Employee Retention in the Ski School Industry
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Employee Retention in the Ski School Industry

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The goal of this research project was to provide understanding of employee retention the ski school industry. To prepare for this research, ideas were developed based on the results from previous ...

The goal of this research project was to provide understanding of employee retention the ski school industry. To prepare for this research, ideas were developed based on the results from previous studies; Hinkin and Tracey (2000, 2006, 2008), Milman (2002), and Ismert and Petrick (2004). Being that jobs in the ski school are seasonal, retention was measured as the intent to return the following season. To assess the reasons for retention, five factors related to retention were presented to participants.

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    Employee Retention in the Ski School Industry Employee Retention in the Ski School Industry Document Transcript

    • Employee Retention in the Ski School Industry byMontgomery Bopp Research was completed from August-September of 2011 as part of the curriculum for a M.S. in Industrial/Organizational Psychology at Springfield College in Springfield, MA. The population for this research was gathered from the Mount Snow Ski School in West Dover, VT. Abstract: The goal of this research project was to provide understanding of employee retention the ski school industry. To prepare for this research, ideas were developed based on the results from previous studies; Hinkin and Tracey (2000, 2006, 2008), Milman (2002), and Ismert and Petrick (2004). For the purposes of this presentation, the Procedures, Statistical Analysis, Survey Sample, and Review Of Literature sections have been moved to follow the Conclusion section. Method The goal of this research was to understand retention in the ski industry. Being that jobs in the ski school are seasonal, retention was measured as the intent to return the following season. To assess the reasons for retention, five factors related to retention were presented to participants. The participants, measures, procedures, and statistical analysis are discussed in detail in the methods section. Participants Participants for this study were eighty-five (n = 85) male and female ski instructors from Mount Snow in West Dover, Vermont. Participants were grouped based on age (18-35, 36-50, 51+), experience (1-2 years, 3-9 years, 10+ years), part-time or full-time status, and full-day or hourly program types. As required by this study all participants were 18 years of age and above. The following table provides group sizes for each demographic criteria: 0 10 20 30 40 50 60 70 80 Age Experience Status Program 18-35 (n=28) 36-50 (n=29) 51+ (n=28) 1-2 yrs (n=29) 3-9 yrs (n=29) 10 yrs (n=27) Part-Time (n=68) Full-Time (n=17) Full-Day (n=47) Hourly (n=38)
    • Measures Participants completed a survey on surveymonkey.com. Demographic measures included in the survey required participants to list age, years of experience, employment status (either part-time or full-time), and the type of program they worked in (either full-day or hourly programs). To measure the intention to return, participants responded to the question “If the opportunity is available, do you plan to return to Mount Snow for the 2011-2012 season?”, with a response choice of yes or no. Measurements were taken for five factors related to retention; (1) agreement with management, (2) pay, (3) benefits/perks, (4) camaraderie, and (5) sense of fulfillment. Participants responded to a 5-point Likert item for each variable. For example, agreement with management was assessed by asking “In deciding whether or not to return to Mount Snow, how important is it to you to get along with your managers?” Participants answered the question with a rating of 1 (not important) to 5 (very important). Results Upon completion of data analysis, several significant findings were revealed. The one-way ANOVA conducted for age showed that the 51+ group reported significantly lower ratings for benefits than the 36-50 group, F(2, 82) = 4.33, p < .05. The one-way ANOVA conducted for age also showed that the 51+ group reported significantly higher ratings for sense of fulfillment than the 18-35 group, F(2, 82) = 6.43, p < .05. The one-way ANOVA conducted for experience showed that the 10+ years group rated a sense of fulfillment significantly higher than the 3-9 years group, F(2, 82) = 3.42, p < .05. The following tables represent the results from the three mentioned ANOVA procedures: 3.4 3.6 3.8 4 4.2 4.4 4.6 4.8 Benefits (m) 36-50 51+
    • Of the fifteen independent groups t-tests conducted, one revealed a significant finding. Full- time participants reported a significantly higher rating for a sense of fulfillment (M = 4.71, SD = .47) than did part-time participants (M = 4.35, SD = .84), t(83) = -1.66, p< .05. The following table represents the results from the mentioned t-test procedure: 3.6 3.8 4 4.2 4.4 4.6 4.8 5 Fulfillment (m) 18-35 51+ 3.8 3.9 4 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 Fulfillment 3-9 yrs 10+ yrs
    • Discussion The findings of the present study revealed four significant findings. The first is that participants in the 51+ age group reported significantly lower ratings for benefits than the 36-50 group. That is, benefits were less important to those in the 51+ group when making the decision to return to Mount Snow the following season than it was for those in the 36-50 group. This could be due to a demographic difference in these groups. Those in the 36-50 group may have greater family needs, such as dependent ski passes which are available to them by working for Mount Snow. Those in the 51+ group may not need those perks as much. The second significant finding is that participants in the 51+ group reported significantly higher ratings for sense of fulfillment than those in the 18-35 group. This means that a sense of fulfillment is more important to those in the 51+ group when deciding to return the following season than it is to those in the 18-35 group. Perhaps those in the 51+ group are more concerned with a sense of fulfillment because the other factors (agreement with management, pay, benefits/perks, camaraderie) are not necessary to their well-being at work. There are probably more people in the 51+ group that are working at Mount Snow as a second job or a retirement job, so concrete factors such as pay and benefits may not matter as much to them. In comparison participants in the 18-35 group may value pay and benefits because they rely on them more. They may also value relationships with managers and camaraderie for the reason that they need healthy work relationships to advance their career in the future. Results also showed a significant difference in sense of fulfillment between levels of experience. Participants in the 10+ years group rated a sense of fulfillment significantly higher than those in the 3-9 years group. Once again the possibility exists that those in the 3-9 years group consider more concrete factors such as pay and benefits when deciding to return to Mount Snow. It could also be that those in the 10+ years group may explain their long-standing commitment by valuing a sense of fulfillment. After all, they probably wouldn’t have been with Mount Snow for more than ten years if they didn’t find their jobs to be fulfilling. 4.1 4.2 4.3 4.4 4.5 4.6 4.7 4.8 Fulfillment Part-Time Full-Time
    • The fourth and final finding reported in this study is that participants in the full-time group rated a sense of fulfillment higher than those in the part-time group. Those in the part-time group are only required to work a couple weekends a month and a designated amount of holidays. Therefore their decision to return might be because of the benefits such as a season’s pass and discounts. In comparison those in the full-time group are striving to work forty hours a week. By making a living as instructors, perhaps they also have a greater drive to seek a sense of fulfillment from these longer work weeks. Conclusion There is a clearly consistent theme that emerges from the present study; concrete versus ambiguous factors of retention have different meanings to different groups of employees in the ski industry. From the results we can determine that seasonal employees come in all shapes and sizes. There are those who are committed to working full-time for their main source of income, those that are working leisurely for the experience or benefits, and everything in between. The greatest theme in the present study was a sense of fulfillment. Ski resorts can use this information to understand that a sense of fulfillment is clearly important to certain groups of employees. By identifying these employees, resorts can retain them by assuring that they receive work assignments that are fulfilling to them. For those employees not concerned with a sense of fulfillment, resorts need to assure that they receive the amount of pay, benefits, and working environment that will keep them satisfied and coming back each year. By identifying the specific needs of each employee, resorts can save through retaining year after year. Procedures After gaining approval from the Institutional Review Board, permission was requested from the ski school director at Mount Snow to access participants via email. Then all Mount Snow Ski School employees were contacted via email. The email requested participation in a survey that would take 5 – 10 minutes. The email included a link to an on-line survey website (www.surveymonkey.com). On that website participants were presented with an informed consent form before beginning the survey. Once informed consent had been acknowledged participants proceeded to the survey. First demographic measures were taken. After that participants were asked if they intend to return the following season. Lastly the participants were asked five questions relating to the importance of each of the five factors of retention. Upon completion of the survey, participants were given an opportunity to contact the researcher for any further questions. Statistical Analysis The demographic information in questions 2-5 served as the independent variables in the analysis of the dependent variables assessed with questions 6-10. A one-way ANOVA factor analysis was used to determine differences between the three age groups in relation to the five independent variables. A second one-way ANOVA factor analysis was used to determine difference between the three experience groups and the five independent variables. Both ANOVA tests were followed up with post hoc LSD tests. In addition, fifteen independent groups t-tests were conducted to analyze the data comparing the five independent variables with employment status, program type, and intention to return. SSPS Statistics 18.0 was used for the data analysis. The level of significance was set at .05.
    • Survey Sample 1.) Please list your age: ___ 2.) How many seasons have you worked for Mount Snow Ski School (including the 2010-2011 season)? ___ 3.) Please indicate your employment status at Mount Snow for the 2010-2011 season: a. Part-time ___ b. Full-time ___ 4.) Please indicate the type of program you worked in at Mount Snow for the 2010-2011 season: a. Full-day lesson program ___ b. Hourly lesson program ___ 5.) If the opportunity is available, do you plan to return to Mount Snow for the 2011-2012 season? a. Yes ___ b. No ___ 6.) In deciding whether or not to return to Mount Snow, how important is it to you to get along with your managers? (Circle the number corresponding with your answer) 1 2 3 4 5 Not Important Neutral Very Important 7.) In deciding whether or not to return to Mount Snow, how important is your rate of pay to you? (Circle the number corresponding with your answer) 1 2 3 4 5 Not Important Neutral Very Important 8.) In deciding whether or not to return to Mount Snow, how important are the benefits/perks that Mount Snow provides to you? (Circle the number corresponding with your answer) 1 2 3 4 5 Not Important Neutral Very Important 9.) In deciding whether or not to return to Mount Snow, how important are the relationships you have with your coworkers at Mount Snow to you? (Circle the number corresponding with your answer) 1 2 3 4 5 Not Important Neutral Very Important 10.) In deciding whether or not to return to Mount Snow, how important is it to you to feel a sense of fulfillment from your job at Mount Snow? (Circle the number corresponding with your answer) 1 2 3 4 5 Not Important Neutral Very Important
    • Review of Literature Introduction The topic of retention has been a major concern for human resources and industrial/organizational psychology for a long time. Though the solutions to increasing retention are not always clear, we know that turnover is a major antagonist of retention. Thus it is important that research in both areas be studied to gain better total understanding of each topic. In the resort and hospitality industries, retention is just as important. Being that many jobs in resorts and hotels are seasonal, the goal of retaining employees takes on different characteristics. Organizations have to question the idea that retaining on a seasonal basis means that retained employees will be coming and going each year. The goal then becomes a matter of keeping employees coming back season after season. Hinkin and Tracey (2000, 2006, 2008) have broken ground researching turnover in hotels for a long time. The two researchers have worked together to investigate the costs of turnover and have also developed tools to measure the cost of turnover and the factors associated with turnover. The 2008 study examined employee turnover in hotels in relation to job complexity, property sizes, room rates, average capacities, and chain affiliation. The results of the 2008 study provided insight into the nature of turnover and how it can be itemized. The hotel industry is very similar to the resort industry. The seasonal peaks in business, migrating nature of employees, and service related jobs make for a fair comparison between hotels and resorts. Thus research conducted in hotels can be very useful in researching resorts. When it comes to retention, several tactics can be used to keep employees from leaving an organization. Milman (2002) researched retention of hourly wage employees in small to medium sized attraction facilities in Florida. Milman (2002) investigated the reasons behind turnover in order to understand the factors related to retention. Surveys were used to assess job characteristics and to measure retention. Analysis of the survey responses yielded several trends associated with retention. What Milman (2002) found can serve as useful information to all resorts and organizations containing hourly wage employees. The seasonal nature of attraction facilities makes the results of this study even more meaningful to resorts of all kinds. Though in this case the focus of research was based on summer seasonal organizations, the implications can be applied to winter seasonal organizations as well. Ismert and Petrick (2004) researched retention in the ski industry in Colorado and New Mexico. Researchers determined six job attributes related to retention, then surveyed participants on which attributes were most important to them. The goal of the research was to determine differences between first year and returning employees. The results showed staggering differences between the two groups, which serves as great information to ski resorts everywhere. To understand retention in the ski industry, previous research must be gathered and interpreted. This step aids the research process by providing understanding of the issues most important to retention. For the purposes of this literature review, topics will be organized in the following sections; Employee Turnover, Retention, and Employment in the Ski Industry. Employee Turnover Hinkin and Tracey (2000, 2006, 2008) have researched turnover in multiple studies. Most of the research has been conducted in the hospitality industry, specifically hotels. The purpose of the 2008 study was to examine the influence of job and property-based factors associated with turnover.
    • Based on previous research, Hinkin and Tracey (2008) developed five categories for the cost of turnover: predeparture, recruitment, selection, orientation and training, and lost productivity (Hinkin& Tracey, 2000, 2006). Predeparture begins once an employee has given notice of their resignation. Predeparture costs include exit interviews, severance packages, and any other processing that goes along with resigning an employee. Recruitment involves all the processes of pooling applicants for the position. Selection is the process of filtering through applicants in order to make a hiring decision. Orientation and training costs include the processes of bringing an individual into an organization. Whether the individual needs extensive training or minor introduction to company procedures depends on the position and the organization. Lost productivity is the largest cost of the five categories (Hinkin& Tracey, 2006). Lost productivity stems from two sources. The first is that employees who are intending to leave the organization are less productive. The second is that new employees face a period of learning in which productivity is low to start. The purpose of the study was to compare the cost of each of the five categories, as well as total cost of turnover, across different hotel settings (Hinkin& Tracey, 2008). The first comparison was made between jobs with different complexities. Jobs with more cognitive demand require better candidates, and therefore researchers hypothesized that highly complex jobs would have higher turnover costs. The second comparison was made between chain-affiliated and independent hotel properties (Hinkin& Tracey, 2008). Given the structure and flexibility provided by chain hotels, researchers hypothesized that independent hotels would have higher turnover costs. The next comparison was made between hotels with high room rates and low room rates (Hinkin& Tracey, 2008). Hotels with higher room rates will have higher standards of quality and this will increase the job complexity. For that reason researchers hypothesized that turnover costs would be higher for hotels with higher room rates. The fourth comparison was made between hotels with high occupancy and low occupancy (Hinkin& Tracey, 2008). Hotels with higher occupancy will have higher levels of stress, which researchers hypothesized would increase the cost of turnover. The fifth and final comparison was made between large and small properties (Hinkin& Tracey, 2008). Similar to occupancy, larger hotels demand more from employees, which will lead to higher stress. Thus, researchers hypothesized larger hotels would have higher turnover costs. For data collection researchers developed a web-based turnover tool (Tracey &Hinkin, 2005). This tool is designed to assess turnover in each of the five categories developed by the researchers. Human resources managers of 33 hotel properties responded in this study (Hinkin& Tracey, 2008). The task for participants was to voluntarily provide data for at least one employed position by using the web-based tool. Of the 33 respondents, most jobs were of low complexity (n=28) (Hinkin& Tracey, 2008). Almost half (n=14) of the properties were independent. More than half (n=19) of the properties had room rates at or below the midmarket range. The average occupancy was 70 percent, with a range of 45 to 89 percent. Lastly, the average number of rooms was 180, ranging from 20 to 720 rooms. In order to accurately analyze the results, the sample was split in different ways for different hypotheses. Responses were separated into chain-affiliated and independent groups to assess different types of hotel properties (Hinkin& Tracey, 2008). Average daily rate (ADR) was used to split the sample according to high room rates and low room rates. For job complexity, number of rooms, and occupancy, the sample was split according to the median level of response for such factors. For
    • all factors the average dollar cost for each cost category and the average total cost of turnover was determined. To compare level of job complexity, each job was assessed by using the U.S. Department of Labor’s Occupational Information Network (O*Net) (Hinkin& Tracey, 2008). O*Net’s specific vocational preparation (SVP) ratings measure how long it takes for individuals to learn a new job. The higher the SVP, the higher the job complexity. Results indicated that total cost of turnover was significantly higher for complex jobs, which supports researcher hypotheses. In addition to total cost, complex jobs reported significantly higher costs for predeparture, recruiting, and lost productivity. In regards to chain-affiliation, the only significant difference existed in predeparture costs (Hinkin& Tracey, 2008), with independent hotels having higher predeparture costs. Though this was the only significant difference, it shows some support for researcher hypotheses. According to room rates, hotels with higher ADR had significantly higher turnover costs associated with selection, lost productivity, and total cost (Hinkin& Tracey, 2008). This data supports researcher hypotheses. Results revealed that hotels of different occupancy rates had slight but non-significant differences (Hinkin and Tracey, 2008). This finding did not support researcher hypotheses. The final hypothesis was supported by the data (Hinkin& Tracey, 2008). Larger hotels had significantly higher turnover expenses in regards to total cost, selection, and lost productivity. This supports researcher hypotheses. Researchers interpreted this finding as a suggestion that larger properties require more from their employees, increasing job complexity. The results of this study (Hinkin& Tracey, 2008) have serious implications for turnover in the hospitality industry. The biggest issue has to be job complexity. Organizations must take more consideration in reference to complex jobs if turnover costs are to be lowered. The factors of room rates, occupancy, and size show support for job complexity as well. Higher levels for such factors indicate higher responsibility for employees, which increases job complexity. Predeparture costs were a significant factor in relation to chain-affiliation (Hinkin& Tracey, 2008). A possible explanation for this finding is that chain hotels have more effective processes in place for the predeparture process than do independent hotels. Overall this study serves as a good example for organizations in the hospitality industry. The differences reported shine light on the roots of turnover and the costs associated with turnover. Thus organizations can benefit from investing in the areas of turnover costs. Retention Retention is a subject that warrants a great deal of attention. Understanding retention is the key to reducing turnover costs. Retention has been the focus of numerous articles and studies, and future research will continue to go further into the subject. In 2002, Milman studied retention in the attraction industry. Specifically, Milman (2002) investigated retention of hourly wage employees at small to medium-sized attraction facilities in Orlando, Florida. The focus of the study was to determine the causes of turnover of hourly wage employees, to investigate the issues related to turnover in this industry, and to explore methods of retention. For the purposes of this study, an hourly employee was defined as ‘‘an employee who works in an attraction facility on an hourly basis for a period of at least six months’’ (p. 43). In addition, employee turnover was defined as ‘’the number of persons hired within six months to replace those leaving or dropped from the workforce’’ (p. 43). Lastly, small to medium sized facilities were operationally defined as facilities with 500 or less employees.
    • A self-administered questionnaire was designed to survey respondents on job responsibilities, job search process, previous employment experience, and evaluation of current employment experience (Milman, 2002). To measure retention, respondents rated current job satisfaction, the likelihood of referring someone else to the current organization, and the likelihood of remaining with the current employer. The study also surveyed participants on possible reasons that could incline them to leave for another job. In total, 13 facilities from the Orlando, Florida area were used to access the data (Milman, 2002). Of the 446 questionnaires administered, 172 participants responded. The median age for participants was 36-40, and the mean experience was 3.5 years. Most participants had a high school degree or higher (83.5 percent). The employees surveyed worked an average of 30.4 hours per week in a variety of positions (Milman, 2002). The employees worked in guest relations (22.9 percent), merchandise (12.9 percent), food services (11.2 percent), and maintenance (8.8 percent). When asked what attracted them to their current job, participant responses followed distinct trends (Milman, 2002). The most common responses were employee working environment (46.7 percent), flexible schedules (45.1 percent), and interaction with people of different backgrounds (44.0 percent). Interestingly, employee benefits (15.2 percent) and free admissions/discounts (14.7 percent) were mentioned much less. To evaluate the current employment experience of participants, 22 employment characteristics were presented in the questionnaire to be rated by importance (Milman, 2002). Respondents rated each item on a five-point scale ranging from 1 (unimportant) to 5 (very important). Results showed that employees valued nice people to work with (mean = 4.58), humane approach to employees (mean = 4.56), introductory training (mean = 4.55), clear information on job tasks (mean = 4.52), and fun and challenging job (mean = 4.47). Lower on the list was health benefits for the employee (mean = 3.83), retirement plan (mean = 3.62), and health benefits for the employee’s family (mean = 3.51). Again the results show that employees valued intrinsic factors more than the extrinsic. In reference to retention, this study surveyed job satisfaction, likelihood of referring a friend or family member to seek employment at the same organization, and likelihood that the participant would remain with the organization for the next 12 months (Milman, 2002). A five-point scale was used also to assess these variables. Results showed that ‘’71.5 percent of respondents were either ‘satisfied’ or ‘very satisfied’ with their current job’’ (p. 46). The majority of respondents (56.2 percent) rated themselves as ‘likely’ or ‘very likely’ to refer someone else to work with the current organization. Likewise, 63.4 percent of respondents were ‘likely’ to ‘very likely’ to remain with the organization for the next 12 months. Pearson correlation revealed that all three retention predictors were highly correlated. Pearson correlations were also used in comparing present experiences with the organizations (Milman, 2002). Not surprisingly, job satisfaction, likelihood of referring another to work with the current organization, and likelihood of remaining with the organization were all positively correlated with better current experiences working with the organization. The multiple correlates of job satisfaction suggest that job satisfaction has a high influence on retention. Interestingly, when reporting reasons for inclination to leave for another job, respondents rated extrinsic reasons the highest (Milman, 2002). Traits were presented to participants to be rated on a five-point scale from 1 (no value) to 5 (very high value). The two traits rated the highest were better pay (mean = 4.42) and better health benefits (mean = 3.98). This finding is intriguing because
    • on the 22-item evaluation of current experience neither better pay or better health benefits were ranked high. To identify factors indicative of retention, three multiple regression analyses were conducted (Milman, 2002). The dependent variables were the responses to the five-point items of level of satisfaction with the current job, likelihood to refer a friend or family member to work for the same organization, and likelihood to remain with the current organization for the next 12 months. Each dependent variable was paired against all other variables in the study to determine common factors associated with retention. Results of the regression analyses showed several common themes. For job satisfaction, respondents were more likely to be satisfied if they had a sense of fulfillment, clear responsibilities, did not have another job, had consistent working hours, and would not move to another company because of management style (Milman, 2002). Among other factors, participants had a higher likelihood of referring friends and family members to work for the organization if they had a sense of fulfillment, consistent working hours, and better experiences with regards to performance reviews. Lastly, participants were more likely to stay with the organization for the preceding 12 months if they had a sense of fulfillment, would not move to another company because of management style, clear responsibilities, consistent working hours, and increase benefits, among other factors. The indicators as revealed by this study serve as valuable information to any organization. With the data presented by this study (Milman, 2002) a wealth of knowledge and understanding develops in regards to retention. The light shed into the 22 job characteristics, job satisfaction, and retention can be used in future research for time to come. Such information is crucial to businesses in the attraction and seasonal industries. Employment in the Ski Industry Ismert and Petrick (2004) researched ski areas to better understand seasonal employment and what job attributes influence retention. Once those attributes were determined, Ismert and Petrick (2004) examined differences in retention between first year and returning employees, and what levels of quality are needed for those six attributes. The study was completed by surveying employees from four ski resorts in Colorado and New Mexico. To begin the study, Ismert and Petrick (2004) designed a questionnaire to be administered via interview to a pilot sample of 20 seasonal employees at Arapahoe Basin ski resort in Colorado. The result of this pilot study revealed six common job attributes related to retention; management attitude, amount of money paid, job benefits, camaraderie, job challenge, and job satisfaction. The actual sample for the study was drawn from four ski resorts; Purgatory at Durango Mountain Resort and Arapahoe Basin in Colorado, as well as Taos Ski Valley and Red River Ski and Snowboard Area in New Mexico (Ismert&Petrick, 2004). From these areas 364 employees were asked to participate. Of those asked to participate, 324 agreed to complete a six-page questionnaire. The sample population was made up of 49.7 percent first-year employees (n = 161) and 50.3 percent returning employees (n = 163). The questionnaire included five sections; job dimensions (experience, pay, hours, etc.), importance of the six job attributes, standard of quality for the attributes, satisfaction with the attributes, and a demographic section (Ismert&Petrick, 2004). The fourth section of the questionnaire asked respondents to rate level of satisfaction with each job attribute on a 10-point scale ranging from very satisfied to very dissatisfied (Ismert&Petrick, 2004). The fourth section also asked respondents to rate intention to return on a 7-point scale
    • ranging from no way to certainly. A regression analysis was used to determine which indicators best predicted intention to return. The regression analysis revealed that satisfaction with camaraderie was a significant predictor of intention to return among first-year employees (p < .05) (Ismert&Petrick, 2004). For returning employees, satisfaction with management attitude, money, and benefits were significant predictors of intention to return (p < .05). Regression was also used to determine which attributes were the best predictors of overall job satisfaction among participants (Ismert&Petrick, 2004). For first-year employees, management attitude, camaraderie, and job challenge were significant predictors of job satisfaction (p < .05). Money, camaraderie, and job challenge were significant predictors of satisfaction for returning employees (p < .05). To determine the standards of quality for each job attribute, the third section included a series of questions relating to changes in each job attribute and how those changes would affect intention to return (Ismert&Petrick, 2004). For example, participants were asked how they would feel about returning if (1) wages stayed the same, (2) wages increase $0.25, (3) wages increase $0.50, (4) wages increase $1.00, (5) wages increase $2.00, and (6) wages increase $3.00. Participants responded with a 5-point scale ranging from very favorable to very unfavorable. The neutral mark was used as the lowest point of quality for each attribute. The data from the third section were organized by norm curves which indicated the point at which most employees would return based on the standards of that attribute (Ismert&Petrick, 2004). Returning to the above mentioned example, results showed that the standard of quality for wages was wages stay the same. Management attitude considered to be fair was found to be the standard of quality for management attitude. For benefits, the standard of quality was found to be benefits stay the same. The standard for camaraderie was found to be camaraderie with half. Lastly, the standard for job challenge was 25% of time, meaning respondents were likely to return if the job was challenging 25% of the time. The results of the current study have serious implications for the service industry. The results showed that there are six clear indicators of intention to return (Ismert&Petrick, 2004). It is also clear that a difference exists between first-year and returning employees. First-year employees value camaraderie when considering their decision to return whereas returning employees value wages, management attitude, and benefits. In regards to satisfaction, first-year employees value satisfaction with management attitude, camaraderie, and job challenge. Likewise, returning employees value satisfaction with camaraderie and job challenge, as well as satisfaction with money. These differences need to be considered when organizations are designing retention programs. Also, the standards of quality can be utilized by organizations when assessing the six job attributes. With this information, resorts can see retention rates maintain acceptable levels, which will save money and time. Future research can consider ski resorts in other areas of North America and what other attributes may serve as predictors of retention (Ismert&Petrick, 2004). Lastly, insight could be gained by researching these attributes from the perspectives of the employer and the guests. Conclusion The studies discussed in this literature review provide good information related to retention. Whether in hotels, attraction facilities, or ski resorts, the characteristics of seasonal employment create a unique working environment. Because of this, research in the resort and hospitality
    • industries must investigate not only the factors related to retention but also the type of jobs employees have and the demographics associated with the employees. Research by Hinkin and Tracey (2000, 2006, 2008) has shown that the costs of turnover are different for jobs and organizations of different characteristics. Job complexity plays a big role in the cost of turnover as the training and lost productivity for more complex jobs boosts costs. It seemed that the characteristics related to the different sizes and operating abilities of hotels shared a link with job complexity as well. Therefore further research should take job complexity very seriously. The nature of hourly wage employees is important to discuss as well because seasonal jobs often offer hourly wages to employees. Milman’s (2002) study found that self fulfillment, relationships with management, and clear understanding of responsibilities were very important to hourly wage employees. Being that ski resorts operate with many hourly wage employees, such factors can be important in researching retention in ski resorts. Other factors related to retention in ski resorts can be linked to Ismert and Petrick’s (2004) study. The six job attributes that were studied provided a great foundation for research on retention in ski resorts. The differences between first year and returning employees shows that actions need to be taken by ski resorts to cater to both types of employees if retention is to be improved or sustained. Still more support can be found for the six attributes by examining resorts in other areas of the country. Also, support can be gained by investigating differences between ski resort employees based on demographics other than tenure. In research the goal is always to move forward and to progress the field of study. From the topics discussed in this literature review, the window for further research has been opened. The six job attributes associated with retention (Ismert&Petrick, 2008), the characteristics of retention for hourly wage employees (Milman, 2002), and the issue of job complexity (Hinkin and Tracey, 2004) set the stage for studies to further investigate the crucial topic of retention. With this in mind, retention in ski resorts can be much better understood with future research. References Hinkin, T. R., & Tracey, J. B.2006. Development and use of a web-based tool to measure the costs of employee turnover: Preliminary findings. Ithaca, NY: Cornell University School of Hotel Administration Center for Hospitality Research. Hinkin, T. R., & Tracey, J. B.2000. The cost of turnover: Putting a price on the learning curve. Cornell Hotel and Restaurant Administration Quarterly 41(3): 14-21. Ismert, M., &Petrick, J. F. (2004). Indicators and Standards of Quality Related to Seasonal Employment in the Ski Industry. Journal of Travel Research, 43(1), 46-56. doi:10.1177/0047287504265512 Milman, A. (2002). Hourly employee retention in the attraction industry: Research from small and medium--sized facilities in Orlando, Florida. Journal of Leisure Property, 2(1), 40. Retrieved from EBSCOhost. Tracey, J., &Hinkin, T. R. (2008). Contextual factors and cost profiles associated with employee turnover. Cornell Hospitality Quarterly, 49(1), 12-27. doi:10.1177/0010880407310191