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The role of food apps servitization on repurchase intention: A study of FoodPanda

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  • Yeo, Sook Fern
  • Tan, Cheng Ling
  • Teo, Shen Long
  • Tan, Kim Hua

Abstract

With the exponential growth of smartphone applications (apps), companies have embraced the new concept of platform service supply chain (PSSC). The food industry in particular has quickly adopted this concept through the use of food apps, such as Foodpanda, which is becoming popular among consumers when it comes to ordering food in Malaysia. As such, this study investigated the relationships between factors that drive customer repurchase intention in food delivery apps within the context of Malaysia. Data were collected from 250 respondents between October 2019 and January 2020. This study will employ a non-probability purposive sampling. In this study, two statistical analysis techniques were used for data analysis and testing of hypothesis, namely, Statistic Package for Social Science (SPSS) version 25 and Partial Least Square Structural Equation Modeling (PLS-SEM) version 3.2.9. As a result, perceived usefulness, social influence, and trust displayed a significant and positive influence on customer repurchase intention for food apps. The outcomes retrieved from the importance-performance matrix analysis (IPMA) revealed that both importance and performance of perceived usefulness highly contributed to customer repurchase intention for food apps. This research has important implications for Foodpanda to continuously improve its food delivery apps service platform and achieve customer satisfaction, leading to repurchase intention. Having that said, this study sheds new light on the platform serviceability within the food industry.

Suggested Citation

  • Yeo, Sook Fern & Tan, Cheng Ling & Teo, Shen Long & Tan, Kim Hua, 2021. "The role of food apps servitization on repurchase intention: A study of FoodPanda," International Journal of Production Economics, Elsevier, vol. 234(C).
    • Handle: RePEc:eee:proeco:v:234:y:2021:i:c:s0925527321000396
    DOI: 10.1016/j.ijpe.2021.108063
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    2. Dogra, Nikhil & Adil, Mohd & Sadiq, Mohd & Dash, Ganesh & Paul, Justin, 2023. "Unraveling customer repurchase intention in OFDL context: An investigation using a hybrid technique of SEM and fsQCA," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
    3. Meena, Purushottam & Kumar, Gopal, 2022. "Online food delivery companies' performance and consumers expectations during Covid-19: An investigation using machine learning approach," Journal of Retailing and Consumer Services, Elsevier, vol. 68(C).
    4. Yeo, Sook Fern & Tan, Cheng Ling & Kumar, Ajay & Tan, Kim Hua & Wong, Jee Kit, 2022. "Investigating the impact of AI-powered technologies on Instagrammers’ purchase decisions in digitalization era–A study of the fashion and apparel industry," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    5. Kolagar, Milad & Parida, Vinit & Sjödin, David, 2022. "Ecosystem transformation for digital servitization: A systematic review, integrative framework, and future research agenda," Journal of Business Research, Elsevier, vol. 146(C), pages 176-200.
    6. Tsai, Pei-Hsuan & Chen, Chih-Jou & Hsiao, Wei-Hung & Lin, Chin-Tsai, 2023. "Factors influencing the consumers’ behavioural intention to use online food delivery service: Empirical evidence from Taiwan," Journal of Retailing and Consumer Services, Elsevier, vol. 73(C).
    7. Charpin, Remi & Lee, Min Kyung & Wu, Ting, 2021. "Mobile procurement platforms: Bridging the online and offline worlds in China's restaurant industry," International Journal of Production Economics, Elsevier, vol. 241(C).

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