Ali Rıza Firuzan

Determining Six Sigma success factors in Turkey by using structural equation modeling

Since it includes strong statistical and executive techniques, Six Sigma (SS) succeeded in many countries and different sectors. Especially successful SS applications of many international companies have increased the interest of other companies. As a result of this, the number of implemented SS projects in various countries has increased. Although successful SS projects are often in mind, the number of failed projects because of various reasons is not as low as to be ignored. As well as there are many factors that affect the success level of SS projects, and these factors vary according to countries. In this study, a survey was applied to 117 people who have 1 of SS belts in order to determine success levels of the SS projects in Turkey. By using explanatory factor analysis and structural equation modeling, critical success factors were determined. According to the results, project selection and its scope, quality culture and defining and measuring of metrics were determined as the top factors that are affecting success levels of SS projects applied in Turkey. The results of the study were also compared with the results of similar projects implemented in other countries.

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

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.

THE EFFECTS OF HOSPITAL QUALITY OF CARE ON PATIENT BELONGING: STRUCTURAL EQUALITY MODEL AND MEDIATION

The aim of the study is to measure the effects of perceived and expected service quality levels on patient loyalty. In total, 370 patients participated in this research. The Structural Equation Modeling (SEM) method to test the causal relationship model. The corresponding model in the study emerged as acceptable fit with the model. The result of the study indicate that perceived service quality and patient loyalty are statistically significant and positively related to each other. Additionally, perceived service quality has found to be an important mediator between expected service quality and patient loyalty. After patients have treatment in corresponding hospital, they have been affected by service quality as mush as cost of medication. As patient satisfaction increases, their loyalty increases. It is suggested to hospital management that they might course of action to patients for improving Reliability and Assurance SERVQUAL factorsThe aim of the study is to measure the effects of perceived and expected service quality levels on patient loyalty. In total, 370 patients participated in this research. The Structural Equation Modeling (SEM) method to test the causal relationship model. The corresponding model in the study emerged as acceptable fit with the model. The result of the study indicate that perceived service quality and patient loyalty are statistically significant and positively related to each other. Additionally, perceived service quality has found to be an important mediator between expected service quality and patient loyalty. After patients have treatment in corresponding hospital, they have been affected by service quality as mush as cost of medication. As patient satisfaction increases, their loyalty increases. It is suggested to hospital management that they might course of action to patients for improving Reliability and Assurance SERVQUAL factors