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Article
Publication date: 6 July 2012

Stephen Swailes, L.G. Al Said and Saleh Al Fahdi

Successful localization policies are critical to the resolution of difficult social problems in the Gulf States relating to rising populations and youth unemployment. Successful…

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Abstract

Purpose

Successful localization policies are critical to the resolution of difficult social problems in the Gulf States relating to rising populations and youth unemployment. Successful localization is proving difficult, however, and this paper aims to look specifically at Omanization in an effort to contribute to a better understanding of a complex socio‐economic arena.

Design/methodology/approach

The paper is based on 25 interviews with Ministerial officials and senior private sector managers with human resource management responsibilities in Oman. Interviews were open‐coded to allow factors specific to Oman to emerge from the data.

Findings

Key findings are that the perceptions of the employability of locals remains a difficult supply side problem and employers' preferences for foreign labour remains a difficult demand side problem.

Research limitations/implications

The paper is strengthened by the involvement of senior managers yet it is difficult to separate stereotypes of local labour from stereotypes of foreign workers.

Practical implications

The insights reported in the paper identify key areas for further development of localization policy.

Originality/value

The paper provides a new perspective on the difficulties of localization in the Gulf States.

Details

International Journal of Public Sector Management, vol. 25 no. 5
Type: Research Article
ISSN: 0951-3558

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Article
Publication date: 6 November 2023

Muneza Kagzi, Sayantan Khanra and Sanjoy Kumar Paul

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior…

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Abstract

Purpose

From a technological determinist perspective, machine learning (ML) may significantly contribute towards sustainable development. The purpose of this study is to synthesize prior literature on the role of ML in promoting sustainability and to encourage future inquiries.

Design/methodology/approach

This study conducts a systematic review of 110 papers that demonstrate the utilization of ML in the context of sustainable development.

Findings

ML techniques may play a vital role in enabling sustainable development by leveraging data to uncover patterns and facilitate the prediction of various variables, thereby aiding in decision-making processes. Through the synthesis of findings from prior research, it is evident that ML may help in achieving many of the United Nations’ sustainable development goals.

Originality/value

This study represents one of the initial investigations that conducted a comprehensive examination of the literature concerning ML’s contribution to sustainability. The analysis revealed that the research domain is still in its early stages, indicating a need for further exploration.

Details

Journal of Systems and Information Technology, vol. 25 no. 4
Type: Research Article
ISSN: 1328-7265

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Article
Publication date: 20 February 2025

Hanan Ahmed Al-Balushi, Harcharanjit Singh and Irfan Saleem

This study, using stakeholder theory and diffusion of innovations (DOIs), aims to examine the readiness of Omani health-care firms to adopt artificial intelligence (AI). This…

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Abstract

Purpose

This study, using stakeholder theory and diffusion of innovations (DOIs), aims to examine the readiness of Omani health-care firms to adopt artificial intelligence (AI). This adoption is seen as a key step towards ensuring green innovation and sustainable performance (SP) in the health-care sector.

Design/methodology/approach

This study adopted convenience and referral sampling techniques to enhance the response rate for the limited number of health-care firms using AI. Using explanatory research design, structure equation modelling and employees as the unit of analysis, a random sample technique is used to distribute the structured questionnaire to five hospitals in North Al-Batinah, including Shinas, Liwa and Sohar cities. Smart PLS 4.1 analyses the responses.

Findings

The research demonstrates that AI could significantly enhance SP, a finding that is of utmost importance in the current health-care landscape. This study also tested green knowledge sharing as a boundary condition. Furthermore, the study’s findings indicate that AI leads to the emergence of green innovation and SP, suggesting that firms are willing to adopt AI and achieve the sustainable development goals (SDGs).

Practical implications

This study implies that stakeholders, including the Omani Government and Middle Eastern firms, should prioritize investments in AI technologies tailored to sustainability initiatives.

Originality/value

This research study makes three significant and unique contributions. Firstly, it uniquely integrates stakeholder and DOIs theories to explain the mediating function of green innovation and the moderating effect of green knowledge sharing. Secondly, it provides a unique Middle Eastern context, where the government’s focus on the health sector is crucial. Finally, this study outlines a clear and actionable pathway for the Middle East to achieve the SDGs, thereby enlightening the reader on the potential of AI in the health-care sector.

Details

Society and Business Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1746-5680

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