Designing a Human Resources Improvement Model Based on Cloud Computing (Case Study: Tejarat Bank)

Document Type : Original Article

Authors

1 Ph.D. Candidate, Department of Management, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.

2 Assistant Professor, Department of Management, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran.

Abstract

Today, improving human resources is one of the most used areas of cloud computing in organizations. Because on the one hand, it has implementation complexities and diverse systems, and its implementation requires the use of numerous software, and on the other hand, it is possible to use the human resources services of organizations. The aim of the current research was to design a human resource improvement model based on cloud computing in Tejarat Bank. The research method is applied and descriptive, which was done with a mixed exploratory approach (qualitative-quantitative). The statistical population in the qualitative stage was 30 people from banking and university experts who were selected by a purposeful judgment method, and in the quantitative stage, all the experts of Tejarat Bank were 5998 people. To identify the components of human resource improvement, the Delphi method was used in four rounds, and to design the model, the structural equation method with Smart PLS3 software was used. Delphi results showed that human resources improvement based on cloud computing in Tejarat Bank includes 46 components in the form of 4 dimensions (educational improvement, professional improvement, organizational improvement, and individual improvement). Also, based on the results of structural equation modeling, it can be said: the dimensions of educational improvement, professional improvement, organizational improvement, and individual improvement have a positive effect on the improvement of human resources in Bank Tejarat at the rate of 0.864, 0.571, 0.701, and 0.622, respectively.

Keywords


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Volume 4, Issue 2
2023
Pages 253-278
  • Receive Date: 10 April 2023
  • Revise Date: 20 June 2023
  • Accept Date: 06 July 2023
  • First Publish Date: 06 July 2023
  • Publish Date: 01 October 2023