Risk Perception and Behavioural Intention of Tourists Towards Risk-Prone Destinations: The Mediating Role of Place Attachment

Abstract

The aim of this study is to explore and analyze tourists’ behaviour towards Kashmir Valley, India, specifically in terms of their place attachment and intended future behaviour in response to perceived political risk. The study also examines the mediating role of two facets of place attachment (place dependence and place identity) in therelationship between perceived political risk and tourists’ behavioural intentions. The study employed a self-administered questionnaire to gather data from 286 respondents using convenience sampling. Additionally, the structural equation modelling (SEM) approach was employed to analyze the data. The findings showed that perceived political risk does not directly affect behavioural intention; however, political risk perception negatively impacts both place dependence and place identity. Moreover, the results suggest that place dependence and place identity are positively related to behavioural intention. Finally, place dependence and place identity have a fully mediating role in the relationship between perceived political risk and behavioural intention. The results of this study are anticipated to aid destination marketers in understanding how perceived political risk affects the formation of tourists’ place attachment and their future travel behaviour.

Keywords

Perceived political risk place dependence place identity behavioural intention mediation

Introduction

The success and development of tourism destinations depend largely on understanding future tourist behaviour in terms of revisiting and recommending intentions (Weaver & Lawton, 2011). This is because many destinations rely heavily on repeat visitors, as they are a desirable market segment in terms of staying longer at a destination, being more satisfied and spreading positive word-of-mouth publicity (WOM), and the marketing cost of serving this type of market segment is significantly lower than serving first-time visitors (Zhang et al., 2014). Thus, a vital component for tourism businesses to achieve success is understanding tourist behaviour, which is determined by many factors (Stylos et al., 2016). Among them, the two crucial factors are perceived risk (Hasan et al., 2017) and place attachment (Dwyer et al., 2019). Thus, understanding the effect of both perceived risk and place attachment on tourists’ future travel behaviour offers valuable insights for marketers in effective destination marketing (Dang & Weiss, 2021). In this context, numerous studies have investigated and reported on the positive relationship between place attachment and behavioural intention (Brown et al., 2016; Han et al., 2019; Nghiêm-Phú et al., 2021). For example, studies have revealed that the attachment tourists have to a particular destination determines their destination choice and revisit intentions (Brown et al., 2016).

The literature also supports the idea that future travel behaviour of tourists largely depends on their perception of the risk of a destination. In light of this, numerous studies have been done in the past to assess the components of perceived risk and how they affect tourists’ behaviour intentions (Najar et al., 2020). Similarly, the predictors of place attachment, such as satisfaction (Hosany et al., 2017), destination image (Song et al., 2017), service quality (Cheng et al., 2021), memorable tourism experience (Tsai, 2016) and tourist motivation (Prayag & Lee, 2018), have been widely studied in the literature. However, the role of perceived risk as an important antecedent in the formation of place attachment has been the least explored area. Moreover, place attachment has been used as a mediator between satisfaction and behavioural intentions (Lee et al., 2012), destination attractiveness and loyalty intentions (Nasir et al., 2020) and destination image and future travel behaviour (Song et al., 2017). The mediating role of place attachment between perceived risk and behavioural intention is a recent concern still unstudied in the literature. This study is an attempt to fill these gaps in the literature by assessing the influence of perceived political risk and place attachment on behavioural intention. It also attempts to examine the mediating role of place attachment between perceived political risk and tourists’ behavioural intentions.

The study was conducted in Kashmir valley, India. The place is also called ‘paradise on earth’, having a tremendous potential to attract visitors but is being perceived as a risky destination by prospective tourists owing to the decades-long political instability in the region (Chaudhary & Islam, 2021). The tourism industry in the Kashmir valley has suffered a lot because of this continuous political unrest, also affecting its image and has been considered a volatile destination (Chahal & Devi, 2015). Many researchers are of the opinion that tourist destinations, despite having tremendous potential for tourism, lose some of their allure if they are susceptible to crises (Sonmez, 1998). Therefore, tourism development at any place can flourish only under tranquil conditions (Lee et al., 2021; Neumayer, 2004). Given the ongoing political turmoil in Kashmir valley, the travel advisories and high-risk perceptions that tourists hold towards Kashmir as a destination create a need to study tourists’ political risk perception and how it influences their place attachment and behavioural intentions, including revisit and recommendation intentions. This study begins with an introduction to the study, followed by a literature review covering perceived risk, place attachment and behavioural intentions. It is followed by the research objectives, theoretical model and methodology adopted for the study. Finally, the study presents a discussion, implications, limitations and future research directions.

Literature Review

Perceived Risk

The concept of perceived risk has been studied in the tourism literature for over two decades in many diverse studies (e.g. Chew & Jahari, 2014; Rather, 2020; Roehl & Fesenmaier, 1992). The importance of studying tourism risk perception is attributed to service-specific characteristics of tourism, such as intangibility, perishability, inseparability and variability (Artuğer, 2015). Moreover, exposure of the tourism industry to both controllable and uncontrollable factors such as disease and natural disasters, bad weather, political unrest, crime, unfriendly locals, striking airport personnel and so on, often raise the tourist’s level of perceived risk, making destinations more vulnerable and less attractive to visit (Perpiña et al., 2017). Many researchers believe that tourists avoid risky destinations and look for safe ones (e.g. Chew & Jahari, 2014; Khasawneh & Alfandi, 2019). Bauer (1960, p. 390) used the term ‘perceived risk’ first time in marketing by stating ‘consumer behaviour involves risk in the sense that any action of a consumer will produce consequences which he cannot anticipate with anything approaching certainty, and some of which at least are likely to be unpleasant.’ In the tourism context, perceived risk is described as ‘what is perceived and experienced by tourists during the process of purchasing and consuming tourism services, as well as while they are at the destination’ (Tsaur et al., 1997, p. 796).

There are generally three types of risks that have been identified: absolute, real and perceived (Haddock, 1993). The present study merely focuses on perceived risk, as tourists only experience risk pertinent to themselves (Quintal et al., 2010). The existing literature supports the notion that perceived risk is a multi-dimensional construct with various risk dimensions (Fuchs & Reichel, 2006; Najar et al., 2020). The literature suggests that such dimensions include general travel risks (equipment, social, psychological, satisfaction, financial and time risks) as well as the destination-specific risks such as natural disasters, crime, health and political risks. However, keeping in view the recommendations of researchers who have suggested that risk perception and travel behaviour are context-specific (Harun et al., 2018), only a single dimension of perceived risk, that is, political risk, has been taken into account in this study.

Political Risk

Political risk has been defined as ‘a situation in which conditions and mechanisms of governance and rule are challenged as to their political legitimacy by elements operating from outside of the normal operations of the political system’ (Hall & O’Sullivan, 1996, p. 106). From this definition, all challengeable tasks of governance and rules and regulations from outside the political framework are frequently connected with violent events (Neumayer, 2004). Risks associated with political volatility and terrorism have been identified as major concerns, even among experienced travellers, in influencing their travel intentions (Sönmez & Graefe, 1998). Previous research affirmed that the variable political dimension has a significant effect on changing the nature and developmental scenario of the tourism industry (Murphy et al., 2000). Similarly, Buda (2016) pointed out that political instabilities are viewed as antagonistic to the nature and form of the tourism planning and development process and enhance destination competitiveness.

Finally, it is said that political instability at a destination changes tourists’ minds, which often leads to tourists’ switching or cancellation behaviour, which can ultimately lead to substantial economic losses for the host community and the destination government (Walters et al., 2018). Therefore, crisis events such as war, political tensions or terror activities disrupt the stability of a country and have a strong adverse influence on tourism demand (Mansfeld & Pizam, 2006). In tourism literature, various authors have considered a political risk as an attribute of physical risk (Reichel et al., 2007), whereas some authors have taken it as a separate dimension (Seddighi et al., 2001; Sönmez & Graefe, 1998), where it is defined as ‘the risk of becoming involved in the political turmoil of the destination being visited’.

Place Attachment

The tourism literature has seen an increase in the use of place-related notions like a sense of place and place/destination attachment. Place attachment as a concept has been derived from attachment theory, which refers to ‘a positive connection or bond between a person and a particular place’ (Williams & Vaske, 2003, p. 831). The concept of place attachment also encompasses any service relationships to which people feel emotionally tied in a tourism environment where human interactions are crucial in determining one’s experiences within a particular destination (Trauer & Ryan, 2005). Investigating place attachment is justified by the fact that research in socio-environmental psychology has indicated that people’s perceptions regarding their physical surroundings and the relationships they have developed with them significantly impact their behaviours (Beig & Nika, 2019; Sthapit et al., 2022).

The dimensionality of place attachment taken by researchers varies in tourism literature. For instance, Tsai (2012) has argued that there are three dimensions of place attachment, that is, place identity, place dependence and affective attachment. However, Gross and Brown (2006) found convergence of the construct into a single dimension. Similarly, Chen et al. (2014) found various dimensions of place attachment, including nature bonding, place dependence, affective attachment and place identity. The two dimensions of place attachment, that is, place identity and place dependence, have become a matter of consensus in the academic world and are prevalent in tourism literature (Wang et al., 2021). Place dependence is the functional bond between the individual and the physical environment of a particular destination wherein the desired needs and motives of a tourist are satisfied by the activities offered at the destination (Anton & Lawrence, 2014). Place identity, in contrast, is an emotional bond created when the image of a place is in congruence with the tourist’s self-image (Ujang & Zakariya, 2018). Therefore, the current study has also used these two dimensions to measure the place attachment of tourists visiting the Kashmir valley.

Behavioural Intention

The existing literature has given a prominent place to behavioural intention, which is the most widely discussed topic in tourism literature (Li et al., 2018). It has been studied as a dependent variable in many past studies in order to understand the destination choice of tourists and their prospective motivations and behaviours (Afshardoost & Eshaghi, 2020). Tourists’ intentions to revisit and recommend a particular destination to others have been used to conceptualize behavioural intention in many studies (Chi & Qu, 2008; Prayag et al., 2017; Sharma & Nayak, 2018). Many researchers are of the opinion that repeat visitors are highly satisfied by actively participating in consuming tourism services, enhancing their stay at a destination and spreading positive WOM (Zhang et al., 2014). Many scholars have defined revisit intention as a tourist repeating an activity or revisiting a destination and an important indicator of consumer loyalty (Baker & Crompton, 2000; Prayag & Ryan, 2012). It is mostly seen as a type of post-visit behaviour (Cole & Scott, 2004). Thus, the two crucial indicators of behavioural intention are repeat visitation (Stylos et al., 2016) and WOM publicity, which acts as the most authentic source of information for attracting potential tourists towards a particular destination (Veasna et al., 2013).

Perceived Risk and Behavioural Intention

In the existing literature, many scholars have confirmed that risk perceptions are negatively related to tourists’ behavioural intentions (Chew & Jahari, 2014; Harun et al., 2018; Rather & Najar, 2022). Tourists’ tendency to avoid revisiting risky destinations advocates the negative impact of perceived risk on revisit intentions (Perpiña et al., 2019; Rittichainuwat & Chakraborty, 2009). This argument is supported by the fact that terrorism-prone destinations often see fewer tourist arrivals (Rittichainuwat & Chakraborty, 2009). Similarly, An et al. (2010) have studied various risks at the destination level and suggested that physical risk being an exception, all other types of risks, including political and also natural disasters, significantly affect revisit intention among tourists.

Moreover, tourists are discouraged from going to risky places because of perceived travel risks (Sönmez & Graefe, 1998). As safety and security are given the highest priority by tourists in their destination selection process, any kind of crisis such as crime, violence, war, terrorism and political instability strongly influences the intention to visit a particular destination (Cavlek, 2002). Considering the above discussion, the following hypothesis is put forth.

H1: Perceived political risk negatively affects tourists’ behavioural intentions.

Perceived Risk and Place Attachment

The understanding of information in a particular scenario and evaluation of external threats serve as the foundation for risk perception. It greatly influences a person’s emotional state of mind and behavioural tendencies (Wang et al., 2020). Numerous research studies have demonstrated that individual attitude and emotional attachment predictions are based on risk perception (Prayag & Ryan, 2012; Wang, 2015). According to Bonaiuto et al. (2016), place attachment is negatively impacted by individuals’ perceptions of threats of natural disasters (earthquakes, volcanoes, etc.). Zhan et al. (2016) conducted a research study on residents in the two most hit areas of China’s Wenchuan earthquake, suggesting that perceived risk has a negative impact on place attachment. Wang et al. (2020) conducted a study to explore the mechanism of potential tourists’ risk perception in severe COVID-19 epidemics and found that perceived risk negatively impacted place attachment. Based on the above literature, it is proposed that:

H2: Perceived political risk negatively affects tourists’ place dependence.

H3: Perceived political risk negatively affects tourists’ place identity.

Place Attachment and Behavioural Intention

There have been empirical studies on how place attachment and behavioural intentions are related (Dwyer et al., 2019). Place attachment has been proven to be a strong predictor of behavioural intentions by various studies (Yuksel et al., 2010). It is said that a strong tourist attachment to a place leads to a greater willingness to revisit the place and an increased inclination to recommend the place to others compared with those with weak place attachments (Dang & Weiss, 2021). For example, several studies (Kil et al., 2012; Ramkissoon et al., 2013) have found that in nature-based recreation settings, place attachment has a positive influence on pro-environmental behaviours. Tsai (2012) confirmed that tourists’ behavioural intentions are positively influenced by place identity and place dependence. Lee et al. (2012) demonstrate that place dependence predicts WOM in the context of festivals. Loureiro (2014) has found that place dependence has a positive effect on revisit intentions and recommendations in rural tourism settings. Place identity has also been proven to be the most significant indicator of venue attachment when revisiting host cities (Brown et al., 2016). Based on this, the following hypotheses are established:

H4: Place dependence positively affects tourists’ behavioural intentions.

H5: Place identity positively affects tourists’ behavioural intentions.

Mediating Role of Place Attachment

Many disciplines have used the construct of place attachment in studying human behaviour within the physical environment (Dwyer et al., 2019). However, the destination environment affected by external risks negatively influences the behavioural intentions of tourists (Chew & Jahari, 2014) and place attachment (Wang et al., 2020). Similarly, the concept of place attachment is positively related to the behavioural intentions of tourists (Dwyer et al., 2019). In other words, individuals with strong place attachments are more likely to spread positive WOM publicity and show a high propensity to repeat visits (Kil et al., 2012). Therefore, according to the sequential approach of mediation, we can assume a mediation effect when the effect of an independent variable (IV) on the mediator (M) and the effect of the (M) on a dependent variable (DV) are provided based on previous literature and empirical studies (Rasoolimanesh et al., 2021). From the above literature, it can be said that perceived political risk impacts place attachment, thereby affecting the behavioural intentions of tourists. Thus, the following hypotheses are presented:

H6: There is a mediating effect of place dependence in the relationship between perceived political risk and behavioural intention.

H7: There is a mediating effect of place identity in the relationship between perceived political risk and behavioural intention.

Study Objectives

The following objectives of this empirical study are to examine: (a) the influence of perceived political risk on behavioural intention and place attachment, (b) the influence of place attachment on behavioural intention and (c) the mediating effect of place attachment in the relationship between perceived political risk and behavioural intention of tourists.

Theoretical Model

A theoretical model shown in Figure 1 has been developed to clearly show the various hypotheses developed for the study. It is hypothesized that there exist direct and indirect relationships between perceived risk, place attachment and behavioural intention.

Figure 1.

Theoretical Model.

Methodology

A structured questionnaire with multiple-item scales was used to measure all of the study constructs. The scale was adapted from previous studies, and only a few changes were made to the items on the scale to make them suitable for this study’s context. A 5-point Likert scale with 1 denoting ‘strongly disagree’ and 5 denoting ‘strongly agree’ was used to evaluate the constructs. The 4-item Fuchs and Reichel (2006) scale was used as the basis for the political risk scale. Place attachment was measured using eleven items adapted from previous studies (Williams & Roggenbuck, 1989; Williams & Vaske, 2003). The behavioural intention was finally operationalized using four questions that were taken from Pike et al. (2010). The items used to measure the study’s constructs were derived from previous research, and these constructs have been examined by researchers in a variety of sociocultural settings. Thus, pilot testing was done to ensure the face and content validity of the research instrument through expert review. The study instrument was enhanced in terms of content, relevancy and conciseness based on expert feedback so that respondents could understand it better.

The study employed non-probability convenience sampling due to the small size of tourist population visiting the study area and absence of a sampling frame. According to Memon et al. (2017), the two main requirements for doing probability sampling are known population size and the availability of a sampling frame. The data was collected in the months of March and April 2022 using a self-administered questionnaire from four well-known tourist locations in Kashmir, which include Gulmarg, Sonamarg, Pahalgam and Srinagar. These sites were chosen for a number of factors. First, these places are the most well-known, receive the most visitors compared to other places and are included in most travellers’ itineraries (Najar et al., 2020). Second, the popularity of these destinations for a variety of reasons, such as leisure, recreation, religious pilgrimage and adventure, offers a thorough understanding of the desires and motivations of the target market (Indian Brand Equity Foundation, 2019).

The study’s sample size was chosen taking into account Roscoe’s (1975) recommendation that a sample size greater than 30 and lower than 500 is suitable for the majority of behavioural research. Another rule of thumb to determine sample size is using an item-to-respondent ratio, meaning either 5 or 10 respondents per item in a questionnaire should be taken (Hair et al., 1998). According to Costello and Osborne (2005), a higher ratio of 20 respondents per item in the questionnaire is better for sample size estimation. The questionnaire used in this study had a total of 19 items, and using the ratio of 15:1 as the respondent-to-item ratio, the value comes out to be 285 respondents. The questionnaire was distributed to 350 tourists, but only 286 functional responses were used in the research study.

Data Analysis and Findings

The statistical programmes SPSS version 22.0 and AMOS version 23.0 were used to analyze the data. According to the descriptive analysis, 46.8% were female and 53.2% were male. Most respondents belonged to the age group of 34 to 48, making up the majority (39.8%). The majority of respondents (65%), as seen in Table 1, were repeat visitors.

Table 1.

Demographic Profile of Tourists.

Variables		Frequency	Percentage
Gender	Male	152	53.2
	Female	134	46.8
Age	18–33	93	32.5
	34–48	114	39.8
	49–63	79	27.7
No. of visits	First time	97	33.9
	2nd time	122	42.7
	More than second time	67	23.4

Measurement Model

The measurement model as shown in Figure 2, consisting of four constructs, was tested using confirmatory factor analysis (CFA). The results for CFA indicated an acceptable data fit to the model with χ2/df = 2.240, GFI = 0.91, NFI = 0.91, CFI = 0.95, RMSEA = 0.06 and RMR = 0.057. Next, the construct validity was determined on the basis of composite reliability (CR) and average variance extracted (AVE). It is evident from Table 2 that the CR and AVE values for all constructs of the measurement model were above the recommended thresholds of 0.70 and 0.50, respectively (Hair et al., 2010). The discriminant validity of all the constructs was assessed by comparing the square roots of the AVE values with the latent variable correlations (Fornell & Larcker, 1981). For each construct, the AVE’s square root exceeded the correlation between constructs, thus showing discriminant validity (see Table 3).

Figure 2.

Measurement Model.

Table 2.

Results of CFA.

Variables and Its Items	SL	CR	AVE
Perceived political risk		0.858	0.602
I am apprehensive about political uncertainties while visiting Kashmir (PR1).	0.785
I am worried about terrorism in Kashmir (PR2).	0.765
Anticipating physical threats creates fear in me at this destination (PR3).	0.700
Protests and violence create an unsafe environment for tourists to visit Kashmir (PR4).	0.846
Place dependence		0.930	0.657
This place is appropriate for meeting my requirements (PD1).	0.843
This place suits my taste compared to other places (PD2).	0.861
The place cannot be replaced by any other tourist place to fulfil my travel needs (PD3).	0.876
Visiting this place gives me more satisfaction than visiting any other place (PD4).	0.874
I do not see any other place better than this place (PD5).	0.765
For me, doing what I do in Kashmir is more vital than doing it anywhere else (PD6).	0.723
There is no substitute for doing the types of things I do in Kashmir (PD7).	0.715
Place identity		0.874	0.634
I identify very strongly with this place (PI1).	0.753
Visiting this place is of great significance to me (PI2).	0.833
It has become part of my life to visit this destination (PI3).	0.804
The place holds great attachment for me (PI4).	0.792
Behavioural intention		0.910	0.716
I will prefer this destination for the future (BI1).	0.877
It is worthwhile to revisit Kashmir (BI2).	0.879
I am emotionally connected to this place (BI3).	0.818
I would recommend my relatives and friends to visit Kashmir (BI4).	0.809

Note: SL = Standard loadings, CR = Composite reliability, AVE = Average variance extracted.

Table 3.

Discriminant Validity.

Construct	PR	PD	PI	BI
PR	0.776	–	–	–
PD	−0.552	0.811	–	–
PI	−0.687	0.439	0.796	–
BI	−0.572	0.621	0.656	0.846

Note: ‘PR = Political risk, PD = Place dependence, PI = Place identity, BI = Behavioural intention. The numbers presented diagonally in bold italics are the square roots of AVEs for the constructs, compared with the correlation of other constructs in the same matrix’.

Structural Model

The subsequent step is to test the structural model, which is based on examining the casual relationships among the constructs of the study (see Figure 3). The model fit indices for the structural model were within acceptable ranges with χ2/df = 2.23, GFI = 0.91, NFI = 0.91, CFI = 0.95, RMSEA = 0.06 and RMR = 0.062. The results of structural equation modelling along with path coefficients are given in Table 4. The results showed an insignificant direct relationship between perceived political risk and behavioural intention (β = −0.03, p > 0.001). Thus, H1 is not statistically supported. The statistical evidence supports hypotheses H2 and H3, as perceived political risk negatively impacts both place dependence (β = −0.561, p < 0.001) and place identity (β = −0.694, p < 0.001). Finally, hypotheses H4 and H5 are statistically supported as both place dependence (β = 0.410, p < 0.001) and place identity (β = 0.460, p < 0.001) positively impact behavioural intention.

Figure 3.

Structural Model.

Table 4.

Structural Model Estimates.

Direct Effects	β	R ²	t-Value	p-Value	Result
PR↓BI	−0.03	0.0009	−0.389	0.698	H1 not supported
PR↓PD	−0.561	0.31	−8.577	***	H2 supported
PR↓PI	−0.694	0.48	−9.582	***	H3 supported
PD↓BI	0.410	0.16	6.683	***	H4 supported
PI↓BI	0.460	0.21	5.802	***	H5 supported

Note: *** Significant for p < 0.001.

Mediation (the Bootstrap Approach)

The mediation was checked through the bootstrapping method. It is used to produce a representation of the sampling distribution of all specified indirect effects through the re-sampling process by running thousands of new samples, ideally at a time. The confidence intervals for a given indirect effect are formed on the basis of this bootstrapping process (Preacher & Hayes, 2008). Table 5 shows the results of the bootstrapping at 5,000 bootstrap samples with a 95% bias-corrected percentile. The significance of the indirect effect was tested using a confidence interval. If the confidence interval contains zero, it is said that the indirect effect is not statistically significantly different from zero at p < 0.05 (Preacher & Hayes, 2008). The mediating effect of place dependence (β = −0.264) and place identity (β = −0.366) indicates that both place dependence and place identity act as mediators in the relationship between perceived political risk and behavioural intention. Therefore, H6 and H7 are statistically supported.

Table 5.

Mediation Results.

			Bootstrap Estimates			95% Confidence Interval
Specific Indirect Effects			β	SE	P	LLCI	ULCI	Hypothesis Test
PR →	PD →	BI	−0.264	0.064	0.001	−0.404	−0.155	H5 supported
PR →	PI →	BI	−0.366	080	0.001	−0.569	−0.243	H6 supported

Note: ‘β = Regression coefficient, SE = Standard error, P = Probability value, LLCI = Lower limit confidence interval, ULCI = Upper limit confidence interval’.

Discussion and Implications

The current study develops and analyzes a holistic model that takes into account the impact of risk perception and place attachment on travellers’ behavioural intentions towards the valley of Kashmir. First, the results for H1 showed that perceived political risk did not directly influence tourists’ behavioural intentions. Scholars assert that perceived risk and travel behaviour are negatively related (Artuğer, 2015; Rittichainuwat & Chakraborty, 2009). This study does not disprove this claim since place dependence and place identity acted as mediators in this study, thus nullifying the direct effect of perceived political risk on behavioural intention. Second, the results for H2 and H3 showed that perceptions of political risk negatively affected place dependence and place identity. The findings are incongruent with the previous literature that suggests that risk perception has a negative influence on place attachment (Wang et al., 2020; Zhan et al., 2016). The findings suggest that tourists’ political risk perceptions result in a negative change in their functional as well as emotional-symbolic meanings of the place. Third, the results for hypotheses H4 and H5 indicated that place dependence and place identity positively influence behavioural intention. These results suggest that the more attached tourists are to a place, the more likely they will revisit and recommend the destination to others. The findings support earlier research that found a direct relationship between dimensions of place attachment and behavioural intentions (Isa et al., 2019; Loureiro, 2014).

Moreover, the relationship between place identity and behavioural intention (β = 0.460) was found to be higher than the place dependence (β = 0.410). This shows that place identity has a greater impact on promoting behavioural intentions. Accordingly, several authors advocate that emotions act as a significant predictor of an individual’s behaviour (Yu & Dean, 2001). Similarly, according to Alvarez and Campo (2014), in destinations experiencing an ongoing crisis, emotional attachment has a stronger effect on the behavioural intentions of tourists.

Finally, results for H6 and H7 showed that place dependence and place identity both fully mediate the direct effect of political risk on behavioural intentions. Furthermore, it was found that the significant indirect path of political risk to place identity on behavioural intention (β = −0.366) was greater than the indirect path of political risk to place dependence on behavioural intention (β = −0.264). These findings are justified because the study was conducted in Kashmir valley, which has great natural and cultural resources and where tourists respond more emotionally to natural recreational benefits than to artificial ones, thus making place identity a key mediator between perceived political risk and behavioural intention (Kil et al., 2012). Similar findings were made by Sonmez (1998), who found that places affected by crises like political instability raise the level of tourists’ perceived risk, which in turn leads to negative feelings and finally affects the behavioural intentions of tourists towards such destinations. The overall findings of the mediation analysis point to the necessity of considering two key mediators, like place dependence and place identity, when theorising tourist risk perceptions of a specific destination and their related behavioural intentions towards that destination. The study also emphasized the significance of incorporating and assessing the role of tourists’ risk perception and place attachment in the future design of efficient marketing strategies for reducing negative perceptions. According to the findings, behavioural intention, which is a key factor in the successful management of tourism businesses, is primarily determined by risk and the attachment tourists have towards risky destinations.

Theoretical Implications

This study offers a significant contribution to the body of literature. First, this study fills a research gap by empirically verifying the link between perceived political risk and place attachment as well as the importance of place dependence and place identity as significant intervening variables between political risk perception and behavioural intention. Second, most theories of risk perception, like protection motivational theory (PMT) by Rogers (1975) and information integration theory (IIT) by Anderson (1981), evaluated risk at the cognitive level, and fewer efforts have been made to consider emotions and feelings to represent affective evaluations (Yang & Nair, 2014). The concept of evaluating risk at the affective level was introduced by Loewenstein et al. (2001), who suggested that emotions and feelings explain a broader range of risk-related decisions. Thus, the present study has evaluated perceived risk affectively by assessing its relationship with the emotion-based and functional-based components of place attachment. Finally, this study broadens the literature on tourists’ behaviour and applies it to the risky destination context, especially by incorporating perceived political risk and place attachment.

Managerial Implications

This study provided several managerial implications. First, the study of the mechanisms behind visitors’ perceptions of political risk offers an explanatory framework for understanding the attitudes and behaviours of tourists in reaction to perceived risks as well as a strong foundation for developing and enhancing tourist risk management techniques. In this regard, perceived political risk can be minimized through the assurance of tourist safety by the local government, free insurance coverage and the execution of precautionary measures to ensure that visitors do not feel unwanted anxiety and discomfort while visiting Kashmir. Given that place dependence and place identity have a positive link to behavioural intention, it follows that these two factors of place attachment will have a stronger impact on travel behaviour if they are properly managed. Therefore, to encourage tourists’ future travel behaviour and boost destination performance, destination marketers should continually improve place attachment, particularly place identity for riskier locations.

In light of this, destination marketers should intensify their efforts to provide a secure environment, top-notch attractions and better tourist services to guarantee that visitors will have memorable experiences and enhance the functional aspects of tourists’ place attachment. Similarly, the emotional-based aspect of a tourist’s place attachment can be enhanced through organising cultural events, reality shows, shooting of Bollywood movies, familiarization trips and exclusive promotional and discount offers on tour packages and activities. These marketing activities will assist in attracting potential as well as repeat tourists by encouraging visitors to develop a strong emotional connection to the place.

Limitations and Future Research

This study has a number of limitations. First, the findings may not make the proper causal inferences between the constructs under investigation because the current study is cross-sectional. Future studies on longitudinal data should be conducted. Second, the study did not examine how demographic factors such as experience, age and gender affect risk perception and place attachment. Future studies are therefore required to examine the role of visitor demographic traits as moderators in the link between perceived risk, place attachment and behavioural intentions. Third, this study proposes that perceived risk serves as an antecedent of place attachment, in accordance with previous studies (Bonaiuto et al., 2016; Wang et al., 2020). According to other studies (Bernardo, 2013; Quinn et al., 2018), perceived risk has been conceptualized as a consequence of place attachment. To further understand the relationship between place attachment and risk perception, more research is needed to test competing models. Finally, place identity and place dependence were used to conceptualize place attachment. Future research should take into account additional dimensions, including social bonding and place memory, when measuring place attachment.

Footnotes

Acknowledgement

The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Usual disclaimers apply.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Funding

The authors received no financial support for the research, authorship and/or publication of this article.

ORCID iDs

Ab Hamid Rather

Asif Ahmad Bhat

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