Modelling of Passenger Satisfaction and Reuse Intention with Monorail Services in Kuala Lumpur, Malaysia: A Hybrid SEM-ANN Approach

Ibrahim, Ahmad Nazrul Hakimi; Borhan, Muhamad Nazri; Mat Yazid, Muhamad Razuhanafi; Hassan, Sitti Asmah; Arham, Ahmad Firdhaus; Hashim, Sharizal

doi:10.3390/math11153361

Cited by 3 publications

(2 citation statements)

References 111 publications

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“…These findings indicated that the proposed model explains 70.4% and 59.5% of passenger satisfaction and reuse intention, respectively. Both perceived quality and perceived value were found to significantly influence satisfaction, with the ANN identifying perceived quality as the most crucial predictor of satisfaction [51].…”

Section: Sem-annmentioning

confidence: 99%

Navigating Passenger Satisfaction: A Structural Equation Modeling–Artificial Neural Network Approach to Intercity Bus Services

Rahnama,

Cortez,

Monzon

2024

Sustainability

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The phenomenon of passenger satisfaction is an important issue for public transport services and transport companies. Clarifying the relationship between influencing attributes and passenger satisfaction significantly improves service satisfaction. This study examines passenger satisfaction with intercity buses and, in particular, the role of digital information channels (websites and mobile apps) in promoting sustainable travel choices on the Madrid–Bilbao route. This study analyzed data from 459 passengers to identify the key factors influencing the bus choice for intercity bus travel. Punctuality, safety, and ticket price are the most important determinants. We use a combined structural equation modeling (SEM) and artificial neural network (ANN) approach to capture the intricate relationships between service attributes and information channels. The results show that information channels, travel experience, and ticket prices significantly impact passenger satisfaction, which bus operators should improve. Also, inserting the SEM result as input for the ANN showed that ticket price is the most significant predictor of satisfaction, followed by information channels (84%) and travel experience (65%). This approach provides valuable insights for improving the passenger experience. This study emphasizes integrating digital transformation strategies into public transport systems to promote sustainable mobility goals.

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Section: Sem-annmentioning

confidence: 99%

Navigating Passenger Satisfaction: A Structural Equation Modeling–Artificial Neural Network Approach to Intercity Bus Services

Rahnama,

Cortez,

Monzon

2024

Sustainability

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“…It encompasses six variables: customer expectations, perceived quality, perceived value, customer satisfaction, customer complaints, and customer loyalty [13]. Building on the ACSI framework, Ibrahim et al utilized structural equation modeling (SEM) to explore factors influencing passengers' satisfaction with monorail services and their willingness to continue using the service [26]. Chen et al, based on ACSI, constructed a research model involving heritage perception value, perceived enjoyment, visit satisfaction, and post-visit behavioral intentions, validating it through SEM [27].…”

Section: Shared Micro-mobility Satisfactionmentioning

confidence: 99%

A Quantitative Study on Factors Influencing User Satisfaction of Micro-Mobility in China in the Post-Sharing Era

Cheng,

Yang,

et al. 2024

Sustainability

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In the post-sharing era, the evolution of the shared micro-mobility industry has transitioned from expanding market share to providing precise services. The focus on user satisfaction has shifted from a singular emphasis on functional utility to diversified product values. Product perceived value has emerged as a comprehensive factor for enhancing user satisfaction, aiding companies in formulating precise services, mitigating urban resource wastage, and promoting sustainable urban development. From the perspective of product perceived value, this study combined the analysis of factors affecting user satisfaction of shared micro-mobility and the interaction between these aspects and carried out the following two studies. Research No. 1: By mining the user review data on app platforms related to shared micro-mobility and adopting the latent dirichlet allocation (LDA) algorithm, we have initially identified 17 major factors affecting the satisfaction of users and summarized these factors into four research topics constituting product perceived value. Research No. 2: On the basis of Research No. 1, the content of the American Customer Satisfaction Index (ACSI) was expanded, and a user satisfaction research model focusing on the perceived value of shared micro-mobility products was constructed. Afterwards, by using the data collected in questionnaire surveys, structural equation modeling (SEM) was used to model the user satisfaction of shared micro-mobility through SEM, which was deployed to establish an empirical analysis. It is found that (1) both user expectation and product quality can positively affect the perceived value of products through interactive experience; (2) factors such as user expectation, product quality, interactive experience, and subjective consciousness can positively affect user satisfaction through the perceived value of products, with user expectation delivering the greatest influence; and (3) subjective consciousness has a direct positive effect on users’ willingness to continuously use a product but no significant effect on user satisfaction. These findings expand the user satisfaction theoretical model in the field of shared micro-mobility, constitute suggestions for product development and service promotion in the shared micro-mobility industry, and can provide new ideas and methods for the sustainable development of urban transportation.

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Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling

Chen,

Yin,

Tian

et al. 2024

PLoS ONE

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This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspective. This study utilizes a sample of 336 national research project team members from various Chinese universities, research institutes, and corporations to analyze the theoretical model. Additionally, a two-stage hybrid partial least squares structural equation modeling (PLS-SEM) approach, combined with artificial neural network techniques (ANN), is employed to evaluate the hypotheses. The empirical findings of this study reveal a positive association between the intensity of IPP and RTI within national research project teams. Research and development investment intensity (R&DII) is identified as the primary predictor, while integrated leadership (IL) and group potential (GP) play crucial moderating roles. These groundbreaking findings extend the scope of innovation-driven and AMO theories, providing a proactive model for national research project teams to propose improvements to the IPP system, ultimately enhancing the realization of RTI.

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Modelling of Passenger Satisfaction and Reuse Intention with Monorail Services in Kuala Lumpur, Malaysia: A Hybrid SEM-ANN Approach

Cited by 3 publications

References 111 publications

Navigating Passenger Satisfaction: A Structural Equation Modeling–Artificial Neural Network Approach to Intercity Bus Services

Navigating Passenger Satisfaction: A Structural Equation Modeling–Artificial Neural Network Approach to Intercity Bus Services

A Quantitative Study on Factors Influencing User Satisfaction of Micro-Mobility in China in the Post-Sharing Era

Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling

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