Business Statistics For Employee Customer Chain – Analysis And Recommendations

Factors affecting customer satisfaction in the gym

Describe about the Business Statistics for Employee Customer Chain.

Introduction:

The dataset in this assignment consists of the data about the survey in a gym. The gym mentioned in this report has proposed a change. The reaction of the customers regarding the change is to be analyzed in this report. The opinion about the change proposed in the gym many vary according o the customers. The change that is being proposed may work well for one group of customer while the change may not be liked by the other group. For example, the female group may be attracted by a discount offered in the gym while the discount may not work well for the male customers.

In this dataset, the information about the type of exercise performed, the height, weight, physical fitness of the customers is being obtained. The data has been analyzed using various statistical techniques. The change that is to be proposed has to be determined on the basis of the results of data analysis. A survey has been conducted among the customers to know whether the customers are in favor of the proposed change or not. The data has been analyzed using various techniques such as testing of hypothesis and confidence intervals. The report will give an idea about the success of the proposed change.

According to Wu & Shih (2014), the customer loyalty is a very important factor in the function of a gym. The customer loyalty is driven by many factors such as the quality of service, machineries in the gym and others. According to Makover (2016), a study has been conducted to know about the factors affecting customer satisfaction in the gym. The study has been conducted among the fitness clubs located in South Florida. The customer satisfaction that is customer loyalty, brand loyalty and others are driven by thee service and quality provided in the fitness centers. Therefore, it is recommended that the customer satisfaction should be ensured in a gym to improve the business of the gym.

The customer satisfaction can be ensured with the help of the service provided in the gym. The service provided in the gym can be explored with the help of the change in the body mass index of the customers and the number of minutes spent in the weighing exercise. The following scatter diagram has been obtained for the two variables.

                         

Exploring service provided in the gym

Figure: Scatter diagram

Source: Created by author

The scatter diagram given above has been obtained by plotting the time spent by the customers in a weighing machine and the body mass index of the customers. The body mass index of the customer is a measurement of body fitness. The body mass index is measured by the weight of the person divided by the height of the person. The regular exercise is expected to reduce the Body mass index of the people. Therefore, the Body mass index is expected to have a negative relationship with the time spent in weighing machine. The co efficient of regression analysis will help to know about the relationship between the two variables. The regression line obtained in this case is:

• y = -1.106*x + 48.84 +e.

The value of the regression co efficient obtained is -1.106. Therefore, it can be said that the model is not very good fitted. However, the model shows that there is a negative relationship between the body mass index and the time spent on weighing machine.

A regression analysis has been conducted taking the B.MI as the dependent variable and the time spent on weighing machine as the independent variable.

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.191417
R Square	0.03664
Adjusted R Square	0.02681
Standard Error	2.816598
Observations	100

Table 1: Adjusted R-squared values of regression analysis

(Source: Created by author)

ANOVA
	df	SS	MS	F	Significance F
Regression	1	29.56975	29.56975	3.727329	0.056419
Residual	98	777.4562	7.933226
Total	99	807.0259

Table 2: ANOVA of regression analysis

(Source: Created by author)

	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	26.68483	0.444478	60.03638	4.22E-79	25.80278	27.56689	25.80278	27.56689
Q12: Minutes on weight machine.	-0.03311	0.017149	-1.93063	0.056419	-0.06714	0.000923	-0.06714	0.000923

Table 3: Regression analysis of B. M. I and time spent on weighing machine

(Source: Created by author)

The results of regression analysis show that the time spent on weighing machine has an inverse relation with the B.M.I. A test has been conducted to know whether the regression co efficient is significantly different from zero or not. The single sample t-test has been conducted for the purpose. The objective of the test is to see if the regression co efficient is significantly different from zero or not. The p-value of the test obtained is more than 0.05 for the slope. Therefore, the regression co efficient has a significant effect on the dependent variable. The regression co efficient is significantly different from zero. Therefore, one can say that as the value of B. M. I increases, the value of time spent in weighing machine decreases. There is an inverse relation between the two.

The mean and variance of the two variables are given in the following table:

MEASURES	B . M. I	Q12: Minutes on weight machine.
MEAN	26.021	20.05
STANDATD DEVIATION	2.855132	16.50673

Table 4: Mean and variance of B. M. I and time spent on weighing machine

(Source: Created by author)

Regression analysis of body mass index and weighing exercise

Managerial advice:

The quality of weighing exercise in the gym is very poor. The results of regression analysis show that. It has been pointed out that customer satisfaction is one of the main reasons driving the change in the business of the gym. The condition of physical exercise needs to be improved. The gym can employ better trainer to bring about the proposed change. The efficient trainer can bring about betterment of physical exercise in the gym.

A survey has been conducted among the gym customers to know about the proportion of people who are in favor of the proposed change. The survey has been conducted by taking a sample of one thousand customers. The survey has been conducted by taking the help of sampling method. The aim of doing so is to save the time and labor in conducting the study. The customers were asked if they liked the proposed change or not. It has been found that out of a total of one thousand customers, a total of 892 customers are in favor of the proposed change. This means that majority of the customers likes the proposed change. A t-test has been conducted to see if the number of people who are in support of the change is greater than .5 or not. The null hypothesis of the test is H0: p= 0.5 and the alternative hypothesis is H1: p ≠ 0.5. The term p denotes the proportion of people who are in favor of the change. The alternative hypothesis indicates that the proportion of people can be greater than or less than 0.5. The value of the proportion has been calculated to be 0.892 which is much greater than 0.5. The test statistic is :

• t = (p – 0.5)/S.E(p)

The term S.E (p) denotes the standard error of the proportion. The formula for the calculation of standard error is:

• E (p) = sqrt(p(1-p)/n).

The value of standard error that has been calculated on the basis of the given sample is 0.31038. The value of the test statistic is 1.2629. The test statistic is said to follow a standard normal distribution as the value of the sample is very large. The value of the t statistic has been calculated to be 1.645 at 10 % significance level. Therefore, the null hypothesis of the test is accepted as the p-value is greater than given level of significance 10 percent.

A confidence interval has been calculated for the proportion of people as well. The confidence interval has been calculated by the following formula:

• I = ( p – 1.645* S.E (p) , p + 1.645 * S.E (p))

The confidence interval has been calculated to be (0.31038032, 1.402575). This implies that the value of the proportion is expected to lie within this interval.

Conclusion and recommendation:

The report gives an idea about the customer service in a gym. The gym has proposed a new change to bring about the efficiency in the customers. A new fitness trainer has been introduced in the gym. The study suggest that majority of customers are in support of the proposed change.

The recommendations that follow from the test are:

Therefore, it is recommended from the study that the gym should bring about the proposed change to increase its customers. With the help of the proposed change, the gym can increase customer satisfaction and increase customer loyalty. The customers has also voted in favor of the change.

The fitted regression model is not very good as is explained by the adjusted R-squared. This may be due to the insufficient sample or improper sampling techniques. Therefore, a proper sample should be used for the study.

References:

Makover, B. (2016). Examining the employee-customer chain in the fitness industry.

Polyakova, O., & Mirza, M. T. (2016). Service quality models in the context of the fitness industry. Sport, Business and Management: An International Journal, 6(3).

Wu, L. C., & Shih, I. (2014). The product development process of an enterprise from an SSME perspective. Service Business, 8(1), 29-50.