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Configuring AI-guided sustainable competitive advantage for SMEs through business model innovation: A systematic literature review approach

  • Ariful Islam
  • , Md Asadul Islam
  • , Francesca Dal Mas*
  • , Justyna Fijałkowska
  • , Mahfuzur Rahman
  • , Maurizio Massaro
  • *Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

9 Scopus citations

Abstract

Researchers have been exploring an effective framework for achieving competitive advantage for many years, specifically tailored to small and medium-sized enterprises (SMEs) to ensure their long-term survival. The recent surge in advanced technologies, particularly artificial intelligence (AI), has made their debates more challenging. Thus, the study proposes a conceptual framework specifically designed to leverage AI for long-term competitive advantage in SMEs, examining their business models through this lens. This study conducts a systematic literature review (SLR) to cover a broad range of relevant literature within a final sample of 69 articles. The SLR method was chosen to integrate research in a systematic, transparent, and reproducible way. For qualitative analysis and framework derivation, the study draws on a thematic ontological analysis. The study identifies multiple research streams at the intersection of advanced technology and entrepreneurship aimed at enhancing the competitiveness of SMEs. The primary outcome of this study is the development of a comprehensive business model framework, encompassing both external antecedents (namely, market and industry dynamics, technological infrastructure, government policies and support, strategic alliances, socio-cultural factors) and internal antecedents (digital leadership, dynamic capabilities/adaptability, entrepreneurial mindset, data strategy, growth/resilience), ultimately contributing to sustainable performance. Practically, the study provides a comprehensive avenue for SME owners and managers to adopt and use AI in business strategies and operations. Based on the results, SMEs can implement automation and machine learning to streamline business processes, minimize manual labor, and boost overall operational efficiency. More theoretical and practical implications, along with limitations and future directions, are also discussed, revealing multiple theoretical gateways and an agenda for subsequent empirical work.

Original languageEnglish
Article number101921
JournalJournal of Engineering and Technology Management - JET-M
Volume78
DOIs
StatePublished - 1 Oct 2025

Bibliographical note

Publisher Copyright:
© 2025 The Authors

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • Artificial intelligence
  • Business Model
  • Business strategy
  • Small and medium enterprises
  • Sustainable competitive advantage

ASJC Scopus subject areas

  • Industrial relations
  • General Engineering
  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

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