According to Hair et al. [61], the definition of convergent validity is the degree to which a measure is positively correlated with the alternative measures of the same construct. The validity was assessed on the basis of two criteria: (i) the standardised factor loading (or item loading) should be greater than 0.50 and significant [61], and (ii) the average variance extracted (AVE) for all constructs must be at least 0.50 [62]. As can be seen in Table 4, the standardised factor loading for all items are greater than the threshold value of 0.50 , where the minimum item loading is 0.654 and is thus significant. In addition, the values of all AVE range between 0.517 and 0.857 , which are greater than the 0.50 threshold value recommended by Fornell and Larcker [62]. Therefore, the convergent validity has been proven to be good as all constructs fulfilled the above-mentioned criteria.

\subsection*{4.2.3. Discriminant Validity}

The definition of discriminant validity given by Hair et al. [61] is the degree to which a construct is truly distinct from others based on empirical standards. This validity is measured by comparing the AVE value of each construct with the squared correlation between these constructs as well as with all other constructs [35]. The results presented in Table 4 shows that the AVE values for all constructs are higher than the squared correlation and meet the requirement proposed by Fornell and Larcker [62]. Thus, the discriminant validity in this study is acceptable.

\subsection*{4.3. Evaluation of the Structural Model}

After confirming the validity and reliability of the measurement model, the recommended hypotheses were evaluated using covariance-based structural equation model (CB-SEM). Results showed that the model for exploring the determinants of passengers' satisfaction with the Kuala Lumpur LRT service is well-fitted as all values of the goodnessof-fit indices $\left(\chi^{2} / \mathrm{df}=2.63, \mathrm{CFI}=0.95, \mathrm{NFI}=0.93, \mathrm{GFI}=0.95, \mathrm{AGFI}=0.93, \mathrm{RMSEA}=0.07\right)$ satisfy the requirement for fit criteria. The overall model structure with the standardised estimates and the significance of the relationship between the constructs is illustrated in Figure 3. The structural equation model (see Figure 3) explained $28 \%$ of the variance in perceived quality, $61 \%$ of the variance in perceived value, and $76 \%$ of the variance in passenger satisfaction.

![](https://cdn.mathpix.com/cropped/2024_03_22_30fd31a2d83817f3f9dcg-09.jpg?height=691&width=1248&top_left_y=857&top_left_x=587)

Figure 3. Structural equation model.

Hypotheses 1 to 3 suggest that passenger expectation has a positive impact on perceived quality, perceived value and passenger satisfaction. The standardised regression coefficient presented in Figure 3 shows that passenger expectation has a significant positive and direct effect on perceived quality $(\beta=0.526, p<0.001)$ and perceived value $(\beta=0.115$, $p<0.05)$ and not significant effect on passenger satisfaction $(\beta=0.075, p>0.05)$. Thus, hypotheses 1 and 2 are supported, while hypothesis 3 is not supported. The positive relationship between perceived quality and perceived value and between perceived quality and passenger satisfaction is stated in hypotheses 4 and 5 . The results indicate that perceived quality has a significant positive influence on perceived value $(\beta=0.532, p<0.001)$ and passenger satisfaction $(\beta=0.361, p<0.001)$. These results confirm hypotheses 4 and 5. Hypothesis 6 states that perceived value has a positive impact on passenger satisfaction, and the result showed a significant positive relationship between the two constructs $(\beta=0.238, p<0.001)$. Therefore, hypothesis 6 is accepted. A summary of the hypothesis testing model is given in Table 5.

Table 5. Summary of hypothesis testing model.

\begin{tabular}{cccccc}

\hline Hypothesis & & Relationship & & Hypothesis \\

\hline H1 & Passenger expectation & with & Perceived quality & $0.526^{* *}$ & Supported \\

H2 & Passenger expectation & with & Perceived value & $0.115^{*}$ & Supported \\

H3 & Passenger expectation & with & Passenger satisfaction & $0.075^{\text {n.s. }}$ & Not supported \\

H4 & Perceived quality & with & Perceived value & $0.532^{* *}$ & Supported \\

H5 & Perceived quality & with & Passenger satisfaction & $0.361^{* *}$ & Supported \\

H6 & Perceived value & with & Passenger satisfaction & $0.238^{* *}$ & Supported \\

\hline

\end{tabular}

Note: H, Hypothesis; $\beta$, Standardised regression coefficient; ${ }^{*} p<0.05,{ }^{* *} p<0.001 ;$ n.s., not significant.

\section*{5. Discussion of the Results}

\subsection*{5.1. Theoretical Implications}

This study aims to explore the determinants of passenger satisfaction in the context of light rail transit (LRT) service in Kuala Lumpur, Malaysia, which is an alpha city in the South Asian region, by investigating the role of passenger expectation, perceived quality and perceived value based on the passengers' past experience with the Kuala Lumpur's LRT service. The interrelationship of the model was tested using a set of data obtained through a customer satisfaction survey of the urban rail transit in Kuala Lumpur, Malaysia using a structural equation model approach. The conceptual framework in this study was assessed and validated, and this theoretically contributed to the understanding of the factors influencing passengers' satisfaction with the urban rail transit. It is crucial to explore the factors influencing passengers' satisfaction with the urban rail transit, especially in the context of Malaysia, given that rail transit is one of the government's strategies to reduce the dependency on private motorised transport and to increase the public transport modal share up to $40 \%$ in 2030 [63]. Specifically, the rail transit in the urban area of the future will be the backbone of the public transport network in the city.

According to this study, three factors-namely passenger expectation, perceived quality and perceived value - can have a direct or indirect impact on passenger satisfaction. The outcomes of this study are congruent with the earlier research in transportation. The present study found that passenger expectation has a direct and significant effect on perceived quality, perceived value and passengers' satisfaction level towards the LRT service. Put differently, passenger expectation not only has a direct influence on their level of satisfaction, but it also has an indirect influence on passenger satisfaction via perceived quality and perceived value. This finding is congruent with those made by Shen et al. [22] and Zhang et al. [33]. The findings also confirmed the positive influence of perceived quality on perceived value and passenger satisfaction reported in various previous research $[23,43-48]$. Similar with the evidences provided by previous studies, the structural equation model used in this study justifies the significant and positive influence of perceived value on satisfaction with the LRT service [53-58]. Hence, passenger expectation, perceived quality and perceived value can be considered as antecedents to passengers' satisfaction with the LRT service in Kuala Lumpur.

Of the three factors influencing the satisfaction level of the passengers of Kuala Lumpur LRT service, perceived quality was found to be the strongest determinant of the feeling of satisfaction among passengers. This finding is consistent with those of recent works in the field of public transport [22,23,38,53]. It is apparent that passengers who use urban rail transit service, in this context the LRT, have a higher level of satisfaction when the service provided is beyond their expectation. In other words, the high-quality service brings about a higher level of satisfaction with the LRT service. According to Ibrahim et al. [13], punctuality, number of trips per day, ticket price or types of passes, cleanliness and comfort in both in the train and at the station, safety on the train and at the station, customer service and more are the main elements of service quality that have been proven to affect perceived service quality as well as passengers' satisfaction with rail-based public transport. This study also found that passengers would be more satisfied with the LRT service if they felt that the trip with the LRT was good value. In this study, value is made up of perceived cost (monetary) and perceived benefits (non-monetary) [52]. The low cost of the trip, short travel time, and comfort during the journey are the indicators that contribute to the perceived value in public transport generally and in urban rail transit specifically. Given that these factors have a direct effect on passenger satisfaction, they have to be given serious consideration in the effort to enhance passengers' satisfaction with the LRT service.