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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

Authors: Atitaou Asmae; Boulkhir Layla; Assi Driss; Touhami Fatima; Hamidi Charaf;

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.

Keywords

Artificial Intelligence, cooperative efficiency, technological innovation, digital skills, binary logistic regression.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green