Managerial Decisions Run the Research

¶ … Managerial Decisions

Run the Research Methods for Managerial Decisions simulation and then answer the following questions, in short answer format:

Laura wanted to build a multiple regression model based on advertising expenditures and coffee times price index. Based on the selection of all normal values she obtained the following:

Multiple R = 0.738

R-square = 0.546

By using lagged values she came up with the following:

Multiple R = 0.755

R-square = 0.570

Explain the differences in using these different models. How could CoffeeTime further optimize this model?

By having the lagged values included in the second multiple regression equation, more variation in the dependent variables are defined. Without using any lagged variables, only a small proportion of total predictability in the dependent variable is produced through the use of this statistical technique. Adding in lagged independent variables, most notably the lagged value of competitor's advertising spending will also increase the Multiple R. And R-square values generated, as greater variability in the dependent variable will be explained. The steps that CoffeeTime can take to increase the robustness of this model and further optimize it are to include more independent variables that specifically address the spending of competitors, their pricing, and consumer demand.

A b.

Tourism is one consideration for CoffeeTime's future. A survey of 1,233 visitors to Mumbai last year revealed that 110 visited a small cafe during their visit. Laura claims that 10% of tourists will include a visit to a cafe. Use a 0.05 significance level to test her claim. Would it be wise for her to use that claim in trying to convince management to increase their advertising spending to travel agents? Explain.

Yes, it would, provided she uses a one-tailed Z-test at the.05 confidence level and chooses a sample size of 120. Further, the null and alternative hypotheses to either reject or accept the hypothesis that tourists do in fact have a statistically significant influence on CoffeeTimes' sales could be completed. The use of the z-test provides a comparison of sample means to ascertain the statistical significance of tourists having a significant financial impact on CoffeeTime coffee shop sales.

Part 2:

What additional strategy (or variation on a given strategy) would you recommend to the key decision maker in the simulation to solve the challenge given? Prepare a 350-word memo to the simulation's key decision maker advocating your recommendation.

There are many more challenges involved in the development of forecasting models and the development of predictive analytics as they relate to the impact of both CoffeeTime's and competitor's advertising spending. The following are additional considerations in the development of more thorough predictive analytics and statistical forecasting models of the Indian market for CoffeeTimes' beverages and sandwiches:

Advertising spending increasing overall market growth or cannibalizing competitive sales? This is a major question that needs to be addressed through more econometric modeling, specifically looking at the aggregate impact of industry-wide spending on increasing the total market size for served coffee in key segments of the market vs. forcing consolidation of the market and cannibalization of sales. This dichotomy of market direction could best first be tested from the standpoint of attempting to predict aggregate demand and consumption for coffee in India for three to five years. Next taking the approach of using a standardized z-test to compare means, the variation in advertising levels by competitor could next be used to ascertain if advertising spending was forcing customer churn, or conversely leading to the attracting of entirely new customers. The combination of regression analysis and z-test of sample means would be able to define this in greater depth.