Please use this identifier to cite or link to this item: http://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1449
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dc.contributor.authorMa, Lan.-
dc.contributor.authorRay, Arghya.-
dc.contributor.authorSharma, Varda.-
dc.contributor.authorBala, Pradip Kumar.-
dc.date.accessioned2022-11-18T12:12:14Z-
dc.date.available2022-11-18T12:12:14Z-
dc.date.issued2022-
dc.identifier.citationMa, 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.issn2321 – 9378-
dc.identifier.urihttp://idr.iimranchi.ac.in:8080/xmlui/handle/123456789/1449-
dc.description.abstractDuring 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.isoenen_US
dc.publisherIMI Konnecten_US
dc.subjectCOVID-19 Pandemicen_US
dc.subjectDelivery Timeen_US
dc.subjectOnline Food Delivery Servicesen_US
dc.subjectService Qualityen_US
dc.subjectStaff Behaviouren_US
dc.subjectIIM Ranchien_US
dc.titleExamining quality aspects in Indian online food delivery 15 services during COVID-19 pandemic: an NLP-based qualitative approachen_US
dc.typeArticleen_US
dc.volume11en_US
dc.issue3en_US
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