E-loyalty formation of Generation Z: Personal characteristics and social influences

Singh, Ranjit; Sibi, P.S. Article — Published Version E-loyalty formation of Generation Z: Personal characteristics and social influences Journal of Tourism, Heritage & Services Marketing Suggested Citation: Singh, Ranjit; Sibi, P.S. (2023) : E-loyalty formation of Generation Z: Personal characteristics and social influences, Journal of Tourism, Heritage & Services Marketing, ISSN 2529-1947, International Hellenic University, Thessaloniki, Vol. 9, Iss. 1, pp. 3-14, https://doi.org/10.5281/zenodo.8054004 This Version is available at: https://hdl.handle.net/10419/272334 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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UDC: 658.8+338.48+339.1+640(05) http://doi.org/10.5281/zenodo.8054004 Published online: 10 June 2023 www.jthsm.grpyright © 200 Some rights reserved. Except otherwise noted, this work is licensed under https://creativecommons.org/licenses/by-nc-nd/4.0 E-loyalty formation of Generation Z: Personal characteristics and social influences Ranjit Singh Pondicherry University, India P.S. Sibi Pondicherry University, India Abstract: Purpose: This study examines the personal characteristics and social influence of Generation Z on their eloyalty towards tourism websites. In contrast to previous models, this study explores the effect of perceived compatibility and innovativeness (personal characteristics) and subjective norm (social influence) on perceived usefulness and trust on tourism websites, which in turn influence e-loyalty in a generational context. These factors are crucial in e-commerce, but they have not been studied together in the context of tourism, especially for Generation Z. Methods: Using a sample size of 389 respondents falling within Generation Z in India, the proposed model was validated using PLS-SEM. A quantitative approach was followed in this study and the data was collected by using a survey questionnaire. Results: Within the wider context of technology adoption, the findings show the decisive role of both personal characteristics and social influence in determining the e-loyalty of Generation Z towards tourism websites. Implications: The implications of understanding the e-loyalty of Generation Z may assist tourism firms in retaining them by developing and implementing effective marketing strategies. Moreover, the study’s most significant contribution is that it considers Generation Z, a generation that will shape the world’s future economy and a digital sector with significant purchasing power and influence. Keywords: e-loyalty; Generation Z; Perceived compatibility; Innovativeness; Subjective norm; Tourism websites JEL Classification: A13, C31, L84 Biographical note: Ranjit Singh ([email protected]) is a PhD scholar in tourism at the Department of Tourism Studies, Pondicherry University, Puducherry, India. His ongoing research is in the area of loyalty, tourism policy and planning and destination management. P.S. Sibi ([email protected]) is an Associate Professor at the Department of Tourism Studies, Puducherry, India. Her areas of interest are special interest tourism, loyalty, travel agency management, tour operation, accessible tourism, inclusive tourism, and gender. Corresponding author: Ranjit Singh ([email protected]). . 1 INTRODUCTION Commercial transactions on the internet, commonly referred to as e-commerce in tourism, have been growing significantly in recent years due to the advancement of information technology and its convenience for the customer to organize the trip, especially among the section of young consumers (Song et al., 2021). Consequently, travellers increasingly seek and use information from various sources, evaluate the information, and make a decision. Tourist destinations tend to change with a single "click". Therefore, tourism managers utilize websites to influence consumer's decisions, market tourism products, and attract and keep customers, thereby gaining commercial and financial benefits for their organizations (Buhalis et al., 2020). Considering all these reasons and factors such as customer acquisition cost, multiplayer competitive market with multiple channels, the intangible nature of tourism product, insecurity associated with e-commerce and high consumer demand, there is a significant interest among the scholars to understand online consumer behavior in tourism, particularly their e-loyalty (Abou-Shouk & Khalifa, 2017; Valvi & Fragkos, 2012). Finding elements that influence e-loyalty is essential to online travel websites, especially for generational cohorts like Generation Z, who are tech-savvy and extremely different from previous generations (Fernandes & Radebe, 2018). Existing literature on e-loyalty frequently focuses on technical aspects like website quality (Mahadin et al., 2020; Tsai, 2017) and security (Cui et al., 2018; Cui et al., 2015; 4 Ranjit Singh & P.S. Sibi Bui, 2022), or it is limited to relational factors like satisfaction (Christou, 2010; Jeon & Jeong, 2017; Parra- Lopez et al., 2018). For Generation Z, these technological and relational features might not be enough to explain their loyalty, given the influence of changing technology on their decision-making behavior. According to studies (Dimitriou & AbouElgheit, 2019; Priporas et al., 2017; Thees et al., 2021), Generation Z have distinct attitudes, characteristics, and behaviors compared to previous generations and targeting them is recognized as the most significant challenge in the future of marketing. More precisely, it warrants additional research on understanding the formation of eloyalty and developing new causal models from existing ones, given that this subject has received little attention and that, now more than ever, the website serves as a critical link between consumers and products. Research on e-loyalty studying Generation Z is crucial from both theoretical as well as managerial perspectives. Firstly, they have a population of 2.5 billion, with fastest income growth and it is expected to quadruple to about $33 trillion (Schroders Wealth Management, 2021). Secondly, they are also socially conscious, technologically savvy, and extremely innovative they seek change constantly, and are comfortable in the virtual world. Therefore, they are more likely to participate in activities like online shopping and have a different response to e-commerce than prior generations (Dimitriou & AbouElgheit, 2019). Generation Z customers have witnessed several political, social, technical, and economic shifts throughout their brief lifetimes. Therefore, “Consumers are less loyal to retailers, and they expect retailers to get the product to them, as a consequence retailers feel pressure to find new ways to grab and hold consumers’ attention. They have higher expectations, no brand loyalty and care more about the experience” (Priporas et al., 2017, p. 376). Additionally, they adopt innovative technologies particularly related to their lifestyle (Wood, 2013). Furthermore, remaining connected with their social-circle through social media is crucial in their lives. Therefore, the influence of social groups termed subjective norms is a critical factor influencing their behavioral intention, including loyalty (Broadbent et al., 2017; Krakover & Corsale, 2021). Hence, unlike their earlier generational cohort, social influence and personal characteristics can influence e-loyalty of Generation Z significantly. Therefore, the existing models of e-loyalty may have limitations while describing e-loyalty of Generation Z. Nevertheless, despite their importance as a potential niche market, studies reflecting the formation of eloyalty of Generation Z are limited (Martínez-González & Álvarez-Albelo, 2021; Nechoud et al., 2021) in the context of tourism especially the literature addressing the influence of personal characteristics and social influence. To fulfil this gap, this study has proposed and tested a novel model that may help understand the formation of e-loyalty from the perspective of Generation Z. By contextualizing the effect of personal characteristics such as perceived compatibility (Ahmet Bulent Ozturk et al., 2016) and innovativeness with new technologies (F Cui et al., 2018) and social factors like the subjective norm (Ruiz-Mafe et al., 2016) on their perceived usefulness and trust and the effect of perceived usefulness and trust on their e-loyalty, the study has validated the proposed model using PLS-SEM. Finally, following the other tourism researchers, the study has also included an Importance-Performance Analysis (IPMA) to aid the process (Martínez-González & Álvarez-Albelo, 2021). Moreover, the investigation of this group represents a generational approach that has the potential of generalizability because homogenous online marketing activities may be adopted on a worldwide scale. 2 LITERATURE 2.1 E-loyalty and its drivers According to Anderson & Srinivasan, (2003, p. 125) “eloyalty is defined as the customer's favorable attitude toward an electronic business resulting in repeat buying behaviour”. E-loyalty, or online loyalty is the consumers intention to repurchase and revisit a website even though other websites are available (Cyr, 2008). Tourism literature defines it as an attitude of preference or favorability toward a travel website, which results in a desire to purchase from it (Cui et al., 2018). With the development of e-commerce in tourism, a growing interest has been observed among scholars in understanding e-loyalty (IJspeert & Hernandez-Maskivker, 2020; Purwanto, 2022). Consumer e-loyalty is now considered to be one of the most crucial issues for academics and industry professionals involved in marketing and management of tourism (Mahdzar et al., 2022). This is because it allows developing and maintaining a continuously beneficial relationship with consumers, leading to increased sales and profits for tourism businesses (Chatzigeorgiou, 2017; Abou-Shouk & Khalifa, 2017). Retaining an existing customer is a financial imperative for online businesses as soliciting new customers is considerably expensive (Lin & Luarn, 2003). Moreover, online loyalty has been examined less than offline loyalty, with very little research being done in the tourism industry and much lesser research is being done among young people compared to other segments (Buhalis et al., 2020). When it comes to defining and measuring e-loyalty in the tourism industry, there is no general agreement. Indeed, in the research, e-loyalty has been primarily regarded as an extension of offline consumer loyalty (Gommans et al., 2001). Just as it does in the offline context, an attitudinal approach to loyalty predominates over a behavioral approach (McKercher et al., 2012) in the literature. However, it has been argued that intention is a better predictor of actual behavior (Amaro & Duarte, 2013; Buhalis et al., 2020). The Technology Acceptance Model has served as the basis for the vast majority of the research that has been done on eloyalty. This model developed by Davis et al., (1989) has been extended, modified and applied in various research settings (Amaro & Duarte, 2015; Lew et al., 2020; Pavlou, 2003). Both ease of use and usefulness continue to be essential elements in TAM models, which are used to judge whether new technologies are adopted or if users remain loyal to existing technologies online. The current research takes this broad framework as its starting point and acknowledges the essential role that trust and perceived usefulness play in shaping the e-loyalty of Generation Z to online travel websites. On the other hand, this study considers a set of personality traits and social influence as extraneous variables rather than features relevant to the evaluation of the technology itself. The report E-LOYALTY FORMATION OF GENERATION Z: PERSONAL CHARACTERISTICS AND SOCIAL INFLUENCES 5 concentrates on behavioural aspects associated to a certain section of customers known as Generation Z. As a result, the innovation diffusion model is being utilised in this investigation in order to establish the antecedent variables. The innovation diffusion model has been utilised to explain the online purchasing behaviour in a variety of settings (Min et al., 2019). This model highlightss the factors influencing the attitude towards a new market offering. The factors include personal innovativeness, nature of the innovation, the uncertainty or risk factors (Purani et al., 2019). Primarily, based on this theory, this study considers perceived compatibility, subjective norm, and innovativeness as the variables influencing perceived usefulness and trust, which in turn affects loyalty of the customer. 2.2 Generation Z People born between 1995 and 2010 are called Generation Z (Katz et al., 2022). They are true digital natives because they have grown up with access to digital technologies such as the internet, social networks, and mobile devices. As a result, they are adept at using these tools to gather information from a variety of sources, analyse it, and draw meaningful conclusions. Younger generations favour the Internet as a source of knowledge since it is the most accessible and userfriendly information resource (Puiu et al., 2022). They are brand-savvy shoppers who have seen it all and know exactly where to look for the products they desire. They are more analytical and pragmatic in their decision making and interactions with institutions; they view consuming as a right of passage rather than a commodity; they see it as a means of expressing their unique sense of self; and they become increasingly concerned with ethical issues (Baltescu, 2019). According to Thangavel et al. (2022), today’s youth value autonomy above obedience, are independent yet value teamwork, seek happiness, and need guarantees about their future. Although wealth, education, occupation, family size, composition, and so on all have a role in determining whether or not an individual decides to take a vacation, the literature often analyses tourism consumption behaviour without explicitly invoking the life cycle model. However, cohort effects are quite powerful in influencing vacation-planning decisions (Baltescu, 2019). According to research by Haddouche & Salomone (2018), young travellers who identify as part of Generation Z can be challenging to keep as customers because of their pampered nature. The travel habits of Generation Z, represent a departure from the norm when it comes to how tourists interact with the local environment and community (Baltescu, 2019). 3 HYPOTHESIS DEVELOPMENT 3.1 Perceived compatibility Research has shown that members of Generation Z prefer products and services that are compatible with their lifestyle and value systems (Broadbent et al., 2017). Additionally, perceived compatibility has been shown to be a crucial personal characteristic that influences the willingness to use electronic wallet of Generation Z (Do & Do, 2020). Generation Z has never known life without the internet, unlike previous generations. Since birth, they have been exposed to the internet, so they have a strong grasp of technology and are accustomed to using it (Goh & Lee, 2018). Therefore, they would be more likely to use online travel websites (Vieira et al., 2020). It is expected that customers will adopt more quickly if they perceive that online purchases do not conflict with their interests and preferences (Peña-García et al., 2020; Nella & Christou, 2021). Since online purchases match their values, lifestyle and habits of Generation z, they develop a sense of trust on the online travel websites. Previous studies also support that compatibility positively influences trust (Cazier, 2003; Cazier et al., 2002). Türker et al. (2022) concluded that perceived compatibility positively influence trust. Similarly, Williams et al. (2017) also identified a significant relation between perceived compatibility and trust. In the online travel website context, usefulness describes how a particular website can facilitate accomplishing shoppingrelated tasks. Generally, technology-compatible people instantly regard the technology as consistent with their preexisting thoughts about the technology and their requirements for it. As a result, usability beliefs are easily triggered. People from Generation Z, are known for their innovativeness, and their strong ideas regarding the usability of emerging technologies (Purani et al., 2019). Previous literature supports a statistically significant association between compatibility and perceived usefulness (Agarwal & Karahanna, 1998; Crespo & Rodríguez, 2008). Türker et al. (2022) identified perceived compatibility strongly influence perceived usefulness in the online context. Purani et al. (2019) also concluded that perceived compatibility of the website significantly determine the perceived usefulness. Therefore, the study hypothesizes that H1. Perceived compatibility of travel websites has a positive and direct influence on perceived usefulness. H2. Perceived compatibility of travel websites positively influence trust. 3.2 Perceived innovation The degree to which an individual is receptive to new technical ideas and eager to experiment with that technology is defined as innovativeness in new technologies. It is a personality trait that motivates customers' initial desire to experiment with new technologies before their actual experience with any particular technology (San Martín & Herrero, 2012). This characteristic makes these innovators an attractive segment for businesses looking to stimulate innovation in technological environments (Ciftci et al., 2021). As members of Generation Z have grown up alongside information technology, they have demonstrated to be highly tech-savvy. As a result, they are more likely to adopt new technological innovations - whether it is for e-commerce transactions or social media consumption (Dimitriou & AbouElgheit, 2019). Kwon et al. (2007) have shown that highly innovative customers create favorable opinions about certain technological advances and are also open to taking risks. These opinions will reflect in their beliefs about the usefulness (Purani et al., 2019). Also, studies (Fagan et al., 2012; Parveen & Sulaiman, 2008) have demonstrated that innovativeness with new technologies positively influences perceived usefulness. Purani et al. (2019) identified 6 Ranjit Singh & P.S. Sibi innovativeness positively determines the perceived usefulness in the online purchase context. It is also worth noting that customers may gain more intrinsic benefits if the new information system is more innovative (Venkatesh et al., 2012), creating trust in its usability. According to previous studies (Cui et al., 2018), consumer innovativeness directly influences trust. Consumers' perceptions of a company's trustworthiness are formed based on their previous experiences; therefore, it is believed that perceived innovation will have an impact on trust (Konuk, 2019). Moreover, An et al. (2022) also identified a positive relation between innovativeness and trust. Thus, this study hypothesizes: H3. Innovativeness will have a direct and positive influence on perceived usefulness. H4. Innovativeness will have a direct and positive influence on influence trust. 3.3 Subjective norm Subjective norm explains the extent to which a customer's behaviour is influenced by the perceptions of peer groups, friends or colleagues, and relatives (Hasbullah et al., 2016). Subjective norms are important for technological acceptance because they help reduce perceived risk (Purani et al., 2019). Generation Z trusts their peer groups (Fontein, 2019). As a result, their loyalty formation is based on peer recommendations (StudentBeans, 2021). In their seminal paper, Davis et al. (1989) reported that people tend to use technology more because of what other people want them to do and because of their own feelings. TAM2 model identifies subjective norms significantly influence perceived usefulness (Venkatesh & Davis, 2000). Studies have further ratified this assumption (Kim et al., 2009; Purani et al., 2019). Türker et al. (2022) identified subjective norm strongly influence perceived usefulness and trust in online context. Gong et al. (2019) confirm that the subjective norm is also a predictor of trust in the online context. While using technology, people may rely on the opinions of those who are important to them and then build trust beliefs in the system accordingly (Li et al., 2008). Furthermore, previous studies have revealed that subjective norms significantly influence trust (Chaouali et al., 2016; Wu et al., 2008). Thus, this study hypothesizes: H5. Subjective norms positively influence perceived usefulness. H6. Subjective norms positively influence trust. 3.4 Trust Trust is crucial for any transaction involving a buyer-seller relationship, particularly those that contain an element of risk such as interacting with e-commerce websites. Using an online travel website generally requires customers' personal and financial information. Therefore, customers may have concerns about security and privacy level to limit the amount of risk and support their decision to utilize travel websites (Kim et al., 2011). Pavlou (2003) confirms trust significantly influences perceived usefulness in consumer acceptance of ecommerce. Other studies (Alalwan et al., 2018; Aloudat et al., 2014) also discuss and supports trust positively influences the perceived usefulness of the technology. Online customers remain loyal to the trusted websites. Previous research (Cui et al., 2018; Purani et al., 2019) have shown that trust positively influences e-loyalty. Particularly the study (Thomas et al., 2018) confirms the influence of trust on e-loyalty in the context of Generation Z. Thus, this study hypothesizes: H7. Trust on the website positively influences perceived usefulness. H8. Trust on the website positively impact e-loyalty. 3.5 Perceived usefulness Perceived usefulness could be defined as the benefits achieved via the use of technologies (Davis, 1989). These perceived benefits may relate to how customers perceive usefulness of travel websites to accomplish their tasks, saving them time, effort, and money (Alalwan et al., 2018). Previous literature (Cyr, 2008; Purani et al., 2019) supports existence of a relationship between perceived usefulness and e-loyalty. According to Hsu et al. (2013), perceived usefulness is an important variable in determine the e-loyalty of the customer. The same proposition is a also supported by Chiu et al. (2009).Thus, this study hypothesizes: H9. Perceived usefulness of travel website positively influence e-loyalty The proposed hypothesized model and hypotheses are shown in Figure 1. Figure 1: Conceptual model 4 RESEARCH METHODOLOGY 4.1 Research design and data analysis The research was conducted between February and April 2022 utilizing a quantitative method. This study adopts a descriptive and causal approach. The reason for applying PLS-SEM in this study is its benefits in studying behavior of humans and its excellent predictive capability when employing reflecting indicators and a wide variety of sample sizes (Hair et al., 2012). An Importance-Performance Analysis (IPMA) was also conducted to recognize the variables that need to be managed to foster e-loyalty among the Generation Z (Buhalis et al., 2020). 4.2 Data collection This research is conducted to understand the online loyalty of a specific generational cohort called Generation Z. Therefore; this research needed respondents who were born in and after 1995. As a result, the study surveyed graduate and postgraduate students in India particularly Odisha because of E-LOYALTY FORMATION OF GENERATION Z: PERSONAL CHARACTERISTICS AND SOCIAL INFLUENCES 7 their age and better level of education than the general public, students have a significant commercial and influential value, and they are an adequate depiction of virtual consumers (Buhalis et al., 2020). These academic students are considered a major target market for online retailers because of their computer literacy (Buhalis et al., 2020). A paperbased survey based on convenience sampling was conducted to collect the responses. We asked the respondents to consider their most often visited online travel website and then reply based on their last six-month experience with that particular online travel website. Totally, 430 questionnaires were distributed to collect the data. However, of the total questionnaires, a total of 389 valid questionnaires were received and used in this research. In the responses received, 65% were male, and 35% were female, and the response rate was 90.47%. They were all born between 1995 and 2002. 4.3 Variable and measurement The dependent variable is e-loyalty, and the independent variables are compatibility, innovativeness, subjective norm, perceived usefulness and trust. All the variables are measured using the standard scales available in the literature focusing on the online purchase based five-point Likert scale. The indicators measuring the Perceived usefulness and trust variables were adopted from studies (Cui et al., 2018; Purani et al., 2019). The scales for compatibility, innovativeness, eloyalty and subjective norm measurement were adopted from previous studies (F Cui et al., 2018; Purani et al., 2019; Vijayasarathy, 2004). The construct compatibility and subjective norms were measured using three indicators each. Innovativeness was measured using four indicators. Perceived usefulness and trust had six and four indicators respectively. The dependent variable e-loyalty was measured by three indicators. All the indicators and their adopted sources are shown in Table 1. Table 1: Scale indicators 4.4 Common method bias In behavioral research, common method bias is a potential concern.. Therefore, scholars have recommended examining the collected data for any common method variance that may occur as a result of using a single survey method (Ali et al., 2018). Based on the suggestions of Kock & Lynn (2012), the study used the full collinearity VIFs among all the variables in the model to check the common method bias. This study identified that the values were less than 5 indicating there was no serious issue of common method variance (Hair et al., 2011). 5 RESULTS 5.1 Measurement model Reliability was measured using the internal consistency reliability and indicator reliability based on composite reliability and indicator outer loading, respectively (Hair et al., 2011). All the values related to the evaluation of reliability were found in the acceptable range. The Cronbach's alpha, the outer loadings and composite reliability values are greater than 0.70 (Hair Jr et al., 2016) (Table 2). These results verify that the measurement model is internally consistent and valid. Table 2: Construct reliability and validity Convergent validity was found adequate because Average Variance Extracted (AVE) values were greater than 0.5. This study used Fornell-Larcker criterion to measure construct validity (Fornell & Larcker, 1981). The square roots of the AVE of each construct (diagonal value) were greater than its corresponding correlation coefficients (Table 3), indicating each construct is significantly different from other constructs (Hair et al., 2012). Furthermore, Table 3 also represents discriminant validity based on the result of another criterion called the heterotrait–monotrait (HTMT) ratio of correlations (Henseler et al., 2015). As indicated in Table 3, all the values below the threshold value (less than 0.85) demonstrate that all the constructs are empirically unique and have no discriminant validity issue. 8 Ranjit Singh & P.S. Sibi Table 3: Discriminant validity 5.2 Structural model This study used the non-parametric procedure bootstrapping to estimate the p-value, path coefficients and t-value for the hypothesized relationship (Hair et al., 2012). PLS-SEM method produces the estimation using sample data that best predict the endogenous construct. As a result, it has no standard goodness-of-fit indices for evaluating the structural model. Therefore, the overall model fit is primarily evaluated using R2, Q2, and path coefficient values in PLS-SEM models (Ali et al., 2018). Tenenhaus et al. (2005) suggest another operational solution to address the issues by recommending goodness-of-fit (GoF) criteria. This index is meant for validating the PLS model globally. The baseline values of GoF to validate the PLS model are small=0.1, medium=0.25 and large=0.36 (Wetzels et al., 2009). The results of this analysis showed that the GoF was 0.558, which led us to the conclusion that the model is fit (Table 4). Table 4: R2, Q2 and GoF test Table 4 shows the value of R2. It is a measure of the model's predictive accuracy, which varies between 0 and 1. Perceived 4compatibility, subjective norm and innovativeness explain 46.8% of trust, whereas perceived compatibility; subjective norm, innovativeness and trust explain 62.2% of perceived usefulness. Trust and perceived usefulness predicts 29.3% of e-loyalty. In all the case of endogenous latent variables, the value of R2 were above the acceptable level proposed by Hair et al. (2015). Additionally, the Cross-validated redundancy (Q2) method was used which measures the predictive relevance of a structural model (Hair et al., 2014). The study estimated the Q2 value for each construct using the sample reuse technique of blindfolding. It is an evaluation criterion for the PLS path model's cross-validated predictive significance (Faizan Ali et al., 2011). As shown in Table 4, the value of Q2 for perceived usefulness, trust and e-loyalty are 0.373, 0.316 and 0.204, respectively indicating the exogenous constructs have predictive relevance since the values are greater than 0. The result of the structural model and hypotheses are presented in Table 5 and Figure 2. All nine hypotheses are supported regarding the causal relationship since the p-value is significant. Perceived compatibility, subjective norm and innovativeness significantly influence trust. Furthermore, the study identified Perceived compatibility, subjective norm, innovativeness, and trust significantly influenced perceived usefulness. The result also revealed that perceived usefulness and trust are significant predictors of e-loyalty. For all the causal relationships, the magnitude effect is strong. Thus, the exogenous latent construct contributes significantly to explaining the endogenous latent construct. Table 5: Path coefficients and p-values Figure 2: Structural model 5.3 Importance-performance analysis Additionally, the study conducted Importance-Performance Analysis (IPMA). It is an easily applied technique developed by Martilla & James (1977) to measure the importance and performance of the attributes that can yield useful insight for the firm regarding the aspects which needs more attention. It identifies the relative importance of predecessors in explaining the target construct based on the strong total effect to draw conclusions. In addition, it also accounts for the performance of the each constructs based on the their average scores (Ringle & Sarstedt, 2016). According to Streukens et al. (2017), PLS-SEM IPMA has several advantages over traditional IPMA. PLS-SEM is a critical analytical tool for determining the significance score because it can examine a complex grid of relationships that connects various drivers to a single construct. Second, PLS-SEM allows for the inclusion of latent constructs in the IPMA analysis. Figure 3 shows the IPMA result for the dependent variable of e-loyalty. The IPMA result estimated that in order to predict e-loyalty, E-LOYALTY FORMATION OF GENERATION Z: PERSONAL CHARACTERISTICS AND SOCIAL INFLUENCES 9 perceived usefulness (0.39) has the highest importance, followed by trust (0.28) and innovation with new technologies (0.27). All three variables are close to the maximum productivity line and necessitate immediate attention in terms of resources (Bacon, 2003). Figure 3: Importance-performance map 6 DISCUSSION In this research, we validate the influence of personal characteristics and social influence on the e-loyalty of Generation Z customers. Many studies have been conducted to understand the factors that influence online loyalty formation. However, in the context of Generation Z, the extant literature has no evidence highlighting the importance of personal characteristics and social influence in e-loyalty formation. Tourism scholars have argued that travel behavior varies across generations, emphasizing the importance of identifying the specific expectations of each generation (Gardiner et al., 2014). Compared to the previous generation, the change in attitudes and behaviors among Generation Z is a concern for marketers due to their differences from previous generations. Most importantly, it is a topic of high priority for marketers to foster loyalty among Generation Z (Dimitriou & AbouElgheit, 2019). Interestingly, it is challenging for all marketers to identify the factors that could help capture and retain their loyalty (Ayuni, 2019; Papana & Spyridou, 2020; Samitas et al, 2020). As a result, for the advancement of theory, it is critical to identify the antecedent elements that are relevant to Generation Z. Many studies have sought the impact of many antecedent factors such as website design and eWOM (Buhalis et al., 2020), website personalization, website usability and website content (Martínez-González & Álvarez-Albelo, 2021), e-service quality and online customer value (Ayuni, 2019), customer experience (Fernandes & Radebe, 2018) on e-loyalty. Though these elements may have an impact on the loyalty formation process of Generation Z, personality characteristics and social influence have an significant impact in determining their e-loyalty (Purani et al., 2019). The study identified that innovativeness is an important antecedent of perceived usefulness and trust among the Gen Z. It has been confirmed that personal innovativeness has a significant relationship with perceived usefulness and trust. This is similar to Priporas et al. (2017), who identified that Generation Z are more focused on new innovation in humancomputer interactions in an e-retail settings. Gen Z is the generation that drives innovation further upward by utilizing emergent technology, hyper-connectivity, and cooperation (Morgan, 2016). According to Wood (2013), innovation is one of the important trends in Generation z, and they have more choices in the marketplace than their predecessors. This generations’ willingness to spend money on technological and design-based innovation is high. Both Generations Z and Y often share many characteristics. Previous research (Purani et al., 2019) on Generation Y also identified innovation with new technologies is a significant factor for eloyalty. Additionally, the study found out that the perceived level of technology compatibility influences perceived usefulness and trust. While booking tourism products and services online is gaining importance in India, some unexplored market segments are still yet to be served (Behera & Dash, 2019). Technology compatibility and innovativeness are critical in the context of e-retailing (Purani et al., 2019). Compatibility evaluates how well an existing technology is consistent with consumption practices that are used to accomplish consumption goals (Lim et al., 2022). Hence compatibility is associated with an individual's values, past experience, lifestyle and needs (Rogers, 2010). Moreover, studies already support the influence of perceived compatibility on perceived usefulness and trust which in turn influences e-loyalty in the context of tourism and hospitality (Amaro & Duarte, 2015; A B Ozturk et al., 2016; Wang et al., 2016). Furthermore, a review conducted by Morosan & Bowen, (2018) reports that compatibility is a crucial antecedent of e-loyalty. For Generation Z, it is usual to buy travel and tourism products from online websites since they are "digital natives," having grown up in a digitized world where they perform most of their tasks on a digital device (Hameed & Mathur, 2020). According to Fernandes & Radebe (2018), they expect a digital platform to be available for everything they do, whether buying food online, playing games, learning, reading, or watching television. Interestingly, when purchasing a tourist product, more than 95% of the younger generation use the Internet (Martínez- González & Álvarez-Albelo, 2021). It indicates that booking tourism products online is compatible with the existing value, lifestyle, and needs of Generation Z. As a result, the study emphasizes the need to enable compatibility to attain higher levels of e-loyalty. Subjective norms are found to impact both perceived usefulness and trust. Subjective norms are especially important because Generation Z highly trusts peer networks and their perspectives (Silva et al., 2017). They are the earliest generation to have grown up in a digital era of advanced technological developments, making them one of the most active social media platform users, frequently exchanging information and conversing with their peers online (Kitchen & Proctor, 2015). According to Broadbent et al. (2017), "For all the rapid pace of change, young people overwhelmingly say that their values were influenced by traditional sources – parents (89%) followed by friends 10 Ranjit Singh & P.S. Sibi (78%) and teachers (70%)" (p. 10). Therefore, peer approval is extremely essential to them because they need to feel like they belong somewhere. Thus, when it comes to the behavioral responses that result in loyalty, they are heavily influenced by peer recommendations. Previous studies also emphasize that subjective norms significantly influence the behavior of Generation Z (Goh & Jie, 2019; Goh & Lee, 2018; Kamenidou et al., 2019; Korol & Spyridou, 2020; Nuryyev et al, 2021) 7 CONCLUSIONS AND IMPLICATIONS This paper responds to an important concern of academicians regarding the process by which Generation Z forms e-loyalty, particularly to online travel websites. In this study, we address two crucial characteristics (personal characteristics and social influence) and their influence on the e-loyalty behaviour of the Generation Z travellers. Previously, authors (Purani et al., 2019) have considered these variables are important for e-loyalty formation and have not been examined together in the context of travel and tourism particularly Generation Z. From the best of our knowledge, this is the first model in tourism which considers both social influence and personal characteristics and their influence on e-loyalty. The most significant contribution of the study is that it considers Generation Z, a generation that will shape the future economy of the world (Broadbent et al., 2017; Spyridou, Polyzos, & Samitas, 2023). This is necessary because of the commercial and financial benefits that eloyalty generates, especially with respect to Generation Z, a digital sector with significant purchasing power and influence. Studying e-loyalty of young consumers is also gaining momentum because of the insecurity associated with purchasing tourism products online due to their intangible nature and the insecurity of e-commerce itself which hampers its growth (Buhalis et al., 2020). From the theoretical perspective, a model describing the eloyalty formation of Generation Z has been developed and validated using SEM. The results were statistically significant thus contributing to theoretical development of the sparsely studied concept of e-loyalty among Gen Z travellers. Further, the proven rigour of the SEM allowed us to generate a causal model which significantly predicts the antecedents of e-loyalty among Gen Z in a tourism context. Other authors have successfully employed this methodology in connection to the variables used (Buhalis et al., 2020). This study has several theoretical contributions. First, Generation Z is increasingly becoming the dominant demographic in the market, and it is essential to get the attention of this group by appealing to the special characteristics they exhibit online. In this light, the research offers some guidance on how to develop an e-loyalty that will appeal to members of Generation Z. Second, most studies of the studies have been conducted based on the website evaluation factors undermining the influence of personal characteristics and social influence. Therefore, the study theoretically contributes to the literature by extending the understanding of e-loyalty concept considering the perceived compatibility, innovativeness and subjective norm in the context of Generation Z. Third, the study highlights perceived usefulness and trust are the two measure determinates of e-loyalty for Generation Z. This would assist the scholar to broaden the concept in terms of e-loyalty and compare and contrast the findings of this study with other generational cohorts. Four, the study contributes to the literature by explaining the factors creating the usefulness of the website and building trust. The study has practical implications for tourism companies. From the practitioner's point of view, understanding the eloyalty of Generation Z is an important aspect for tourism companies helping them formulate and implement successful marketing initiatives. The model developed in the study will be a valuable tool for managers. It allows them to clearly identify the target population based on personal characteristics and the social influence of a specific generational cohort with distinct traits. Additionally, Due to its predictability and generalizability practitioners can find this study useful for market segmentation and planning operational strategies. 7.1 Limitations and future suggestions Like other studies, it has its own set of limitations and suggests areas for future investigation. Loyalty is difficult to measure since several factors affect loyalty formation. This study tries to understand loyalty formation considering only some personality traits and subjective norms. There are other personality characteristics such as perceived behavioral control, risk aversion, need for cognition, etc. They influence e-loyalty and the adoption of electronic commerce technologies. It could be interesting to probe how these factors influence the loyalty of Generation Z. 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