An Empirical Study of Smartphone Companies in An Emerging Economy: The Role of Trust and Commitment in Fostering Consumer Engagement and Loyalty Via Social Media

The purpose of this research is to learn more about the mental processes that drive customer involvement, with a focus on the roles that loyalty and trust play in this phenomenon online. By investigating the connection between brand engagement on social media, brand affection, consumer trust, and brand loyalty, this study hopes to fill a vacuum in the existing literature. SEM smartPLS was used to analyze data from 251 replies on smartphone and clothing brands. Customers’ commitment and trust are moderated not by their feelings but by demographic factors like age and gender. There is a direct and indirect connection between consumer involvement and trust. Customer happiness, brand loyalty, and brand de-votion are all factors that may be predicted and developed with active consumer engagement, as the study shows. Although not all of the predictions of the conceptual model are supported by the data presented here, the study does offer important theoretical and practical insights into how to improve customer engagement, relational marketing strategies, and the consumer acquisition process. The novelty and significance of this article come from its analysis of what motivates customers to interact with a brand online and from the creation of a conceptual model that examines the role of customer engagement as a mediator in the generation of brand loyalty, brand love, and


Introduction
By highlighting the importance of dedication, involvement, and trust in the creation of fervent brand advocates, this study seeks to shift the focus of customer satisfaction surveys in a new direction. That "con-dominantly needed for the production of both substantial amounts of either a beneficial or detrimental effect" (their italics) is something that Mano and Oliver (1993, p. 455) write about. Hofmeyr and Rice (2000) argue that customers are less likely to be loyal to a brand if they have no control over the products and suppliers they use. Businesses as well as marketers place a premium on customer happiness and loyalty since they are considered to be cornerstones of marketing theory (Zaman et al., 2018). The advantages to companies and the various studies that have investigated the correlation between happy customers and repeat purchases (Khan et al., 2022a).
In the past decade, consumers have increasingly turned to the interactive platforms provided by social media in order to communicate with brands and peers (Mubarik et al., 2021a). Over 4 billion individuals are expected to utilize social media in 2019, a 9 percent increase from 2018 (Clement, 2020). There has been a consistent uptick in the number of people relying on social media for things like market analysis, customer relationship management, support after the sale, and special deals (Miao et al., 2022). Forbes' Chief Marketing Officer, or CMO, Survey from February 2018 (Moorman, 2018) found that 11% of marketing budgets were allocated to social media. Most CEOs claim that majority of social media activities are the "brand development and publicity" campaigns (Khan et al., 2022c). Academic studies improve a company's visibility and credibility in the eyes of consumers (Mubarik et al., 2021b). Brand fan sites (BFPs) are a recent trend in marketing, with companies investing in them to increase user engagement and brand loyalty.
Marketers, service providers, and hotels, according to Itani et al. (2019) and Meire et al. (2019), may all stand to implement the concept of engagement. By "individual relationship to a brand," So et al. (2014) mean "a client's mental, emotional, and behavioral choices beyond the buying scenario". Marketing that encourages participation from tourists is essential since it speeds up the process of making new memories and creating value (Chathoth et al., 2013). According to Aluri et al. (2019), companies in the tourism sector may now leverage online consumer engagement tactics to foster deeper relationships with their brands' most loyal patrons (Miao et al., 2022). Encourage voting via the Internet and posting and sharing vacation memories on social media networks to strengthen customer interactions in the tourism industry (Touni et al., 2020). According to research (Bilro et al., 2019;Prentice & Loureiro, 2018), organizations whose customers actively participate in the business tend to have happier, more loyal customers. Loureiro and Lopes (2019) state that studies on customer engagement in the tourist business via social media are scant and preliminary. (Loureiro & Lopes, 2019) There is a lack of published research on the topic of tourists' use of social media. Researchers have not yet agreed on a consistent paradigm for studying consumer participation in social media, despite the growing theoretical and managerial relevance of this phenomenon (Khan et al., 2022a). More than twenty studies have focused on consumer participation via social media, despite the fact that it is a relatively new concept compared to customer happiness and loyalty (Mubarik et al., 2021a). At least eight measures for gauging client interaction in social media have arisen from these studies. Although studies have shown a correlation between customer participation and brand loyalty, conclusive proof is missing. Academics have an obligation to explore the mechanisms that may serve as intermediaries between consumer engagement and brand loyalty (Khan et al., 2022b). This study looks at how the attachment to brands and trust among consumers influence the connection between social media activity and loyalty to brands in the travel sector.
With the rise of major social media sites like TikTok, Snapchat, Twitter, WeChat, LinkedIn, and Facebook, consumer contact has become more vital than ever (Mubarik et al., 2021a). In 2020, Facebook's monthly active users will reach 2.8 billion, followed by 800 million on Instagram, 200 million on WhatsApp, and 150 million on Messenger. Many research investigations have looked at both the practical and theoretical elements of customer engagement as social media use has grown, such as measurements for consumer engagement in the Chilean wine business and recommendations based on characteristics that influence customer engagement (Zaman et al., 2018).
Affective structures may have a role in the connection between consumer pleasure and brand loyalty, although this hasn't been studied before. Examples of such indicators of brand loyalty are a consumer's emotional investment in the brand and their willingness to recommend it to others. No data, however, support the claim that emotional attachment plays a mediating role in the connection between customer happiness and brand loyalty. Following the sixth scenario, we speculate that emotional structures moderate the link between satisfaction and loyalty, expanding on the findings of Oliver's (1999) study that implies satisfaction starts in an intermediate process leading to loyalty. We hope to learn if emotive ideas like love and connection play a mediating role in the sequence of occurrences that culminates in loyalty.

Customer engagement theory
New research on customer loyalty highlights the importance of making customers feel good about doing business with your company (Khan et al., 2022a). We think the degree of emotional connection and enjoyment in the setting of social media depends on the nature of the relationship, and that trust and commitment create good feelings and satisfaction. We believe that the cornerstones of a strong business-client relationship are loyalty and trust on the part of the clients. Therefore, we contend that customer trust and loyalty are affected by satisfaction and positive emotions. Customer participation is crucial to the success of relationship marketing since it influences existing consumers' opinions of the company and attracts new ones (Jiang et al., 2019). When seen through the lens of service-centric reasoning, customer interactions provide light on the dynamic between businesses and their customers, as well as other interested parties (Mubarik et al., 2021b). According to studies, consumer participation mediates between its causes and its consequences. Consumer participation, for instance, was found to moderate the effects of place attachment and authenticity on confidence, devotion, and co-creation (Rather et al., 2019). Customer participation behavior can benefit either customers or enterprises (Khan et al., 2022c). The research offers a number of theories in light of the significance of client engagement and the information gap about the mediating function of customer engagement between trust characteristics and customer loyalty.
Hypothesis 1 (H1): CE mediates the relationship between trust and customer loyalty

Trust plays an essential role
It's generally agreed that trust is crucial in establishing a rapport between companies and their clients. When consumers have faith in a company, they are likelier to stick with it (So et al., 2016b). Customers are inclined to form loyal brand connections if they have high confidence in the company, which shows a propensity for depending on other companies (Moorman et al., 1993). Tsai et al. (2012) found that most trusting consumers were also the most engaged, while  found that customers who felt a sense of community in online social networks were likelier to trust such sites. Reliability is closely related to feelings of fulfillment and pleasant emotions in various research settings, including the Internet. Therefore, we postulate that trust contributes to both contentment and pleasant feelings.
Hypothesis 2 (H2): Trust is positively related to customer engagement.

Commitment reflects
The notion of commitment is linked to an individual's mental state, affecting their actions about a particular brand or product (Khan et al., 2022a). Customers get invested in a business when their loyalty is reciprocated by enthusiastic support for the company. (Mollen & Wilson,2010) argue that loyalty is correlated with customers' perception of the brand as a living, breathing entity with its personality. Customers who are emotionally invested in a brand are more likely to choose that company over competitors. Bowden argues that the study of CE requires attention to both rational and emotional forms of dedication. In several research studies, commitment has been found to be a strong indicator of consumer loyalty. As a result, we'd like to put out the following theory.
Hypothesis 3 (H3): Commitment has a positive impact on customer engagement.

Positive emotions
The positive feelings that consumers experience stem from their rational and emotional assessments of their purchasing decisions (Bagozzi et al., 1999). Expectations for outcomes tend to be more optimistic when people feel good emotions like agreeability, excitement, and autonomy (Pansari & Kumar, 2017). We propose that hedonic value and consumer involvement are just two mental states activated by positive emotional appraisals of consuming experiences (Bagozzi et al., 1999;Pansari and Kumar, 2017). Therefore, according to the hypothesis, optimistic feelings have a beneficial effect on client participation. Pansari and Kumar (2017) found that although good emotions directly impact, the benefits of happy feelings appear not contingent on any particular circumstances. Our research suggests that managers may increase customer engagement by allocating resources to improve customer touchpoints' quality. As seen with Four Seasons Hotels, which received more than eighty percent favorable feedback and the top ranking on social media in the hospitality and travel sectors, client engagement is linked with additional elements for firm performance and can thus justify such expenditures (Khan et al., 2022c). Customers are more invested and productive after a visit to Four Seasons because of the great feelings of contentment and joy they feel there. As a result, the following theory is put forth: Hypothesis 4 (H4): Positive emotions positively affect customer engagement.

Brand loyalty
"A customer's preference to, and dedication to, a specific brand" (Fullerton, 2003) is the definition of brand loyalty. According to research , brand loyalty is crucial to the success of marketing strategies. Attitude and behavioral brand loyalty are both studied in the literature (Oliver, 1999). Behavioral loyalty may be gauged by how frequently a customer repurchases the brand in question, whereas attitudinal loyalty can be gauged by how committed the customer is to the brand in question . According to the work of Aaker (1991) analyzing the relationship between customers and brands (Fetscherin et al., 2014), brand loyalty is the greatest level. According to the study's authors, brand loyalty is the most important aspect of the customer-brand connection, and it can be gauged by combining measures of customer behavior and perception. As stated by Oliver (1999), loyalty to a brand is defined as customers' "firm dedication to purchasing the same brand consistently." So et al. (2016) define "customer engagement" as "customers' activities with a company other than purchases." Engaged consumers are more likely to remain brand loyal (So et al., 2014;Vivek et al., 2012). It has been shown that product and brand-level controls have a significant impact on consumer trust and, by extension, loyalty . Total customer satisfaction is achieved when customers actively participate in online brand communities (Brodie et al., 2013).

Hypothesis 5 (H5):
There is an effect of customer engagement on brand loyalty.

Customer loyalty
Brand loyalty is "a customer's preference for, and commitment to, a particular brand" (Fullerton, 2003). Repeat business results from a "multifaceted" construct that includes behavioral and psychological variables (Too et al., 2019),the term "customer engagement" describes a consumer's emotional investment in a brand after their first purchase. By highlighting the significance of client lifetime value in promoting long-term buying behaviors, including recurring purchases, selling more, and cross-selling, Kumar et al. (2010) established a relationship between customer engagement and loyalty. Bowden (2009) echoed this sentiment when he spoke about how crucial customer relationships are to establishing brand loyalty. Harrigan et al. (2017) showed similar results for tourist businesses on social media, correlating customer interaction to commitment in an online context. According to several studies, there is a clear correlation between customer involvement and customer loyalty. Therefore, the following hypothesis is put forth: Hypothesis 6 (H6): CE is positively related to customer loyalty.

Customer satisfaction
Customers who have a positive experience with the results of their purchases are more likely to become loyal patrons. Customers who are pleased with the services they receive are more inclined to advocate for the company they've dealt with and the brand itself. According to empirical research (Cambra-Fierro et al., 2016;Dessart et al., 2015), customer happiness significantly impacts CE. As a result, we anticipate that consumer engagement with life insurance brands will increase when customers are pleased with the services and products offered by these brands. Our proposed theory is based on the following arguments: Hypothesis 7 (H7): Customer satisfaction is positively associated with CE, customer satisfaction and brand love.

Brand love
According to , brand loyalty is an "unpredictable outcome" among happy customers arising from positive brand business experiences. Satisfying experiences have been observed to foster emotional ties and passionate bonds between customers and brand corporations (Soscia, 2007). According to research by Long-Tolbert and Gammoh (2012), CBR ebbs and flows in response to changes in customer satisfaction. Consumers are more likely to recommend a product or service to others after having a good experience if they are satisfied with it (Cho & Hwang, 2020). There is a clear correlation between customer satisfaction and brand loyalty (Song et al., 2019). Several researches have shown that a beautiful brand experience promotes emotional attachment or brand love (Khan et al., 2020), even though pleasure is an intangible result of customer experience. According to studies across sectors, satisfaction is correlated with brand loyalty (Khan et al., 2020). To learn more about this connection, The research suggest the hypothesis: Hypothesis 8 (H8): Customer satisfaction has a significant relationship with brand love.

Brand love -brand loyalty
In consumer-brand interactions, "brand love" is a relatively new notion that refers to extreme devotion to a particular brand. Brand managers should prioritize this result to create long-lasting connections with their clients. Many different aspects of a person's mind, heart, and actions contribute to their strong feelings of attachment to a brand, that brand love can be operationalized using  framework. It's the cumulative effect of a consumer's many experiences with a brand over time.
This study aims to examine the direct influence of brand affection on brand loyalty among pleased and attached consumers using the brand love scale developed by . Several studies have demonstrated that pleased customers are more loyal to a brand. The researchers propose that brand love might mediate between customer happiness and brand loyalty. Accordingly, the research hypothesis is that among happy, committed consumers, there is a direct beneficial influence of affection for the brand on brand loyalty: Hypothesis 9 (H9): brand loyalty has a positive impact on brand love.

Variations in the model in gender perspective
Marketers often categorize consumers based on their gender, with studies showing that women are more loyal to their favorite brands than men are (Byrnes et al., 1999;Tifferet & Herstein, 2012). However, women are more likely to make impulsive purchases and value hedonic product features like emotional arousal, fun, and entertainment more than men (Coley & Burgess, 2003;Zhong & Mitchell, 2010). Marketers need to consider that customers are not a monolithic whole when developing segmentation strategies (Chawla & Joshi, 2020). To account for substantial gender inequalities and offer a road map for better outcomes, this research presents a hypothesis to quantify the variances in model relations: Hypothesis 10 (H10): The relationships of different variables in the model are moderated by gender.

Variations in the model in age perspective
Given their potential as a growing and appealing group while having less purchasing power, the influence of young customers on firms' marketing strategies has been the subject of many research studies . It is often held that younger consumers are less loyal to a company's brand since they are more willing to try out novel products and services . Socialization, media consumption, technological adoption, and purchasing practices are only a few areas where the literature has explored generational disparities in consumer attitudes and behaviors. However, there is little research on how the varying ages of consumers affect CBR. To successfully match marketing offers and programs, it is crucial to have an understanding of this phenomenon. The following hypothesis is proposed to investigate the influence of young customers on CBR in this study: Hypothesis 11 (H11): The relationships of different variables in the model are moderated by age.

Instrument
The questionnaire that was used in this study was a two-part survey. The first part covered customer satisfaction, commitment, engagement, loyalty, trust, positive feeling, love for the brand, and loyalty to the company. The second part of the survey inquired about the age and gender of the participants. A twenty-three item scale assessment was adopted from prior studies and adjusted to meet the setting of this research to guarantee that the directions and inquiries were clearly understood. All questions were responded to using a five-point option response system like that of the Likert scale, with one representing strongly disagreeing and five strongly agreeing. We chose to utilize a Likert scale since it has been frequently employed in studies involving comparable research variables. Respondents were briefed about the study's goals, the questionnaire's format, and the appropriate use of the Likert scale before being asked to fill it out.

Data collection
Facebook was selected as a social networking site to probe the bond between respondents and their favorite businesses. A quantitative marketing study survey technique was utilized to describe and assess the relationships between the proposed dimensions. Over four months, respondents to a cross-sectional, self-administered survey posted on Facebook provided their responses. Mail and social media campaigns were used in addition to Facebook shopping and brand community groups to enlist respondents. Participants were assured of anonymity and freedom of choice. The study employed a non-probability sample strategy commonly utilized in earlier research on consumer engagement: convenience sampling. The study had qualifying questions, including when respondents joined Facebook, how long they spend on the site each week, what brands they are regular customers of, how often consumers interact with those brands on Facebook, and how often they buy products from those brands.
Participants were asked to respond to the questions in light of their loyalty to a particular brand.

Sample size
To verify the study methodology's reproducibility, the questionnaire responses were uploaded to Google Forms. Respondents who have made two or more transactions were targeted for this online survey via the convenience sample technique. Over the course of two months, we received 251 replies. Structural equation modeling requires at least 100 or 200 samples (Maccallum et al., 1999;Boomsma & Hoogland, 2001).

Analysis Techniques
In this work, we used the partial least squares-structural equation model (PLSSEM) to examine the interrelationships between our independent variables. The data was segmented and examined independently to check for the influences of both gender and age. This study followed the two-stage procedure suggested by Anderson and Gerbing (1988) and elaborated on their findings using the method presented by Hair et al. (2019). Harrigan et al. (2017) presented eleven measures to measure consumer engagement, whereas Park et al. (2010) proposed ten things to measure brand attachment. Zeithaml, Berry, and Parasuraman (1996) each developed four questions and items to assess consumer trust and brand loyalty. With the exception of questions on respondents' emotional investment in the brands, which were scored on a scale from 1 (strongly disagree) to 5 (strongly agree), all other questions in the survey were evaluated using this scale. The use of these measures is consistent with prior studies. There is a comprehensive survey question list in the research.

Designing and Unitizing
The content analysis followed the steps outlined by Krippendorf and the context chosen to examine BFP postings made by consumers on social media platforms like Facebook and Twitter. This research looked at the social media activity of four brands operating in the Turkish market: two manufacturers of long-lasting products (Toyota Turkey and Renault Turkey) and two producers of fast-moving consumer goods (FMCG) (Coca-Cola Turkey and PepsiCo Turkey). As a result, we broke down the performance of these four consumer brands by looking at their individual Facebook and Twitter brand postings.

Search procedure
Using Google Scholar, we looked for papers that presented empirical results on the topics related to the variables being studied. Second, we re-examined the articles uncovered by the digital search for more studies that developed scales to measure social media engagement. Last but not least, we used the same keyword combination to search eight distinct online databases (JSTOR, Emerald, etc). The Academy of Marketing Science's Annual and World Marketing Congresses, the European Marketing Academy, etc were all scoured by hand to supplement our research.

Analysis and Results
The data were analyzed in two phases. Confirmatory factor analysis was used to verify the reliability of the measuring instrument, and structural model estimation followed. The method of partial least squares (PLS) was used, and the SmartPLS 3 program was used throughout. The variance-based PLS-SEM method, which manages both the structural and measurement models at once, was used to guarantee the uniformity of the data distribution. SEM was used mostly for forecasting and investigating the largest possible variation.

Measurement model validation
Calculating the outer loadings, quantifying the composite reliability (CR), the average variance extracted (AVE), and the discriminant validity were used to evaluate the reflecting measurement models. To test the measurement model's convergent validity, factor loadings, CR, and AVE were calculated (Hair et al., 2013). Table 2 demonstrates that all item loadings were more significant than the 0.6 threshold value suggested by the literature (Chin et al., 2008). Our CR and Cronbach's values, which indicate how well the construct indicators reflect the latent construct, exceeded the recommended value of 0.7 (Hair et al., 2013), as did our AVE, which reflects the total amount of indicator variation that can be attributed to the latent construct.
Checking for minimal correlations between the measure of interest and measures of other constructs was used to determine discriminant validity, indicating that the measure under consideration does not merely reflect other factors. Table 3 demonstrates that the discriminant validity of the measures was adequate (Fornell & Larcker, 1981), as the square root of the AVE (diagonal values) for each construct was greater than their respective correlation coefficients. According to our findings, the measuring model had sufficient convergent and discriminant validity. Table 1 Demographic profile of respondents  Table 2 Validity and reliability of constructs and loadings

Discriminant validity
Discriminant validity refers to the extent to which a construct is distinct from other constructs in the same model . Two primary techniques for assessing discriminant validity are the Fornell and Larcker criterion and the Heterotrait-Monotrait (HTMT) correlation ratio. Table 3 displays the outcomes of the Fornell and Larcker criterion.

Assessment of structural model
SmartPLS 3.0 was used to assess the structural model in accordance with Chin (1998 criteria. The method of partial least squares (PLS) assessment, which may accomplish this goal by either minimizing structural errors or enhancing variation explanation capacity (Chin, 1998), was used to optimize the predictive ability of variables that are endogenous. Table 4 shows the R2 value for the model's prediction capacity in terms of endogenous constructs. These numbers can be thought of as a continuum from 0.39 to 0.68. According to Chin's (1998) definition of considerable, moderate, and weak R2 values, the results we found were substantially stronger than moderate. Values of R2 over 0.10 (10%) are recommended by Falk and Miller (1992). For further evaluation of the overall model fit, the standard root mean square residual (SRMR) was determined, and it was found to be 0.050, which is an excellent result. Hu and Bentler (1998) state that values between 0.10 and 0.08 are considered suitable.

Hypotheses testing
PLS analysis was used to check the validity of the six hypotheses developed for this study. A two-tailed t-test was employed to determine the statistical significance of each postulated association in the research model given that the factors that are independent could have both a beneficial or detrimental effect on the variables that are dependent. Two-tailed t-test (df = 300) overall significance set at p 0.05 and t1.96 as the threshold. To get a significance level of 0.01, a t-value of more than 2.63 is required, and a t-value of above 3.40 is required to achieve a significance level of 0.001.

Table 5
Hypothesis testing Table 4 Results of R2

Discussion and Implications
In the setting of online shopping and digital advertising, new studies have underlined the importance of customer interaction in creating lasting relationships (Hollebeek et al., 2014). The purpose of this research was to explore, with an emphasis on customer experience (CE), the variables that contribute to consumer participation in online marketing. According to the research, customer engagement (CE) is a key predictor of customer loyalty and is fueled by trust and commitment. According to the research, the correlation between customer satisfaction and customer experience is stronger in B2B than in B2C organizations, which may be attributable to the former's more structured approach to client relationship management (Beckers et al., 2018). According to Junco et al. (2013), the satisfaction-CE path is roughly two times as strong within the Twitter sector, suggesting that Twitter may be a beneficial and easily available marketing tool for constructing an improved consumer satisfaction-CE route.
In terms of disparities between the sexes, the study indicates that women are more likely than men to go from loyalty to love for a brand. On the other hand, if elderly consumers are happy with the products or services they receive from a business, they are inclined to develop a deep affection for that business and its brand. Brand loyalty among male consumers is not based on positive experiences with the product or service.It's worth noting that the study's results might be impacted by the fierce monopolistic rivalry between multiple enterprises in the research's product area that sell essentially similar items. Moreover, the present examination found a modest association between brand loyalty and consumer happiness, contrary to the findings of previous research.
In conclusion, the findings of this study shed light on the importance of CE in fostering customer loyalty by revealing the aspects that contribute to consumer engagement. The study's results have significance for companies that want to create lasting relationships with their customers, particularly in the realms of digital marketing and e-commerce.

Theoretical implications
This study is in response to the growing body of literature demanding exhaustive examinations of how best to involve customers in the design and development of digital products. We will go deeper into the theoretical contributions of this study using the results of our newly suggested model of CE.
First, by concentrating on the audience, this study broadens the literature on customer-brand interactions, especially in the field of social media marketing. When done right, social media marketing has the potential to remind, inform, and excite clients, setting the framework for undying devotion. Businesses may focus on value co-creation, lasting connections, and the development of brand love through customer engagement, a notion with its origins in relationship advertising and customer support-dominant thinking. This study introduces a fresh approach to the investigation of consumer involvement in social media marketing. The model relies on responses from 391 consumers throughout the world who expressed an interest in a certain brand and who use Facebook as consumers.
Thus, the empirical study concurs with the proposed method of assessing CE from a global viewpoint. There has been a lot of research on the topic of consumer involvement in digital settings centered around relationships between consumers and businesses because of the widespread use of social media. That's why this research is so important.
The second major contribution of this research is an examination and validation of the CE scale built on the items proposed by Vinerean and Opreana. The elements on the scale were selected because they met Islam and Rahman's criteria and were able to be readily generalised to reflect different situations. Therefore, by validating a consumer engagement metric, the research complements the efforts of previous academic studies.
The third significant addition is the demonstration of the reliability of CE and its primary predictors through empirical testing. Consistent with other research, this study indicated that a customer's level of commitment was a significant predictor of their level of involvement. Since CE may motivate customers to take action-such as repeat purchases and interactions with favored brands-commitment and CE go hand in hand. The model's validity is further supported by a multi-group analysis that considers a demographic variable, as has been suggested by several writers. Social media is a potent tool for creating interaction, gaining feedback, and building trust with your audience, as stated in the most current article on social media marketing published in the Harvard Business Review (2020). Positive feelings directly impact consumer involvement, but they do not help build trustworthy, loyal relationships, according to the study's authors. This suggests that their impact is not influenced by anything else. Managers should invest in creating more positive customer experiences because they have been shown to increase customer engagement, increasing the likelihood of a customer developing a strong emotional connection to the brand over time (Loureiro et al., 2012).
Third,in light of this need, our study explores how consumer participation influences brand loyalty for social media companies serving the tourist industry. Previous studies have shown that consumer involvement increases brand loyalty (Brodie et al., 2013); however, our results don't back this up. According to the study, customers are less loyal to online companies than they are to the brands of physical items (Zillifro & Morais, 2004). According to Levy (2014), contrasting genuine devotion with pretenses of commitment is crucial. Because customers with false loyalty are readily lured to operators who give items with reduced costs and easy service, recurrent purchase behaviors do not indicate genuine loyalty in the false loyalty situation.

Practical implications
The results of this study are significant for managers, as they highlight the importance of trust and commitment in understanding why customers develop a connection to specific companies. To encourage customers to invest in a company, managers must recognize the value of trust and commitment and develop expansion and improvement strategies accordingly. Utilizing customer relationship management (CRM) and other digital solutions can aid in managing relationship marketing effectively.
It is well-known that consumers develop strong emotional bonds with their preferred companies. Therefore, managers should strive to provide customers with a positive experience by offering competitive pricing, high-quality products, and attractive packaging. Additionally, brand managers should focus on creating compelling content, particularly for social media, that aligns with the company's long-term objectives and strategy.
As customers' emotional investment in a company contributes to their loyalty, brand managers should understand that consumers often associate their own identities with the products they buy. Consequently, the product's marketing strategy should concentrate on differentiating it from competitors' offerings, while marketers should also identify variables that contribute to the formation of connections, such as loyalty and love. This could involve improving product quality, creative product design, and eye-catching packaging.
Ultimately, customer brand loyalty is most closely linked to emotional attachment to the brand, which managers may utilize to their advantage by customizing loyalty messaging and programs to their target demographic and paying attention to customer preferences. To create customer experiences, companies that value CE must go beyond customer happiness and consider how their consumers can participate.

Limitations and future research
This investigation covers much ground, but it is not exhaustive. Although thorough consideration was given to the definitions and operationalizations of each variable in the literature, it became clear that there are numerous methods to operationalize these parameters. Therefore, the study model does not account for all potential variables/factors, and the content of posts may be evaluated from multiple perspectives.
The framework utilized in this study could be expanded in future research by utilizing a larger sample size and adapting it to new contexts. Although gender and age were used as moderating demographic variables in this study, other demographic variables may be investigated in future research.
Data was collected through convenience sampling, and the study's narrow focus on smartphone consumers makes generalization challenging. To address this deficiency, future research could broaden the scope of the proposed model to include studies of it with a variety of product categories and user populations using alternative sampling strategies.

Conclusion
Due to the rise of social media and other digital channels, businesses have established relationships with consumers that extend beyond the sale of goods. Similarly, studies have demonstrated that consumers who actively engage with their preferred businesses on social media have a higher brand engagement overall. This study contributes to the corpus of knowledge on e-services by investigating how life insurance customers' virtual chat experiences influence their emotions and participation level. It demonstrates that a customer's level of trust in a company's service providers and governing bodies considerably influences their level of engagement, which in turn affects their loyalty. Although the researchers note several exceptions, they believe customer interaction will be the primary focus of future marketing research. The integration of data demonstrates that emotional and trust-based factors significantly impact consumer engagement and that these factors should not be examined in isolation. Efforts by businesses to gain a deeper understanding of the variables that influence consumers' propensity to purchase can result in increased value for both consumers and vendors. As social media and digital platforms evolve, it will be increasingly crucial to comprehend consumer engagement and the role of trust and emotion in influencing it.