Acceptance and Satisfaction of Food Waste Mobile Application in a Developing Country: Insights from Extended UTAUT2 and IPMA

Food waste is a major global problem and has prompted the development of digital solutions such as food waste mobile applications (FWMA). However, factors influencing the user adoption of these applications, especially in developing countries, remain unexplored. The purpose of this study is to analyze existing behavior towards FWMA and modeling factors that influence acceptance of FWMA in the developing country - Indonesia, while also observing efforts to improve its effectiveness and user satisfaction. To achieve this, an acceptance model is developed using the Extended Unified Acceptance and Use Theory 2 (UTAUT2 Extended) model. Moreover, the Importance-Performance Matrix Analysis (IPMA) framework is used to identify areas for improvement and prioritize efforts to increase customer satisfaction in the application of the FWMA. A preliminary sample of 79 respondents completed an online questionnaire consisting of 30 questions and using a five-point Likert scale with anchor values of strongly agree and strongly disagree. The results show that the average frequency of purchases made by respondents via the FWMA system is relatively low, i.e., three or less per month, and that the majority of respondents learnt about the FWMA system from social media and their friends. As far as demographic data is concerned, women are more likely to use the FWMA than men. In particular, according to the UTAUT2 Extended Model, factors influencing satisfaction with the use of FWMA include social influence, habit and trust; furthermore, satisfaction and different food choices influence the intention to use the use of FWMA. Finally, the IPMA results reinforce the focus on increasing satisfaction through diversified food choices by providing a framework for developers and policy makers to support the uptake of the FWMA in developing economies by building trust, promoting habits and strategically increasing food diversity.