dc.contributor.author |
Ma, Lan. |
|
dc.contributor.author |
Ray, Arghya. |
|
dc.contributor.author |
Sharma, Varda. |
|
dc.contributor.author |
Bala, Pradip Kumar. |
|
dc.date.accessioned |
2022-11-18T12:12:14Z |
|
dc.date.available |
2022-11-18T12:12:14Z |
|
dc.date.issued |
2022 |
|
dc.identifier.citation |
Ma, L., Ray, A., Sharma, V., & Bala, P. K. (2022). Examining quality aspects in Indian online food delivery 15 services during COVID-19 pandemic: an NLP-based qualitative approach. IMI Konnect. 11 (3), 15-30. |
|
dc.identifier.issn |
2321 – 9378 |
|
dc.identifier.uri |
http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1449 |
|
dc.description.abstract |
During the COVID-19 pandemic, as people were forced to stay indoors due to lockdowns and
government restrictions, accessing restaurants was mostly possible through online food delivery services
(OFDs). With the increase in demand, it was also observed that the OFDs were charging higher prices.
To examine quality aspects of Indian OFDs during the COVID-19 pandemic, we have used a multimethod approach utilizing qualitative data from 19 customers about two OFDs in India (C1 and C2)
and online customer reviews from C1 (2,00,011) and C2 (86,931). Results show that during the
pandemic although consumers were happy about the ease of use of the platforms, customers have
expressed concerns related to delayed services, the behaviour of staff and limited options to choose from.
We have also linked to different dimensions of SERVQUAL to understand the factors that people have
mostly discussed about OFDs in the COVID-19 pandemic. The study concludes with various
implications. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
IMI Konnect |
en_US |
dc.subject |
COVID-19 Pandemic |
en_US |
dc.subject |
Delivery Time |
en_US |
dc.subject |
Online Food Delivery Services |
en_US |
dc.subject |
Service Quality |
en_US |
dc.subject |
Staff Behaviour |
en_US |
dc.subject |
IIM Ranchi |
en_US |
dc.title |
Examining quality aspects in Indian online food delivery 15 services during COVID-19 pandemic: an NLP-based qualitative approach |
en_US |
dc.type |
Article |
en_US |
dc.volume |
11 |
en_US |
dc.issue |
3 |
en_US |