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Article

Linking Fintech Payment Services and Customer Loyalty Intention in the Hospitality Industry: The Mediating Role of Customer Experience and Attitude

by
Rashed Al Karim
1,*,
Farid Ahammad Sobhani
2,
Md Karim Rabiul
3,
Nusrat Jahan Lepee
1,
Mohammad Rokibul Kabir
1 and
Mohammad Abdul Matin Chowdhury
1
1
School of Business Administration, East Delta University, Chattogram 4209, Bangladesh
2
School of Business & Economics, United International University, Dhaka 1212, Bangladesh
3
Faculty of Hospitality and Tourism, Prince of Songkla University, Phuket 83120, Thailand
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(24), 16481; https://doi.org/10.3390/su142416481
Submission received: 10 November 2022 / Revised: 25 November 2022 / Accepted: 29 November 2022 / Published: 9 December 2022

Abstract

:
Although Fintech services benefit the hospitality industry significantly, studies conducted in Bangladesh are limited. Investigations on the mediating role of customer experience and attitude in the relationship between Fintech services and customer-loyalty intention are also scarce. Therefore, this study explores the association between Fintech services and customer-loyalty intention in the hospitality sector in Bangladesh. Additionally, it looks into how customer attitude and experience mediate the link between Fintech services and customer-loyalty intention. Data were collected from 365 respondents (customers) selected conveniently from 15 hotels (3-, 4-, and 5-star) in the two most renowned cities in Bangladesh, i.e., Chattogram and Cox’s Bazar. Smart-PLS was used to test the proposed model. The results of the study revealed that Fintech services, customer experience, and customer attitude significantly impacted customer-loyalty intention. Moreover, customer experience and customer attitude mediated the relationship between Fintech services and customer loyalty intention. The distinctive contribution of this investigation is the mediation of customer experience and customer attitude in the Fintech services and customer-loyalty intention relationship, as well as adding value to the existing Fintech literature. The study’s findings will help the hospitality sector in Bangladesh become more competitive and improve the quality of its services. Fintech companies and hospitality organizations must make careful plans to encourage the widespread implementation of Fintech.

1. Introduction

Fintech services, an umbrella term for advanced technologies that facilitate financial services, has brought extraordinary digital-financial system advancements, mainly in developed and developing countries [1,2]. Although technology advancements have specific detrimental effects on the hospitality sector, they have also created significant benefits [3]. In particular, the development of financial technology-using businesses has widened the availability of alternative financing sources [4]. Nowadays, companies in the hospitality industry have easy access to different Fintech enterprises. The hospitality industry must use the benefits of information and communication technology to increase its number of customers and occupancy rate [3]. Fintech services offer numerous benefits for the hospitality industry in reducing financing expenses, marketing and promoting benefits, giving more straightforward access to financial resources, and convenience for collecting funds for financing different projects through crowdfunding platforms [5].
To improve the customer experience, Fintech services combine new procedures with creating and providing individualized, round-the-clock financial services [6,7]. The digital and social realms combine in the Fintech and online environments to provide a personalized customer experience [8]. To deliver a consistent customer experience across several domains, businesses work to increase connection and integration. Customer experiences are distinctive, innovative, enduring moments and feelings encountered during consumption, influencing recommendations and future-purchase patterns. Customer experience is crucial for competitive advantage, diversity, and loyalty. Loyal customers not only spend more money but also provide favorable word-of-mouth recommendations, reduce service costs, and are less price sensitive [9,10].
Moreover, customer loyalty has been the most vital feature for many service organizations. Loyal customers are essential to success and getting a new customer costs significantly more than keeping an existing one [11,12]. In Bangladesh, many customers use Fintech services yearly, making their tours convenient and hassle-free. Bangladesh ranks 77th in terms of the availability of financial services and 86th in terms of the affordability of such services [13]. However, Bangladeshi firms are still in the early stages of development of Fintech technology. Consequently, the current customer base is used to traditional methods, and privacy issues are likely to remain a significant concern for them as long as security measures are not effectively communicated [14]. In developing nations like Bangladesh, Fintech has the potential to broaden financial inclusion and speed up the growth of the financial industry [15]. Based on this rationale and debate, the present study examines how Fintech services impact customer loyalty intention in the hospitality industry in Bangladesh.
In addition, only some Fintech-based studies measured customer-loyalty intention toward Fintech services in the hospitality industry. However, researchers in Bangladesh have studied Fintech in banking [13,16]. As Fintech is still in the early stage in the Asian market, much research has been conducted to look at the benefits and costs of Fintech to provide the most up-to-date solutions for individuals and businesses [17,18]. Although those studies significantly contribute to Fintech service, two essential gaps still need to be addressed. First, studies that measured tourist loyalty intention through Fintech services in the hospitality industry are limited. Precisely, only a few studies explored the benefits of Fintech services in the Bangladeshi hospitality sector. Second, among the limited studies on Fintech services in hospitality, to our knowledge, the mediating role of consumer experience and customer attitude in the link between Fintech services and customer-loyalty intention is still not being explored.
Therefore, this piece of research fulfills the above gaps and enhances the knowledge of Fintech services in the Bangladeshi hospitality industry. To assess the importance of Fintech services (i.e., ease of use, competitiveness, perceived security, perceived value, and usefulness), the current study first considers how Fintech services affect customer loyalty intention before assessing how customer experience and attitude mediate the Fintech services and loyalty intention association.
As the hotel business evolves toward digitization in Bangladesh, the study’s findings are expected to be disruptive by significantly expanding the literature on financial technology and its services. As Fintech is still an emerging concept in Bangladesh, this study may increase the awareness of Bangladeshi people regarding Fintech services with the increasing reputation of Fintech services. Finally, the study findings will benefit the Bangladesh hospitality industry since Fintech significantly contributes to service delivery, customer experience, productivity, effectiveness, and transaction-costs reduction. Therefore, to increase the competitiveness and service performance of the hospitality sector in Bangladesh, Fintech firms and hospitality organizations must plan adequately to promote Fintech deployment on a wide-ranging scale.

2. Literature Review

2.1. Fintech Services

According to Kim et al. [19], “Fintech is a service sector which uses mobile-centred IT technology to enhance the efficiency of the financial system” (p. 1058). According to Gomber et al. [7], Fintech refers to financial industry innovators and disruptors who utilize the internet and automated-information processing to take advantage of the accessibility of communication across all platforms. New business models employed by these firms provide more opportunities, flexibility, and security than traditional financial services [7,20]. Fintech offers swifter, more dependable, and less expensive financial services [21]. Using cutting-edge technology and creative business models like peer-to-peer (P2P) technology, cryptocurrencies, crowdfunding services, financial services, including payments, investments, insurance, and loans are being changed. Fintech companies, in particular, provide alluring value promises such as, faster, less cumbersome, convenient, and more efficient experiences for financial services [21,22]. In addition, fund transfers, seamless payments, perceived privacy, and perceived value are among the most disrupted Fintech aspects. Although Fintech service-innovation tactics may differ, Fintech service providers consistently offer secure and convenient client services to decrease the time and effort a customer must spend on traditional financial services [7,20,23].
Fintech has reached a long way in the past decade, and its services are now employed in the banking and finance, telecommunications, aviation, and wholesale sectors [24]. Despite the concerns about the technology’s security risks, individuals are adopting and using Fintech services daily due to its ease and economic benefits [25]. Fintech applications may improve transparency of mobile financial transactions, cost-effectiveness, and convenience [26]. To assure reliability and speed up customer experience, Fintech service providers must ensure that their goods and services are easy to use, meet demands, and protect customer data. Fintech services are designed as customer-oriented, easy-to-use, simple, convenient financial services with greater service values [27,28]. By reviewing the literature on Fintech services [23,29,30,31] and considering the hospitality industry in Bangladesh, the present study incorporates ease of use, competitiveness, perceived security, value, and usefulness as Fintech services that facilitate and support the financial activities of the Bangladeshi consumers.
Ease of Use: The individual effort to use new technology is associated with the easing of use [30,32,33]. The usability of using Fintech services is described as the ease of use, which includes evaluating the Fintech service interface and the convenience of accessing Fintech services via various electronic devices [34]. Ease of use measures how intuitively Fintech apps perform and reduce the expected anxiety associated with using a Fintech service [23]. Customers, even tech-savvy ones, such as, the millennials, may still have positive engagement with a Fintech company even if they do not care about the usability of products and services.
Competitiveness: Competitiveness connotes efficiency, agility, adaptability, technology, quality, productivity, and value creation [35,36]. Fintech may enhance the traditional- business process by reducing bank-operating expenses, making services more efficient, improving risk control, giving customers better customer-focused business models, and making banks more competitive overall [37,38]. Fintech breakthroughs are thus a crucial component of every service sector’s business strategy. Fintech innovations utilizing mobile technology, blockchain, and artificial intelligence are the key consideration for improving competitiveness across advanced customer services [39].
Perceived Value: Understanding perceived value can be connected to service quality and price [23]. The perceived value allows for a monetary evaluation of the benefit to consumers. The perceived value is higher when the customer experience is more meaningful [40]. A key driver of behavioral intentions to utilize banking services, particularly digital financial services, is the perceived value of those services [41]. Fintech’s accessibility allows customers to perform financial transactions anywhere and anytime. Technically savvy customers will adopt new technologies if they offer superior value [42].
Perceived Security: Customers’ perceptions of the system’s ability to carry out transactions safely are reflected in perceived security in finance [43]. Concerns about using Fintech have grown because of news about financial crimes committed with Fintech, making the use of Fintech seem volatile [44]. The perceptions of the transaction system’s security on the Fintech platform positively impact the adoption of Fintech [45]. Regarding online financial transactions, Martins et al. [46] found that users’ perceptions toward the payment system are significantly impacted by perceived risk, which in turn affects their propensity to utilize the service. Huei et al. [30] showed that perceived security negatively impacts customers’ opinions about Fintech products and services.
Usefulness: Usefulness is the degree to which an individual believes that using new technology will increase his or her job performance [47]. When users believe that new technology is beneficial, they will have a positive attitude toward it [48]. Ventre and Kolbe [49] state that the technology’s perceived usefulness heavily influences individuals’ intentions. Customers will feel that using Fintech services is a pleasant experience and be more ready to utilize them if they see positive comments. Moreover, when customers assume that utilizing Fintech services is valuable and advantageous, they will advocate it, impacting and enhancing other customers’ mindsets about using Fintech services [48].

2.2. Theoretical Framework and Hypothesis Development

2.2.1. Technology Acceptance Model (TAM)

Many studies have shown that user intentions are intricately related to adoption or behavior [50]. According to Davis [51], TAM could predict and explain user acceptance of information technology. Davis et al. [33] contended that external variables should be considered when establishing the drivers for the behavioral responses to technological features. Several researchers have combined TAM with extraneous factors and found it helpful to accurately forecast technology adoption across various technologies and settings, including information, software applications, and e-commerce. Additionally, TAM asserts that a person is more likely to embrace technology, service, or behavior if it improves his or her performance and is deemed beneficial [52,53]. Users may stick with Fintech services if they receive favorable reviews and have pleasant experiences. In this study, TAM was employed to describe how customers behave loyally toward Fintech services, benefiting from the service’s functionality through user experience. Therefore, the present study modifies TAM to explore the elements influencing customer-loyalty intention to Fintech services while making hotel payments. Table 1 summarizes prior studies that used TAM in the hospitality industry.

2.2.2. Fintech Services and Customer Experiences

Experiences may be characterized in terms of customers’ feelings and beliefs regarding what is happening when engaging in an activity. Previous research has revealed that a company’s interaction with its customers is impacted by the experience of their interaction [61]. Besides, the customer experience comprises the entire experience of products or services of a firm over time [62], encompassing the stages of search, purchase, consumption, and after-sale phases of the experience [63]. When customers make a purchase, they have an experience that may be good or bad, resulting in feelings of pleasure and sentiment toward the firm [64]. If the customer is satisfied, they are more likely to make another purchase, which should lead to a tangential benefit. In a similar essence, customer experience is contingent on the extent to which expected potential benefits are fulfilled [61,64]. In line with Verhoef et al. [65], the customer experience incorporates the consumer’s cognitive, affective, emotional, social, and physical responses into the business. However, customer experience is a holistic term that has been defined in several different ways. Consumer experience, particularly in an online environment, is conceptualized by Rose et al. [66] as two components, namely cognitive and affective [61].
Moreover, customer experience is co-created by the interactions of some elements. It is a present state in any individual responding to a stimulus. Specific stimuli elicit experiences as they develop as responses to single-touch points. Hence, perception and experience are crucial to value fortitude, and that value is always resolute by the recipient of service—in the exclusive experience of that usage [67,68,69,70]. Consequently, an individual’s overall assessment of an event (product or service) is theoretically diverse from the occasion and the feelings experienced [50]. Applying this perception to customer experience, an optimistic overall appraisal of the services (Fintech services) forms positive emotional reactions among customers. Firms should focus on improving connectivity and integration to give their customers a unified experience across channels. Fintech is customer-focused and may offer intuitive, user-friendly, and practical financial services [28]. By giving customers access to automated and optimized procedures, Fintech enhances the customer experience [71]. Thus, we propose:
H1. 
Fintech services directly influence customer experiences.
H2. 
Customer experiences mediate the Fintech services and loyalty-intention relationship.

2.2.3. Fintech Services and Customer Attitudes

According to the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB), consumer attitude is one of the critical components in purchase or usage intention [72]. Consumer attitudes are formed through the features of products or services provided by Fintech companies through their perceived usage facilities and proposition of values and risks. Accordingly, Fintech services only develop user attitudes while consumers assess the trade-offs of the advantages and securities. Customers’ positive attitudes toward utilizing Fintech services will increase if the Fintech services allow them to acquire important information on businesses or conduct transactions in real time, free of time and location constraints [30]. Fintech services that are easy to use, have social operating systems, and have application programs simple to download will influence customers’ attitudes toward utilizing such services [48]. Previous investigations found that Fintech services (e.g., ease of use and perceived usefulness of a system) significantly impact customer attitudes toward the system and suggest that individuals’ attitudes about technology will change if they perceive Fintech services to be helpful and user-friendly [30,48]. Accordingly, we propose the following hypotheses:
H3. 
Fintech services directly influence customer attitude.
H4. 
Customer attitude mediates Fintech services and loyalty-intention relationship.

2.2.4. Customer Experience and Customer Loyalty Intentions

Customer loyalty is one of the most intended consequences of any business-to-customer relationship. Businesses attempt to identify the ideal elements that will entice customers to return to gain loyalty [10]. A positive customer experience can result in increased organizational commitment, represented in customer loyalty [73]. Since customer experience positively impacts loyalty, the company benefits in various ways, involving improved trust, customer satisfaction, loyalty, repurchase, and positive word-of-mouth [10,74,75]. Equally, customer experiences form an emotional association, and thus, developing trust, antedates needs, and expanding retention that demonstrate a crucial role in drawing loyalty intentions [23]. A recent KPMG survey showed that customers were likely to be loyal due to product (or service) quality (74%), product consistency (quality, value, taste, etc.) (65%), customer service (56%), and shopping experience (55%) [76]. While positive experience builds loyalty intention, awful experience does not. Consequently, we suggest the following hypothesis:
H5. 
Customer experiences directly influence customer-loyalty intention.

2.2.5. Customer Attitude and Customer Loyalty Intention

Customer loyalty refers to how strongly a customer sticks with a business or service in terms of attitudes and behaviors, especially when there are alternatives available from other sources [77]. Customers who often make the same purchases or use the same services are valuable to established companies. A repeated purchaser affirms a more excellent average customer value, and thus drawing the imperative of customer loyalty [78,79]. Customer loyalty is so essential since it is less expensive to retain customers than to get new ones [80]. Thereby, the following hypothesis is developed:
H6. 
Customer attitudes directly influence customer-loyalty intention.

3. Methods

3.1. Sample and Population

To assess the hypotheses shown in Figure 1, a structured questionnaire was employed to collect data from customers of 3-, 4-, and 5-star hotels in Bangladesh’s two most renowned cities, i.e., Chattogram and Cox’s Bazar. Chattogram is the second biggest port city and Cox’s Bazar is Bangladesh’s most visited tourist destination. Between them, there are 22 hotels. The survey questionnaire was divided into two sections. The first section was the demographic section. It has four questions about gender, age group, educational qualification, and profession to develop the profile of the respondents. The second section had 28 questions separated into six segments: ease of use, competitiveness, perceived security, perceived value, usefulness, customer experience, customer attitude, and customer loyalty. Of the 22 hotels contacted, only 15 allowed the survey to be undertaken by their customers. Since the list of hotel customers was unavailable, Krejcie and Morgan’s [81] guideline was applied to determine the sample size. Accordingly, for an unknown population, 384 samples are enough to represent the entire population.

3.2. Measurement of Constructs

All items used to gauge the study variables were carefully chosen after thoroughly reviewing the literature. Fintech services were assessed using 16 items (three items for ease of use, four items for competitiveness, three items for perceived security, three items for perceived value, and three items for usefulness) adapted from [23,34,36,45] with minor adjustments made to them. A six-item unidimensional customer experience scale was adapted from [23] to measure customer experience. Molinillo et al. [54] and Rose et al. [59] also used these two dimensions to observe customer experience. The unidimensional scale was used since it gives a single factor in the factor analysis, as suggested by [82,83].
Besides, three items were selected to measure customer attitude from [34]. Lastly, three items from [84] were used to measure customer-loyalty intention. A five-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) was used to capture customer perceptions of the study constructs.

3.3. Data Collection Procedure

After contacting the managers of every hotel, the questionnaires were distributed to the targeted hotels by applying a convenience-sampling technique. Convenience sampling offered the flexibility to diversify our participants to capture various aspects of the sociocultural and socio-economic issues associated with the Fintech services and customer loyalty intention. Moreover, researchers prefer to use convenience-sampling techniques to obtain data from a conveniently available pool of participants.
A total of 530 questionnaires were circulated to the managers of the participating hotels. Managers were requested to distribute questionnaires to the hotel customers with a pencil and an open envelope with each questionnaire. The hotel managers, who agreed to participate willingly, conveniently distributed the survey to customers. We did not collect personal information to keep the respondents’ profiles anonymous. Customers were requested to close the envelope after filling out the survey for bias-free opinions. Only closed envelopes were accepted as valid responses. Data collection occurred between March and May 2022. After missing data and outliers were removed, 365 questionnaires were found to be usable, conceding a response rate of 68.87%. Such a response rate was considered good for social-sciences research.

3.4. Demographic Profile

Table 2 shows the demographic details of the survey respondents. The proportion of male (52.6%) and female respondents (47.4%) was almost equal. Nearly half of them were between 21 and 30 years old (45.2%). Single respondents were dominant (51.23%), with married respondents a distant second (39.73%). Most respondents had a college/diploma or higher education degree (84.7%). Regarding employment, 41.4% were students, followed by service holders (22.5%), self-employed (17.8%), and other categories (18.4%).

4. Analysis and Findings

4.1. Analyzing Tools

The opinions collected from customers were analyzed by PLS-SEM. This second-generation multivariate-data-analysis method can assess linear and additive causal models supported by a theory, in line with Chin [85]. According to Lowry and Gaskin [86], PLS-SEM is a reliable and flexible statistical approach for data analysis suitable for finding various relationship effects, including direct and indirect effects. PLS-SEM is more robust, valid, and trustworthy than covariance-based analysis, according to Ringle et al. [87]. PLS-SEM runs with a small sample size, non-normal data distribution, and minimal measurement-scale constraints [85].

4.2. Measurement Model

To verify the construct reliability of the measurement model, the composite reliability (CR) was tested. These criteria must be greater than 0.7. Additionally, to establish convergent validity, the average variance extracted (AVE) must be larger than 0.5. Convergent validity was established as the AVE values varied from 0.528 to 0.822, and the CR values ranged from 0.916 to 0.947 (see Table 3), exceeding the cut-off values of 0.5 and 0.7 [88]. Nevertheless, the data supported unidimensional Fintech service because factors analysis shows that all 5- dimensions’ items were highly correlated. Consequently, the unidimensional scale was used since it gave a single factor in the factor analysis see[82].
Moreover, the HTMT ratio should be less than either 0.85 or 0.9 to show discriminant validity [89]. Table 4 displays the HTMT findings for discriminant validity, suggesting that the model’s discriminant validity was established.

4.3. Structural Model

This study employed the bootstrap procedure using 5000 samples of a reflecting- measurement model to evaluate the hypotheses. We first calculated the variance inflation factor (VIF) to test multicollinearity. Table 5 shows that each predictor’s VIF value was below the threshold value of 3.0 as they varied from 2.207 to 2.805 [88], indicating that multicollinearity was unlikely to be a problem for this study. The findings of the structural- model evaluation and hypothesis testing are displayed in Table 5.
The result depicted that Fintech services had a significant effect on customer experience (β = 0.319; p < 0.01) and customer attitude (β = 0.711; p < 0.01). Hence, H1 and H2 were supported. Likewise, both customer experience (β = 0.134; p < 0.01) and attitude (β = 0.392; p < 0.01) significantly impacted customer-loyalty intention, supporting H5 and H6. In the mediation effects, both customer experience (β = 0.089; p < 0.01) and attitude (β = 0.279; p < 0.01) significantly mediated the Fintech services and customer loyalty intention relationship (H2 and H4). Regarding the mediating effects, the result showed that all direct hypotheses were supported, with partial mediation at p < 0.01. Partial mediation emerges when both direct and indirect effects are significant [90].

4.4. Fit Indices

Table 6 displays that the cross-validated redundancies or the Q2 values of endogenous variables (i.e., customer attitude, customer experience, and customer-loyalty intentions) were larger than zero, indicating that the model had predictive power [88]. Moreover, as per the study model, Fintech services had a large effect on both customer attitude (f2 = 1.022) and customer experience (f2 = 0.808) but a small effect on customer-loyalty intention (f2 = 0.111) (Cohen, 1988). Furthermore, the R2 values for customer attitude, customer experience, and customer-loyalty intention were 0.506, 0.447, and 0.587, respectively, which seemed to be high and appropriate for behavioural-science studies [88]. Overall, our model had moderate predictive power.

5. Discussion

In this study, we analyzed the relationships of Fintech services with customer-loyalty intention and the mediating influence of customer experience and attitude on such ties. The findings depicted that Fintech service was found to be a significant determining factor of customer experience (H1) and attitude towards using (H3) in the hotel sector of Bangladesh. The research findings imply that Fintech services provided by Bangladeshi hotels help increase their customers’ loyalty and offer a competitive advantage over competitors [91]. This finding is consistent with prior research, which illuminates a positive relationship between Fintech services and customer loyalty [23,48]. Fintech services that offer easy payment methods, highly secure data security, and privacy systems are more likely to gain user trust and keep consumers in the long run. Users may remain loyal to Fintech services if they receive positive feedback and a better experience. In addition, Fintech services have had an excellent opportunity to grow, retain a pleasant experience, and gain loyal customers. Hence, Fintech services will thrive in the future [53].
Moreover, both customer experience (H5) and attitude (H6) are positively associated with customer-loyalty intention. Prior studies such as Barbu et al. [23] also found a positive connection between customer experience and loyalty intentions. Consumer experience has a favorable impact on loyalty. The hotels that provide Fintech services to their customers make a payment and benefit in various ways, including increased trust, customer loyalty, commitment, and positive word-of-mouth [10,74,75]. A positive customer experience can result in increased commitment to the organization, which is reflected in customer loyalty [73,92]. Equally, Chuang et al. [48] found a positive association between users’ attitudes and their intentions to use Fintech services in Taiwan. Individual experience can shape a person’s attitude toward a certain thing, similar to a persistent desire, preference, or identity, and likely to result in loyalty. In other words, people’s attitudes toward information technology can impact their willingness to use it in the future [30].
Furthermore, the study’s finding reveals that both customer experience (H2) and attitude (H4) mediate the Fintech services and customer-loyalty intention relationship and also found them as a significant explanatory factor in mediating the Fintech service and customer-loyalty intention association. Earlier studies [23,30,48] did not contemplate the mediating role of customer experience and attitude in the relationship between Fintech services and customer-loyalty intention. Therefore, the current study fills the gap and adds value to the existing literature on Fintech services and loyalty intentions. The results would be valuable to researchers, Fintech operators, and hotel enterprises by recognizing and encouraging the adoption of Fintech goods and services in the hospitality sector of Bangladesh.

6. Conclusions

6.1. Theoretical Implications

To the researchers’ knowledge and existing evidence, this study is one of the few that explored customer-loyalty intention towards Fintech services in the hospitality industry in Bangladesh. Thus, this study adds value to the existing domain of Fintech literature in the global context, including Bangladesh. This study is different from other studies [13,16] because previous studies have been conducted in other sectors, such as banking. Besides, those studies looked at the benefits and costs of Fintech to provide the most up-to-date solutions for individuals and businesses. This is different from those studies because it combines TAM with extended variables, including ease of use, competitiveness, perceived security, perceived value, and usefulness, to evaluate customers’ loyalty intentions when paying for hotels [23,36].
None of the earlier research made an effort to investigate the causes of consumers’ loyalty intentions toward Fintech payment systems in the Bangladeshi hotel sector. Earlier scholarly outputs rarely examined the effects of these constructs on loyalty intention from using any technology or technology-enabled payment services. In this regard, the current study significantly contributes to the knowledge of Fintech-payment services. The suggested model, which connects the technology-acceptance model, extended technology-acceptance model, and service-science literature for evaluating loyalty intention, is unique because it establishes a link between these theoretical frameworks. The results specifically advance our understanding of how technology payment services may cultivate present clients into being devoted to Fintech services.
Second, understanding the various customer-centric attributes of Fintech services and their impact on customer loyalty is critical [54,55,56]. This study focused on how Fintech services generate customer loyalty for hospitality customers. To the best of the researchers’ knowledge, prior research did not consider the mediating effect of customer experience and attitude in the association between Fintech services and customer-loyalty intention. We tested these relationships by collecting opinions from customers of Bangladesh in the hospitality setting. Thus, findings contribute to the TAM model that the use of Fintech services is a significant predictor of customer attitude and experience; in turn, customers show loyalty to the companies. Explicitly, the existing investigation contributes a more profound comprehension of these mediating variables (customer experience and attitude) to the technology-acceptance model. Thus, the findings add value to the existing literature on technology-based Fintech payment services and customer-loyalty intention.

6.2. Managerial Implications

In terms of managerial implications, this study highlighted the critical areas that the Bangladeshi government and Fintech companies must evaluate and improve. Moreover, this research study recognized some practical implications and recommendations for Fintech businesses to provide effective Fintech services to create a reliable customer base in Bangladesh. The findings will assist managers in interconnecting with the consumers and allocating resources effectively to strike a balance between delivering new Fintech services to customers and maintaining profitability and investing in Fintech to keep existing customers. For example, to encourage more people to use Fintech products or services, the establishment and enhancement of information technology infrastructure should be prioritized. Nonetheless, policymakers may be prompted to enact applicable legislation (e.g., security, privacy) due to the drive to promote Fintech products and services among consumers.
Nevertheless, the execution of Fintech in the hospitality industry can only expand if it gives customers a prominent place in the firm’s business model. Fintech firms should develop an all-encompassing system to take a proactive approach to resolve potential customer issues and provide benefits to customers by fast communicating developments to their services. Businesses in Fintech must continue to invest in service security to avoid a surge in consumer risk perception and to secure crucial financial data and operations [69], which may aid in consumer security crises.
Our study identifies the components of the Fintech-payment services and outcomes of customer experience in Fintech, as well as demonstrates how Fintech businesses must integrate customer experience into their business models from a managerial standpoint. Moreover, from a management’s standpoint, the customer experience may be enhanced by strengthening and portraying a product or brand in an aesthetic way [23]. Firms strive to improve the purchase experience for clients and maximize their perceived value, and firms cannot fully control the customer experience but may affect it through stimuli [93]. Thus, businesses have understood that by adding value to their goods and services, demand will continually grow as the consumer experience is enhanced.

6.3. Research Limitations and Future Scope

This study has a few limitations that must be considered when evaluating the findings. First, the survey was conducted only in Chittagong and Cox’s Bazar. As we could not cover all districts, the results may not be generalizable to the whole population of hotel customers in Bangladesh. Future studies can cover all the divisions in Bangladesh by increasing the sample size. Furthermore, since a convenience-sample technique was utilized, affecting the accurate representation of the whole population, future studies may adopt other sampling techniques. Also, the present study explored only five features of Fintech services (i.e., ease of use, competitiveness, perceived security, perceived value, and usefulness). Future studies can explore other features and integrate them with new Fintech services. Lastly, we used only customer experience and attitude as mediator variables and did not utilize any moderator. In future studies, researchers can use a combination of mediating and moderating variables for an enhanced theoretical understanding.

Author Contributions

Finding gaps, writing literature, data collection, analysis, and writing contribution, R.A.K., N.J.L. & M.A.M.C.; Establishing the problem statement, formulating the hypotheses, and improving the organization of the paper, M.K.R.; Funding acquisition and Supervision, F.A.S. & M.R.K. All authors have read and agreed to the published version of the manuscript.

Funding

Funded by Institute for Advanced Research Publication Grant of United International University, Ref. No.: IAR-2022-Pub-038.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are available on demand.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mention, A.L. The Future of Fintech. Res. Technol. Manag. 2019, 62, 59–63. [Google Scholar] [CrossRef]
  2. Jin, C.C.; Seong, L.C.; Khin, A.A. Factors Affecting the Consumer Acceptance towards Fintech Products and Services in Malaysia. Int. J. Asian Soc. Sci. 2019, 9, 59–65. [Google Scholar] [CrossRef] [Green Version]
  3. Temelkov, Z. Financial technology companies as a positive disruptor for the hospitality industry. Sci. Refereed Online J. Impact Factor 2019, 54, 72–77. Available online: http://eprints.ugd.edu.mk/21561/ (accessed on 9 November 2022).
  4. Zhang, B.Z.; Baeck, P.; Ziegler, T.; Bone, J.; Garvey, K. Pushing Boundaries: The 2015 UK Alternative Finance Industry Report. 2016. Available online: https://ssrn.com/abstract=3621312 (accessed on 25 August 2022).
  5. Grèzes, V.; Emery, L.; Schegg, R.; Perruchoud, A. Crowdfunded tourism activities: Study on the direct impact of Swiss crowdfunding platforms on the tourism industry. In Proceedings of the Conference: Travel & Tourism Research Association, Innsbruck, Austria, 22–24 April 2015; pp. 1–10. [Google Scholar]
  6. Pollari, I.; Ruddenklau, A. Pulse of Fintech H2 2019. In Global Trends; KPMG International: Amstelveen, The Netherlands, 2020; p. 9. [Google Scholar]
  7. Gomber, P.; Kauffman, R.J.; Parker, C.; Weber, B.W. On the Fintech Revolution: Interpreting the Forces of Innovation, Disruption, and Transformation in Financial Services. J. Manag. Inf. Syst. 2018, 35, 220–265. [Google Scholar] [CrossRef]
  8. Bolton, R.N.; McColl-Kennedy, J.R.; Cheung, L.; Gallan, A.; Orsingher, C.; Witell, L.; Zaki, M. Customer experience challenges: Bringing together digital, physical and social realms. J. Serv. Manag. 2018, 29, 776–808. [Google Scholar] [CrossRef] [Green Version]
  9. Cetin, G. Experience vs. quality: Predicting satisfaction and loyalty in services. Serv. Ind. J. 2020, 40, 1167–1182. [Google Scholar] [CrossRef]
  10. Lemon, K.N.; Verhoef, P.C. Understanding customer experience throughout the customer journey. J. Mark. 2016, 80, 69–96. [Google Scholar] [CrossRef]
  11. Alam, M.M.D.; Karim, R.A.; Habiba, W. The relationship between CRM and customer loyalty: The moderating role of customer trust. Int. J. Bank Mark. 2021, 39, 1248–1272. [Google Scholar] [CrossRef]
  12. Al Karim, R.; Habiba, W. How CRM Components Impact Customer Loyalty: A Case from Bangladesh Banking Industry. J. Manag. Inf. 2020, 7, 43–61. [Google Scholar] [CrossRef]
  13. Khanam, M.J.J. Regulatory Challenges and Social Opportunities of Financial Inclusion through Fintech in Developing Countries with Reference to Bangladesh. September 2020. Available online: https://ritsumei.repo.nii.ac.jp/?action=repository_action_common_download&item_id=13918&item_no=1&attribute_id=20&file_no=1 (accessed on 29 August 2022).
  14. Rahman, B.; Ahmed, O.; Shakil, S. Fintech in Bangladesh: Ecosystem, Opportunities and Challenges. Int. J. Bus. Technopreneurship 2021, 11, 73–90. [Google Scholar]
  15. Rashid, H. Prospects of Digital Financial Services in Bangladesh in the Context of Fourth Industrial Revolution. Asian J. Soc. Sci. Leg. Stud. 2020, 2, 88–95. [Google Scholar]
  16. Ahmed, N.; Rony, R.J.; Khan, S.S.; Ahmed, M.S.; Sinha, A.; Saha, A.; Amir, S.; Abeer, I.A.; Sarcar, S. Resilience During COVID Pandemic: Role of Fintech in the Perspective of Bangladesh. 2022. Available online: https://ssrn.com/abstract=4009497 (accessed on 22 September 2022).
  17. Eickhoff, M.; Muntermann, J.; Weinrich, T. What do Fintechs actually do? A Taxonomy of Fintech Business Models. In Proceedings of the International Conference on Information Systems—Transforming Society with Digital Innovation, ICIS 2017, Seoul, Republic of Korea, 10–13 December 2017. [Google Scholar]
  18. Stulz, R.M. Fintech, BigTech, and the Future of Banks. J. Appl. Corp. Financ. 2019, 31, 86–97. [Google Scholar] [CrossRef]
  19. Kim, Y.; Park, Y.J.; Choi, J.; Yeon, J. An empirical study on the adoption of “Fintech” service: Focused on mobile payment services. Adv. Sci. Technol. Lett. 2015, 114, 136–140. [Google Scholar]
  20. Wang, M.; Chang, Y. Technology leadership, brand equity, and customer loyalty towards fintech service providers in China. In Proceedings of the Twenty-Fourth Americas Conference on Information Systems, New Orleans, LA, USA, 16–18 August 2018. [Google Scholar]
  21. Oshodin, O.; Molla, A.; Karanasios, S.; Ong, C.E. Is Fin tech a disruption or a new eco-system? An exploratory investigation of banks response to fintech in Australia. In Proceedings of the 28th Australasian Conference on Information Systems, Sydney, Australia, 3–6 December 2017. [Google Scholar]
  22. Gulamhuseinwala, I.; Bull, T.; Lewis, S. FinTech is gaining traction and young, high-income users are the early adopters. J. Financ. Perspect. 2015, 3, 16–23. [Google Scholar]
  23. Barbu, C.M.; Florea, D.L.; Dabija, D.C.; Barbu, M.C.R. Customer experience in fintech. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 1415–1433. [Google Scholar] [CrossRef]
  24. Moore, G.C.; Benbasat, I. Fintech Adoption: A Critical Appraisal of the Strategies of Paytm in India. IUP J. Manag. Res. 2020, 19, 7–17. [Google Scholar]
  25. Haqqi, F.R.; Suzianti, A. Exploring Risk and Benefit Factors Affecting User Adoption Intention of Fintech in Indonesia. In Proceedings of the 3rd Asia Pacific Conference on Research in Industrial and Systems Engineering, Depok, Indonesia, 16–17 June 2020; pp. 13–18. [Google Scholar]
  26. Ryu, H.S. What makes users willing or hesitant to use Fintech? The moderating effect of user type. Ind. Manag. Data Syst. 2018, 118, 541–569. [Google Scholar] [CrossRef]
  27. Nawayseh, M.K. Fintech in COVID-19 and beyond: What factors are affecting customers’ choice of Fintech applications? J. Open Innov. Technol. Mark. Complex. 2020, 6, 153. [Google Scholar] [CrossRef]
  28. Baber, H. Impact of Fintech on customer retention in Islamic banks of Malaysia. Int. J. Bus. Syst. Res. 2020, 14, 217–227. [Google Scholar] [CrossRef]
  29. Alkhazaleh, A.M.K.; Haddad, H. How does the Fintech services delivery affect customer satisfaction: A scenario of Jordanian banking sector. Strateg. Chang. 2021, 30, 405–413. [Google Scholar] [CrossRef]
  30. Huei, C.T.; Cheng, L.S.; Seong, L.C.; Khin, A.A.; Leh Bin, R.L. Preliminary study on consumer attitude towards Fintech products and services in malaysia. Int. J. Eng. Technol. (UAE) 2018, 7, 166–169. [Google Scholar] [CrossRef]
  31. Morgan, P.J.; Trinh, L.Q. Fintech and Financial Literacy in the Lao PDR. 2019. Available online: https://ssrn.com/abstract=3398235 (accessed on 8 October 2022).
  32. Doan, T.T.T. The Effect of Perceived Risk and Technology Self-Efficacy on Online Learning Intention: An Empirical Study in Vietnam. J. Asian Financ. Econ. Bus. 2021, 8, 385–393. [Google Scholar]
  33. Davis, F.D.; Bagozzi, R.P.; Warshaw, P.R. User acceptance of computer technology. J. Manag. Sci. 1989, 35, 982–1003. [Google Scholar]
  34. Setiawan, B.; Nugraha, D.P.; Irawan, A.; Nathan, R.J. User Innovativeness and Fintech Adoption in Indonesia. J. Open Innov. Technol. Mark. Complex. 2021, 7, 188. [Google Scholar] [CrossRef]
  35. Arulraj, D.J.; Annamalai, T.R. Firms’ Financing Choices and Firm Productivity: Evidence from an Emerging Economy. Int. J. Glob. Bus. Compet. 2020, 15, 35–48. [Google Scholar] [CrossRef]
  36. Dwivedi, P.; Ibrahim, J.; Rajeev, A. Role of Fintech Adoption for Competitiveness and Performance of the Bank: A Study of Banking Industry in UAE. Int. J. Glob. Bus. Compet. 2021, 16, 130–138. [Google Scholar] [CrossRef]
  37. Momaya, K.S. The Past and the Future of Competitiveness Research: A Review in an Emerging Context of Innovation and EMNEs. Int. J. Glob. Bus. Compet. 2019, 14, 1–10. [Google Scholar] [CrossRef] [Green Version]
  38. Wang, Y.; Xiuping, S.; Zhang, Q. Can fintech improve the efficiency of commercial banks? —An analysis based on big data. Res. Int. Bus. Financ. 2020, 55, 101338. [Google Scholar] [CrossRef]
  39. Momaya, K.S.; Pandey, P.; Vallaturu, V.K.; Sonar, R.M.; Bodduri, A.K.S. Fintech platforms, and competitiveness: Exploring role of MoT as a differentiator for firms of Indian origin (FIOs). In Proceedings of the 29th International Conference on Management of Technology, Cairo, Egypt, 13 September 2020. [Google Scholar]
  40. Cajetan, I.M.; Patrick, O.E. Digital Banking, Customer Experience and Bank Financial Performance: UK Customers’ Perceptions. Eletronic Libr. 2018, 34, 1–5. [Google Scholar]
  41. Garg, R.; Rahman, Z.; Qureshi, M.N. Measuring customer experience in banks: Scale development and validation. J. Model. Manag. 2014, 9, 87–117. [Google Scholar] [CrossRef]
  42. Shiau, W.-L.; Yuan, Y.; Pu, X.; Ray, S.; Chen, C.C. Understanding fintech continuance: Perspectives from self-efficacy and ECT-IS theories. Ind. Manag. Data Syst. 2020, 120, 1659–1689. [Google Scholar] [CrossRef]
  43. Lee, E.-Y.; Lee, S.-B.; Jeon, Y.J.J. Factors influencing the behavioral intention to use food delivery apps. Soc. Behav. Pers. Int. J. 2017, 45, 1461–1473. [Google Scholar] [CrossRef]
  44. Najib, M.; Fahma, F. Investigating the Adoption of Digital Payment System through an Extended Technology Acceptance Model: An Insight from the Indonesian Small and Medium Enterprises. Int. J. Adv. Sci. Eng. Inf. Technol. 2020, 10, 1702. [Google Scholar] [CrossRef]
  45. Najib, M.; Ermawati, W.; Fahma, F.; Endri, E.; Suhartanto, D. FinTech in the Small Food Business and Its Relation with Open Innovation. J. Open Innov. Technol. Mark. Complex. 2021, 7, 88. [Google Scholar] [CrossRef]
  46. Martins, C.; Oliveira, T.; Popovič, A. Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. Int. J. Inf. Manag. 2014, 34, 1–13. [Google Scholar] [CrossRef]
  47. Hu, Z.; Ding, S.; Li, S.; Chen, L.; Yang, S. Adoption Intention of Fintech Services for Bank Users: An Empirical Examination with an Extended Technology Acceptance Model. Symmetry 2019, 11, 340. [Google Scholar] [CrossRef] [Green Version]
  48. Chuang, L.-M.; Liu, C.-C.; Kao, H.-K. International Journal of Management and Administrative Sciences (IJMAS) The Adoption of Fintech Service: TAM perspective. Int. J. Manag. Adm. Sci. 2016, 3, 1–15. [Google Scholar]
  49. Ventre, I.; Kolbe, D. The Impact of Perceived Usefulness of Online Reviews, Trust and Perceived Risk on Online Purchase Intention in Emerging Markets: A Mexican Perspective. J. Int. Consum. Mark. 2020, 32, 287–299. [Google Scholar] [CrossRef]
  50. Suzianti, A.; Haqqi, F.R.; Fathia, S.N. Strategic recommendations for financial technology service development: A comprehensive risk-benefit IPA-Kano analysis. J. Model. Manag. 2021, 17, 1481–1503. [Google Scholar] [CrossRef]
  51. Davis, F.D. Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Q. 1989, 13, 319. [Google Scholar] [CrossRef]
  52. Sciarelli, M.; Prisco, A.; Gheith, M.H.; Muto, V. Factors affecting the adoption of blockchain technology in innovative Italian companies: An extended TAM approach. J. Strategy Manag. 2021, 15, 495–507. [Google Scholar] [CrossRef]
  53. Le, M.T.H. Examining factors that boost intention and loyalty to use Fintech post-COVID-19 lockdown as a new normal behavior. Heliyon 2021, 7, e07821. [Google Scholar] [CrossRef] [PubMed]
  54. Yang, H.; Song, H.; Cheung, C.; Guan, J. How to enhance hotel guests’ acceptance and experience of smart hotel technology: An examination of visiting intentions. Int. J. Hosp. Manag. 2021, 97, 103000. [Google Scholar] [CrossRef]
  55. Huang, Y.C.; Chang, L.L.; Yu, C.P.; Chen, J. Examining an extended technology acceptance model with experience construct on hotel consumers’ adoption of mobile applications. J. Hosp. Mark. Manag. 2019, 28, 957–980. [Google Scholar] [CrossRef]
  56. Hasni, M.J.S.; Farah, M.F.; Adeel, I. The technology acceptance model revisited: Empirical evidence from the tourism industry in Pakistan. J. Tour. Futures, 2021; ahead-of-print. [Google Scholar]
  57. Singh, S.; Srivastava, P. Social media for outbound leisure travel: A framework based on technology acceptance model (TAM). J. Tour. Futures 2019, 5, 43–61. [Google Scholar] [CrossRef]
  58. Lew, S.; Tan, G.W.-H.; Loh, X.-M.; Hew, J.-J.; Ooi, K.-B. The disruptive mobile wallet in the hospitality industry: An extended mobile technology acceptance model. Technol. Soc. 2020, 63, 101430. [Google Scholar] [CrossRef] [PubMed]
  59. Bae, S.Y.; Han, J.H. Considering cultural consonance in trustworthiness of online hotel reviews among generation Y for sustainable tourism: An extended TAM model. Sustainability 2020, 12, 2942. [Google Scholar] [CrossRef]
  60. Jung, J.; Park, E.; Moon, J.; Lee, W.S. Exploration of sharing accommodation platform airbnb using an extended technology acceptance model. Sustainability 2021, 13, 1185. [Google Scholar] [CrossRef]
  61. Molinillo, S.; Navarro-García, A.; Anaya-Sánchez, R.; Japutra, A. The impact of affective and cognitive app experiences on loyalty towards retailers. J. Retail. Consum. Serv. 2020, 54, 101948. [Google Scholar] [CrossRef]
  62. Karim, R.A.; Islam, M.W. Assessing customer demand and customer satisfaction through social and environmental practices in the hotel sector of Bangladesh. GeoJournal Tour. Geosites 2020, 30, 843–851. [Google Scholar] [CrossRef]
  63. Van Thiel, D.; Van Raaij, F. Explaining customer experience of digital financial advice. Economics 2017, 5, 69–84. [Google Scholar]
  64. Moliner-Tena, M.A.; Monferrer-Tirado, D.; Estrada-Guillén, M. Customer engagement, non-transactional behaviors and experience in services: A study in the bank sector. Int. J. Bank Mark. 2019, 37, 730–754. [Google Scholar] [CrossRef]
  65. Verhoef, P.C.; Lemon, K.N.; Parasuraman, A.; Roggeveen, A.; Tsiros, M.; Schlesinger, L.A. Customer experience creation: Determinants, dynamics and management strategies. J. Retail. 2009, 85, 31–41. [Google Scholar] [CrossRef] [Green Version]
  66. Rose, S.; Clark, M.; Samouel, P.; Hair, N. Online customer experience in e-retailing: An empirical model of antecedents and outcomes. J. Retail. 2012, 88, 308–322. [Google Scholar] [CrossRef]
  67. Vargo, S.L.; Lusch, R.F. Service-dominant logic: Continuing the evolution. J. Acad. Mark. Sci. 2008, 36, 1–10. [Google Scholar] [CrossRef]
  68. Brakus, J.J.; Schmitt, B.H.; Zarantonello, L. Brand Experience: What is It? How is it Measured? Does it Affect Loyalty? J. Mark. 2009, 73, 52–68. [Google Scholar] [CrossRef]
  69. De Keyser, A.; Lemon, K.N.; Klaus, P.; Keiningham, T.L. A framework for understanding and managing the customer experience. Mark. Sci. Inst. Work. Pap. Ser. 2015, 85, 15–121. [Google Scholar]
  70. Homburg, C.; Jozić, D.; Kuehnl, C. Customer experience management: Toward implementing an evolving marketing concept. J. Acad. Mark. Sci. 2017, 45, 377–401. [Google Scholar] [CrossRef]
  71. Turlais, V. Business Scenario Planning for Declining Industry. J. Bus. Manag. 2016, 11, 14. [Google Scholar]
  72. Ajzen, I. The Theory of Planned Behavior. Organ. Behav. Hum. Decis. Process. 1991, 50, 179–211. [Google Scholar] [CrossRef]
  73. Khan, I.; Fatma, M.; Kumar, V.; Amoroso, S. Do experience and engagement matter to millennial consumers? Mark. Intell. Plan. 2021, 39, 329–341. [Google Scholar] [CrossRef]
  74. Becker, L.; Jaakkola, E. Customer experience: Fundamental premises and implications for research. J. Acad. Mark. Sci. 2020, 48, 630–648. [Google Scholar] [CrossRef] [Green Version]
  75. Bleier, A.; Harmeling, C.M.; Palmatier, R.W. Creating Effective Online Customer Experiences. J. Mark. 2018, 83, 98–119. [Google Scholar] [CrossRef]
  76. KPMG. The Truth About Customer Loyalty. 2019. Available online: https://assets.kpmg/content/dam/kpmg/xx/pdf/2019/11/customer-loyalty-report.pdf (accessed on 8 October 2022).
  77. Fornell, C. A National Customer Satisfaction Barometer: The Swedish Experience. J. Mark. 1992, 56, 6–21. [Google Scholar] [CrossRef]
  78. Jenneboer, L.; Herrando, C.; Constantinides, E. The Impact of Chatbots on Customer Loyalty: A Systematic Literature Review. J. Theor. Appl. Electron. Commer. Res. 2022, 17, 212–229. [Google Scholar] [CrossRef]
  79. Brandtzaeg, P.B.; Følstad, A. Why People Use Chatbots. In Internet Science; INSCI 2017; Springer: Cham, Switzerland, 2017; pp. 377–392. [Google Scholar]
  80. Herrmann, A.; Xia, L.; Monroe, K.B.; Huber, F. The influence of price fairness on customer satisfaction: An empirical test in the context of automobile purchases. J. Prod. Brand Manag. 2007, 16, 49–58. [Google Scholar] [CrossRef]
  81. Krejcie, R.; Morgan, S. Sample size determination. Bus. Res. Methods 1970, 4, 34–36. [Google Scholar]
  82. Floyd, F.J.; Widaman, K.F. Factor analysis in the development and refinement of clinical assessment instruments. Psychol. Assess. 1995, 7, 286–299. [Google Scholar] [CrossRef]
  83. Rabiul, M.K.; Shamsudin, F.M.; Yean, T.F.; Patwary, A.K. Linking leadership styles to communication competency and work engagement: Evidence from the hotel industry. J. Hosp. Tour. Insights 2022, in press. [CrossRef]
  84. Parasuraman, A.; Zeithaml, V.A.; Malhotra, A. ES-QUAL: A multiple-item scale for assessing electronic service quality. J. Serv. Res. 2005, 7, 213–233. [Google Scholar] [CrossRef] [Green Version]
  85. Ringle, C.M.; Sarstedt, M.; Straub, D.W. Editor’s comments: A critical look at the use of PLS-SEM in “MIS Quarterly”. MIS Q. 2012, 36, iii–xiv. [Google Scholar] [CrossRef] [Green Version]
  86. Lowry, P.B.; Gaskin, J. Partial least squares (PLS) structural equation modeling (SEM) for building and testing behavioral causal theory: When to choose it and how to use it. IEEE Trans. Prof. Commun. 2014, 57, 123–146. [Google Scholar] [CrossRef]
  87. Chin, W.W. How to Write Up and Report Pls Analyses; Springer: London, UK, 2010. [Google Scholar]
  88. Hair, J.F.; Howard, M.C.; Nitzl, C. Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. J. Bus. Res. 2020, 109, 101–110. [Google Scholar] [CrossRef]
  89. Henseler, J.; Hubona, G.; Ray, P.A. Using PLS path modeling in new technology research: Updated guidelines. Ind. Manag. Data Syst. 2016, 116, 2–20. [Google Scholar] [CrossRef]
  90. Nitzl, C.; Roldán Salgueiro, J.L.; Cepeda-Carrión, G. Mediation analysis in partial least squares path modeling: Helping researchers discuss more sophisticated models. Ind. Manag. Data Syst. 2016, 116, 1849–1864. [Google Scholar] [CrossRef]
  91. Hoe, L.C.; Mansori, S. The Effects of Product Quality on Customer Satisfaction and Loyalty: Evidence from Malaysian Engineering Industry. Int. J. Ind. Mark. 2018, 3, 20. [Google Scholar] [CrossRef] [Green Version]
  92. Keiningham, T.; Ball, J.; Benoit, S.; Bruce, H.L.; Buoye, A.; Dzenkovska, J.; Nasr, L.; Ou, Y.C.; Zaki, M. The interplay of customer experience and commitment. J. Serv. Mark. 2017, 9, 1–72. [Google Scholar] [CrossRef]
  93. Kranzbühler, A.M.; Kleijnen, M.H.; Morgan, R.E.; Teerling, M. The multilevel nature of customer experience research: An integrative review and research agenda. Int. J. Manag. Rev. 2018, 20, 433–456. [Google Scholar] [CrossRef]
Figure 1. Theoretical framework of this study.
Figure 1. Theoretical framework of this study.
Sustainability 14 16481 g001
Table 1. Summary of Previous Studies Used TAM in the Hospitality Sector.
Table 1. Summary of Previous Studies Used TAM in the Hospitality Sector.
Author(s)VariablesFindings
Yang et al. [54]Perceived ease of use; perceived usefulness; technology readiness; technology amenities;
visiting intentions
(1) Perceived ease of use and perceived usefulness are correlated with technology amenities but not with technology readiness.
(2) Technology readiness affects intentions to visit smart hotels, but technology amenities do not.
Huang et al. [55]Perceived ease of use; perceived usefulness; consumers’ experiences; behavioral intention(1) Perceived ease of use and perceived usefulness have positive impacts on hotel consumers’ experiences of mobile apps,
(2) Perceived usefulness and user experience influence hotel apps acceptance by customers.
Hasni et al. [56]Perceived ease of use; perceived usefulness; behavioural intentionThe findings reveal that the perceived usefulness and perceived ease of use of a social-media platform positively impact the behavioral intention
Singh and Srivastava [57]Perceived usefulness; perceived ease of use; perceived trust; social capital.TAM model validated though perceived usefulness and perceived ease of use as determinants of SM usage.
Lew et al. [58]Technology self-efficacy; perceived critical mass, usefulness, ease of use, mobile self-efficacy, perceived enjoyment; behavioral intentionMobile ease of use, usefulness, self-efficacy, and perceived enjoyment are positively correlated to behavioral intention
Bae and Han [59]Cultural consonance; perceived ease of use; Perceived usefulness; attitude towards websites; intention to use the website(1) An agreed-upon cultural model of trustworthiness of online hotel reviews exists among sample members.
(2) Cultural consonance of trustworthiness and perceived ease of use and attitude towards websites were correlated.
Jung et al. [60]Network externalities; trust; interactivity; ease of use; usefulness; intention to repurchase.(1) Network externalities are essential to account for trust and interactivity; interactivity is an influential element to both ease of use and usefulness.
Table 2. Sample characteristics (n = 365).
Table 2. Sample characteristics (n = 365).
DemographicCategoriesFrequencyPercent
GenderMale19252.6
Female17347.4
Age Group21–30 Years16545.2
31–40 Years11130.4
41–50 Years4311.8
Above 50 Years4612.6
Marital StatusSingle18751.23
Married14539.73
Separated/divorced339.04
EducationHSC/Diploma6317.3
Graduation15943.6
Post-graduation8723.8
Others5615.3
ProfessionSelf-employed6517.8
Service Holder8222.5
Student15141.4
Others6718.4
Table 3. Construct Reliability and Validity, and Items.
Table 3. Construct Reliability and Validity, and Items.
Fintech Based Services [α = 0.940, CR = 0.947, AVE = 0.528]FL
EOU1: It is easy to use Fintech services.0.693
EOU2: I think the operation interface of Fintech is friendly and understandable0.651
EOU3: It is easy to have device to use Fintech services0.747
COM1: Fintech services reduce the expense of financial transactions and services.0.725
COM2: Fintech services help to improve the services quality.0.666
COM3: Fintech services save my time.0.809
COM4: Fintech services increase flexibility.0.765
PRS1: I feel Fintech services are a secure system.0.715
PRS2: Providing information while using Fintech services feels secure to me.0.661
PRS3: I am not worried about data/information security while using Fintech services.0.766
PRV1: I can save my money using Fintech services.0.617
PRV2: For the given price, I rate Fintech services as a good offer.0.707
PRV3: I consider Fintech services to be a good purchase.0.773
USE1: Fintech services have the ability to meet my need.0.774
USE2: I can save a lot of time using Fintech services.0.752
USE3: Fintech services increase my efficiency.0.778
Customer experience [α = 0.891, CR = 0.916, AVE = 0.646]
CEX1: Information attained from Fintech based service is useful.0.726
CEX2: Information gained from Fintech based service brings interesting ideas to mind.0.872
CEX3: I learned a lot from using Fintech based service.0.749
CEX4: I feel optimistic using Fintech based service.0.825
CEX5: I feel good using Fintech based service.0.777
CEX6: I feel enthusiastic using Fintech based service.0.862
Customer Attitude [α = 0.892, CR = 0.933, AVE = 0.822]
CAT1: In my opinion using Fintech based service is a worthy idea.0.908
CAT2: I believe using Fintech based service provides pleasant experience.0.919
CAT 3: I am inquisitive towards Fintech based service.0.893
Customer Loyalty Intentions [α = 0.867, CR = 0.919, AVE = 0.790]
CLI1: I will share positive things regarding Fintech based service to other individuals.0.885
CLI2: I will definitely recommend Fintech based service to other individuals.0.906
CLI3: I will definitely continue using Fintech based service.0.875
Note: Fl = factor loading; CR = composite reliability; AVE = average variance extracted.
Table 4. Discriminant Validity (HTMT Ratio).
Table 4. Discriminant Validity (HTMT Ratio).
ATUCECLIFS
ATU
CE0.819
CLI0.8160.698
FS0.7570.6810.740
Notes: FS = Fintech Services; CE = Customer Experience; ATU = Customer Attitude; CLI = Customer Loyalty Intention.
Table 5. Summary of Hypothesis Results (Direct and Indirect Relationships).
Table 5. Summary of Hypothesis Results (Direct and Indirect Relationships).
Hypothesis PathBetat-Valuesp-ValuesDecisionVIF (<3.0)
Direct Hypotheses
H1Fintech services → customer experience0.66926.2370.000Supported2.805
H3Fintech services → customer attitude0.71127.0050.000Supported2.508
H5Customer experience → customer loyalty intention0.1342.6320.004Supported2.207
H6Customer attitude → customer loyalty intention0.3925.4660.000Supported
Mediation Hypotheses
H2Fintech services→ customer experience → customer loyalty intention0.0892.6080.005Supported
H4Fintech services→ customer attitude→ customer loyalty intention0.2795.3170.000Supported
Table 6. Model Quality.
Table 6. Model Quality.
ConstructR Square (R2)Effects Size (f2)Predictive Relevance (Q2)
Customer attitude0.506 (M)1.022 (L)0.412
Customer experience0.447 (M)0.808 (L)0.259
Customer-loyalty intension0.587 (M)0.111(S)0.459
Notes: L = large; M = moderate; S = small.
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MDPI and ACS Style

Karim, R.A.; Sobhani, F.A.; Rabiul, M.K.; Lepee, N.J.; Kabir, M.R.; Chowdhury, M.A.M. Linking Fintech Payment Services and Customer Loyalty Intention in the Hospitality Industry: The Mediating Role of Customer Experience and Attitude. Sustainability 2022, 14, 16481. https://doi.org/10.3390/su142416481

AMA Style

Karim RA, Sobhani FA, Rabiul MK, Lepee NJ, Kabir MR, Chowdhury MAM. Linking Fintech Payment Services and Customer Loyalty Intention in the Hospitality Industry: The Mediating Role of Customer Experience and Attitude. Sustainability. 2022; 14(24):16481. https://doi.org/10.3390/su142416481

Chicago/Turabian Style

Karim, Rashed Al, Farid Ahammad Sobhani, Md Karim Rabiul, Nusrat Jahan Lepee, Mohammad Rokibul Kabir, and Mohammad Abdul Matin Chowdhury. 2022. "Linking Fintech Payment Services and Customer Loyalty Intention in the Hospitality Industry: The Mediating Role of Customer Experience and Attitude" Sustainability 14, no. 24: 16481. https://doi.org/10.3390/su142416481

APA Style

Karim, R. A., Sobhani, F. A., Rabiul, M. K., Lepee, N. J., Kabir, M. R., & Chowdhury, M. A. M. (2022). Linking Fintech Payment Services and Customer Loyalty Intention in the Hospitality Industry: The Mediating Role of Customer Experience and Attitude. Sustainability, 14(24), 16481. https://doi.org/10.3390/su142416481

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