What drives e-hailing apps adoption? An analysis of behavioral factors through fuzzy AHP

Abstract

PurposeIn the era of digitalization and technology, tremendous changes have taken place in the taxi industry worldwide. The traditional taxi service has transformed into the latest innovative technology-based e-hailing service. There are innumerable factors that drive the user adoption of e-hailing apps. This study aims to primarily concentrate on identifying, analyzing and ranking these factors which have an impact on the user intention toward using e-hailing apps.Design/methodology/approachThe e-hailing app users in the state of Punjab and Chandigarh are the target population for the study. A fuzzy analytical hierarchy process technique has been applied to analyze and codify the determinants that influence the user intention of adopting e-hailing apps. The primary factors that have been considered for the study are social influence, perceived usefulness, facilitating conditions, perceived ease of use, self-efficacy, perceived risk, compatibility and trust.FindingsThe study revealed that “Perceived Usefulness” is the factor that influences user intention to use e-hailing apps the most, while “Perceived Risk” the least. The sub-criteria codified in the top priority was as follows: “Overall, I find the e-hailing app useful in booking a taxi (C15)”; “I do not need some people to use e-hailing apps (C52); “I believe e-hailing app is compatible with existing technology (C61).” The sub-criterion “E-hailing app service provider keeps its promise (C72)” was demonstrated to have the least impact on the user intention of adopting e-hailing apps.Research limitations/implicationsThe study has been confined to only eight factors selected from the extended technological acceptance model framework and some related technology acceptance theories. Some more other factors may have an impact on user adoption of e-hailing apps, which need to be added further. Also, the scope of the study should be enhanced by expanding the geographical area beyond the selected region.Practical implicationsThe findings of the study enable the e-hailing service providers and marketers to understand the users’ intention in a better way, to make improvements in e-hailing apps and formulate strategies accordingly.Originality/valueThe previous literature provides the base to the present study for identifying the factors affecting user behavioral intention toward e-hailing apps and information technology. The findings and results of the present research make value addition to the existing knowledge base.