Employee Turnover in a Nature-based Tourism Resort: Beyond Job Satisfaction

Abstract

Attractive nature-based tourism (NBT) locations for tourists may not translate into attractive work locations for employees. Therefore, we use the therapeutic landscapes concept and extend the person-environment fit theory to encompass a person-location fit. In Study 1, we interviewed employees and identified what locational characteristics, or lack thereof, might lead to intention to quit their jobs. Three distinct themes emerged—lack of infrastructure, lack of interaction opportunities, and lack of consumption opportunities—offering an explanation for high employee turnover in nature-based tourism. In Study 2, we introduced a locational characteristic construct and, using structural equation modeling, found that inferior locational characteristics are positively associated with the employee’s intention to quit their job; and that this relationship, mediated by the employee’s intention to quit the location, is a better explanation than job satisfaction. Our findings point out new directions for researchers, organizations and policymakers.

Keywords

turnover intention (intention to quit)person-location fit person-environment fit nature-based tourism (NBT)tourism employees therapeutic landscape job satisfaction

Introduction

Nature-based tourism—also referred to by its acronym NBT, or simply as “nature tourism”—refers to tourism that is based on the natural attractions of an area that is, the biological and geographical features that have a specific appeal to tourists who enjoy and appreciate such attractions experientially (Ceballos-Lascuráin, 1996; Texas Parks and Wildlife, 2023).Worldwide, nature-based tourism is the fastest growing segment in the tourism industry; it is also the most common type of tourism sought after by travelers to developing countries (Campos-Soria et al., 2018; Centre for the Promotion of Imports from developing countries (CBI), EU, 2023; Ólafsdóttir, 2021; The Nature Conservancy, 2017, 2021). A nature tourism resort is a unit in a nature-based tourism location that consists of all those activities, areas and installations that are intended to serve the specific needs of tourists, including hotels, gastronomy, entertainment, and environment (Żemła, 2021).

Nature-based tourism has consistently been shown to promote positive mental health and well-being for tourists (Buckley, 2023) for two reasons. First, the natural environments at these sites serve as therapeutic landscapes, and the landscapes themselves promote health and wellbeing of tourists (Foley et al., 2019; Williams, 2017). Second, the cultural ecosystem services provided by the nature tourism resorts provide tourists with recreational, esthetic, and spiritual benefits which also enhance their wellbeing (Williams & Ólafsdóttir, 2023). Resorts in such remote, rural locations enable tourists to experience these benefits by offering them opportunities to pursue nature-related activities in close proximity to nature, while at the same time ensuring that tourists have access to modern amenities, comforts and luxuries (Kiryakova-Dineva et al., 2022; Laing & Crouch, 2011; Packer & Ballantyne, 2012; Weber, 2001).

Interestingly, what creates an ideal person-location fit for the tourist (customer) does not seem to extend to the employees of a nature tourism resort. The tourism industry, being labor intensive, accounts for 8% to 10% of total global employment and is among the world’s top job-creating industries, representing 10.4% of global gross domestic product and one in four of all newly created jobs (ILO, 2022; WTTC, 2021). However, the industry also experiences high employee turnover (Marchante et al., 2006; McCole, 2013), which the International Labor Organization (ILO) terms as a “decent work deficit” (ILO, 2022). For example, in India (an emerging economy), where the tourism industry represents roughly 7% of the gross domestic product, employee turnover rates are estimated at up to 50% (Business Standard, 2007; Economic Times, 2010; HRWorld, 2023). Despite this, employee-related academic research in tourism has not got sufficient attention (see Baum, 2018; Baum et al., 2016; Goh & Okumus, 2020; ILO, 2022; McCole, 2013).

This situation is exacerbated in emerging economies because here, outside the resorts themselves, the general level of amenities in locations where nature tourism resorts are situated, being rural areas, is very poor (Ministry of Tourism, Govt. of India, 2022; Press Information Bureau of India, 2000; The Hindu, 2015; UNCTAD, 2015). This presents a dilemma of sorts: in all countries, nature tourism resorts must operate in rural, often, remote locations. At the same time, especially in emerging economies, the ability to retain employees at these resorts is hindered by the unsatisfactory locational characteristics. Since nature-based tourism is labor-intensive, the local labor pool may be insufficient, fueling the need to attract employees from other areas to live and work in these locations (Lundberg et al., 2009; Rosentraub & Joo, 2009; D. J. Solnet et al., 2014b). However, an attractive destination for tourists may not translate into an attractive work location for the labor force needed by resorts in these locations (D. J. Solnet et al., 2014b).

Accordingly, in this paper, we study the factors contributing to nature-based tourism employees’ intention to quit their job, and in doing so, we also compare the role of job satisfaction and the locational characteristics at the location in which the nature tourism resort is situated. In order to do this, the paper is comprised of two studies. Study 1 is qualitative, and we identify what characteristics, or lack thereof, in the location where a nature tourism resort is situated, might cause employees to wish to quit their job. Based on this, we conceptualize the locational characteristics construct. Study 2 is a quantitative study in which we test whether the lack of the locational characteristics identified in study 1 leads to employees’ intention to leave the job because they want to leave the location the resort is situated in, and compare this set of relationships with the role of job satisfaction. Our paper focuses solely on employees in a nature tourism resort in an emerging economy, namely India.

We contribute to literature in the following ways. Firstly, we empirically illustrate that locational characteristics at the nature-based tourism location may be an important determinant in employee turnover. Secondly, and as a related point, we indicate the three dimensions underlying the locational characteristics construct, and also identify a list of specific locational attributes that may contribute to employees’ desire to leave the location and quit their job. Thirdly, we extend both the therapeutic landscape theory propounded by health geographers (Bell et al., 2018; Doughty et al., 2023), as well as the person-environment fit theory (French et al., 1974 onward) by pointing out that, unlike the current assumptions of geographers, landscapes may not be universally therapeutic in aiding wellbeing, and that the person-location fit in a nature-based tourism location is different for tourists (customers) and employees. Fourthly, by focusing on a nature tourism resort in an emerging economy, we identify a situation in which tourist (customer) and employee preferences are in opposition. We thus study a unique situation in tourism and human resources literature in which an organization may, by its very nature, be compelled to operate in a particular location for its tourists (customers), but that the locational characteristics might itself contribute to high employee turnover. Finally, our study is situated in fields that have significant economic costs at both the State and organization levels. In an emerging economy, tourism is an important contributor to economic growth and employment (cf. ILO, 2022; WTTC, 2021), and employee turnover in tourism therefore has policy implications for the State. Employee turnover is also very costly to the organization, and can undermine its success in the tourism sector (Cascio, 1991; Liu & Wall, 2006; Stamolampros et al., 2019).

Literature Review

Therapeutic Landscape Theory for Nature-Based Tourists at Hill Stations

Therapeutic landscape theory studies the effects of physical environments on physical and mental health and wellbeing (Bell et al., 2018; Gesler, 1992; Williams & Ólafsdóttir, 2023). With regard to nature-based tourism, natural environments and geographies are considered to be therapeutic landscapes that bring recreational, esthetic and spiritual benefits to tourists, which in turn enhances tourist wellbeing (Williams & Ólafsdóttir, 2023). In particular, the colors blue and green in landscapes promote wellbeing (Foley et al., 2019). These colors—water and natural greenery—are characteristic of “hill stations,” a British colonial term for towns situated at higher altitudes. In colonial times, hill stations were initially established for the health, recovery and wellbeing of ailing British colonialists and their families (Reed, 1979). While the curative aspects of hill stations were gradually called into question, hill stations continued to be considered therapeutic landscapes, restorative to those who were overworked or exhausted, and helping to make people happier by enriching their mind and body and enlarging their experience (King, 2012). Hill stations were established all over Asia and Africa. Many of these have endured today, with the greatest number in India, and these are frequented by large numbers of Indian tourists for the therapeutic benefits and wellbeing they provide (Mehra, 2023).

Person-Environment Fit Theory and Person-Location Fit

Our study focuses on the effect of locational characteristics on employees’ intention to quit their jobs. Therefore, we employed the theoretical paradigm of the person environment (P-E) fit theory. P-E fit is defined as “the goodness of fit between the characteristics of the person and the properties of the environment” (French et al., 1974, p. 316). Management literature has used P-E fit theory to examine issues such as person-job fit, person-organization fit (Kristof-Brown et al., 2005) or national context fit (Claus et al., 2011; Rodrigues, 2016). In the tourism and hospitality field, D. J. Solnet et al. (2014a), in their conceptual study, first added consideration of location to the issue of retaining employees in more remote tourism destinations. Specifically, they added the idea of “person-location fit” to the theory of P-E fit. They also pointed out, theoretically, that employees consider not only the characteristics of the job and organization, but also that of the location (D. J. Solnet et al., 2014a). In this case, a poor person-location fit for the employee occurs when the locational characteristics in the nature-based tourism location are unsatisfactory for the employee.

Locational Characteristics and Intention to Quit for Employees

Intention to quit one’s job—often called turnover intention—may be defined as a conscious and deliberate willingness to leave (Tett & Meyer, 1993). In fact, intention to quit one’s job is often the strongest predictor of turnover (Abrams et al., 1998; Egan et al., 2004; Griffeth et al., 2000; Lee & Mowday, 1987; Michaels & Spector, 1982; Peltokorpi et al., 2023), mediating the effects of nearly all the other antecedents of actual turnover behavior (Hom et al., 2017; Tett & Meyer, 1993).

The concept of person-location fit has perhaps been most thoroughly studied in expatriate literature, at the country level. Rodrigues (2016) conceptualized the country environment as being comprised of seven country level factors. For each of these seven country level factors, there are several aspects that may cause expatriates to experience a lack of fit to the new location cognitively, affectively, and behaviorally (Haslberger et al., 2013), because the expatriate finds the locational characteristics of the new country wanting. The most common response to, or outcome of, this perceived lack of locational characteristics is the expatriate’s intention to leave their current overseas job (c.f. Bhaskar-Shrinivas et al., 2005; Hechanova et al., 2003; Zimmermann & Sparrow, 2007). The same may be expected for employees in a nature-based tourism location. Therefore,

Hypothesis 1. The greater the lack of locational characteristics for an employee at the nature tourism resort, the greater the employee’s intention to quit the job.

Turnover in the Tourism Industry

Research on employee turnover is scarce in tourism literature (Baum, 2018; Baum et al., 2016; Goh & Okumus, 2020; Ladkin, 2011; Ladkin et al., 2023), even though turnover plays a role in tourism success (Liu & Wall, 2006). However, some studies exist. We have summarized these in Table 1.

Table 1.

Past Research on Employee Turnover in the Tourism Sector.

Category	Factors affecting turnover in the hospitality and/ or tourism sector	Literature
Characteristics of the workplace	Poor pay, work overload, work environment; compensation and benefits.	Bonn and Forbringer (1992), Pizam and Thornburg (2000), Poulston (2008), Stamolampros et al. (2019), Zhao et al. (2016).
	Interpersonal relations among coworkers.	Bonn and Forbringer (1992), Nei et al. (2015), O’Neill and Davis (2011), Pizam and Thornburg (2000).
	Degree to which pre-employment expectations are met.	Pizam and Thornburg (2000).
	Supervisor support; senior leadership.	Bonn and Forbringer (1992), Nei et al. (2015), Stamolampros et al. (2019).
	Inadequate career progression.	Bonn and Forbringer (1992), McGinley et al. (2014), Zopiatis et al. (2014).
	Fair promotions and clear career paths.	Stamolampros et al. (2019), Wong et al. (2017).
	Leader-follower value incongruence; cultural values.	Tang et al. (2015), Stamolampros et al. (2019).
	Frequency of emotional labor.	Humphrey et al. (2015).
	Opportunity to display creativity and self-efficacy.	H. Chen et al. (2018, M. H. Chen et al. 2018), Kattara and El-Said (2013), Robinson and Beesley (2010), Wang et al. (2014).
Characteristics of employee personal life	Work-life fit, job and personal life involvement, family obligations, work-life balance.	Bonn and Forbringer (1992), Haar et al. (2014), Hsieh et al. (2008), Karatepe and Uludag (2008), Richter et al. (2015), Stamolampros et al. (2019).
	Age, length of service.	Karatepe and Uludag (2008).
	Fit with community (not empirically tested; not based on remoteness of location in tourism sector).	Haldorai et al. (2019), Qiu et al. (2015), Tanova and Holtom (2008).
Characteristics of external factors	Housing, transportation, child care, healthcare, leisure, physical environment, social environment and education opportunities.	Bonn and Forbringer (1992).

In perhaps the most comprehensive study to date regarding tourism and turnover, Bonn and Forbringer (1992) applied Mobley’s (1982) findings from exit interviews with regard to why people leave their jobs to the tourism and hospitality industry. They classified individuals’ reasons for turnover into six categories, of which two categories were external factors (housing, transportation, child care, healthcare, leisure, physical environment, social environment and education opportunities) and personal (spouse transferred, illness or death in family, to be married, personal reasons). Tanova and Holtom (2008) studied community fit, which measured satisfaction with interactions in the community, as one of the job embeddedness factors to explain voluntary turnover; but their study was not concerned with either locational characteristics or the tourism and hospitality industry. Similarly, Haldorai et al. (2019) illustrated that better community fit prevents employees leaving five-star hotels in an urban metropolis, Kuala Lumpur, which is the capital city and largest federal city of Malaysia. Thus, the idea of location influencing turnover in the tourism industry was, at best, implied indirectly, because the extent and quality of external factors available and the extent to which personal responsibilities or community fit can be fulfilled will be dependent on the location in which the nature tourism resort is situated.

To conceptualize person-location fit for employees in the tourism industry, we focused on identifying which locational characteristics of a tourist destination affect employee turnover intentions. Addressing this gap becomes more pressing with the ascendancy of nature-based tourism and therapeutic landscapes for tourists (Buckley, 2023; Centre for the Promotion of Imports from developing countries (CBI), EU, 2023; Ólafsdóttir, 2021; The Nature Conservancy, 2017, 2021). We also borrowed from expatriate literature, choosing only the aspects relevant to the tourism industry, and also kept in mind that, in the developing world, employees in nature tourism resorts are usually not expatriates but are instead from the same country. We integrated across existing tourism and expatriate literature, as a preliminary review, to identify the aspects of a location that are likely to affect employees’ intention to quit their current job in nature tourism resorts. These aspects include (i) cost of living, price levels vis a vis quality of life in the location; (ii) ease of availability, timeliness, cost, or type of transport facilities for employee and family, traffic infrastructure and congestion; (iii) technology available at the location for entertainment or household tasks; (iv) quality or cost of medical care in the location; (v) availability, price or quality of goods in the location; (vi) spousal issues in the location (job opportunities or adjustment to the new location); (vii) schooling and childcare facilities at the location; (viii) employee commitments in their personal life (like responsibility to take care of parents, siblings, spouse or children); (ix) alternate job opportunities at the location; (x) ease of organizing and maintaining utilities in the location; (xi) climate and pollution levels in the location; (xii) locals’ exposure to outsiders, openness to people from other regions and their openness to forging friendships with outsiders; (xiii) types of recreational and other non-work activities available; (xiv) ease of connections, distance and time difference between the nature-based tourism location and employees’ hometowns; (xv) support technologies for communication with loved ones such as telecommunications (mobile phone connectivity) and electricity supply; (xvi) quality and cost of housing (Bonn & Forbringer, 1992; Haldorai et al., 2019; Karatepe et al., 2006; Karatepe & Uludag, 2008; Pizam & Thornburg, 2000; Rodrigues, 2016; D. J. Solnet et al., 2014a).

When any of the above aspects are unfavorable in the location of nature tourism resorts, we argue that employees’ failure to adjust to the location may increase their intention to quit the location and to quit their job (cf. Bhaskar-Shrinivas et al., 2005; Hechanova et al., 2003). In other words, contradicting what health geographers currently assume implicitly, we argue that landscapes may not necessarily be universally therapeutic, and that the person-location fit in a nature-based tourism location may be different for tourists (customers) and employees.

We further argue, based on current literature, that employees may need affordable and comfortable amenities in the location (Bonn & Forbringer, 1992; Rodrigues, 2016). Employees may also seek satisfactory social interactions at the location, in their personal life and in the community (Bonn & Forbringer, 1992; Haar et al., 2014; Haldorai et al., 2019; Hsieh et al., 2008; Karatepe & Uludag, 2008; Richter et al., 2015; Rodrigues, 2016; Stamolampros et al., 2019; Tanova & Holtom, 2008). Employees also gage how well off they are through their consumption of goods and services, which means that the availability of goods and services for consumption at the location becomes crucial (Adrangi & Kerr, 2022; Ger, 1997). If any of these three dimensions are lacking, the resulting lack of wellbeing leads to turnover intention because the employee wishes to leave the location (Huang et al., 2018).

Thus, for employees in a nature tourism resort, the locational characteristics, or lack thereof, may themselves lead to an employees’ intention to leave the location, which, in turn, leads to an intention to quit the job. In other words, when employees consider locational characteristics deficient, employees’ intention to leave the location increases, which results in an intention to quit the job. Integrating these thoughts, we have

Hypothesis 2. The relationship between the lack of locational characteristics and intention to quit the job is mediated by the employee’s intention to leave the location in which the nature tourism resort is situated.

Job satisfaction is most commonly defined as a positive emotional state resulting from the appraisal of one’s job or job experiences (Locke, 1976). Job satisfaction has an inverse relationship with an employee’s intention to quit their job (Egan et al., 2004; Muchinsky & Morrow, 1980; Trevor, 2001). In fact, a meta-analysis of 155 studies showed that job satisfaction predicts intention to quit more strongly than any other attitude (Tett & Meyer, 1993). The relationship has held in the tourism and hospitality sector as well, for example, in the case of frontline hotel employees in Northern Cyprus (Karatepe et al., 2006). Thus, if we refer solely to existing empirical tourism literature, the relationship between job satisfaction and intention to quit the job should be adequate to explain why employees leave their jobs. However, based on the literature discussed earlier in this paper (e.g., Bonn & Forbringer, 1992; Haldorai et al., 2019; Karatepe et al., 2006; Karatepe & Uludag, 2008; Pizam & Thornburg, 2000; Rodrigues, 2016; D. J. Solnet et al., 2014a), we argue that for employees in nature-based tourism, the locational characteristics of the nature tourism resort might be a better predictor of employees’ intention to quit their job, as compared to job satisfaction. Therefore, we have,

Hypothesis 3. Locational characteristics are a better predictor than job satisfaction of the employee’s intention to quit the job in the nature tourism resort.

The various relationships examined in this research are represented in Figure 1.

Figure 1.

Relationships examined in this article.

Overview of Study 1 and Study 2

Our aim in this paper is to study the factors that contribute to nature-based tourism employees’ intention to quit their job, and the role of both job satisfaction and the locational characteristics at the location in which the nature tourism resort is situated.

Our studies focused on employees of a nature tourism resort in one emerging country, that is, India. While tourism contributed only 6.8% to the gross domestic product of India in 2019, this sector generated over 15% of all jobs in the country by 2020, or almost half of all the jobs created in the services sector (Ministry of Tourism, Govt. of India, 2022; World Bank, 2023; WTTC, 2021). Notably, the ILO has specifically identified two main constraints in nature-based tourism growth in India (i) infrastructure and civic amenities at tourist locations and (ii) shortage of skilled employees in the tourism sector (ILO, 2009; NCAER, 2014).

We collected our data in a nature tourism resort in a hill station in the Western Ghats mountain ranges in southern India. This hill station is one of the most searched-for tourism destinations in India online and has consistently been voted as one of the top hill station destinations in the country. The closest airport is on the coastal plains 150 km (93 miles) away and the closest railway station is 70 km (43 miles) away from the resort. The district in which the hill station is situated has only two hospitals that are operated by the local government, and no public colleges of higher education. While a few private hospitals and colleges of higher education are available, the cost of service/tuition is much higher at these private organizations (Digital India, 2024a). There are only 985 to 5,759 telephones per 100,000 population; 109 to 223 km of road per 100 km²; the number of doctors per 10,000 people is just 1 to 3; only about 50% of the primary schools have access to electricity and less than 45% have a playground (Census, Govt. of India, 2011). The district is very sparsely populated at just 135 people per square kilometer, with most people engaged in plantation agriculture, such as coffee and pepper (Census, Govt. of India, 2011). Additionally, the district has seen a negative decadal growth rate in population since the beginning of the millenium. Therefore, the tourism industry is almost wholly dependent on employees from outside the district (Digital India, 2024b).

The nature tourism resort under consideration in this paper had 208 employees. For tourists, the average daily rate for two adult guests in one room was approximately $100. Within the resort, guest rooms have modern comforts including Wi-Fi, and restaurants, spas, activity areas and so on are also provided. Guests are offered possibilities of relaxation among verdant surroundings, and scenic trails along sunset views, waterfalls, elephant camps, springs, and tropical forests characteristic of the Western Ghats. Apart from this resort, the organization owning it has a chain of similar nature tourism resorts in six other states in India (four in north and central India; three in the south).

We undertook two studies for our investigation. The purpose of the first study was to identify which locational characteristics—starting from the probable characteristics we narrowed down from extant literature—might cause employees to wish to quit their job at a nature tourism resort. Due to limited past work in this space (e.g., Bonn & Forbringer, 1992; Haldorai et al., 2019; Karatepe et al., 2006; Karatepe & Uludag, 2008; Pizam & Thornburg, 2000; Rodrigues, 2016; D. J. Solnet et al., 2014a), we used a qualitative study to ensure more depth and richness of data. Thereafter, a second study used the findings from the first study to create a locational characteristics scale, which was then used to test our hypotheses.

Study 1

This study was qualitative in nature and dealt with identifying which locational characteristics, or lack thereof, in the location where a nature tourism resort is situated, might cause employees to wish to quit their job.

Sample

We conducted semi-structured interviews with 30 employees. Since the lowest levels of organizational hierarchy in the resort had the most employees that is, there was an unbalanced representation of a particular stratum within the population, we used stratified random sampling (e.g., Guest, 2014; Trost, 1986). We ensured that the 30 employees interviewed represented all 11 departments and eight levels of hierarchy, in rough proportion to the number of employees in each level (Glaser & Strauss, 1967). Data saturation was reached quickly because of the study’s narrow scope (Grady, 1998). However, to ensure that this saturation was not an artifact of the level-of-hierarchy, we continued taking the interviews to gather information from all levels (or strata) in the organization (Gobo, 2008).

Procedure

Through our literature review, we had identified 16 locational aspects from literature that could potentially affect employees’ intention to quit. For each of these aspects, the interviewee was asked whether that aspect makes them wish to quit, and if yes, to describe why it causes them to do so. Interviewees had also been categorized based on tenure, gender, level in the organization, whether the employee’s hometown is in the same district, whether the employee was married, has children, or dependent parents and siblings, in order to rate responses only for those who may be affected by a particular aspect (e.g., childcare facilities are only relevant for those employees with dependent children). After all the interviews were completed, the authors, each working alone, tabulated the results according to the 16 aspects to look for commonalities. They then compared their individual analyses and where there were differences, discussed these together till they came to an agreement (Glaser & Strauss, 1967).

Findings for Study 1

Descriptive statistics for the interview sample are presented in Table 3. When we analyzed the interview data by separating across different demographic characteristics, we did not find any substantial differences, possibly because of the a priori categorization method we followed. For example, there was no difference in the findings due to employee gender, hierarchical level in the organization, marital status, and so on.

Column 2 in Table 2 presents the factors that more than 25% of interviewees cited as reasons why they might want to leave the location of the hill station, and consequently, their job. We broadly termed these factors as locational characteristics. On further examination, we found that the locational characteristics could be grouped into three distinct location-related dimensions—the lack of infrastructure at the location, the lack of interaction opportunities at the location, and the lack of consumption opportunities at the location where the nature tourism resort is situated. Table 2 specifies the dimensions, the corresponding locational characteristics, and examples of related quotations from the interview respondents.

Table 2.

Findings from Study 1.

Locational characteristics dimension	Finding	Examples
Lack of infrastructure	Location does not have good transportation facilities.	“[LOCATION] has bad roads.”
		“Condition of roads are bad, especially during rain.”
		“Transport (facilities) in Bangalore is better.”
	Location has poor-quality housing.	“Now we have water problems. Before we used to have induction… we used to boil with that and drink, but now we need to carry water from the resort.”
	Location does not have good quality schools.	“There aren’t enough of schools.”
		“(Child’s) growth will not be there because you can’t join swimming, art and craft, instrumental… in this, Bangalore and Mysore is better.”
Lack of interaction opportunities	Location is very far from hometown.	“If I get transferred to somewhere nearby to my hometown that would be better… since I am the eldest daughter, I have certain responsibilities.”
	Location is very far from hometown.	“I feel like leaving my job and going there (hometown)… if it (the function) is pre-planned, then we can go, but otherwise it is very difficult.”
	The local people at the location are not friendly.	“(No one) cares – small town, right? They have small mind.”
	The local people at the location are not friendly.	“The way they (locals) speak is rude.”
	Spouse has difficulty in the location.	“It is difficult for them (spouse) to find a job here… In case they don’t find a job here, that will influence me to leave my job.”
		“If they (spouse) come down here and they have some adjusting problem, that will affect me to leave the job.”
		“We are looking for an (job) opportunity in [LOCATION], but we are not finding it. It is very difficult. She was getting around 70,000 when she got married, after marriage she resigned… but now we are facing that issue that she doesn’t want to lose this knowledge because she studied well. What she thinks is I am personally spoiling her (chances). She thinks like - you are not giving me opportunity to grow.”
Lack of consumption opportunities	Location does not have good mobile or wifi services.	“I am not very happy with that (mobile and wifi services), it influence me to leave my job.”
	Location does not have good mobile or wifi services.	“Once my mom’s sister was admitted in the hospital and we had to go soon but there was network problem, so there was an issue.”
	Location does not have the things the employee would like to buy.	“That is one problem I face in [LOCATION]. Example clothing and other products we use, we don’t get here, we have to travel to Mysore or Bangalore… Quality also not much – few products are ok, others are not good.”
		“Clothing they get to second quality clothes and sell at the same (Bangalore city) price.”
	Location does not have entertainment outside work.	“Entertainment is lacking in [LOCATION]… that is affecting me to go (job-wise) somewhere else.”
		“No malls, like shopping mall and at least one good restaurant in the town (is lacking). Now KFC also they are starting, but similarly one Indian restaurant and one shopping mall should be there.”
		“There is no cinema hall, there is no good vegetarian restaurant. So day out with the family is zero.”

The lack of infrastructure dimension mainly revolved around the lack of amenities including transportation, housing, and schools and facilities for children. Even though the employees were aware that these factors were beyond the capability of their organization to remedy, they still perceived these factors as being serious enough to consider leaving the location, and hence their job as well, even when they identified as locals. This is because the lack of infrastructure makes living and working at the remote nature-based tourism location very difficult for employees, eventually causing them to leave their jobs because they wish to leave the location.

The lack of interaction opportunities dimension comprises of factors related to the employee’s social well-being. Since nature tourism resorts in emerging economies may not always be well connected by transport (e.g., the district in which the resort in this study is located has no railway or air connectivity), it becomes difficult for employees to go back to their hometowns for family functions, to celebrate festivals with friends and family, to take care of elderly parents or younger siblings, and so on. If the employee is married, these issues are doubled because the spouse faces the same problems too. Further, because nature-based tourism is likely to be the only major industry in these remote locations, it is very difficult for a married employee’s spouse to find work in their respective field. These issues might have been mitigated if the employee (and spouse) were able to become part of the local community at these remote locations. In our sample, employees reported that they lacked interaction opportunities with both their families back home and the local community, which results in a desire to leave their job because of the remote nature-based tourism location.

The third dimension, the lack of consumption opportunities, represents the aspects that are tied to employees as consumers. When employees come from more developed locations to work in a less developed one (such as those in which nature tourism resorts are located), they seem to be aware that they might not have a broad choice set in the products and services they wish to consume. However, what they fail to consider is that the remote location might not even provide them with an entire category of products and services. For example, employees in this study did not complain about the lack of variety of movies shown at a theater, but rather that there was no theater at all. Also, employees were unable to consume products and services that are ubiquitous in urban parts of the country, like cellular services. Furthermore, being situated in locations that capitalize on their untouched natural beauty, nature resorts are usually the entertainment in that location. While this is exactly what the tourists to the resorts are seeking, for employees working at the resort, this creates a vacuum with regard to their entertainment outside the workplace. Therefore, the employee seeks another location where such consumption opportunities are available, and consequently, wish to quit their job at the nature tourism resort.

Study 2

Study 2 used the items developed from the interviews in Study 1 to create a valid and reliable locational characteristics scale, which was then used to test our three hypotheses.

Sample

We collected data through a survey of 150 employees of the same nature tourism resort as Study 1. The employees sampled in Study 1 did not take part in Study 2, but together, the employees in Study 1 and 2 covered all employees at the resort who agreed to participate. The descriptive statistics of the sample are presented in Table 3. The survey data were collected by presenting the questionnaire to the respondents at their workplace, while assuring and ensuring confidentiality.

Table 3.

Descriptive Statistics.

Study 1 (n = 30)		Study 2 (n = 150)
Demographic	Statistic	Demographic	Statistic
Gender		Gender
Male	50%	Male	71%
Female	50%	Female	29%
Marital status		Age
Married	17%	Average	28
Single	83%	Median	26
		Range	18–49
Level in the org.
Managerial	40%	Marital status
Non-managerial	60%	Married	26%
		Single	74%
Months at the org.
Average	19	Level in the org.
Median	12	Managerial	31%
Range	2–96	Non-managerial	69%
Number of children		Months at the org.
0	87%	Average	21
1 or 2	13%	Median	12
3	0%	Range	1–124
Resident status		Number of children
Local	30%	0	77%
Non-local	70%	1 or 2	21%
		3	2%
		Resident status
		Local	41%
		Non-local	59%

Measures

Our locational characteristics scale was developed based on the findings from Study 1. All the other scales used were from existing literature. The details of the items used for each measure are presented in Table 4. All scale items were measured on 7-point likert-type scales anchored by “strongly agree” and “strongly disagree.” The data were found to be normal when assessed using the Shapiro-Wilk normality test and the Shapiro-Francia normality test.

Table 4.

Measures Used in Study 2.

Items	Cronbach alpha	Factor loadings	Composite reliability
Locational characteristics	.81		0.80
Lack of infrastructure dimension (factor loading = 0.95)
1. [LOCATION] does not have good transportation facilities.		0.71
2. [LOCATION] has very poor-quality housing.		0.70
3. [LOCATION] does not have good quality schools.		0.76
Lack of consumption opportunities dimension (factor loading = 0.54)
4. [LOCATION] does not have good mobile or Wi-Fi services.		0.70
5. [LOCATION] does not have much entertainment outside work.		0.99
6. [LOCATION] does not have the things I would like to buy.		0.81
Lack of interaction opportunities dimension (factor loading = 0.76)
7. [LOCATION] is very far from my hometown.		0.55
8. The local people in [LOCATION]are not friendly to me.		0.77
9. My spouse has difficulty in [LOCATION].		0.58
Job satisfaction
1. I am satisfied with my job at [organization name].	0.75^a
Intention to quit job	0.89		0.89
1. I often think about quitting my job at [organization name].		0.78
2. If it is possible, I am willing to quit my job at [organization name].		0.92
3. I will probably be looking for another job soon.		0.86
Intention to quit location	0.93		0.93
1. I often think about leaving [LOCATION].		0.89
2. If it is possible, I am willing to leave [LOCATION].		0.89
3. I will probably be looking to work in another location outside [LOCATION] soon.		0.92

Minimum estimated reliability.

Locational Characteristics

Based on the findings from Study 1, we used all three dimensions of the locational characteristics construct. Each dimension comprised of three items. The higher the score on this scale, the more the respondent perceived that the location in which the nature tourism resort was situated was deficient. The model fit of the confirmatory factor analysis including these dimensions was good (χ²/df = 2.8, IFI = 0.90, CFI = 0.89, SRMR = 0.054). The composite reliability of this construct was 0.80 which exceeded the recommended threshold of 0.70 (Bagozzi & Yi, 2012), and the coefficient alpha was .81, again above the required threshold (Hair et al., 2006; Nunnally, 1978).

Job Satisfaction

Following past research, we used a single item to measure overall job satisfaction (e.g., Alessandri et al., 2017; Carrillo et al., 2020; Dobrow et al., 2016). Using the modification of the correction for attenuation formula proposed by Wanous and Reichers (1996) and Wanous et al. (1997), the minimum reliability of job satisfaction in our study was estimated to be 0.75.

Intention to Quit Job (IQJ)

This is a three-item scale. The items of this scale were borrowed from existing literature (Becker, 1992; Boshoff & Allen, 2000; Chang et al., 2013; A. C. C. Lu & Gursoy, 2016). The Cronbach alpha for this scale was .89.

Intention to Quit Location (IQL)

This construct was measured using the same items as those in the intention-to-quit-job scale by changing the words “job” and the name of the organization to the name of the location in which the nature tourism resort was situated. The Cronbach alpha for this scale was .93.

Control Variables

In this study, we controlled for the respondent’s level in the organization (Spector, 1997), gender (Griffeth et al., 2000; Russ & McNeilly, 1995), and number of months they have worked in the organization (Griffeth et al., 2000; Russ & McNeilly, 1995).

Analysis

To test our hypotheses, we used covariance-based structural equation modeling (CB-SEM). As per the minimum sample size formula in CB-SEM (Westland, 2010), the recommended sample size is 142.¹ Since our sample size was 150, we decided it was sufficient to adopt CB-SEM in this study.

The locational characteristics construct was modeled as a second-order latent variable comprising of three dimensions—lack of infrastructure, lack of interaction and lack of consumption opportunities—and each dimension comprised of three items (observed variables).

We simultaneously tested for the mediation of the employee’s intention to quit the location (H1 and H2) and to determine whether this, or job satisfaction, is the stronger path leading to an employee’s intention to quit the job, for an employee working at a nature tourism resort (H3).

Results

In addition to the confirmatory factor analysis and the reliability analyses that were conducted (see the description of each measure), we checked for convergent and discriminant validity to ensure the quality of our measures. We used the criteria by Fornell and Larcker (1981), who proposed that when the average variance extracted (AVE) is less than .50, then “the variance due to measurement error is larger than the variance captured by the construct” (p. 46) and thus the validity of the construct comes into question. They also proposed that when the AVE of any construct is greater than the squared correlations between that construct and any other construct in the model, then discriminant validity is established. In our study, the AVE of each measure was above 0.50 and the AVEs were greater than the squared correlations between any of the constructs (see Table 5). Also, the Cronbach alpha for all measures was greater than .70 (see Table 4). These analyses suggest that the reliability and validity of the constructs are acceptable. Further, there was no issue of multicollinearity since all variance inflation factors were below 10. We also tested and found no evidence for common method bias using methods outlined by Podsakoff et al. (2003).

Table 5.

Correlation Table (Study 2).

Construct	LC	JS	IQJ	IQL
Locational characteristics (LC)	1
Job satisfaction (JS)	−0.02	1
Intention to quit job (IQJ)	0.55**	−0.21**	1
Intention to quit location (IQL)	0.65**	−0.29*	0.80**	1
Number of items	9	1	3	3
AVE	0.59	–	0.73	0.80

Note. AVE = average variance extracted.

p < .05. **p < .01.

When we separately analyzed the relationship between job satisfaction and the employee’s intention to quit their job, we found support for existing literature’s claim of an inverse relationship between job satisfaction and the employee’s intention to quit their job (β = −.18, p < .01). Similarly, when we separately analyzed the relationship between deficient locational characteristics and an employee’s intention to quit their job, the results suggested that the deficient locational characteristics at the remote location where a nature tourism resort is situated result in an employee’s intention to quit their job (β = .89, p < .001). However, when we simultaneously compared the two paths leading to an employee’s intention to quit their job, as proposed in the model of this study, the results changed. We found that (i) the relationship between deficient locational characteristics and an employee’s intention to quit their job was non-significant (H1 not supported), (ii) the employee’s intention to quit the location fully mediated the relationship between deficient locational characteristics and an employee’s intention to quit their job (p < .001; H2 supported), even while (iii) the relationship between job satisfaction and the employee’s intention to quit their job became non-significant (H3 supported). The results of the SEM analysis are presented in Table 6 and Figure 2.

Table 6.

SEM Results.

Relationship	Standardized estimates
Job satisfaction → intention to quit job	−0.01
Lack of locational characteristics → intention to quit job	0.02
Lack of locational characteristics → intention to quit location#	0.81***
Intention to quit location → intention to quit job##	0.85***

Note. Fit indices: χ²/df = 1.95, IFI = 0.90, TLI = 0.88, CFI = 0.90, RMSEA = 0.08, SRMR = 0.08. Total effect for the path lack of locational characteristics → intention to quit job is 0.69.

r ² value = .66.

r ² value = .73.

***

p < .001.

Figure 2.

Results of the SEM.

In addition, we considered the impact of the three individual locational characteristics dimensions on the employee’s intention to quit the location and intention to quit their job. There were strong correlations between these dimensions and the dependent variables, indicating that these dimensions were worth investigating separately as well (see Table A1 in the Appendix). Through an SEM analysis, we found that the dimension “lack of interaction opportunities” had the largest impact on the employee’s intention to quit their job, fully mediated through their intention to quit the location. The lack of interaction opportunities dimension (β = .976) had a much greater role to play in determining the overall attractiveness of locational characteristics, followed by the lack of infrastructure dimension (β = .774) and then the lack of consumption opportunities dimension (β = .456). These results are reported in the Appendix in Table A2.

For our sample, issues related to the location of nature tourism resorts are neither limited to a particular gender nor to the employee’s level in the organization. Both controls were non-significant in the models, implying that the concerns related to the locational characteristics are fairly universal for all employees in such organizations. The only control that was statistically significant was the number of months the employee had worked in the organization. Thus, all else equal, the longer the employee had worked at the organization, the less likely they were to wish to quit their job. Perhaps such employees became accustomed to the way-of-life in the remote locations and, over time, had accepted or overcome the issues related to the locational characteristics at such locations.

We also performed a locals versus non-locals comparison. That is, we compared the results when only data from employees who were locals were used versus when only data from employees who were not locals were used. The findings of the main study held for both groups. Further, there was no significant difference between the results of the two models, except that the strength of the relationships was slightly higher in the case of non- locals.

To further support our proposed model, we analyzed an alternative model in which we added a direct relationship between locational characteristics and job satisfaction to test if job satisfaction (and not intention to quit the location) is the true mediator for the relationship between locational characteristics and intention to quit the job. However, the results of this analysis indicated that the direct relationship between locational characteristics and job satisfaction is non-significant (β = −.008, p = .87), thereby strengthening the claim of our proposed model.

Discussion

In this study, we empirically demonstrated that the locational characteristics of a nature-based tourism destination are an important determinant of employees’ intention to quit their job. Through our qualitative Study 1, we identified which specific aspects of the location, or lack thereof, affected employees’ intention to quit, and also broadly grouped these aspects into three dimensions: lack of infrastructure, lack of interaction opportunities and lack of consumption opportunities. In Study 2, which used quantitative methods, we tested whether the lack of locational characteristics identified in Study 1 had a quantifiable effect on the employees’ intention to quit the location and therefore, to quit the job. We did so by conceptualizing and using a locational characteristics construct. We illustrated that the relationship between the lack of locational characteristics at the location of a nature tourism resort and the employee’s intention to quit their job is mediated by the employee’s intention to quit the location; and that this relationship is a better explanation for an employee’s intention to quit their job than is job satisfaction. In addition, we examined the effect of demographic factors and also compared the model for local employees versus non-local employees. In this section, we discuss our contributions to literature based on the research gaps we outlined in the introduction.

Firstly, we have produced what we believe is the first empirical paper that takes into account the effect of locational characteristics on employee turnover intention in a nature tourism resort, thus answering the call to introduce a new potentially important construct (i.e., locational characteristics construct) to turnover literature in HRM (Maertz & Griffeth, 2004), as well as to the rather sparse tourism literature on employee issues (Baum, 2018; Baum et al., 2016; Goh & Okumus, 2020; Shasha et al., 2020). The tourism sector has a high employee turnover rate (Business Standard, 2007; Economic Times, 2010; HRWorld, 2023). The costs associated with severance, followed by the costs associated with recruitment, selection, training, and development of new employees, as well as the costs associated with the expected lower performance of newcomers, can result in costs of up to 200% of an employee’s annual salary (Allen et al., 2010; Cascio, 1991; Stamolampros et al., 2019). Further, studies have illustrated the link between tourism success and the availability of an appropriate labor supply (Liu & Wall, 2006). Yet, employee turnover continued to be under researched by scholars (Ladkin, 2011; Ladkin et al., 2023). Through our study in the area of nature-based tourism, we partially address this need for further research. In doing so, we went beyond existing empirical tourism studies that considered only workplace environments or workplace attitudes and behavior, and instead looked at locational characteristics, a construct that was external to both the organization and the employee.

Secondly, our analysis of the data in Study 1 revealed the aspects of locational characteristics that employees at a nature tourism resort in India found deficient. These could be further grouped into three dimensions, judgmentally arrived at from Study 1 and empirically validated by Study 2 (see Table 2 and Figure 2 respectively). The three dimensions included (1) lack of infrastructure (transportation, quality of housing, schooling and facilities for children); (2) lack of interaction opportunities (distance from hometown, lack of interaction in location, spousal difficulties in location); and (3) lack of consumption opportunities (communication technologies, availability of goods and services, entertainment outside work).

We discuss these findings in the order of impact that each of the three dimensions had in determining the attractiveness of locational characteristics. With regard to our findings about employees’ lack of interaction opportunities, employees expressed difficulties in maintaining their social interactions with their home community. This makes intuitive sense as nature tourism resorts are typically located in remote locations that inhibit employees from easily traveling back to their hometowns over the weekends or for short holidays to spend time with their immediate and extended families (cf. Karatepe & Uludag, 2008). At the same time, employees and their spouses may find it difficult to replace their lost social connections with new ones in the nature-based tourism location. After all, large sections of the local community in more isolated locations are unlikely to allow outsider membership into their groups (e.g., Inbakaran & Jackson, 2005). Therefore, in essence, when working at nature tourism resorts, employees are forced to stay away from the in-groups that they belong to while at the same time feeling like an out-group member to the locals of the location in which the nature tourism resort is located. Such a situation develops within the employee a sense of being ostracized. Previous HRM research has pointed out that a poor P-E fit affects interaction adjustment (Nolan & Morley, 2014) and that unsatisfactory social interactions in the employee’s personal life and in the community lead to increased voluntary turnover of employees (Bonn & Forbringer, 1992; Haar et al., 2014; Haldorai et al., 2019; Hsieh et al., 2008; Karatepe & Uludag, 2008; Mitchell et al., 2001; Richter et al., 2015; Stamolampros et al., 2019; Tanova & Holtom, 2008). This may be because ostracism can lead to withdrawal (Ren et al., 2016; Smart Richman & Leary, 2009), which ultimately results in a desire to quit their job at what they perceive is an unwelcoming remote nature-based tourism location. Generation Y and Generation Z employees, who are generally defined as being born after 1980, now dominate the tourism, and hospitality workforce (Goh & Lee, 2018; D. Solnet et al., 2016). Some HRM studies have demonstrated that Generation Y and Generation Z employees consider cordial interpersonal relations, good socialization and networking even with people from other cultures as important to reduce their intention to quit, sometimes even more important than pay and working hours (Brown et al., 2015; Goh & Lee, 2018; Tang et al., 2015). While tourists might well choose to temporarily exchange their social lives for solitude in a therapeutic landscape, employees and their spouses feel deprived of their social needs permanently, which may be why the therapeutic landscape cannot counteract the social isolation they feel. Therefore, our study points to the need to pay more attention to the social and interactional needs of employees in nature-based tourism locations, where these needs may be especially hard to fulfill.

Similarly, our two studies uncovered that the lack of infrastructure (inadequate transportation, poor quality of housing, deficient schooling, and facilities for children) also contributes to an employee’s desire to leave the location and therefore, to an intention to quit their job. Interestingly, tourism literature has covered some of these attributes before, but only one study before ours focused on employees (Bonn & Forbringer, 1992). Elsewhere, the lack of infrastructure and civic amenities has been considered a constraint in nature-based tourism (ILO, 2009; Ministry of Tourism, Govt. of India, 2022; NCAER, 2014; Press Information Bureau of India, 2000; The Hindu, 2015; UNCTAD, 2015), but this was from the tourist (customer) perspective and not that of the employee. Our paper empirically illustrates that employees in nature-based tourism may also prefer affordable and comfortable amenities in the location (Bonn & Forbringer, 1992; Rodrigues, 2016), just as tourists have shown an increasing preference for comfortable and luxurious living in nature-based tourism locations (Kiryakova-Dineva et al., 2022).

Further, our studies demonstrate that the lack of consumption opportunities (poor communication technologies, non-availability of goods and services, lack of entertainment outside work) also contributes to employees’ desire to leave the location and therefore, to intention to quit their job. Previous HRM and marketing literature indicate that employees in emerging economies may measure their wellbeing in terms of the consumption of goods and services, and the non-availability of such goods and services causes them to wish to leave the location (Adrangi & Kerr, 2022; Ger, 1997). In fact, the idea that infrastructure and consumption opportunities may affect expatriates is well developed (Rodrigues, 2016), as is the idea that locational characteristics might affect individual migrants’ choice to move (Moon, 1995). So, we are rather surprised that this topic is under-researched for employees in nature-based tourism locations. This dearth of research is part of a more widespread tendency in tourism literature that shies away from adopting an employee orientation (Ladkin et al., 2023), leading to ignoring the social, infrastructural, civic and technological needs and wellbeing of employees, and the subsequent effect on employees’ intention to quit. As infrastructural and consumption needs of nature-based tourists have been increasingly catered to by the tourism industry, this has predominantly translated to more organizationally or customer-focused research, such as S. Sun et al. (2020) study about technology readiness and technology acceptance among hotel workers. Meanwhile, our research indicates that employees found their needs unmet, resonating with other studies about contemporary employees, including in emerging economies. The employees in our sample may have been working in a remote nature tourism resort, but they are aware about and aspire to be part of the wider social, economic, and technological changes occurring in other locations in their country, such as in urban areas (Goh & Okumus, 2020; D. Solnet et al., 2016).

Thirdly, our paper makes some important theoretical contributions. We had anchored our paper in both therapeutic landscape theory as well as P-E fit theory, in particular person-location fit (Bell et al., 2018; Doughty et al., 2023; French et al., 1974; D. J. Solnet et al., 2014a). The therapeutic landscapes of a remote nature-based tourism location have been found to promote the physical and mental wellbeing of overworked or exhausted tourists (Buckley, 2023; Foley et al., 2019; Williams, 2017; Williams & Ólafsdóttir, 2023). This has especially held true for the green and blue natural landscapes of Indian hill stations (Kennedy, 1996; King, 2012). We can thus explain the increasing demand for comfortable and luxurious nature-based tourism in the light of therapeutic landscapes serving as a stress coping mechanism for tourists during and after the COVID-19 pandemic (Kiryakova-Dineva et al., 2022; Mental Health Foundation, 2021). Blending therapeutic landscape and P-E fit theories, we can construe that therapeutic landscapes such as the nature-based tourism location in a hill station in India provide an enhanced person-location fit for the tourist (customer of therapeutic landscapes) by increasing their health and well-being. However, as our paper illustrates, there seems to be no such effect of therapeutic landscapes on employees; in fact, there is a poor person-location fit for employees because of deficient locational characteristics, with the resulting intention to quit the location causing an intention to quit the job. In fact, in a significant contribution to theory, we illustrated that, locational characteristics, mediated by intention to quit the location, provided a better explanation of intention to quit the job than job satisfaction (which hitherto was considered the best attitudinal predictor of intention to quit; Tett & Meyer, 1993 onward). Further, the employee sample we interviewed did not point out as desirable any of the therapeutic features, benefits or activities that hill stations and other nature-based tourism locations purportedly have. In fact, both our studies on employees in a nature-based tourism location contradict the contemporary erroneous assumption in tourism, health and geographical literature that therapeutic landscapes are universally beneficial for the well-being of people, and that an increase in time spent in such locations will have more positive effects (Bell et al., 2015). Our research indicates that this is not the case for the employees in a nature tourism resort.

We discuss the implications of this couched in post-colonial critical literature. Nature-based tourism has existed since colonial times, especially in hill stations which were established by the colonialists for the hill stations’ therapeutic landscapes and attendant benefits, and simultaneously as exclusive places for colonialists far away from what was considered the more enervating locally inhabited areas (Kennedy, 1996). Unfortunately, our study indicates that this exclusive mindset may persist in post-colonial hill station tourism today. Nature tourism resorts, including in hill stations, have catered to a new emergent set of Indian elite tourists since at least the mid-1990s (Mehra, 2023). Tourists enjoy good person-location fit due to the hill station’s therapeutic landscapes promoting their health and well-being, as well as giving tourists recreational, esthetic, and spiritual benefits, while at the same time enjoying the comfort and luxury that the resort provides (Buckley, 2023; Foley et al., 2019; Kiryakova-Dineva et al., 2022; Williams, 2017; Williams & Ólafsdóttir, 2023). On the other hand, tourism employees may experience poor person-location fit due to what Manuel-Navarrete (2016) terms as the ghettoization of tourism employees within these hill stations, which, being rural areas, present significant adjustment challenges posed by the deficient locational characteristics in rural versus urban locations in an emerging economy (Cooke, 2009; J. Sun et al., 2020). Thus, by specifically focusing on a nature-based tourism site in an emerging economy, where locational characteristics vary drastically compared to such sites in North America or western Europe (Cooke, 2009), we bring nuance in terms of producing penetrative and explanatory tourism research. In our studies, employees at a nature tourism resort in a hill station pointed at the lack of infrastructure, lack of interaction opportunities, and lack of consumption opportunities characteristic of the location, contributing to a reduction in their wellbeing (Adrangi & Kerr, 2022; Ger, 1997). The ensuing poor person-location fit contributed to their intention to leave the location and by extension, their job. In other words, our study extends therapeutic landscape theory by illustrating that landscapes may not be universally therapeutic, and that the quality of the person-location fit might moderate the effect of therapeutic landscapes on their purported benefits.

Fourthly, by showing how the locational characteristics of a nature-based tourism destination may increase employees’ intention to quit their job, while simultaneously drawing tourists seeking the location’s therapeutic benefits, we identify a situation in which tourist (customer) and employee preferences are in opposition. Nature tourism resorts must necessarily be situated in more remote, rural locations. Yet in an emerging economy, this means employees working in these resorts might live in areas with unsatisfactory locational characteristics. Thus, our research is conducted in an organization whose purpose compels it to be situated in a particular location for its tourists (customers), but the locational characteristics might themselves contribute to high employee turnover. Unfortunately, even the few studies on wellbeing in the hospitality sector have a predominantly organizational orientation, such as the effect of perceived corporate social responsibility on employee wellbeing (Su & Swanson, 2019). In fact, Kusluvan et al. (2010) asserted that the tourism sector lacks enlightened HRM practices. Mooney and Baum (2019) attribute this neglect to tourism academia’s reluctance to deal with contentious topics and to adopt a critical lens when studying the employment of individuals in the sector. Seen in this light, our research regarding the differential experience of employees and tourists with regard to their person-location fit to the therapeutic landscape of a nature tourism resort highlights an opposing situation without easy solutions, which may be why contemporary tourism research does not want to more critically research issues affecting the employees who cater to nature-based tourists’ needs (Baum et al., 2016; Mooney & Baum, 2019; Veijola et al., 2014).

Our paper contributes theoretically to the turnover literature in HRM in two ways. One, it illustrates that job satisfaction need not always be the best predictor of intention to quit one’s job. Specifically, in Study 2, we illustrated that although job satisfaction is inversely related to intention to quit one’s job, locational characteristics also predict an employee’s intention to quit the location, and consequently, intention to quit one’s job. When both relationships are tested simultaneously, the locational characteristics, mediated by the employee’s intention to quit the location, is actually a better explanation than job satisfaction for an employee’s intention to quit their job. This implies that there is a strong empirical case to consider the person-location fit as a predictor of employee turnover intentions. This is especially true of sectors where the choice of organizational location is constrained. Yet, as it stands now, HRM research primarily tends to fall back on to conventional attitudes like job satisfaction or organizational commitment to predict turnover (e.g., Karatepe et al., 2006).

Two, we identified three dimensions of locational characteristics (lack of infrastructure, lack of interaction opportunities and lack of consumption opportunities) and that they affect employees’ intention to quit. New HRM research delving into job attitudes must consider the needs and values of a new generation of employees in such locations, and study specific HRM practices that reduce turnover intention for this hitherto invisible population of employees. The predominantly young workforce in emerging economies have different values and outlooks toward work (Lumbreras & Campbell, 2020). This workforce further has several job opportunities (Ready et al., 2008), and an inclination toward moving to more developed areas (Z. Lu & Song, 2006; Tacoli et al., 2008). Yet the tourism industry still suffers from what the ILO terms as a “decent work deficit” (HRWorld, 2023; ILO, 2022). Current neglect in tourism research of employee needs and wellbeing and the rise of humanistic management (Pirson, 2017) together offer one promising avenue to resolve these challenges (Ladkin et al., 2023).

At the organizational level, in order to prevent turnover, nature tourism resorts may have to think of innovative work arrangements that overcome the disadvantages of their location. Importantly, these arrangements should specifically be directed toward helping employees overcome locational deficiencies (such as enabling wi-fi connectivity for employees to keep in touch with their hometowns), rather than only addressing issues regarding the nature of the job or the workplace as is currently being done. We state this because, as our results in Study 2 indicate, while job satisfaction predicts intention to quit the job, the relationship becomes insignificant in the presence of poor locational characteristics.

Finally, from a policy perspective, governments may have to invest strategically in local amenities which employees in the labor-intensive tourism sector find attractive. Tourism is an important driver of employment globally, being among the top job creating industries, allowing for quick entry into its workforce by youth, women, migrant and unskilled workers, and a significant contributor to gross domestic product (ILO, 2022; WTTC, 2021). Specifically, nature-based tourism is the fastest growing segment in the tourism industry and the most sought-after type of tourism by tourists visiting emerging economies (Campos-Soria et al., 2018; Centre for the Promotion of Imports from developing countries (CBI), EU, 2023; Ólafsdóttir, 2021; The Nature Conservancy, 2017, 2021)—so much so that these dilemmas should be considered, not just by local governments, but also by state and federal governments in emerging countries. At the same time, governments will have to deal with the dilemma of whether such investments are in the interests of the sustainability of local livelihoods, and fragile ecosystems (Vincent & Thompson, 2002; Wondirad et al., 2020).

Limitations

In our research, we faced some constraints that offer opportunities for future research. Firstly, although the organization in our studies had a chain of nature tourism resorts, the organization gave us full access to the management and employees at only one location. This was done to avoid too much disruption in daily operations at all its nature-based tourism locations in the country. Therefore, we acknowledge the possibility that the results of Study 1, wherein we refined the 16 locational characteristics identified from expatriate and tourism literature into the three dimensions and nine aspects that are relevant to employees of nature-based tourism (see Table 2), might be an artifact of the specific location in which the resort under study was situated. However, since our results in both studies are fairly robust and based on the details provided to us about the other resort locations of the organization, we believe that this nature tourism resort serves as a typical example of nature tourism resorts, not just in this organization, but in other parts of the country as well (see ILO, 2009). In such a scenario, we are not attempting to “generalize the individual case or event, which… is unrepeatable, but [rather] the key structural features” of turnover intention (Gobo, 2008, p. 206). In other words, we aim to illustrate that job satisfaction may not be the best predictor of turnover intention when locational characteristics cause an employee to want to quit the location (and thus the job too). Nonetheless, we hope that future nature-based tourism research builds on our findings in more varied contexts to examine employees’ needs and the extent to which tourist locations meet those needs. Such replication of our work across more nature-based tourism locations or organizations or even countries will increase the generalizability of the ideas we presented here.

In addition, urban nature-based tourism has been growing in recent years, especially since the pandemic and its associated travel restrictions. Despite being a contradiction in terms, such nature-based tourism is found within large cities (Higham & Lück, 2002). Gathering information from employees of urban nature tourism resorts could further help to confirm our position regarding person-location-fit, which should be better in a large city. Unfortunately, we did not have access to such a resort in India, but future researchers might consider this as an avenue for further exploration in this space.

Footnotes

Appendix

Table A2.

SEM Results for Individual Locational Characteristics Dimensions.

Relationship	Standardized estimates	Type of mediation
LInf → intention to quit job	0.14*	Partial mediation
LInf → intention to quit location	0.18**	Partial mediation
LCon → intention to quit job	−0.01	Full mediation
LCon → intention to quit location	0.14*	Full mediation
LInt → intention to quit job	0.01	Full mediation
LInt → intention to quit location	0.48***	Full mediation
Intention to quit location → intention to quit job	0.75***	NA

Note. Fit indices: χ²/df = 1.90, IFI = 0.91, TLI = 0.88, CFI = 0.91, RMSEA = 0.07, SRMR = 0.08. LInf = lack of infrastructure; LCon = lack of consumption opportunities; LInt = lack of interaction opportunities.

p < .05. **p < .01. ***p < .001.

Acknowledgements

We would like to acknowledge and thank Supreeth for her assistance with data collection at the nature resort. We also thank the Economy of Francesco (EoF) Academy and the EoF Fellowship for their support in our work. Finally, we thank the editors and reviewers of this paper for helping to improve our work.

Author Contributions

Caren Rodrigues: Conceptualization; Methodology; Writing - original draft; Writing - review & editing. Anup Krishnamurthy: Conceptualization; Methodology; Writing - original draft; Writing - review & editing. Manoj Joseph D’Souza: Conceptualization; Methodology; Writing - original draft; Writing - review & editing.

Declaration of Conflicting Interests

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

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Caren Rodrigues

Anup Krishnamurthy

Notes

Author Biographies

Caren Rodrigues is a distinguished researcher and thinker. She has received the Director’s Merit Award at IIM-Bangalore for doctoral coursework; the Wings of Excellence Award at the St. Gallen Symposium in Switzerland; and was ranked sixth globally in the 2018 Peter Drucker Challenge for her innovative contribution to management thought.

Anup Krishnamurthy is currently associate dean at SJIM. Apart from his publications, he has also co-authored a book related to advertising and consumer behavior in the Indian context. His doctoral thesis was judged the Best Marketing Thesis in India for the year 2016 to 2017, by the International Marketing Trends Congress and ESCP.

Manoj Joseph D’Souza is the former director of SJIM. He is currently serving at AIMIT, St. Aloysius University, Mangalore. A university rank-holder, he has built expertise in the flipped classroom pedagogy and in brand building of business schools.

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