شناسایی و رتبه بندی بنگاه های اقتصادی حمل و نقلی بر اساس شاخص های ارزیابی عملکرد با استفاده از روش مولتی مورا
الموضوعات :
gholam reza einy sarkalleh
1
,
hosien MAHMODY
2
,
Hossien Afzali
3
,
MOSTEFA REZVANY DOST
4
,
hafez ashkan
5
1 - exper
2 - مدیر کل
3 - Researcher at the institute for Trade Student and Research (ITSR)
4 - STUDENT
5 - هیئت علمی
تاريخ الإرسال : 03 الأربعاء , جمادى الأولى, 1440
تاريخ التأكيد : 20 السبت , جمادى الأولى, 1440
تاريخ الإصدار : 15 الإثنين , جمادى الأولى, 1440
الکلمات المفتاحية:
تصمیم گیری چند معیاره,
حمل و نقل,
بنگاههای اقتصادی,
تصمیم گیری گروهی,
ملخص المقالة :
امروزه صنعت حمل و نقل در کشور پیشرفت روز افزون داشته و در عین حال هزینه های عملیاتی زیادی را به خود اختصاص داده است. شناسایی و ارزیابی عملکرد بنگاههای اقتصادی و در نهایت بازخور و تحلیل شاخص های ارزیابی یکی از موضوعات اساسی در صنعت حمل و نقل می باشد. در این تحقیق با استفاده از تکنیک های تصمیم گیری چند معیاره و روش خبرگی (دلفی) به شناسایی شاخص های تاثیر گذار در عملکرد یک بنگاه اقتصادی حمل و نقلی پرداخته و سپس با استفاده از روش تصمیم گیری مولتی مورا که یکی از روش های نوین در تصمیم گیری چند معیاره می باشد و با در نظر گرفتن معیارهای تعیین شده، اولویت بندی و رتبه بندی بین شاخص های عملکردی پیشنهادی صورت می پذیرد. مقاله حاضر علاوه بر شناسایی شاخص های تاثیرگذار در ارزیابی عملکرد بنگاه های اقتصادی حمل و نقلی به مطالعه موردی در خصوص پنج شرکت حمل و نقلی و رتبه بندی آن، به تشریح گام های روش مولتی مورا و نیز پرداخته شده است.
المصادر:
Arzu Akyuz, G., Erman Erkan, T., Mahallesi, K. (2010). Supply chain performance measurement: a literature review, 5137–5155.
Bergquist, K., Fink, C., Raffo, J. (2017). Identifying and ranking the world’s largest clusters of inventive activity, No. 34.
Biswas, P., Pramanik, S., Giri, B. (2015). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment.
Carvalho, L., Meier, S., W. Wang, S. (2016). Poverty and Economic Decision-Making: Evidence from Changes in Financial Resources at Payday, 260-84.
Einy Sarkalleh, Gholam Reza, Afzali, Hossien, Khademy Nejad, Mojtba, Miandoabchi, Elnaz. (2017). Proposing a New Genetic Algorithm Multi-capacity to Solve the Multi-Storage Routing problem with Multi-capacity Vehicles. Journal of Industrial Management, 12(42), 87-98.
Evaluating Significance of Green Manufacturing Enablers Using MOORA Method for Indian Manufacturing Sector, 303-314.
FHWA/FTA. (1993). U.S. Department of Transportation. Metropolitan Planning Process: Major Metropolitan Transportation Investments, Federal Register, Part II,
Guerra, E., de Lara, A., Malizia, Díaz, P. (2009). MULTICRITERIA DECISION MAKING: Advances in MCDM Models, Algorithms, Theory, and Applications, 51(4).
Gunasekaran, A., Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications.
Gunasekaran, A., Patel, C., Tirtiroglu, E. (2016). Performance measures and metrics in a supply chain environment, 71 - 87.
Hafezalkotob, A. Hafezalkotob, A. (2015). Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications, Mater. Dec., 87, 949–959.
Hafezalkotob, A., Hafezalkotob, A. (2015). Extended MULTIMOORA method based on Shannon entropy weight for materials selection, Journal of Ind. Eng. Int., 12(1), 1–13.
Karimzadeh, R. (2008). Selection of favorable projects in transport companies using Bernardo's decision-making method. Journal of Transportation, 4(4), 329-338.
Leonidovna Zaytseva, A., Anatol'yevna Menukhova, T. (2016). On the Issue of the Innovation Policy at the Road Transport Enterprises, 11(4), 2206-2211.
Rajak, S., Parthiban, P., Dhanalakshmi, R. (2016). Sustainable transportation systems performance evaluation using fuzzy logic, 503-513.
Skrypnikov, A., Dorokhin, S., Kozlov, V. G., Chernyshova, E. V. (2017). Mathematical Model of Statistical Identification of Car Transport Informational Provision, 12, (2).
Sun, J., Yuan, Y., Yang, R., Ji, X., Wu, J. (2018). Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis, 75-86.
Thokala, P., Devlin, N., Marsh, K., Stuart Peacock, S. (2016). Multiple Criteria Decision Analysis for Health Care Decision Making an Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force, 1–13.
Wang, J., Wu, J., Wang, J., Zhang, H., Chen, X. (2015). TOPSIS method for multi-attribute group decision-making, under single-valued neutrosophic environment.
_||_
Arzu Akyuz, G., Erman Erkan, T., Mahallesi, K. (2010). Supply chain performance measurement: a literature review, 5137–5155.
Bergquist, K., Fink, C., Raffo, J. (2017). Identifying and ranking the world’s largest clusters of inventive activity, No. 34.
Biswas, P., Pramanik, S., Giri, B. (2015). TOPSIS method for multi-attribute group decision-making under single-valued neutrosophic environment.
Carvalho, L., Meier, S., W. Wang, S. (2016). Poverty and Economic Decision-Making: Evidence from Changes in Financial Resources at Payday, 260-84.
Einy Sarkalleh, Gholam Reza, Afzali, Hossien, Khademy Nejad, Mojtba, Miandoabchi, Elnaz. (2017). Proposing a New Genetic Algorithm Multi-capacity to Solve the Multi-Storage Routing problem with Multi-capacity Vehicles. Journal of Industrial Management, 12(42), 87-98.
Evaluating Significance of Green Manufacturing Enablers Using MOORA Method for Indian Manufacturing Sector, 303-314.
FHWA/FTA. (1993). U.S. Department of Transportation. Metropolitan Planning Process: Major Metropolitan Transportation Investments, Federal Register, Part II,
Guerra, E., de Lara, A., Malizia, Díaz, P. (2009). MULTICRITERIA DECISION MAKING: Advances in MCDM Models, Algorithms, Theory, and Applications, 51(4).
Gunasekaran, A., Kobu, B. (2007). Performance measures and metrics in logistics and supply chain management: a review of recent literature (1995–2004) for research and applications.
Gunasekaran, A., Patel, C., Tirtiroglu, E. (2016). Performance measures and metrics in a supply chain environment, 71 - 87.
Hafezalkotob, A. Hafezalkotob, A. (2015). Comprehensive MULTIMOORA method with target-based attributes and integrated significant coefficients for materials selection in biomedical applications, Mater. Dec., 87, 949–959.
Hafezalkotob, A., Hafezalkotob, A. (2015). Extended MULTIMOORA method based on Shannon entropy weight for materials selection, Journal of Ind. Eng. Int., 12(1), 1–13.
Karimzadeh, R. (2008). Selection of favorable projects in transport companies using Bernardo's decision-making method. Journal of Transportation, 4(4), 329-338.
Leonidovna Zaytseva, A., Anatol'yevna Menukhova, T. (2016). On the Issue of the Innovation Policy at the Road Transport Enterprises, 11(4), 2206-2211.
Rajak, S., Parthiban, P., Dhanalakshmi, R. (2016). Sustainable transportation systems performance evaluation using fuzzy logic, 503-513.
Skrypnikov, A., Dorokhin, S., Kozlov, V. G., Chernyshova, E. V. (2017). Mathematical Model of Statistical Identification of Car Transport Informational Provision, 12, (2).
Sun, J., Yuan, Y., Yang, R., Ji, X., Wu, J. (2018). Performance evaluation of Chinese port enterprises under significant environmental concerns: An extended DEA-based analysis, 75-86.
Thokala, P., Devlin, N., Marsh, K., Stuart Peacock, S. (2016). Multiple Criteria Decision Analysis for Health Care Decision Making an Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices Task Force, 1–13.
Wang, J., Wu, J., Wang, J., Zhang, H., Chen, X. (2015). TOPSIS method for multi-attribute group decision-making, under single-valued neutrosophic environment.
