Evaluation of Quality in Public Transport Services: The Use of Quality Dimensions as an Input for Fuzzy TOPSIS

Aquino, Joás Tomaz de; Melo, Fagner José Coutinho de; Jerônimo, Taciana de Barros; Medeiros, Denise Dumke de

doi:10.1007/s40815-018-0524-1

Cited by 34 publications

(22 citation statements)

References 40 publications

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“…Nassereddine and Eskandari [42] reported an integrated MCDM method based on Delphi method, analytic hierarchy process (AHP), and preference ranking organization method for enrichment of evaluations (PROMETHEE) for evaluating the passenger satisfaction levels of the public transportation systems in Tehran. de Aquino et al [5] applied fuzzy technique for order performance by similarity to ideal solution (TOPSIS) method to evaluate the service quality of the Brazilian bus rapid transit (BRT) system. Moreover, Aydin [6] combined statistical analysis, fuzzy trapezoidal numbers, and the TOPSIS method to evaluate the service quality levels of rail transit lines for multiple periods.…”

Section: Literature Reviewmentioning

confidence: 99%

“…It provides an efficient and environmentally friendly service to urban passengers and plays an important role in easing traffic pressure and reducing carbon emission from automobiles [3,4]. The service quality of the public transportation system is highly valued by the authorities and managers [5,6]. Since passenger satisfaction is an important factor that affects the usage of public transportation, it is critical and important to understand the passenger satisfaction of public transportation to meet passenger requirements and preferences [7].…”

Section: Introductionmentioning

confidence: 99%

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Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment

Huang

et al. 2020

Sustainability

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Passenger satisfaction is an important factor that affects the choice of travel modes for municipalities, especially in big cities. This evaluation is an important task for managers when they are considering improving the competitiveness of the public transportation system. However, passenger satisfaction evaluation is difficult as the information provided by passengers is often vague, imprecise, and uncertain. This paper aims to propose a new method, using Pythagorean fuzzy sets and multi-objective optimization by a ratio analysis plus full multiplicative form method (MULTIMOORA), to evaluate the passenger satisfaction level of the public transportation system under large group environment. The former is employed to represent the satisfaction assessments of rail transit network provided by passengers. The latter is extended and used to determine the passenger satisfaction levels of rail transit lines. In addition, a combination weighting method is suggested to compute the relative weights of evaluation criteria. A case study of the rail transit network in Shanghai is provided to demonstrate the effectiveness of the proposed passenger satisfaction evaluation method. The result shows that the new method proposed in this study can not only model passengers’ satisfaction evaluation information with more uncertainties, but also determine more reasonable and credible satisfaction levels of rail transit lines.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment

Huang

et al. 2020

Sustainability

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“…Sendo uma ferramenta estratégica para o diagnóstico do grau de satisfação da organização, a elaboração da pesquisa de clima organizacional deve estar alinhada com o planejamento estratégico da organização devendo ser aplicado no questionário variáveis que sejam fundamentais para o sucesso da análise do clima organizacional, ou seja, ao realizar a pesquisa a organização deve estar atento ao feedback para todos quanto aos resultados e melhorias de curto prazo e longo prazo. A ausência de feedback, bem como a ausência de melhorias, nos aspectos apontados pela pesquisa, pode gerar mais insatisfação e até mesmo a perca da credibilidade quanto à própria pesquisa (AQUINO et al, 2019).…”

Section: Clima Organizacionalunclassified

Avaliação Da Qualidade Do Serviço Prestado Por Uma Unidade De Ensino Da Rede Pública Na Região Metropolitana Do Recife

Matias¹,

Jerônimo²,

Melo³

2020

Blucher Engineering Proceedings

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“…Customer satisfaction measurement is the key to understanding the current service level of cold chain logistics enterprises, which can strengthen the communication between customers and enterprises (Ferrentino and Boniello, 2020). Moreover, the key factors affecting customer satisfaction can be identified through measurement, which is conducive to discovering the cold chain logistics enterprise's advantage and disadvantage, thereby improving the logistics operations (de Aquino et al , 2019). However, most of the research on cold chain logistics at this stage focuses on the operations (distribution management and inventory management), and the research on customer satisfaction measurement is limited.…”

Section: Introductionmentioning

confidence: 99%

Exploring customer satisfaction in cold chain logistics using a text mining approach

Lim¹,

Song

2021

IMDS

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PurposeWith the fierce competition in the cold chain logistics market, achieving and maintaining excellent customer satisfaction is the key to an enterprise's ability to stand out. This research aims to determine the factors that affect customer satisfaction in cold chain logistics, which helps cold chain logistics enterprises identify the main aspects of the problem. Further, the suggestions are provided for cold chain logistics enterprises to improve customer satisfaction.Design/methodology/approachThis research uses the text mining approach, including topic modeling and sentiment analysis, to analyze the information implicit in customer-generated reviews. First, latent Dirichlet allocation (LDA) model is used to identify the topics that customers focus on. Furthermore, to explore the sentiment polarity of different topics, bi-directional long short-term memory (Bi-LSTM), a type of deep learning model, is adopted to quantify the sentiment score. Last, regression analysis is performed to identify the significant factors that affect positive, neutral and negative sentiment.FindingsThe results show that eight topics that customer focus are determined, namely, speed, price, cold chain transportation, package, quality, error handling, service staff and logistics information. Among them, speed, price, transportation and product quality significantly affect customer positive sentiment, and error handling and service staff are significant factors affecting customer neutral and negative sentiment, respectively.Research limitations/implicationsThe data of the customer-generated reviews in this research are in Chinese. In the future, multi-lingual research can be conducted to obtain more comprehensive insights.Originality/valuePrior studies on customer satisfaction in cold chain logistics predominantly used questionnaire method, and the disadvantage of which is that interviewees may fill out the questionnaire arbitrarily, which leads to inaccurate data. For this reason, it is more scientific to discover customer satisfaction from real behavioral data. In response, customer-generated reviews that reflect true emotions are used as the data source for this research.

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Evaluation of Quality in Public Transport Services: The Use of Quality Dimensions as an Input for Fuzzy TOPSIS

Cited by 34 publications

References 40 publications

Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment

Passenger Satisfaction Evaluation of Public Transportation Using Pythagorean Fuzzy MULTIMOORA Method under Large Group Environment

Avaliação Da Qualidade Do Serviço Prestado Por Uma Unidade De Ensino Da Rede Pública Na Região Metropolitana Do Recife

Exploring customer satisfaction in cold chain logistics using a text mining approach

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