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									                  Is There a Correlation between Employee Turnover and Restaurant Revenue

                                     in Gaming-Centric Casino Restaurants?



                                                                                                 Karl D. Brandmeir
                                                                       International University of Applied Sciences
                                                                                             Bad Honnef, Germany
                                                                                    k.brandmeir@fh-bad-honnef.de


                                                     Abstract

          This study investigates the relationship between employee turnover and restaurant revenue in gaming-
centric casino restaurants. In gaming-centric casinos, the restaurant operations, as well as all other departments
in the resort, have the singular duty to support the casino operations. In amenity-centric casino resorts, each
restaurant, as well as all other departments, are revenue and profit centers and tend to operate as you would
expect any free-standing operation. The data for this study were from buffets, steakhouses, and coffee shops in
casinos in three geographic locations.
          The results of this study go counter to those of free-standing restaurants. In the gaming-centric casino
environment, employee satisfaction (as measured by employee turnover percentages) does not have a strong
influence on restaurant revenues.

Key words: Employee turnover, Casinos, Food and beverage revenue.

                                                        Introduction

          Turnover has been studied by many researchers attempting to understand the causes of employee
turnover (Pizam & Thornburg, 2000; Deery, et al., 1999; Gilbert, 1998; Laker & Shimko, 1991; Hawk, 1976).
An earlier study by Hinkin and Tracey (2000,) found that the cost of employee turnover rose nearly 400% from
1983 to 2000. Woods and Macaulay (1989) examined six restaurant companies and six hotel companies. Their
findings indicate that the reasons for employee turnover were nearly the same as an earlier study by Wasmuth
and Davis (1983). Both studies found that employee turnover was an accepted fact within the industry. Deery
and Shaw (1999) studied the relationship of organizational culture and employee turnover and suggested that
there is a turnover culture in the hotel industry. The implication from their work suggests that hotel management
must manage the work culture by providing clear roles, job descriptions, supervisory support, the necessary
equipment and less overtime. Selecting the personalities that fit into the hotel culture is of primary concern for a
starting point.
          The conceptual framework for this study is the service profit chain developed and studied by Heskett,
Sasser, and Schlesinger (1997). Leonard Schlesinger found a direct link between employee and customer
satisfaction. This was the result of his Partner/Manager Program during his time as the COO of Au Bon Pain
and became part of the book The Service Profit Chain by Heskett, et al., 1997.




  Internal        Employee                                                                           Revenue
                                  Employee         External        Customer         Customer         Growth &
  Service        Satisfaction
                                   Loyalty         Service        Satisfaction       Loyalty        Profitability
  Quality
                                                   Quality


Figure 1: The Service Profit Chain

Source: Loveman, G. (1998). Employee satisfaction, customer loyalty, and financial performance: An
empirical exanimation of the service profit chain in retail banking. Journal of Service Research 1(1), 18-31;
Heskett, J., Sasser Jr., W.E., and Schlesinger, L. (1997). The service profit chain. New York: The Free Press.
          Wiley (1996) found that in a business services setting not only were employee and customer
satisfaction positively related but also business performance. His study of a retail chain did find that employee
satisfaction was not related to business performance. In fact, business performance was actually negatively
related to customer satisfaction. This would then question the possibility of linkage between employee
satisfaction and restaurant performance. This linkage has been shown in some industries such as banks and
restaurants However, the possible linkage of employee turnover and restaurant revenue in gaming-centric
casinos has not been studied. In contrast, employee turnover in such an environment has been shown to
influence customer satisfaction (Brandmeir, 2002).

                                                     Literature Review

Employee Satisfaction and Financial Results

          Employee satisfaction and customer satisfaction has been well documented in the literature. However,
the linking of customer satisfaction and financial performance has mixed results (Anderson, Fornell, and
Lehman, 1994).They also found that customer satisfaction in one period carried over into future periods.
          Xu and van der Heijden (2005) found that good service quality to consumers can be achieved only
through properly managing the employees. These authors examined the financial impact of service within a
Chinese securities firm in the context of the service profit chain model. Ton and Huckman (2008) found that
employee turnover is associated with decreased profit margins and customer satisfaction.
          Maddern, et al., (2007) also looked at the role of staff satisfaction and service quality in the financial
services industry in the United Kingdom. The results confirmed that staff satisfaction is a key determinant of
service quality. This result agrees with other service profit chain literature.
          The accounting profession is also looking at customer satisfaction, or other non-financial measures, as
a way of predicting future financial performance. Ittner and Larcker (1998) found support for the use of non-
financial measurements such as customer satisfaction as a predictor of future financial performance measures
such as revenue and revenue growth.
          Wildes and Parks (2005) found that food servers were more likely to recommend their jobs to others if
there was good internal service quality in the work place. Not only would the food servers recommend their jobs
to others but they would stay longer, thereby reducing turnover.
          Murphy and Williams (2004) looked at compensation as an impact on restaurant mangers’ intention to
leave. They studied a plan by Outback Steakhouses that was thought to reduce management turnover. The
results showed two different findings. First the managers were influenced by non-traditional plan attributes such
as deferred compensation, stock options and ownership interests as opposed to salary, and retirement plans.

The Service Profit Chain

          Hurley and Estelami (2007) looked at the service profit chain, employee satisfaction, and customer
satisfaction linkage. While the study used data from a chain of convenience stores, it is a related to the
hospitality service business. The results demonstrate that employee turnover was effective in predicting
employee satisfaction and customer satisfaction. A similar result to Brandmeir (2002) that found employee
turnover rates influenced customer service quality in gaming-centric casino restaurants.
          Banker, et al., (2000; 2005) found that non-financial measures indicated future financial results. Both
studies involved full-service hotel companies. Smith and Wright (2004) had similar findings when looking at
customer loyalty and financial outcomes. Their findings indicate that customer loyalty explained revenue
growth, profitability, and competitive advantage.
          Gupta, et al., (2007) used data from a national restaurant chain to study guest satisfaction and restaurant
performance. The results demonstrate that restaurants that focused on food quality, appropriate cost, and
attentive service showed greater guest intent to return. This intent to return translated into increased sales.
          The literature suggests that employee turnover is increasingly a focus by management. Employee
turnover, employee satisfaction, and customer satisfaction are useful for indications of future financial
performance. Some firms are including such measures as a means of accessing management performance for
bonuses. The literature has also shown that non-hospitality operations and hospitality operations have similar
results from employee turnover, employee satisfaction, customer satisfaction, and financial performance. While
restaurants and hotels have benefited from these studies, there have not been any studies published about the
casino entertainment industry on the subject of the relationship between employee turnover and revenue
performance in restaurants.
                                                        Methodology
          This study uses secondary data from three gaming-centric casino resorts for a ten month period. The
turnover data was collected by the human resources department and is recorded consistently across the
restaurants and regions on a monthly basis. The historical data came directly from the corporation personnel
records. For each restaurant, the employee turnover data was reported for front-of-the-house and back-of-the-
house. The employee turnover is measured and reported as a ratio of the number of employees that left to the
total number of employees for each month for the three restaurants (buffet, coffee shop, and steakhouse) in each
region.
          The revenue for each restaurant for the ten month study period was the data used by the corporation
office to report revenues and expenses to the appropriate state and federal taxing authorities. These figures were
the subject of multiple audits by public and private entities.
          Multiple regression analysis was chosen as the method of analysis since there is a single metric
dependant variable of restaurant revenue and more than two independent variables (Hair et al., 1998).
Restaurant location, restaurant type, and restaurant region were used as control variables, since there was a
possibility of revenue variation due to these factors. Monthly restaurant revenue was regressed by the two
employee turnover variables. Before conducting a multiple regression analysis, the data were examined for the
assumptions of regression such as normality, linearity, and multi-collinearity.

                                                          Results

Table 1
Descriptive Statistics for Variables
_____________________________________________________
Variable                    Mean     Std. Deviation  N
Restaurant revenue1         396.77         206.58   180
Month                        15.50           8.68   180
Region                        3.00           1.00   180
Restaurant type               2.00            .81   180
Front of house                2.86           3.08   180
Back of house                 3.03           4.75   180
1: In thousands of dollars

          Histogram and normal p-p plots were used to assess normality and linearity. No violations of normality
and linearity were detected. A two part process was used to assess multiple correlations between the
independent variables and identify any possible multi-collinearity.
          First, the collinearity of combinations of variables in the data was assessed using the condition index.
The most common threshold value used for the condition index is 30 (Hair et al., 1998). Secondly, the
regression coefficient variance-decomposition matrix was used to determine the proportion of variance for each
regression coefficient. Those variables identified as exceeding the threshold in the first step are then examined
to identify variables with variance proportions of .90 or above (Hair et al.; Pedhazur, 1997). If two or more
coefficients are above the .90 threshold for variance proportion for a variable identified in step 1, then a
collinearity problem is indicated. Table 2 shows the collinearity diagnostics discussed above.
Table 2
Collinearity Diagnostics (a)

                                           Variance Proportions
Model Dimension       Eigen Condition                            restaurant front of back of
                     -value      Index` Constant month region type           house house
1          1          3.633      1.000    .00     .02        .01     .01
           2           .208      4.183    .01     .84        .03     .12
           3           .122      5.455    .01     .03        .38     .59
           4           .037      9.929    .98     .12        .58     .28
2          1          4.495      1.000    .00     .01        .00     .01      .01     .01
           2           .691      2.550    .00     .02        .00     .00      .02     .87
           3           .474      3.078    .00     .04        .02     .00      .81     .00
           4           .195      4.798    .01     .79        .08     .08      .02     .05
           5           .109      6.418    .01     .01        .29     .73      .12     .03
           6           .035     11.272    .98     .13        .60     .18      .01     .04
a: Dependent Variable: restaurant revenue

         Table 3 shows the model summary. Model one is the summary of the control variables. Model one
shows that the control variables (month, location, and restaurant type) explained 42.9% of the variance of the
monthly restaurant revenue for the ten months in this study, R2 = .429, p<.000. Model two results show that
restaurant turnover only explained an additional 4.3% of the variability in restaurant revenue. R2 change=.472,
p<.001.

Table 3
Model Summary(c) for the Dependant Variable: Restaurant Revenue

                                       Std. Error
                               Adjusted of the
Model      R       R Square    R Square Estimate                         Change Statistics
                                                       R Square                                     Sig. F
                                                       Change      F Change        df1        df2   Change
1        .655(a)     .429       .420       157.362      .429        44.161         3         176     .000
2        .687(b)     .472       .457       152.201      .043         7.070          2        174     .001

a: Predictors: (Constant), restaurant type, region, month
b: Predictors: (Constant), restaurant type, region, month, back of house, front of house
c: Dependent Variable: restaurant revenue

                                           Conclusions and Recommendations

         The results of this study run a bit counter to what one would expect from reviewing the literature
concerning employee turnover and financial performance. A small amount of the monthly restaurant revenue
variance (4.3%) is explained. It is important to re-emphasize that this study used data from gaming-centric
casino resorts. Gaming-centric casino resorts are focused on maximizing the casino revenues, and all other
departments, including food and beverage, exist to support the casino. Amenity-centric casino resorts take a
very different approach. These operations are focused on maximizing the individual revenue streams from all of
the departments such as hotel, restaurants, convention space, spa, and the casino. For Clark County Nevada (Las
Vegas), the non-gaming revenues for the year 2007 were 52.1 % of the total (Nevada Gaming Control Board,
2007).
         An explanation of gaming-centric restaurant design and philosophy may be helpful. Keep in mind that
all departments operate in support of the casino. Therefore, operational efficiency is paramount Ideally; a
restaurant would operate at full capacity during its hours of operation. Such a situation would allow
management to maximize labor efficiency which is the largest expense for a restaurant. To operate at full
capacity, the management must have potential customers ready to be seated as soon as the current customer
leaves. This is accomplished by designing the restaurant capacity to be too small for the casino capacity. The
result is a waiting line forms since there are more potential customers than seats available. Waiting line facilities
are designed and built at the entrance to the restaurants.
          The result has implications for the gaming-centric casino environment. While turnover costs were not
part of this study, several researchers cited in this paper did look into this aspect of turnover. These costs would
also apply to gaming-centric casino operations. Employee turnover and perceived service quality are linked and
can influence gaming revenue (Brandmeir, 2002). This linkage could have a large impact on total revenues not
just restaurant revenues. Operationally, revenues will be impacted by pricing in place of increasing cover counts
(number of customers). While seating efficiency may increase covers counts a little, this already is part of the
operational philosophy. However, as the casino landscape changes to more amenity driven revenues, as noted
above, restaurants will certainly need to be redesigned and expanded if they need to operate in that style of
environment. It should also be noted that the three gaming-centric casinos in this study were not in Las Vegas.
It should also be noted that most casinos in the United States are gaming-centric. However, the majority of the
new casinos being built world-wide are amenity-centric. There are very few public studies available about food
and beverage operations within the gaming-centric casino environment. This study adds to the body of
knowledge for such an operational philosophy.
          No implications can be made from this work about amenity-centric operations. The operational
philosophies are very different. The results are only applicable to the resorts in this study. While other gaming-
centric casinos may be designed in a similar fashion and operate with the same operational philosophy,
additional studies would need to be done to see if the result is similar. It is also possible that physical location of
the casino operation may have an impact on restaurant revenues.
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