From words to pixels: text and image mining methods for service research
ISSN: 1757-5818
Article publication date: 9 October 2019
Issue publication date: 15 November 2019
Abstract
Purpose
The purpose of this paper is to describe and position the state-of-the-art of text and image mining methods in business research. By providing a detailed conceptual and technical review of both methods, it aims to increase their utilization in service research.
Design/methodology/approach
On a first stage, the authors review business literature in marketing, operations and management concerning the use of text and image mining methods. On a second stage, the authors identify and analyze empirical papers that used text and image mining methods in services journals and premier business. Finally, avenues for further research in services are provided.
Findings
The manuscript identifies seven text mining methods and describes their approaches, processes, techniques and algorithms, involved in their implementation. Four of these methods are positioned similarly for image mining. There are 39 papers using text mining in service research, with a focus on measuring consumer sentiment, experiences, and service quality. Due to the nonexistent use of image mining service journals, the authors review their application in marketing and management, and suggest ideas for further research in services.
Research limitations/implications
This manuscript focuses on the different methods and their implementation in service research, but it does not offer a complete review of business literature using text and image mining methods.
Practical implications
The results have a number of implications for the discipline that are presented and discussed. The authors provide research directions using text and image mining methods in service priority areas such as artificial intelligence, frontline employees, transformative consumer research and customer experience.
Originality/value
The manuscript provides an introduction to text and image mining methods to service researchers and practitioners interested in the analysis of unstructured data. This paper provides several suggestions concerning the use of new sources of data (e.g. customer reviews, social media images, employee reviews and emails), measurement of new constructs (beyond sentiment and valence) and the use of more recent methods (e.g. deep learning).
Keywords
Acknowledgements
The authors appreciate the help of the doctoral candidate Alec Slepchuk in assisting the compilation of text mining papers.
Citation
Villarroel Ordenes, F. and Zhang, S. (2019), "From words to pixels: text and image mining methods for service research", Journal of Service Management, Vol. 30 No. 5, pp. 593-620. https://doi.org/10.1108/JOSM-08-2019-0254
Publisher
:Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited