Text analytics and new service development: A hybrid thematic analysis with systematic literature review approach

Saeed Rouhani, Saba Sadat Bozorgi, Hannan Amoozad Mahdiraji*, Demetris Vrontis

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose

This study addresses the gap in understanding text analytics within the service domain, focusing on new service development to provide insights into key research themes and trends in text analytics approaches to service development. It explores the benefits and challenges of implementing these approaches and identifies potential research opportunities for future service development. Importantly, this study offers insights to assist service providers to make data-driven decisions for developing new services and optimising existing ones.

Design/methodology/approach

This research introduces the hybrid thematic analysis with a systematic literature review (SLR-TA). It delves into the various aspects of text analytics in service development by analysing 124 research papers published from 2012 to 2023. This approach not only identifies key practical applications but also evaluates the benefits and difficulties of applying text analytics in this domain, thereby ensuring the reliability and validity of the findings.

Findings

The study highlights an increasing focus on text analytics within the service industry over the examined period. Using the SLR-TA approach, it identifies eight themes in previous studies and finds that “Service Quality” had the most research interest, comprising 42% of studies, while there was less emphasis on designing new services. The study categorises research into four types: Case, Concept, Tools and Implementation, with case studies comprising 68% of the total.

Originality/value

This study is groundbreaking in conducting a thorough and systematic analysis of a broad collection of articles. It provides a comprehensive view of text analytics approaches in the service sector, particularly in developing new services and service innovation. This study lays out distinct guidelines for future research and offers valuable insights to foster research recommendations.
Original languageEnglish
Number of pages41
JournalEuroMed Journal of Business
Early online date17 Sept 2024
DOIs
Publication statusE-pub ahead of print - 17 Sept 2024

Keywords

  • Text Analytics
  • Service Quality
  • Sentiment Analysis
  • Topic Modeling
  • Systematic Review

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