24(5), 393–411 (2014)CrossRefGoogle Scholar
  39. Drach-Zahavy, A., Erez, M.: Challenge versus threat effects on the goal-performance relationship. Organ. Behav. Hum. Decis. Process. 88(2), 667–682 (2002)CrossRefGoogle Scholar
  40. Elliot, A.J., Harackiewicz, J.M.: Goal setting, achievement orientation, and intrinsic motivation: a mediational analysis. J. Pers. Soc. Psychol. 66(5), 968 (1994)CrossRefGoogle Scholar
  41. Elliot, A.J., McGregor, H.A.: A 2\(\times \) 2 achievement goal framework. J. Pers. Soc. Psychol. 80(3), 501 (2001)CrossRefGoogle Scholar
  42. ESA: Essential facts about the computer and video game industry: 2014 sales, demographic, and usage data (2014).
  43. Farzan, R., DiMicco, J.M., Millen, D.R., Brownholtz, B., Geyer, W., Dugan, C.: When the experiment is over: deploying an incentive system to all the users. In: Symposium on Persuasive Technology (2008a)Google Scholar
  44. Farzan, R., DiMicco, J.M., Millen, D.R., Dugan, C., Geyer, W., Brownholtz, E. A.: Results from deploying a participation incentive mechanism within the enterprise. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp. 563–572. ACM (2008b)Google Scholar
  45. Fornell, C., Larcker, D.F.: Structural equation models with unobservable variables and measurement error: algebra and statistics. J. Market. Res. 18(3), 382–388 (1981)CrossRefGoogle Scholar
  46. Fransella, F. (ed.): Personality: Theory, Measurement and Research, vol. 719. Routledge Kegan & Paul, London (1981)Google Scholar
  47. Freund, A.M., Hennecke, M., Riediger, M.: Age-related differences in outcome and process goal focus. Eur. J. Dev. Psychol. 7(2), 198–222 (2010)CrossRefGoogle Scholar
  48. Gartner: Gartner says by 2014, 80 percent of current gamified applications will fail to meet business objectives primarily due to poor design (2012).
  49. Gurrin, C., Smeaton, A.F., Doherty, A.R.: Lifelogging: personal big data. Found. Trends Inf. Retr. 8(1), 1–125 (2014)CrossRefGoogle Scholar
  50. Hackel, T.S., Jones, M.H., Carbonneau, K.J., Mueller, C.E.: Re-examining achievement goal instrumentation: convergent validity of AGQ and PALS. Contemp. Educ. Psychol. 46, 73–80 (2016)CrossRefGoogle Scholar
  51. Hair, J.F.J., Black, W.C., Babin, B.J., Anderson, R.E.: Multivariate Data Analysis, 7th edn. Prentice Hall, Upper Saddle River (2010)Google Scholar
  52. Hair, J.F., Ringle, C.M., Sarstedt, M.: PLS-SEM: indeed a silver bullet. J. Market. Theory Pract. 19(2), 139–152 (2011)CrossRefGoogle Scholar
  53. Hair, J.F., Hult, G.T.M., Ringle, C., Sarstedt, M.: A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications, London (2016)zbMATHGoogle Scholar
  54. Hamari, J.: Transforming homo economicus into homo ludens: a field experiment on gamification in a utilitarian peer-to-peer trading service. Electron. Commer. Res. Appl. 12(4), 236–245 (2013)CrossRefGoogle Scholar
  55. Hamari, J.: Do badges increase user activity? A field experiment on effects of gamification. Comput. Hum. Behav. 71, 469–478 (2017)CrossRefGoogle Scholar
  56. Hamari, J., Eranti, V.: Framework for designing and evaluating game achievements. In: Proceedings of Digra 2011 Conference: Think Design Play, Hilversum, Netherlands, September 14–17 (2011)Google Scholar
  57. Hamari, J., Koivisto, J.: Measuring flow in gamification: dispositional flow scale-2. Comput. Hum. Behav. 40, 133–143 (2014)CrossRefGoogle Scholar
  58. Hamari, J., Koivisto, J.: “Working out for likes”: an empirical study on social influence in exercise gamification. Comput. Hum. Behav. 50, 333–347 (2015a)CrossRefGoogle Scholar
  59. Hamari, J., Koivisto, J.: Why do people use gamification services? Int. J. Inf. Manag. 35(4), 419–431 (2015b)CrossRefGoogle Scholar
  60. Hamari, J., Keronen, L.: Why do people play games? A meta-analysis. Int. J. Inf. Manag. 37(3), 125–141 (2017)CrossRefGoogle Scholar
  61. Hamari, J., Tuunanen, J.: Player types: a meta-synthesis. Trans. Digit. Games Res. Assoc. 1(2), 29–53 (2014)Google Scholar
  62. Hamari, J., Koivisto, J., Pakkanen, T.: Do persuasive technologies persuade?—A review of empirical studies. In: Spagnolli, A. et al. (eds.) Persuasive Technology, LNCS 8462, pp. 118–136. Springer, Cham (2014a)Google Scholar
  63. Hamari, J., Koivisto, J., Sarsa, H.: Does gamification work?—A literature review of empirical studies on gamification. In: Proceedings of the 47th Annual Hawaii International Conference on System Sciences, Hawaii, USA, January 6–9 (2014b)Google Scholar
  64. Hamari, J., Huotari, K., Tolvanen, J.: Gamification and economics. In: Walz, S.P., Deterding, S. (eds.) The Gameful World: Approaches, Issues, Applications. MIT Press, Cambridge (2015)Google Scholar
  65. Hamari, J., Shernoff, D.J., Rowe, E., Coller, B., Asbell-Clarke, J., Edwards, T.: Challenging games help students learn: an empirical study on engagement, flow and immersion in game-based learning. Comput. Hum. Behav. 54, 170–179 (2016). CrossRefGoogle Scholar
  66. Hanus, M.D., Fox, J.: Assessing the effects of gamification in the classroom: a longitudinal study on intrinsic motivation, social comparison, satisfaction, effort, and academic performance. Comput. Educ. 80, 152–161 (2015)CrossRefGoogle Scholar
  67. Hassan, L., Nader, A.: Gamification design in action: the practical cases of gamification platforms for employee work motivation and citizens’ civic engagement. In: Proceedings of the International Conference on ICT Management for Global Competitiveness and Economic Growthin Emerging Economies (ICTM 2016), pp. 67–70. ISBN: 978-83-64389-62-7 (2016)Google Scholar
  68. Hernandez, B., Montaner, T., Sese, F.J., Urquizu, P.: The role of social motivations in e-learning: how do they affect usage and success of ICT interactive tools? Comput. Hum. Behav. 27(6), 2224–2232 (2011)CrossRefGoogle Scholar
  69. Hildebrand, C., Häubl, G., Herrmann, A., Landwehr, J.R.: When social media can be bad for you: community feedback stifles consumer creativity and reduces satisfaction with self-designed products. Inf. Syst. Res. 24(1), 14–29 (2013)CrossRefGoogle Scholar
  70. Hirschheim, R., Klein, H.K.: A glorious and not-so-short history of the information systems field. J. Assoc. Inf. Syst. 13(4), 188 (2012)Google Scholar
  71. Huotari, K., Hamari, J.: A definition for gamification: anchoring gamification in the service marketing literature. Electr Mark. 27(1), 21–31 (2017). CrossRefGoogle Scholar
  72. Jones, B.A., Madden, G.J., Wengreen, H.J.: The FIT game: preliminary evaluation of a gamification approach to increasing fruit and vegetable consumption in school. Prev. Med. 68, 76–79 (2014)CrossRefGoogle Scholar
  73. Jung, J.H., Schneider, C., Valacich, J.: Enhancing the motivational affordance of information systems: the effects of real-time performance feedback and goal setting in group collaboration environments. Manag. Sci. 56(4), 724–742 (2010)CrossRefGoogle Scholar
  74. Jonker, J.J., Piersma, N., Van den Poel, D.: Joint optimization of customer segmentation and marketing policy to maximize long-term profitability. Exp. Syst. Appl. 27(2), 159–168 (2004)CrossRefGoogle Scholar
  75. Kim, E.A., Ratneshwar, S., Roesler, E., Chowdhury, T.G.: Attention to social comparison information and brand avoidance behaviors. Market. Lett. 27(2), 259–271 (2016)CrossRefGoogle Scholar
  76. Koivisto, J., Hamari, J.: Demographic differences in perceived benefits from gamification. Comput. Hum. Behav. 35, 179–188 (2014)CrossRefGoogle Scholar
  77. Koivisto, J., Hamari, J.: The rise of motivational information systems: a review of gamification literature. Working paper (2017)Google Scholar
  78. Krasnova, H., Wenninger, H., Widjaja, T., Buxmann, P.: Envy on Facebook: a hidden threat to users’ life satisfaction? Wirtschaftsinformatik 92, 1–16 (2013)Google Scholar
  79. Krasnova, H., Widjaja, T., Buxmann, P., Wenninger, H., Benbasat, I.: Research note—why following friends can hurt you: an exploratory investigation of the effects of envy on social networking sites among college-age users. Inf. Syst. Res. 26(3), 585–605 (2015)CrossRefGoogle Scholar
  80. Latham, G.P.: Goal setting: a five-step approach to behavior change. Org. Dyn. 32(3), 309–318 (2003)CrossRefGoogle Scholar
  81. Landers, R.N.: Developing a theory of gamified learning: linking serious games and gamification of learning. Simul. Gaming 45, 752–768 (2014)CrossRefGoogle Scholar
  82. Landers, R.N., Bauer, K.N., Callan, R.C.: Gamification of task performance with leaderboards: a goal setting experiment. Comput. Hum. Behav. 71, 508–515 (2017)CrossRefGoogle Scholar
  83. Latham, G.P.: Motivate employee performance through goal setting. Handb. Princ. Org. Behav. 107, 119 (2000)Google Scholar
  84. Lee, C., Bobko, P., Earley, P.C., Locke, E.A.: An empirical analysis of a goal setting questionnaire. J. Org. Behav. 12(6), 467–482 (1991)CrossRefGoogle Scholar
  85. Lehdonvirta, V.: Virtual consumption. Turku School of Economics, No. A-11 (2009)Google Scholar
  86. Lin, K.Y., Lu, H.P.: Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput. Hum. Behav. 27(3), 1152–1161 (2011)CrossRefGoogle Scholar
  87. Ling, K., Beenen, G., Ludford, P., Wang, X., Chang, K., Li, X., Resnick, P.: Using social psychology to motivate contributions to online communities. J. Comput. Mediat. Commun. 10(4), 00–00 (2005)CrossRefGoogle Scholar
  88. Lieberoth, A.: Shallow gamification testing psychological effects of framing an activity as a game. Games Cult. 10(3), 229–248 (2015)CrossRefGoogle Scholar
  89. Locke, E.A., Latham, G.P. (eds.): New Developments in Goal Setting and Task Performance. Routledge, Abingdon (2013)Google Scholar
  90. Locke, E.A., Latham, G.P.: Goal setting: a motivational technique that works!. Prentice Hall, Upper Saddle River (1984)Google Scholar
  91. Locke, E.A., Latham, G.P.: Building a practically useful theory of goal setting and task motivation: a 35-year odyssey. Am. Psychol. 57(9), 705 (2002)CrossRefGoogle Scholar
  92. Locke, E.A., Shaw, K.N., Saari, L.M., Latham, G.P.: Goal setting and task performance: 1969–1980. Psychol. Bull. 90(1), 125 (1981)CrossRefGoogle Scholar
  93. Loock, C.M., Staake, T., Thiesse, F.: Motivating energy-efficient behavior with green IS: an investigation of goal setting and the role of defaults. MIS Q. 37(4), 1313–1332 (2013)CrossRefGoogle Scholar
  94. Lowry, P.B., Gaskin, J.: Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: when to choose it and how to use it. IEEE Trans. Prof. Commun. 57(2), 123–146 (2014)CrossRefGoogle Scholar
  95. Lunenburg, F.C.: Goal-setting theory of motivation. Int. J. Manag. Bus. Admin. 15(1), 1–6 (2011)Google Scholar
  96. Lupton, D.: The Quantified Self: A Sociology of Self-Tracking. Polity Press, Cambridge (2016)Google Scholar
  97. Mamdani, A., Pitt, J., Stathis, K.: Connected communities from the standpoint of multi-agent systems. New Gener. Comput. 17(4), 381–393 (1999)CrossRefGoogle Scholar
  98. Mann, T., De Ridder, D., Fujita, K.: Self-regulation of health behavior: social psychological approaches to goal setting and goal striving. Health Psychol. 32(5), 487 (2013)CrossRefGoogle Scholar
  99. Mäntymäki, M., Islam, A.N.: The Janus face of Facebook: positive and negative sides of social networking site use. Comput. Hum. Behav. 61, 14–26 (2016)CrossRefGoogle Scholar
  100. McGonigal, J.: Reality is Broken: Why Games Make Us Better and How They Can Change the World. Penguin, London (2011)Google Scholar
  101. Mealiea, L.W., Latham, G.P.: Skills for Managerial Success: Theory, Experience, and Practice. Irwin, Toronto (1996)Google Scholar
  102. Mehta, R.: The self-quantification movement-implications for healthcare professionals. SelfCare 2(3), 87–92 (2011)Google Scholar
  103. Morschheuser, B., Hamari, J., Koivisto, J.: Gamification in crowdsourcing: a review. In: Proceedings of the 49th Annual Hawaii International Conference on System Sciences (HICSS), Hawaii, USA, January 5–8 (2016).
  104. Morschheuser, B., Riar, M., Hamari, J., Maedche, A.: How games induce cooperation? A study on the relationship between game features and we-intentions in an augmented reality game. Comput. Hum. Behav. 77, 169–183 (2017)CrossRefGoogle Scholar
  105. Munson, S.A., Consolvo, S.: Exploring goal-setting, rewards, self-monitoring, and sharing to motivate physical activity. In: 2012 6th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth) and Workshops, pp. 25–32. IEEE (2012)Google Scholar
  106. Nahrgang, J.D., DeRue, D.S., Hollenbeck, J.R., Spitzmuller, M., Jundt, D.K., Ilgen, D.R.: Goal setting in teams: the impact of learning and performance goals on process and performance. Organ. Behav. Hum. Decis. Process. 122(1), 12–21 (2013)CrossRefGoogle Scholar
  107. Nicholson, S.: A user-centered theoretical framework for meaningful gamification. In: Proceedings of Games+Learning+Society 8.0 (GLS 8.0) (2012)Google Scholar
  108. Nicholson, S.: A recipe for meaningful gamification. In: Gamification in Education and Business, pp. 1–20. Springer, Berlin (2015)Google Scholar
  109. Ng, J.Y., Ntoumanis, N., Thøgersen-Ntoumani, C., Deci, E.L., Ryan, R.M., Duda, J.L., Williams, G.C.: Self-determination theory applied to health contexts a meta-analysis. Perspect. Psychol. Sci. 7(4), 325–340 (2012)CrossRefGoogle Scholar
  110. Norman, D.A., Draper, S.W.: User Centered System Design, pp. 1–2. Hillsdale, NJ (1986)Google Scholar
  111. Nunnally, J.: Psychometric Methods. McGraw-Hill, New York (1978)Google Scholar
  112. Oinas-Kukkonen, H.: A foundation for the study of behavior change support systems. Pers. Ubiquit. Comput. 17(6), 1223–1235 (2013)CrossRefGoogle Scholar
  113. op den Akker, Jones, V.M., Hermens, H.J.: Tailoring real-time physical activity coaching systems: a literature survey and model. User Model. User-Adap. Inter. 24(5), 351–392 (2014)CrossRefGoogle Scholar
  114. Orji, R., Vassileva, J., Mandryk, R.L.: Modeling the efficacy of persuasive strategies for different gamer types in serious games for health. User Model. User-Adap. Inter. 24(5), 453–498 (2014)CrossRefGoogle Scholar
  115. Parameswaran, M., Whinston, A.B.: Research issues in social computing. J. Assoc. Inf. Syst. 8(6), 336 (2007)Google Scholar
  116. Petkov, P., Köbler, F., Foth, M., Medland, R., Krcmar, H.: Engaging energy saving through motivation-specific social comparison. In: CHI’11 Extended Abstracts on Human Factors in Computing Systems, pp. 1945–1950. ACM (2011)Google Scholar
  117. Pintrich, P.R.: The role of goal orientation in self-regulated learning. Handb. Self Regul. 451, 451–502 (2000)CrossRefGoogle Scholar
  118. Presslee, A., Vance, T.W., Webb, R.A.: The effects of reward type on employee goal setting, goal commitment, and performance. Account. Rev. 88(5), 1805–1831 (2013)CrossRefGoogle Scholar
  119. Raftopoulos, M.: Towards gamification transparency: a conceptual framework for the development of responsible gamified enterprise systems. J. Gaming Virtual Worlds 6(2), 159–178 (2014)CrossRefGoogle Scholar
  120. Rasch, R.H., Tosi, H.L.: Factors affecting software developers’ performance: an integrated approach. MIS Q. 16, 395–413 (1992)CrossRefGoogle Scholar
  121. Rawassizadeh, R., Price, B.A., Petre, M.: Wearables: has the age of smartwatches finally arrived? Commun. ACM 58(1), 45–47 (2015)CrossRefGoogle Scholar
  122. Richter, A., Koch, M.: Functions of social networking services. In: Proceedings of International Conference on the Design of Cooperative Systems, pp. 87–98 (2008)Google Scholar
  123. Rigby, C.S.: Gamification and motivation. In: Walz, S.P., Deterding, S. (eds.) The Gameful World: Approaches, Issues, Applications, pp. 113e137. MIT Press, Cambridge (2014)Google Scholar
  124. Roskes, M., Elliot, A.J., De Dreu, C.K.: Why is avoidance motivation problematic, and what can be done about it? Curr. Dir. Psychol. Sci. 23(2), 133–138 (2014)CrossRefGoogle Scholar
  125. Santhanam, R., Liu, D., Shen, W.C.M.: Research note–gamification of technology-mediated training: not all competitions are the same. Inf. Syst. Res. 27, 453–465 (2016)CrossRefGoogle Scholar
  126. Seaborn, K., Fels, D.I.: Gamification in theory and action: a survey. Int. J. Hum Comput Stud. 74, 14–31 (2015)CrossRefGoogle Scholar
  127. Swan, M.: Emerging patient-driven health care models: an examination of health social networks, consumer personalized medicine and quantified self-tracking. Int. J. Environ. Res. Pub. Health 6(2), 492–525 (2009)CrossRefGoogle Scholar
  128. Swan, M.: The quantified self: fundamental disruption in big data science and biological discovery. Big Data 1(2), 85–99 (2013)CrossRefGoogle Scholar
  129. Tandoc, E.C., Ferrucci, P., Duffy, M.: Facebook use, envy, and depression among college students: is facebooking depressing? Comput. Hum. Behav. 43, 139–146 (2015)CrossRefGoogle Scholar
  130. Taylor, S., Todd, P.A.: Understanding information technology usage: a test of competing models. Inf. Syst. Res. 6(2), 144–176 (1995)CrossRefGoogle Scholar
  131. Tuominen-Soini, H., Salmela-Aro, K., Niemivirta, M.: Stability and change in achievement goal orientations: a person-centered approach. Contemp. Educ. Psychol. 36(2), 82–100 (2011)CrossRefGoogle Scholar
  132. Uhlmann, T.S., Battaiola, A.L.: Applications of a roleplaying game for qualitative simulation and cooperative situations related to supply chain management. In: International Conference on HCI in Business, pp. 429–439. Springer International Publishing (2014)Google Scholar
  133. Van der Heijden, H.: User acceptance of hedonic information systems. MIS Q. 28(4), 695–704 (2004)CrossRefGoogle Scholar
  134. VandeWalle, D.: Development and validation of a work domain goal orientation instrument. Educ. Psychol. Measur. 57(6), 995–1015 (1997)CrossRefGoogle Scholar
  135. VandeWalle, D., Cron, W.L., Slocum Jr., J.W.: The role of goal orientation following performance feedback. J. Appl. Psychol. 86(4), 629 (2001)CrossRefGoogle Scholar
  136. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46(2), 186–204 (2000)CrossRefGoogle Scholar
  137. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. Manag. Inf. Syst. 27(3), 425–478 (2003)CrossRefGoogle Scholar
  138. Vesa, M., Hamari, J., Harviainen, J.T., Warmelink, H.: Computer games and organization studies. Org. Stud. 38(2), 273–284 (2017)CrossRefGoogle Scholar
  139. Wack, S.R., Crosland, K.A., Miltenberger, R.G.: Using goal setting and feedback to increase weekly running distance. J. Appl. Behav. Anal. 47(1), 181–185 (2014)CrossRefGoogle Scholar
  140. Wang, X., Schneider, C., Valacich, J.S.: Enhancing creativity in group collaboration: how performance targets and feedback shape perceptions and idea generation performance. Comput. Hum. Behav. 42, 187–195 (2015)CrossRefGoogle Scholar
  141. Whitson, J.R.: Gaming the quantified self. Surveill. Soc. 11(1/2), 163 (2013)Google Scholar
  142. Willemsen, M.C., Graus, M.P., Knijnenburg, B.P.: Understanding the role of latent feature diversification on choice difficulty and satisfaction. User Model. User-Adap. Inter. 26(4), 347–389 (2016)CrossRefGoogle Scholar
  143. Webster, J., Martocchio, J.J.: Microcomputer playfulness: development of a measure with workplace implications. MIS Q. 16(2), 201–226 (1992)CrossRefGoogle Scholar
  144. Wright, B.E.: The role of work context in work motivation: a public sector application of goal and social cognitive theories. J. Public Adm. Res. Theor. 14(1), 59–78 (2004)CrossRefGoogle Scholar
  145. Yee, N.: Motivations of play in online games. J. Cyberpsychol. Behav. 9, 772–775 (2006)CrossRefGoogle Scholar
  146. Yee, N., Ducheneaut, N., Nelson, L.: Online gaming motivations scale: development and validation. In: Proceedings of the SIGCHI conference on human factors in computing systems, pp. 2803–2806. ACM (2012)Google Scholar
  147. Zhang, P.: Technical opinion motivational affordances: reasons for ICT design and use. Commun. ACM 51(11), 145–147 (2008)CrossRefGoogle Scholar
  148. Zimmerman, B.J.: From cognitive modeling to self-regulation: a social cognitive career path. Educ. Psychol. 48(3), 135–147 (2013)MathSciNetCrossRefGoogle Scholar
  149. Zuckerman, O., Gal-Oz, A.: Deconstructing gamification: evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity. Pers. Ubiquit. Comput. 18(7), 1705–1719 (2014)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V., part of Springer Nature 2018

Authors and Affiliations

  1. 1.Gamification Group, Laboratory of Pervasive Computing, Computing and Electrical EngineeringTampere University of TechnologyTampereFinland
  2. 2.Gamification Group, Digital Media, Faculty of HumanitiesUniversity of TurkuPoriFinland
  3. 3.Gamification Group, Tampere Research Center for Information and Media, Faculty of Communication SciencesUniversity of TampereTampereFinland
  4. 4.Information Systems Sciences, Department of Management and OrganizationHanken School of EconomicsHelsinkiFinland
  5. 5.Department of Information and Service EconomyAalto University School of BusinessAaltoFinland

Personalised recommendations