ارائه مدل کاربردی انتخاب و اولویت بندی پیمانکاران در شرکتهای پروژه محور( مطالعه موردی:مپنا)
محورهای موضوعی : مدیریت صنعتی
HOSEIN KARBAKHSH RAVARI
1
(
PhD. student,Management,Faculty of Literature,Islamic Azad University of Kerman ,Kerman,Iran
)
sanjar salajegheh
2
(
Associate Professor, Management,Faculty of Literature,Islamic Azad University of Kerman,Kerman,Iran
)
ayyub Sheikhi
3
(
Associate Professor,Department of Statistics, Faculty of Mathematics and Computer, Shahid Bahonar University of Kerman,Kerman,Iran
)
کلید واژه: تصمیم گیری چندمعیاره, نظریه داده بنیاد, انتخاب پیمانکار, اولویت بندی,
چکیده مقاله :
تصمیم گیری دقیق برای انتخاب پیمانکاران در راستای مدیریت یک پروژه، از مهمترین عوامل موفقیت و افزایش بهره وری یک پروژه می باشد. به نحویکه استخراج یک مدل کاربردی از مجموعه عوامل موثر بر انتخاب پیمانکاران، می‌تواند نقش مهمی در بهبود عملکرد پروژه داشته باشد، بنابراین، ارائه مدل مذکور، هدف اصلی این تحقیق بنیادین – کاربردی می باشد. رویکرد این تحقیق، تلفیق پژوهش های کیفی وکمی بوده وجامعه آماری آن، خبرگان مدیریت پروژه می باشند. درگام نخست ساختار مدل، با تجزیه و تحلیل داده‌های گردآوری شده از رویکرد تئوری داده بنیاد، شکل گرفته است. درگام بعدی جهت آزمودن مدل مفهومی تحقیق و فرضیه‌ها از روش تحلیل عاملی تأییدی و معادلات ساختاری مبتنی بر واریانس با استفاده از متد حداقل مربعات جزئی استفاده شده و پردازش داده‌های تحقیق به کمک نرمافزار اسمارت پی ال اس انجام گردیده است. در گام آخر جهت بهبود و کاربردی کردن مدل، از تکنیک تحلیل سلسله مراتبی فازی، وزن معیارها سنجش شده و اولویت بندی آنها تعیین گردیده است. درنهایت با استفاده از تکنیک تاپسیس فازی، یک نمونه کاربردی از انتخاب پیمانکار، پیاده سازی شده است. نتایج به دست آمده، نشان می دهد؛ برای انتخاب کارآ یک پیمانکار، می توان بااستفاده از مدل ارائه شده و براساس ضرایب تعیین شده و اولویت بندی زیرمعیارهای توانمندی رفتاری و فنی، امکانات شرکت واهداف برونسپاری ، به شرایط تصمصیم گیری مطلوبی دست یافت.
Accurate decision making for selecting contractors in order to manage a project is one of the most important factors of success and enhancing productivity of a project. So, extracting a practical model from the set of factors affecting the selection of contractors can play an important role in improving the project performance, therefore, providing the proposed model is the main objective of this fundamental-applied research. The approach of this research is the integration of the qualitative and quantitative research and the statistical community are the experts of project management. At first, the model structure has been explained by analysis of data collected from the fundamental data theory approach. In the next step to test the conceptual model of research and hypothesis, the method of confirmatory factor analysis and structural equations based on variance was used using partial least squares method and data processing was performed using SMART PLS software. In the last step, to improve and applicability of the model, fuzzy analytic hierarchy technique, the weight of the criteria has been measured and prioritized .Finally, using fuzzy TOPSIS technique, an applied sample of contractor selection has been implemented. The results show that for the efficient selection of a contractor, by using a proposed model based on the determined coefficients and prioritize the sub-criteria of behavioral and technical capability, the company's capabilities and outsourcing goals, the achieving of optimal decision-making conditions is possible.
1- Banaitienė, Nerija. Neringa GudienėAudrius Banaitis, Jorge Lopes. (2013). Development of a Conceptual Critical Success Factors Model for ConstructionmProjects: a Case of Lithuania. 11th International Conference on Modern Building Materials, Structures and Techniques, MBMST.
2- Chan, R., Kumar, M. (2007). Lean management model for construction of high-rise apartment buildings. Journal of construction engineering and management American Society of Civil Engineers, Reston, 133(5): 374-384.
3- Chen, Chen- Tung, Sue- Fen Hung. (2007). Applying fuzzy method for measuring criticality in project network.International Journal of Information Sciences 177:2448- 58.
4- Chen, M Bubshalt. A. A. & Al-Gobali, K. H. (2013). Contractor prequalification in Saudi Arabia. Journal of Management in Engineering, 12: 50–54.
5- El Mokadem, M. (2017). The classification of supplier selection criteria with respect to lean or agile manufacturing strategies. Journal of Manufacturing Technology Management, 28 (2): 232-249.
6- Fikri, Dweiri. Kumar, Sameer. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 72(15): 467-468.
7- Hasani Derakhshandeh, Sholeh. (2017). Multi-criteria Decision Making Technique for Selecting the Best Oil and Gas Equipment Supplier. 5th International Conference on Economics. Management, Accounting with Value Creation Approach. Shiraz.
8- Herroelen, W.S. Leus, R. Demeulemeester, E.L. (2014). Critical chain project scheduling-do not oversimplifies. Project Management Journal 33(4): 46–60.
9- Hosseinpour, Afsaneh. & Mahmoud Alborzi. (2017). Combining Data Envelopment Analysis and Hierarchical Analysis Process in Selection of Contractors Tendered. 2nd International Conference on Management and Accounting. Tehran.
10- Jain, Vipul. & Kumar, Arun. (2018). Supplier selection using fuzzy AHP and TOPSIS. Neural Computing and Applications, 29 (7): 555–564.
11- Monfared, Masoud & Salari, Masoud. (2016). Investigating Selection of Top Contractors by Considering the Role of Internal Resources of the Organization. Project Management Quarterly, 3 (1): 18-27.
12- Olson, N, Soetanto, AR J Dainty, J Glass, A D F Price. (2006).Towards an explicit design decision process: the case of the structural frame. Construction Management and Economics, 24(6): 603-614.
13- Samiaah M. Hassen M. Al-Tmeemya, Hamzah Abdul-Rahmanb, Zakaria Haruna (2011). Future criteria for success of building projects in Malaysia, International Journal of Project Management
14- Sarayloo, Zahra & Farhadi, Ali. (2017). Supplier Selection and Ranking Using Delphi Techniques, Hierarchical Analysis and Taguchi Loss Function. 2nd International Conference on Management and Accounting Techniques, Tehran.
15- Taghvaei, C. Hadyeh & Esmaeilian, Majid. (2017). Supplier Evaluation and Ranking Using a Combined Approach of Kano and TOPSIS Methods in the Fuzzy Environment. 2nd International Conference on Industrial Management. Babolsar, University of Mazandaran.
_||_1- Banaitienė, Nerija. Neringa GudienėAudrius Banaitis, Jorge Lopes. (2013). Development of a Conceptual Critical Success Factors Model for ConstructionmProjects: a Case of Lithuania. 11th International Conference on Modern Building Materials, Structures and Techniques, MBMST.
2- Chan, R., Kumar, M. (2007). Lean management model for construction of high-rise apartment buildings. Journal of construction engineering and management American Society of Civil Engineers, Reston, 133(5): 374-384.
3- Chen, Chen- Tung, Sue- Fen Hung. (2007). Applying fuzzy method for measuring criticality in project network.International Journal of Information Sciences 177:2448- 58.
4- Chen, M Bubshalt. A. A. & Al-Gobali, K. H. (2013). Contractor prequalification in Saudi Arabia. Journal of Management in Engineering, 12: 50–54.
5- El Mokadem, M. (2017). The classification of supplier selection criteria with respect to lean or agile manufacturing strategies. Journal of Manufacturing Technology Management, 28 (2): 232-249.
6- Fikri, Dweiri. Kumar, Sameer. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. Expert Systems with Applications, 72(15): 467-468.
7- Hasani Derakhshandeh, Sholeh. (2017). Multi-criteria Decision Making Technique for Selecting the Best Oil and Gas Equipment Supplier. 5th International Conference on Economics. Management, Accounting with Value Creation Approach. Shiraz.
8- Herroelen, W.S. Leus, R. Demeulemeester, E.L. (2014). Critical chain project scheduling-do not oversimplifies. Project Management Journal 33(4): 46–60.
9- Hosseinpour, Afsaneh. & Mahmoud Alborzi. (2017). Combining Data Envelopment Analysis and Hierarchical Analysis Process in Selection of Contractors Tendered. 2nd International Conference on Management and Accounting. Tehran.
10- Jain, Vipul. & Kumar, Arun. (2018). Supplier selection using fuzzy AHP and TOPSIS. Neural Computing and Applications, 29 (7): 555–564.
11- Monfared, Masoud & Salari, Masoud. (2016). Investigating Selection of Top Contractors by Considering the Role of Internal Resources of the Organization. Project Management Quarterly, 3 (1): 18-27.
12- Olson, N, Soetanto, AR J Dainty, J Glass, A D F Price. (2006).Towards an explicit design decision process: the case of the structural frame. Construction Management and Economics, 24(6): 603-614.
13- Samiaah M. Hassen M. Al-Tmeemya, Hamzah Abdul-Rahmanb, Zakaria Haruna (2011). Future criteria for success of building projects in Malaysia, International Journal of Project Management
14- Sarayloo, Zahra & Farhadi, Ali. (2017). Supplier Selection and Ranking Using Delphi Techniques, Hierarchical Analysis and Taguchi Loss Function. 2nd International Conference on Management and Accounting Techniques, Tehran.
15- Taghvaei, C. Hadyeh & Esmaeilian, Majid. (2017). Supplier Evaluation and Ranking Using a Combined Approach of Kano and TOPSIS Methods in the Fuzzy Environment. 2nd International Conference on Industrial Management. Babolsar, University of Mazandaran.
