Developing a Model of Toll Road Service Quality using an Artificial Neural Network Approach
Published at : 29 Apr 2016
Volume : IJtech
Vol 7, No 4 (2016)
DOI : http://dx.doi.org/10.14716/ijtech.v7i4.2612
Zuna, H.T., & Hadiwardoyo, S.P., & Rahadian, H., 2016. Developing a Model of Toll Road Service Quality using an Artificial Neural Network Approach. International Journal of Technology, Volume 7(4), pp. 562-570
| Herry T. Zuna | Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia |
| Sigit Pranowo Hadiwardoyo | Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia |
| Hedy Rahadian | Department of Civil Engineering, Faculty of Engineering, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia |
Road infrastructure
includes toll roads developed to support mobility and economic activity. The
toll road is part of the road network and is an alternative that can save
travelers time and give them better service. The level of service of the toll
road is strongly connected to the level of satisfaction of toll road users;
therefore, customer satisfaction needs to be included in development models.
The purpose of this study was to develop a model approach to customer
satisfaction using an artificial neural network (ANN). Two models of customer
satisfaction, SERVQUAL and Minimum Service Standards (SPM), have been used to
modify the Toll Road Service Quality (TRSQ) model. This study has been able to
explain that TRSQ has a value of R2, meaning the result is better
than that of the other two models. The TRSQ model itself consists of seven
dimensions: information, accessibility, reliability, mobility, security, rest
areas, and responsiveness. Reliability is the dimension with the greatest
effect on customer satisfaction.
Artificial neural network; Customer satisfaction; Quality of service; Toll road