Determining the service quality of the city bus service based on users’ perceptions and expectations

Deb, Saikat; Ahmed, Mokaddes Ali

doi:10.1016/j.tbs.2018.02.008

Cited by 83 publications

(38 citation statements)

References 36 publications

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“…Therefore, the goodness-of-fit statistics had values of chi-square/df = 4.79, which was lower than 5 (Hu and Bentler [26]). Furthermore, RMSEA = 0.050 (0.047-0.053) < 0.08 [27,28], SRMR = 0.041 < 0.08 [26], CFI = 0.973 ≥ 0.90 [26], and TLI = 0.952 ≥ 0.80 [29,30], which met the criteria, as shown in Figure 5. When creating measurement modes as second-order CFA to measure motorcycle riding behavior, the second-order CFA was created with the highest loading factors of 0.824 for safety equipment, 0.798 for stunts, 0.584 for control errors, and 0.538 for traffic errors.…”

Section: Model Parameter Estimationmentioning

confidence: 92%

“…The hypothesis was tested using the following criteria of goodness-of-fit statistics: value of chi-square/df of <5 (Hu and Bentler [26]), root mean square error (RMSEA) of <0.08 [27,28], standardized root mean square residual (SRMR) of <0.08 [26], comparative fit index (CFI) of ≥0.90 [26], and Tucker-Lewis index (TLI) of ≥0.80 [29,30].…”

Section: Hypothesis Testingmentioning

confidence: 99%

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Development of Self-Assessment Indicators for Motorcycle Riders in Thailand: Application of the Motorcycle Rider Behavior Questionnaire (MRBQ)

et al. 2020

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The purposes of this research are (1) to create a motorcycle riding behavior measurement model for a Thai population by Motorcycle Rider Behavior Questionnaire (MRBQ) modification with exploratory factor analysis (EFA); (2) to verify the measurement model by second-order confirmatory factor analysis (second-order CFA); and (3) to define the guidelines of the self-assessment report for Thai people in terms of riding motorcycles. Collected data were distributed among four areas: metro-municipalities, municipalities, district municipalities, and non-municipalities from five regions. The sample consisted of 1516 motorcycle riders who were at least 20 years old. Of these riders, 91.4% had motorcycle riding licenses, 84.4% had over five years of experience in motorcycle riding, 75.5% used a motorcycle to go to work/study, and 82.1% used a helmet sometimes. Exploratory factor analysis (EFA) and second-order confirmatory factor analysis (second-order CFA) were used for measurement model creation. The results presented 26 indicators that were confirmed to compose the motorcycle riding behavior of Thai people at a statistical significance level of α = 0.05; these were separated into four factors, namely, traffic error, control error, stunts, and safety equipment. The results of this MRBQ study can inform future study of the motorcycle riding behavior of Thai people.

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Section: Model Parameter Estimationmentioning

confidence: 92%

Section: Hypothesis Testingmentioning

confidence: 99%

Development of Self-Assessment Indicators for Motorcycle Riders in Thailand: Application of the Motorcycle Rider Behavior Questionnaire (MRBQ)

et al. 2020

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“…Similarly, quality is seen in terms of technology, in which it is identified with the relevant norms, standards and assumptions set in projects (Saha and Theingi, 2009). In other terms, for example in the sociological aspect, quality is the response of customers to specific features of products and services (Deb and Ahmend, 2018), while in humanistic terms, quality is the creation of an appropriate standard of living referring to the culture and work (Zeithaml et al, 1996;Wang et al, 2017). There is also an approach to quality that, in the most general sense, reflects the level of consumer's satisfaction (Prentice and Kadan, 2019;Kaczmarczyk, 2016).…”

Section: Concept Of Quality and Its Characteristic Featuresmentioning

confidence: 99%

Main Determinants of Shaping the Quality of Air Transport Services

Hawlena¹,

Mazurek-Kusiak²,

Kobyłka³

2019

ERSJ

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Purpose:The purpose of the article is to demonstrate the impact of the most important determinants on the selection of the best quality variant of the air service level, depending on the proposed price, standard, comfort, service quality, loyalty, scope of additional services and other criteria. Design/Methodology/Approach: Research on the determinants governing the choice of the air travel segment is based on available literature, statistical documentation, IATA and ULC, Airbus and Boeing, and mainly based on own empirical research. The tests carried out using the diagnostic survey method included two comparable periods in 2011 and 2018. They were carried out on a group of 321 passengers, who started their journey at Katowice-Pyrzowice, Kraków-Balice, Rzeszów-Jasionka and Lublin-Świdnik airports. Findings: The undertaken research based on own empirical study demonstrates the decisive importance of quality in creating the unique services and added value. The effectiveness of reasons determining the passengers' movements between traditional and low-cost carriers, was also demonstrated as a result of the improvement of consumer service in internal, intersegmental and inter-branch conditions of competition. Practical Implications: The key determinant of obtaining a competitive market advantage by service providers is the improvement of passenger service quality at the departure port, on the aircraft and at the destination port. The skill and effectiveness of this dominant use is demonstrated by the level of elimination of unfavorable features of the service already in the design phase, the dimension of the outflow of loyal passengers to competitors, the number of new increments and the expansion of loyal customers, which is expressed in a synthetic way by the increase in purchases. Originality/Value: Comparison of services of traditional air carriers with the low-cost carriers on the polish market. Data can be compared with other countries.

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“…The evaluation and assessment of the quality of transport offered is a challenging topic that has actracted many studies in the last years [1][2][3]. In addition, it is a crucial step in decisional processes, since policy makers and transport authorities are expected to assess the quality of all services.…”

Section: Introductionmentioning

confidence: 99%

Comparing Transport Quality Perception among Different Travellers in European Cities through Co-Cluster Analysis

Pirra

Pensa

2019

Sustainability

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The quality of the transport system offered at city level constitutes an important and challenging goal for society, for local authorities, and transport operators. Therefore, appropriate evaluation of travellers' satisfaction is required to support service performance monitoring, benchmarking, and market analysis. This aspect implies the collection of satisfaction levels for different passengers' groups, as it could provide interesting suggestions for identifying priority areas of action. To this end, an original study aimed at understanding the main aspects affecting the common view of satisfaction among different kinds of travellers at European level is presented in this paper. A specific survey investigating how travellers perceive the quality of their journey is proposed to people living in cities characterised by different sizes. Data are then analysed through a multi-view co-clustering algorithm, an innovative machine learning technique that highlights clusters of respondents grouped according to various categories of features. Such results could be used by local authorities and transport providers to understand the specific actions to be operated to improve the quality of transport service offered in a market segmentation dimension.

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Determining the service quality of the city bus service based on users’ perceptions and expectations

Cited by 83 publications

References 36 publications

Development of Self-Assessment Indicators for Motorcycle Riders in Thailand: Application of the Motorcycle Rider Behavior Questionnaire (MRBQ)

Development of Self-Assessment Indicators for Motorcycle Riders in Thailand: Application of the Motorcycle Rider Behavior Questionnaire (MRBQ)

Main Determinants of Shaping the Quality of Air Transport Services

Comparing Transport Quality Perception among Different Travellers in European Cities through Co-Cluster Analysis

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