Applying Six Sigma in urban public transportation to reduce traffic accidents involving municipality buses


Kuvvetli U., FİRUZAN A. R.

TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE, vol.30, pp.82-107, 2019 (SSCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 30
  • Publication Date: 2019
  • Doi Number: 10.1080/14783363.2017.1297198
  • Journal Name: TOTAL QUALITY MANAGEMENT & BUSINESS EXCELLENCE
  • Journal Indexes: Social Sciences Citation Index (SSCI), Scopus
  • Page Numbers: pp.82-107
  • Keywords: Six Sigma, public transportation, traffic accidents, logistic regression, DMAIC, QUALITY MANAGEMENT, SUCCESS FACTORS, SIX-SIGMA, CONCEPTUAL-MODEL, SERVICE QUALITY, IMPLEMENTATION, METHODOLOGY, FRAMEWORK, ORGANIZATIONS, CHALLENGES
  • Dokuz Eylül University Affiliated: Yes

Abstract

Although Six Sigma is a really effective methodology with its strong data-based decision-making aspect, the majority of Six Sigma applications have focused on the private industry and manufacturing sectors. Moreover, the number of case studies implemented in public service is very limited. Despite the fact that the urban public transport sector directly affects the quality of both citizens' economic and social lives, and is one of the most important indicators of modern cities, the literature has not provided any cases of Six Sigma applications in this sector. This paper presents a case study where Six Sigma DMAIC methodology was implemented in the urban public transport sector. The aim of the case study is to reduce traffic accidents as they constitute a critical problem in this sector. The application of DMAIC methodology and Six Sigma tools and principles were used to identify areas of improvements in specifying appropriate bus drivers for lines/routes and bus types, and also in determining the factors that increase risk overall. In this study, various statistical analyses like ANOVA, logistic regression, k-means cluster analysis, and other non-parametric tests were used. An improvement approximately at a rate of 20% was provided as a result of the gains achieved. The results of the study indicate that the application of systematic and data-driven quality improvement approaches such as Six Sigma or Lean with some simple changes and adjustments can contribute to the service quality of public firms.