A Decision Tree Approach for Achieving High Customer Satisfaction at Urban Interchanges

Author:

Tsami Maria1,Adamos Giannis2,Nathanail Eftihia3,Budiloviča Evelina Budilovich4,Jackiva Irina Yatskiv4,Magginas Vissarion1

Affiliation:

1. University of Thessaly , Department of Civil Engineering , Pedion Areos, GR-38334 Volos , Greece , Ph.: +302421074133, Fax: +302421074131

2. University of Thessaly , Department of Civil Engineering , Pedion Areos, GR-38334 Volos , Greece , Ph.: +302421074158, Fax: +302421074131

3. University of Thessaly , Department of Civil Engineering , Pedion Areos, GR-38334 Volos , Greece , Ph.: +302421074164, Fax: +302421074131

4. Transport and Telecommunication Institute , Lomonosova Street 1, LV-1019 Riga , Latvia , Ph.: +37167100544, Fax: +37167100660

Abstract

Abstract This paper introduces a decision tree approach, which can be used for the assessment of the design, operation and services provided at urban transport interchanges. Realizing a customer satisfaction survey, feedback was received from 239 users of the Riga International Coach Terminal on crucial attributes, including: travel information, wayfinding information, time and movement, access, comfort and convenience, station attractiveness, safety and security, emergency situation handling and overall satisfaction. Findings revealed the most significant parameters that need to be addressed in order to increase users’ satisfaction, which can gradually improve the overall attractiveness of the terminal and the efficient provision of its services.

Publisher

Walter de Gruyter GmbH

Subject

Computer Science Applications,General Engineering

Reference25 articles.

1. 1. ADB (2015) Improving interchanges: Introducing best practices on multimodal interchange hub development in the People’s Republic of China. ASIAN DEVELOPMENT BANK.

2. 2. Acharia, T., Yang, I., Lee, D. (2015) Application of J48 Decision Tree for the Identification of Water Bodies Using Landsat 8 OLI Imagery. In: 2nd International Electronic Conference on Sensors and Applications. Online.

3. 3. Ahishakiye, E., Omulo, E., Taremwa, D., Niyonzima, I. (2017) Crime Prediction Using Decision Tree (J48) Classification Algorithm, International Journal of Computer and Information Technology, 6(3): 188-195.

4. 4. Allmuali, H., Kaneda, S., Akiba, Y. (2002) Development and Applications of Decision Trees. In: Expert Systems, Vol.1, Academic Press.

5. 5. Breiman, L., Friedman, J H., Olshen, R.A., and Stone, C.J. (1984) Classification and regression trees. Monterey, CA: Wadsworth.

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