Gamification Strategies and Customer Churn Reduction in Entrepreneurial Retail Firms: An Empirical Study of Millennials DOI: https://doi.org/10.33093/ijomfa.2026.7.1.10

Main Article Content

Si Chong En
Oo Yu Hock
Nor Azila Mohd Noor
Zheng Feei Ma
Khairul Nizam Mahmud

Abstract

This study investigates the impact of gamification strategies on customer churn reduction in entrepreneurial retail firms, focusing on Millennial consumers in Malaysia’s Klang Valley. Customer churn threatens profitability, particularly for emerging enterprises, and gamification has emerged as a potential tool to enhance customer engagement and retention. Drawing on the Self-Determination Theory, the study examines three gamified marketing interventions: membership programmes, contest rewards, and personalised discounts as direct predictors of churn reduction. A quantitative, cross-sectional research design was employed, using a structured questionnaire distributed to 180 Millennial consumers through purposive sampling. The data were analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) via SmartPLS 4.0. Results indicate that all three gamification strategies significantly reduce customer churn, with contest rewards exerting the strongest influence, followed by personalised discounts and membership programmes. The model demonstrated moderate explanatory power and satisfactory predictive validity based on PLS Predict analysis. The originality of this research lies in its focus on customer churn as a direct behavioural outcome of gamification, rather than the more commonly explored mediators such as loyalty or engagement. Additionally, the study contributes to the evolving application of PLS-SEM by incorporating both explanatory and predictive assessments. The findings offer theoretical advancement and practical guidance for entrepreneurial retailers aiming to enhance retention through gamification-driven strategies tailored to the preferences and behaviours of Millennial consumers.

Article Details

How to Cite
En, S. C., Hock, O. Y. ., Noor, N. A. M. ., Ma, Z. F., & Mahmud, K. N. . (2026). Gamification Strategies and Customer Churn Reduction in Entrepreneurial Retail Firms: An Empirical Study of Millennials: DOI: https://doi.org/10.33093/ijomfa.2026.7.1.10. International Journal of Management, Finance and Accounting, 7(1), 280–311. https://doi.org/10.33093/ijomfa.2026.7.1.10
Section
Management, Finance and Accounting

References

Aldás-Manzano, J., Ruiz-Mafé, C., Sanz-Blas, S., & Lassala-Navarré, C. (2009). Key drivers of internet banking services use. Online Information Review, 33(4), 672–695. https://doi.org/10.1108/14684520910985675.

Alfattah Al Attar, M. M. A. (2024). The impact of digital marketing gamification strategies on consumer behavior in the clothing retail industry (Master’s thesis, Istanbul Sabahattin Zaim University). ProQuest Dissertations & Theses Global. https://www.proquest.com/docview/3186546122.

Amartuvshin, N., Chung, J. F., & Al-Khaled, A. A. S. (2021). Factors Affecting Online Purchase Intention of Gen Y in Klang Valley, Malaysia. International Journal of Academic Research in Business and Social Sciences, 11(4), 983–1034. http://dx.doi.org/10.6007/IJARBSS/v11-i4/9767.

Berger, A., Schlager, T., Sprott, D. E., & Herrmann, A. (2018). Gamified interactions: whether, when, and how games facilitate self–brand connections. Journal of the Academy of Marketing Science, 46, 652-673. https://doi.org/10.1007/s11747-017-0530-0.

Bravo, R., Catalán, S., & Pina, J. M. (2023). The impact of gamified loyalty programmes on customer engagement behaviours. A hotel industry application. Journal of Hospitality and Tourism Technology, 14(5), 925-940. https://doi.org/10.1108/JHTT-02-2022-0033.

Brown, D. M. (2025). How internal marketing can increase the satisfaction and retention of Generation Z employees in the banking sector. International Journal of Bank Marketing. https://doi.org/10.1108/IJBM-01-2024-0049.

Butler, S. (2024). Young people on social media in a globalized world: self-optimization in highly competitive and achievement-oriented forms of life. Frontiers in Psychology, 15, 1340605. https://doi.org/10.3389/fpsyg.2024.1340605.

Castaldo, S. (Ed.). (2024). Customer Loyalty: Theory, Measurement, and Management. EGEA spa.

Cheung, M. L., Pires, G. D., Rosenberger, P. J., & De Oliveira, M. J. (2020). Driving consumer–brand engagement and co-creation by brand interactivity. Marketing Intelligence & Planning, 14(1), 523-541. https://doi.org/10.1108/MIP-12-2018-0587.

Chong, S. E., Lim, X. J., Ng, S. I., & Kamal Basha, N. (2025). Unlocking the enigma of social commerce discontinuation: exploring the approach and avoidance drivers. Marketing Intelligence & Planning. https://doi.org/10.1108/MIP-10-2023-0536.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Lawrence Erlbaum Associates.

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approach (5th ed.). SAGE Publications.

de Boer, E., & Chin, X. Y. (2025). Designing the Best Currency for Your Loyalty Program. In Loyalty Programs and the Currency Effect: A Comprehensive Guide to Realizing the Power of Points (pp. 21-47). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-78849-9_2.

Deci, E. L., & Ryan, R. M. (2000). The “What” and “Why” of Goal Pursuits: Human Needs and the Self-Determination of Behavior. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01.

Dimock, M. (2019). Defining generational cutoffs: The end of Millennials and the rise of Gen Z. Pew Research Center. https://coilink.org/20.500.12592/j9n0zz.

Djafarova, E., & Bowes, T. (2021). ‘Instagram made me buy it’: Generation Z impulse purchases in fashion industry. Journal of Retailing and Consumer Services, 59, 102345. https://doi.org/10.1016/j.jretconser.2020.102345.

Dunn, T. J., Baguley, T., & Brunsden, V. (2014). From alpha to omega: A practical solution to the pervasive problem of internal consistency estimation. British Journal of Psychology, 105(3), 399–412. https://doi.org/10.1111/bjop.12046.

Elhadidy, I. A., Gao, Y., & Elnokrashy, O. M. (2024). Humble leadership: elevating service recovery in hospitality. Management Decision. https://doi.org/10.1108/MD-11-2023-2142.

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104.

Goldberg, R. (2024). Gamification in fashion retail: Assessing contributions to customer loyalty, retention, and brand recall in the South African market. Malaysian E-Commerce Journal (MECJ), 8(2), 51-56. http://doi.org/10.26480/mecj.02.2024.51.56.

Hahn, E. D., & Ang, S. H. (2017). From the editors: New directions in the reporting of statistical results in the Journal of World Business. Journal of World Business, 52(2), 125–126. https://doi.org/10.1016/j.jwb.2016.12.003.

Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2022). Multivariate data analysis (9th ed.). Cengage Learning.

Hamari, J. (2013). Transforming homo economicus into homo ludens: A field experiment on gamification in a utilitarian peer-to-peer trading service. Electronic Commerce Research and Applications, 12(4), 236–245. https://doi.org/10.1016/j.elerap.2013.01.004.

Hasnat, R. (2020). A gamification theory: A study of loyalty enhancement in the retail context (Master’s thesis). Umeå University. Retrieved from https://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172340.

Henseler, J., Ringle, C., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135. https://doi.org/10.1007/s11747-014-0403-8.

Jahan, I., & Sanam, T. F. (2024). A comprehensive framework for customer retention in E-commerce using machine learning based on churn prediction, customer segmentation, and recommendation. Electronic Commerce Research, 1-44. https://doi.org/10.1007/s10660-024-09936-0.

Khodakarami, F., Andrew Petersen, J., & Venkatesan, R. (2024). Customer behavior across competitive loyalty programs. Journal of the Academy of Marketing Science, 52(3), 892-913. https://doi.org/10.1007/s11747-023-00965-z.

Kirgiz, O. B., Kiygi-Calli, M., Cagliyor, S., & El Oraiby, M. (2024). Assessing the effectiveness of OTT services, branded apps, and gamified loyalty giveaways on mobile customer churn in the telecom industry: A machine-learning approach. Telecommunications Policy, 48(8), 102816. https://doi.org/10.1016/j.telpol.2024.102816.

Koivisto, J., & Hamari, J. (2019). The rise of motivational information systems: A review of gamification research. International Journal of Information Management, 45, 191–210. https://doi.org/10.1016/j.ijinfomgt.2018.10.013.

Krishna, S. M., & Agrawal, S. (2024). Creative Performance of Millennials and Generation Z: What Matters More, Intrinsic or Extrinsic Rewards?. Administrative Sciences, 15(1), 11. https://doi.org/10.3390/admsci15010011.

Leclercq, T., Poncin, I., Hammedi, W., Kullak, A., & Hollebeek, L. D. (2020). When gamification backfires: The impact of perceived justice on online community contributions. Journal of Marketing Management, 36(5-6), 550-577. https://doi.org/10.1080/0267257X.2020.1736604.

Lim, W. M., Das, M., Sharma, W., Verma, A., & Kumra, R. (2025). Gamification for sustainable consumption: a state-of-the-art overview and future agenda. Business Strategy and the Environment, 34(1), 1510-1549. https://doi.org/10.1002/bse.4021.

Lipman, S. A. (2024). One size fits all? Designing financial incentives tailored to individual economic preferences. Behavioural Public Policy, 8(2), 264-278. https://doi.org/10.1017/bpp.2020.21.

Rachbini, W., Soeharso, S. Y., Wulandjani, H., Fathoni, M. A., & Rahmawati, E. (2024). From boomers to millennials: unraveling the complexities of online shopping behavior in Indonesia. Innovative Marketing, 20(3), 144-157.

http://dx.doi.org/10.21511/im.20(3).2024.12.

Ramayah, T., Cheah, J., Chuah, F., Ting, H., & Memon, M. A. (2018). Partial least squares structural equation modeling (PLS-SEM) using SmartPLS 3.0: An updated and practical guide to statistical analysis (2nd ed.). Pearson Malaysia.

Razak, I. (2024). Increasing consumer engagement through gamification in marketing campaigns. Journal of Economics and Business (JECOMBI), 4(02), 91-98.

Ringle, C. M., Wende, S., & Becker, J.-M. (2022). SmartPLS 4. Oststeinbek: SmartPLS. Retrieved from https://www.smartpls.com.

Savard, M., & Telahigue, I. (2025). Enhancing Customer Retention in the Mobile Industry: A Problem-Solving Approach. Journal of Consumer Satisfaction, Dissatisfaction and Complaining Behavior, 38(1), 149-166.

Schaarschmidt, M., & Dose, D. B. (2023). Customer engagement in idea contests: Emotional and behavioral consequences of idea rejection. Psychology & Marketing, 40(5), 888-909. https://doi.org/10.1002/mar.21794.

Shahroodi, K., Darestani, S. A., Soltani, S., & Saravani, A. E. (2024). Developing strategies to retain organizational insurers using a clustering technique: Evidence from the insurance industry. Technological Forecasting and Social Change, 201, 123217. https://doi.org/10.1016/j.techfore.2024.123217.

Shmueli, G., Sarstedt, M., Hair, J. F., Cheah, J. H., Ting, H., Vaithilingam, S., & Ringle, C. M. (2019). Predictive model assessment in PLS-SEM: Guidelines for using PLSpredict. European Journal of Marketing, 53(11), 2322–2347. https://doi.org/10.1108/EJM-02-2019-0189.

Shobana, J., Gangadhar, C., Arora, R. K., Renjith, P. N., Bamini, J., & devidas Chincholkar, Y. (2023). E-commerce customer churn prevention using machine learning-based business intelligence strategy. Measurement: Sensors, 27, 100728. https://doi.org/10.1016/j.measen.2023.100728.

Sikri, A., Jameel, R., Idrees, S. M., & Kaur, H. (2024). Enhancing customer retention in telecom industry with machine learning driven churn prediction. Scientific Reports, 14(1), 13097. https://doi.org/10.1038/s41598-024-63750-0.

Tadepally, V., Shivannagari, S., & Nikhileswar, D. (2024). Case studies in churn prediction and customer retention. In K. Hemachandran, D. Choudhury, R. V. Rodríguez, J. A. Wisse, & R. Reyathi (Eds.), Predictive analytics and generative AI for data-driven marketing strategies (1st ed., p. 10). Chapman and Hall/CRC. https://doi.org/10.1201/9781003472544.

Vieira, J., Gomes da Costa, C., & Santos, V. (2024). Talent management and generation z: a systematic literature review through the lens of employer branding. Administrative Sciences, 14(3), 49. https://doi.org/10.3390/admsci14030049.