Integration of Personnel Services with Public Transportation Modes: A Case Study of Bogazici University

Authors

  • Ilgin Gokasar Department of Civil Engineering, Bogazici University, İstanbul, Turkiye Author
  • Ozan Karaman Department of Civil Engineering, Bogazici University, İstanbul, Turkiye Author

DOI:

https://doi.org/10.31181/jscda1120231

Keywords:

Personnel services, Vacancy optimization, Public transport, Integration

Abstract

Personnel service is a common application that is offered by employers to provide comfortable transportation for the employees. It is mostly applied in developing countries and even though it brings some convenience for both sides, it also has downsides. Especially, the extra cost of the system for institutions and additional congestion created during peak hours due to the wrong optimization of the service routes are huge problems that can be fixed by proper applications. Moreover, such an optimization would create huge benefits in general because of the extensiveness of the application. Besides some of the employees have complaints about the arrangement of the services which results in private car usage in the long term. The purpose of this study is to optimize the personnel service system in a systematic way and additionally, to combine the system with public transportation to be able to obtain a new approach. Therefore, the first method optimizes the routes whereas the second method gives a new suggestion for the system. The data of the study is obtained from the current personnel services of Boğaziçi University. During the process, the Geographic Information System (GIS) is utilized to investigate all possibilities. The study showed that both of the offered methods results better than the conventional approach by improving personnel welfare, congestion during peak hours and transportation habits.

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Published

2023-08-23

How to Cite

Gokasar, I. ., & Karaman, O. (2023). Integration of Personnel Services with Public Transportation Modes: A Case Study of Bogazici University. Journal of Soft Computing and Decision Analytics, 1(1), 1-17. https://doi.org/10.31181/jscda1120231