Tourism Impact Dimensions, Residents’ Quality of Life and Support for Tourism in Hunza Valley, Pakistan

Tourism is a unique sector which, rather than providing goods and services to a client, transports clients as a product, where the production of goods coincides with their consumption (Wilson & Ypeij, 2012). Globally, tourism is emerging as one of the main sources of revenue for numerous developing and developed countries as it improves the mutual economy of guests and host nations (Arshad et al., 2018). In FY2018, the overall input of travel and tourism to the world's GDP was USD 8,272.3 billion (WTTC, 2018). Worldwide, a 6% increase was observed in international tourist arrivals (overnight guests) worth USD 1.4 billion (UNWTO, 2019). Simultaneously, travel and tourism statistics report Pakistan as a prospective tourism spot, to contribute PKR 2,349 billion (USD 22,286.3 million) to the world's GDP, and its share is expected to grow by 5.8% (WTTC, 2018). Such potential for growth is likely to create intense competition that causes tourism destinations to apply management and marketing strategies that help them survive in the tourism field (Pırnar & Günlü, 2012). In the tourism literature, however, the majority of studies have focused on the impacts of tourism, concerning substantial marketing implications (Woo et al., 2016). A key reason for the growing interest in this type of study is the knowledge and awareness of tourism development and its effects, both positive and negative, at the local level (Ko & Stewart, 2002).

Studies have found that money generated through tourism impacts economically not only the country at large but also individual communities and their residents, through increased employment opportunities, income levels, and advanced public infrastructures (Sinclair & Gursoy, 2016). Opposite to potential monetary growth, however, is the ecological deterioration and negative sociocultural impact of tourism (Choi & Sirakaya, 2005). The literature review suggests that tourism impacts can be studied from various perspectives including environmental, economic, social, and cultural (K. Kim et al., 2013). By relying on tourism impacts, Dogan et al. (2002) stated that support for tourism (SFT) that is important for community growth, effective operation, competitiveness, and sustainability, can be transformed.

Residents’ SFT is defined as ‘a function of what residents understand about tourism development and how it influences them and their community’ (Telfer & Sharpley, 2015). Over the last four decades, research on residents’ SFT has flourished increasingly (Allen et al., 1988; Lin et al., 2019; Nunkoo & Ramkissoon, 2011; Nunkoo & So, 2016; Pizam, 1978). Owing to the evidence that supportable tourism is likely to address the needs of residents in tourism development, residents’ SFT is seen as a necessity for sustainability (Sharpley, 2014). Since tourism depends profoundly upon the willingness of residents, it is very important to comprehend what factors influence residents’ support for tourism (Yoon et al., 2001).

In their research, Jun et al. (2012) investigated the perceived economic gain of residents, the ecocentric attitude of residents, and tourism-related jobs as antecedents of SFT. In another study, Sinclair et al. (2015) used residents’ trust, their identity, residents’ perception of imperialism, and the residents’ perception of tourism growth as antecedents of residents’ SFT growth. Furthermore, Nunkoo and So (2016) included trust in local government, knowledge of tourism, power in tourism, satisfaction with quality of life (QOL), and personal benefits from tourism as factors influencing residents’ SFT. However, investigation of residents’ SFT concerning residents’ quality of life (QOL) is still latent and has gained little academic attention (Nunkoo & So, 2016; Woo et al., 2015).

A plethora of research has examined affiliations between tourism impacts perceived by residents and their SFT (Dong Wan & Stewart, 2002; Dogan et al., 2002; Jurowski & Gursoy, 2004; Nunkoo & Ramkissoon, 2010) through different mediating factors (Lin et al., 2019; Rasoolimanesh et al., 2019). Under Social Exchange Theory (SET), tourism development factors are found to impact residents’ SFT (Woo et al., 2015). However, these contributions are based on a partial set of constructs and are represented by different, yet inconsistent, propositions (Nunkoo & So, 2016). In the Asian context, trivial research has been conducted regarding residents’ SFT (Jaafar et al., 2015; Jaafar et al., 2017; Rasoolimanesh et al., 2015; Rasoolimanesh et al., 2017; Zamani-Farahani et al., 2012). In the Pakistani context, much of the research has focused on tourism-driven economic growth, tourist spatial attitudes, terrorism, tourism, and religious travelers, branding spiritual tourism, ecotourism, tourism impact on deficit in balance of payment, ethnic minorities, and development of tourism (Chowdhury et al., 2017; Haq & Medhekar, 2013; Haq & Wong, 2013; 2019; Raza & Jawaid, 2013; Rovillé, 1988; Ullah et al., 2010). Despite increasing interest in tourism development research, knowledge about how positive attitudes and behaviors towards further SFT can be fostered among residents of Hunza valley (Pakistan) is still scarce. This paper attempts to fill this gap by focusing on tourism impacts’ dimensions and residents’ QOL. By combining SET with bottom-up spillover theory (Rootenberg, 2012), this paper aims to develop and empirically validate a baseline model for residents’ SFT in Pakistan.

This paper contributes to the existing tourism literature in four significant ways. Firstly, it adds to existing knowledge by empirically testing the impact of tourism on residents’ SFT by focusing on residents’ perception regarding tourism impact dimensions and its influence on residents. Secondly, it investigates residents’ QOL from the perspective of satisfaction with various life satisfaction domains (including material, community, emotional, and health & safety wellbeing). Thirdly, residents’ QOL is usually measured as an outcome in the literature (e.g., Kim et al., 2013; Al-Saad 2018); however, this paper posits QOL as an antecedent of residents’ support for tourism development. Fourthly, this paper examines dynamic interactions of tourism impact dimensions with various life satisfaction domains through the construct of QOL which encompasses various life satisfaction domains (including material, community, emotional, and health & safety well-being), because of the spillover effect of a particular well-being domain on other well-being domains (Kim, 2002; Kim et al., 2013).

Earlier studies have observed numerous aspects that can shape residents’ attitudes and perceptions towards tourism development. These aspects include socioeconomic factors, tourism dependency, spatial factors, and residents’ perception of tourism (Gursoy et al., 2018). Though prior research was descriptive and atheoretical, this research area has over the years reached the phase of theoretical maturity as well as methodological sophistication (Nunkoo & Smith, 2013). Among various theories, SET has made important theoretic contributions in the tourism literature (Al-Saad et al., 2018; Ap, 1990; Fredline & Faulkner, 2000; D. Gursoy, Chi, & Dyer, 2009; Nkemngu, 2015). SET posits that residents’ attitudes and their SFT growth will be influenced by their assessment of the significances of tourism for their communities as well as for themselves, and for that exchange tourism is necessary to have in the community (Andereck et al., 2005; Özel & Kozak, 2017). Besides this, Andrews & Withey's (1976) bottom-up spillover theory has assisted in conceptualising residents’ quality of life (Diener, 1984; Sirgy, 2002; Sirgy & Lee, 2006). The theory proposes that QOL is influenced by various life satisfaction domains and sub-domains such as domestic, community/societal, leisure, and healthy life (Kruger, 2012; Neal et al., 2007; Sirgy, 2002; Uysal et al., 2012). These two theories have been used in this paper to hypothesise an association between key research constructs.

This paper followed a quantitative research design to test the hypothesised relationship between tourism impact dimensions, residents’ quality of life, and support for tourism. Residents of Hunza valley having diverse occupational status served as the target population. However, the research population was unknown due to the unapproachability of the population statistics and information about the residents of the Hunza valley. Where it is impossible to create a sampling frame, it is a prerequisite for a researcher to practice a non-probability sampling technique, which at least is considered a viable substitute for random sampling (Saunders et al., 2009). Using purposive sampling, an adequate sample size of 384 was found for the generalisation of results to an unknown target population with a 95% confidence interval (Sekaran & Bougie, 2016). Before that, a small-scale test was performed for this study to evaluate its design. Such pilot studies are frequently conducted to minimise the risks involved in largescale survey research (Khan & Khan, 2020). In this paper, primary data was collected through scheduled visits to Hunza valley, while the survey was conducted by distributing questionnaires through paper-based (hard copy) and online (Google forms) means. Table 1 summarises the demographic profile of the research participants.

Following Al-Saad et al. (2018), Kim (2002), Kim et al. (2013), and Nunkoo & So (2016), a literature-based questionnaire was adopted (Table 2). The research instrument was comprised of 61 items divided into three main segments. The first two segments were comprised of 54 items measuring economic impact (8 items), social impact (6 items), cultural impact (7 items), environmental impact (5 items), QOL (22 items) including its four well-being domains, and the outcome variable SFT (6 items). The tourism impact dimensions and residents’ SFT were answered through a 5-point Likert scale ranging from (strongly disagree to strongly agree), whereas residents’ QOL was answered through a 5-point Likert scale ranging from (very unsatisfied to very satisfied).

A total of 650 questionnaires were distributed, out of which 50 questionnaires were removed because 32 of them were returned completely blank while the rest of the 18 were partially filled. After excluding unusable responses, 600 entries were found for survey analysis. This dataset was further scrutinised through data cleaning and outlier identification. As a result, 39 responses were dropped and finally, 561 responses were used for hypotheses testing. SPSS v.23 was used for descriptive statistics, multi-collinearity, reliability, validity, and linear regression analysis. Also, PROCESS Macro 3.3 was used for parallel mediation analysis. Construct reliability was established through Cronbach's alpha, discriminant validity, and convergent validity using average variance extracted (AVE) and Fornell Larcker criterion. The structural model analysis was done through R-square and path coefficients.

Descriptive statistics were used to summarise data and to demonstrate an average level of respondent agreeableness on a particular construct. In the preliminary analysis, the multicollinearity test is suggestible for measuring the extent to which two or more predictors are correlated in a multiple regression model (Hair et al., 2010; Raykov & Marcoulides, 2006; Saunders et al., 2009). The simplest way of diagnosing multicollinearity is to test the correlation coefficients between predictors (Hair et al., 2010). Correlation coefficients for all predictors were within the threshold of <0.9 as can be seen in Table 3. Multicollinearity diagnostics were also performed using Landau and Everitt's (2004) value of tolerance, VIF, and condition index suggesting no potential issues of collinearity in the dataset (Table 4).

According to Hair et al. (2012), convergent validity indicates that at least 50% variance of indicators can be explained by the latent variable. To achieve convergent validity, AVE must be higher than 0.5. Table 5 shows that the AVE for all variables was above the threshold.

For the discriminant validity, the SQRT of each variable's AVE should be greater than the correlation of a particular variable with any of the other variables in the model and should be at least 0.50 (Fornell & Larcker, 1981; Hair et al., 2012). In this paper, discriminant validity for all constructs was established achieving AVE >0.5 (Table 6).

In the existing literature, the majority of studies were descriptive (Al-Saad et al., 2018a; Nkemngu, 2015b; Suntikul, Pratt, I Kuan, et al., 2016), only an individual study with regression analysis was conducted till now (Khizindar, 2012). Explicitly, this paper contributes to the literature by providing empirical evidence on the relationship between tourism impact dimensions and residents’ QOL in Hunza valley, Pakistan.

In the Hunza valley, tourism has long been viewed as a tool for monetary development. The findings of this paper reveal that residents perceived that monetary aspects of tourism exert a positive impact on their support for tourism. This positive relationship between the economic dimension and residents’ QOL could be because (i) tourism has developed into a sizable industry in Hunza valley and (ii) residents of this valley perceive tourism as a vital source of income/revenue. In line with prior studies, findings of this paper exhibited tourism as an economically fruitful activity for local businesses, which not only improves residents’ standard of living but also enhances their quality of life (Al-Saad et al., 2018a; Nkemngu, 2015b; Suntikul, Pratt, I Kuan, et al., 2016).

In their studies, Al-Saad et al. (2018b) and Nkemngu (2015b) reported tourism as a means to increased entertainment facilities that encourage positive residents’ perceptions about tourism. Likewise, the empirical analysis showed the positive social impact of tourism on residents’ quality of life in the Hunza valley. Corresponding to Khizindar (2012a), residents have a positive perception of tourism as it creates social benefits and opportunities including local services and better maintenance of roads. On the cultural impact of tourism, findings revealed that tourism yields cultural benefits to the residents of Hunza valley by encouraging activities that increase demand for local artifacts, restore local traditions, and enhance residents’ pride in their cultural identity. These results are consistent with previously reported findings (Al-Saad et al., 2018a; Khizindar, 2012; Nkemngu, 2015b).

Stylidis (2012) argued that residents recognise the more economic, social, and cultural impact of tourism on their QOL, but have little or no difference in their perceptions of the environmental impact on their QOL. In support of Yang et al. (2017a), the environmental impact of tourism on residents’ QOL was found to be insignificant. SET postulates that residents seem to consider their costs and benefits when estimating an interchange (Ap, 1992b). This proposition is validated by the analysis of results indicating that residents’ QOL brings positive attitudinal changes in residents’ SFT. In the Hunza valley, findings of the survey showed that residents support tourism because they perceive that tourism development is significant for their community. Most of the respondents also agreed that the tourism industry is one of the most essential industries for their community. Thus, their community is likely to attract more tourists, as it benefits local people by improving their standard of living, the standard of community services, and community conditions (Nunkoo & Ramkissoon, 2010a, 2010b).

The findings of this paper reported that residents’ QOL mediates the relationship between three dimensions of tourism impact (economic, social, and cultural) and residents’ SFT. Earlier studies emphasised the association between tourism impacts and residents’ QOL (Al-Saad et al., 2018a; Kim et al., 2013b; Yang et al., 2017b), and between residents’ QOL and their SFT (Woo et al., 2015b). In line with SET and bottom-spillover theory, this paper reported the mediating role of residents’ QOL between tourism impact dimensions and residents’ SFT.

This paper assessed support for tourism from the residents’ perspective and their quality of life along with four dimensions of tourism impact. Analysis of primary data reported a significant association between tourism impact dimensions and residents’ QOL, confirming that residents’ perception regarding tourism impact is correlated with higher levels of satisfaction with their QOL (Al-Saad et al., 2018a; Kim et al., 2013b; Suntikul, Pratt, I Kuan, et al., 2016). These findings suggest that tourism administrators and planners should realise residents’ multidimensional perspective to escalate their gratification with QOL through tourism impact dimensions. By increasing residents’ QOL, tourism administrators, developers, and marketers can make a more competitive and supportable tourist destination.

During analysis, it was found that residents of Hunza valley positively discern the three dimensions (social, cultural, and economic) of tourism impacts. These three dimensions were found to be significant predictors of residents’ QOL and their SFT growth. These findings can help local administrators and tourism planners in promoting a positive perception of residents about tourism in the valley. This can be done by arranging internal learning campaigns to escalate residents’ cognizance about social, cultural, and economic advantages of tourism growth; thereby, increasing residents’ SFT. Local authorities can also run awareness campaigns involving residents, particularly in the planning, organising, and decision-making process of tourism development. Such participation will promote favorable resident attitudes towards tourism by increasing their ownership of and involvement in the promotion of tourism activities. This is significantly important for achieving residents’ support for tourism as a key to the long-term success of the tourism industry in the Hunza valley.

Lastly, this study has its limitations that open avenues for further research on tourism and related indicators. This paper used four well-being domains to examine the influence of residents’ perception about tourism impacts on their QOL and their SFT. Future researchers are encouraged to extend the proposed model by examining the role of other well-being domains such as social life, household life, travel life, and work life. The findings of this paper are based on data collected from Hunza valley residents only. Further research on these variables can be conducted by gathering data from diverse destinations that may show a different level of tourism growth. Moreover, the perception of residents about tourism impacts, QOL, and their SFT may vary based on their demographic information, personality, and destination type. Thus further studies are encouraged to consider residents’ characteristics in the model.