پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شمارهها | 6,223 |
| تعداد مقالات | 67,680 |
| تعداد مشاهده مقاله | 114,874,791 |
| تعداد دریافت فایل اصل مقاله | 89,547,323 |
A Hybrid Fuzzy Decision-Making Approach to Select the Best online-taxis business | ||
| Advances in Industrial Engineering | ||
| دوره 54، شماره 2، تیر 2020، صفحه 99-120 اصل مقاله (805.51 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jieng.2021.320051.1754 | ||
| نویسندگان | ||
| S. Sina Aria1؛ S. Ali Torabi* 2؛ Sina Nayeri2 | ||
| 1School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Ira | ||
| 2School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran. | ||
| چکیده | ||
| In the recent decade, significant growth of internet-based platforms and changes in people’s moving preferences has led to an increase in the electronic taxis businesses. Hence, investigating the factors affected by such businesses can help increase their profits and, at the same, time their customers’ satisfaction level. In this study, a hybrid fuzzy decision-making approach is proposed to examine the best online-taxis business selection problem. The proposed framework firstly determines the interrelationships between criteria and sub-criteria, by applying the Fuzzy Decision making trial and evaluation laboratory (FDEMATEL) method. Then, the weights of the criteria and sub-criteria are calculated using an integrated Fuzzy Best-Worst Method (FBWM) and the Fuzzy Analytic network process (FANP). In this regard, at first, the local weights of indicators are calculated using the FBWM regardless of interrelationships between them. Then, the final (i.e. global) weights of indicators, considering their interrelationships, are measured employing the FANP method. Afterwards, the feasible alternatives are prioritized by employing the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) method. For each step of the proposed framework, a questionnaire is designed and distributed between experts. The results show that the most important criteria and sub-criteria for passengers are cost and reasonable price, respectively. Finally, some managerial insights are provided. | ||
| کلیدواژهها | ||
| Startup-Based Business؛ Online-taxis؛ Multiple-attribute decision-making؛ Hybrid methods | ||
| مراجع | ||
|
[1] Liu, X.. (2019). “Evolution and simulation analysis of co-opetition behavior of E-business internet platform based on evolutionary game theory.” Cluster Computing, Vol.22, No.4, pp.10241-10250.
[2] Zhang, Y., Guo, H., Li, C., Wang, W., Jiang, X. and Liu, Y. (2016). “Which one is more attractive to traveler, taxi or tailored taxi? An empirical study in China.” Procedia engineering, Vol.137, pp.867-875.
[3] Munandar, J.M. and Munthe, R.C.F. (2019). “How technology affects behavioral intention (case study of online transportation in Indonesia and Thailand).” The South East Asian Journal of Management.
[4] Etminani-Ghasrodashti, R. and Hamidi, S. (2019). “Individuals’ Demand for Ride-hailing Services: Investigating the Combined Effects of Attitudinal Factors, Land Use, and Travel Attributes on Demand for App-based Taxis in Tehran, Iran”. Sustainability, Vol.11, No. 20, p.5755.
[5] Eboli, L. and Mazzulla, G. (2012). “Structural equation modelling for analysing passengers’ perceptions about railway services”. Procedia-Social and Behavioral Sciences, Vol.54, pp.96-106.
[6] Si, Y., Guan, H. and Cui, Y. (2019). “Research on the Choice Behavior of Taxis and Express Services Based on the SEM-Logit Model”. Sustainability, Vol.11, No.10, p.2974.
[7] Cheewathanakornkul, C. and Jiratchot, C. (2018). “Customer satisfaction and word of mouth towards online taxi providers: a case study of Grab and Uber”. Journal of Supply Chain Management: Research and Practice, Vol.12 No.1, pp.66-76.
[8] Sir, G.D.B. and Çalışkan, E. (2019). “Assessment of development regions for financial support allocation with fuzzy decision making: A case of Turkey”. Socio-Economic Planning Sciences, Vol. 66, pp.161-169.
[9] Skalna, I., Rebiasz, B., Gawel, B., Basiura, B., Duda, J., Opila, J. and Pelech-Pilichowski, T. (2015). “Advances in fuzzy decision making”. Studies in Fuzziness and Soft Computing, Vol. 333.
[10] Lin, C.J. and Wu, W.W. (2008). “A causal analytical method for group decision-making under fuzzy environment”. Expert Systems with Applications, Vol. 34, No.1, pp.205-213.
[11] Baykasoğlu, A., Kaplanoğlu, V., Durmuşoğlu, Z.D. and Şahin, C. (2013). “Integrating fuzzy DEMATEL and fuzzy hierarchical TOPSIS methods for truck selection”. Expert Systems with Applications, Vol. 40, No.3, pp.899-907.
[12] Rezaei, J. (2015). “Best-worst multi-criteria decision-making method”. Omega, Vol. 53, pp.49-57.
[13] Guo, S. and Zhao, H. (2017). “Fuzzy best-worst multi-criteria decision-making method and its applications”. Knowledge-Based Systems, Vol. 121, pp.23-31.
[14] You, P., Guo, S., Zhao, H. and Zhao, H. (2017). “Operation performance evaluation of power grid enterprise using a hybrid BWM-TOPSIS method”. Sustainability, Vol. 9, No. 12, p.2329.
[15] Saaty, T.L. (1996). “Decision making with dependence and feedback: The analytic network process” Vol. 4922. Pittsburgh: RWS publications.
[16] Büyüközkan, G. and Çifçi, G. (2012). “A novel hybrid MCDM approach based on fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS to evaluate green suppliers”. Expert Systems with Applications, Vol. 39, No. 3, pp.3000-3011.
[17] Jain, V., Sangaiah, A.K., Sakhuja, S., Thoduka, N. and Aggarwal, R. (2018). “Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry”. Neural Computing and Applications, Vol. 29, No. 7, pp.555-564.
[18] Hsieh, C.H. and Chen, S.H. (1999). A model and algorithm of fuzzy product positioning. Information sciences, Vol. 121, No. 2, pp.61-82.
[19] Chen, S.H., Wang, P.W., Chen, C.M. and Lee, H.T. (2010). “An analytic hierarchy process approach with linguistic variables for selection of an R&D strategic alliance partner”. Computers & Industrial Engineering, Vol. 58, No. 2, pp.278-287. | ||
|
آمار تعداد مشاهده مقاله: 362 تعداد دریافت فایل اصل مقاله: 338 |
||