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A predictive model for collaborative leadership in digital transformation: Does it make a difference in Oman’s e-government performance?

Nasser Masaaod Al-Khayari (School of Accounting and Finance, Binary University College of Management and Entrepreneurship, Bandar Puchong Jaya, Malaysia)
Midya Yousefi (Department of Educational Leadership, Kean University – Wenzhou Campus, Wenzhou, China)
Osaro Aigbogun (Curtin University of Technology – Sarawak Campus Malaysia, Miri, Malaysia)

Foresight

ISSN: 1463-6689

Article publication date: 9 July 2024

Issue publication date: 9 October 2024

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Abstract

Purpose

This paper aims to investigate the role of collaborative leadership in government digital transformation in the Sultanate of Oman. To analyze collaborative leadership, the research examines four exogenous variables: self-directed team, power-sharing, relational intelligence and agility. The endogenous variable chosen to represent Oman's e-Government performance is organizational performance.

Design/methodology/approach

A quantitative method was applied to gather cross-sectional data in a questionnaire survey. Using a stratified sampling technique, the data were collected from 100 information and communication technology and e-government officials who assume leadership responsibilities. Partial least square structural equation modeling (PLS-SEM) examined measurement and structural models.

Findings

The role of collaborative leadership in the performance of government digital transformation in the Sultanate of Oman was examined in this study. Collaborative leadership was categorized into four exogenous variables: self-directed team, power-sharing, relational intelligence and agility. Oman’s e-government performance operationalized as the organizational performance was selected as the endogenous variable. The results show that the self-directed team and agility components of collaborative leadership significantly positively impacted the performance of government digital transformation in the Sultanate of Oman.

Research limitations/implications

The major limitation of this research was that the study covered only four collaborative leadership attributes: self-directed teams, power-sharing, relational intelligence and agility. The study should have covered building trust, commitment, emotional intelligence, vision and communication skills.

Practical implications

These results are important for government policy creators and decision-makers aiming to enhance government digital transformation performance by leveraging collaborative leadership.

Social implications

Addressing collaborative leadership in management can be done through awareness of its importance to critical decision-makers and embedding it in the organization's governance, policies and human resource career path. In particular, it is recommended that public sector leaders continuously monitor self-managing teams and teamwork practices within the organization.

Originality/value

The originality and contribution of the above article lie in its investigation of the role of collaborative leadership in the context of government digital transformation in the Sultanate of Oman. The study contributes to the existing literature by examining the impact of four exogenous variables, self-directed team, power-sharing, relational intelligence and agility, on collaborative leadership. Additionally, the research uses a quantitative approach and uses PLS-SEM to analyze the data. The findings highlight the significant positive impact of self-directed team and agility components of collaborative leadership on the performance of government digital transformation. These insights provide valuable implications for government policy creators and decision-makers aiming to enhance digital transformation in the public sector by effectively implementing collaborative leadership strategies.

Keywords

Citation

Al-Khayari, N.M., Yousefi, M. and Aigbogun, O. (2024), "A predictive model for collaborative leadership in digital transformation: Does it make a difference in Oman’s e-government performance?", Foresight, Vol. 26 No. 5, pp. 775-792. https://doi.org/10.1108/FS-08-2023-0163

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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