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Study on the Free Trial of IT Services from Users’ Decision Perspective: A Conceptual Framework

  • Weiling Jiao
  • Hao Chen
  • Yufei Yuan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 513)

Abstract

Nowadays, information technology services (ITS) are offered to individual end users from free to fee, free trial has become a necessary and crucial promotion strategy to many information technology companies, which calls for advancing our understanding on free trial phenomena. In this paper, we define free trial as an inseparable whole process including the initial trial, experience, and fared use stage from users’ decision prospective, and build a theoretical framework conceptualizing the dynamics surrounding users’ decision making in free trial. Using this framework, we further develop the research model; investigate corresponding decision variables and present propositions. The integrated conceptual framework provides a comprehensive understanding of users’ adoption, purchase intentions, and behaviors for ITS promoted by free trial.

Keywords

Free trial IT service Behavior dynamics Three-stage framework 

Notes

Acknowledgements

Science and Technology Department of Jiangsu Province: Study on the integration platform development and key technology of big data on industry in the context of intelligent cloud manufacturing

References

  1. 1.
    Cheng HK, Tang QC (2010) Free trial or no free trial: optimal software product design with network effects. Eur J Oper Res 20(52):437–447CrossRefGoogle Scholar
  2. 2.
    Foubert B, Gijsbrechts E (2016) Try it, you’ll like it—or will you? The perils of early free-trial promotions for high-tech service adoption. Mark Sci 35(5):810–826CrossRefGoogle Scholar
  3. 3.
    Scott CA (1976) The effects of trial and incentives on repeat purchase behavior. J Mark Res 13(3):263–269CrossRefGoogle Scholar
  4. 4.
    Zhu DH, Chang YP (2014) Investigating consumer attitude and intention toward free trials of technology based services. Comput Hum Behav 30:328–334CrossRefGoogle Scholar
  5. 5.
    Cheng HK, Liu Y (2012) Optimal software free trial strategy: the impact of network externalities and consumer uncertainty. Inf Syst Res 23(2):488–504CrossRefGoogle Scholar
  6. 6.
    Kim HW, Chan HC, Gupta S (2007) Value-based adoption of mobile internet: an empirical investigation. Decis Support Syst 43(1):111–126CrossRefGoogle Scholar
  7. 7.
    Kahneman, Tversky A (1979) Prospect theory: an analysis of decision under risk. Econometrica (47):263–291CrossRefGoogle Scholar
  8. 8.
    Oestreicher SG, Zalmanson L (2013) Content or community? A digital business strategy for content providers in the social age. MIS Q 37(2):591–616CrossRefGoogle Scholar
  9. 9.
    Oh H (2016) Free versus for-a -fee of a paywall on the pattern and effectiveness of word-of-mouth via social media. MIS Q 40(1):31–56Google Scholar
  10. 10.
    Bone PF (1995) Word-of-mouth effects on short-term and long-term product judgments. J Bus Res 32(3):213–223CrossRefGoogle Scholar
  11. 11.
    Davis FD (1989) Perceived usefulness, perceived ease of use, and users acceptance of information technology. MIS Q 13(3):319–340CrossRefGoogle Scholar
  12. 12.
    Sriram S, Chintagunta PK, Manchanda P (2015) Service quality variability and termination behavior. Manage Sci 61(11):2739–2759CrossRefGoogle Scholar
  13. 13.
    Bicen P, Madhavaram S (2013) Research on smart shopper feelings. Mark Theor Pract 21(2):221–234CrossRefGoogle Scholar
  14. 14.
    Liu CZ, Yoris AA, Choi HS (2014) Effects of freemium strategy in the mobile app market: an empirical study of google play. J Manage Inf Syst 31(3):326–354CrossRefGoogle Scholar
  15. 15.
    McKinney V, Yoon K, Zahedi F (2002) The measurement of web-customer satisfaction: an expectation and disconfirmation approach. Inf Syst Res 13(3):296–315CrossRefGoogle Scholar
  16. 16.
    Cheng HK, Li S, Liu Y (2015) Optimal software free trial strategy: limited version, time-locked, or hybrid? Prod Oper Manage 24(3):504–517CrossRefGoogle Scholar
  17. 17.
    Vinod P, Jaipur R, Laxmi V (2009) Survey on malware detection methods. In: Proceedings of the 3rd international conferences on software, pp 74–79Google Scholar
  18. 18.
    Bhattacherjee A (2001) Understanding information systems continuance: an expectation confirmation model. MIS Q(25):351–370CrossRefGoogle Scholar
  19. 19.
    Oliver RL, DeSarbo WS (1988) Response determinants in satisfaction judgments. J Consum Res 14:495–507CrossRefGoogle Scholar
  20. 20.
    Csikszentmihalyi M (2000) The costs and benefits of consuming. J Consum Res 27(2):267–272CrossRefGoogle Scholar
  21. 21.
    Su X (2009) A model of consumer inertia with applications to dynamic pricing. Prod Oper Manage 18(4):365–380CrossRefGoogle Scholar
  22. 22.
    Bolton LE, Warlp L, Alba JW (2003) Customer perceptions of price (un)fairness. J Consum Res 29:474–491CrossRefGoogle Scholar
  23. 23.
    Bhattacherjee A, Premkumar G (2004) Understanding changes in belief and attitude toward information technology usage: a theoretical model and longitudinal test. MIS Q 28(2):229–254CrossRefGoogle Scholar
  24. 24.
    Lin K, Lu H (2011) Why people use social networking sites: an empirical study integrating network externalities and motivation theory. Comput Hum Behav 27:1152–1161CrossRefGoogle Scholar
  25. 25.
    Lynch R, Dembo M (2004) The relationship between self-regulation and online learning in a blended learning context. Int Rev Res Open Distrib Learn 5:1–6Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Economics and Management SchoolYancheng Institute of TechnologyYanchengChina
  2. 2.Faculty of Management and EconomicsDalian University of TechnologyDalianChina
  3. 3.DeGroote School of BusinessMcMaster UniversityHamiltonCanada

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