Service quality dimensions in Austrian food retailing – a text mining approach for physical retail stores

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28120%2F24%3A63576518" target="_blank" >RIV/70883521:28120/24:63576518 - isvavai.cz</a>

Result on the web

<a href="https://www.tandfonline.com/doi/full/10.1080/09593969.2024.2371456" target="_blank" >https://www.tandfonline.com/doi/full/10.1080/09593969.2024.2371456</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1080/09593969.2024.2371456" target="_blank" >10.1080/09593969.2024.2371456</a>

Result language

angličtina

Original language name

Service quality dimensions in Austrian food retailing – a text mining approach for physical retail stores

Original language description

Investigating Service Quality (SQ) and its implications for customer satisfaction has become an increasingly popular research area. Especially in the context of physical grocery retailing, ensuring customer satisfaction has become a key success factor. Most previous research studies apply traditional methods (e.g. surveys) for physical shops and utilize text mining-based approaches mainly for e-commerce. In our paper, we propose a novel approach based on LDA. By combining expert-based word counting analysis with the LDA approach, we confirm that unsupervised text mining based on LDA can be used as a reliable approach to cluster textual comments to SQ dimensions in physical retail settings. We have analyzed over 163,000 publicly available textual customer reviews related to the Austrian market, which is special in terms of its extremely high density of retail outlets, high price levels and a tendency towards traditional form of shopping. Our results show that personal interaction, policies, and product-related aspects seem to be positive drivers of customer satisfaction, while reliability is a clear driver of customer dissatisfaction. Results also show a significantly higher relevance of personal interaction in smaller stores and cities with fewer than 5,000 inhabitants than in other store types and bigger cities. Regarding practical implications, hypermarkets should focus on physical aspects to reduce negative reviews and increase efforts in personal interaction to increase positive reviews. On the other hand, smaller stores should continue to rely on personal interaction to avoid negative reviews and might focus on higher reliability to generate more positive reviews. The applied text-mining approach enables future research with a starting base to analyze SQ dimensions and their relevance in additional countries or area, as e.g. fashion or hardware retail.

Czech name

—

Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

—

OECD FORD branch

50204 - Business and management

Project

—

Continuities

V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

International Review of Retail, Distribution and Consumer Research

ISSN

0959-3969

e-ISSN

1466-4402

Volume of the periodical

neuveden

Issue of the periodical within the volume

neruveden

Country of publishing house

GB - UNITED KINGDOM

Number of pages

36

Pages from-to

1-36

UT code for WoS article

001257385400001

EID of the result in the Scopus database

2-s2.0-85197436316