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.

1. 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)

2. 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+

3. 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

4. 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

5. 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.

6. 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

7. 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.

8. 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

9. 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.

10. 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

11. 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

12. 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

13. 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