Menu Expand

How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans

  1. Journals
  2. Economics, Finance, Business & Management
  3. Zeitschrift für die gesamte Versicherungswissenschaft
  4. Vol. 112, Issue 3
  5. pp. 281–306

JOURNAL ARTICLE

Cite JOURNAL ARTICLE

Style
Unger, F. How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans. Zeitschrift für die gesamte Versicherungswissenschaft, 112(3), 281-306. https://doi.org/10.3790/zverswiss.2023.1426401
Unger, Franziska "How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans" Zeitschrift für die gesamte Versicherungswissenschaft 112.3, 2023, 281-306. https://doi.org/10.3790/zverswiss.2023.1426401
Unger, Franziska (2023): How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans, in: Zeitschrift für die gesamte Versicherungswissenschaft, vol. 112, iss. 3, 281-306, [online] https://doi.org/10.3790/zverswiss.2023.1426401
Format
Download

How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans

Unger, Franziska

Zeitschrift für die gesamte Versicherungswissenschaft, Vol. 112 (2023), Iss. 3 : pp. 281–306

Read Now Download (PDF)

Additional Information

Article Details

Publisher Name
Duncker & Humblot
DOI
https://doi.org/10.3790/zverswiss.2023.1426401
Language
German
Pages
26

Author Details

Dr. Franziska Unger, M.Sc., Lehrstuhl für Betriebswirtschaftslehre, insbesondere Versicherungsmarketing, Rechts- und Wirtschaftswissenschaftliche Fakultät, Friedrich-Alexander-Universität Erlangen-Nürnberg, Lange Gasse 20, 90403 Nürnberg.

References

  1. Ajzen, I. (1991): The theory of planned behavior. Organ. Behav. Hum. Decis. Process. 50(2), 179–211.  Google Scholar
  2. Ajzen, I./Madden, T. J. (1986): Prediction of goal-directed behavior: Attitudes, intentions, and perceived behavioral control. J. Exp. Soc. Psychol. 22(5), 453–474.  Google Scholar
  3. Alami, H./Rivard, L./de Oliveira, R. R./Lehoux, P./Cadeddu, S. B. M./Savoldelli, M./Ag Ahmed, M. A./Fortin, J.-P. (2020): Guiding pay-as-you-live health insurance models toward responsible innovation in health. J. Particip. Med. 12(3).  Google Scholar
  4. Berger, I.E./Ratchford, B. T./Haines, G. H. (1994): Subjective product knowledge as a moderator of the relationship between attitudes and purchase intentions for a durable product. J. Econ. Psychol. 15(2), 301–314.  Google Scholar
  5. Bleier, A./Eisenbeiss, M. (2015): The importance of trust for personalized online advertising. J. Retail. 91(3), 390–409.  Google Scholar
  6. Chen, Y./Pu, P. (2014): HealthyTogether: Exploring social incentives for mobile fitness applications. ACM International Conference Proceeding Series, 25–34.  Google Scholar
  7. Coelho, P. S./Henseler, J. (2012): Creating customer loyalty through service customization. Eur. J. Mark. 46(3/4), 331–35.  Google Scholar
  8. Courneya, K. S./Bobick, T. M./Schinke, R. J. (1999): Does the theory of planned behavior mediate the relation between personality and exercise behavior?. Basic Appl. Soc. Psychol. 21(4), 317–324.  Google Scholar
  9. Deci, E. L./Ryan, R. M./Koestner, R. (1999): A meta-analytic review of experiments examining the effects of extrinsic rewards on intrinsic motivation. Psychol. Bull. 125(6), 627–668.  Google Scholar
  10. Eling, M./Kraft, M. (2020): The impact of telematics on the insurability of risks. J. Risk Financ. 21(2), 77–109.  Google Scholar
  11. German Federal Ministry of Health: Prevention. https://www.bundesgesundheitsministerium.de/service/begriffe-von-a-z/p/praevention.html (2023). Accessed 11 January 2023.  Google Scholar
  12. Gould, S. J. (1988): Consumer attitudes toward health and health care: a differential perspective. J. Consum. Aff. 22(1), 96–118.  Google Scholar
  13. Hamari, J./Hassan, L./Dias, A. (2018): Gamification, quantified-self or social networking? Matching users ’ goals with motivational technology. User Model. User-Adapt. Interact. 28(1), 35–74.  Google Scholar
  14. Hamari, J./Koivisto, J. (2014): Measuring flow in gamification: Dispositional flow scale-2. Comput. Hum. Behav. 40, 133–143.  Google Scholar
  15. Hamari, J./Koivisto, J. (2015): “Working out for likes”: An empirical study on social influence in exercise gamification. Comput. Hum. Behav. 50, 333–347.  Google Scholar
  16. Holsapple, C. W./Wu, J. (2007): User acceptance of virtual worlds: The hedonic framework. Data Base Adv. Inf. Syst. 38(4), 86–89.  Google Scholar
  17. Johnson, D./Deterding, S./Kuhn, K. A./Staneva, A./Stoyanov, S./Hides, L. (2016): Gamification for health and wellbeing: A systematic review of the literature. Internet Invent. 6, 89–106.  Google Scholar
  18. Jones, B. A./Madden, G. J./Wengreen, H. J. (2014): The FIT Game: Preliminary evaluation of a gamification approach to increasing fruit and vegetable consumption in school. Prev. Med. 68, 76–79.  Google Scholar
  19. Knaack, N. (2007): Chancen und Grenzen der Bonifizierung von Gesundheitsverhalten in der Gesetzlichen Krankenversicherung: eine theoretische und empirische Analyse. Dissertation, Universität Dortmund.  Google Scholar
  20. Lee, B. C. Y. (2012): The determinants of consumer attitude toward service innovation – the evidence of ETC system in Taiwan. J. Serv. Mark. 26(1), 9–19.  Google Scholar
  21. Lee, J./Kim, J./Choi, J. Y. (2019): The adoption of virtual reality devices: The technology acceptance model integrating enjoyment, social interaction, and strength of the social ties. Telemat. Inform. 39, 37–48.  Google Scholar
  22. Lewis, Z. H./Swartz, M. C./Lyons, E. J. (2016): What’s the point?: A review of reward systems implemented in gamification interventions. Games Health J. 5(2), 93–99.  Google Scholar
  23. Lupton, D. (2017): Self-tracking, health and medicine. Health Sociol. Rev. 26(1), 1–5.  Google Scholar
  24. Morschheuser, B./Riar, M./Hamari, J./Maedche, A. (2017): How games induce cooperation? A study on the relationship between game features and we-intentions in an augmented reality game. Comput. Hum. Behav. 77(August), 169–183.  Google Scholar
  25. op den Akker, H./Jones, V. M./Hermens, H. J. (2014): Tailoring real-time physical activity coaching systems: a literature survey and model. User Model. User-Adapt. Interact. 24(5), 351–392.  Google Scholar
  26. Park, J. K./John, D. R. (2014): I think I can, I think I can: Brand use, self-efficacy, and performance. J. Mark. Res. 51(2), 233–247.  Google Scholar
  27. Pereira, P./Duarte, E./Rebelo, F./Noriega, P. (2014): A Review of Gamification for Health-Related Contexts. In: Marcus, A. (eds.), Design, User Experience, and Usability. User Experience Design for Diverse Interaction Platforms and Environments. DUXU 2014. Lecture Notes in Computer Science, vol 8518. Springer, Cham.  Google Scholar
  28. Ryu, G./Feick, L. (2007): A penny for your thoughts: referral reward programs and referral likelihood.J. Mark. 71(1), 84–94.  Google Scholar
  29. Scherenberg, V./Greiner, W. (2008a): Bonusprogramme – Zwischen Wettbewerb und Prävention. Gesundh. Sozpolit. 62(3), 19–25.  Google Scholar
  30. Scherenberg, V./Greiner, W. (2008b): Präventive Bonusprogramme: Auf dem Weg zur Überwindung des Präventionsdilemmas. Hans Huber, Bern.  Google Scholar
  31. Sihler, P./Voeth, M. (2019): Der Preis der Freiheit – Analyse der Kundenakzeptanz verhaltensabhängiger Preise. Schmalenbachs Z. betriebwirtsch. Forsch. 71(1), 45–78.  Google Scholar
  32. Techniker Krankenkasse: TK-Bonusprogramm. https://www.tk.de/techniker/gesundheit-und-medizin/praevention-und-frueherkennung/tk-bonusprogramm-2024580 (2023). Accessed 13 January 2023.  Google Scholar
  33. Trope, Y./Liberman, N. (2010): Construal-level theory of psychological distance. Psychol. Rev. 117(2), 440–463.  Google Scholar
  34. Unger, F./Steul-Fischer, M. (2023): Rewards for a healthy lifestyle: The impact of reward type and timing in pay-as-you-live pricing. Mark. ZFP. 45(1), 66-84.  Google Scholar
  35. Venkatesh, V. (2000): Determinants of perceived ease of use: Integrating control, intrinsic motivation, acceptance model. Inf. Syst. Res. 11(4), 342–365.  Google Scholar
  36. Wiegard, R. B./Breitner, M. H. (2019): Smart services in healthcare: A risk-benefit-analysis of pay-as-you-live services from customer perspective in Germany. Electron. Mark. 29(1), 107–123.  Google Scholar
  37. Wiegard, R./Guhr, N./Krylow, S./Breitner, M. H. (2019): Analysis of wearable technologies’ usage for pay-as-you-live tariffs: recommendations for insurance companies. Z. gesamte Versicherungswiss. 108(1), 1–26.  Google Scholar
  38. Wulf, N./Betz, S. (2021): Daten-Ökosysteme wider Willen: Herausforderungen des Pay-as-you-live-Geschäftsmodells im Kontext deutscher Krankenversicherungen. HMD Prax. Wirtschaftsinform. 58(3), 494–506.  Google Scholar
  39. Zhu, Y./Dailey, S. L./Kreitzberg, D./Bernhardt, J. (2017): “Social networkout”: connecting social features of wearable fitness trackers with physical exercise. J. Health Commun. 22(12), 974–980.  Google Scholar
  40. Zuckerman, O./Gal-Oz, A. (2014): Deconstructing gamification: evaluating the effectiveness of continuous measurement, virtual rewards, and social comparison for promoting physical activity. Pers. Ubiquitous Comput. 18(7), 1705–1719.  Google Scholar

Abstract

Krankenversicherungsanbieter versuchen zunehmend, die Konsumenten zu einem gesunden Lebensstil zu motivieren, indem sie Belohnungsmechanismen in ihre Preisgestaltung und Services aufnehmen. Folglich entwickelten sich sogenannte Pay-as-you-live (PAYL) Tarife in der Krankenversicherung, welche das Potenzial haben, die langfristigen Kosten für die Versicherer zu senken, indem sie eine gesündere Lebensweise der Konsumenten fördern. PAYL Tarife belohnen gesundheitsfördernde Verhaltensweisen (z. B. Krebsvorsorge, körperliche Aktivität) der Verbraucher mit einem Rabatt auf die Versicherungsprämie oder mit Geld- oder Sachprämien. Die optimale Ausgestaltung derartiger Tarife wurde bisher aufgrund der Neuartigkeit wenig erforscht. Die Ergebnisse einer experimentellen Studie zeigen, dass Konsumenten eine höhere gesundheitsförderliche Verhaltensintention angeben, wenn Aktivitäten mit hoher Regelmäßigkeit (z.B. körperliche Aktivität) belohnt werden im Vergleich zu Aktivitäten mit geringer Regelmäßigkeit (z.B. Krebsvorsorge). Ferner ist die Einstellung der Verbraucher gegenüber PAYL Tarifen positiver, wenn bei Aktivitäten mit hoher Regelmäßigkeit keine sozialen Interaktionselemente eingesetzt werden, als wenn diese vorhanden sind. Je positiver die Einstellung der Konsumenten gegenüber einem PAYL Tarif, desto stärker ist die gesundheitsförderliche Verhaltensintention.

Table of Contents

Section Title Page Action Price
Franziska Unger: How the Type of Activity and the Inclusion of Social Interaction Affect Customers’ Health Behavior Intentions and Attitudes to Pay-As-You-Live Plans 281
Abstract 281
Zusammenfassung 281
1. Introduction 282
2. Theoretical Background 284
2.1 Type of Activity Rewarded 284
2.2 Elements of Social Interaction 286
3. Experimental Study 288
3.1 Method 288
3.2 Results 289
4. General Discussion 293
4.1 Theoretical Implications 293
4.2 Managerial Implications 294
4.3 Limitations and Future Research Directions 295
References 296
Appendix 299

Contact

Duncker & Humblot GmbH Carl-Heinrich-Becker-Weg 9 12165 Berlin, Deutschland T: +49 30 790006-0

Quick Navigation

2024 Duncker & Humblot GmbH

Powered by CloudPublish

We use cookies to ensure that you get the best experience on our website. Learn more about how we use cookies.