Restaurant Services on Resorts - Report Example

Part One: Identification of dependent variable and focal points

The table below represents data on independent variables affecting the restaurants located in different types of resorts.

Types of resort

No. of resorts interviewed

Independent variables

competition

New government policies

Historical resorts

14

3

6

5

Island resorts

21

12

6

3

Tourism resort

25

4

14

7

Grand resorts

32

12

15

5

luxury resorts

24

14

8

2

Spa resorts

35

16

18

1

tropical resorts

33

16

15

2

Golf resorts

16

5

10

1

Totals= 200

The data above represent three major risks that affect the performance of restaurants located in different types of resorts. These risks include; competition, new government policies, and change in customer demand. When these risks are not managed and controlled, they may lead to business failure. The data was collected from two hundred restaurants located in eight types of resorts using both questionnaires and interviews. The two methods of data collection were preferred since the hotels have busy schedules. Therefore, the interview was used when the respondent was available, and questionnaires were used if the respondent was unavailable. Seventy restaurants responded through interviews, and one hundred and thirty restaurants responded through questionnaires. The dependent variable is the restaurant's performance, and independent variables are; competition, new government policies, and change in customer demand.

Restaurants are business establishments whose aims are to provide food and drinks to customers. Restaurant services are provided directly to customers; hence the services need to be unique and satisfactory to attract more customers. The target businesses are restaurants located in different types of resorts that serve both local and international customers, depending on their location. The categories of the resorts that responded were; Golf resort, Historical resorts, Island resort, Tourism resort, Grand resorts, luxury resorts, Spa resorts, and tropical resort.

The risk of competition occurs when there is a high-class restaurant near or around the location of the business. As a result, the businesses have to upgrade the services provided to compete with other restaurant businesses, such as a variety of foods on the menu. This risk affects the business more if the business is small and new. The risk of change in customer demand affects the business if the customers demand shift away from what the business provides. It leads to a decrease in the number of customers, and more losses are incurred. When the losses persist, the business may be closed due to many debts from continuously incurred losses. Every financial year the government makes rules and regulations that guide how restaurants should provide services. When the rules and regulations are favorable to the business, such as reducing business license costs and reducing interest loans to encourage entrepreneurs to borrow for restaurant expansion. The businesses incur losses and debts if the regulations are not favorable. When the risks persist for an extended period, many businesses are closed to prevent huge debts for losses incurred by the businesses.

Independent Variables

Summary of dependent variables

Categorical or qualitative

Association with the dependent variable

Competition

Qualitative variables

When competition is high the business survival is meager and vice versa

Change in customer demand

Qualitative variables

When customer demand changes away from what business provides, the survival chances are meager and vice versa

New government policies

Qualitative variables

Affirmative government policies increase business survival, and harmful government policies reduce business survival.

Part Two: Mapping Decision to Outcome

Types of resort

No. of resorts interviewed

Independent variables

competition

Historical resorts

14

3

Island resorts

21

12

Tourism resort

25

4

Grand resorts

32

12

luxury resorts

24

14

Spa resorts

35

16

tropical resorts

33

16

Golf resorts

16

5

Scatter plot of competition against the number of resorts interviewed.

Types of resort

No. of resorts interviewed

Independent variables

New government policies

Historical resorts

14

6

Island resorts

21

6

Tourism resort

25

14

Grand resorts

32

15

luxury resorts

24

8

Spa resorts

35

18

tropical resorts

33

15

Golf resorts

16

10

A Scatter plot of new government policies against the number of resorts interviewed.

Types of resort

No. of resorts interviewed

Independent variables

Change in customer demand

Historical resorts

14

5

Island resorts

21

3

Tourism resort

25

7

Grand resorts

32

5

luxury resorts

24

2

Spa resorts

35

1

tropical resorts

33

2

Golf resorts

16

1

Scatter plot of change in customers' demand against the number of resorts interviewed.

The regression equation for independent variables

Independent variables

Regression equation

Competition

Y=0.537x-3.1759

New government policies

Y=0.5023x-1.0579

Change in customer demand

Y=-0.0394x+4.2338

Interpretation of scatter plot and regression equation

The regression equation for competition shows a positive correlation between restaurant businesses and competition in the market. The positive coefficient of 0.537 means that an increase in competition affects the restaurant business directly. If restaurants are offering the same services nearby, they tend to compete for customers by providing good services. As a result, the restaurant has to improve the services, for example introducing new dishes on the menu, offering free dessert or appetizer once per month, and selling food and drinks at affordable prices. Therefore, when the customers notice the unique and variety of food available at the restaurant, they will be frequent customers. The restaurant will withstand stiff competition and make more profit.

The regression equation of new government policies gives a positive coefficient of 0.5023. The positive regression coefficient shows that there is a constructive association between the predictor variable and constant variables. It means that if the new government policies are promising to the restaurant management and operations, good profits are made. As a result, restaurants can expand to provide a variety of services. Therefore, entrepreneurs are encouraged to start and operate new restaurants in the country.

Change in customer demand gives a negative coefficient of -0.0394. The negative number shows that there is no association between the constant variable and the predictor variables. The negative correlation means that when the customers' demand changes, the restaurant is affected negatively. When the customers’ demands change, there is no consumption in the restaurants, and the profit level decreases. A decrease in profits level affects restaurant operations such as paying bills. If the changes in customer demand persist, they might result in business closure until the demand patterns change.

Multiple regressions

Part Three: Revised Regression Equation

Residual plot for completion

Residual plot for new government policies

Residual plot for change in customer demand

Nonlinear relationship

To determine if there is a nonlinear relationship among the independent variables with the dependent variable, we need to find the correlation of the independent variables to test if there is an association with the dependent variable.

Log transformation for competition

Log transformation for new government policies

Log transformation for change in customer demand

The table below represents nonlinearities from the log transformations

Independent variables

Log transformation

Presence of nonlinearities

Competition

12.555In(x)-29.567

Nonlinear relationship present

New government policies

Y=11.221In(x)-24.088

Nonlinear relationship present

Change in customer demand

Y=-0.734In(x)+5.5793

Nonlinearities not present

The independent variables of competition and new government policies have a nonlinear relationship with the dependent variable. The association displays that the predictor and control variables relate hand in hand with each other. If competition and government policies increase, the survival chances for the restaurant business are also increased. In the case of a change in customers' demand, there is no positive association; hence nonlinearities are absent.

Correlation table

Dependent variable

competition

Government policies

Change in customer demand

Dependent variable

1

competition

0.68154

1

Government policies

0.810063

0.213559

1

Change in customer demand

0.053266

-0.48447

0.119999

1

Multicollinearity is not present since there are no repetitive variables on the correlation table above. There are no large numbers above 0.5 that could be added to give a correlation of more than one when using the correlation.

Part Four: Model Validation

The project aims to determine how competition, government policies, and change in customer demand affect the restaurant performance in different types of resorts. Performance of the restaurant business represents the dependent variable while the independent variables are competition, new government policies, and change in customer demand. Linear regression shows the line of best fit where the coefficient of regression is calculated to determine if there is positive and negative regression. Competition and government policies have positive regression proving that the two variables are important in determining whether a new business can survive in the market. On the other hand, change in customers' demand has a negative influence on the performance of restaurants since it affects the profit levels of the business leading to business failure. To reduce the negative regression from the change in customer demand, the restaurants have to increase the varieties of drinks and food on the menu. An increase in varieties will help the restaurant stay in business even if the demands change. The supply is not limited; hence the customers’ demands are satisfied by the business.

In multi-regression, the p-values of the three independent variables are very high. As a result, the hypothesis of testing if the above independent variables affect the performance of the restaurant business is accepted. The first evidence to support the acceptance of the hypothesis is the presence of positive regression on competition and new government policies. The second evidence is log transformation, which shows the relation between the dependent and independent variables. It becomes stronger if the changes in the independent variables are favorable to the restaurant business. For example, positive government policies like reduced license costs improve the business performance, and varieties of foods help the restaurant survive the stiff competition. The statistical tests used above shows consistency of the three independent variables used, whereby completion and new government show association with restaurant performance and change in customers' demand shows a negative association. If the restaurants sampled have a variety of food products, they would not have been affected by a change in customer demand. The above project can be used by new entrepreneurs to study the market characteristics before starting a new business.