4.2.1. Measurement Indicators of the HBM and the SERVQUAL Model
In this section, we employed CFA to establish the representativeness of observed indicators derived from rail transport passengers in relation to the latent factors, i.e., SERVQUAL and the HBM. The CFA results were obtained using Muthén and Muthén’s Mplus 7.2 software. Our analysis revealed that all indicators significantly contributed to the SERVQUAL and the HBM factors, with each parameter showing significance at the 0.01 level. While the appropriate AVE and CR values for all factors in this study met the criteria of 0.5 and 0.7, respectively, it is essential to consider the findings from previous literature [
50,
60]. Their research confirmed that when CR exceeds 0.7, an AVE value higher than 0.4 is still considered acceptable. Therefore, our results align with the acceptable threshold as per the established literature. The model fit statistics (see table footnote) indicate a good fit between the model and empirical data, meeting the acceptance criteria. For further details on the model estimation results, please refer to
Table 4.
Regarding the table, all indicators obtained from research questionnaires can be used as components of the HBM and SERVQUAL factors with 0.01 level significance. The results illustrated that INT3 (“I will recommend to the people around me that they use the rail transportation service”) is the most explainable factor for explaining passengers’ intention. Thus, PSU1 (“I’ve heard of viral outbreaks or diseases affecting train users”) plays the role of the most influential factors as a component of perceived susceptibility. Next, perceived severity found that PSE5 (“Illness and death affect the lives of people I know, such as my family”) was the best representative indicator. The perceived benefit revealed that PBE2 (“I think traveling by train can give me more value than other modes, despite the pandemic”) was the most influential indicator for explaining users’ views. Furthermore, the perceived barrier had indicator PBA3 as the most representative factor (“Despite the unusual situation, the train service has not yet been stopped. I will still be able to use rail transportation”). Then, cue to action was derived as CUE2, “My residence has easy access to rail transport, so I use it regularly in all situations”, was the highest measurement indicator. Finally, for the health motivation of users, it was found that MOT1 (“I value the safety of my family’s life and property”) was the most influential thing that passengers value.
For the concept of SERVQUAL, the factor that was a good fit for tangibility is TAN3: “The train stations and their toilets are kept clean, even under unusual circumstances”. The results revealed that most passengers have focused on cleanliness and hygiene as affected by the epidemic. Second, the reliability of rail service was best measured by REL3: “When there is a problem, the railway staff shows sincerity by solving the problem for you”. Next, it was also found that RES4 (“Staff provide timely and efficient service”) was the most important indicator for responsiveness of service from the perspective of rail users. Further, ASS3, “Employees have in-depth training and knowledge”, was the most influential factor in representing the assurance of rail transportation. Lastly, service empathy could be measured the most by EMP1: “Employees are attentive individually, whether or not problems arise in every situation”.
Regarding
Table 4, we ensured the absence of high correlations (multicollinearity) among the main factors of the model by conducting correlation tests. The beta weights were used to compute all observed indicators into the main factors, resulting in five constructs for the SERVQUAL model: tangibility, reliability, responsiveness, assurance, and empathy. Additionally, the HBM model comprised seven constructs: perceived susceptibility, perceived severity, perceived benefit, perceived barriers, cue to action, health motivation, and intention. The correlations between these constructs are presented in
Table 5.
To assess the discriminant validity, we examined the square roots of the AVE, which provide a good explanation of the constructs. Prior studies have suggested that the square roots of AVE for each factor should be greater than the correlation coefficients of their counterparts [
51,
61]. Our results confirmed that the statistical values fall within the acceptable range. Furthermore, according to Mukaka [
62], correlations between relevant variables should be less than 0.8, which we also found to hold true in our study. These findings provide strong evidence of the validity and reliability of the model.
4.2.2. Influence of the HBM on Service Quality Expectation
Table 6 and
Figure 2 display the outcomes of the model estimation concerning the determinants impacting passengers’ inclination to utilize rail transportation within a novel travel epoch. These determinants were initially postulated in the conceptual model. The goodness of fit of the model is evidenced by the following statistics:
= 2.795; CFI = 966; TLI = 960; SRMR = 0.038; and RMSEA = 0.033. The practical model integrates indicators derived from SERVQUAL and incorporates the HBM to elucidate the behavioral intent associated with railway utilization. The ensuing sections will furnish comprehensive elaboration on each facet.
Regarding the findings, they underscore and validate the enduring significance of the SERVQUAL model components in explicating the service quality inherent to rail transportation. Notably, “tangibility” surfaces as the foremost influencer, an emblematic indicator constituting a pivotal facet of service quality as perceived by passengers. This concurs with the conclusions of Miranda et al. [
17] and Gopal Vasanthi et al. [
21], whose investigations substantiate the affirmative and substantial correlation between tangibility and passenger contentment. Subsequently, “empathy” takes the stage, encapsulating considerations of attentiveness and deference toward passengers’ interests. 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 factors engender passenger confidence and foster an enduring rapport with the service, an insight echoed by [
34]. Additionally, “assurance”, the final strand within the SERVQUAL framework, while exhibiting comparably lower factor loading, retains its significance within the passenger paradigm. Its pertinence is evident from the work of Hundal and Kumar [
63], whose findings underscore the significant associations between all SERVQUAL indicators and the perceived service quality among intercity rail passengers.
Building upon the findings regarding hypotheses H1, H2, and H3, this study delved further into the pivotal role that the level of service quality required by passengers can play in positively influencing factors such as perceived benefits, health motivation, and cues to action for the post-pandemic era. Based on this premise, a clear conclusion can be drawn: enhancing the quality of service provision would lead passengers to perceive the benefits and value of the service more profoundly. The correlation between health motivation and perceived benefit is evident. When passengers recognize that a service contributes to an improved quality of life or provides safety and healthcare support, which is particularly relevant during epidemics, their motivation for maintaining health is amplified. Cues to action encompass the impact of human trends, ease of accessibility, and advertising. Rail transportation services that manifest significant improvements in service quality, such as emphasizing the importance and robustness of their offerings or ensuring convenient access, tend to generate greater incentives for passengers to opt for these services.
Furthermore, the outcomes stemming from
H4,
H5, and
H6 provide substantiated support for the adverse impact of SERVQUAL on perceived susceptibility, perceived severity, and perceived barriers within the context of the study. Within the framework of a post-pandemic scenario, the notion of perceived threat is intricately linked to the risk and severity associated with COVID-19 infection. Consequently, these concerns tend to escalate when the quality of rail transport services diminishes. As such, the enhancement of rail service quality assumes a crucial role in serving as an indicator for mitigating risks. Ding et al.’s [
26] findings demonstrated that improving service quality (such as cleaning public transport vehicles and stations) is also an important component of mitigating passengers’ risk perceptions.
Furthermore, it is worth noting that SERVQUAL exerts a negative influence on perceived barriers. The sweeping global changes triggered by significant events such as pandemics elicit heightened apprehensions among passengers regarding unforeseen incidents. Navigating public transportation becomes an arduous task in the midst of a pandemic, primarily due to the pervasive fear of epidemics acting as a formidable barrier for passengers. Hence, the amelioration of service quality emerges as a potent strategy that bolsters passenger confidence and subsequently diminishes these barriers.
In the context of factors positively shaping passengers’ intentions to utilize railway transportation, as evidenced by
H10, the results incontrovertibly demonstrate that cues to action wield the most pronounced and favorable impact on intention. This substantiates the notion that the broader environmental factors, encompassing interpersonal relationships, advertising campaigns, and ease of accessibility, collectively impinge upon users’ attraction and intention. This empirical finding aligns seamlessly with the observations of Razmara et al. [
28] and Yuen et al. [
44], whose research underscores the societal and interpersonal influences that significantly mold individual behavior. To elucidate, when individuals within one’s social sphere exhibit specific behaviors, a ripple effect often ensues, with others emulating such behaviors [
64,
65]. Exploring the consequences of the SERVQUAL analysis (
H7) unveils a dual impact. The investigation not only exposes an indirect effect of SERVQUAL on intention, mediated by the components of the HBM, but also identifies a direct effect. This twofold influence highlights the enduring significance of comprehensive service quality in cultivating passenger inclination towards embracing railway transportation in the post-pandemic era [
66,
67]. Hence, enhancing the quality of rail transport services across all facets—be it accessibility, passenger assistance, staff interactions, safety measures, reliability, or other pertinent factors—consequently leads to an increased inclination among passengers to utilize the service. Emanating from the exploration of perceived benefits (
H8), a constructive impact on intention becomes evident. This prevailing pattern serves as an overarching framework that readily explicates the mechanisms through which users are drawn to a given service. Should railway passengers glean a perception of service quality surpassing the associated costs, their willingness to opt for rail transportation heightens across diverse scenarios. Equally pivotal is the element of health (
H9), which emerges as a compelling motivation underpinning passengers’ service quality perception. This inference resonates harmoniously with the findings of Ortiz-Sánchez et al. [
68], who underscore the potency of health awareness and motivation in shaping attitudes towards activities, ultimately culminating in decision-making dynamics.
On the contrasting side, within the context of this study, certain factors have emerged that exert a negative impact on passengers’ intentions to engage with railway services. These factors encompass perceived susceptibility (
H11), perceived severity (
H12), and perceived barrier (
H13). The findings concerning perceived susceptibility align with the investigations of Morowatisharifabad [
29]. This line of reasoning emanates from the recognition that any semblance of sensitivity, vulnerability, or apprehension regarding unforeseen incidents or potential pandemics can arise at any moment. Particularly for passengers who must endure extended periods of travel until reaching their destination terminal, heightened vulnerability is concomitant with a diminished inclination to utilize the service. The perception of risk assumes pivotal importance from the passengers’ perspective, thereby warranting acknowledgment by relevant regulatory bodies. Likewise, perceived severity demonstrates a connection with intention. Passengers who harbor concerns encompassing general safety or the potential outbreak of an epidemic tend to exhibit an acute awareness of the corresponding severity. This observation echoes the findings of Lajunen and Räsänen [
43], who discerned that bolstering railway safety engenders heightened passenger confidence, subsequently amplifying their intention to avail railway services. Regrettably, apprehensions regarding change or perceived barriers likewise manifest as deterrents to passenger intention, a phenomenon also corroborated by Razmara et al. [
28]. Essentially, this signifies that an escalation in perceived barriers among passengers is directly proportional to a decrease in their intention to patronize rail services. Human behavior often gravitates towards establishing routines for recurrent activities and can be inclined against deviations in the environment. Consequently, unanticipated events or epidemics can elicit anxiety and a sense of insecurity among passengers, thereby undermining their willingness to employ the service. Hence, if service providers aspire to allure and cultivate trust among users, they must consistently refine service quality to ameliorate the barriers residing within passengers’ perceptions.