سنجش رضایت مشتری با استفاده از تصمیم گیری گروهی و تکنیک Ftopsis ( مطالعه موردی شرکت پارس پرند حیان )
محورهای موضوعی : مدیریت صنعتیAli-Akbar Farhangi 1 , Mahmmud Lotfi 2 , Bahare Karbasian 3
1 - Professor in Management, University of Tehran
2 - PhD Student in Industrial Management, Faculty of Management, University of Tehran, Member of Academic Staff, Islamic Azad University, Mobarake Branch, Isfahan, Iran
3 - PhD Student in Industrial Management, Faculty of Management, University of Tehran, Kish Campus
کلید واژه: تصمیم گیری گروهی, Group decision making, تصمیم گیری چند شاخصه, تکنیک تاپسیس فازی, customer satisfaction, رضایتمندی مشتری, Ftopsis, اوزان کاردینال, Cardinal weight,
چکیده مقاله :
در دنیای امروز سازمانهای موفق خواهند بود که بتوانند رضایت مشتریان خود را بیشتر تأمین کنند چرا که مشتری مهمترین دارایی سازمان می باشد. با توجه به اهمیت موضوع، این مقاله بر ان است که با استفاده از تکنیکهای تصمیم گیری گروهی و تکنیکهای تصمیم گیری چند معیاره فازی اقدام به رتبه بندی عوامل موثر بررضایتمندی مشتری نماید. در این راستا ابتدا با استفاده از تکنیک دلفی به همراه مقیاس لیکرت فازی به عنوان روشی مناسب برای تهیه پرسشنامه جهت شناسایی معیارها و شاخصهای آن استفاده شده است. در ادامه با استفاده از تکنیک تأپسیس فازی جهت رتبه بندی معیارهای موثر بررضایتمندی به مشتریان اقدام شده است. و با توجه به وجود ابهام و عدم قطعیت در اظهارات تصمیم گیرندگان بیان داده ها به صورت قطعی نامناسب تشخیص داده شده است و از آنجا که قضاوتهای انسانی نمیتوانند به وسیله مقادیر عددی دقیق برآوردشوند و معمولاً مبهم هستند از روشهای تصمیم گیری چند شاخصه فازی استفاده شده است. در ادامه با استفاده از یک مدل برنامه ریزی خطی اقدام به تعیین اوزان کاردینال سئوالات مطرح شده در پرسشنامه گردیده است.در انتها یک فرمول برای اندازه گیری رضایتمندی مشتریان ارائه شده است.
Abstract In today’s world, successful organizations will be able to meet its customer satisfaction because customers are the most important assets. This paper tends to use the group decision-making and fuzzy multi-criteria decision-making techniques to rank the customer’s satisfaction factors. In this respect, the Delphi technique with a fuzzy Likert scale is used as suitable methods for preparing a questionnaire to identify criteria and indicators. The results indicate that the effective metrics for ranking fuzzy TOPSIS technique leads to acting customer’s satisfaction.
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2- Asgharpour, M., J. (2004). Multiple criteria Decision Making. Tehran university publication.
3- Azar, Adel, & Momeni, M. (1999). Statistics and its application in management. Samt publishing co.
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5- Chen, S.J,& Hawng, C.L.(1992). Fuzzy multiple attribute decision making, Methods and opplications, springer -Verlag, New york.
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7- Ertagrul, I. & karakasoglu, N. (2007). Fuzzy Topsis method for academic member Selection in enginnering Faculty., M. Iskender (Ed). Innovations in e-learning, instruction technology, assessment and engineering education. The Netherlands: Springer.
8- Expert Systems with Applications, 36 (2), 3887–3895.
9- Freund, J.E,. (1992).Mathematical statics prentice. Hall Inc., Fifth edition.
10- Gob, R., Mccollin., & Cond Ramalhoto, M.F.(2007). Ordinal methodology in the analysis of likert scales Quality and Quantity, 41(5), 601-626.
11- Haghshenas, Farideh & Saiedi, Nima. (2011).Ranking of effective factor on carpet industry with topsis technique. Journal of new marketing.1(1),137-154.
12- Hazer, M. (1996). Decision making in management. Center for public Management training.
13- Hwang, C., Hong, D.H., and Seok, k., H. (2006). Support vector interval regression Machine for crisp input and output data. Journal of Fuzzy sets and systems, 156(8), 111- 1125.
14- kavosi, Seyed Mohammad Reza & Saghaei, Abbas.(2001). Method of measuring customer Satisfaction, Tehran, publisher Sabzan. Second Edition.
15- kazemi, M. & Mohajer, Sh.(2010).Ranking of effective factors on customer satisfaction Concerning service Quality in Branches of Eghtesad Novin Bank, Mashhad. Journal of Industrial Management Faculty of Humanities Islamic Azad university of Sanandaj, 4(10).
16- kelemenis, A. & Askounis, D. (2010). A new topsis based multi multi-criteria approach to personnel selection. Expert Systems With applications, 37,499-508.
17- Mirzaichaboki , Mohsen. (2010). Formulating Strategy and ranking of strategy with fuzzy topsis for choka company. Islamic Azad university central branch.
18- Moradi, M.(2011).Designing and explaining the customer loyalty model in insurance industry. Journal of industrial management faculty of Humanities Islamic Azad university of Sanandaj, 5(14).
19- Robson, Mike. (1994). Problem solving in Groups. Gower Publisher Company, second edition. Limited, USA.
20- Semih, O., Selin, Soner, & kara, Isik, E. (2009). Long Term Supplier Selection Using a Combined Fuzzy MCDM Approach: A Case Study for a Telecommunication Company. journal of Expert Systems with Applications, 36(2), 3887-3895.
21- Yeh, C.H., Deng, H. (2004). A Practical Approach to Fuzzy Utilities Comparison in Fuzzy Multi-Criteria Analysis, International Journal of Approximate Reasoning, 35 (2), 179-194.
22- Yue, Z.L, Jiayy & ye, G.D. (2009). An Approach For multiple attribute group decision making .International journal System, 17(3), 317- 332.
_||_1- Asgharpour, M., J. (2003). Group Decision making and game theory. Tehran university publication.
2- Asgharpour, M., J. (2004). Multiple criteria Decision Making. Tehran university publication.
3- Azar, Adel, & Momeni, M. (1999). Statistics and its application in management. Samt publishing co.
4- Azar, Adel. & Rajobzodeh, Ali. (2011). Application Decision making. Negah Danedh press.
5- Chen, S.J,& Hawng, C.L.(1992). Fuzzy multiple attribute decision making, Methods and opplications, springer -Verlag, New york.
6- Dick, A. S., & Basu, k. (1994). Customer loyalty: toward and integrated conceptual framework. Journal of the Academy and marketing science, 22 (2), 99-113.
7- Ertagrul, I. & karakasoglu, N. (2007). Fuzzy Topsis method for academic member Selection in enginnering Faculty., M. Iskender (Ed). Innovations in e-learning, instruction technology, assessment and engineering education. The Netherlands: Springer.
8- Expert Systems with Applications, 36 (2), 3887–3895.
9- Freund, J.E,. (1992).Mathematical statics prentice. Hall Inc., Fifth edition.
10- Gob, R., Mccollin., & Cond Ramalhoto, M.F.(2007). Ordinal methodology in the analysis of likert scales Quality and Quantity, 41(5), 601-626.
11- Haghshenas, Farideh & Saiedi, Nima. (2011).Ranking of effective factor on carpet industry with topsis technique. Journal of new marketing.1(1),137-154.
12- Hazer, M. (1996). Decision making in management. Center for public Management training.
13- Hwang, C., Hong, D.H., and Seok, k., H. (2006). Support vector interval regression Machine for crisp input and output data. Journal of Fuzzy sets and systems, 156(8), 111- 1125.
14- kavosi, Seyed Mohammad Reza & Saghaei, Abbas.(2001). Method of measuring customer Satisfaction, Tehran, publisher Sabzan. Second Edition.
15- kazemi, M. & Mohajer, Sh.(2010).Ranking of effective factors on customer satisfaction Concerning service Quality in Branches of Eghtesad Novin Bank, Mashhad. Journal of Industrial Management Faculty of Humanities Islamic Azad university of Sanandaj, 4(10).
16- kelemenis, A. & Askounis, D. (2010). A new topsis based multi multi-criteria approach to personnel selection. Expert Systems With applications, 37,499-508.
17- Mirzaichaboki , Mohsen. (2010). Formulating Strategy and ranking of strategy with fuzzy topsis for choka company. Islamic Azad university central branch.
18- Moradi, M.(2011).Designing and explaining the customer loyalty model in insurance industry. Journal of industrial management faculty of Humanities Islamic Azad university of Sanandaj, 5(14).
19- Robson, Mike. (1994). Problem solving in Groups. Gower Publisher Company, second edition. Limited, USA.
20- Semih, O., Selin, Soner, & kara, Isik, E. (2009). Long Term Supplier Selection Using a Combined Fuzzy MCDM Approach: A Case Study for a Telecommunication Company. journal of Expert Systems with Applications, 36(2), 3887-3895.
21- Yeh, C.H., Deng, H. (2004). A Practical Approach to Fuzzy Utilities Comparison in Fuzzy Multi-Criteria Analysis, International Journal of Approximate Reasoning, 35 (2), 179-194.
22- Yue, Z.L, Jiayy & ye, G.D. (2009). An Approach For multiple attribute group decision making .International journal System, 17(3), 317- 332.