Generative AI Capability, Business Model Innovation, and Business Development Performance: A Moderated Mediation Framework for SMEs in an Emerging Market

Generative artificial intelligence (GenAI) is increasingly accessible to small and medium-sized enterprises in emerging economies, yet the organisational mechanisms that link GenAI capability to business development outcomes remain insufficiently understood. Drawing on Dynamic Capabilities Theory and the Resource-Based View, this study examines the association between GenAI capability and business development performance (BDP) in Jordanian SMEs through the mediating role of business model innovation (BMI) and the moderating role of market sensing agility (MSA). A cross-sectional survey of owner–managers and senior decision-makers was analysed using partial least squares structural equation modelling. The results indicate that GenAI capability is positively associated with BDP, with BMI accounting for a meaningful share of the link, while MSA strengthens the mediated pathway such that the association is substantially more pronounced among firms with higher levels of market sensing capacity. The findings suggest that returns to GenAI investment in resource-constrained markets depend less on technological access and more on the firm’s capacity to reconfigure its business model and interpret the external environment effectively. The study contributes to the dynamic capabilities literature in emerging-market contexts and provides direction for managers and policymakers concerned with digital transformation in the SME sector.

Authors

Institutions

Publication Details

Journal
Administrative Sciences
Published
2026-06-26
DOI
https://doi.org/10.3390/admsci16070310
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generative AI Capability, Business Model Innovation, and Business Development Performance: A Moderated Mediation Framework for SMEs in an Emerging Market

Sulaiman Weshah, Raed Wishah, Hamzah Rahahleh
Administrative Sciences
Big Data and Business Intelligence
article

Generative AI Capability, Business Model Innovation, and Business Development Performance: A Moderated Mediation Framework for SMEs in an Emerging Market

Sulaiman Weshah, Raed Wishah, Hamzah Rahahleh
article en

Abstract

Generative artificial intelligence (GenAI) is increasingly accessible to small and medium-sized enterprises in emerging economies, yet the organisational mechanisms that link GenAI capability to business development outcomes remain insufficiently understood. Drawing on Dynamic Capabilities Theory and the Resource-Based View, this study examines the association between GenAI capability and business development performance (BDP) in Jordanian SMEs through the mediating role of business model innovation (BMI) and the moderating role of market sensing agility (MSA). A cross-sectional survey of owner–managers and senior decision-makers was analysed using partial least squares structural equation modelling. The results indicate that GenAI capability is positively associated with BDP, with BMI accounting for a meaningful share of the link, while MSA strengthens the mediated pathway such that the association is substantially more pronounced among firms with higher levels of market sensing capacity. The findings suggest that returns to GenAI investment in resource-constrained markets depend less on technological access and more on the firm’s capacity to reconfigure its business model and interpret the external environment effectively. The study contributes to the dynamic capabilities literature in emerging-market contexts and provides direction for managers and policymakers concerned with digital transformation in the SME sector.

Administrative SciencesVol. 16(7)
Applied Science Private University (JO), Princess Sumaya University for Technology (JO), Al-Balqa Applied University (JO)
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Big Data and Business Intelligence
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.