Volume 9, Issue 3 (Autumn 2022)
johe 2022, 9(3): 166-172 |
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Bozorgkhoo N, Hashemzadeh Khorasgani G. Identification of Health, Safety and Environmental (HSE) Parameters Affecting Cloud Computing in Providing Intelligent Services in Rail Transportation System. johe 2022; 9 (3) :166-172
URL: http://johe.umsha.ac.ir/article-1-762-en.html
URL: http://johe.umsha.ac.ir/article-1-762-en.html
1- Department of Industrial Management, Faculty of Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
2- Department of Industrial Management, Faculty of Management, South Tehran Branch, Islamic Azad University, Tehran, Iran , Gh_hashemzadeh@azad.ac.ir
2- Department of Industrial Management, Faculty of Management, South Tehran Branch, Islamic Azad University, Tehran, Iran , Gh_hashemzadeh@azad.ac.ir
Abstract: (1090 Views)
Background and Objective: The present study was designed and conducted to identify and determine the parameters of health, safety, and environment (HSE) affecting cloud computing in providing intelligent services in the rail transportation system.
Materials and Methods: This cross-sectional study was carried out based on the Delphi technique and expert opinions on the rail transportation system in 2020. This research was performed in five steps, including a comprehensive review of the related literature, identification, presentation of HSE parameters affecting cloud computing in providing intelligent services in the rail transportation system, and three Delphi rounds. Sixteen experts participated in the field of HSE and rail transportation. The coefficient of variation (CV) and desirability of each parameter were considered at < 20% and ≥ 4, respectively.
Results: Based on this Delphi study, 15 parameters related to HSE and influential on cloud computing technology in the provision of intelligent services in the rail transportation system were introduced. Moreover, the CV index was estimated at 8.0%. The parameters of future research, the existence of a skilled workforce, and cloud service resource management tools had the highest degree of desirability (4.875).
Conclusion: The findings indicated that identifying functions and challenges of HSE regarding cloud computing technology in the rail transportation system could help decision-makers to improve effective services in the rail transportation system and reduce the associated risks.
Materials and Methods: This cross-sectional study was carried out based on the Delphi technique and expert opinions on the rail transportation system in 2020. This research was performed in five steps, including a comprehensive review of the related literature, identification, presentation of HSE parameters affecting cloud computing in providing intelligent services in the rail transportation system, and three Delphi rounds. Sixteen experts participated in the field of HSE and rail transportation. The coefficient of variation (CV) and desirability of each parameter were considered at < 20% and ≥ 4, respectively.
Results: Based on this Delphi study, 15 parameters related to HSE and influential on cloud computing technology in the provision of intelligent services in the rail transportation system were introduced. Moreover, the CV index was estimated at 8.0%. The parameters of future research, the existence of a skilled workforce, and cloud service resource management tools had the highest degree of desirability (4.875).
Conclusion: The findings indicated that identifying functions and challenges of HSE regarding cloud computing technology in the rail transportation system could help decision-makers to improve effective services in the rail transportation system and reduce the associated risks.
Keywords: Cloud Computing, Delphi Technique, Health Safety and Environment (HSE), Rail Transport System
Type of Study: Research Article |
Subject:
Safety
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