Factors Affecting Intention to Use Food Order-Delivery Feature of Ride-Hailing Applications: The UTAUT Approach

Abstract

Since ride-hailing platforms in Indonesia provide food order-delivery feature, there has been a change in public spending behavior from conventional to electronic, even on the most basic element, i.e., food. The purpose of this study is to identify critical factors affecting consumers’ adoption of ride-hailing applications to buy food using the Unified Theory of Acceptance and Use of Technology (UTAUT) approach. This study uses a cross-sectional design with a non-probability sampling method. Data was collected from self-administered questionnaire, resulting a total sample of 315 respondents across Indonesia. The respondents are GrabFood and GoFood consumers and the food order-delivery feature of Grab and Gojek (the ride-hailing applications). The study employs PLS-SEM technique to analyze the relationships among variables. The findings show performance expectancy, social influence, and facilitating conditions positively influence behavioral intention to use food order-delivery features in ride-hailing applications. On the other hand, effort expectancy does not influence behavioral intention. The results corroborate the role of food-order feature of ride-hailing applications in the change of Indonesian consumer behavior. Referring to the study results, theoretical contributions and practical implications are provided.

Factors influencing consumers' continued use of food delivery apps in the post-pandemic era: insights from Saudi Arabia

“…Clients appear to be more driven to adopt new technologies if they consider such technologies as useful in their everyday lives (Abed, 2018). PE has been found to be a strong predictor of BI in past studies, particularly in the area of food delivery app acceptance (Lee et al, 2019;Puriwat and Tripopsakul, 2021;Surya et al, 2021). Accordingly, the following hypothesis was developed in the current study.…”

“…In other words, the information given to an individual by others plays a critical role in shaping this individual's awareness of a new technology system and the BI towards it (Dwivedi et al, 2019). SI serves as a key determinant of BI and consumers' propensity to engage with food delivery apps (Palau-Saumell et al, 2019;Puriwat and Tripopsakul, 2021;Surya et al, 2021). Thus, the following hypothesis was developed.…”

Understanding the use of travel and restaurant platforms through the UTAUT2 model

“…Regarding UTAUT-UTAUT2 in analysing TRPs, there are studies in specific fields as tourism apps (Ali et al, 2022;Kamboj and Joshi, 2021;Palos-Sanchez et al, 2021), recommendation tools (Assaker et al, 2020), entertainment (Aranyossy, 2022), restaurants (Nazmi et al, 2022;Palau-Saumell et al, 2019;Surya et al, 2021), or hotel booking (Nawaz et al, 2020;San Martin and Herrero, 2012).…”

“…Facilitating Conditions as variable relates to the users' perception to implement resources and resource to technology in a systematic approach, so it can be satisfactory (Venkatesh et al, 2003(Venkatesh et al, , 2012. In the TRPs area, it is taken into consideration for its impact in user behaviour (San Mart ın and Herrero, 2012;Escobar-Rodr ıguez and Carvajal-Trujillo, 2014;Gupta and Dogra, 2017;Gupta et al, 2018;Surya et al, 2021). Additionally, some studies show that FC lack an inherent effect and should not be taken into consideration (Palos-Sanchez et al, 2021).…”