Seasonal Employees

Abstract

High year-to-year retention of seasonal employees can be a source of competitive advantage for tourism organizations. Past studies of seasonal employee retention have examined the issue from the perspective of job satisfaction. However, many tourism jobs have similar responsibilities from organization to organization suggesting another construct might also affect employee retention. The purpose of this study was to examine retention through the lens of employee sense of community (SOC) toward the tourism organization. Significant differences were found in SOC levels between those who returned to work at resorts and those who did not. Moreover, a logistic regression model showed SOC to be a good predictor of retention. Like in previous studies, factors that impact retention appear to be different for first year employees than experienced ones. However, the results suggest that somewhat different approaches for improving retention should be taken than the recommendations from past studies of seasonal employee retention.

Keywords

seasonal employees employee retention sense of community job satisfaction human resources ski resort

Introduction

Tourism is a very seasonal industry with demand peaking at different times of year. This seasonality causes major operational and policy challenges for the hospitality and tourism industries (Baum 1999). One of the main challenges involves staffing. As organizations adapt their labor force to variations in visitation volume, it is often necessary to release many employees at the end of a season with the hopes of attracting back the best ones when they are needed again, often nearly a year later. It is this interruption in employment that adds a unique challenge to managing human resources in organizations that rely on seasonal employees. In a year-round position, employees who are very unhappy with their jobs are likely to actively seek another opportunity. However, if employees are only marginally dissatisfied with their jobs, they may take a more passive approach and only explore other jobs if an opportunity presents itself. For seasonal employees who are marginally dissatisfied, this passive approach is less likely since employees are dismissed at the end of the season, forcing them to look for other opportunities. Further, because many seasonal employees are migratory, the employment situation must be desirable enough to entice employees to relocate back each year.

Because a tourist’s experience is so closely linked with employee performance (Lundberg, Gudmundson, and Andersson 2009), the effective management of human resources is critical to top line profitability (Owen and Teare 1996). Leaders of tourism organizations have long known that the difference between success and failure depends on customer satisfaction, provided by a quality workforce (Ford and Heaton 2001), and it follows that an organization that is better able to attract and retain a high-quality workforce will have an advantage over its competitors. This link between human resources (HR) management and profitability is reinforced by Kotler, Bowen, and Makens (2003), who bring a marketing perspective to HR management when they write that “good internal programs create employee satisfaction, which in turn creates customer satisfaction” (Kotler, Bowen, and Makens 2003, p. 353). Despite the recognized relationship between high-quality employees and the success of tourism organizations, turnover in the industry has remained consistently high (Hoque 2000; Jerris 1999; Sims 2007; Wood 1992; Woods 1997), a problem that is in part caused by, and in part exacerbated by, the fact that so many tourism organizations rely on seasonal employees.

There are many ways in which turnover can negatively impact an organization. Financially, turnover increases direct costs related to recruiting and training new employees each year. Hinkin and Tracey (2000) identified categories of costs associated with turnover that include recruitment costs (advertising and search fees), selection costs (interview and reference checking), hiring costs (induction and initial training, relocation expenses, uniforms), lost productivity costs from unfilled positions, the learning curve of new employees, and loss of expertise. Moreover, turnover has been associated with diminished service quality (Milikić 2010), and Adidam (2006) has contended that an inability to retain seasonal employees could damage an organization’s reputation: “High turnover sends a very clear signal that something is wrong somewhere in an organization” (p. 137).

Because of the negative impacts of turnover, the ability to retain high-quality seasonal employees is important to individual organizations and collectively to successful tourism destinations (Martensen and Grønholdt 2001). Although much research has been conducted on employee turnover, few studies have focused on the retention of seasonal employees despite the importance of this issue to the tourism industry (Lee and Moreo 2007; Reynolds, Merritt & Gladstein 2004); The few studies that have been conducted in this area (e.g., Alverén et al. 2012; Dickson and Huyton 2008; Ismert and Petrick 2004; Lee and Moreo 2007; Lundberg, Gudmundson, and Andersson 2009; Sims 2007) have made important contributions to better understanding issues of seasonal tourism employment. However, they, like all studies, have limitations. Two important limitations of tourism seasonal employee retention studies (including those cited in the previous sentence) include that they (1) focus on existing employees, and not those who have left organizations, and (2) study turnover intention, rather than actual turnover behavior. Another commonality among these studies is that they all focus primarily on issues related to job satisfaction. This study aims to make a contribution to the seasonal employment retention literature by examining the issue while addressing these limitations.

Job satisfaction has been a very common lens through which to examine employee retention (Mitchell et al. 2001), and most studies have indeed found a relationship between job satisfaction and turnover intention. Despite the contributions of these studies, however, retention of seasonal employees remains an important issue to tourism managers. Moreover, many tourism industries provide jobs that have very similar responsibilities and require similar types of qualifications (e.g., downhill ski instructor). Because of this, satisfaction with the job itself might not vary too much from organization to organization, suggesting that another construct might be worth studying in addition to job satisfaction.

Many of the retention and turnover studies that have examined various elements of job satisfaction have found a relationship between retention and the work environment (Earle 2003; Mobley 1982; Reynolds, Merritt, and Gladstein 2004), organizational culture (Earle 2003; Swanljung 1981), camaraderie (Alverén et al. 2012; Ismert and Petrick 2004; Lee-Ross 1995), and social relations (Alverén et al. 2012; Ismert and Petrick 2004; Lee-Ross 1995). Because each of these factors are independent of job responsibilities and could be impacted by organizational policies and managerial actions, studies that focus on their relationship with retention may be worthwhile. One construct that comprises many of these factors is sense of community.

Prior to the industrial revolution, people were more communal than today and found a sense of community in their towns, neighborhoods, churches, and other places where common values, shared responsibilities, and interpersonal interactions were a part of everyday life (Chavis et al. 1986). For many people today, it is the workplace that provides this opportunity to experience a sense of community (Burroughs and Eby 1998). Colleagues can provide support during difficult times, and a workplace team may provide a sense of camaraderie and community that may no longer be available outside of work. Moreover, the need for community may be greater for seasonal tourism employees given the fact that many employees have relocated away from family and longtime friends, and that the working conditions of seasonal tourism jobs can be challenging as a result of such factors as low pay, long hours, night and weekend schedules, lack of personal time, little opportunity for advancement and growth, routine and demanding job responsibilities, and dissatisfaction with supervisors (Pavesic and Brymer 1990).

In an exploratory narrative study of tourism leadership, Harris (2009) discussed the importance of developing a sense of community among staff. Others have examined the relationship between sense of community and retention in contexts other than tourism employment, including residential neighborhoods (Graves 2012), festival attendance (Drengner, Jahn, and Gaus 2012), university students (Jacobs and Archie 2008), and unions (Catano et al. 1993). Perhaps the most relevant previous study was conducted by McCole et al. (2012), who found a strong relationship between sense of community and seasonal employees in a residential summer camp setting. These studies assist in justifying a study of the relationship between sense of community and seasonal tourism employee retention.

Psychological Sense of Community

This article proposes that in addition to commonly studied constructs such as job satisfaction, another construct, Psychological Sense of Community (henceforth referred to as sense of community or SOC), impacts seasonal employees’ decisions about whether to return to work at a ski resort. A review of online ski job postings shows that most ski resorts across North America offer very similar jobs with similar responsibilities. It is argued here that satisfaction with the job itself may vary little from resort to resort and, therefore, some other construct could be responsible for influencing seasonal employees’ decisions to return to the same resort year to year, rather than taking a similar job at another resort.

Many scholars and psychologists had talked about sense of community for years before Seymour Sarason (1974) established the concept in his seminal work on the subject. Sarason is largely credited with sparking SOC as a field of study. A dozen years later, after scholars had conducted several studies related to the concept of sense of community, McMillan and Chavis (1986) developed a theory by identifying the elements that work together to produce the experience of sense of community. They proposed the following definition for sense of community: “Sense of community is a feeling that members have a belonging, a feeling that members matter to one another and to the group, and a shared faith that members’ needs will be met through their commitment to be together” (p. 9). Their proposed conceptual framework has four elements that make up sense of community and each of these four elements has a number of attributes, all of which together comprise SOC. The first element is membership, which describes the sense of belonging that community members feel. Influence addresses members’ sense of mattering and making a difference to the group. The third element is integration and fulfillment of needs. This is the feeling that community members meet other members’ needs while they meet their own. The last element is shared emotional connection, which is the commitment and belief that members have and will continue to have shared experiences together. Today McMillan and Chavis’s work persists as the principal framework for SOC research in both geographic and relational contexts, leading Mannarini and Fedi (2009) to conclude that it “remains the primary theoretical anchorage for most studies in SOC” (p. 212).

Although the McMillan and Chavis theory has been widely applied in academic research, it has been the topic of ongoing debate over the years as scholars aim to advance their understanding of SOC. Most of the debate around the McMillan and Chavis four-factor theory has focused on how it is measured, specifically with regard to the factor structure (Chipuer and Pretty 1999; Long and Perkins 2003; Obst and White 2004 ; Obst, Zinkiewicz, and Smith 2002; Peterson, Speer, and Hughey 2006).

Recently, Nowell and Boyd (2010) brought the academic conversation on SOC itself asking the question, “are we measuring the right things?” rather than “are we measuring things the right way?” (p. 829). They go on to argue that sense of community has been viewed from a human needs theory perspective where community is a “resource” that provides for members’ physiological and psychological needs, such as affiliation, power, and affection. Nowell and Boyd propose a values-based perspective for sense of community in which “one’s sense of connection to the community is rooted in a sense of responsibility for the community that may exist independent of any expectation of needs fulfillment” (p. 829). In a response to the Nowell and Boyd article, McMillan (2011), the lead author on the work that introduced the theory of Psychological Sense of Community (McMillan and Chavis 1986), disputes that the Sense of Community theory he and Chavis proposed viewed SOC as a resource rather than a responsibility. The McMillan (2011) article provides several examples from the original work that demonstrated how SOC is both a resource and responsibility.

Although understanding of SOC continues to progress, the elements and subelements of SOC that McMillan and Chavis presented, include several possible explanations for a link between SOC and retention whether the theory is viewed from the perspective of the community as a resource or as sense of community as responsibility. These include that members make a personal investment to the community (and, therefore, lose that investment by leaving the community); that members are attracted to groups over which they are allowed to influence (and with seasonal jobs, opportunities for influence are more likely when employees return, are known, and have seniority than when they are new); that a bond develops among those who spend time together, and deepens the more time they spend with one another (something employees may not wish to sacrifice by moving to a new employer); that members feel a sense of responsibility for the well-being of the community (and might therefore return to an organization to support their fellow “community members”); that when people with similar values come together, they find that they have similar priorities, needs, and goals and therefore realize they might be better able to meet their needs by remaining together (if employees have found a place that is consistent with their values, leaving for a new place comes with the risk that some needs won’t be met as well).

These proposed links between elements of SOC and retention are supported by theory. One of the oldest theories to explain behavior is the reinforcement theory of motivation (Skinner 1938), which purports that an individual’s behavior is a function of its consequences. Applying this theory to the present context, if a seasonal employee’s needs (e.g., need for affiliation and need to influence) are met at a particular organization, she would seek to reinforce that need fulfillment by returning to the resort the following year; if her needs are not met, she would seek a different community (employer) the following year. As McMillan and Chavis write, “people do what serves their needs” (1986, p. 8). This view supports rational choice models; however, as Nowell and Boyd (2010) contend in their explanation of SOC as responsibility, community members often act in irrational ways that benefit their communities without expecting personal benefit for themselves. They argue that such behavior is attributed to a sense of responsibility and draws from logic of appropriateness including institutional theory, cultural theory, and sense making (e.g., Hall 1980; Meyer and Rowan 1976; Weick Sutcliffe, and Obstfeld 2005). This notion of SOC as responsibility could also help to explain why people who feel a sense of community at an organization would return the next year out of a responsibility to other community members.

The Present Study

This study examined the relationship between sense of community and the retention of seasonal employees at four ski resorts in the United States. The United States is home to nearly 500 of the world’s 2,100 ski areas (Skistar 2012). During the 2011-2012 ski season, the United States experienced 60.1 million skier-days, generating $6 billion in direct spending at U.S. ski resorts (NSAA 2012). Despite this high level of tourism activity, growth in the U.S. ski industry has been stagnant in recent years (Brooke 2005), creating a zero-sum market in which ski areas must compete for a relatively fixed number of skiers by offering the best possible ski resort experience. That experience is largely influenced by the resort’s employees. According to a study of visitors to 10 U.S. ski resorts, 78% indicated that employee attitudes were important or very important to the quality of their experience, and 100% indicated that employee attitudes are at least slightly important to ski resort quality (Ormiston, Gilbert, and Manning 1998).

The ski industry sees service quality as a means to gain competitive advantage (Hudson and Shephard 1998) and has long known about the importance of employees in providing a high-quality tourism experience. About 20 years ago, Peter Drucker (1992) stated that ski organizations routinely report that people are their greatest assets. Around that time, the general manager of Aspen Snowmass ski resorts explained the importance of human resources to the ski industry when he reflected:

I learned early on that we’re in the people business. Every ski area has lifts, parking lots, restaurants and machinery. Yet one is more successful than the next because of the way its management treats its employees and in turn, the way employees treat the guest. (Campbell 1993, p. 43)

Ismert and Petrick (2004) later supported this notion when they wrote that human resources challenges are among the most pressing issues for the ski industry. Although ski resorts face several human resources challenges, employee retention has been identified as a particularly important challenge to ski resorts.

Purpose

The primary purpose of this study was to examine the relationship between a seasonal ski resort employee’s sense of community (SOC) toward the organization, and the likelihood of returning to work at the resort the following season. A secondary objective of the study was to examine the SOC-retention relationship among first-year employees and experienced employees. Ismert and Petrick (2004) found that camaraderie and social relationships were more important for first-year employees than for more experienced seasonal employees, and recommended managers consider using different incentives to retain employees based on their experience level. Because the current study examines retention from the perspective of organizational community, which is related to camaraderie and social relationships, the researcher wanted to examine whether a similar phenomenon existed for first-year employees as Ismert and Petrick observed.

Five research questions guided this research:

Research question 1: Are sense of community levels higher for seasonal employees who return to their resort than those who do not return the following winter?

Research question 2: Are sense of community levels higher for those who indicate a desire to return to their resort, even if they do not return?

Research question 3: Is sense of community toward an organization a good predictor variable for a seasonal employee’s return to that organization the following year?

Research question 4: Is sense of community toward an organization a good predictor variable for a “first-year” seasonal employee’s return to that organization the following year?

Research question 5: Is sense of community toward the organization a good predictor variable for an “experienced” seasonal employee’s return to that organization the following year?

For this study, the definition of an experienced employee matches that of Ismert and Petrick (2004) and includes any employee who has worked at the organization for more than one season.

Method

Subjects

This study involved 1,264 employees from four ski resorts in the Rocky Mountain region of the United States during a three-week period approximately one month before the opening of the ski season. Previous studies involving seasonal employees at ski resorts (Alverén et al. 2012; Dickson and Huyton 2008; Ismert and Petrick 2004; Lee and Moreo 2007; Lundberg, Gudmundson, and Andersson 2008; Sims 2007) have taken place during the ski season, presumably to take advantage of participants being gathered in one geographic area. For this study, however, the researcher believed it was important to survey participants during the ski “off-season” as the decision to return to work at the resort (or not return) is generally made during this time. Also, one limitation of many employee retention studies is that they only involve existing employees and not those who have left the organization. In an effort to form a more complete understanding of the issues of retention, this study sampled all seasonal employees who had worked at the resorts the previous year, regardless of whether they ultimately returned to work at the resort (“returnees”) or did not return (“nonreturnees”) for the upcoming ski season. Subjects were contacted via email about one month before the winter ski season using addresses provided by the resorts. To differentiate between returnees and nonreturnees, respondents were asked whether they intended to return, and later the lists of names for each group were verified with the resorts.

Procedure

The attempt to survey employees during the skiing off-season presented a challenge in reaching participants because they were scattered around the world. To effectively contact the seasonal employees from the previous ski season, emails with links to a web-based survey were used in this study. Dillman, Smyth, and Christian (2008) explained that with certain populations, the increased reach of electronic surveys can help to increase the percentage of the target population sampled. Since a large portion of the sample population in this study were in their 20s, it seemed likely that most would have access to, and familiarity with, the Internet. According to a Pew study (Zickuhr and Madden 2012), 97% of Americans aged 18–29 use the Internet. Moreover, every seasonal employee at the resorts had provided email addresses with their contact information, and all four resorts reported using those email addresses to communicate with employees. This information supported the use of an Internet-based survey with the target population, without unreasonably increasing the chance of sampling bias. The 532 seasonal employees who completed surveys represented a 42% response rate of the 1,264 employees whose emails were not returned because of bad addresses, although it is likely that this response rate is actually higher, since some of the email addresses provided by the resorts may have been incorrect or abandoned but did not elicit a “dead” email address response.

Instrument

The survey used for this study included items to measure sense of community, job satisfaction, wage, experience at the resort, and demographic information. To measure sense of community, the survey included the Brief Sense of Community Index (SCI) (Perkins et al. 1990). The SCI is based on the construct developed by McMillan and Chavis (1986) and as such is one of the few measures of community that is grounded in psychological theory (Chipuer and Pretty 1999). The SCI consists of 12 items and produces a score for each participant ranging from 0 to 12, with the higher scores indicating a higher sense of community.

Although many studies have shown the SCI to be a valid measurement of SOC, it has received some criticism over the years (Chipuer and Pretty 1999; Long and Perkins 2003; Obst and White 2004; Peterson, Speer, and Hughey 2006). The validity and reliability of the SCI as a measurement of overall sense of community has been satisfactory; however, measurement of the four dimensions of Sense of Community have shown inconsistent and low reliability. Despite the criticisms of the SCI as a reliable measure of the four dimensions, the general consensus among community psychology scholars is that the SCI is still a valid measure of overall SOC. Obst and White (2004) explain, “Whereas a growing body of evidence points to the inadequacy of the current SCI to measure these four dimensions, the present findings indicate that the SCI does have good internal consistency as a measure of overall Sense of Community” (p. 703). At the time the present study was being planned and piloted, two instruments had recently been developed that claimed to be valid measures of both overall SOC and the four dimensions of the construct: the Brief Sense of Community Scale (Peterson, Speer, and McMillan 2008) and the Sense of Community Index–2 (Chavis, Lee, and Acosta 2008). However, because no other studies had yet supported either of these, the researcher used the SCI as an overall measure of SOC because it had wide support for such use in the literature.

Per the recommendations of the instrument’s authors, a change in instructions for this study replaced the words “neighbors” and “block” with “fellow employees” and “(name of) resort” (see Appendix A). This type of adaptation to this instrument is quite common and it has been used successfully to measure sense of community in many different settings, including adults in the workplace (Burroughs and Eby 1998; Klein and D’Aunno 1986; Pretty and McCarthy 1991; Pretty, McCarthy, and Catano 1992), religious communities (Miers and Fisher 2002), immigrant groups (Sonn and Fisher 1996), college students (McCarthy, Pretty, and Catano 1990; Pretty 1990), Internet communities (Obst, Zinkiewicz, and Smith 2002), residential neighborhoods (Chipuer and Pretty 1999; Kingston et al. 1999; Pretty, Andrews, and Collett 1994), and union participation (Catano et al. 1993). Additionally, a pilot test for this survey was conducted with 20 former employees of ski resorts and each indicated in postsurvey interviews that the changes in words to the SCI (i.e., “resort” instead of “neighborhood”) were understood as the researcher intended.

To examine constructs beyond SOC, and to include comparison variables for the logistic regression model, a single-item measure of job satisfaction (Yang, Brown, and Moon 2011) was included in the survey, as was an item that asked subjects to report their hourly wage from the previous year. Standard demographic questions were also included in the survey.

Data Analysis

The Sense of Community Index (SCI) produced scores for each respondent and independent t-tests were used to compare SCI mean scores between variables to address each of the first two research questions. For research questions 3–5, logistic regression was employed to assess which factors best predicted actual year-over-year retention. Logistic regression was used because in this case, the dependent variable is binary (whether or not a seasonal employee returned to work at the same resort). For significant differences resulting from the t-tests, effect size was calculated for all significant mean differences using Cohen’s d. Cronbach’s alpha was used to compute internal reliability of the dichotomous variables.

Results

Of the 532 respondents, 59% were male, 15% were international employees, 88% were Caucasian, 10% were Hispanic or Latino, and the mean age was 27. The two most common jobs were instructor (24%) and lift operator (16%). Ski patrol, food and beverage server, cook, and supervisor each comprised 7% of the respondents. The average number of seasons employed at the resort was 1.9, the average hourly wage was $10.22, and 70% of respondents were first-year employees. Of those responding, 33% returned to work for their same resort (“returnees”). The mean job satisfaction score for all respondents was 2.75 out of 5, with returnees reporting higher job satisfaction scores than nonreturnees (Table 1).

Table 1.

Differences in Job Satisfaction by Seasonal Employee Return Status.

Return status	n	Job Satisfaction		t(530)	p	d
Return status	n	M	SD	t(530)	p	d
Returnees	360	2.42	0.993	−11.414	<.001	1.08
Nonreturnees	172	3.44	0.900

The mean SCI score for all 532 analyzed respondents was 7.66 on a scale of 0 to 12, with 12 indicating the highest level of sense of community. The Cronbach’s alpha for the SCI was .77. A comparison of the mean SCI scores for those who returned (returnees) and those who did not return (nonreturnees) not only showed a statistically significant difference, but also a strong effect size of .86 (Table 2). These results add support to the first hypothesis that returnees have higher sense of community levels than nonreturnees.

Table 2.

Differences in SCI by Seasonal Employee Return Status.

Return status	n	Sense of Community		t(530)	p	d
Return status	n	M	SD	t(530)	p	d
Returnees	360	7.08	2.24	−9.078	<.001	0.86
Nonreturnees	172	8.88	1.95

Because one of the resorts was concerned that many of the nonreturnees would have wanted to return to the resort but could not for a number of reasons (i.e., new full-time jobs, university attendance, etc.) another research question involved desire to return. To operationalize those with a desire to return, respondents who indicated that they would not be returning to the same resort were asked if they “wanted to return.” Of the 360 nonreturnees, 188 (52%) indicated that they wanted to return, even though they did not return. The scores of these respondents were combined with returnees (who presumably wanted to return, though weren’t asked) to form a dummy variable for those who “desired to return.” The results of this survey item were used to address the second research question involving desire to return to the same resort. The sense of community scores for those who showed a desire to return to their resort were significantly higher (p < .001) than the nonreturnees who did not “want to return” with a very high effect size of 1.9 (see Table 3). This suggests that those with a desire to return to the same resort, whether they do or not, have higher sense of community levels than those who do not have a desire to return to work at the same resort they worked at the previous winter.

Table 3.

Differences by Desire to Return to the Same Resort as the Previous Winter.

Return status	n	Sense of Community		t(530)	p	d
Return status	n	M	SD	t(530)	p	d
Desire to return	359	8.73	1.79	20.875	<.001	1.90
No desire to return	173	5.42	1.53

To address the third research question (whether sense of community is a good predictor of whether an employee actually returns the following season), logistic regression analysis was conducted to predict seasonal employees’ retention using SCI, job satisfaction, hourly wage, age, years employed at the resort, and gender as predictors (see Table 4). A test of the full model against a constant-only model was statistically significant, indicating that the predictors, as a set, reliably distinguished whether a seasonal employee returned to work at his/her resort (chi-square = 207.706, p < .001, with df = 6). Nagelkerke’s R² of .458 indicated a moderate relationship between prediction and grouping variables. Prediction success overall was 80.7% (90.4% for nonreturnees and 60.1% for returnees). The Wald criterion demonstrated that SCI, job satisfaction, gender, and age made significant contributions to prediction. Hourly wage and number of years employed at the resort were not significant predictors, both falling just outside the significance level of .05. The exp(B) value indicates that when SCI increases by one unit (on a scale from 0 to 12), the odds ratio is 1.38 times as large and therefore seasonal employees are about 1.4 times more likely to return to a resort for every 1-point increase in SCI score. Similarly, and related to other studies of seasonal employee retention that found a relationship between job satisfaction and retention (e.g., Alverén et al. 2012; Dickson and Huyton 2008; Ismert and Petrick 2004; Lee and Moreo 2007; Lundberg, Gudmundson, and Andersson 2008; Sims 2007), a 1-unit increase in job satisfaction score (on a scale from 1 to 5) means employees are about 2.2 times more likely to return to their resort. Although this may seem to indicate that job satisfaction is a stronger predictor of return than SCI, it is important to remember that the SCI is a more sensitive measurement (a 12-point scale) compared to job satisfaction (a 5-point scale), and therefore offers more opportunity for 1-unit increases (or decreases). To better compare the strength of SCI and job satisfaction as predictors of year-over-year employee retention, the scores for SCI, job satisfaction, hourly wage, age, and years of employment were standardized and another logistic regression was conducted. Table 5 shows that once standardized, SCI and job satisfaction are still the strongest predictors of retention, and although job satisfaction still has a higher exp(B) than SCI, the difference is small, indicating that an increase in sense of community is about as likely to lead to employee retention as an increase in job satisfaction.

Table 4.

Logistic Regression Results for Seasonal Employee Year-to-Year Retention.

Model χ²	df	Significance	–2 Log L	Nagelkerke R²
207.706	6	<.001	449.734	.458
Model classification accuracy rate	80.7%
Nonreturnees	90.4%
Returnees	60.1%
	B Value	SE	Wald	Significance	Exp(B)
Step 1^a
Job satisfaction	0.779	0.130	36.184	<.001	2.180
Gender (0 = F; 1 = M)	0.991	0.242	16.775	<.001	2.694
Seasons current resort	0.195	0.102	3.669	.055	1.216
SCI	0.322	0.062	26.816	<.001	1.380
Hourly wage	0.117	0.066	3.107	.078	1.124
Age	0.044	0.015	8.582	.003	1.045
(Constant)	−8.863	0.903	96.389	<.001	0.000

Table 5.

Logistic Regression Results for Seasonal Employee Year-to-Year Retention Using Standardized Scale Scores.

Model χ²	df	Significance	–2 Log L	Nagelkerke R²
207.706	6	<.001	449.734	.458
Model classification accuracy rate	80.7%
Nonreturnees	90.4%
Returnees	60.1%
	B Value	SE	Wald	Significance	Exp(B)
Step 1^a
Job satisfaction	0.837	0.139	36.184	<.001	2.310
Gender (0 = F; 1 = M)	0.991	0.242	16.775	<.001	2.694
Seasons current resort	0.317	0.166	3.669	.055	1.373
SCI	0.743	0.143	26.816	<.001	2.102
Hourly wage	0.279	0.159	3.107	.078	1.322
Age	0.412	0.141	8.582	.003	1.509
(Constant)	−1.487	0.179	69.402	<.001	0.000

Logistic regression was also conducted to predict retention among first-year employees using SCI, job satisfaction, hourly wage, age, and gender as prediction variables (research question 4). A test of the full model against a constant only model was also statistically significant, but the Nagelkerke’s R² of .255 indicated a much weaker relationship between prediction and grouping variables (see Table 6). Prediction success overall was 82.0%, higher than the first model, but prediction success was much higher for nonreturnees (96.9%) than for returnees (27.6%), indicating that although the model seems to predict first-year employees who do not return with great success, it is a weaker predictor for first-year employees who do return to work at their resort. The Wald criterion demonstrated that SCI, job satisfaction, gender, and hourly wage made significant contributions to prediction. Exp(B) values indicate that for first-year employees, the likelihood that job satisfaction and SCI will lead to an employee’s return is about 1/5 less than with the overall seasonal workforce. These indicate that both job satisfaction and SCI are still stronger predictors of retention than wage and age, but not as strong among first-year employees as among the overall workforce.

Table 6.

Logistic Regression Results for Year-to-Year Retention of First-Year Seasonal Employees.

Model χ²	df	Significance	–2 Log L	Nagelkerke R²
65.894	5	<.001	310.799	.255
Model classification accuracy rate	82.0%
Nonreturnees	96.9%
Returnees	27.6%
	B value	SE	Wald	Significance	Exp(B)
Step 1^a
Job satisfaction	0.710	0.167	36.184	<.001	2.034
Gender (0 = F; 1 = M)	0.639	0.293	16.775	.029	1.895
SCI	0.518	0.171	26.816	.003	1.679
Hourly wage	0.492	0.214	3.107	.021	1.635
Age	0.092	0.258	8.582	.772	1.096
(Constant)	−1.602	0.241	44.161	<.001	0.201

To address the fifth research question, another logistic regression was conducted to predict retention among experienced employees (those who had worked at their resorts for more than one year), using the same prediction variables as for first-year employees (SCI, job satisfaction, hourly wage, age, and gender). A test of the full model against a constant-only model was statistically significant and the Nagelkerke’s R² of .618 indicated a moderately strong relationship between prediction and grouping variables (see Table 7). Prediction success overall was 83.6%, and unlike the model for first-year employees, was fairly strong for both nonreturnees (73.3%) and returnees (90.2%). The 90.2% prediction success rate for returnees is larger than the 60.1% for returnees in the model for the entire workforce and much higher than the 27.6% success rate in the model for first-year employees. This suggests that the model is a very good predictor of return for experienced employees, and a fairly good predictor for nonreturnees. The Wald criterion demonstrated that SCI, job satisfaction, gender, and age made significant contributions to prediction. Exp(B) values indicate that the likelihood that job satisfaction will lead to an employee’s return is about the same as it was for the overall seasonal workforce. However, the Exp(B) is much higher for SCI in this model, indicating that a 1-unit increase in SCI will increase the likelihood that experienced employees will return to their resorts by nearly five times.

Table 7.

Logistic Regression Results for Year-to-Year Retention of Experienced Seasonal Employees.

Model χ²	df	Significance	–2 Log L	Nagelkerke R²
92.709	5	<.001	111.220	.618
Model classification accuracy rate	83.6%
Nonreturnees	73.3%
Returnees	90.2%
	B Value	SE	Wald	Significance	Exp(B)
Step 1^a
Job satisfaction	0.983	0.310	10.076	.002	2.674
Gender (0 = F; 1 = M)	1.623	0.535	9.206	.002	5.068
SCI	1.602	0.397	16.279	.000	4.961
Hourly wage	−0.202	0.243	0.691	.406	0.817
Age	0.682	0.307	4.933	.026	1.978
(Constant)	−0.784	0.442	3.151	.076	0.456

Discussion and Conclusions

The purpose of this study was to examine the issue of seasonal employee turnover, which can cause many negative impacts on tourism organizations. Most of the existing studies of seasonal employee turnover/retention have examined the issue from the perspective of job satisfaction and have generally found a link between the two, yet the need to improve seasonal retention persists. This study addressed the seasonal employee turnover/retention issue through an additional lens by examining the relationship between a seasonal employee’s sense of community level toward their organization and the likelihood of that employee returning to work for the organization the following year. If a relationship exists between the two, it may be possible for an organization to increase year-to-year employee retention rates by improving the sense of community throughout the organization. It should, however, also be noted that many employees only plan to spend one season working at a ski resort, so some level of variance in return will go unexplained regardless of the constructs measured. The sense of community construct used in this study (Macmillan and Chavis 1986) offers suggestions that can help guide ski resort managers’ efforts to increase sense of community throughout their organization. This study differed from many other studies of seasonal employee retention by including both current employees and past employees, as well as by using actual turnover (or return) rather than intention to turnover as a dependent variable.

The differences in sense of community scores between returnees and nonreturnees, and between those who desired to return and those who did not desire to return to their resorts, suggest that there is indeed a relationship between sense of community and retention of seasonal employees. Further, the logistic regression model suggests that increasing sense of community will increase the likelihood of a seasonal employee returning the following year. Retaining a higher percentage of desirable seasonal employees can be an important source of competitive advantage for organizations, as turnover has been linked to financial costs, (e.g., Hinkin and Tracey 2000), diminished service quality (e.g., Milikić 2010), and organizational reputation (e.g., Adidam 2006). The results of this study suggest that tourism organizations might be rewarded by developing a sense of community among their employees.

Lundberg, Gudmundson, and Andersson (2009) found that the seasonal workforce at tourism organizations has subgroups that have different needs. In another study of North American ski resort seasonal employees, Ismert and Petrick (2004) found that first-year seasonal employees and more experienced seasonal employees differed in the factors that lead to job satisfaction. The findings of the present study support the findings of Ismert and Petrick in that sense of community seemed to impact the retention of first-year employees differently than experienced employees, and this finding is consistent with Louis’s work (1980) on the importance of socialization among newcomers to an organization. For first-year employees, sense of community was a weaker predictor for those who returned than it was for those who did not return. This could suggest that sense of community acts as a hygiene factor (Herzberg, Mausner, and Snyderman 1959), meaning that although a high sense of community will not necessarily predict an employee’s return, low sense of community might influence an employee’s decision to not return. However, the results from experienced employees suggested that sense of community was a strong predictor for those who did not return and a very strong predictor for those who did.

This difference between first-year and experienced employees is consistent with the elements and subelements that comprise the sense of community construct. As previously mentioned, the McMillan and Chavis theory (1986) indicates that community members develop a deeper bond as they spend more time together and share experiences. To address this, resorts could organize more events that aim to create shared emotional connections between first-year and experienced employees. Even policies related to housing and behind-the-scenes employee common areas could create space for connections to occur.

Additionally, the element of membership involves the sense of belonging that community members feel. Community members who perceive themselves as being on the outside of an existing community will tend to have a lower sense of community than those who feel as though no community exists. In other words, an individual’s sense of community may be lower if a community exists and he/she is not part of it, than if the overall sense of community is weak throughout the community. It is therefore possible that first-year employees feel that the experienced employees, for whom sense of community is a good predictor of return to the organization, are part of a community that they themselves do not feel a part of. If this is accurate, resorts could work to better integrate first-year and experienced employees. Also, because another of the four elements of sense of community is influence, one way of integrating first-year and experienced employees might be to ask experienced employees to mentor first-year employees with specific instructions to introduce them to other experienced employees. This would likely improve the sense of influence among the experienced employees, while increasing the likelihood that the first-year employees feel more like they are members of the community at the resort.

The Ismert and Petrick study (2004) showed that satisfaction with camaraderie was shown to be the strongest indicator of intention to return for first-year employees. That study also showed that for experienced employees, satisfaction with compensation was more important. In the present study, sense of community was a stronger predictor for experienced employees than for first-year employees and wages were not found to be a significant predictor variable in the logistic regression model for experienced employees, whereas it was a significant variable in the model for new employees.

Based on their results, Ismert and Petrick (2004) recommended that tourism managers consider different approaches to retention for new employees and experienced employees. The present study supports that recommendation; however, the specific ways in which leaders should address retention of these subgroups is somewhat different than the Ismert and Petrick study which recommended that “ski resort management may find success in using team-building activities for first-year employees, while returning employees would benefit more if resources were used to increase compensation.” (p. 54). The results of the present study would not necessarily recommend the opposite of this, but with regard to the recommendation of team building, would recommend that it include first-year employees and experienced employees together, rather than simply among first-years. The results also suggest that with regard to increasing the odds of retaining an experienced employee, investing in the development of sense of community may be a better investment than investing in higher wages, since SCI was found to be a strong predictor variable of retention among experienced employees, and wages were not found to be a significant predictor of retention.

In addition to enhancing the literature on seasonal employee retention, this article contributes to the growing number of recent articles in the Journal of Travel Research (JTR) that address important issues related to ski resort management. Ski holidays are an important segment of the tourism economy, and like any tourism industry, ski resorts face unique issues and have distinctive research needs. This study, like the Ismert and Petrick study (2004), addressed the important challenge of attracting and retaining high-quality seasonal staff. Other recent JTR papers have addressed issues equally important to the industry, including the development of quality indicators and standards (Ormiston, Gilbert, and Manning 1998), the effect of promotional discount programs on skier behavior (Perdue 2002), the impact of weather on lift ticket sales (Shih, Nicholls, and Holecek 2009) and the motivations and normative evaluations of summer visitors (Needham et al. 2011).

The present study is the second one to find a link between sense of community and the retention of seasonal employees (McCole et al. 2012 is the other). This supported link seems to be a promising area for further examination in other organizational contexts including those with year-round employees. Studies could also research other organizational benefits of sense of community besides employee retention. Past studies on SOC have identified several benefits to employees who experience a high sense of community (Burroughs and Eby 1998; McCarthy, Pretty, and Catano 1990; McMillan and Chavis 1986; Pretty and McCarthy 1991; Pretty, McCarthy, and Catano 1992). The collective assessment of these studies is that employees with high senses of community will be superior performers. Examining this assessment directly would be a worthwhile endeavor. Another suggestion for further research would be to examine the success of initiatives to build sense of community. Such a study could help to determine (1) which initiatives actually raise sense of community levels among employees and (2) whether retention rates change in direct relationship to sense of community scores.

This study has several limitations. First, as previously mentioned, studies have shown the SCI to be a valid measurement of overall SOC; however, it is no longer considered to be a valid measurement of the four dimensions of the SOC construct. An instrument that could provide valid data on the four dimensions might give more insight as to which elements of sense of community have a stronger link to employee retention and therefore more practical insights to tourism managers. Over time, a more valid and reliable measure of SOC and its four dimensions may emerge from the literature and would be recommended for use in future studies.

Other limitations concern generalizability. This study was conducted at four ski resorts in the western United States. Because of geographic boundaries (mainly mountains), the resorts exist in somewhat isolated and relatively small communities, and employees tend to interact outside of work more than they might in a different environment. Moreover, the communities around the ski resorts have limited space for development, causing high housing prices. It is therefore common for seasonal staff to share housing in greater numbers than they might do in environments with more affordable housing options. These factors would seem to have a distinct effect on one’s sense of community and although other types of tourism organizations might find these results useful, generalization would require further study. Moreover, the selection of resorts were not randomly sampled, but rather responded to a request to participate, a sampling design, which also restricts generalizability. Response rate is another limitation. Although the rate of 42% is adequate when compared to other comparable studies that used unsolicited web-based surveys, this rate also limits generalizability. In conclusion, it is hoped that this study contributes to the literature by examining a construct, sense of community, which appears to impact seasonal employees’ decisions to return to their organization. Moreover, the elements and subelements of the sense of community construct provide tourism managers with insights on how they might improve retention among their seasonal employees while increasing sense of community levels.

Footnotes

Appendix A

Declaration of Conflicting Interests

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

Funding

The author disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The author thanks Michigan AgBio Research and National Institute of Food and Agriculture (NIFA) for supporting the research program that has led to this publication.

Author Biography

Dan McCole, Ph.D., MBA is an Assistant Professor in the Department of Community Sustainability at Michigan State University. His academic work focuses on the role of natural resource- and agriculture-based tourism on sustainable community/regional development. Specific research interests include collaborative planning/collective action, human resources management and evaluation.

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