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Toplu Taşımacılıkta Müşteri Memnuniyetini Geliştirmek için Aralıklı Tip-2 Bulanık Yöntemini Temel Alan Bütünleşik Bir TOPSIS, GRA ve VIKOR

Year 2018, , 274 - 293, 16.03.2018

Muhammet Deveci

https://doi.org/10.17776/csj.347964
Cited By: 2

Abstract

Son zamanlarda, aralıklı tip-2 yöntemleri ile
çok kriterli karar verme problemleri hem araştırmacıların hem de
uygulayıcıların dikkatini çekmiştir. Bu çalışmada, İstanbul’daki tüm taşıma
modlarında (metro, otobüs ve metrobüs) müşteri memnuniyetinin değerlendirilmesi
için bir aralıklı tip-2 bulanık TOPSIS ve GRA tabanlı VIKOR yöntemi
önerilmiştir. Buna ek olarak, problemi çözmek için aralıklı tip-2 bulanık
TOPSIS yöntemi de kullanılmaktadır. Toplu taşıma kullanıcılarının hizmet
memnuniyetini etkileyen faktörleri araştırmak için bir online (çevrimiçi) anket
yürütülmüştür. Veriler, İstanbul’da toplu taşıma kullanıcısı olan 323 kişiden
toplanmıştır. Sonuç olarak, toplu taşımada müşteri memnuniyetinin
değerlendirilmesi için bir aralıklı tip-2 bulanık çok kiriterli karar verme
yöntemi önerilmiştir. Çeşitli çok kiriterli karar verme yöntemlerinin
performansları, önerilen ve aralıklı tip-2 bulanık TOPSIS yöntemlerinin
etkinliğini ve esnekliğini keşfetmek amacıyla birbiriyle karşılaştırılmıştır.
Sonuçlar, önerilen yöntemin değerlendirme problemleri ve diğer MCDM problemleri
için güvenilir ve pratik olduğunu göstermektedir.

Keywords

Müşteri memnuniyeti Toplu taşıma Aralıklı tip-2 bulanık çok kriterli karar verme TOPSIS GRA VIKOR

References

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  • [2]. Tang K. X., Waters N. M., The internet, GIS and public participation in transportation planning. Progress in Planning, 64 (2005) 7-62.
  • [3]. Turan M., Kent İçi Ulaşımın Enerji Tasarrufu Üzerindeki Olası Etkileri, Yüksek Lisans Tezi, Gazi Üniversitesi Sosyal Bilimler Enstitüsü Uluslararası İktisat Bilim Dalı, Ankara, 1998.
  • [4]. Litman T., Valuing transit service quality improvements. Journal of Public transportation. 11 (2008) 43-63.
  • [5]. APTA, Public Transportation: Benefits for 21st Century. American Public Transport Association Report, 2007, Washington, DC.
  • [6]. Belbag S., Deveci M., Uludag A. S., Comparison of Two Fuzzy Multi Criteria Decision Methods for Potential Airport Location Selection. In ICORES, 2013, 270-276.
  • [7]. Yavuz S., Deveci M., Bulanik TOPSIS ve Bulanik VIKOR Yöntemleriyle Alisveris Merkezi Kurulus Yeri Seçimi ve Bir Uygulama/Selection of Shopping Center Location with The Methods of Fuzzy VIKOR and Fuzzy TOPSIS and An Application. Ege Akademik Bakis, 14 (2014): 463.
  • [8]. Deveci M., Demirel N. Ç., John R., Özcan E., Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey. Journal of Natural Gas Science and Engineering, 27 (2015) 692-705.
  • [9]. Demirel N. Ç., Deveci M., Eser G., Comparative analysis of fuzzy multi-criteria decision making for location selection of Textile plant in Turkey. In Proceedings of International Academic Conferences (No. 4006524). International Institute of Social and Economic Sciences, 2016.
  • [10]. Deveci M., Demirel N. Ç., Ahmetoğlu E., Airline new route selection based on interval type-2 fuzzy MCDM: A case study of new route between Turkey-North American region destinations. Journal of Air Transport Management, 59 (2017) 83-99.
  • [11]. Demirel, N. Ç., Demirel, T., Deveci, M., Vardar, G., Location selection for underground natural gas storage using Choquet integral. Journal of Natural Gas Science and Engineering, 45 (2017) 368-379.
  • [12]. Deveci M., Özcan E., John R., Öner S. C., Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey. Journal of Air Transport Management. 69C (2018) 83-98.
  • [13]. Demirel T., Öner S. C., Tüzün S., Deveci M., Öner M., Demirel N. Ç., Choquet integral-based hesitant fuzzy decision-making to prevent soil erosion. Geoderma, 313 (2018) 276-289.
  • [14]. Gupta R., Srivastava B., Tamilselvam S., Making public transportation schedule information consumable for improved decision making. In 2012 15th International IEEE Conference on Intelligent Transportation Systems, 2012, 1862-1867.
  • [15]. Diab E. I., Badami M. G., El-Geneidy A. M., Bus transit service reliability and improvement strategies: Integrating the perspectives of passengers and transit agencies in North America. Transport Reviews, 35 (2015) 292-328.
  • [16]. Levner E., Ceder A., Elalouf A., Hadas Y., Shabtay D., Detection and improvement of deficiencies and failures in public-transportation networks using agent-enhanced distribution data mining. In Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on-IEEE, 2011, 694-698.
  • [17]. Dias A., Telhada J., Carvalho M. S., A decision support system for a flexible transport system. ECEC-The European Concurrent Engineering, 1 (2011) 75-79.
  • [18]. Diab E. I., & El-Geneidy A. M., 2012. Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception. Transportation Research Part A: Policy and Practice, 46(2012) 614-625.
  • [19]. Mnif S., Galoui S., Elkosantini S., Darmoul S., Said L. B., Ontology based performance evaluation of public transport systems. In Advanced Logistics and Transport (ICALT), 2015 4th International Conference on –IEEE, 2015, 205-210.
  • [20]. Sadovnikova N., Parygin D., Kalinkina M., Sanzhapov B., Ni T. N., Models and Methods for the Urban Transit System Research. In Creativity in Intelligent, Technologies and Data Science. Springer International Publishing, 2015, 488-499.
  • [21]. Mokhtarian M. N., Sadi-Nezhad S., Makui A., A new flexible and reliable interval valued fuzzy VIKOR method based on uncertainty risk reduction in decision making process: An application for determining a suitable location for digging some pits for municipal wet waste landfill. Computers & Industrial Engineering, 78 (2014) 213-233.
  • [22]. Gupta P., Mehlawat M. K., Grover N., Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Information Sciences, 370 (2016) 184-203.
  • [23]. Vahdani B., Hadipour H., Sadaghiani J. S., Amiri, M., Extension of VIKOR method based on interval-valued fuzzy sets. The International Journal of Advanced Manufacturing Technology, 47 (9-12) (2010) 1231-1239.
  • [24]. Ghorabaee M. K., Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing, 37 (2016) 221-232.
  • [25]. Qin J., Liu X., Pedrycz W., An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowledge-Based Systems, 86 (2015) 116-130.
  • [26]. Datta S., Samantra C., Mahapatra S. S., Banerjee S., Bandyopadhyay, A., Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval-valued fuzzy numbers. International Journal of Procurement Management, 5 (2012) 647-678.
  • [27]. You X. Y., You J. X., Liu H. C., Zhen L., Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Systems with Applications, 42 (2015) 1906-1916.
  • [28]. Jahan A., Edwards K. L., VIKOR method for material selection problems with interval numbers and target-based criteria. Materials & Design, 47 (2013) 759-765.
  • [29]. Liu H. C., Liu L., Wu J., Material selection using an interval 2-tuple linguistic VIKOR method considering subjective and objective weights. Materials & Design, 52 (2013) 158-167.
  • [30]. Park J. H., Cho H. J., Kwun Y. C., Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making. Computers & Mathematics with Applications, 65 (2013) 731-744.
  • [31]. Chen S. M., Lee L. W., Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert systems with applications, 37 (2010) 2790-2798.
  • [32]. Hwang C.L., Yoon K., Multiple attributes decision making methods and applications. Springer, Berlin Heidelberg, 1981.
  • [33]. Chen C.T., Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114 (2000) 1-9.
  • [34]. Chen M. F., Tzeng G. H., Combining grey relation and TOPSIS concepts for selecting an expatriate host country. Mathematical and Computer Modelling, 40 (2004) 1473-1490.
  • [35]. Kuo M. S., Wu J. W., Pei L., A soft computing method for selecting evaluation criteria of service quality. Applied mathematics and computation, 189 (2007) 241-254.
  • [36]. Kuo M. S., A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines. Transportation Research Part E: Logistics and Transportation Review, 47 (2011) 1177-1193.
  • [37]. Kuo M. S., Liang G. S., Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 38 (2011) 1304-1312.
  • [38]. Wei G. W., Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making. Expert systems with Applications, 38 (2011) 11671-11677.
  • [39]. Celik E., Bilisik O. N., Erdogan M., Gumus A. T., Baracli H., An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul. Transportation Research Part E: Logistics and Transportation Review, 58 (2013) 28-51.
  • [40]. Opricovic S., Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, 2 (1998) 5-21.
  • [41]. Opricovic S., Tzeng G.H., Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, , 156 (2004) 445-455.
  • [42]. Opricovic S., Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38 (2011) 12983-12990.
  • [43]. http://www.iett.gov.tr
  • [44]. IETT, İstatistik Raporu, 2016, İstanbul.
  • [45]. IBB, 2015-2019 Stratejik Planı, 2016,
  • [46]. İstanbul. http://www.ibb.gov.tr/tr- TR/kurumsal/Birimler/StratejikPlanlama Md/Documents/2010_2014/stratejikplan15_19.pdf
  • [47]. IETT, İstatistik Raporu, 2016, İstanbul.
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An Integrated TOPSIS, GRA and VIKOR Based on Interval Type-2 Fuzzy Method to Improve Customer Satisfaction in Public Transportation

Year 2018, , 274 - 293, 16.03.2018

Muhammet Deveci

https://doi.org/10.17776/csj.347964
Cited By: 2

Abstract

Recently,
multi-criteria decision making problems with interval type-2 fuzzy methods have
received increasing attention both from researchers and practitioners. In this study,
an interval type-2 fuzzy TOPSIS and GRA based VIKOR method is proposed for the
evaluation of the customer satisfaction in all the transportation modes in
Istanbul (metro, bus and bus rapid transit). Furthermore, the interval type-2
fuzzy TOPSIS method is also utilized to solve the problem. An online survey is
conducted to investigate factors affecting public transport users’ satisfaction
with the service. Data is collected from 323 public transport users in
Istanbul. As a result, an interval type-2 fuzzy multi-criteria decision making
method has been proposed for the evaluation of customer satisfaction in public
transportation. The performances of various multi-criteria decision making
methods are also compared with each other with a view to exploring the
effectiveness and flexibility of proposed method and interval type-2 fuzzy
TOPSIS method. The results show that the proposed method is reliable and
practical for evaluate problems and other MCDM problems.

Keywords

Customer satisfaction Public transportation Interval type-2 fuzzy multi criteria decision making TOPSIS GRA

References

  • [1]. Evren G., Ulaştırma Planlamasında Gelişmekte Olan Ülkelere Özgü Sorunlar. 3. Ulaştırma Kongresi, 1995, 11-24.
  • [2]. Tang K. X., Waters N. M., The internet, GIS and public participation in transportation planning. Progress in Planning, 64 (2005) 7-62.
  • [3]. Turan M., Kent İçi Ulaşımın Enerji Tasarrufu Üzerindeki Olası Etkileri, Yüksek Lisans Tezi, Gazi Üniversitesi Sosyal Bilimler Enstitüsü Uluslararası İktisat Bilim Dalı, Ankara, 1998.
  • [4]. Litman T., Valuing transit service quality improvements. Journal of Public transportation. 11 (2008) 43-63.
  • [5]. APTA, Public Transportation: Benefits for 21st Century. American Public Transport Association Report, 2007, Washington, DC.
  • [6]. Belbag S., Deveci M., Uludag A. S., Comparison of Two Fuzzy Multi Criteria Decision Methods for Potential Airport Location Selection. In ICORES, 2013, 270-276.
  • [7]. Yavuz S., Deveci M., Bulanik TOPSIS ve Bulanik VIKOR Yöntemleriyle Alisveris Merkezi Kurulus Yeri Seçimi ve Bir Uygulama/Selection of Shopping Center Location with The Methods of Fuzzy VIKOR and Fuzzy TOPSIS and An Application. Ege Akademik Bakis, 14 (2014): 463.
  • [8]. Deveci M., Demirel N. Ç., John R., Özcan E., Fuzzy multi-criteria decision making for carbon dioxide geological storage in Turkey. Journal of Natural Gas Science and Engineering, 27 (2015) 692-705.
  • [9]. Demirel N. Ç., Deveci M., Eser G., Comparative analysis of fuzzy multi-criteria decision making for location selection of Textile plant in Turkey. In Proceedings of International Academic Conferences (No. 4006524). International Institute of Social and Economic Sciences, 2016.
  • [10]. Deveci M., Demirel N. Ç., Ahmetoğlu E., Airline new route selection based on interval type-2 fuzzy MCDM: A case study of new route between Turkey-North American region destinations. Journal of Air Transport Management, 59 (2017) 83-99.
  • [11]. Demirel, N. Ç., Demirel, T., Deveci, M., Vardar, G., Location selection for underground natural gas storage using Choquet integral. Journal of Natural Gas Science and Engineering, 45 (2017) 368-379.
  • [12]. Deveci M., Özcan E., John R., Öner S. C., Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey. Journal of Air Transport Management. 69C (2018) 83-98.
  • [13]. Demirel T., Öner S. C., Tüzün S., Deveci M., Öner M., Demirel N. Ç., Choquet integral-based hesitant fuzzy decision-making to prevent soil erosion. Geoderma, 313 (2018) 276-289.
  • [14]. Gupta R., Srivastava B., Tamilselvam S., Making public transportation schedule information consumable for improved decision making. In 2012 15th International IEEE Conference on Intelligent Transportation Systems, 2012, 1862-1867.
  • [15]. Diab E. I., Badami M. G., El-Geneidy A. M., Bus transit service reliability and improvement strategies: Integrating the perspectives of passengers and transit agencies in North America. Transport Reviews, 35 (2015) 292-328.
  • [16]. Levner E., Ceder A., Elalouf A., Hadas Y., Shabtay D., Detection and improvement of deficiencies and failures in public-transportation networks using agent-enhanced distribution data mining. In Industrial Engineering and Engineering Management (IEEM), 2011 IEEE International Conference on-IEEE, 2011, 694-698.
  • [17]. Dias A., Telhada J., Carvalho M. S., A decision support system for a flexible transport system. ECEC-The European Concurrent Engineering, 1 (2011) 75-79.
  • [18]. Diab E. I., & El-Geneidy A. M., 2012. Understanding the impacts of a combination of service improvement strategies on bus running time and passenger’s perception. Transportation Research Part A: Policy and Practice, 46(2012) 614-625.
  • [19]. Mnif S., Galoui S., Elkosantini S., Darmoul S., Said L. B., Ontology based performance evaluation of public transport systems. In Advanced Logistics and Transport (ICALT), 2015 4th International Conference on –IEEE, 2015, 205-210.
  • [20]. Sadovnikova N., Parygin D., Kalinkina M., Sanzhapov B., Ni T. N., Models and Methods for the Urban Transit System Research. In Creativity in Intelligent, Technologies and Data Science. Springer International Publishing, 2015, 488-499.
  • [21]. Mokhtarian M. N., Sadi-Nezhad S., Makui A., A new flexible and reliable interval valued fuzzy VIKOR method based on uncertainty risk reduction in decision making process: An application for determining a suitable location for digging some pits for municipal wet waste landfill. Computers & Industrial Engineering, 78 (2014) 213-233.
  • [22]. Gupta P., Mehlawat M. K., Grover N., Intuitionistic fuzzy multi-attribute group decision-making with an application to plant location selection based on a new extended VIKOR method. Information Sciences, 370 (2016) 184-203.
  • [23]. Vahdani B., Hadipour H., Sadaghiani J. S., Amiri, M., Extension of VIKOR method based on interval-valued fuzzy sets. The International Journal of Advanced Manufacturing Technology, 47 (9-12) (2010) 1231-1239.
  • [24]. Ghorabaee M. K., Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robotics and Computer-Integrated Manufacturing, 37 (2016) 221-232.
  • [25]. Qin J., Liu X., Pedrycz W., An extended VIKOR method based on prospect theory for multiple attribute decision making under interval type-2 fuzzy environment. Knowledge-Based Systems, 86 (2015) 116-130.
  • [26]. Datta S., Samantra C., Mahapatra S. S., Banerjee S., Bandyopadhyay, A., Green supplier evaluation and selection using VIKOR method embedded in fuzzy expert system with interval-valued fuzzy numbers. International Journal of Procurement Management, 5 (2012) 647-678.
  • [27]. You X. Y., You J. X., Liu H. C., Zhen L., Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. Expert Systems with Applications, 42 (2015) 1906-1916.
  • [28]. Jahan A., Edwards K. L., VIKOR method for material selection problems with interval numbers and target-based criteria. Materials & Design, 47 (2013) 759-765.
  • [29]. Liu H. C., Liu L., Wu J., Material selection using an interval 2-tuple linguistic VIKOR method considering subjective and objective weights. Materials & Design, 52 (2013) 158-167.
  • [30]. Park J. H., Cho H. J., Kwun Y. C., Extension of the VIKOR method to dynamic intuitionistic fuzzy multiple attribute decision making. Computers & Mathematics with Applications, 65 (2013) 731-744.
  • [31]. Chen S. M., Lee L. W., Fuzzy multiple attributes group decision-making based on the interval type-2 TOPSIS method. Expert systems with applications, 37 (2010) 2790-2798.
  • [32]. Hwang C.L., Yoon K., Multiple attributes decision making methods and applications. Springer, Berlin Heidelberg, 1981.
  • [33]. Chen C.T., Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy sets and systems, 114 (2000) 1-9.
  • [34]. Chen M. F., Tzeng G. H., Combining grey relation and TOPSIS concepts for selecting an expatriate host country. Mathematical and Computer Modelling, 40 (2004) 1473-1490.
  • [35]. Kuo M. S., Wu J. W., Pei L., A soft computing method for selecting evaluation criteria of service quality. Applied mathematics and computation, 189 (2007) 241-254.
  • [36]. Kuo M. S., A novel interval-valued fuzzy MCDM method for improving airlines’ service quality in Chinese cross-strait airlines. Transportation Research Part E: Logistics and Transportation Review, 47 (2011) 1177-1193.
  • [37]. Kuo M. S., Liang G. S., Combining VIKOR with GRA techniques to evaluate service quality of airports under fuzzy environment. Expert Systems with Applications, 38 (2011) 1304-1312.
  • [38]. Wei G. W., Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making. Expert systems with Applications, 38 (2011) 11671-11677.
  • [39]. Celik E., Bilisik O. N., Erdogan M., Gumus A. T., Baracli H., An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul. Transportation Research Part E: Logistics and Transportation Review, 58 (2013) 28-51.
  • [40]. Opricovic S., Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, 2 (1998) 5-21.
  • [41]. Opricovic S., Tzeng G.H., Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, , 156 (2004) 445-455.
  • [42]. Opricovic S., Fuzzy VIKOR with an application to water resources planning. Expert Systems with Applications, 38 (2011) 12983-12990.
  • [43]. http://www.iett.gov.tr
  • [44]. IETT, İstatistik Raporu, 2016, İstanbul.
  • [45]. IBB, 2015-2019 Stratejik Planı, 2016,
  • [46]. İstanbul. http://www.ibb.gov.tr/tr- TR/kurumsal/Birimler/StratejikPlanlama Md/Documents/2010_2014/stratejikplan15_19.pdf
  • [47]. IETT, İstatistik Raporu, 2016, İstanbul.
  • [48]. IBB, 2015-2019 Stratejik Planı, 2016, İstanbul. http://www.ibb.gov.tr/tr-TR/kurumsal/Birimler/StratejikPlanlamaMd/Documents/2010_2014/stratejikplan15_19.pdf
There are 48 citations in total.

Details

Primary Language English
Journal Section Engineering Sciences
Authors

Muhammet Deveci

Publication Date March 16, 2018
Submission Date October 31, 2017
Acceptance Date March 15, 2018
Published in Issue Year 2018

Cite

APA Deveci, M. (2018). An Integrated TOPSIS, GRA and VIKOR Based on Interval Type-2 Fuzzy Method to Improve Customer Satisfaction in Public Transportation. Cumhuriyet Science Journal, 39(1), 274-293. https://doi.org/10.17776/csj.347964

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