| Pub. Date | : May, 2022 |
|---|---|
| Product Name | : The IUP Journal of Marketing Management |
| Product Type | : Article |
| Product Code | : IJMM010522 |
| Author Name | : Garima Arora and Ashok Kumar |
| Availability | : YES |
| Subject/Domain | : Marketing |
| Download Format | : PDF Format |
| No. of Pages | : 11 |
Several empirical studies have sought to measure the dimensions of service quality of cab aggregators from the perspective of passengers. While many studies have tried to group the items into SERVQUAL scale, a few studies include dimensions related to both traditional cab service quality and service quality of mobile apps to give a holistic picture. Further, most of the studies employ CFA and/or EFA to identify the dimensions. Nonprobability sampling techniques (convenience and purposive sampling) have been used in almost all the previous studies. The paper highlights the lack of consensus among researchers pertaining to these dimensions, thus suggesting the need for further research to refine the measurement criteria of service quality of cab aggregators.
Different modes of transport cater to the needs of travelers, be it intracity or intercity. Taxies are a significant mode of transport, catering to day-to-day requirements (Dong et al., 2017; Li and Szeto, 2019; and Yu et al., 2019). They provide customized service, all-time availability, prompt service, convenience, comfort, last mile connectivity and privacy to the travelers (Schaller, 2007; He and Shen, 2015; Shaaban and Kim, 2016; and Yu et al., 2019). Further, technological advancement has led to development in the existing transportation services (Chen and Nie, 2017). Taxi hailing services allow passengers to hail services using mobile websites/applications. Thus, they basically bring service providers and users on a common platform using information technology (Anderson and Gerbing, 1998; and Katz, 2015). There has been tremendous growth in this sector across the globe (Lee, 2018). Over the years, it has been confirmed by several studies that consumers' preference is biased towards e-hailing services vis-a-vis traditional public transport services (Rayle et al., 2016; Hall and Kruenger, 2018; and Young and Farber, 2019). Cab aggregators rely on smartphones, mobile payment technology and