Influence of User-Generated Online Content in Promoting Tourism in Pakistan: Testing the Theory of Planned Behavior

1. Introduction

Recently, there has been an increase in the interest for user-generated online content via platforms, such as YouTube, Facebook, Instagram, and Twitter (Dwivedi et al., 2018; Knoll, 2016; Shiau et al., 2017). Being active on social media has become an essential goal of the marketing strategies as the online product presentation via corporate accounts and marketing on various social media sites has proven to be effective (Gensler et al., 2013). Besides the online fan pages and branded posts, consumers vigorously generate and circulate multi-media content together with their estimations on products and merchandises. Such content and estimations, also known as user-generated content, has been identified as more prevalent and effective ways than traditional advertisements (Aral et al., 2013; Lipizzi et al., 2015; Welbourne & Grant, 2016).

Zeng and Gerritsen (2014) documented that one-third of customers search for a forum, communication board, or virtual community prior to making a travel decision because they believe that online reviews will help them in the decision-making process. Online communities have facilitated communication among the travelers who discuss their experiences and feelings. It is due to sharing of their worthy experiences that encourages and discourages the other travelers from traveling (Cheung et al., 2008; Dwivedi et al., 2018). The growth in communication technologies have extended the reach of communication media, particularly the internet which delivers immense amount of information and facilitates the tourists to convey any knowledge about travel-related products or services promptly and effortlessly access the content incessantly from anywhere. Currently, tourists have become extra careful and considerate in choosing the destinations as they are becoming vigilant in discovering sufficient data about particular places before planning their trips. This response may be subject to the influence generated through positive communication/reviews, optimistic image, and trust given to specific tourist destinations.

Approximately 80% of travelers rely on social media's content to plan a tour, gather information, and wisely consider the travel reviews by other visitors (Murphy & Chen, 2014). The promotion of tourism is also assured by the government of Pakistan in expectancy of a $1 trillion input to the economy by 2025 (Azam et al., 2022). According to the World Economic Forum data, Pakistan was ranked 83rd on the International Travel and Tourism Development Index in 2021, up from 89th in 2019. Ecological tourism is being specified as an important tool for economic growth and progress (Rafiq, 2019). Due to its vast socio-economic development opportunities and impact in recent years, tourism research put more emphasis on the examinations of visitor's visit and re-visit intention (Tajeddini et al., 2021). Individuals gather material, publicized reviews, shared opinions and experiences that eventually inspire their travel intention on social media platforms. It is said that the images of a nation's identity can be crafted, demolished, and rebuilt by the media (Han, 2017). The people of Pakistan are portrayed negatively in the Western media as a Muslim society because of recurring discourses regarding military activities, acts of terrorism, and violence (Bashir & Crews, 2012). Similarly, the local Pakistani media also in the same boat to broadcast anti-West viewpoints amongst individuals (Hassan, 2018), giving rise tomisinterpretationson both sides. Media has the power to manipulate and influence the perspectives of people and create biased representations. One way to combat such misrepresentations is to encourage socialization among people that will encourage them to perceive the actual reality. Several new media platforms, particularly Web 2.0, can be used for this purpose to motivate people-to-people connectivity, which can then assist in altering dominant narratives and perceptions. As, media constructs notions centered upon their own sensory experiences, real world as constructed by the media might indeed vary substantially from the real truth (Shoemaker & Reese, 1996). Such a viewpoint is also pertinent to news reports regarding the new and unknown topics because the audience cannot verify the veracity of such narratives due to the lack of access to the real-life experiences or tales being described (Yousaf, 2015). As a result, poor representation of a particular society or nation fosters stereotypes in the minds of those watching (Baran et al., 2004). The scholars investigated the influence of social media on image of Pakistan as a tourist destination. They found out that social media played a noteworthy part in altering the negative image of Pakistan and endorsing its tourism prospective. The previous researches also acknowledged numerous factors, such as the quality of the reviews, the reliability of the source, and the engagement of the audience that greatly influenced the tourism promotion via social media (Ali et al., 2020).

Kaosiri et al. (2009), examined the association between social media usage and tourist perception and discovered that the visitors who utilize social networking sites tend to view user-generated material for better experiences. The tourism sector of economy helps to maintain peace, reduce poverty, and build the market quickly and broadly. It is additionally described as the biggest unilateral monetary transfer from developed to developing nations (Mitchell & Ashley, 2009). Social media, which is utilized by the travelers in their choice of destinations, has profoundly changed the methods in which travel agencies sell and advertise their services. The development of improved international ties and cultural awareness has fostered tourism on a social level (Mak, 2004). To sum up, tourism effects society, economy, and culture as well as providing the host nation with a wide range of opportunities (Hye & Khan, 2013). Hence, many positive consequences of tourism can be seen on a country's social, political, and economic structures.

In 2018, about 122,891,000 careers were generated by the travel and tourism (3.8% of total employment) however, this was raised by 2.2% (3.9% of total employment) in 2019 (Manzoor et al., 2019). With the escalating consumption of social media, tourists depend robustly on consumer-generated online information when constructing travel-related decisions (Hwang et al., 2018). A customer who is more active in making decisions about sightseeing would be found more involved in gathering information on accommodations, expeditions, meals, and so on through social media than one who is less active in the activity (Icoz et al., 2018). Hwang et al. (2018) discovered that the users who get satisfactory results after following online reviews are tend to return to the online reviewing websites again and again.

Objectives

The study aims to explore the different types of information that the travelers are seeking on social media and they influence their decision-making process. The main focus is to analyze the effect of user-generated online content on destination image formation, tourist attitude towards the destination, subjective norms, behavioral intentions, motivation to travel, and actual behavior using the conceptualframework of theory of planned behavior. The emphasis of the research is to outspread the conceptual TPB model in order to examine the hypothetical relationships by adding UGOC effects and destination image formation to the model of theory of the planned behavior.

Research Hypotheses

1. Whether and to what extent the user-generated online content (UGOC) affects the online representation of destination image, attitude towards destination, traveler's subjective norms, perceived behavioral control as well as tourist's travel intention?

In order to find the answer to this question, the research investigated the extent to which the user-generated online content (UGOC) affects and influence the perception of tourists regarding the selection of tourist destination. In this regard, Liu et al. (2023) investigated the impact of social media on tourists' destination image and travel intention. Wang et al. (2017) observed the link among social media, smartphones, perceived behavioral control, and travel intent along with their influence on decision-making ability of tourists. Perez-Vega et al. (2018) identified the humanoid, hedonic, and functional facets of social media usage in travel decision making. The study discovered that social media can offer tourists with reliable and personalized content, facilitate tour planning and decision-making, and improve their whole experience and gratification. Whereas, Hossain and Islam (2017) proposed a conceptual model that associated social media usage to subjective norms and tourist behavior. The study recommended that online travel content can nurture traveler's subjective norms by offering social cues, expectations and norms, while leading to alter their attitudes and behaviors in destination decision-making.

2. Whether and to what extent the user-generated online content act as a substantial predictor of destination image, attitude towards destination, subjective norms, perceived behavioral control, and also the visit intention?

This research focuses on the role of UGOC as a substantial predictor in influencing tourists' attitude and behavior. Kim et al. (2005) identified how social media and electronic word-of-mouth (WOM) can nurture U.S. tourists' trust in Korea as an ideal tourist destination. The investigation explored that the optimistic social media reviews and online word-of-mouth meaningfully impacted destination trust and intention to visit. Crick (2003) in his Caribbean research advised that when residents express hostile sentiments to visitors, the outcome is pessimistic WOM and a possible recession in the productivity. A meta-analysis of 61 studies on tourist destination choice was undertaken by Brouder et al. (2015) and discovered that perceived behavioral control is a major predictor of travel intention and perceived behavioral control, together with attitudes and subjective norms that significantly influence the travel intentions. Han et al. (2018) studied the factors that influence Korean tourists' intention to partake in sustainable tourism behavior when visiting South Korea's Jeju Island. According to the findings, attitudes and perceived behavioral control were important predictors of intention, although subjective norms had a weaker influence. Munar et al. (2014) research discovered traveler's inspirations for communicating their experiences through social media. The study explored that social media usage can influence traveler's actual behavior and also their tour and destination decisions. The research also identified that communicating travel experiences via social media can enrich destination image and inspire others' travel behavior. Kim et al. (2005) looked at how travel constraints and motivation affect destination loyalty, as well as how attitudes and subjective norms moderate this relationship. Bieger and Wittmer (2006), for example, investigated the role of subjective norms in the perspective of ski tourism. They found that ski intention is positively impacted by subjective norms thus, emphasizing the importance of social influence in influencing the travel behavior.

3. Whether and to what extent travel intention acts as a significant predictor of altering tourist actual behavior?

To find the answer to this question, the research investigates the role of travel intention in predicting the tourist's actual behavior. In their literature review, Ye et al. (2011) applied psychology theories along with TPB, to understand rural tourism behavior which includes factors that influence travel decision making in rural destinations. Wang et al. (2017) research discovered the influence of user-generated online content on tourist behavior and also the link between travel intent and actual behavior. Therefore, the current research proposes that social media might be an operative tool for destination promotion and endorsing actual travel behavior.

Literature Review

Social Networks as Tourist's Communication Platform in Digital Realm

According to the January 2022 DataReportal's global overview, social media progression has continued to accelerate with the figure of digital media consumers internationally increasing from 4.2 billion in January 2021 to 4.62 billion in January 2022 and 424 million fresh consumers coming online in the preceding 12 months. The typical regular time spent consuming digital media is 2h 27m (Chaffey, 2024). As stated by one study, 48% of tourists use Instagram to find new places to visit (Qazi & Baigh, 2024). Whereas, 34% of the travelers reserved their long weekend after seeing someone else's digital media posts and 74% of the travelers said they utilize digital media when travelling (Kopanakis, 2020). The tourist industry has been effectively digitalized and its credit goes to social media. Social media has transformed the tourism industry in the sense that every aspect of a tourist destination is now at the tip of every individual's finger (Tareen & Sultan, 2022). This demonstrates that the travelers use social media to register, estimate time and cost and find other important travel information.

The Revival of Tourism in Pakistan

Any kind of damage, according to Schwab and Brende (2012, p. 14), can harm a country's reputation and may have a considerable effect on tourism as suspicion can cause travelers and visitors to suspend, delay, or alter their travel plans. Hefner et al. (2008) has stated that Pakistan is suspected as a breeding ground for extremism that causes obstacles in the advancement of the hospitality industry. Currently, the Pakistan's tourism industry is now gaining visitors' trust. International chains of hotels are expanding their offerings and innovators are coming up with new methods of assisting guests (Kryukova et al., 2020). Pakistan's global marketplace standing has upgraded and now the country is regarded as a geographically and sacredly amusing destination. Pakistan has been entitled as the most preferential location for travelers in 2020 by a luxury and lifestyle magazine based in the United States (Syed & Haq, 2021). Furthermore, Pakistan has been ranked 83rd, up from 89th in the previous edition of the index in 2019 (Radio Pakistan, 2022).

Influence of Destination Image on Travel Decision-Making

In their study, Assaker et al. (2011) discovered that destination imagery inspires people to come back to a desired location repeatedly. Pike (2002) from his assessment of 142 destination images carried out between 1973 and 2000, revealed that the traveler's observation of a destination image can influence a wide-ranging matter including length of stay, frequency of stay, and also the apparent significance of the place to them. Destination image influences behaviors in two ways, (1) to inspire the process of making decision about the destination and (2) to form the behaviors that occur after the process of decision-making, such as evaluation (satisfaction), contribution (on-site encounter), and forthcoming behavioral intentions (intent to return) (Lee et al., 2005).

Perceived Behavioral Control (PBC) Builds Self-Confidence to Travel

According to Murphy et al. (2007), tourists require various kinds of content at various periods while making decisions about a desired destination, from preparing ahead of time to during and after the trip. Typically, content from an honest source will matter and has a long-lasting impact when forming the first impression of one destination versus the others. Additional data may be needed to obtain a more comprehensive approach and knowledge of that destination. Therefore other sources, such as informative books, tourism organizations, or content on digital media are used for greater impact in decision-making. In the tourism industry, amongst those sources, online reviews/comments are preferred because they are unbiased, low cost, and easy to access (Cam et al., 2019). A variety of alternate destinations are presented to decision makers in destination decision-making (Crompton, 1992; Decrop & Snelders, 2005). Moreover, it is hypothesized that the variety of sources, for example, travel documentaries, friends and families, and previous stay effect the intention to travel (Crompton, 1992; Decrop & Snelders, 2005; Hyde & Laesser, 2009; Seddighi & Theocharous, 2002; Woodside & Lysonski, 1989).

Subjective Norms (SN) – Endorsement of Opinions

In a study conducted in the United States, Litvin et al. (2004) explained that the visitor's decisions are heavily impacted by the online word-of-mouth endorsements of vloggers and bloggers with more effective choices that depend on the influence social media partakes. The examiners proposed that the restaurant vendors that aim to attract tourists has transferred their focus from old-fashioned marketing strategies to online inter-personal marketing channels. More importantly and unlike the traditional word-of-mouth, social media provides an online communication ‘space' that might be searched, connected, and accessed. Since tourists increasingly depend on web search engines to find travel related content, social media has undoubtedly altered the structure of travel related content, the availability of travel material, tourist's acquaintance and insight into a variety of travel related products. Social media can create virtual communities and alter relationships with an impact that extends the boundaries away from the readers and creators of word-of-mouth. By persuading users during their online information searches, it actually creates a newer form of reality.

Attitude towards Destination Influencing Intention

Social media is regarded as the most acceptable as well as a trustworthy source of interaction which significantly caused the formation of destination image. Even though commercial information sources, for instance magazines as well as brochures, are imperative at raising destination awareness, the user-generated online content through social media have a far-reaching impact and have a strong influence on city image formation. According to Phau et al. (2010), traveler's content on social media has a significant impact over destination awareness, travel intention, and perceived image. Kim and Morrison (2005) argued that influencing the traveler's perceptions is critical because they typically decide on the place with the utmost favorable imagery. According to Zeng and Gerritsen (2014), 1/3^rd of online travel consumers follow online communities, communication board, or some other forums before making an online travelling purchase as they supposed that online content could be pertinent to the buying behavior. According to Forrester Research (2006), 34.7% of total time spent online is due to or related to travelling and another survey found that more than 74% of people travel. Numerous websites with reviews have had a significant impact on traveler's decisions as well as attitudes, while making it effortless for tourists to disseminate their content and providing access to such reviews and comments (Jalilvand & Samiei, 2012).

Theoretical Framework

For the research, Ajzen's model of (1991) Theory of Planned Behavior (TPB) was used, that defined how behavior is formed and how social media alters the behavior of travelers in their decision-making process. According to the planned behavior theory, an individual's attitude towards the behavior accompanied by the prevalent subjective norms provides insights into factors that control behavior which altogether effect person's behavioral intention (Ajzen, 1991). He asserts that an alteration in beliefs would result in alteration of attitudes and norms. Intentions would also change as a result of this chain which will ultimately change the desired behavior. For a better understanding of the effects of user-generated online content, this study incorporates its influence on destination image, travel intention, attitude towards destination, perceived behavioral control, subjective norms, and actual behavior discussed in this model.

Methodology

The factors, such as destination image, travel intention, attitude towards destination, perceived behavioral control and subjective norms, and actual behavior were taken as dependent variables. Whereas, UGOC effects are taken as independent variables. The questionnaire was created based on the literature to investigate the association among the variables that the current research discovered. The main objective of the research was to observe the interactions among electronic word-of-mouth, destination image formation, attitude of tourists towards destination, and intention to travel. To study the influence of online travel content on shaping attitude as well as intention to travel, the scale was adopted by utilizing Jalilvand and Samiei's (2012) research. Moreover, with some modifications, this research adopted the scale of Ahmad et al. (2019).

The users of social media were identified as the target audience or population for data collection, while users of public groups and users of tourism-related groups and pages of social networking platform, such as Facebook made up the study's sample. The study used probability sampling and stratified random sampling to acquire the data. With stratified random sampling, a sample from each of the selected groups (or strata) was taken distinctly. Once the population was split into strata, then through simple random sampling the individuals were selected from each group in fraction to the total population. The population of survey is divided into three groups which included foreigners who visited Pakistan and shared their experiences on Facebook. The second group consisted of individuals who moved abroad and visited Pakistan in the vacations and lastly, the individuals who live in Pakistan and traveled to other cities to explore the beauty of Pakistan. The responses of the participants from each of these groups were combined and then analyzed to present the entire targeted population. The questionnaire was created and maintained using Google Forms and distributed via WhatsApp and Facebook Messenger. The questionnaire covers a total of 41 questions and is based on the 5-point Likert scale which contains, such as Strongly Agree, Agree, Neutral, Disagree, and Strongly Disagree as close-ended options. The size of sample includes 300 participants out of which 291 were validated. The research questionnaire assured all respondents that their responses would be kept private and used only for research analysis and examination. SPSS software is utilized to effectually analyze the outcomes in a logical way, in which the correlation analysis, reliability analysis, and hypotheses testing were carried-out.

Results

This section has been divided into two parts. The first one consists of respondent's demographic information which includes gender, age, marital status, education, and occupation status. The last part of the section consists of inferential statistics and overall results of the study. It is further divided into correlations and simple linear regression.

Description of the Sample

Total number of 291 Pakistani local's and foreigners participated in the survey. Out of the 291 participants, 53 (18.2%) were undergraduate whereas 172 (59.1%) were graduate and 66 (22.7%) were post-graduate. The ages of participants were between 30 to 60 years. Out of 291 individuals, 112 (38.5%) were below 30 whereas 147 (50.5%) were between the ages of 31-60 and 32 (11.0%) were above the age of 60. Around 191 (65.6%) male respondents and 100 (34.4%) female respondents participated in the survey among which 160 (55.0%) were single and 131 (45.0%) were married. As shown in the table above, of the 291 participants only 27 (9.3%) were un-employed whereas 37 (12.7%) were retired, while 75 (25.8%) were students, 48 (16.5%) were entrepreneur and 104 (35.7%) were employed.

Table 1

Pearson Product-Moment Correlation Coefficient

Pearson product-moment correlation coefficient was applied to find an association of attitude, subjective norms, perceived behavioral control, and destination image with the travel intention of tourist. The table above indicates that destination image shares a strong association with the travel intention that is .235**, while perceived behavioral control among other variables share .218** relationship with travel intention which is quite higher than the other variables. Additionally, subjective norms share the least .214** association with travel intention as compared to other variables. The Pearson correlation value r is =.000 at a significant 2-tailed which is less than 0.05 and 0.01. Therefore, the hypotheses are accepted because the result is statistically significant (p<0.05). Hence, it is proved that a change in destination image would significantly affect the travel intention of tourists.

Table 2

Pearson Product-Moment Correlation Coefficient of UGOC vs Actual Behavior

Pearson product-moment correlation coefficient was applied to find an association between UGOC effect on tourist actual behavior and to test the hypothesis. The table indicates a positive relationship between the UGOC effects and tourist actual behavior. Pearson correlation value r is =.290** at a significant 2-tailed .004 which is less than 0.05 and 0.01. Therefore, the H3 hypothesis is accepted because the result is statistically significant (p<0.05). Hence, a change in UGOC would significantly affect the tourist actual behavior.

Therefore, by examining the hypotheses it is discovered that the destination image shares a strong association with the actual behavior and travel intention that is .290 and .235**, while the perceived behavioral control among other variables shares .218** relationship with travel intention which is quite higher than the other variables. Additionally, SN share the least .214** association with travel intention as compared to the other variables.

The following hypotheses were tested by using simple linear regression. The relationship between a given dependent variable and one or more independent variables is described and evaluated by the regression.

Table 3

Simple Linear Regression of the Predictor UGOC Effect

Simple linear regression was used to analyze the effects of user-generated online content (UGOC) on shaping the tourist attitude towards destination. The independent variable (UGOC Effect) and dependent variable (Attitude) were entered. The results of R² adjusted = .056 and the regression coefficient (B=.264, 95%CI [.142, .386]) indicate that increase in one UGOC effect corresponded on an average to bring an increase in tourist attitude at a score of .264 points. Additionally, the R² value of .059 revealed that the predictor variable explained 6% variance in shaping the tourist attitude towards destination. The above table reveals that the standardized beta-value =.243 for UGOC effect which indicates the individual variables' contribution in predicting the dependent variable. Hence, the hypothesis is accepted and proved that the UGOC effect is a significant predictor for shaping tourist attitude towards destination.

In order to examine the effects of UGOC on traveler's subjective norms (SN), both independent variable (UGOC Effect) and dependent variable (SN) were entered. The results of R² adjusted =.151 and the regression coefficient (B=.391, 95%CI [.283, .498]) indicate that increase in one UGOC effect corresponded on an average to bring an increase in subjective norms at a score of .391 points. The value of Pearson correlation =.389 is also significant (p<0.01). Additionally, the R-Square value of .151 revealed that the predictor variable explained the 15% variance in subjective norms. The above table reveals the standardized beta-value =.389 for the UGOC effect which indicates the individual variables' contribution in predicting the dependent variable. Hence, the hypothesis is accepted and it can be said that user-generated online content (UGOC effect) is a significant predictor of changing the traveler's subjective norms.

To observe the effect of UGOC on tourist's travel intention, the independent variable (UGOC Effect) and dependent variable (Travel Intention) were entered. The results of R² adjusted =.029 and the regression coefficient (B=.153, 95%CI [.050, .256]) indicate that an increase in one UGOC effect corresponded on an average to being an increase in travel intention at a score of .153 points. Additionally, the R² value of .029 revealed that the predictor variable explained the 2.9% variance in travel intention. The above table reveals that the standardized beta-value =.170 for UGOC effect which indicates the individual variables' contribution in predicting the dependent variable. Thus, the value of p=0.04 is significant (p<0.01 and 0.05). Therefore, this indicates that the independent variable has significant capability in predicting the tourist's travel intention hence the hypothesis is accepted.

A simple linear regression was evaluated to examine the effect of UGOC on the tourist's perceived behavioral control. For this purpose, the independent variable (UGOC Effect) and dependent variable (PBC) were entered. The results of R² adjusted =.145 and the regression coefficient (B=.395, 95%CI [.284, .506]) indicate that an increase in one UGOC effect corresponded on an average to bring an increase in PBC at a score of .395 points. Additionally, the R² value of .145 revealed that the predictor variable explained the 14.5% variance in PBC. The above table shows that the standardized beta-value=.381 for UGOC effect which indicates the individual variables' contribution in predicting the dependent variable. Thus, the value of p=0.00 is significant (p<0.01). Therefore, this indicates that the independent variable has significant capability in altering the tourist's perceived behavioral control hence, the hypothesis is accepted.

To analyze the effect of UGOC on altering the destination image, both the independent variable (UGOC Effect) and dependent variable (Destination Image) were entered. The results of R² adjusted =.190 and the regression coefficient (B=.374, 95%CI [.285, .463]) indicate that an increase in one UGOC effect corresponded on an average to bring an increase in the destination image at a score of .374 points. Additionally, the R² value of .193 revealed that the predictor variable explained the 19.3% variance in destination image. The above table shows that the standardized beta-value =.439 for UGOC effect which indicates the individual variables' contribution in predicting the dependent variable. Thus, the value of p=0.00 is significant (p<0.01). Therefore, this indicates that the independent variable has significant capability in altering the destination image hence, the hypothesis is accepted.

Table 4

Simple Linear Regression of the Predictor Travel Intention

A simple linear regression was evaluated to examine the effect of travel intention on tourist actual behavior. The independent variable (Travel Intention) and dependent variable (Actual Behavior) were entered. The results of R² adjusted =.049 and the regression coefficient (B=.213, 95%CI [.114, .349]) indicate that an increase in one travel intention corresponded on an average to bring an increase in actual behavior at a score of .213 points. Additionally, the value of Pearson correlation =.222 is also significant (p<0.01). Furthermore, the R² value of .049 revealed that the predictor variable explained 5% variance in the travel intention. The above table reveals that the standardized beta-value=.222 for travel intention which indicates the individual variables' contribution in predicting the dependent variable. Thus, the value of p is significant (p<0.01). Hence, the hypothesis is accepted because the result is statistically significant and it can be said that the travel intention is a significant predictor of tourist actual behavior.

Consequently, by examining the hypotheses it is discovered that UGOC effect is a strong and significant predictor of promoting destination image with the standardized beta-value=.439 and regression coefficient=.374 as compared to the altering traveler perceived behavioral control whose standardized beta-value =.381 and regression coefficient =.395. Whereas, UGOC impact is a strong and significant predictor of shaping subjective norms whose standardized beta-value =.389 and regression coefficient =.391 as compared to the attitude towards the destination whose standardized beta-value =.243 and regression coefficient =.264.

Discussion

User-generated online content through social media plays an imperative role in advancing Pakistan's tourism. It aids tourism industries and groups to influence a widespread audience and display the exquisiteness and diversity of the country. Theory of Planned Behavior is a theoretical framework that can help us understand how and why people make decisions, including tourism decisions. It identifies the importance of attitudes, subjective norms, and perceived behavioral control in influencing intentions and behaviors. This study incorporates user-generated online content effect and destination image, in the model for a better understanding of the effect of user-generated online content on promoting positive destination image and influencing tourist intention to travel. Pearson product-moment correlation was used to investigate the relationship between user-generated online content effect, destination image and attitude towards destination, perceived behavioral control, and social norms with travel intention, as well as the relationship between user-generated online content effect and actual behavior. The effect of user-generated online content on destination image, attitude towards destination, travel intention, subjective norms, perceived behavioral control, and the impact of tourist intention to travel on actual behavior was investigated using simple linear regression.

It was hypothesized that there is likely to be an association between user-generated online content (UGOC) effect on online representation of destination image, attitude toward destination, traveler's subjective norms, perceived behavioral control as well as tourist's travel intention and actual behavior. Moreover, it was also assumed that user-generated online content is a significant predictor of destination image, attitude toward destination, subjective norms, perceived behavioral control also visit intention. The research concludes that the user-generated online content may play a crucial role in promoting tourism in a country and impact the decision-making behavior of the travelers. The existing literature by Ye et al. (2020) provides insight into how experiential importance, destination image, and travel motivation influence tourists' satisfaction levels and subsequent behavioral intentions.

Berezan et al. (2016) examines the impact of attitudes, subjective norms, and perceived behavioral control on Generation Y travelers' willingness to utilize social media for travel-related information seeking and Mok et al. (2000) study that focuses on how escape potential and destination attractiveness effect tourists' intentions to travel and offers perceptions on the elements that influence prospective visitors' decision-making and travel intentions, the outcome of these studies are synchronized to the findings of the hypothesis being studied. Many theoretical inferences stem from this examination. Firstly, there are only a few investigations that have inspected the factors which effect tourist's travel intention through the consumption of social media via user-generated online content. There are a few studies that have applied the TPB model to understand the behavioral intention of travelers through the impact of user-generated online content. It is important to mention that the lack of theoretical models in prior studies may provide substantial challenges for the development of interference frameworks in the future. This investigation is predominantly established on how well the theory predict travel behavioral intentions, how the theory support and broaden the relationship, and how the examination or associations aid the forthcoming studies, which fallouts in the achievement of this investigation's aims. Therefore, this study bridges that gap and complements to the theoretical expansion of the area and augments the existing literature by filling this gap. Hence, this is an originality and distinctiveness of the research which might be utilized as a blueprint for the forthcoming investigations.

The data for this study was gathered via an online questionnaire. Although it may be the most practical and efficient method of data collection, there are a number of disadvantages to this approach because it is impossible for the research to identify the respondent. Since the respondent's identity is kept private, several questions about the participants' backgrounds may arise. Only one predictor that is UGOC Effect is examined in regression analysis, future studies can change the predictor variable and examine the other variables cause and effect on each other. Pakistan has a diverse range of attractions, from its natural beauty, cultural heritage, and historical sites to its adventure and sports, food and music. Developing tailored marketing initiatives that showcase these varied elements of the country can help attract a variety of visitors. Ensure that the cultural, linguistic, social, and dietary needs of visitors are satisfied. This research article concludes by offering a thorough analysis of the connections that exist between UGOC and different facets of the visitor's behavior. When combined with empirical data, the TPB's integration as a theoretical framework enhances our comprehension of the mechanisms influencing tourist dynamics in the digital era. In the context of Pakistan's tourist business, this study adds significantly to the body of knowledge on user-generated content and destination marketing.

Conflict of Interest

The author of the manuscript has no financial or non-financial conflict of interest in the subject matter or materials discussed in this manuscript.

Data Availability Statement

The data associated with this study will be provided by the corresponding author upon request.