Adopting the CATALYST Framework: A sociotechnical approach to business intelligence in agricultural SMEs in developing economies

Small agribusiness SMEs in resource-constrained economies cannot extensively utilize BI decision support systems for they pose barriers. This paper provides a theoretical synthesis for building a sociotechnical framework around the multifaceted challenges and opportunities affecting BI adoption in this context. Building up from sociotechnical systems theory, the Technology-Organization-Environment (TOE) framework, dynamic capabilities framework, and resource-based view, we conceptualize the CATALYST (Context-aware Adaptive Technology Adoption for Limited-resource Yet Sustainable Transformation) framework. The framework focuses on how technological capabilities and organizational preparedness, human and social dynamics, and constraints in the environment interrelate. The CATALYST framework promotes the technical and socio-economic alignment of solutions through an adaptive five-step process consisting of Context Assessment, Alignment Strategy Development, Adaptive Implementation, Learning and Evolution, and Transformation Consolidation, beyond mere digital transformation to inclusive and sustainable transformation. This synthesis extends the innovation adoption theory and digital agriculture frameworks, alongside practical considerations for policymakers and stakeholders through whose endeavors BI might be accomplished throughout developing regions.

Authors

Publication Details

Journal
World Journal of Advanced Engineering Technology and Sciences
Published
2025-06-17
DOI
https://doi.org/10.30574/wjaets.2025.15.3.1020
Citations
3
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
6.85
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article

Adopting the CATALYST Framework: A sociotechnical approach to business intelligence in agricultural SMEs in developing economies

Anup Ghimire, Shristi Shrestha, R. N. Leslie, Praveen Jain
3 citations
World Journal of Advanced Engineering Technology and Sciences
Big Data and Business Intelligence
6.85
article

Adopting the CATALYST Framework: A sociotechnical approach to business intelligence in agricultural SMEs in developing economies

Anup Ghimire, Shristi Shrestha, R. N. Leslie, Praveen Jain
article en
3 citations

Abstract

Small agribusiness SMEs in resource-constrained economies cannot extensively utilize BI decision support systems for they pose barriers. This paper provides a theoretical synthesis for building a sociotechnical framework around the multifaceted challenges and opportunities affecting BI adoption in this context. Building up from sociotechnical systems theory, the Technology-Organization-Environment (TOE) framework, dynamic capabilities framework, and resource-based view, we conceptualize the CATALYST (Context-aware Adaptive Technology Adoption for Limited-resource Yet Sustainable Transformation) framework. The framework focuses on how technological capabilities and organizational preparedness, human and social dynamics, and constraints in the environment interrelate. The CATALYST framework promotes the technical and socio-economic alignment of solutions through an adaptive five-step process consisting of Context Assessment, Alignment Strategy Development, Adaptive Implementation, Learning and Evolution, and Transformation Consolidation, beyond mere digital transformation to inclusive and sustainable transformation. This synthesis extends the innovation adoption theory and digital agriculture frameworks, alongside practical considerations for policymakers and stakeholders through whose endeavors BI might be accomplished throughout developing regions.

World Journal of Advanced Engineering Technology and SciencesVol. 15(3)
Openalex Percentile: Top 4%
Big Data and Business Intelligence
6.85
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