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Propelling MSMEs towards automation adoption and sustainable development

Vysakh Kani Kolil et al.

International Journal of Productivity and Performance Management2026https://doi.org/10.1108/ijppm-02-2025-0146article
AJG 1ABDC B
Weight
0.41

Abstract

Purpose This study examines key factors influencing automation adoption among micro, small, and medium enterprises (MSMEs), focusing on the cashew industry. It explores how automation contributes to sustainable development while addressing financial, infrastructural, and digital literacy constraints. Design/methodology/approach Using the Unified Theory of Acceptance and Use of Technology-2 (UTAUT2) framework, data from 234 MSMEs were analyzed via structural equation modeling to assess behavioral intention (BI) and use behavior. Additionally, it maps adoption factors to sustainable development goals (SDGs). Findings Performance expectancy (ß = 0.533), effort expectancy (ß = 0.319), social influence (ß = 0.128), and facilitating condition (ß = 0.156) emerged as the significant predictors of BI. The moderation analysis showed mixed results, with education influencing performance expectancy (p = 0.043), and age (p = 0.001) and operational duration (p = 0.035) influencing effort expectancy. This study reveals that the automation adoption factors contribute to seven SDGs (#4, #8, #9, #10, #12, #16, and #17) through workforce upskilling, improved job conditions, industrial efficiency, sustainable production, financial inclusivity, governance transparency, and business resilience. Originality/value This study is unique in systematically mapping automation adoption factors in MSMEs to SDGs that go beyond economic and industrial outcomes, addressing social equity, governance, and sustainability. Applying UTAUT2 in the cashew sector, it bridges research gaps in digital transformation for resource-constrained industries.

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https://doi.org/https://doi.org/10.1108/ijppm-02-2025-0146

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@article{vysakh2026,
  title        = {{Propelling MSMEs towards automation adoption and sustainable development}},
  author       = {Vysakh Kani Kolil et al.},
  journal      = {International Journal of Productivity and Performance Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1108/ijppm-02-2025-0146},
}

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Evidence weight

0.41

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.25 × 0.4 = 0.10
M · momentum0.55 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.