Fostering customer revisit to upscale hotels through hotel marketing mix: the mediating role of satisfaction and the moderating role of social influence

Revisit intention is a noteworthy aspect of business accomplishment in the hospitality industry, influencing visitors' opinions on revisiting the exact location (Rasoolimanesh, Iranmanesh, Seyfi, Ari Ragavan, & Jaafar, 2023; Chen, Cheng, & Kim, 2020). In the hospitality industry, revisit intention is crucial for generating customer loyalty and encouraging repeat visits, which in turn fosters continuous financial growth (Chen et al., 2020; Elgarhy & Mohamed, 2023; Chen & Chen, 2010). Hotels can establish enduring customer relationships that result in positive word-of-mouth recommendations through social influence by emphasising enhanced revisit intention (Wang, Vo-Thanh, Gursoy, Dang-Van, & Nguyen, 2024). The potential to increase customers' desire to return is a potential benefit of revisiting a particular location. Hence, the marketing mix has a significant influence on visitors' intentions to return, driven by satisfaction (Watjanasoontorn, Viriyasuebphong, & Voraseyanont, 2019; Elgarhy & Mohamed, 2023). Moreover, positive word-of-mouth encourages visitors to visit locations. Social influence increases the number of hotel visitors and the likelihood of previous customers returning (Wang et al., 2024). Accordingly, hoteliers typically provide a variety of incentives and discounts, as well as coupons and promotions, to foster long-term relationships with tourists through their repeat business. Thus, revisiting intention is essential for developing loyal consumers and attaining sustainable business success (Chen & Yuan, 2020).

In addition, for attaining sustainable business performance, the hotel marketing mix plays a crucial role in the hospitality industry for maintaining or strengthening market position, as its primary goal is to persuade local and international customers to purchase and use the company's goods and services (Kwok, Tang, & Yu, 2020; Praesri, Meekun, Lee, & Hyun, 2022; Kotler, Makens, Bowen, & Baloglu, 2018; Karim, 2015). The hotel marketing mix helps retain current customers while attracting as many new guests as possible (Elgarhy & Mohamed, 2023). For any organisation, the marketing mix aims to attract and satisfy customers, promote the business, differentiate it from competitors, and create brand awareness (Karim, Jahan, Jebunnesa, & Lepee, 2023). The marketing mix in hospitality-based businesses enhances financial execution and competitive advantages, enabling short-term and long-term capability development (Tay, Chan, & Mohamad, 2023; Blut, Teller, & Floh, 2018). Additionally, in the competitive business environment of the hospitality industry, understanding the customer's purchasing decision process, as well as their desire to repurchase or revisit, is a prerequisite for acquiring market share and is an essential aspect in making policy suggestions (Kim, Lee, & Kim, 2020).

Over the years, research has been conducted on hotel marketing mix and revisit intention in developed and developing nations. Nevertheless, there is a shortage of empirical research in Bangladesh that integrates the marketing mix (product, price, location, and promotion) with the “Theory of Planned Behaviour” (TPB) to elucidate customer revisit intentions in the hospitality industry. Notably, most of the marketing mix-related investigations were based on other sectors, such as banking (Hossain et al., 2020), ready-made garments (Karim et al., 2023), dairy firms (Farid et al., 2023), tourism destinations (Hasan, Mim, Hossaın, & Khan, 2023; Pramanik & Rakib, 2020; Sarker & Begum, 2015), and dining restaurants (Mannan, Chowdhury, Sarker, & Amir, 2019). Studies have barely been conducted on how the hotel marketing mix individually affects guests' satisfaction and revisit intentions in Bangladesh's hotel industry setting. In addition, the existing study is one of the few to investigate how satisfaction fosters visitors' revisit intention as a mediator, and the role social influence can play in moderating it. Notably, few studies have examined social influence as a moderating variable in the association between satisfaction and revisit intention in the hospitality industry context. Consequently, it offers the following questions:

1. How does satisfaction mediate the relationship between the hotel marketing mix and revisit intention?

2. Does social influence moderate the relationship between satisfaction and revisit intention?

This study used Ajzen's (1991) “Theory of Planned Behaviour (TPB)” as the theoretical basis. According to TPB, a person's attitude, subjective norms, and perceived behavioural controls significantly influence their actual behaviour and willingness to exert effort in particular actions. In this study, the marketing mix influences how people perceive the hotel, leading to satisfaction, which then encourages positive attitudes toward revisit intention. Subjective norms are the social pressures that people feel to do or not do a certain behaviour and affect visitors' decisions about whether or not to go back to a hotel based on the social pressure they feel from family and friends, online reviews, and social media. Perceived behavioural control affects how feasible and manageable a visitor thinks it is to return, which in turn affects revisit behaviour. People who feel in control of a situation are more likely to desire to go back and repeat it (Ajzen, 1991; Yeh, Guan, Chiang, Ho, & Huan, 2021).

The study is noteworthy as the outcomes assist the hotel practitioners in understanding the impact of various marketing mix components, including pricing policies, advertising campaigns, and distribution channels, on customer satisfaction and visitors' intentions to return in the context of the Bangladeshi hospitality industry. By identifying the efficient marketing mix strategy that impacts visitor satisfaction, social influence, and return intent, hotel managers can make informed decisions about marketing strategies, resource allocation, and service enhancements in the hospitality industry of Bangladesh.

Satisfaction refers to a customer's emotional response to the discrepancy between their expectations and the actual outcomes achieved in meeting their needs, goals, or desires (Kim & Kim, 2022). Customer satisfaction is crucial for a business's success, influencing future purchases (Rajput & Gahfoor, 2020), and is a vital metric for assessing a hotel's long-term performance and product quality. It demonstrates how successfully a firm satisfies customer expectations and is essential to the hotel service mix. In such a setting, to attract customers and boost their satisfaction with their location, product, or service, the marketing mix is the primary strategy employed by hotels to create a positive attitude toward the hotel, according to TPB. Kwok et al.'s (2020) study suggests that understanding the influence of hotel marketing mix components on visitor satisfaction can help hospitality companies optimise satisfaction and profitability. The hotel sector provides various marketing mix facilities to observe travellers' demands and expectations (Quang, 2017). According to Elgarhy and Mohamed (2023), service providers must understand the components of the marketing mix to attract customers, primarily through their purchasing behaviors and closely linked to customer satisfaction.

In the hospitality industry, a product or service refers to any item that service providers offer to satisfy the customer's requirements or desires (Armstrong & Kotler, 2006). Any hotel can only provide high-quality products if it can identify client needs and develop products or services to meet them (Xie, 2020). Hotel rooms are products sold to customers, varying in quality, size, price, branding, and design, encompassing all aspects of the product or service (Sudari, Tarofder, Khatibi, & Tham, 2019). Hoteliers should improve product quality to satisfy the demands of visitors since research demonstrates a favourable association between product quality and satisfaction (Elgarhy & Mohamed, 2023).

Price, as defined by Praesri et al. (2022), is the monetary value a tourist pays for a service or product. As highlighted by Elgarhy and Mohamed (2023), the influence of marketing efforts is a decisive factor in determining pricing. The openness and reliability of digital marketing enable customers to compare pricing with competing products. The survival of an organisation in the hospitality industry is guaranteed by the pricing of services, which is also influenced by customer purchasing power, service costs, service quality, and specific sectors catering to visitors (Al-Debi & Ashraf, 2014; Kim & Hyun, 2011).

Equally, hotels strive to find the most convenient location for travellers, as a well-located hotel attracts customers and generates more revenue (Yin, Fang, & Cheng, 2022). Tourists prioritise the location of their destination and hotel when visiting scenic locations, as personal emotions, perceptions, and aesthetics significantly influence their satisfaction with the area. Hotels must be positioned near tourist attractions to satisfy customers since a good location hotel facilitates business meetings, sociability, and participation in leisure activities (Xie, 2020). Scholars (Quang, 2017; Sudari et al., 2019) discovered a substantial positive association between location and tourist satisfaction.

Promotion is a marketing strategy utilised by marketers to reach target audiences, provide accurate product information, convince them, enhance advertising efficiency, segment audiences, improve communication, and inform customers about products (Kim & Hyun, 2011; Kadhim, Abdullah, & Abdullah, 2016). Marketers develop various websites and social media platforms (e.g. Twitter, Instagram, Facebook) to advertise their hotels. Promotion seeks to increase recognition, sales, and trust in the brand (Yin et al., 2022). Hotel promotion considerably influences tourist satisfaction since it identifies the industry's target market, attracts new visitors, and expands loyalty, all while acknowledging customer experiences and distinguishing the firm from rivals (Quang, 2017). In line TPB, these interconnected marketing mix components help to shape customers' positive attitudes through adequate services that satisfy tourists, which are crucial for hotels to retain business and to ensure successful marketing strategy. Considering the preceding discussion, we propose:

According to Rajput and Gahfoor (2020), tourist satisfaction measures the degree to which tourists are satisfied with the firm's services and offerings. One of the most important variables influencing a visitor's future purchase intentions is their level of satisfaction (Khoo, 2020). In the hotel business, satisfaction can help create reputations, develop a favourable brand image, and promote growth and stability among travellers (Clemes, Gan, & Ren, 2011; Karim & Islam, 2020; Karim & Fayez, 2020). On the other side, tourists who visit a place repeatedly are considered to have revisit intention (Alkhozaim, Gull, Bashir, Alshiha, & Alnasser, 2025). Revisit intention is also described as the likelihood of an individual returning to a particular place or destination (Wu, Li, & Li, 2018). Visitors' decision to return is heavily influenced by their satisfaction; hotel repurchase, also known as hotel revisit, seeks to entice customers to return for positive experiences and suggest the exact location/hotel to others (Gholipour Soleimani & Einolahzadeh, 2018; Wu, Ai, Yang, & Li, 2015, 2018). Kim and Kim (2022) state that excellent customer satisfaction leads to enhanced customer retention, higher lifetime value, and a better brand reputation. While tourists derive greater satisfaction from purchasing a product or service, they are inclined to repeat the purchasing process for the same item or service (Rajput & Gahfoor, 2020). Studies have shown a significant correlation between visitor satisfaction and future visits, with higher satisfaction levels indicating a higher likelihood of future visits (Rasoolimanesh et al., 2023). Dissatisfaction with hotel products or services with staying experiences reduces returns and referrals to a hotel (Kim, Kim, & Kim, 2009), while research shows a positive correlation between increased satisfaction and higher return visitation rates (Hussein, 2020; Chen & Chen, 2010; Gholipour Soleimani & Einolahzadeh, 2018). Hence, we hypothesise that:

The hotel marketing mix plays a crucial role in determining the likelihood of visitors returning, as it effectively communicates the overall guest experience (Yin et al., 2022). A comprehensive marketing mix implementation strategy can potentially motivate customers to be involved in subsequent purchases (Mannan et al., 2019; Lahtinen, Dietrich, & Rundle-Thiele, 2020; Watjanasoontorn et al., 2019). Hotels can create a memorable and gratifying guest experience that encourages visitors to return by strategically positioning the components of the marketing mix—product, location, price, and promotion (Kotler et al., 2018).

When developing hospitality products, it is essential to consider the diverse range of requirements and interests of visitors, including those who prefer to stay within their comfort zones and those who enjoy extended excursions (Yin et al., 2022). The price represents the monetary value exchanged for the service, encouraging tourists to view the hotel as an excellent purchase and increasing their likelihood of returning (Ranjbarian & Pool, 2015). Price is a critical factor in establishing and maintaining long-lasting relationships between tourists and service distributors, as tourists frequently assess the utmost value for their money, which is closely associated with customer satisfaction and hotel revenue (Clemes et al., 2011; Al-Debi & Ashraf, 2014; Kadhim et al., 2016; Sudari et al., 2019). The location is essential when choosing a hotel because guests' journeys are often scheduled depending on their location. Hotels near tourist attractions should be easily accessible by car, provide clear instructions, offer safe and pleasurable facilities, and create an environment that encourages repeat visits from tourists (Ranjbarian & Pool, 2015; Yin et al., 2022).

Promotion creates programs that influence travellers' desire to return by increasing awareness and loyalty to the hotel brand. Hotel marketers utilise many websites to promote their services (Yin et al., 2022). Hotels that utilise an organised hotel marketing mix can differentiate themselves from competitors and enhance the value of their products to travellers, thereby increasing the likelihood of repeat visits. To encourage repeat visits, hoteliers offer numerous benefits to their loyal customers (Gholipour Soleimani & Einolahzadeh, 2018). They frequently offer loyal consumers numerous incentives, price discounts, awards, upgrades, and surprises to foster long-term relationships with them (Watjanasoontorn et al., 2019). As a result, if customers are delighted with the hotel's marketing mix offerings, they have a higher probability of returning (Yin et al., 2022). Thus, the proposed hypotheses are:

Following Choo, Ahn, and Petrick (2019), visitors' future purchase and revisit intentions for any product, service, or location are significantly influenced by satisfaction. Tourist satisfaction serves as a crucial link between the hotel marketing mix and revisit intention, as it encompasses the overall visitor experience and influences whether tourists will return to the hotel in the future (Khoo, 2020; Wantara & Prasetyo, 2023). Hotel marketing mix elements, such as product, location, price, and promotion, directly impact tourist satisfaction, increasing visitor retention and the likelihood of returning when expectations are met during their stay (Watjanasoontorn et al., 2019). Since the hospitality industry intensifies its competition, the need for effective marketing strategies that influence visitor satisfaction and return intention becomes more urgent. In keeping with TPB, successful marketing mix execution generates favourable memories and positive attitudes towards the hotel, influencing visitor satisfaction and the inclination to return (Kim et al., 2009; Mannan et al., 2019). Yin et al. (2022) found that the marketing mix and visitor satisfaction have a substantial impact on return intention.

Hotels can enhance their marketing mix by identifying areas that require improvement and implementing the requisite modifications to improve visitor satisfaction. They can also encourage repeat visits by assessing their satisfaction through feedback (Kim & Kim, 2022). Hotels can even create customised experiences on the hotel marketing mix that enhance visitor satisfaction and shape a positive attitude, thereby increasing the probability of their return, consistent with TPB. By thoroughly understanding the hotel marketing mix, hoteliers can indirectly encourage visitors to return by identifying the requirements of their target market (Hussein, 2020; Kim et al., 2020). Accordingly, the offered hypotheses are:

Social influence refers to the impact of individuals, groups, and society on a person's thoughts, feelings, and actions (Lee-Anant, 2025; Wang et al., 2024). It influences behaviour and actions to align with significant social groups (Spears, 2021). In proportion to TPB, social influence significantly guides customers' perceptions, feelings, and behavioural responses toward a hospitality company, making it a crucial factor in driving an individual's actions (Tanford & Montgomery, 2015; Wang et al., 2024).

In social settings, people often make decisions while others are present, which can influence their choices (Hoyer, MacInnis, & Pieters, 2012). Customers' activities in a behavioural setting are usually influenced by their perceptions, assessments, and emotions, as well as by the impact of others, in line with the social norms of TPB (Solomon, 2020). Friends, family, and other customers might influence a consumer's focus. Therefore, following TPB, in the hotel sector, social influence can affect customers' attitudes, feelings, and actions, including positive word of mouth, intentions to revisit, and recommendations (Wang et al., 2024).

Moreover, a community perceives customers with a larger circle of friends (followers) as more influential. This is especially true when e-platforms incorporate social network services that enable users to find and view reviews from friends (Lee, Hosanagar, & Tan, 2015; Pan, Hou, Liu, & Niu, 2018). Social influence theory suggests that customers communicate their complete experiences at a hotel to others, which enhances their relationships and nurtures the formation of shared values, attitudes, behaviours, and preferences regarding that hotel (Lee et al., 2015). Recommendations from friends are considered more influential than those from unfamiliar sources, as they are viewed as more trustworthy when contemplating a return visit to a hotel (Pantelidis, 2010; Ji, Nicolau, & Liu, 2023).

Moreover, research indicates that the number of connections a reviewer has influences their reputation, as colleagues tend to favour those with a higher number of connections. Factors such as trust, herd behaviour, and social influence play a crucial role in this relationship (Ji et al., 2023; Lee et al., 2015). A person's hotel reviews significantly impact their friends' likelihood of visiting, as friends' endorsements are deemed more trustworthy. In the world of vacations and tourism, social influences have a profound impact on every phase of travel — from before the trip to during and after the trip. Many experts argue that social influence has profoundly changed how individuals organize and partake in vacation experiences (Lee-Anant, 2025; Sedera, Lokuge, Atapattu, & Gretzel, 2017). Through social media, guests can share their hotel experiences in real-time, across various timeframes, and in large volumes throughout their journeys, which may encourage others to consider revisiting (Ji et al., 2023). Thus, the proposed hypotheses are:

We developed a structured survey instrument to evaluate the hypotheses formulated (Figure 1). Surveys were conducted at numerous upscale hotels in Chattogram, Bangladesh's commercial capital, and Cox's Bazar, a popular tourist destination renowned for its world's longest sandy beach. In addition, the number of hotels in Bangladesh is not publicly available on the government website or any other website, but prior research and local newspapers indicate that 44 hotels with a star rating belong to eight divisions, which cover many different cities (Rabiul, Al Karim, & Ahmed, 2023). There are 22 hotels in Chattogram and Cox's Bazar (Karim, Rabiul, & Arfat, 2024).

Furthermore, the population size of the selected hotels was unknown due to the lack of a comprehensive list of hotel visitors, and some hotels were hesitant to disclose the information due to privacy concerns. As a result, we followed Krejcie and Morgan's (1970) recommendation, which argues that a sample size of 384 is enough if the population is unspecified. The study employed convenience sampling, a non-probability sampling procedure, to select respondents based on their accessibility, which aligns with prior hospitality research (Karim et al., 2024; Karim & Mehzabeen, 2025). Convenience sampling enables researchers to collect data from readily available groups of individuals without requiring a sample frame.

All measuring items for the study constructs were adapted from earlier studies and then modified for the current research context (Table 2). The exogenous variable hotel marketing mix encompassed four dimensions: product (PRD), price (PRC), location (LCN), and promotion (PRM). The five-item PRD scale was obtained from Xie (2020), a four-item scale was employed to evaluate PRC from Bradley (2001) and Clemes et al. (2011), three items of LCN were selected from Bradley (2001), and three items of PRM were chosen from Kim and Hyun (2011). Three items from Clemes et al. (2011) were used to assess the mediating variable of tourist satisfaction, while three items from Wang et al. (2024) were adapted to measure the moderating variable of social influence. Two items from Kim et al. (2009) measured the endogenous variable revisit intention. The study uses a 5-point Likert scale to gauge respondents' agreement or disagreement with a specific statement, ranging from strongly disagree (1) to strongly agree (5).

Consent was requested from the HR managers to survey all 22 hotel customers. However, only 19 hotels were granted permission, and three declined due to privacy concerns. Consequently, 19 hotels with a star rating were selected for data acquisition in these two cities. To assess content validity, we sent the questionnaire to two managers from the rated hotels to evaluate the relevance of the marketing mix and other items, and to two university professors to assess the consistency of the items and for grammatical errors. Before administering the survey, we pre-tested the questionnaire with 10 hospitality customers in Chattogram City to identify potential misunderstandings and ambiguities in the questions and to mitigate ambiguity in the scale items. We modified the questions based on input from thirty respondents. For example, in response to the pre-test feedback, we replaced the term “organization” with “hotel” in all items.

Accordingly, the questionnaires were distributed directly to hotel guests, with the cooperation of hotel management, ensuring privacy and confidentiality through written assurances. We ensured the participants that data was used for educational purposes, and no private information was gathered or shared with others. The data collection procedure was initiated in October 2024, during the peak season for domestic visitors. The survey was closed in December 2024, following numerous follow-ups. After several follow-ups, of the 600 questionnaires distributed, 404 responses have been confirmed as valid, and the remaining questionnaires have been discarded due to incompleteness and missing values, resulting in a response rate of 67.33%.

This investigation employed statistical techniques to verify the hypotheses and ensure the validity of the data. This investigation addressed non-response bias by partitioning the dataset into two groups: early (October 2024) and late (December 2024). Levene's test revealed no significant differences between the two groups. The common method bias (CMB) was assessed as the data were exclusively collected from hotel customers. We used procedural remedies and Harman's single-factor test to assess to identify potential biases. Following MacKenzie and Podsakoff (2012), specific guidance was provided to the participants, reassuring them that their responses would be handled prudently to address privacy concerns and that they were free to participate; they could withdraw themselves anytime during the survey. Besides, they were further instructed that there were no right or wrong responses for each question. Instead, they should give their true judgments and opinions. In addition, Harman's single-factor test revealed that one single factor could explain 47.66% of the total variance, which is lower than the suggested value of 50% (Podsakoff & Organ, 1986).

The demographic profile of the respondents is illustrated in Table 1. The results indicate that approximately 56.68% of respondents are male, while 43.32% are female. Once more, 37.38% of the respondents are between the ages of 21 and 30, 35.40% are between the ages of 31 and 40, and the remaining 27.22 % are between the ages of 41 and 50 and over 50. Additionally, 35.89% of the respondents have obtained a bachelor's degree, 31.44% have completed their master's degree, and 21.29 % are classified as others (diploma, postgraduate diploma under technical & vocational education). Regarding profession, the highest 38.86% were service holders, 30.20% of respondents were students, and 18.56% were from business. The demographic data about the respondents' occupations indicated a higher prevalence of service holders and students compared to businesspeople and other groups. This is due to the availability of those individuals throughout the data collection period.

In proportion to Hair, Howard, and Nitzl (2020), the measurement model should be evaluated for convergent and discriminant validity using the average variance extracted (AVE) and composite reliability (CR) values. Additionally, the values of outer loadings are used to assess the reliability of the indicators.

The indicators' loading, composite reliability, and AVE were determined using the conventional PLS algorithm in Smart PLS software. Generally, the AVE values should be more than 0.5, and the outer loading should be 0.7 and above (Hair et al., 2020). According to Table 2, all items have an item loading of more than 0.70 (ranging from 0.773 to 0.939), except for SI3; therefore, the item was deleted due to lower item loading (0.671).

The composite reliability (CR) and Cronbach Alpha (α) values are used to assess the internal consistency reliability, and both values must exceed 0.70 (Hair et al., 2020). Table 2 indicates that the Cronbach's alpha (α) values of all variables range from 0.783 to 0.881. Besides, the CR values are higher than 0.70 (range from 0.874 to 0.937), thus ensuring the model's internal consistency.

The average variance extracted (AVE) is a typical method for measuring convergence validity, and the value should be greater than 0.50 (Hair et al., 2020). The PLS algorithm's output shows that all of the construct's AVE values exceeded the minimal mentioned value (Table 2).

The discriminant validity was assessed using the HTMT ratio. To facilitate the differentiation between the two constructs, the HTMT should be significantly smaller than 0.85 or 0.90 (Henseler, Hubona, & Ray, 2016). The results (Table 3) show that all correlation values are less than the specified cut-off value of 0.90, indicating that discriminant validity exists among the constructs.

The bootstrapping procedure in SmartPLS software was used to evaluate the significance of the path coefficients, utilizing 5,000 bootstrap samples and 404 cases, as described by Hair et al. (2020). The multicollinearity among study variables was confirmed before testing the study hypotheses using the variance inflation factor (VIF). The results (Table 3) indicated that the VIF values were all less than the cut-off value of 3.0 recommended by Hair et al. (2020). Multicollinearity is, therefore, not an issue for this investigation. Table 4 shows that product (β = 0.240, t = 3.562), price (β = 0.184, t = 2.862), location (β = 0.162, t = 3.060), and promotion (β = 0.207, t = 3.949) have significant positive relationships with hotel customers' satisfaction. The hypotheses H1, H2, H3, and H4 were supported based on their t-values and p-values.

Similarly, hypotheses H5 and H8 were confirmed, as product (β = 0.132, t = 1.868) and promotion (β = 0.163, t = 2.980) are found to correlate significantly with customer revisit intention. Conversely, price (β = 0.027, t = 0.413) and location (β = 0.033, t = 0.772) have an insignificant correlation with customer revisit intention to the hotel; therefore, hypotheses H6 and H7 were not confirmed based on their significance values. In addition, hypotheses H9 and H10 were validated, as both satisfaction (β = 0.350, t = 7.423) and social influence (β = 0.327, t = 4.845) were found to be positively correlated with hotel revisit intention (Figure 2). Furthermore, customer satisfaction partially mediates the association between product (β = 0.003, t = 0.200) and promotion (β = 0.003, t = 0.200). Again, customer satisfaction fully mediates the associations between hotel price (β = 0.003, t = 0.200), location (β = 0.003, t = 0.200), and hotel revisit intention. Thus, all four mediation hypotheses (H11, H12, H13, and H14) were confirmed. Along with the proposition of Nitzl, Roldan, and Cepeda (2016), partial mediation was demonstrated when both direct and indirect linkages were confirmed. Lastly, regarding the moderating effects, social influence (β = 0.105, t = 3.111) verified Hypothesis H15 and moderates the association between customer satisfaction and hotel revisit intention. The moderation slope is presented in Figure 3.

The R² value, PLS prediction (Q² value), and SRMR value were used to evaluate the model quality (Table 5). The R² values for revisit intention and satisfaction were 0.609 and 0.468, respectively, indicating moderate explanatory power of the model, following Chin (1998). Additionally, the Q² values for all the endogenous variables are greater than 0, demonstrating that the model has predictive relevance. Furthermore, Table 5 revealed that the SRMR value of 0.076 is less than the recommended value of 0.08, indicating an acceptable level of model fit (Hair et al., 2020).

The study's results indicated that the four components of the hotel marketing mix—product, price, location, and promotion—positively correlate with the satisfaction of tourists at 3, 4, and 5-star hotels. Consequently, hypotheses H1 (PRD→TS), H2 (PRC→TS), H3 (LCN→TS) and H4 (PRM→TS) were confirmed and supported by several previous studies (Quang, 2017; Sudari et al., 2019) where competitive price, an ideal location, appealing promotional campaigns, and a well-organized product offering all contribute to tourists' satisfaction. Xie (2020) identified the following as key factors that contribute to tourist satisfaction: hotel products (including hygiene, well-maintained rooms, and comfortable surroundings), hotel prices (representing the exchange of money for services), hotel location near tourist attractions, and effective hotel promotion. Overall, a well-structured hotel marketing mix has a significant impact on tourist satisfaction and influences their decisions to make repeat purchases (Sudari et al., 2019; Elgarhy & Mohamed, 2023).

In addition, hotel revisit intention was substantially influenced by the hotel's product and promotion, while the hotel price and location did not exhibit any significant association with revisit intention. Consequently, hypotheses H5 (PRD → RI) and H8 (PRM → RI) were supported, confirming the findings of other studies that indicate positive associations between these factors (Gholipour Soleimani & Einolahzadeh, 2018; Elgarhy & Mohamed, 2023). Hypotheses H6 (PRC → RI) and H7 (LNC → RI) were not confirmed, and the outcomes were supported by Tay et al. (2023), who noted that an improper marketing mix strategy can sometimes demotivate tourists from revisiting their intention. Following Mannan et al. (2019) and Lahtinen et al. (2020), an inclusive price and suitable location can potentially inspire customers to make repeat purchases. According to Tay et al. (2023), strategically organising a hotel's marketing mix can produce positive visitor experiences and repeat purchases, thereby guaranteeing the hospitality sector's resilience and success in challenging times. The hotel industry must enhance the quality of its marketing mix strategy by recognising the deficiencies that customers have identified and by creating amenities consistent with their evolving needs and preferences to increase their revisit intention (Kim et al., 2020).

Consistent with prior research that has demonstrated a positive relationship between satisfaction, social influence, and hotel revisit intention (Wu et al., 2015, 2018; Rasoolimanesh et al., 2023), the hypotheses H9 (TS→RI) and H10 (SI→RI) were confirmed. Visitor satisfaction has a significant impact on the hospitality industry, influencing hotel selection, consumer behaviour, and the likelihood of repeat business. It helps to build a positive corporate image, establish a reputation, and maintain visitor growth and stability (Rasoolimanesh et al., 2023). Similarly, social influence has a substantial impact on a hotel's performance, as feedback from others significantly increases revenue for firms in the hospitality sector. Effective social influence that highlights a hotel's features and services can help it advance (Wang et al., 2024).

Furthermore, the findings show that visitor satisfaction partially mediates the relationship between product, promotion, and revisit intention, and hypotheses H11 (PRD → TS → RI) and H14 (PRM → TS → RI) are verified. Likewise, visitor satisfaction fully mediates the association between price, location, and revisit intention, validating hypotheses H12 (PRC → TS → RI) and H13 (LCN → TS → RI). Thus, tourist satisfaction significantly affects tourists' willingness to make future purchases and returns. Hotel marketing mix components, such as hotel products, price, location, and advertising, directly impact visitor satisfaction because they meet the expectations of visitors during their stay. Previous research has demonstrated that the hotel marketing mix and visitor satisfaction have a significant influence on guests' intentions to return (Choo et al., 2019). Finally, social influence substantially moderated the relationship between visitor satisfaction and revisit intention, and hypothesis H15 (TS*SI→RI) was supported. In the hotel industry, social influence can impact customers' attitudes, emotions, and behaviours, such as encouraging positive word of mouth, intentions to return, and recommendations (Wang et al., 2024).

This pioneering study explores how the hotel marketing mix affects tourist satisfaction and their intention to revisit in the Bangladeshi hotel sector. It also investigates the moderating effect of social influence on the relationship between satisfaction and the intention to return. The study reveals that tourists' satisfaction mediates the relationship between all components of the hotel marketing mix and their intention to revisit the hotel. Moreover, tourist satisfaction and social influence have a positive influence on their intention to revisit. Additionally, social influence serves as a moderator between tourist satisfaction and hotel revisit intention. Thus, the findings have substantial theoretical contributions to the literature on the hotel marketing mix in the hospitality industry. Furthermore, the study presents a robust, integrated model that incorporates several variables significantly impacting visitor satisfaction and their intentions to return, thereby enhancing the context of hospitality marketing. Moreover, the study presents a model that examines the direct and indirect relationships between the hotel marketing mix and tourist revisit intention, mediated by tourist satisfaction, offering rational insights for the industry and adding value to the existing body of knowledge.

Likewise, this study makes a substantial contribution to the theory of planned behaviour (TPB) by establishing the connection between the hotel marketing mix and the intention to revisit, as it reveals the mediating role of visitor satisfaction and the moderating effect of social influence. The findings of moderating role of social influence is the unique contribution of this study for the hospitality industry. Using the TPB framework, hotels can enhance their marketing mix strategies by incorporating customer behaviour, marketplace dynamics, and preferences. TPB offers valuable insights into the influence of various marketing strategies on customer behaviour and decision-making in the hospitality industry when applied to the hotel marketing mix.

The study's results offer several beneficial viewpoints for hotel management in Bangladesh. Results indicate that the quality of the hotel, its price, location, and promotional activities substantially impact tourist satisfaction. Therefore, managers must prioritise their efforts in hotel marketing strategies, as this directly affects customer satisfaction. Furthermore, satisfied customers are more likely to recommend the hotel to others, be willing to pay higher prices, and be more likely to return.

Conversely, the hotel's price and location negatively influence the desire to revisit. This issue may be attributed to the exorbitant prices of hotel rooms and cuisine and the failure to provide essential amenities relevant to the hotel's location, compared to the price, which is vital for the visitors' overall experience. Based on the price-related finding, managers can redesign the pricing strategy and launch several loyalty programs for discounts to enhance satisfaction and revisit intention. Hotels close to popular tourist destinations should be conveniently reachable, provide explicit directions, offer secure amenities, and promote repeat visits to guarantee a pleasant stay (Ranjbarian & Pool, 2015). Hence, managers should prioritise providing a relaxing and delightful hotel environment, which includes the look of buildings, landscapes, vehicles, internal decor, equipment, personnel, uniforms, signage, and printed materials, since these visible cues substantially influence customer revisit intention through their satisfaction (Elgarhy & Mohamed, 2023).

In summary, the investigation illustrated a novel understanding of the influence of the hotel marketing combination (quality, price, location, and promotion) on satisfaction and revisit intention. In particular, the indirect effects of a hotel's marketing mix on revisit intention are more significant than their direct effects, mainly when satisfaction is a mediator. Additionally, social influence strengthens the correlation between satisfaction and revisit intention. This study empirically validated findings that provided critical theoretical evidence for accurately capturing visitors' satisfaction, social influence, and revisit intention. Given that, hotel managers should strategically utilise the components of the hotel marketing mix to efficiently serve guests, thus enhancing tourist satisfaction, generating positive word of mouth through effective social influence, and increasing the likelihood of repeat visits to a particular hotel.

Numerous limitations of this study should be noted when understanding and generalising its findings. First, this study's limitation lies in its suggested conceptual model and path directions, as each model is only partially effective and universally competitive. More research is recommended to re-evaluate hypothetical relationships in other hotel marketing mix components. Next, the study's sample size of 404 respondents was restricted to Chittagong and Cox's Bazar, which may partially represent the hotel industry's target population. Future research should consider incorporating additional tourist-oriented cities to improve the understanding of the associations among study variables. Next, the convenience sampling method was employed, which cannot accurately represent the whole population and may yield biased findings. Any probability sampling approach can be utilized in future investigations to obtain a more generalizable result. In addition, this study focuses on four hotel marketing mix categories (product, price, location, promotion) and overlooks other factors like people, process, and physical evidence. Future research should explore all the marketing mix components in the same context. Additionally, this study investigated tourist satisfaction as a mediating variable and social influence as a moderating variable. Consequently, future research may incorporate additional variables as mediating variables (e.g. tourist delight, experience, hotel image, reputation) and moderating variables (e.g. loyalty, retention). Lastly, this study collected cross-sectional data from Chattogram and Cox's Bazar, two renowned tourist destinations. Thus, future studies may use time-lag data to mitigate common method bias and yield accurate results.