The Impact of Artificial Intelligence on the Efficiency of Artisan Production Cooperatives: Case of Sewing and Embroidery Cooperatives on Fabric and Leather for Moroccan Women

ABSTRACT: In an increasingly competitive global environment, Moroccan artisan cooperatives, particularly those specializing in sewing and embroidery, face significant challenges in maintaining their relevance and efficiency. The integration of advanced technologies, such as Artificial Intelligence (AI), emerges as a strategic solution to enhance their competitiveness. This study seeks to identify and analyze the key factors influencing AI adoption within these cooperatives, aiming to propose targeted solutions to overcome existing barriers. To achieve this, the research employs a methodological approach combining multiple correspondence analysis and binary logistic regression. The study examines variables such as the culture of innovation, members’ digital skills, access to digital infrastructure, public policy support, and the effectiveness of data utilization. The sample consists of 50 women-led cooperatives from various regions across Morocco. The findings reveal that a strong culture of technological innovation, coupled with advanced digital skills and adequate access to digital infrastructure, is essential for the successful adoption of AI. Additionally, effective public policy support and optimal data utilization significantly contribute to enhancing the efficiency and competitiveness of these cooperatives. These results underscore the potential of AI to drive sustainable growth and bolster the global competitiveness of Moroccan artisan cooperatives.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-21
DOI
https://doi.org/10.5281/zenodo.15062713
Primary Topic
Insect and Pesticide Research
Type
article
Field-Weighted Citation Impact
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article

The Impact of Artificial Intelligence on the Efficiency of Artisan Production Cooperatives: Case of Sewing and Embroidery Cooperatives on Fabric and Leather for Moroccan Women

Zenodo (CERN European Organization for Nuclear Research)
Insect and Pesticide Research
article

The Impact of Artificial Intelligence on the Efficiency of Artisan Production Cooperatives: Case of Sewing and Embroidery Cooperatives on Fabric and Leather for Moroccan Women

article en

Abstract

ABSTRACT: In an increasingly competitive global environment, Moroccan artisan cooperatives, particularly those specializing in sewing and embroidery, face significant challenges in maintaining their relevance and efficiency. The integration of advanced technologies, such as Artificial Intelligence (AI), emerges as a strategic solution to enhance their competitiveness. This study seeks to identify and analyze the key factors influencing AI adoption within these cooperatives, aiming to propose targeted solutions to overcome existing barriers. To achieve this, the research employs a methodological approach combining multiple correspondence analysis and binary logistic regression. The study examines variables such as the culture of innovation, members’ digital skills, access to digital infrastructure, public policy support, and the effectiveness of data utilization. The sample consists of 50 women-led cooperatives from various regions across Morocco. The findings reveal that a strong culture of technological innovation, coupled with advanced digital skills and adequate access to digital infrastructure, is essential for the successful adoption of AI. Additionally, effective public policy support and optimal data utilization significantly contribute to enhancing the efficiency and competitiveness of these cooperatives. These results underscore the potential of AI to drive sustainable growth and bolster the global competitiveness of Moroccan artisan cooperatives.

Zenodo (CERN European Organization for Nuclear Research)
Cadi Ayyad University (MA), Université Ibn Zohr (MA), Université Sultan Moulay Slimane (MA)
Industry, innovation and infrastructure
Openalex Percentile: Top 58%
Insect and Pesticide Research
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