Interval Valued Intuitionistic Fuzzy AHP-WASPAS Based Public Transportation Service Quality Evaluation by a New Extension of SERVQUAL Model: P-SERVQUAL 4.0

Service quality is one of the most important factors that increase the use of public transportation, especially in metropolitan cities such as Istanbul. When evaluating service quality in public transportation systems, one of the most important factors is customer satisfaction. The increase in service quality increases the usage of public transport system utilization and it helps to solve many problems such as traffic congestion, air and noise pollution and energy consumption. For this purpose, the SERVQUAL model is extended with two new criteria related to Industry 4.0 and the pandemic to understand and evaluate the service quality of public transport systems. New criteria added into the SERVQUAL model and a novel P-SERVQUAL 4.0 (Pandemic SERVQUAL 4.0) model is presented. The novel service quality evaluation model is constructed as a three level hierarchical structure to evaluate public transport systems during the pandemic. Then, the evaluation model is modeled as a multi criteria decision making problem and a novel AHP (Analytic Hierarchy Process) integrated WASPAS (Weighted Aggregated Sum Product Assessment) under interval valued intuitionistic fuzzy (IVIF) environment methodology is employed. A real case application to evaluate Istanbul public transport systems is presented in this study. The proposed novel model is applied to evaluate the most used public transportation alternatives such as IETT Bus, Metrobus, Tram, Metro and Marmaray, in Istanbul. By the application of P-SERVQUAL 4.0 model;as a result of this study, Marmaray is determined as the best alternative. The proposed methodology can be used by public or private organizations to improve their strategies and operations to adapt Industry 4.0 and prevent the spread of SARS-CoV-2 (COVID-19). Also, the main limitations and the practical and managerial implications of the study are included in the conclusions.

A novel distance learning ergonomics checklist and risk evaluation methodology: A case of Covid-19 pandemic.

Many governments decided to cancel face-to-face teaching and learning activities in schools and universities. They replaced them with online teaching and distance learning activities to prevent the spread of Coronavirus disease 2019 (COVID-19). Due to this sudden change, students experienced some anthropometric, environmental, and psychosocial difficulties at home during the distance learning process. This study focuses on determining the importance of anthropometric, environmental, and psychosocial factors in the distance learning process during the COVID-19 pandemic. This study presents main factors and their subfactors affecting ergonomic conditions of university students during distance learning. A novel distance learning ergonomics checklist is proposed based on the Occupational Safety and Health Administration checklists. The data are collected via a questionnaire filled by 100 university students who attend the Ergonomics course online. Then, the integrated methodology includes Voting Analytic Hierarchy Process integrated Pythagorean Fuzzy Technique for Order Preference by Similarity to An Ideal Solution method is adopted to prioritize the factors determined. Thirty-nine different subfactors are evaluated under five titles, and the most important factors are determined using the proposed methodology. With the results achieved, it is seen that the suggested checklist and proposed methodology can be used by public and private education organizations as a guide for improving their distance learning strategies.