An Approach for Discovering Urban Transport Service Problem Based on Hotline

This paper presents a methodology for actively discovering knowledge in transport hotline databases by analyzing complaints reported by citizens, aiming to assist transportation management departments in planning actions to investigate and improve service quality. The proposed model uses text mining...

Full description

Saved in:
Bibliographic Details
Main Authors: Ruo-yu Wu, Chun-fu Shao, Cheng-xiang Zhuge, Xin-yi Wang, Xu-yang Yin
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2023/5667360
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1832558584004608000
author Ruo-yu Wu
Chun-fu Shao
Cheng-xiang Zhuge
Xin-yi Wang
Xu-yang Yin
author_facet Ruo-yu Wu
Chun-fu Shao
Cheng-xiang Zhuge
Xin-yi Wang
Xu-yang Yin
author_sort Ruo-yu Wu
collection DOAJ
description This paper presents a methodology for actively discovering knowledge in transport hotline databases by analyzing complaints reported by citizens, aiming to assist transportation management departments in planning actions to investigate and improve service quality. The proposed model uses text mining techniques and applies latent Dirichlet allocation (LDA) to identify topics that are related to transportation services. Consequently, we actively analyzed over 230,000 phone calls occurring in a certain province between 1st January and 31st December 2021. Specifically, we actively analyzed nearly 22,000 phone calls about the taxi industry within a selected city, and identified six topics, including lost and found (27.1%), car blocking (20.6%), attitude and behavior (17.1%), online car-hailing (12.8%), illegal operations (11.2%), and fare issues (11.2%). By actively referring to past and ongoing best practices, we actively recommend several policy implications. The proposed method thus actively transforms the service center record into a customer feedback-based assessment system to intently monitor drivers’ professionalism while efficiently addressing customers’ complaints and concerns.
format Article
id doaj-art-4bf7ccec5ce14ae9b83148d1ce427129
institution Kabale University
issn 2042-3195
language English
publishDate 2023-01-01
publisher Wiley
record_format Article
series Journal of Advanced Transportation
spelling doaj-art-4bf7ccec5ce14ae9b83148d1ce4271292025-02-03T01:32:00ZengWileyJournal of Advanced Transportation2042-31952023-01-01202310.1155/2023/5667360An Approach for Discovering Urban Transport Service Problem Based on HotlineRuo-yu Wu0Chun-fu Shao1Cheng-xiang Zhuge2Xin-yi Wang3Xu-yang Yin4Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportKey Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive TransportDepartment of Land Surveying and Geo-InformaticsSchool of Economics and ManagementSchool of Economics and ManagementThis paper presents a methodology for actively discovering knowledge in transport hotline databases by analyzing complaints reported by citizens, aiming to assist transportation management departments in planning actions to investigate and improve service quality. The proposed model uses text mining techniques and applies latent Dirichlet allocation (LDA) to identify topics that are related to transportation services. Consequently, we actively analyzed over 230,000 phone calls occurring in a certain province between 1st January and 31st December 2021. Specifically, we actively analyzed nearly 22,000 phone calls about the taxi industry within a selected city, and identified six topics, including lost and found (27.1%), car blocking (20.6%), attitude and behavior (17.1%), online car-hailing (12.8%), illegal operations (11.2%), and fare issues (11.2%). By actively referring to past and ongoing best practices, we actively recommend several policy implications. The proposed method thus actively transforms the service center record into a customer feedback-based assessment system to intently monitor drivers’ professionalism while efficiently addressing customers’ complaints and concerns.http://dx.doi.org/10.1155/2023/5667360
spellingShingle Ruo-yu Wu
Chun-fu Shao
Cheng-xiang Zhuge
Xin-yi Wang
Xu-yang Yin
An Approach for Discovering Urban Transport Service Problem Based on Hotline
Journal of Advanced Transportation
title An Approach for Discovering Urban Transport Service Problem Based on Hotline
title_full An Approach for Discovering Urban Transport Service Problem Based on Hotline
title_fullStr An Approach for Discovering Urban Transport Service Problem Based on Hotline
title_full_unstemmed An Approach for Discovering Urban Transport Service Problem Based on Hotline
title_short An Approach for Discovering Urban Transport Service Problem Based on Hotline
title_sort approach for discovering urban transport service problem based on hotline
url http://dx.doi.org/10.1155/2023/5667360
work_keys_str_mv AT ruoyuwu anapproachfordiscoveringurbantransportserviceproblembasedonhotline
AT chunfushao anapproachfordiscoveringurbantransportserviceproblembasedonhotline
AT chengxiangzhuge anapproachfordiscoveringurbantransportserviceproblembasedonhotline
AT xinyiwang anapproachfordiscoveringurbantransportserviceproblembasedonhotline
AT xuyangyin anapproachfordiscoveringurbantransportserviceproblembasedonhotline
AT ruoyuwu approachfordiscoveringurbantransportserviceproblembasedonhotline
AT chunfushao approachfordiscoveringurbantransportserviceproblembasedonhotline
AT chengxiangzhuge approachfordiscoveringurbantransportserviceproblembasedonhotline
AT xinyiwang approachfordiscoveringurbantransportserviceproblembasedonhotline
AT xuyangyin approachfordiscoveringurbantransportserviceproblembasedonhotline