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Extraction of Key Factors and Its Interrelationship Critical to Determining the Satisfaction Degree of User Experience in Taxi Passenger Service Using DEMATEL

  • Chunrong Liu
  • Yi Jin
  • Xu Zhu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10920)

Abstract

The user experience of consumers as passengers in taxicab is an important determinant of the satisfaction degree of taxi passenger service. In this study, twelve main factors influential to user experience in taxicab are selected based on twenty-one preliminary factors collected by questionnaire survey and depth interview. The face-to-face surveys are deployed with Decision-Making Trial and Evaluation Laboratory (DEMATEL) questionnaires to evaluate by subjects the directions and the degrees of the interactions between any two main factors. The scores of the Prominence and the Relation of main factors are calculated in DEMATEL tool with thirty-two effective pieces of data as input, and the causal diagram is drawn. The findings show that three factors including ‘the driver’s familiarity with the local roads’, ‘long detours and intentional slowly driving’ and ‘driver’s chatting to passenger(s) when driving’, are key factors influencing the satisfaction degree of the passenger’s user experience, while other three factors such as ‘weather conditions’ and ‘driver’s talking on the cell phone when driving’, have great impact on other main factors, respectively. It can be summarized that the degree of satisfaction of taxi passenger is highly relevant to taxi driver side in the following ways: (1) due to the negative economy and timeliness, the driver’s unfamiliarity with the local roads and behaviors of long detours and intentional slowly driving will heavily decrease the satisfaction degree of user experience; and (2) due to the unsafety, the same is true for driver’s chatting to passenger(s) and talking on the cell phone when driving.

Keywords

Taxi passenger service The satisfaction degree of user experience Decision-Making Trial and Evaluation Laboratory (DEMATEL) Consumer research 

References

  1. 1.
    Liu, L., Chen, Y., Zhang, W.: Passenger demand forecast model for Beijing taxis. Transp. Res. 13, 89–92 (2010). (in Chinese)Google Scholar
  2. 2.
    Hu, S.: Study on the evaluation index system of taxi service to passengers demand oriented. Logist. Eng. Manag. 37, 129–130 (2015). (in Chinese)Google Scholar
  3. 3.
    Curry, G.L., Vany, A.D., Feldman, R.M.: A queueing model of airport passenger departures by taxi: competition with a public transportation mode. Transp. Res. 12, 115–120 (1978)CrossRefGoogle Scholar
  4. 4.
    Cairns, R.D., Liston-Heyes, C.: Competition and regulation in the taxi industry. J. Public Econ. 59, 1–15 (1996)CrossRefGoogle Scholar
  5. 5.
    Xiong, Z.: Beijing taxi market legal regulations. Master’s thesis, Capital University of Economics and Business, Beijing (2013). (in Chinese)Google Scholar
  6. 6.
    Yang, H., Fung, C.S., Wong, K.I., et al.: Nonlinear pricing of taxi services. Transp. Res. Part A 44, 337–348 (2010)Google Scholar
  7. 7.
    Gu, H., Zheng, J.: Economic analysis of taxi price system - taking Beijing as an example. Price Theor. Pract. 04, 16–18 (2002). (in Chinese)Google Scholar
  8. 8.
    Anderson, D.N.: “Not just a taxi”? For-profit ridesharing, driver strategies, and VMT. Transportation 41(5), 1099–1117 (2014)CrossRefGoogle Scholar
  9. 9.
    Rayle, L., Shaheen, S., Chan, N., et al.: App-based, on-demand ride services: comparing taxi and ridesourcing trips and user characteristics in San Francisco. Transportation Research Board Annual Meeting (2014)Google Scholar
  10. 10.
    Zhang, D., Sun, L., Li, B., et al.: Understanding taxi service strategies from taxi GPS traces. IEEE Trans. Intell. Transp. Syst. 16, 123–135 (2015)CrossRefGoogle Scholar
  11. 11.
    Hai, Y., Yan, W.L., Wong, S.C., et al.: A macroscopic taxi model for passenger demand, taxi utilization and level of services. Transportation 27, 317–340 (2000)CrossRefGoogle Scholar
  12. 12.
    Shi, Y., Lian, Z.: Optimization and strategic behavior in a passenger-taxi service system. Eur. J. Oper. Res. 249, 1024–1032 (2016)MathSciNetCrossRefGoogle Scholar
  13. 13.
    Leng, B., Du, H., Wang, J., et al.: Analysis of taxi drivers’ behaviors within a battle between two taxi Apps. IEEE Trans. Intell. Transp. Syst. 17, 296–300 (2015)CrossRefGoogle Scholar
  14. 14.
    Osswald, S., Zehe, D., Mundhenk, P., et al.: HMI development for a purpose-built electric taxi in Singapore. In: Proceedings of the 15th International Conference on Human-Computer Interaction with Mobile Devices and Services, MobileHCI 2013, pp. 434–439. ACM, New York (2013)Google Scholar
  15. 15.
    Moreira-Matias, L., Gama, J., Ferreira, M., Mendes-Moreira, J., Damas, L.: On predicting the taxi-passenger demand: a real-time approach. In: Correia, L., Reis, L.P., Cascalho, J. (eds.) EPIA 2013. LNCS (LNAI), vol. 8154, pp. 54–65. Springer, Heidelberg (2013).  https://doi.org/10.1007/978-3-642-40669-0_6CrossRefGoogle Scholar
  16. 16.
    Moreira-Matias, L., Gama, J., Ferreira, M., et al.: Predicting taxi–passenger demand using streaming data. IEEE Trans. Intell. Transp. Syst. 14(3), 1393–1402 (2013)CrossRefGoogle Scholar
  17. 17.
    Yan, S., Chen, C.Y., Wu, C.C.: Solution methods for the taxi pooling problem. Transportation 39, 723–748 (2012)CrossRefGoogle Scholar
  18. 18.
    Zhang, S., Wang, Z.: Correction: inferring passenger denial behavior of taxi drivers from large-scale taxi traces. PLoS ONE 12(2), e0171876 (2017)CrossRefGoogle Scholar
  19. 19.
    Brandenburg, S., Oehl, M., Seigies, K.: German taxi drivers’ experience and expression of driving anger: are the driving anger scale and the driving anger expression inventory valid measures? Traffic Inj. Prev. 18(8), 807–812 (2017)CrossRefGoogle Scholar
  20. 20.
    Tang, L.L., Li, Q.Q., Chang, X.M., et al.: Modeling of taxi drivers’ experience for routing applications. Sci. China: Technol. Sci. 53, 44–51 (2010)CrossRefGoogle Scholar
  21. 21.
    Shen, H.: Method of calculating satisfaction index of passengers on taxi services. Jiangsu Commun. 11, 31–32 (2003). (in Chinese)Google Scholar
  22. 22.
    Li, D.: Passenger experience-oriented Beijing taxi complaints effective mechanism. Decis. Inf. 5, 96–97 (2015). (in Chinese)Google Scholar
  23. 23.
    Zhou, G.: From customer experience to passenger experience: the value of experiential management in taxi services. China Mark. 19, 27–28 (2015). (in Chinese)CrossRefGoogle Scholar
  24. 24.
    Li, D., Li, L.: Discussion on passenger experience-oriented optimum design of conventional bus. In: Proceedings of China Urban Transportation Planning Annual Meeting and the 27th Symposium, pp. 1–12. China Architecture & Building Press, Beijing (2014). (in Chinese)Google Scholar
  25. 25.
    Hensher, D.A., Mulley, C., Yahya, N.: Passenger experience with quality-enhanced bus service: the tyne and wear ‘superoute’ services. Transportation 37, 239–256 (2010)CrossRefGoogle Scholar
  26. 26.
    Stradling, S., Carreno, M., Rye, T., et al.: Passenger perceptions and the ideal urban bus journey experience. Transp. Policy 14, 283–292 (2007)CrossRefGoogle Scholar
  27. 27.
    Acevesgonzález, C., May, A., Cook, S.: An observational comparison of the older and younger bus passenger experience in a developing world city. Ergonomics 59, 840–850 (2016)CrossRefGoogle Scholar
  28. 28.
    Ahmadpour, N., Lindgaard, G., Robert, J.M., et al.: The thematic structure of passenger comfort experience and its relationship to the context features in the aircraft cabin. Ergonomics 57, 801–815 (2014)CrossRefGoogle Scholar
  29. 29.
    Bogicevic, V., Yang, W., Bilgihan, A., et al.: Airport service quality drivers of passenger satisfaction. Tourism Rev. 68, 3–18 (2013)CrossRefGoogle Scholar
  30. 30.
    Ahmadpour, N., Robert, J.M., Lindgaard, G.: Aircraft passenger comfort experience: un-derlying factors and differentiation from discomfort. Appl. Ergon. 52, 301–308 (2016)CrossRefGoogle Scholar
  31. 31.
    Harrison, A., Popovic, V., Kraal, B.J., et al.: Challenges in passenger terminal design: a conceptual model of passenger experience. In: Proceedings of the Design Research Society (DRS) 2012 Conference, pp. 344–356. Chulalongkorn University, Bangkok (2012)Google Scholar
  32. 32.
    Chou, J.S., Kim, C.: A structural equation analysis of the QSL relationship with passenger riding experience on high speed rail: an empirical study of Taiwan and Korea. Expert Syst. Appl. 36, 6945–6955 (2009)CrossRefGoogle Scholar
  33. 33.
    Foth, M., Schroeter, R.: Enhancing the experience of public transport users with urban screens and mobile applications. In: International Academic Mindtrek Conference: Envisioning Future Media Environments, pp. 33–40. ACM, New York (2010)Google Scholar
  34. 34.
    Fu, Z., Zhang, L., Wu, Q.: About inner space design for trains. Art Des. 4, 34–37 (2008). (in Chinese)Google Scholar
  35. 35.
    Bai, W.: Analysis of interior decoration of subway carriages in the view of ride experience. Mod. Decor. (Theory) 9, 17 (2016). (in Chinese)Google Scholar
  36. 36.
    Xu, J., Zhang, B., Wang, Y.: Emotional design of metro interior facilities. Packag. Eng. 16, 168–172 (2017). (in Chinese)Google Scholar
  37. 37.
    Zheng, Z.: Service design of urban transfer guidance system with ‘unity of knowledge and practice’. Packag. Eng. 38, 19–23 (2017). (in Chinese)Google Scholar
  38. 38.
    Zhou, K.: Analysis of transfer behavior and research on transfer facility configuration in high-speed railway passenger transport hub. Doctoral dissertation, Harbin Institute of Technology (2013). (in Chinese)Google Scholar
  39. 39.
    Wu, H., Chang, S.: A case study of using DEMTEL method to identify critical factors in green supply chain management. Appl. Math. Comput. 256, 394–403 (2015)MATHGoogle Scholar
  40. 40.
    Lin, T., Yang, Y.H., Kang, J.S., Yu, H.C.: Using DEMATEL method to explore the core competences and causal effect of the IC design service company: an empirical case study. Expert Syst. Appl. 38, 6262–6268 (2011)CrossRefGoogle Scholar
  41. 41.
    Shieh, J.I., Wu, H.H., Huang, K.K.: DEMATEL method in identifying key success factors of hospital service quality. Knowl.-Based Syst. 23, 277–282 (2010)CrossRefGoogle Scholar
  42. 42.
    Wang, W.C., Lin, Y.H., Lin, C.L., Chung, C.H., Lee, M.T.: DEMATEL-based model to improve the performance in a matrix organization. Expert Syst. Appl. 39, 4978–4986 (2012)CrossRefGoogle Scholar
  43. 43.
    Wu, H.H., Chen, H.K., Shieh, J.I.: Evaluating performance criteria of employment service outreach program personnel by DEMATEL method. Expert Syst. Appl. 37, 5219–5223 (2010)CrossRefGoogle Scholar
  44. 44.
    Wu, W.W.: Segmenting critical factors for successful knowledge management implementation using the fuzzy DEMATEL method. Appl. Soft Comput. 12, 527–535 (2012)CrossRefGoogle Scholar
  45. 45.
    Bianchi, C., Montemaggiore, G.B.: Building ‘dynamic’ balanced scorecards to enhance strategy design and planning in public utilities: key-findings from a project in a city water company. Revista de Dinámica de Sistemas 2(2), 3–35 (2006)Google Scholar
  46. 46.
    Li, Y., Hu, Y., Zhang, X., et al.: An evidential DEMATEL method to identify critical success factors in emergency management. Appl. Soft Comput. 22, 504–510 (2014)CrossRefGoogle Scholar
  47. 47.
    Altuntas, S., Dereli, T.: A novel approach based on DEMATEL method and patent citation analysis for prioritizing a portfolio of investment projects. Expert Syst. Appl. 42, 1003–1012 (2015)CrossRefGoogle Scholar
  48. 48.
    Lu, X., Wang, K., Hu, J., et al.: A fuzzy-DEMATEL-based analysis of the factors that influence users’ participation behaviors under the crowdsourcing model. Manag. Rev. 29, 101–109 (2017). (in Chinese)Google Scholar
  49. 49.
    Zhang, C., Wu, B.: Measurement of credit risk on China’s peer-to-peer online lending. Stat. Inf. Forum 32, 110–115 (2017). (in Chinese)Google Scholar
  50. 50.
    Vinodh, S., Balagi, T.S.S., Patil, A.: A hybrid MCDM approach for agile concept selection using fuzzy DEMATEL, fuzzy ANP and fuzzy TOPSIS. Int. J. Adv. Manuf. Technol. 83(9–12), 1979–1987 (2016)CrossRefGoogle Scholar
  51. 51.
    Shi, R., Yang, J.: Analysis and research on influencing factors of civil aviation air traffic controllers’ performance based on DEMATEL. J. Civil Aviat. Univ. China 34, 31–35 (2016). (in Chinese)Google Scholar
  52. 52.
    Wu, W.W., Lee, Y.T.: Developing global managers’ competencies using the fuzzy DEMATEL method. Expert Syst. Appl. 31, 499–507 (2007)CrossRefGoogle Scholar
  53. 53.
    Su, C.M., Horng, D.J., Tseng. M.L., et al.: Improving sustainable supply chain management using a novel hierarchical grey-DEMATEL approach. J. Clean. Prod. 134, 469–481 (2016)CrossRefGoogle Scholar
  54. 54.
    Mirmousa, S., Dehnavi, H.D.: Development of criteria of selecting the supplier by using the fuzzy DEMATEL method. Procedia - Soc. Behav. Sci. 230, 281–289 (2016)CrossRefGoogle Scholar
  55. 55.
    Khompatraporn, C., Somboonwiwat, T.: Causal factor relations of supply chain competitiveness via fuzzy DEMATEL method for Thai automotive industry. Prod. Plan. Control 28, 538–551 (2017)CrossRefGoogle Scholar
  56. 56.
    Lan, S., Zhong, R.Y.: An evaluation model for financial reporting supply chain using DEMATEL-ANP. Procedia Cirp. 56, 516–519 (2016)CrossRefGoogle Scholar
  57. 57.
    Li, Y., Huang, J., Chen, M.: The analysis of factors influencing on the collaborative development of manufacturing industry and logistics industry based on DEMATEL. J. Wuhan Univ. Technol. (Inf. Manag. Eng.) 39, 550–555 (2017). (in Chinese)Google Scholar
  58. 58.
    Büyüközkan, G., Güleryüz, S., Karpak, B.: A new combined IF-DEMATEL and IF-ANP approach for CRM partner evaluation. Int. J. Prod. Econ. 191, 194–206 (2017)CrossRefGoogle Scholar
  59. 59.
    Ranjan, R., Chatterjee, P., Chakraborty, S.: Evaluating performance of engineering departments in an Indian University using DEMATEL and compromise ranking methods. Opsearch 52(2), 307–328 (2015)CrossRefGoogle Scholar
  60. 60.
    Nilashi, M., Zakaria, R., Ibrahim, O., et al.: MCPCM: a DEMATEL-ANP-based multi-criteria decision-making approach to evaluate the critical success factors in construction projects. Arab. J. Sci. Eng. 40, 343–361 (2015)CrossRefGoogle Scholar
  61. 61.
    Liu, C.: Analysis of influencing factors of lean construction capability: based on DEMATEL method. Eng. Econ. 27, 33–37 (2017). (in Chinese)Google Scholar
  62. 62.
    Luo, R., Yang, C.: Analysis of risk factors of PPP project based on DEMATEL method - a case study of Qingdao metro Line 3. Contemp. Econ. 15, 136–137 (2017). (in Chinese)Google Scholar
  63. 63.
    Li, Y., Mathiyazhagan, K.: Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector. J. Clean. Prod. 172, 2931–2941 (2018)CrossRefGoogle Scholar
  64. 64.
    Liu, G., Huang, D., Liu, C.: Preference of car form feature based on DEMATEL method. China Packag. Ind. 24, 34–36 (2014). (in Chinese)Google Scholar
  65. 65.
    Yang, F.: Study on influence of passenger car’s form on consumers’ purchase decision. Master’s thesis, Shanghai Jiao Tong University, Shanghai (2016). (in Chinese)Google Scholar
  66. 66.
    Zhou, X., Shi, Y., Deng, X., et al.: D-DEMATEL: a new method to identify critical success factors in emergency management. Saf. Sci. 91, 93–104 (2017)CrossRefGoogle Scholar
  67. 67.
    Muhammad, M.N., Cavus, N.: Fuzzy DEMATEL method for identifying LMS evaluation criteria. Procedia Comput. Sci. 120, 742–749 (2017)CrossRefGoogle Scholar
  68. 68.
    Li, H., Ren, Y., Tao, M.: Research on the key influencing factors analysis of the graduate education quality in China based on DEMATEL method. Sci. Technol. Innov. Herald 14, 209–212 (2017). (in Chinese)Google Scholar
  69. 69.
    Raghuvanshi, J., Agrawal, R., Ghosh, P.K., et al.: Analysis of barriers to women entre-preneurship: the DEMATEL approach. J. Entrep. 26, 220–238 (2017)Google Scholar
  70. 70.
    Sharma, V., Kumar, R., Kumar, R.: QUAT-DEM: quaternion-DEMATEL based neural model for mutual coordination between UAVs. Inf. Sci. 418, 74–90 (2017)CrossRefGoogle Scholar
  71. 71.
    Li, X., Lu, P., Li, C.: Analysis on the influencing factors of disruptive innovations in the state grid and the comprehensive ranking based on Delphi and DEMATEL method. Sci. Technol. Manag. Res. 37(6), 127–133 (2017). (in Chinese)Google Scholar
  72. 72.
    Li, R., Wang, X.: Application of GRA-DEMATEL in influence factors of e-tailers credit evaluation. J. Commer. Econ. 22, 89–91 (2017). (in Chinese)Google Scholar
  73. 73.
    Büyüközkan, G., Güleryüz, S.: An integrated DEMATEL-ANP approach for renewable energy resources selection in Turkey. Int. J. Prod. Econ. 182, 435–448 (2016)CrossRefGoogle Scholar
  74. 74.
    George-Ufot, G., Qu, Y., Orji, I.J.: Sustainable lifestyle factors influencing industries’ electric consumption patterns using fuzzy logic and DEMATEL: the Nigerian perspective. J. Clean. Prod. 162, 624–634 (2017)CrossRefGoogle Scholar
  75. 75.
    Liang, H., Ren, J., Gao, Z., et al.: Identification of critical success factors for sustainable development of biofuel industry in China based on grey decision-making trial and evaluation laboratory (DEMATEL). J. Clean. Prod. 131, 500–508 (2016)CrossRefGoogle Scholar
  76. 76.
    Chen, Y., Liu, J., Li, Y., et al.: RM-DEMATEL: a new methodology to identify the key factors in PM2.5. Environ. Sci. Pollut. Res. Int. 22, 6372–6380 (2015)CrossRefGoogle Scholar
  77. 77.
    Tyagi, M., Kumar, P., Kumar, D.: Assessment of critical enablers for flexible supply chain performance measurement system using fuzzy DEMATEL approach. Global J. Flex. Syst. Manag. 16, 115–132 (2015)CrossRefGoogle Scholar
  78. 78.
    Niu, L., Jiang, Y.: Study on farmers’ willingness and its influencing factors towards small-scale irrigation based on DEMATEL methods. China Rural Water Hydropower 10, 194–200 (2017). (in Chinese)Google Scholar

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© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Shanghai Jiao Tong UniversityShanghaiChina

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