Publication details
E-service quality and e-retailers: Attribute-based multi-dimensional scaling
| Authors | |
|---|---|
| Year of publication | 2021 |
| Type | Article in Periodical |
| Magazine / Source | Computers in Human Behavior |
| MU Faculty or unit | |
| Citation | |
| Web | https://www.sciencedirect.com/science/article/pii/S0747563220303551 |
| Doi | http://dx.doi.org/10.1016/j.chb.2020.106608 |
| Keywords | E-retailing; E-service quality; Multi-dimensional scaling; Discriminant analysis; Brand; Website traffic analysis |
| Attached files | |
| Description | Digital retail is a technology-driven business. Customers shop with the help of cutting-edge self-service technologies deployed by marketers to enhance customer experience and e- service quality (e-SQ). However, there is a lack of understanding of how customers differentiate between various digital retailers while shopping. We attempt to compare similarity and dissimilarity between top e-retailers based on customer perception grounded in seven dimensions of e-SQ using data from an important emerging market. Multi-Dimensional Scaling (MDS) technique was applied to analyze similarity judgments of the respondents to draw an aggregate perceptual map of the selected e-retailers. Subsequently, discriminant analysis was carried out and the results were used to create combined spatial maps of e- retailers and e-SQ attributes. It was found that consumers can perceive top e-retailers as similar or isolated brands. Our findings suggest that all seven e-SQ attributes can create differentiation among leading e-retailing brands. However, we recommend e-retailers to fortify their service recovery dimensions, as consumers give greater importance to them. Further, we benchmarked fulfilment and contact as critical dimensions for managing e-SQ from the top two e-retailers (Amazon India and Flipkart) and discussed how they are deploying cutting-edge technologies to beef up these dimensions. |