Logo PTI Logo icrmat

Proceedings of the 2022 International Conference on Research in Management & Technovation

Annals of Computer Science and Information Systems, Volume 34

Between app efficiency and user wellbeing: a cluster analysis on consumer types and continuance usage of food delivery app


DOI: http://dx.doi.org/10.15439/2022M7606

Citation: Proceedings of the 2022 International Conference on Research in Management & Technovation, Viet Ha Hoang, Vijender Kumar Solanki, Nguyen Thi Hong Nga, Shivani Agarwal (eds). ACSIS, Vol. 34, pages 6974 ()

Full text

Abstract. The introduction of food delivery apps, facilitated by the global pandemic, has created a significant disruption in the hospitality industry. However, how consumers use mobile applications in the context of daily choices and food consumption has not been fully explored. Using data collected through an online questionnaire comprising 165 food delivery app subscribers, k-mean cluster analysis was performed to classify users based on their internal motivations. The results reveal three distinct groups: Health-conscious Eaters, Food Enthusiasts, and Lifetime Diners. Practically, the present exploratory study assists FDA providers to better identify customers, so potentially optimizing marketing initiatives, and maximizing profitability.


  1. Zhang, S., Pauwels, K., & Peng, C. (2019). The impact of adding online-to-offline service platform channels on firms' offline and total sales and profits. Journal of Interactive Marketing, 47, 115-128.
  2. Chotigo, J., & Kadono, Y. (2021). Comparative analysis of key factors encouraging food delivery app adoption before and during the COVID-19 pandemic in Thailand. Sustainability, 13(8), 4088
  3. Kumar, S., Jain, A., & Hsieh, J.-K. (2021). Impact of apps aesthetics on revisit intentions of food delivery apps: The mediating role of pleasure and arousal. Journal of Retailing and Consumer Services, 63, 102686.
  4. Al Amin, M., Arefin, M. S., Alam, M. R., Ahammad, T., & Hoque, M. R. (2021). Using mobile food delivery applications during COVID-19 pandemic: an extended model of planned behavior. Journal of Food Products Marketing, 27(2), 105-126.
  5. Coppola, D. (2022). Estimated online food delivery market size worldwide from 2022 to 2027. Retrieved from https://www.statista.com/statistics/1170631/online-food-delivery-market-size-worldwide/
  6. Tandon, A., Kaur, P., Bhatt, Y., Mäntymäki, M., & Dhir, A. (2021). Why do people purchase from food delivery apps? A consumer value perspective. Journal of Retailing and Consumer Services, 63, 102667.
  7. Rana, P. (2022). Uber Eats, DoorDash Offer New Deals to Court Customers as Growth Cools. Retrieved from https://www.wsj.com/articles/growth-cools-at-once-hot-food-delivery-apps-uber-eats-and-doordash-11658340167
  8. Curry, D. (2022). Food Delivery App Revenue and Usage Statistics (2022). Retrieved from https://www.businessofapps.com/data/food-delivery-app-market/
  9. Perri, J. (2022). Which company is winning the restaurant food delivery war? Retrieved from https://secondmeasure.com/datapoints/food-delivery-services-grubhub-uber-eats-doordash-postmates/
  10. Rong-Da Liang, A., & Lim, W. M. (2011). Exploring the online buying behavior of specialty food shoppers. International Journal of Hospitality Management, 30(4), 855-865.
  11. Chawla, D., & Joshi, H. (2017). Consumer perspectives about mobile banking adoption in India–a cluster analysis. International Journal of Bank Marketing.
  12. Ariguzo, G., & White, D. S. (2011). Africa's Mobile Commerce Segments: A Model-Based Cluster Analysis. Review of Business Research, 11(4), 38-44.
  13. Neunhoeffer, F., & Teubner, T. (2018). Between enthusiasm and refusal: A cluster analysis on consumer types and attitudes towards peer‐to‐peer sharing. Journal of Consumer Behaviour, 17(2), 221-236.
  14. Chen, H.-S., Liang, C.-H., Liao, S.-Y., & Kuo, H.-Y. (2020). Consumer attitudes and purchase intentions toward food delivery platform services. Sustainability, 12(23), 10177.
  15. Ray, A., Dhir, A., Bala, P. K., & Kaur, P. (2019). Why do people use food delivery apps (FDA)? A uses and gratification theory perspective. Journal of Retailing and Consumer Services, 51, 221-230.
  16. Kumar, S., & Shah, A. (2021). Revisiting food delivery apps during COVID-19 pandemic? Investigating the role of emotions. Journal of Retailing and Consumer Services, 62, 102595.
  17. Zhao, Y., & Bacao, F. (2020). What factors determining customer continuingly using food delivery apps during 2019 novel coronavirus pandemic period? International Journal of Hospitality Management, 91, 102683.
  18. Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and system quality: an empirical examination within the context of data warehousing. Journal of management information systems, 21(4), 199-235.
  19. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of management information systems, 19(4), 9-30.
  20. Alalwan, A. A. (2020). Mobile food ordering apps: An empirical study of the factors affecting customer e-satisfaction and continued intention to reuse. International Journal of Information Management, 50, 28-44.
  21. Peters, T., Işık, Ö., Tona, O., & Popovič, A. (2016). How system quality influences mobile BI use: The mediating role of engagement. International Journal of Information Management, 36(5), 773-783.
  22. Kapoor, A. P., & Vij, M. (2018). Technology at the dinner table: Ordering food online through mobile apps. Journal of Retailing and Consumer Services, 43, 342-351.
  23. Diener, E. (2009). Subjective well-being. The science of well-being, 11-58.
  24. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological bulletin, 125(2), 276.
  25. Diener, E., Sapyta, J. J., & Suh, E. (1998). Subjective well-being is essential to well-being. Psychological inquiry, 9(1), 33-37.
  26. Kim, M. J., Lee, C. K., & Preis, M. W. (2020). The impact of innovation and gratification on authentic experience, subjective well-being, and behavioral intention in tourism virtual reality: The moderating role of technology readiness. Telematics and Informatics, 49, 101349.
  27. Stankov, U., Filimonau, V., Gretzel, U., & Vujičić, M. D. (2020). E-mindfulness–the growing importance of facilitating tourists’ connections to the present moment. Journal of Tourism Futures, 6(3), 239-245.
  28. Cecchinato, M. E., Rooksby, J., Hiniker, A., Munson, S., Lukoff, K., Ciolfi, L., . . . Harrison, D. (2019). Designing for digital wellbeing: A research & practice agenda. Paper presented at the Extended abstracts of the 2019 CHI conference on human factors in computing systems.
  29. Gaggioli, A., Riva, G., Peters, D., & Calvo, R. A. (2017). Positive technology, computing, and design: shaping a future in which technology promotes psychological well-being. In Emotions and affect in human factors and human-computer interaction (pp. 477-502): Elsevier.
  30. Wang, Y.-S., Tseng, T. H., Wang, W.-T., Shih, Y.-W., & Chan, P.-Y. (2019). Developing and validating a mobile catering app success model. International Journal of Hospitality Management, 77, 19-30.
  31. Wang, Y. S. (2008). Assessing e‐commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Information Systems Journal, 18(5), 529-557.
  32. Diener, E., Emmons, R. A., Larsen, R. J., & Griffin, S. (1985). The satisfaction with life scale. Journal of personality assessment, 49(1), 71-75
  33. Kim, J. J., Nam, M., & Kim, I. (2019). The effect of trust on value on travel websites: Enhancing well-being and word-of-mouth among the elderly. Journal of Travel & Tourism Marketing, 36(1), 76-89.
  34. Finch, W. H. (2019). A Comparison of Clustering Methods when Group Sizes are Unequal, Outliers are Present, and in the Presence of Noise Variables. General Linear Model Journal, 45(1), 13.
  35. Nelson, A. (2020). Reaching the new healthy consumer. Retrieved from https://www.foodbusinessnews.net/articles/16376-reaching-the-new-healthy-consumer