Management Dynamics Management Dynamics

Abstract Over the years, social media usage has become an inseparable aspect of the travel experience. This study examines the factors that influence Indian travellers' use of social media when travelling abroad for a leisure vacation by incorporating social capital, perceived trust, and dispositional readiness toward social media into the Technology Acceptance Model (TAM). A survey was used to collect data from 280 Indian travellers who had taken at least one international vacation over the last one year. A Structural Equation Modelling using AMOS software revealed that the perceived usefulness (PU) of social media and social capital (SC) of an individual directly impacts the intention to use social media for travel purposes. Perceived ease of use (PEU) and perceived trust (PT) impact intention only indirectly, through their influence on usefulness. Further, the study concludes that the dispositional readiness (attitude) of the users will significantly impact all four constructs, PU, PEU, PT, and SC. Theoretically, the results of the study empirically establish the need for modification to the existing TAM. Although the current model suggests a unidirectional impact of PU and PEU on attitude, our study shows that DR (attitude) impacts PU and PEU. The study also adds to our understanding of SM usage for leisure travel purposes, in addition to providing useful insights into the Indian hospitality and tourism industry.


Introduction
O ver the years social media (SM) have gained significant attention in the hospitality and tourism industry (Kavoura & Kefallonitis, 2019) and have become an inseparable part of the travel experience.The tourism industry is a highly information-based and information-intensive industry (R athonyi, 2013) where SM is used not only for information search but for the overall travel process.The dependence on SM becomes higher for leisure travellers, whose travel patterns are remarkably different from that of business travellers.Unlike the latter, where the destination and duration are usually fixed, for leisure travellers, the destination, duration, and accommodation options are not pre-decided and require active decision-making.This leads to a greater need for information.Travellers turn to social media to mitigate the risk associated with travel (Dwityas & Briandana, 2017;Țuclea et al., 2020).Further, they are more prone to sharing their travel pictures and experiences online, leading to higher use of SM during and after the vacation.Social media influencers are known to impact purchase decisions (Attri & Bhagwat, 2023;Chaudhary, 2022).The user-generated content (UGC) that travellers put in online travel forums as travel reviews is also a means of sharing travel-related experiences and information (Bulencea & Egger, 2013a, 2013b).The reliance on SM for travel has drastically increased in recent pandemic times largely for risk mitigation (Singh & Srivastava, 2023).
Given this large-scale usage of SM during travel, there has been an upsurge in the research on the use of social media in hospitality and tourism in recent times.There have been studies related to the use of social media by travellers.Some have restricted themselves to a specific type of social media like Facebook (Latif et al., 2020;Marder et al., 2019;Sotiriadis & Van Zyl, 2013), Twitter (Dietz et al., 2020), YouTube (Huertas, 2018) or consumer review sites (Briciu & Briciu, 2020).Others have focused on a particular phase of the travel process e.g.travel planning and the choice of tourist destinations (Kang & Schuett, 2013) or sharing content post-travel (Oliveira et al., 2020).These studies underline the need for more empirical exploration of the factors that lead to this large-scale SM adoption by travel consumers in their entire travel process.
Further, most of our understanding of travel behaviour relates to Anglo-Western viewpoints (Cohen et al., 2014;Winters, 2009).Cohen et al. (2014) called for a better understanding of the travel attitudes of BRIC (Brazil, Russia, India, China) nations.Kumar et al. (2022) have investigated the various criteria that enhance tourism in India and the motivating factors that shall help people spend their leisure time.However, there is a limited understanding of travel and social media usage in the context of developing nations (Osei & Abenyin, 2016).There is enough evidence to prove that cultural differences affect the usage of social media (Brandtzaeg, 2010;Fotis et al., 2011;Hodeghatta & Sahney, 2016;Pookulangara & Koesler, 2011;Trepte & Masur, 2016).Considering the above facts, it becomes imperative to study the factors leading to the adoption and social media use for travel-related purposes in developing countries.
India, with rising growth in the outbound travel industry, provides a perfect setting to conduct such a study.To date, studies in India related to social media have been few.Some recent ones include Kamboj and Rahman (2017), Raman and Choudary (2014), Sakshi et al. (2020), Singh andSrivastava (2019), andSingh et al. (2019).Mishra and Satish (2018) studied technology adoption by adolescents.Singh and Srivastava (2019), through a series of semi-structured interviews, proposed a conceptual model to predict SM usage by outbound leisure travellers by extending the Technology Acceptance Model (TAM).This study aims to achieve two objectives.The first is to identify the factors that lead to social media adoption and usage by Indian travellers during their entire travel period of international leisure vacations.Second, it attempts to investigate the impact of dispositional readiness (DR) towards social media usage on these factors.

Literature review and hypotheses development
This study's conceptual framework was derived from the Technology Acceptance Model (TAM).TAM was developed by Davis (1989) to explain the acceptance of new technology inside an organization (TAM).He suggested that attitude that leads to behavioural intention was a product of two constructs, Perceived Ease of Use (PEU) and Perceived Usefulness (PU).He empirically proved that the adoption of new information technologies by the workers in any organization depended on its PU and PEU.He defined PU as the extent to which an individual believes that employing a particular system would improve his or her job performance.Since the model was proposed for explaining the acceptance of technology within an organizational context, the assumption was that workers would use technology only so long as they perceive it useful for achieving their desired results.Subsequent studies have seen the applicability of TAM outside the organizational context.For example, Dieck et al. (2018), Nguyen et al. (2021) and Rauniar et al. (2014) used it to explain the individual's adoption of social media.Assaker (2020), Ayeh et al. (2013), andMendes-Filho et al. (2018) confirmed the applicability of TAM in the context of travel planning.The present study aims to explore the intent to use social media content while travelling.

Perceived usefulness
Travellers will be tempted to use a new technology only if they find it useful to fulfil some specific need.For the current study, PU is mentioned as the degree to which social media help meet the travelrelated needs of an individual.These needs could be physiological, psychological, sociological, or material in nature (Rauniar et al., 2014).A number of TAM meta-analyses (Ukpabi & Karjaluoto, 2017;Yousafzai et al., 2007), as well as independent studies (Amir et al., 2020;Kurniawan et al., 2022;Shao, 2020), have established a strong relationship between PU and intention to use.Hence, we can hypothesize that the perceived usefulness of SM will positively impact the intention to use it for travel purposes.
H1. PU will positively impact the intention to use SM for international leisure vacations purposes.

Perceived ease of use (PEU)
Perceived Ease of Use (PEU) is the extent to which a person perceives that utilising a specific technology would not require effort (Davis et al., 1989).If the user finds the technology challenging, he/she will stay away from it.In this study, it refers to how easily travellers can operate SM sites.Travellers have several options at their disposal to meet their travel needs.They prefer to use SM provided they find it easier to access and use than other available alternatives.The social media site should be able to provide them with the information they are looking for or help them to share experiences with minimum effort.The sites should be intuitive, easy to navigate, and satisfy the travel needs of the users (Raunair et al., 2014).If SM sites are perceived to be complicated, they will be avoided altogether.Ease of use also impacts the perceived usefulness of technology.Higher the ease of use, the higher the perceived usefulness of SM.PEU has been established as an important antecedent for perceived usefulness (Moslehpour et al., 2018;Raza et al., 2017).The association between PEU and intention to use has been established in several previous studies (Amir et al., 2020;Rauniar et al., 2014;Shao, 2020).This helps us formulate the following two hypotheses.H2.PEU will positively impact the intention to use SM for international leisure vacations purposes.
H3. PEU will positively impact the intention to use SM for international leisure vacations purposes.

Perceived trust
The concept of Perceived Trust (PT) has been explored and established as an important extension to TAM, especially where online technologies or ecommerce is concerned (Beldad & Hegner, 2018;Siagian et al., 2022;Singh & Sinha, 2020).It has proven to be important for SM adoption and usage (Rauniar et al., 2014;Teng et al., 2014) in general, and for travel-related purposes in particular (Ayeh et al., 2013).Sharma et al. (2020) also confirmed the impact of trust on the online purchase of travel products.For the current study, PT is described as the confidence that the information found on social media for travel purposes is objective, reliable, and relevant (Singh & Srivastava, 2019).Often prospective travellers mistrust online opinions due to the lack of face-toface interaction and the absence of accountability of the written content (Hajli & Lin, 2016;Sparks & Browning, 2011).The Times ran an investigation that reported a third of all online reviews on TripAdvisor to be fake (Ellson, 2018).These pieces of information not only decrease the trustworthiness of the site, but of overall SM sources in general.On the other hand, there have been studies that indicate that SM content in the form of e-WoM, blogs, FB posts, etc. enjoy higher trust than company-promoted sites (Fotis et al., 2011;Gretzel & Yoo, 2008).Another manifestation of PT is the belief that personal information shared on SM will not be misused.Rauniar et al. (2014) mention the elimination of concern regarding privacy or safety issues of the material posted online.If travellers do not trust the information provided on SM, they will not use it for their travel-related needs.Thus, it is proposed that perceived trust of SM content will impact the Perceived Usefulness of SM.It would also directly impact the intention to use SM for travel goals.
H4. PT will positively impact the PU of SM for international leisure vacations purposes.
H5. PT will positively impact the intention to use SM for international leisure vacations purposes.

Social capital
Social capital (SC) is the tendency of individuals to connect with each other on a regular basis, beyond the sphere of work or home, and to participate in community affairs (Hall, 1999).According to Putnam (2000), social capital refers to the association between people, their social networks, and the related norms of reciprocity and trustworthiness.Individuals having a big social circle, who enjoy meeting and interacting with individuals beyond immediate work or family, can be said to have a high SC.For online interactions, social capital is indicative of the online social circle and interactions of individuals.SC has been established as one of the primary motivations for SM usage (Cristescu & Balog, 2018;Ellison et al., 2007).They found a definite relation between FB use motivation and the creation of SC.Similarly, Oeldorf-Hirsch and Sundar (2016) found social connections and reaching out to others were among the primary motive of individuals sharing photos online.Hsu and Lin (2008) identified community identification to be one of the motivations for participation in blogs.One of the key reasons people utilise social media was found to be social interaction or connectivity (Barker, 2009;Quan-Haase & Young, 2010).Hence, we may hypothesize that the social capital of an individual will have a significant positive effect on the use of SM for travel.
H6. SC will positively impact the intention to use SM for international leisure vacations purposes.

Dispositional readiness
The term disposition has been described by Buss and Craik (1983) as commonly displayed trends in actions.A similar set of actions put together constitute the disposition of an individual.Katz and Raths (1985) define disposition as a collection of routine and automatic acts that appear intuitive or spontaneous.Extending the same concept to the current context, The user's dispositional readiness (DR) would indicate a propensity to participate in social media (SM).Though DR has not been studied in conjunction with TAM previously, a similar construct, attitude, was a part of the earlier TAM Model (Fig. 1).It was suggested that the ease of use and usefulness help form the attitude towards technology usage which would lead to intention and ultimately adoption.In later TAM studies we find that the construct attitude was done away with completely as it was not found to have any significant impact on technology usage (Teo, 2009).In fact, studies "found the attitude construct in the TAM to be unnecessary" (ibid, p.1141) (Fig. 2).Thus, the role of attitude on intention has been a matter of contention.Some studies reported it as in independent variable impacting intention (Hussein, 2017; Shao, 2020) while others found it dependent on PU and PEU, ultimately leading to intention (Razmak & B elanger, 2018).Sharma et al. (2020) studied the impact of generational cohorts on the purchase intention of online travel products.They found that attitude impacted the purchase intention only for millennials.Similarly, Singh et al. (2021) stated that digital platforms help create a positive attitude toward a destination which leads to travel intentions (see Fig. 3).
The current study proposes that the attitude, or the users' dispositional readiness towards SM usage, is an important independent construct, without which the user would not turn towards SM.Individuals who are not positively disposed toward social media usage find online content fake and superficial.Such people prefer to avoid social media despite possessing the necessary skills to operate it.They are sceptical of its content and hence do not find it particularly useful for their travel needs.They also avoid connecting with others online through shared pictures or experiences.Based on the above, we propose the following hypotheses.
H7a. DR towards SM has a direct positive impact on PT.
H7b. DR towards SM has a direct positive impact on PEU.
H7c. DR towards SM has a direct positive impact on PU.
H7d. DR towards SM has a direct positive impact on SC.

Methodology
A cross-sectional quantitative survey study was conducted on Indians who had travelled abroad for a leisure trip during the last one year from the period of the study.The study involved three stages which included the development of a survey questionnaire on the basis of in-depth interviews as well as a literature review, followed by a pretest using exploratory factor analysis and a main survey.Mixed method methodologies have been successfully used for travel-related studies in the past (Singh & Wagner, 2022).

Pre-test
Inputs from 32 in-depth interviews and a literature review were used to prepare an initial survey instrument with 41 items.To refine the instrument, 86 respondents who had taken an international vacation during the past year participated in a pilot study.The respondents were recruited using purposive sampling.This data was subjected to exploratory factor analysis (EFA) to check the dimensionality of each construct.EFA was conducted using the principal component method of extraction and varimax rotation.Kaiser-Meyer-Olkin's measure of sampling adequacy was sufficiently high (0.859).Bartlett's test of sphericity was significant (c 2 ¼ 2986.852,p < 0.001) suggesting that sufficient correlation existed among the items to move ahead with the analysis.After eliminating items that showed poor psychometric properties (<0.5 communality, <0.5 factor loading, or >0.4 cross-loading) the reliability of the items was determined using Cronbach's Alpha.A minimum eigenvalue of 1.0 was used as a criterion for factor decision and factors lower than 0.4 were suppressed.The analysis returned 6 factors comprising of 34 items.These factors accounted for 68.5 percent of the total variance.

Main study
The final instrument consisted of 4 sections.Section one consisted of 3 screening questions, section two included the trip details, section three consisted of 34 items corresponding to the six constructs to be studied and the last section covered the demographic information.Some items were taken from previous studies by Davis (1989), Bashar (2014), and Ellison et al. (2007) and adapted to meet the needs of the current study.The list of social media used was centred on the classification given by Kaplan and Haenlein (2010).Google forms was chosen to administer the questionnaire because of its versatility and user-friendliness.Snowball sampling was adopted to look for respondents who had taken at least one international leisure trip during 12 months from the period of the study.The link to the questionnaire was shared on the authors' social media sites, primarily Facebook, Twitter, and Instagram.The participants were requested to share the link further.A total of 326 forms were filled.Based on the screening questions 26 forms were rejected.A further 20 forms were rejected where the date of the outbound vacation exceeded more than a year from the time of filling in the form.Since Google Forms permits marking each question as 'required', all the 280 forms that emerged from screening were complete and were used for final analysis.

Sample profile
The sample comprised of 62% females.A majority of the respondents (60%) were 40e55 years of age, were married (82%), and were educated (postgraduate e 40.7%; professional degree 40.4%).Slightly more than half (56%) were from the service class, followed by business community (21.1%).A detailed profile of the respondents is provided in Table 1.
The respondents predominantly reflect the upper segment of travel consumers, as seen in the Table.This is consistent with the fact that since the study focusses on outbound leisure travel, it automatically excludes the middle and lower SECs of the Indian population.

Confirmatory Factor Analysis (CFA)/ measurement model testing
The CFA was conducted to test the measurement model.Multiple indices suggested that the proposed model corresponds well to the data.8 2 [155] ¼ 284 which, though was significant at 0.001 levels, is known to be impacted by sample sizes, hence other indices were considered.CMIN/Df value of 1.832 indicated a good model fit as did the other indices: Goodness of fit index (GFI) ¼ 0.910; Comparative fit index (CFI) ¼ 0.946; Incremental fit index (IFI) ¼ 0.947; Tucker-Lewis index (TLI) ¼ 0.934 and Root mean square error of approximation (RMSEA) ¼ 0.055.Overall, the composite reliability was above 0.7 barring for Perceived Trust (0.697).The average variance extracted for all the constructs was greater than 0.5 except for PT and PEU.However, since their composite reliability was above 0.6, it could be assumed that the constructs possessed adequate convergent validity (Fornell & Larcker, 1981) (Refer Table 2).In addition, the data demonstrated sufficient discriminant validity with AVE Overall, it was determined that the measurement results were satisfactory to move forward with the evaluation of structural model.Refer Table 2.

Structural model testing
The results of the testing of the structural model suggested that the model has a reasonable fit.8 2 [160] ¼ 291.078, p ¼ 0.000, CMIN/Df ¼ 1.819, GFI ¼ 0.907; CFI ¼ 0.945; IFI ¼ 0.946; TLI ¼ 0.935 and RMSEA ¼ 0.054.Further, the findings reveal that with the exception of H2 (PEU will positively impact the intention to use SM for international leisure vacations purposes) and H5 (PT will positively impact the intention to use SM for international leisure vacations purposes), all other hypotheses are accepted.H1, H4, H6, H7b and H7d are accepted at p 0.001 level, H3 and H7a are accepted at p 0.01 level, H7d at p 0.05.Refer Table 3.

Discussion
As is indicated by the final model (Fig. 4), it can be concluded that PU (path coefficient 0.58, t ¼ 6.377, p < 0.001) has a strong positive significant impact on intention to use social media for leisure travel purposes, thus supporting H1.This upholds the basic TAM model where perceived usefulness impacts the intent to use technology.In several meta-analyses conducted on TAM related studies (King & He, 2006;Legris et al., 2003;Schepers & Wetzels, 2007;Yousafzai et al., 2010), the relationship between PU and intention has been found to be the strongest.The travellers should find SM useful for them to choose to use it over other available sources of information.
Next, we hypothesized that PEU will positively impact the intention to use SM for international leisure vacations purposes.However, as per our results (path coefficient À0.136, t ¼ À1.705, p ¼ 0.084) this hypothesis is not supported.Past literature shows considerable divergence with respect to the impact of PEU on Intention.Though there are studies that confirm a positive relationship between the two (Ma et al., 2017;Omar Ali et al., 2020;Salloum et al., 2018).King and He (2006) found the link between the PEU and intention two to be the weakest.Similar conclusions were arrived at in the meta-analyses conducted by Schepers and Wetzels (2007), and Yousafzai et al. (2010).It is possible that the effect of PEU on intention is more pronounced when the technology in question .539SC2 -Talking with people through social media makes me curious about 2 places in the world.
.713 Factor 2: Dispositional Readiness DR3 -I browse through social media to pass the time .501.791.559DR2 -I feel out of touch if I haven't logged onto social media for some time.
.802 DR -Social Media is part of my everyday activity.
.863 Factor 3: Perceived Ease of Use PEU3 -Over all I find social media easy to use.
.818 .701.394PEU1 -I can operate any new social media site without external help.
.545 a PEU2_R -It takes me a lot of time to look for information that I want on social media .466Factor 4: Perceived Trust a PT3_R -One cannot trust social media review sites about places to be visited.
.501 .697.451PT -Reviews provided on the social media review sites are dependable.
.837 PT1 -Opinions on social media review sites are unbiased.
.692 .835.910.670PU4 -Social Media helps me learn more about the destination than would otherwise be possible.
.816 PU3 -It would be difficult for me to plan my trip without social media.
.707 PU2 -Social media makes my travel planning easier.
.872 PU1 -Social Media helps in improving my travel plans. .851 a Reverse coded.
is in an organizational setting, for example computers, e-mails or industrial usage technologies.It may differ in social settings, as in the present case.
For hypothesis 6, TAM was extended to include social capital and it was proposed that social capital will affect the intention to use social media.We find that SC (path coefficient 0.28, t ¼ 3.79, p < 0.001) has a positive significant relationship with intention, thus supporting H6.Indians are known to be one of the most prolific users of Facebook.Sharing vacation pictures remains one of the high points of all travel experiences.The likes and comments on the pictures are a reflection of the social capital generated through SM.Ker et al. (2012) concluded that the extent of bragging rights that travellers think they will gain from a particular destination may influence their destination choice.In fact, it has been established that in the future travel will actually be planned as per the number of likes that the pictures of the visit can generate.Use of the location feature in FB is often done to show off.By 'checking-in' at a location, the user shows "how exciting his/her life is" (Grover, 2017).
Contrary to our supposition, PT did not exhibit a significant relation to intention (p ¼ 0.053) thus, H5 was not supported.Possible reasons for this could be that the SM use is independent of trust.Even though the respondents may not trust social media content completely, they use it.
Both PEU (path coefficient 0.27, t ¼ 3.394, p < 0.001) and PT (path coefficient 0.25, t ¼ 3.771, p < 0.001) displayed a significant positive relation with PU, supporting H3 and H4.The effect of PEU on PU has been well established."The major effect  of (perceived) EU is through (usefulness) U rather than directly on (behavioural intention) BI" (King & He, 2006, p. 746).Mendes-Filho et al., (2018) also examined the impact of perceived ease of use on travel planning and concluded that it had a direct impact on usefulness but not on intention.The role of perceived trust in usefulness has also been explored in recent studies (Dutot et al., 2019).Only SM content that is perceived trustworthy by the respondents is considered useful by them.
The results further indicate that DR has a positive and significant influence on each of the constructs PEU, PU, PT and SC.It has the highest impact on SC (path coefficient 0.85, t ¼ 11.27, p < 0.001).This bears weight theoretically as well.One of the highest uses of SM is for social connectivity.Individuals who are not positively disposed towards social media, have a negative attitude towards it, will desist from using it for sharing photos and travel experiences online.They find that constant exposure on SM violates their privacy (Oliveira et al., 2020).They would thus, rather keep away from it.DR is also seen to have a direct positive relation with PT (path coefficient .15,t ¼ 2.070, p ¼ 0.038).Though previous literature has investigated the relation between trust and attitude (Agag & El-Masry, 2017) most of the studies have restricted themselves to exploring a unidirectional impact of trust on attitude.The results suggest that the attitude (in this case DR) will also impact perceived trust.Singh and Srivastava (2019) suggest that travellers who are not positively disposed towards social media usage will have only limited trust in its contents.Similarly, DR shows a significant positive relation with PEU (path coefficient 0.40, t ¼ 4.445, p¼<0.001) and PU (path coefficient 0.26, t ¼ 3.716, p < 0.001).It has been observed that there is a growing number of people who choose to stay away from social media for reasons such as it being a time waster or a constant distraction at the workplace etc.They acknowledge that SM addiction is real, and its overuse impairs the quality of life (Arora et al., 2022).Even if they possess the ability to use it, they will not use it due to their negative attitude towards it.
These results are contrary to previous studies that suggested that DR (or attitude) does not play a significant role in technology adoption (Teo, 2009).Other studies established attitude as a dependent variable, with PEU and PU leading to the formation of attitude (Moon & Kim, 2001;Razmak & B elanger, 2018).However, the results from this study show that the DR acts as an independent variable, and if the consumer is not positively disposed towards technology usage he/she will not use it.

Conclusion and implications
The current study explores and empirically establishes the factors that lead to the large-scale acceptance and usage of SM by Indian leisure travellers.In the process, the study makes important contributions.From an academic perspective, in a significant departure from the TAM, the current study establishes that the dispositional readiness of the user will have an effect on PEU, PU, PT, and SC.Up till now, all the TAM studies have shown either no role of attitude or a unidirectional effect of PU and PEU on attitude.It also establishes that the disposition or the attitude of an individual towards a particular technology usage will also affect PU and PEU.In the current context, it will also affect PT and SC.
From the practitioners' perspective, the study establishes the direct effect of PU on the intention to use SM.Higher the usability of SM content, the higher the chances of it being used for travel.Travel service providers should ensure that their SM media pages give relevant and useful information.The information should be presented in a manner as to pre-empt the needs and preferences of the travellers.AI can be used successfully to study consumer comments and usage patterns to provide personalized experiences.Arora and Lata (2020) have emphasized the importance of comprehensiveness, relevance, and timeliness of YouTube channels as the most significant predictors of their use by travellers.
Next, we find that contrary to the established TAM in this case PEU does not impact intention directly.Rather together with trust, it impacts usefulness, which in turn impacts intention.Web developers, bloggers, and SM content creators should thus ensure that social media sites being created for travel are easy to use.All relevant information should be easily accessible.The sites should be easy to navigate.Too frequent changes in the format, the layout of the site, and requirements of frequent updating may inhibit the ease of use hence the usability of the site.Further, the user should be encouraged to develop trust in the SM content.SM creators should be able to safeguard the privacy of content by putting in checks to safeguard against the leakage of private user information.The travel service providers should also make sure that they provide trustworthy information.Consumer review sites should try to weed out fake reviews by putting in relevant profile checks of the reviewers.They should also try to provide real-time information on their sites so that the consumers can safely depend on it for updated information.Increasing the trustworthiness of SM sites would increase their credibility and would boost their utility, resulting in a greater rate of adoption and usage.
Further, we see that social capital plays an important role in SM adoption.Higher the social capital of an individual, the higher the intention to use SM.Travellers should be provided opportunities to enhance their social capital.They could be encouraged to reach out to others by posting pictures and providing feedback and comments.They could be incentivized They should be provided with ample photographic opportunities like specific marked-out selfie spots and prompted to share these online.Travel destinations can popularize specific hashtags that help in increasing the visibility and shareability of SM posts.Travel service providers can host online communities to encourage travellers to participate in, while retaining some control over the contents (Mendes-Filho et al., 2018).The travellers can be incentivized for posting on social media platforms, which would lead to increased visibility and promotion of their attractions (Lam, Ismail & Lee, S, 2020).

Limitations and future research directions
Though the current study revealed some interesting insights, it has certain limitations.The sample size represents a small reflection of the overall number of Indian tourists who use social media for overseas leisure travel.The proposed model should be further tested using a more comprehensive sample size for better generalization of results.The current study used the snowball sampling method for data collection which might lead to sampling bias.The current study has proceeded with two constructs whose AVE values fell below 0.5.Subsequent studies could look at improving these scales, which could lead to better results.This study establishes the impact of DR on PEU and PU.Further work is required to substantiate this result of a bidirectional impact of DR (attitude) on PU and PEU.It would also be interesting to study the variables that lead to DR.The present study was limited in its scope.The study was conducted in the pre-Corona times.Travel as we knew it is bound to undergo a change.It would be interesting to see how the usage of SM changes as a result of that.Further studies could include additional constructs like perceived enjoyment, frequency of international travel, frequency of social media usage etc.Their interplay with the present constructs could reveal interesting insights.
Factor 5: Intention to use INTD3 -I intend to use social media during and/or after my trip .828.791.563INTD2 -I intend to use the content on social media for my travel decisions .821INTD1 -I intend to use social media to seek travel advice .575Factor 6: Perceived Usefulness PU5 -Over all I find social media useful for the travel experience.

Table 1 .
Demographic profile of respondents.

Table 3 .
Summary of hypothesis testing.