Gateway Estate Lawn Equipment Co. Performance Lawn Equipment Harvard Case Solution & Analysis

Gateway Estate Lawn Equipment Co. Performance Lawn Equipment The case solution  

Question: 2

As the human resources director meeting informed that there is high turnover rate in the field service staff. So the human resources department was suggested to focus on the hiring and recruiting policies and specially on the characters of individuals at the time of hiring of interview. they  think that these character has impact on the employees retention. So they are trying to come up with the individual character that have impact on retention of individual. In a meeting they came to list some individual characters that must be considered such as education years, GPA, and age are good predictors of individual retention. But human resources director is not fully agreed on it. So they want to know whether it has significant impact on retention of not for that we performed statistical methods such as regression to know the fact.

As we-performed regression analysis, after which we came to know that the years of education variable are not predictors of retention. Higher education does not indicate to the significance of greater possibility of retention, because the coefficient of years of education is 0.68, but the p-value is greater than 0.05, which means the years of education variable is not the predictor of the employees’ retention. On the other hand,there is a positive relationship between the college GPA and the employees’ retention, and the hypothesis is rejected because the p-value is 0.5745, which is greater than 0.05. So, the years of education and college GPA are not the predictors of employees’ retention.

Only age, at the time of hiring an employee, is the predictor of employees’ retention, because the p-value is 0.03, which is less than 0.05.It shows the significance of the hypothesis.the t-states is greater than 2, and p-value is less than 0.05. so it  shows significance of hypothesis. The confidence interval does not contain zero so it is also showing significance.

The R-square is only 15% so this model is only have 15% explanatory power of variation in employees retention or employees turnover.

As we come to the conclusion that education years and CGPA does not have significant impact the retention. So we can perform regression only for age to know the significance of impact of age on retention.

The age also does not have significant impact alone.

Question: 3

From our regression analysis; we came to the equation y= 58.184-0.293X. The R-square is 84.9%, which shows 84.9% variation in time of production, which is explained by technology. The new product technology reduces the time of production because the p-value of the coefficient is nearly zero, so it's significant.

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