Research Methods for Managerial Decisions and Survey Instrument

Pages: 9 (1710 words) Published: November 6, 2005
Research Methods for Managerial Decisions and Survey Instrument

By

Mollee Kikumoto

Kelly LaFrance

Jennie McClure

Alvin Trotman

Instructor: Jason M. Etchegaray, Ph.D.

Abstract

After running the "Research Methods for Managerial Decisions" simulation Team B will further explore the multiple regression model and how it relates to Coffee Time predicting weekly revenue more accurately using normal values and lagged values. The difference between the two models will also be explained. This paper will also look at Coffee Time's adverting spending to travel agents, as well as provide the key decision maker in the simulation with recommendations to the challenge Coffee Time has been given. Lastly, Team B will compile a survey that will allow the team to address a problem that requires a decision to be made based on several factors including demographics, operationalizing the problem, the hypotheses, scale development, levels of measurement, instrument design, and face validity.

Introduction:
All Team B members ran the Research Methods for Managerial Decisions and Survey Instrument

Simulation multiple times in order to gain complete data. The multiple regression model is explained

using both normal and lagged values. Tourism was a huge consideration for Coffee Time and Team B

explains why this is an unwise decision in the upcoming paragraphs. Coffee Time comparatively prices

their sales based on the leading competition and markets accordingly. Team B makes suggestions

based on these actions and encourages Coffee Time to spend more than the leading company in all

areas of promotion. A survey instrument has been implemented by Team B to collect data to address

the business decision of : "should Coffee Time provide sandwiches along with coffee."

a.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: 1)Multiple R = 0.738

2)R-square = 0.546
By using lagged values she came up with the following: 1)Multiple R = 0.755
2)R-square = 0.570
Explain the differences in using these different models. How could CoffeeTime further optimize this model?

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