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1 – 1 of 1Nadia A. Abdelmegeed Abdelwahed, Safia Bano, Mohammed A. Al Doghan, Abdulaziz Ahmed Aljughiman, Naimatullah Shah and Bahadur Ali Soomro
Women's empowerment plays a pivotal role in achieving sustainable and sustainable development in developed and developing contexts. The present paper explores the effect of…
Abstract
Purpose
Women's empowerment plays a pivotal role in achieving sustainable and sustainable development in developed and developing contexts. The present paper explores the effect of technology orientation (TO), entrepreneurial orientation (EO), and digital technology self-efficacy (DTSE) on digital innovation (DI) and women's empowerment (WE) among Saudi women.
Design/methodology/approach
This is a cross-sectional study which applies a deductive approach. The study collected data from women in Saudi Arabia actively involved in entrepreneurship and utilizing digital technology. The survey questionnaire is used as a prevalent tool to get responses. Finally, the study concludes based on 316 valid samples.
Findings
The structural equation modeling through SmartPls4, the results exert an insignificant effect of TO on both DI and women empowerment. The study confirmed a positive significant impact of EO on DI but not on WE. Moreover, the DTSE construct is found to be a significant and robust analyst of DI and WE. With regard to mediating effects, DI mediates the relationship between EO, DTSE and WE, but not between TO and WE.
Practical implications
The study's findings contribute to more comprehensive and effective initiatives that foster innovation, gender equality, and WE in entrepreneurial networks. The study would assist policymakers and planners in developing robust strategies focusing on digitalization to boost DI and WE through enhanced DTSE. The study would also offer guidelines for policymakers to achieve sustainable development goals (SDGs) generally and specifically for Saudi Vision 2030, which is particularly ambitious to promote WE.
Originality/value
The study fills the gaps by offering a bunch of predictors, i.e., TO, EO, DTSE and DI, which predict WE in the Saudi context.
Details