How STARA-enabled technological readiness shapes intrapreneurial behaviour and digital competence in China's electric vehicle (EV) manufacturing sector

Purpose This study examines how employees' perceptions of STARA (smart technologies, artificial intelligence, robotics, and algorithms) influence their intrapreneurial behaviour (IB) and digital competence (DC), and how digital dynamism (DD) conditions this relationship. Design/methodology/approach Drawing on Dynamic Capabilities Theory, Sociotechnical Systems Theory, and the Antecedents–Decisions–Outcome framework, the study develops an integrated model explaining how employees' perceptions of STARA shape behavioural responses and digital capability development. Data were collected from full-time employees in China's electric vehicle (EV) manufacturing sector, a context characterized by extensive use of STARA technologies, using an online survey and stratified purposive sampling, resulting in 193 valid responses. Partial least squares structural equation modeling was applied to test the proposed model. Findings The results show that positive perceptions of STARA are associated with higher levels of IB and DC. IB serves as a key mechanism through which perceived STARA relates to DC. This highlights the role of employee behaviour in capability development. DD weakens the positive relationship between perceived STARA and DC, suggesting that high environmental turbulence may constrain employees' ability to translate perceived technological opportunities into DC. Research limitations/implications The study offers a socio-technical explanation of digital capability development by showing how employees' interpretations of technological change and their behavioural responses jointly shape capability outcomes. It highlights the importance of aligning technological change with employee-driven adaptation under conditions of environmental uncertainty. Practical implications The findings provide insights for managers in technology-intensive manufacturing firms. They show how employees' perceptions of STARA and intrapreneurial behaviour can contribute to DC. Social implications The findings suggest that fostering IB and DC can enhance employee adaptability, employability, and career resilience, contributing to a more digitally prepared workforce amid ongoing technological transformation. Originality/value This study contributes to the literature on digital transformation and capability development. It integrates employees' perceptions of STARA with employee behaviour within a sociotechnical framework in the EV manufacturing context.

Authors

Institutions

Publication Details

Journal
Journal of Enterprise Information Management
Published
2026-11-05
DOI
https://doi.org/10.1108/jeim-04-2026-0576
Primary Topic
Innovation and Knowledge Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

How STARA-enabled technological readiness shapes intrapreneurial behaviour and digital competence in China's electric vehicle (EV) manufacturing sector

Syed Hussain Murtaza, Adnan Ullah Khan, Wu Lu, Azhar Ali
Journal of Enterprise Information Management
Innovation and Knowledge Management
article

How STARA-enabled technological readiness shapes intrapreneurial behaviour and digital competence in China's electric vehicle (EV) manufacturing sector

Syed Hussain Murtaza, Adnan Ullah Khan, Wu Lu, Azhar Ali
article en

Abstract

Purpose This study examines how employees' perceptions of STARA (smart technologies, artificial intelligence, robotics, and algorithms) influence their intrapreneurial behaviour (IB) and digital competence (DC), and how digital dynamism (DD) conditions this relationship. Design/methodology/approach Drawing on Dynamic Capabilities Theory, Sociotechnical Systems Theory, and the Antecedents–Decisions–Outcome framework, the study develops an integrated model explaining how employees' perceptions of STARA shape behavioural responses and digital capability development. Data were collected from full-time employees in China's electric vehicle (EV) manufacturing sector, a context characterized by extensive use of STARA technologies, using an online survey and stratified purposive sampling, resulting in 193 valid responses. Partial least squares structural equation modeling was applied to test the proposed model. Findings The results show that positive perceptions of STARA are associated with higher levels of IB and DC. IB serves as a key mechanism through which perceived STARA relates to DC. This highlights the role of employee behaviour in capability development. DD weakens the positive relationship between perceived STARA and DC, suggesting that high environmental turbulence may constrain employees' ability to translate perceived technological opportunities into DC. Research limitations/implications The study offers a socio-technical explanation of digital capability development by showing how employees' interpretations of technological change and their behavioural responses jointly shape capability outcomes. It highlights the importance of aligning technological change with employee-driven adaptation under conditions of environmental uncertainty. Practical implications The findings provide insights for managers in technology-intensive manufacturing firms. They show how employees' perceptions of STARA and intrapreneurial behaviour can contribute to DC. Social implications The findings suggest that fostering IB and DC can enhance employee adaptability, employability, and career resilience, contributing to a more digitally prepared workforce amid ongoing technological transformation. Originality/value This study contributes to the literature on digital transformation and capability development. It integrates employees' perceptions of STARA with employee behaviour within a sociotechnical framework in the EV manufacturing context.

Journal of Enterprise Information Management
Shandong University (CN), SGH Warsaw School of Economics (PL), Hangzhou City University (CN), University of Waikato (NZ)
Openalex Percentile: Top 12%
Innovation and Knowledge Management
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.

Laika access coming soon