Evaluation of passenger service within the area of Beijing west railway station

Abstract

Purpose This study aims to analyze passenger service quality in Beijing West Railway Station from the perspective of passengers, to better understand the current service quality and obtain the areas of weakness for improvement. Design/methodology/approach The research investigates the passenger experience of service in Beijing West Railway Station by using a questionnaire survey. The service quality (SERVQUAL) evaluation method is used to analyze the survey data, and it divides the passenger service into 5 attributes with 20 indicators. This research uses the Likert five-level scale method to process data and calculates the SERVQUAL value and weight difference of each attribute to evaluate the passenger service. Therefore, the deficiencies have been pointed out, so the station manager can improve the passenger service accordingly. Findings It is indicated that among the five studied attributes, Beijing West Railway Station has the smallest service quality value in terms of timeliness, which means this part needs the largest improvement. To the five attributes, each lacks in station security check, ticketing efficiency, station identification accuracy, emergency processing of train delays and the restroom environment, respectively. Originality/value The research can provide specific suggestions for the optimization of the passenger service of Beijing West Railway Station, and provide reference information for the formulation of policies.

Examining the Impact of Service Quality on Passengers’ Intentions to Utilize Rail Transport in the Post-Pandemic Era: An Integrated Approach of SERVQUAL and Health Belief Model

“…As such, empathy emerges as an indispensable cornerstone of railway service, aligning with the insights of Gopal Vasanthi et al [21], which accentuate the need for a robust emphasis on empathy for the enhancement of service quality from the passengers' vantage. Furthermore, the pivotal role of "responsiveness" in gauging service quality finds validation, a stance corroborated by the findings of Shi et al [34]. Moving forward, the facet of "reliability" comes to the fore, embodying customer trust and conviction nurtured through organizational and service reliability-facets such as punctuality, impartiality, and efficient grievance redressal.…”

“…These dimensions were found to capture the key aspects of service quality and were more manageable and practical for measuring and evaluating service quality effectively. The revised model has since been widely adopted and utilized in various service industries to assess and improve service quality [20,34]. This study recognizes the importance of SERVQUAL as having the potential to improve service quality in all dimensions and aims to apply this conceptual framework, in conjunction with the health belief model (HBM), to investigate the factors that influence rail transport service.…”

Quantifying the energy trilemma in China and assessing its nexus with smart transportation

“…Furthermore, improved innovation can accelerate the aging of sunset industries and promote the rise of emerging industries such as intelligent transportation, which then drive the transformation and upgrading of traditional labor-intensive industries. Based on the development of ST, capital-intensive and technological-intensive industries will become the mainstream (Liu et al, 2021;Shi et al, 2021aShi et al, , 2021bZailani et al, 2014).…”

“…As an intensive transportation mode, ST is essential for breaking the extensive energy-based vicious circle of development by replacing more efficient energy utilization with traditional low-efficiency energy utilization. In this regard, ST contributes greatly to the upgrading of the transportation sector towards a more energy-intensive mode (Baygin et al, 2022;Shi et al, 2021aShi et al, , 2021b. In addition, with the popularization and development of smart public transportation, energy saving can be achieved when users change their daily travel behavior.…”

Modeling Extended Service Quality for Public Transportation in the Post-Pandemic Period: Differentiating between Urban and Rural Areas: A Case Study of Intercity Railway, Thailand

“…The data presented in this study are available on request from the corresponding author. Eboli and Mazzulla [9] Italy SEM de Oña et al [56] Italy Decision tree Hundal and Kumar [11] India Gap analysis Eboli et al [24] Italy Fuzzy evaluation Shen et al [19] China SEM Putra and Sitanggang [57] Indonesia Gap analysis Machado-León et al [22] Algeria IPA Miranda et al [58] Portugal Regression Jomnonkwao et al [5] Thailand EFA Yuda Bakti et al [59] Indonesia Hedonic model Wang et al [60] China SEM Wonglakorn et al [21] Thailand SEM Ibrahim et al [10] Malaysia Neural network Shi et al [61] China Evaluation method Yang et al [23] China Regression Hidayat and Choocharukul [62] Thailand and Indonesia SEM Gopal Vasanthi et al [12] India Hierarchical regression This study Thailand Multigroup CFA Note: IPA = important performance-analysis; SEM = structural equation modeling; EFA = exploratory factor analysis; CFA = confirmatory factor analysis.…”