The COVID-19 pandemic has significantly impacted tourist behavior and changed how loyalty to travel destinations is built. This study aims to explore the factors influencing destination loyalty in a post-pandemic context, considering tourists' changing expectations and satisfaction.
Drawing on Expectation Disconfirmation Theory (EDT), the research develops a conceptual model to explore the relationship among perceived value, destination image, experience quality, destination satisfaction and destination loyalty. A convenience sampling strategy was employed to collect data through 264 tourist questionnaires. Partial least squares structural equation modeling was utilized in analyzing data gathered to support hypothesized associations.
Results indicate that experience quality, destination image and perceived value contribute significantly to destination satisfaction, which, in turn, has a strong and positive influence on destination loyalty. Results also highlight the mediating influence of satisfaction in post-pandemic travel environments on developing loyalty.
This study is limited by the application of a cross-sectional design and non-probability sampling, which will probably affect the generalizability of the findings. Future research should employ longitudinal methods and large samples to confirm and generalize the proposed model.
The study provides policymakers and destination marketers with practical insights into the importance of experience quality and perceived value in achieving ultimate tourist satisfaction and loyalty. As a post-pandemic context, these attributes must be a priority to maintain and regain competitive tourism destinations.
This research contributes to the body of tourism literature through the application of EDT in a post-pandemic setting, giving a new perspective on how tourist loyalty is reclaimed through satisfaction driven by shifting perceptions and experiences.
1. Introduction
The worldwide travel and tourism sector has undergone an unprecedented transformation amid the COVID-19 pandemic, presenting complex challenges as well as opportunities for destinations worldwide (Huang, Zhang, & Li, 2022). Before the pandemic, international tourism experienced steady growth, with global tourist arrivals rising from 674 million in 2019 to 1.5 billion in 2020 (UNWTO, 2021). However, the pandemic caused an abrupt and severe disruption, leading to a 74% decline in international tourist arrivals in 2020, marking the most significant downturn in modern tourism history (UNWTO, 2021). As a result, the tourism industry has faced its greatest threat in recent history, and the sector is expected to undergo a substantial downturn (Becker, 2020). This disruption exposes the fragility of the global tourism network, with ripple effects on economies, employment and local communities (Gössling et al., 2020). While the literature has extensively examined the economic and structural consequences of the pandemic (Khalid, Okafor, & Burzynska, 2021; Fernández, Martínez, & Martín, 2022; Ding, Gao, & Xie, 2024), it has fallen short in exploring how tourist behavior and loyalty processes have transformed in this context. This leaves a crucial gap in understanding what motivates tourists to return to destinations where safety, quality of experience and cost are under greater scrutiny.
While the economic impacts of the pandemic have received widespread media coverage, much less attention has been paid to how destinations can rebuild tourist loyalty in the post-pandemic era. Specifically, understanding the roles of experience quality, perceived value and destination image is crucial, as these factors directly influence tourist satisfaction and repeat visits, which are key elements for a sustainable recovery (Natarajan & Veera Raghavan, 2024; Hasan, Uddin, Alim, Azad, & Ali, 2020; Akter et al., 2020). Consequently, the industry's recovery will require innovative strategies, resilience and collaboration among stakeholders to adapt to the new normal and rebuild global travel demand. The establishment of focus early in the process is important because strategies will otherwise stay experimental and delicate without tourist loyalty (Alim, Ray, & Hossain, 2016; Gerke, Adams, Ooi, & Dahles, 2024; Gupta & Matatolu, 2025). As such, this study regards the quality of experience and perceived value as the main antecedents of destination loyalty in the post-pandemic setting.
The downturn was unprecedented, impacting everyone worldwide and raising critical questions for all stakeholders in tourism. This requires swift and long-term actions because the tourism industry is the most directly affected sector during this ongoing pandemic crisis, and it remains severely impacted, needing efforts to recover from this situation (Ling, Ramli, & Rahman, 2020; Ali et al., 2024). Studies highlight that tackling such crises calls for a multi-faceted approach, including health measures, strategic marketing and sustainable innovations (Higgins-Desbiolles, 2020; Sharma & Kumar, 2020; Wilopo & Nuralam, 2025). Since the pandemic is a global crisis, tourism destination planners must improve quality to attract future tourists by providing a better experience during their trips (Higgins-Desbiolles, 2020; Sharma & Kumar, 2020). The global economy is suffering due to the lack of international tourist arrivals caused by border restrictions, and it is expected that the pandemic will lead to further declines in tourism in 2021 (Fotiadis, Polyzos, & Huan, 2021). To address these challenges, experts emphasize that rebuilding trust through transparent communication and high standards of safety is essential to restore tourists' confidence (Fotiadis et al., 2021; Ling et al., 2020; Alim, Jee, Voon, Ngui, & Kasuma, 2021). Therefore, a systematic focus on responsible practices and innovative recovery strategies is crucial for reconstructing and strengthening the tourism industry's resilience for the future.
The tourism scenery after the pandemic is characterized by essential changes in traveler behaviors, expectations and the process of decision-making (Hu & Lu, 2024). On the contrary, tourists sought simpler experiences, highlighting local travel and relishing quality time with friends and family after the pandemic (Stankov, Filimonau, & Vujičić, 2020; Jieyao & Kumar, 2025). This tendency reproduces a rising preference for evocative travel experiences that line up with personal values as well as emotional well-being (Rasoolimanesh, Seyfi, Rastegar, & Hall, 2021; Stankov et al., 2020). Presently, travelers place a greater emphasis on flexibility, safety and meaningful experiences than ever before. These transformative changes necessitate a comprehensive understanding of destination loyalty mechanisms that can guide strategic recovery (Mimaki, Darma, Widhiasthini, & Basmantra, 2022; Jee, Ting, & Alim, 2019). In response to these issues, ensuring and improving destination loyalty can be a good mechanism to survive the tourism industry in a post-pandemic environment. Rasoolimanesh et al. (2021) also stated that the pandemic crisis negatively affected the destination image, and the tourists' travel intentions and future travel behavior. Consequently, fostering destination loyalty through enhanced safety measures, authentic experiences and strategic branding will be essential for the long-term recovery of the tourism sector (Pascual Fraile, Villacé Molinero, Talón Ballestero, & Chaperon, 2025).
Interestingly, tourism loyalty does not only imply repeat travels (Dai, Zhang, Pai, & Lee, 2025), but tourists' willingness to come back to places even in the midst of disruptions, provided that they associate their past visits with high value and satisfaction (Chew & Jahari, 2014; Ling et al., 2020; Sun, Wong, Huang, Kim, & Liu, 2024). Many recent studies examined tourists' destination loyalty in light of this pandemic situation (Lemy, Nursiana, & Pramono, 2020; Chua, Al-Ansi, Lee, & Han, 2020; Higgins-Desbiolles, 2020; Riestyanngrum, Pashaev, Simone, & Sisamuth, 2021; Torres-Pruñonosa, Batlle, De Esteban Curiel, & Díez-Martín, 2024). These studies suggest that fostering loyalty requires a blend of effective crisis management, personalization and innovative customer engagement strategies (Chua et al., 2020; Riestyanngrum et al., 2021). However, to date, antecedents that may affect destination loyalty in the post-pandemic environment remain unexplored. Thus, the present research bridges this gap by investigating experience quality's functions, perceived value and destination image and by examining the mediating effect of satisfaction. This integrated approach provides clearer theoretical and practical guidance for reclaiming tourist confidence and loyalty. Therefore, this study explores the elements influencing tourists' loyalty to destinations in the post-pandemic context. This paper also hypothesized that destination satisfaction might indirectly affect the nexus between the contributing factors and the loyalty toward a destination. The findings aim to expand existing knowledge in this field, representing a significant contribution to the research.
The current research has established a theoretical dialogue by relocating Expectation Disconfirmation Theory (EDT) in the context of tourism after the pandemic where the expectations of travelers, their perception of value and evaluation of the experience have all changed dramatically. It is argued that the existing studies are not fully integrating the behavioral dimensions brought about by the pandemic into the traditional expectation–performance–disconfirmation mechanism of EDT (Rasoolimanesh et al., 2021; Han, Nguyen, Lee, & Quan, 2024; Jebbouri, Zhang, Imran, Iqbal, & Bouchiba, 2022). The study advances the idea of a contemporary extension of EDT by acknowledging the revised cognitive–affective evaluative processes as a part of the model and demonstrating that tourists' satisfaction is an important mediator in crisis-conditioned experiences instead of just being a post-visit evaluative outcome (Salman, Trupp, Stephenson, & Chan, 2024). Thus, the study clarifies the boundaries between experience quality and destination satisfaction, which are two constructs that have often been confused in the past literature (Hassan & Saleh, 2024; Gómez-Suárez, Veloso, & Yagüe, 2025). Furthermore, this research provides a unique contextual contribution through the empirical testing of these relationships in Bangladesh, which is a developing Asian tourism market that has been little examined in loyalty research post-pandemic – where cultural norms, infrastructural constraints and crisis-driven changes uniquely influence tourist perceptions and recovery habits (Alim et al., 2021; Hasan et al., 2020). Since there are no empirical studies in Bangladesh that combine EDT with evaluations of pandemic-specific emotions and cognition, this research not only fills a crucial gap in regional research but also delivers country-specific insights that are very applicable to the future development of tourism strategies focused on resilience.
This scholarly work seeks to explore the impact of perceived value, experience quality and destination image on destination loyalty in the aftermath of the COVID period. Additionally, it aims to analyze the effects mediated by satisfaction on loyalty toward a destination within this context.
The remainder of this study is organized as articulated. The review of literature explores existing research on destination loyalty and its antecedents, particularly in the landscape of the aftermath of the pandemic. The methodology section outlines the study's design, data collection and analytical approaches. Results and analysis present the findings, highlighting key factors influencing destination loyalty. The discussions and implications section interprets the findings, addressing theoretical contributions and practical applications. In conclusion, the study highlights key findings, discusses its shortfalls and offers recommendations for future research.
2. Review of literature and study framework
2.1 Underlying theory
This study's conceptual framework was developed from the lens of EDT. This theory explains how an actor makes decisions (Oliver, 1980). EDT explores the psychological mechanism underlying consumer satisfaction by examining how the initial expectations of an individual interact with their perceived product performance and the subsequent deviation from those anticipated outcomes. It serves as a basis for understanding customer satisfaction levels by linking expectations, perceived performance and disconfirmation. From the notion of this theory, the current study considered experience quality and perceived value that can affect destination satisfaction, and in turn, loyalty toward the destination. This study also examines how the current image of destinations during the pandemic affects tourists' future behavior (see Figure 1).
The framework diagram is arranged from left to right within a single rectangular boundary. On the left side, three rectangles are stacked vertically and labeled from top to bottom as “Perceived Value”, “Destination Image”, and “Experience Quality”. On the right side, two rectangles are stacked vertically and labeled from top to bottom as “Destination Satisfaction” and “Destination Loyalty”. Three solid rightward arrows extend from “Perceived Value”, “Destination Image”, and “Experience Quality” toward “Destination Loyalty” and are labeled “H 1 a”, “H 1 b”, and “H 1 c”, respectively. Three dashed rightward arrows extend from “Perceived Value”, “Destination Image”, and “Experience Quality” toward “Destination Satisfaction” and are labeled “H 2 a”, “H 2 b”, and “H 2 c”, respectively. From “Destination Satisfaction”, a downward arrow labeled “H 3” points to “Destination Loyalty”, indicating that satisfaction influences loyalty.Theoretical framework
The framework diagram is arranged from left to right within a single rectangular boundary. On the left side, three rectangles are stacked vertically and labeled from top to bottom as “Perceived Value”, “Destination Image”, and “Experience Quality”. On the right side, two rectangles are stacked vertically and labeled from top to bottom as “Destination Satisfaction” and “Destination Loyalty”. Three solid rightward arrows extend from “Perceived Value”, “Destination Image”, and “Experience Quality” toward “Destination Loyalty” and are labeled “H 1 a”, “H 1 b”, and “H 1 c”, respectively. Three dashed rightward arrows extend from “Perceived Value”, “Destination Image”, and “Experience Quality” toward “Destination Satisfaction” and are labeled “H 2 a”, “H 2 b”, and “H 2 c”, respectively. From “Destination Satisfaction”, a downward arrow labeled “H 3” points to “Destination Loyalty”, indicating that satisfaction influences loyalty.Theoretical framework
The concept of “destination image” is explored in this paper, which denotes a significant effect on mitigating the complex situation of a destination in a post-pandemic environment (Kim, Holland, & Han, 2013). However, beyond its traditional role, destination image must also be re-evaluated in the context of pandemic-affected tourist behavior, where health security, flexibility and perceptions of risk shape travel decisions that are not captured in existing models (Nuta, Habib, Neslihanoglu, Dalwai, & Rangu, 2025; Meenakshi, Dhir, Kaur, Mahto, & Nicolau, 2025). This work thus picks up EDT in a post-pandemic setting and applies it to destination recovery, an innovation of context and a functional application.
This dynamic conceptual framework builds upon the constructs of destination satisfaction and tourists' destination loyalty, emphasizing their interplay. The study approaches that perceived value, tourists' experience quality and destination image may significantly impact satisfaction and loyalty toward a destination. Particularly, the framework responds to recent controversies surrounding conflicting results from previous work, where some studies have shown pronounced positive effects of these antecedents. In contrast, others show weak or non-existent effects. The disparities need to be addressed in order to refine the theoretical debate. Satisfaction is further proposed as an indirect (mediating) construct in the nexus between tourists' experience quality, perceived value and the image of a destination, influencing loyalty toward the destination. The mediating role of satisfaction is particularly relevant for post-crisis tourism, as tourists may not always translate positive attitudes into loyalty without first achieving a broad sense of reassurance and satisfaction (Salman et al., 2024). The framework contextualizes the interplay between destination satisfaction and loyalty toward a destination in the post-pandemic environment in the context of Bangladesh. This approach aims to provide actionable insights for tourism recovery strategies and enhance resilience in a post-pandemic context.
2.2 Perceived value
Perceived value is considered a crucial determinant of gratification and behavioral intentions. (Oh, 2000; Cronin Jr et al., 2000; Chaichi, Gladwell, & Peschken-Holt, 2025). It refers to the net value or worth a tourist perceives from the trip, assessed by the differences between the benefits received from the trip and the costs and sacrifices incurred by the visitors (Paulose and Shakeel, 2022). In the post-pandemic era, tourists' value perceptions increasingly include non-traditional elements such as hygiene practices, digital ease and pandemic precautions in addition to the traditional benefit-cost trade-off (Zhang et al., 2024). The increased conceptualization strengthens the explanatory power of perceived value as a determinant of satisfaction and loyalty in modern tourist contexts (Qiu, Li, Pan, Wu, & Guo, 2024). Empirical studies emphasize that a higher perceived value positively influences tourists' satisfaction, fostering loyalty and encouraging repeat visitation (Cronin Jr et al., 2000; Hanafiah, Amirah, Asyraff, Zain, & Hussein, 2025). Consequently, it is considered a critical determinant of tourists' decision-making and overall travel experience (Zhang, Chang, Rong, & Chen, 2023). Prior research establishes a robust connection between perceived value and loyalty toward a destination (Chen & Chen, 2010; Kim et al., 2013; Djatmika & Hermawan, 2024), particularly under challenging conditions such as the pandemic (Kock, Nørfelt, Josiassen, Assaf, & Tsionas, 2020; X. Zhang & Tang, 2021). However, contrasting findings also exist; Chen and Tsai (2007) and Qiu et al. (2024) claimed that tourists' perceived value does not affect the creation of loyalty to a destination. These uncertain outcomes verify the need to redefine perceived value in a post-pandemic context, when tourists may attach different values to multiple attributes in comparison to what was valued pre-pandemic. Furthermore, a noteworthy effect of perceived value on destination satisfaction has been found in the literature (Chen & Chen, 2010b; Chen & Tsai, 2007; Han, Kim, & Kim, 2011; Kim et al., 2013; Jin, Lee, & Lee, 2015; Qiu et al., 2024). Therefore, hypotheses derived from these discussions include:
The higher the perceived value by tourists, the greater their loyalty to the destination.
The higher the perceived value for tourists, the greater their satisfaction with the destination.
Destination satisfaction has a significant mediating effect in the nexus between perceived value and tourists' destination loyalty.
2.3 Destination image
The destination image has been recognized as the most crucial component that may evaluate the tourists' pre-, in-situation and post-visitation situation (Sarker et al., 2023). Destination image refers to the accumulation of an individual's beliefs, ideas, expectations and impressions associated with a destination (Jin et al., 2015; Liu, Wang, Cai, & Tse, 2024). The mental illustration of a destination arises through the plodding accumulation of perceptions and insights resulting from dealing out information across numerous sources, encompassing an understanding of its characteristics, advantages and distinctive impact (Zhang, Fu, Cai, & Lu, 2014). Following the pandemic, scholars identify that destination image is now more influenced by health safety perceptions, social responsibility and flexibility, aspects not emphasized in earlier models (Majeed, Zhou, & Kim, 2024; Aburumman, Abou-Shouk, Zouair, & Abdel-Jalil, 2025). Therefore, studying destination image in current times requires the inclusion of these new aspects.
Thereby, a noteworthy destination image is pivotal for fascinating tourists and determining their expectations, as it creates an impact on their decision-making and overall satisfaction (Tasci & Gartner, 2007; Hamdy & Zhang, 2023). Additionally, the destination image is incessantly formed by feedback and experiences, making it an energetic and growing concept (Riestyanngrum et al., 2021). Preceding studies supported that the image of a destination significantly influences loyalty toward a destination (Chen & Tsai, 2007), especially in the post-pandemic environment (Ling et al., 2020; Sharma & Kumar, 2020; Riestyanngrum et al., 2021; Han et al., 2024), while others dispute this claim (Jin et al., 2015; Song, Li, Van Der Veen, & Chen, 2011). However, the image of a destination also has a noteworthy positive influence on satisfaction with the destination. (Chi & Qu, 2008; Jin et al., 2015; Phi, Phuong, & Huy, 2024). Nevertheless, the results of other studies were uneven (Kim et al., 2013; Chen & Tsai, 2007). Accepting these contradictory findings, this study specifically investigates whether pandemic-designed images, such as health and risk attitudes, are stronger predictors of satisfaction and loyalty than pre-pandemic models. Therefore, building upon these findings, the following hypotheses are proposed:
The higher destination image, the greater the tourists' loyalty to the destination.
The higher destination image, the greater the tourists' satisfaction with the destination.
Destination satisfaction has a significant mediating effect in the nexus between destination image and tourists' loyalty to the destination.
2.4 Experience quality
The tourists' experience quality is a crucial component in tourism literature (Chen & Chen, 2010; Kao, Huang, & Wu, 2008; Alonazi et al., 2023). Experience quality reflects the psychological outcome of tourists visiting a destination, highlighting that service quality and experience quality differ in their meanings (Otto & Ritchie, 1996). The tourist experience involves sensory and emotional engagement, to a greater or lesser extent, on the part of the tourist with the tourist destination (Saoualih et al., 2024). Experience quality is measured by the affective evaluation of a tourist visitation experience on a tourist destination (Lian Chan & Baum, 2007; Rezaei Hajiabadi & Mohammad Shafiee, 2024), and it is also defined as the mental affective responses towards visiting experience of a tourist (Chen & Chen, 2010; Cole & Scott, 2004). Whereas its importance cannot be overstated, past research has tended to blur the distinction between experience quality and destination satisfaction by overlapping their respective descriptors, resulting in conceptual vagueness (Hassan & Saleh, 2024; Gómez-Suárez et al., 2025). The current research separates the two by conceptualizing experience quality as the temporary assessment of the tourism experience itself, whereas satisfaction is a global post-visit assessment. Disambiguating this distinction helps achieve theoretical specificity.
However, this construct is rarely used in the literature of these areas of study that measure the nexus between the satisfaction of tourists and loyalty toward a destination. The quality of experience has been found to have a noteworthy effect on tourists' overall satisfaction and their likelihood of returning to a destination (Kao et al., 2008; Chen & Chen, 2010; Abdou, Mohamed, Khalil, Albakhit, & Alarjani, 2022). Moreover, a greater level of quality of experience tends to enhance destination loyalty, as it strengthens emotional connections and positive perceptions of the destination. Studies explained that the experience quality has a notable positive impact on satisfaction with the destination (Chen & Chen, 2010; Jin et al., 2015; Hanafiah et al., 2025). The experience quality has a robust influence, and highest effect on destination loyalty (Rasoolimanesh et al. (2021). However, Chen and Chen (2010) claimed that this does not have a greater impact on loyalty toward the destination. These opposing positions necessitate further empirical studies, particularly under the novel circumstances provided by the pandemic, in which quality of experience is mutually entwined with safety, trust and emotional reassurance. So, this paper develops the following third set of hypotheses:
The higher experience quality of the tourists, the greater the tourist’ destination loyalty.
The higher experience quality of the tourists, the greater the tourist’ destination satisfaction.
Destination satisfaction has a significant mediating effect in the nexus between experience quality and tourists' loyalty to the destination.
2.5 Destination satisfaction and loyalty
Satisfaction toward a destination is considered as the most significant factor which helps to recognize tourists' destination loyalty. Satisfaction is measured by the visitors' post-purchase evaluation of any tourism product or services (Ryan, 1995; Abdou et al., 2022), while, Yüksel and Yüksel (2001) and Chaichi et al. (2025) argue that customer satisfaction is when perceived experience exceeds customers' expectation. Satisfaction is achieved when their expectations before traveling align with the experiences they encounter during their journey (Huddin, Kurnia, Deviyantoro, & Nafiudin, 2024). A highly satisfied tourist is more inclined to foster a favorable emotional attachment to a tourist destination, enhancing their overall loyalty. This emotional connection can also motivate repeat visits and generate word-of-mouth references. Recent studies also suggest that tourism satisfaction in the post-pandemic era relies on novel dimensions such as perceived safety, crisis management and trust-building strategies that must be further incorporated with established models (Komasi, Jamini, Hashemkhani Zolfani, Sadeghi, & Cavallaro, 2025; Kumar & Upadhyay, 2025).
However, destination managers contemplate tourists' loyalty to achieve long-term sustainable goals in operating tourists' destination (Chen & Chen, 2010; Alim et al., 2022). They prefer retention of existing tourists as this approach is less costly than attracting new tourists (Loureiro & González, 2008; Hanafiah et al., 2025). Apart from these, Oliver (1980) defined tourists' loyalty as the most influential determination to revisit a preferred product or service (Herrero-Crespo, San Martín-Gutiérrez, Collado-Agudo, & García-de-los-Salmones-Sánchez, 2024), while the other refers to tourists' loyalty toward a destination as their assessment of the intention to revisit a preferred tourism place or their inclination to refer it to others (Chen & Tsai, 2007; Herrero-Crespo, San Mart, & Gutiérrez, 2022; Djatmika & Hermawan, 2024). Loyal tourists return to the same destinations and recommend them to others, generating positive word-of-mouth and attracting new visitors (Kusnayain, Hussein, & Wu, 2025). These discussions reflect that tourists' destination satisfaction leads to their loyalty toward a particular destination. In relation to this, many previous scholars showed that the satisfaction affects significantly and positively on tourists' destination loyalty (Chen & Chen, 2010; Chen & Tsai, 2007; Chiu, Zeng, & Cheng, 2016; Kani, Aziz, Sambasivan, & Bojei, 2017; Hanafiah & Asyraff, 2023). Through the identification of both supportive and contrary evidence, this study presents a complete picture of the satisfaction–loyalty nexus, particularly in the one-time recovery phase of post-pandemic tourism. Thus, this paper develops the subsequent hypothesis:
The higher the destination satisfaction, the greater the tourists' loyalty to the destination.
3. Methodology
3.1 Survey measures
The measurement items for the proposed conceptual framework were adapted from existing literature in the field, with their reliability and validity previously established through comprehensive research studies. The items were further tested which have shown highly validated in current and previous studies (also see Table 2). For encouraging conceptual precision, each construct was operationally defined with precision and consistent with existing studies to ensure validity and reliability. Including five basic demographic questions, the survey tool includes five underlying constructs. Additionally, The three items for perceived value were taken from Bolton and Drew (1991). Seven items used in the previous study were extracted to construct destination image (Prayag & Ryan, 2011), and eight items related to the quality of experience (Otto & Ritchie, 1996). Three measurement items on the construct of destination satisfaction (Lee, Jeon, & Kim, 2011), and two items on destination loyalty (Chen & Tsai, 2007) were collected from the previous studies.
3.2 Sampling and data collection
The numerical survey was conducted to gather data from prominent tourist destinations in northern Bangladesh, specifically Mahasthangor in Bogra and Paharpur in Naogaon, during October–November 2020. Utilizing a convenience sampling approach, tourists were recruited directly at the destination sites and self-administered survey instruments were distributed. Even though such non-probability sampling limits generalizability, it was adopted due to practical limitations in the midst of the pandemic, and an attempt was made to limit bias by interacting with a diverse group of respondents. Initially, a total of 271 replies were initially gathered, however after eliminating seven responses because of noticeably insufficient data, 264 were deemed useable. According to numerous academics' guidelines (Hoyle, 1995; Tabachnick, Fidell, & Ullman, 2007), the size of the sample was acceptable and satisfied the minimal requirements for the analysis using Partial Least Squares Structural Equation Modelling (PLS-SEM). However, as the data were cross-sectional, causal inferences must be interpreted cautiously. Participants were given with the possibility to showcase their level of agreeing or disagreeing to the statements via a Likert scale of five-point, from 1 signified strongly disagree to 5 signified strongly agree.
3.3 Data analysis
The scholarly work explored the connections within the projected framework through PLS-SEM. To assess the reliability of the indicators, a variance inflation factor analysis was conducted (Hair et al., 2017). The measurement model's quality was evaluated based on threshold values for factor loadings, average variance extracted (AVE), composite reliability (CR) and heterotrait-monotrait (HTMT) criteria. Though there were certain source scales, such as the experience quality construct by Otto and Ritchie (1996), with more items, eight were selected to maintain the context of the study and the respondent manageability without compromising content validity. Pilot testing and expert check assisted this. To assess the significance of the structural model, the study used blindfolding and bootstrapping techniques. These approaches were used to examine the model's precision and the effect sizes of the relationship pathways (Hair et al., 2017; Henseler, Ringle, & Sarstedt, 2015).
4. Results and analysis
4.1 Sample structure
Before going on with the measurement scale and structural model, the study started with a descriptive statistical analysis to verify participant frequencies and percentages. Table 1 contains the answers to the demographic questions. Actually, the sample's (N = 264) demographic traits show its diversity and representativeness. Firstly, the age distribution replicates a balanced mix, with the largest group aged 21–30 (28.8%), followed closely by those aged 41–50 (25.0%) and 31–40 (22.0%). Secondly, gender representation leans slightly toward females, who make up 54.2% of respondents, compared to 45.8% males. Thirdly, the greater part of participants is married (68.9%), with the remaining 31.1% being single. Fourthly, educational backgrounds are notably varied, with graduates forming the largest group (30.1%), followed by Higher Secondary Certificate (HSC) holders (24.7%). Besides, the sample consists of participants with diverse educational backgrounds, from those with less than a Secondary School Certificate (15.3%) to post-graduates (14.0%), offering a well-rounded perspective on educational diversity. Lastly, the income distribution reveals interesting economic stratification, with most of the respondents falling in the middle-income brackets. The largest income group is Tk. 30,001–40000 (31.4%), followed by Tk. 20,001–30000 (28.0%), and less than 20,000 (21.6%).
Summary of sample structure
| Characteristics | (N = 264) | (%) | Characteristics | (N = 264) | (%) |
|---|---|---|---|---|---|
| Sample's Age: | Education | ||||
| 18–20 years | 21 | 8.0 | Less than SSC | 40 | 15.3 |
| 21–30 years | 76 | 28.8 | SSC | 42 | 15.9 |
| 31–40 years | 58 | 22.0 | HSC | 65 | 24.7 |
| 41–50 years | 66 | 25.0 | Graduation | 80 | 30.1 |
| Above 50 years | 43 | 16.2 | Post-graduation | 37 | 14.0 |
| Gender: | Income: | ||||
| Male | 121 | 45.8 | Less than Tk. 20,000 | 57 | 21.6 |
| Female | 143 | 54.2 | Tk. 20,001–30,000 | 74 | 28.0 |
| Marital status: | Tk. 30,001–40,000 | 83 | 31.4 | ||
| Single | 82 | 31.1 | Tk. 40,001–50,000 | 33 | 12.5 |
| Married | 182 | 68.9 | Tk. 50,001–60,000 | 10 | 3.8 |
| Others | – | – | Above Tk. 60,000 | 7 | 2.7 |
4.2 Test of reliability and validity
To assess the validity and reliability of the measurement scales, this paper performed confirmatory factor analysis, average variance extracted (AVE) and composite reliability (CR), using various recommended threshold values to verify convergent validity (Hair, Ringle, & Sarstedt, 2011; Fornell & Larcker, 1981). Showing in Table 2, the loading values, CR values and AVE values exceeded the recommended threshold values of 0.6, 0.708 and 0.50, correspondingly (Hair et al., 2011; Fornell & Wernerfelt, 1987; Wong, 2013). As a result, all three conditions for establishing convergent validity of the model were fulfilled. The study then assessed discriminant validity via the Fornell and Larcker (1981) criterion and the HTMT criterion (Henseler et al., 2015) (see Table 3). According to the Fornell and Larcker criterion, the AVEs square roots were more than the values of correlations for individual pair of the study constructs. Meanwhile, the HTMT criterion designates that a threshold value less than 0.90 between two variables is sufficient to ensure discriminant validity. The HTMT confirmed that the results were less than the critical value of 0.90 for every specific group model assessment. Therefore, the study successfully passed the tests for discriminant validity. These results confirm that measurement scales used are reliable and valid, therefore providing support for the believability of additional structural model analysis in light of initial concerns about shortened scales.
Items and reliability indices
| Construct | Item | Factor loading | CR | AVE |
|---|---|---|---|---|
| Destination Image (DI) | DI3 | 0.76 | 0.79 | 0.56 |
| DI4 | 0.78 | |||
| DI5 | 0.70 | |||
| DI6 | 0.69 | |||
| DI7 | 0.71 | |||
| Destination Satisfaction (DS) | DS1 | 0.81 | 0.84 | 0.63 |
| DS2 | 0.83 | |||
| DS3 | 0.74 | |||
| Experience Quality (EQ) | EQ2 | 0.70 | 0.86 | 0.51 |
| EQ4 | 0.75 | |||
| EQ5 | 0.69 | |||
| EQ6 | 0.69 | |||
| EQ7 | 0.73 | |||
| EQ8 | 0.72 | |||
| Perceived Value (PV) | PV2 | 0.72 | 0.78 | 0.64 |
| PV3 | 0.87 | |||
| Destination Loyalty (DL) | DL1 | 0.88 | 0.88 | 0.79 |
| DL2 | 0.90 |
Note(s): The item DI1, DI2, EQ1, EQ3 and PV1 were removed due to poor factor loading
Test of Discriminant Validity results
| Fornell and Larcker criterion* | Heterotrait-monotrait (HTMT) criterion** | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| DI | DS | EQ | PV | DL | DI | DS | EQ | PV | DL | |
| DI | 0.75 | |||||||||
| DS | 0.46 | 0.79 | 0.70 | |||||||
| EQ | 0.53 | 0.70 | 0.71 | 0.76 | 0.83 | |||||
| PV | 0.35 | 0.42 | 0.37 | 0.80 | 0.67 | 0.73 | 0.59 | |||
| DL | 0.38 | 0.62 | 0.53 | 0.38 | 0.89 | 0.58 | 0.87 | 0.68 | 0.65 | |
Note(s): The values representing diagonally in italic signify the AVE square root, while the coefficients of correlations are signified in the off-diagonal values
**0.90 is the threshold value for Discriminant validity in HTMT Criterion
4.3 Hypotheses testing
Bootstrapping method was applied in the structural model to assess path relationships, confirming the validity and importance of the links between the study variables (Hair et al., 2017). The procedure utilized 5,000 subsamples from the original dataset. Bootstrapping results (refer to Table 4) demonstrate that the direct effects of PV and EQ on DL, PV, DI and EQ on DS, as well as DS on DL were positive and significant statistically. Thereby, hypothesis H1b was rejected because the effect of DI on DL was statistically insignificant indicating that destination image alone may not have any direct effect on loyalty in the sampled context, which aligns with recent literature stressing the mediating role of satisfaction (Jebbouri et al., 2022).
Results of hypotheses testing
| Direct effect | Beta | S.E. | t-value | p-value | 5.00% | 95.00% | Decision | f2 | R2 | VIF | Q2 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| H1a: PV → DL | 0.12 | 0.06 | 1.97 | 0.02 | 0.01 | 0.20 | Supported | 0.02 | 0.42 | 1.26 | 0.31 |
| H1b: DI → DL | 0.06 | 0.05 | 1.33 | 0.09 | −0.01 | 0.14 | Rejected | 0.01 | 1.46 | ||
| H1c: EQ → DL | 0.13 | 0.07 | 1.85 | 0.03 | 0.02 | 0.25 | Supported | 0.01 | 2.21 | ||
| H2a: PV → DS | 0.17 | 0.05 | 3.52 | 0.00 | 0.09 | 0.25 | Supported | 0.05 | 0.53 | 1.20 | 0.32 |
| H2b: DI → DS | 0.08 | 0.05 | 1.56 | 0.06 | −0.01 | 0.17 | Supported | 0.01 | 1.45 | ||
| H2c: EQ → DS | 0.59 | 0.05 | 12.01 | 0.00 | 0.49 | 0.67 | Supported | 0.50 | 1.47 | ||
| H3: DS → DL | 0.45 | 0.08 | 5.85 | 0.00 | 0.31 | 0.57 | Supported | 0.17 | 2.11 |
| Post-hoc (mediation) | Beta | S.E. | t-value | p-value | 5.00% | 95.00% | Decision | |
|---|---|---|---|---|---|---|---|---|
| H4: PV → DS → DL | 0.08 | 0.02 | 3.27 | 0.00 | 0.04 | 0.13 | Supported | |
| H5: DI → DS → DL | 0.04 | 0.03 | 1.45 | 0.15 | −0.00 | 0.10 | Rejected | |
| H6: EQ → DS → DL | 0.27 | 0.05 | 5.39 | 0.00 | 0.19 | 0.38 | Supported |
Note(s): **p < 0.01, *p < 0.05, S.E. = standard error
Furthermore, DS had favourable and important mediating effects on the impact of EQ and PV on DL. On the other hand, DS had minimal and detrimental indirect impacts on the link between DI and DL. As a result, while hypothesis H5 was not supported, hypotheses H4 and H6 were supported. This analysis shows the theoretical contribution by illustrating that experience quality and perceived value influence loyalty to a great extent through satisfaction, with managerial implications for destination management (Phi et al., 2024).
The blindfolding method was utilized to assess the structural model's predictive relevance (Hair Jr et al., 2017; Henseler et al., 2015). The coefficient of determination (R2) was used to evaluate the variance accounted for in the endogenous constructs. Additionally, the model incorporated Stone-Geisser's Q2 to examine cross-validated forecasting significance. Therefore, the results denote that DL had R2 and Q2 values of 0.42 and 0.31, respectively, while DS had R2 and Q2 values of 0.53 and 0.32. These findings indicate that PV, DI and EQ accounted for 42% of the variance in DL and 53% of the variance in DS. Since the Q2 values for both DL and DS (0.31 and 0.32) were more than zero, the structural model demonstrated forecasting significance. Furthermore, to establish robustness, rival models without mediation paths were tested, and it was verified that mediation through DS significantly improved model fit and explanatory power compared to direct-effect-only models (Quang & Thuy, 2024).
Additionally, the effect sizes (f2) were calculated to examine the relative effect between the independent constructs and the dependent constructs (Chin, 2009). As per the data, EQ had its kind impact size, followed by DS and had the highest positive correlations with both DS and DL (f2 = 0.50 and f2 = 0.17, respectively). More information on the impact sizes among the study's constructs is presented in Table 4. Overall, while some of the β values were modest (e.g. PV → DL), the results have substantive implications that certain constructs like experience quality play more of a role in influencing satisfaction, which in turn creates loyalty (Deng, Wang, & Ma, 2024). The failure to detect the significant effect of DI on DL underscores the importance of considering contextual factors and mediators when interpreting results.
Moreover, the effect sizes (f2) measured the relative effect of independent variables on dependent variables (Chin, 2009). The findings indicated the largest effect size for EQ, following by DS, demonstrating the most robust positive correlations with DS and DL at (f2 = 0.50) and (f2 = 0.17), respectively. Table 4 provides further insights into the effect sizes among the study's constructs.
5. Discussions and implications
5.1 Discussions
This main goal of this paper was to examine destination loyalty in Bangladesh, a developing nation, in the wake of the epidemic. In particular, the study explored how, in the post-pandemic context, perceived value, destination image and experience quality impact destination satisfaction and, in turn, destination loyalty. Also, the investigation aimed to uncover potential variations in these relationships across different demographic groups of travelers. Furthermore, it sought to provide actionable insights for destination managers to foster loyalty in the face of evolving tourist behaviors. In fact, the nexus between perceived value, the image of a destination, experience quality, as well as the loyalty of travelers on a destination were looked at and examined the indirect function (mediating role) of destination satisfaction. The results present a nuanced perspective with significant implications for tourism literature, particularly in the context of the post-pandemic recovery. When many earlier studies have used these constructs to explain tourists' destination satisfaction, the importance of perceived value, destination image and tourists' experience quality has gained broader recognition (Chen & Tsai, 2007; Chen & Chen, 2010; Chi & Qu, 2008; Han et al., 2011; Jin et al., 2015; Kim et al., 2013).
The findings, in addition to confirming the well-known associations, are bringing to light some unexpected shifts in behavior that contribute to the theoretical understanding of the post-pandemic tourism dynamics (Rasoolimanesh et al., 2021; Han et al., 2024) To begin with, destination image is, as a rule, one of the strongest loyalty predictors, however, our model indicates that its direct impact becomes, under the condition of risk-sensitive travelers, statistically insignificant. This means that tourists during a crisis rely less on generalized cognitive impressions and more on the very particular experiential cues like perceived safety, service consistency and emotional reassurance (Jebbouri et al., 2022; Salman et al., 2024). Therefore, destination image loses its explanatory power when the internalized perceptions are outweighed by the situational risk appraisals, which is a pattern that has not been adequately studied in past research (Han et al., 2024).
Particularly in the post-pandemic context, this paper reaffirmed the strong impact of perceived value and the quality of visitors' experiences on destination loyalty. These outcomes align with earlier research (Chen & Chen, 2010; Kim et al., 2013; Rasoolimanesh et al., 2021). Additionally, the study underscored the evolving preferences of tourists, emphasizing their demand for personalized experiences and flexible service options. Also, it suggested that destinations which prioritize health protocols and cater to these new preferences are more likely to cultivate loyal visitors. The outcomes highlight that travelers place great importance on premium travel experiences and high-quality services, characterized by well-managed, safe environments and service providers' consistent efforts to keep social distancing amid the pandemic.
Most importantly, the findings show that the quality of the experience is the only factor that has the greatest impact on the satisfaction of the destination, which is much larger than that of the perceived value and the destination image. This increased impact indicates that, in a post-Covid scenario, tourists do not judge their experiences any longer solely on the basis of functional or hedonistic criteria but rather have the soirée and the psychological reassurance by the tourist destination visit (Hassan & Saleh, 2024; Gómez-Suárez et al., 2025). This is a major shift in the models of satisfaction in which experience quality is considered as the cause of such quality since it is now seen as a crisis-responsive quality instead of a constant service quality attribute. These results not only augment the theoretical narrative but also indicate that “quality” of experience is the factor which, in extreme situations like the pandemic, disconnects and translates the customer's satisfaction expectations concerning safety – like the reliability of safety measures, empathy of the staff and emotional comfort, – into the actual customers' satisfaction (Rasoolimanesh et al., 2021; Salman et al., 2024).
Interestingly, despite the pandemic, travelers did not consider destination image as a strongly significant item influencing loyalty. This finding is consistent with previous research (Song et al., 2011; Chen & Tsai, 2007; Jin et al., 2015; Zain, Hanafiah, Asyraff, Ismail, & Bafadhal, 2025). However, such surprising non-significance can be accounted for within the framework of situational priority due to the fact that travelers have given more priority to short-term safety and quality of experience rather than to general destination perceptions at the moment. This suggests a re-conceptualization of the theoretical understanding of destination image, focusing on the context dependence of its influence on loyalty.
5.2 Theoretical implications
The present research applies the EDT to the travel behavior and risk attitudes of Bangladeshi travelers in the post-pandemic period, thereby shifting the focus from the traditional destination image models to the quality of the experience, perceived value and adaptable service strategies. Future researchers may use EDT along with the likes of Protection Motivation Theory or the Theory of Planned Behavior to better understand the decision-making process regarding risk and resort to behavioral intentions.
One of the major contributions is the detection of boundary conditions that alter the influence of value perception, destination image, experience quality, satisfaction and loyalty. In situations perceived as high-risk, the image of the destination does not predict loyalty very well, and factors like safety perception and emotional reassurances become more important (Rasoolimanesh et al., 2021; Han et al., 2024; Jebbouri et al., 2022). The quality of experience acts as a crisis-sensitive indicator of satisfaction (Hassan & Saleh, 2024; Gómez-Suárez et al., 2025), which means that the judgments made in an uncertain situation depend on the emotional comfort provided, safety perceived and reliable service delivery (Salman et al., 2024).
Loyalty hierarchies have been changed by the pandemic with satisfaction playing a mediating role in the converting of experiential security into a long-term commitment, this aspect of EDT has been expanded to cover the crisis-specific emotional contingencies (Han et al., 2024; Jebbouri et al., 2022; Salman et al., 2024). Factors like the type of traveler, the category of destination and the risk tolerance have a moderating effect on these relationships, thus, making clear the contextual diversity and giving direction for future research models built on EDT (Dai et al., 2025; Song et al., 2011).
5.3 Practical implications
The relationships that exist between perceived value, destination image, experience quality and destination loyalty are analyzed in this study. Importantly, it is indicated that loyalty is driven by travelers' satisfaction, alongside perceived value and experience quality. Destination's pleasure is magnified and local cultural values, infrastructure gaps and the economic situation of Bangladesh are among the factors influencing the tourist's perceptions. For instance, limited transport facilities and local service standards are making the quality of experience more significant, while the culture of hospitality is running the development of loyalty.
On the one hand, destination managers should improve the quality of experience, offer immersive and interactive offerings and gain trust through open communication on health protocols and service reliability. They can also arrange events that are rich in culture, ensure safety and manage the people's perceptions, which in turn will lead to higher perceived value, satisfaction and loyalty. The research results point out that under the condition of high perceived risk, the destination image is not enough by itself; the guarantee of safety, service reliability and emotional support is vital (Han et al., 2024; Jebbouri et al., 2022).
The development of experiences should be based on the type of traveler, with local travelers putting the price factor first and foreign ones cleanliness and guidance (Hassan & Saleh, 2024). Specific to destination strategies – urban locations applying crowd-control and digital touchpoints, nature-based sites taking advantage of open spaces and cultural immersion – are in sync with post-pandemic preferences (Rasoolimanesh et al., 2021). The government should incorporate resilience strategies that combine flexible safety protocols, real-time feedback and hybrid preparedness measures in the tourism sector revival plans (Salman et al., 2024).
6. Conclusions
The paper has provided valuable insights into the dynamics of destination loyalty in the post-pandemic travel landscape and offered a thorough comprehension of the complicated behavioral and psychological processes that influence traveler choices. This paper demonstrates a fresh perspective on how destinations can rebuild and sustain visitor loyalty during times of unprecedented global uncertainty. In fact, it emphasizes the need for destinations to adapt their strategies to align with the changing priorities of travelers in a post-pandemic world. Besides, the research focuses on the significance of resilience and innovation in rebuilding tourist trust and engagement. By assessing the intricate relationships between perceived value, destination image, experience quality, as well as destination satisfaction, it redefines how we understand destination loyalty.
The outcomes of the study reveal that post-pandemic travelers are fundamentally different. In fact, they are more risk-averse, practical and focused on secure, well-rounded travel experiences. This transformation underlines the growing importance of trust-building measures and adaptive service designs in meeting new traveler expectations. Moreover, understanding these evolving preferences is vital for fostering long-term loyalty. Particularly, experience quality appeared as the key driver of both destination satisfaction and loyalty. By integrating pandemic-specific factors – such as safety protocols, attentive service interactions and integrated value propositions – the research goes beyond conventional service evaluations. In addition, the study highlights that digital and contactless tourism experiences such as mobile apps, web-based booking platforms and virtual visits can be instrumental in enhancing quality of experience and perceived value and offer operational directions for managerial responses to follow in the future.
The scholarly work emphasizes the psychological complexity of traveler decision-making, where mental and emotional factors intertwine to shape loyalty. It discloses that loyalty is not just a product of tangible experiences but also deeply rooted in the emotional bond of travelers with destinations. This interaction of emotions and perceptions offers a richer understanding of loyalty. Besides, destination satisfaction plays a crucial mediating role, offering deeper insights into how travelers translate tangible service elements into emotional connections. This articulated understanding reframes destination loyalty as a multifaceted psychological journey influenced by various environmental factors, rather than a straightforward, linear process. In fact, this perspective adds valuable theoretical depth, emphasizing that loyalty is shaped by a combination of experiences and emotions rather than any single aspect of service. Managerial recommendations are thus designed to recommend personalized interventions, such as targeted health-safety practices, culturally engaging experiences and customized digital engagement tools, rather than generic “pleasure events,” with greater viability in post-pandemic developing economies.
This study concedes several methodological limitations, that open up valuable and potential avenues for future studies. One crucial limitation underlies in the study's geographic focus, which was restricted to the northern region of Bangladesh. Therefore, expanding the research scope to include a nationwide dataset would yield more diverse insights, reflecting variations across different locales. Additionally, addressing regional disparities can help refine tourism strategies. To improve the applicability of the findings, future studies should take a nationwide approach by collecting data from diverse tourism destinations across all four regions of the country. Such a broader sampling strategy would capture subtle differences in visitor experiences and perceptions across various cultural and geographic contexts, offering a broader and more representative perspective on the dynamics of destination loyalty. Recommendations in the future should consider feasibility of implementation, particularly in post-pandemic resource-constrained contexts, with an assurance that recommended methods are scalable and affordable (Bang-Ning, Jitanugoon, & Puntha, 2025).
Additionally, these methodological limitations highlight several promising avenues for further investigation, paving the way for deeper insights into this important area of research. Given the restrictions on foreign travel during the epidemic of COVID-19, responses for the paper was only collected from local travelers. Future research could explore how international travel patterns impact destination loyalty in the post-pandemic context. To have a better understanding of destination loyalty processes, future research should try to include both local and foreign visitors. Additionally, the experience quality construct was measured using just eight items even though Otto & Ritchie's (1996) framework recommends 23 possible scales. Researchers are urged to create a more thorough measurement tool that precisely represents the overall quality of the tourist experience. Furthermore, by adding other components like destination attachment and personal participation, future research might enhance the theoretical framework and provide a deeper understanding of visitor destination loyalty both before and after global pandemics.
Ethics statement
This study was conducted in accordance with ethical standards. All participants provided informed consent prior to their involvement in the study. Participation was voluntary, and confidentiality of responses was ensured throughout the research process.
