Identification of Key Quality Attributes in Gas Pipeline Transmission Projects Using Repertory Grid Method
محل انتشار: مجله تکنولوژی گاز، دوره: 7، شماره: 1
سال انتشار: 1401
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 209
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شناسه ملی سند علمی:
JR_JGT-7-1_002
تاریخ نمایه سازی: 29 آبان 1402
چکیده مقاله:
The purpose of this study is to identify the key quality attributes in gas transmission projects.By applying Kelly’s personal constructs theory and repertory grid methodology as well as conducting interviews with ۲۰ managers and experts of gas transmission projects, as many as ۲۸۴ quality constructs have been identified. These constructs were classified into ۴۰ categories by using content analysis, and they were subsequently analyzed with statistical methods. By applying the statistical analysis nine quality attributes include, compliance with the standards, competence, appropriateness in design and engineering, effective supervision, sound execution, desirability, convergence, accountability and integration were identified. These construct as the main factors affecting the quality of gas transmission projects.In this study, the data were collected from the gas transmission projects conducted from the employer’s departments. The subsequent studies not only increase the number of interviewees but also apply the contractors’ participation in the interviews to have more comprehensive results. Given the conditions of volume, temperature, and pressure, oil industry projects are of critical sensitivity and significance. The managers of project-oriented organizations can apply the findings of the present study to promote project quality and success.The present study is an original one; it is one of the main issues to be studied in investigating the concept of quality in gas transmission projects. This study includes the experimental evidence regarding the positive effect of quality attributes on the performance of such projects. Moreover, the present study attempts to develop the related literature on quality.
کلیدواژه ها:
نویسندگان
Majid Chegeni
Ph.D. Candidate of Productivity and System Management, School of Industrial Engineering (SIE), Iran University of Science and Technology, Tehran, Iran
Rassoul Noorossana
Full Professor of Industrial Engineering, School of Industrial Engineering (SIE), Iran University of Science and Technology, Tehran, Iran
Siamak Noori
Associate Professor of Industrial Engineering, School of Industrial Engineering (SIE), Iran University of Science and Technology, Tehran, Iran
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