Title

Analysing online reviews of restaurants in Malaysia: a novel approach to descriptive and predictive analytic

Author Affiliation

Muhammad Mohsin Butt is Professor at Institute of Business Administration (IBA), Karachi

Faculty / School

School of Business Studies (SBS)

Department

Department of Marketing

Was this content written or created while at IBA?

Yes

Document Type

Article

Source Publication

International Journal of Electronic Business

ISSN

14706067

Abstract

This paper aims to develop a model of restaurant products and services quality based on consumer sentiments shared on social networks. We applied term frequency-inverse document frequency (TF-IDF) weighted algorithm to generate empirical entities. These entities were incorporated into hypothetically defined constructs which reflect their thematic and sentimental nature, to test our predictive model using variance-based structural equation modelling. The results suggest that consumers have a positive attitude toward Malaysian restaurants regarding price, hospitality, location, waiting time, food variety, and restaurant atmosphere. Restaurant managers are advised to prioritise their restaurant attributes and manage key attributes to sustain and attract customers. By understanding the relative importance of restaurant reviews, restaurant managers are able to create and maintain competitive advantages in the restaurant industry, ultimately achieving customer loyalty and positive brand image.

Indexing Information

Scopus

Publication Status

Published

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