Empowering Nanostores for Competitiveness and Sustainable Communities in Emerging Countries: A Generative Artificial Intelligence Strategy Ideation Process

David Ernesto Salinas-Navarro*, Eliseo Vilalta-Perdomo, Rosario Michel-Villarreal

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

This exploratory study investigates Generative Artificial Intelligence’s (GenAI) use in strategy ideation for nanostores—i.e., small independent grocery retailers—to enhance their competitiveness while contributing to community sustainability. Nanostores, particularly in emerging countries, face intense competition and rapidly changing trends. These stores adopt various strategies by leveraging their proximity to consumers in neighbourhoods, resulting in different business configurations. While the existing literature highlights the broader nanostores’ functions, there is limited research on how they may develop comprehensive strategies to face their challenges. By employing a thing ethnography methodology, this work proposes GenAI thing interviewing—i.e., with ChatGPT 3.5 and Microsoft Copilot—through incremental prompting to explore potential strategy ideation and practices. Key findings suggest GenAI conversations can aid shopkeepers in strategy ideation through human-like written language, aligning with small business dynamics and structures. This proposition results in a GenAI ideation framework for strategy generation and definition. Moreover, this technology can enhance nanostore competitiveness and sustainability impact by enacting improved strategy practices in stakeholder engagements. Accordingly, this work’s main contribution underscores a GenAI-enabled conversational approach to facilitate nanostores’ strategy ideation and embedding in everyday business operations. Future work must address the limitations and further investigate GenAI’s influence on human understanding and technological creation, strategy ideation, adoption, and usability in nanostores.
Original languageEnglish
Article number11244
Number of pages28
JournalSustainability
Volume16
Issue number24
Early online date21 Dec 2024
DOIs
Publication statusPublished - Dec 2024

Bibliographical note

Copyright © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

Keywords

  • emerging countries
  • strategy
  • generative artificial intelligence
  • small businesses
  • competitiveness
  • community sustainability

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