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MARKET STRUCTURE ANALYSIS AT COLUMBIA DRUGSTORES, INC.;Background;Demonstrating the tools and techniques of market structure analysis is made difficult by;the fact that a firm?s competitive strategy is largely based upon proprietary data. Firms jealously;guard price, market share, and profit information for individual markets. No one should expect;Target, for example, to disclose profit-and-loss statements for various regional markets or on a;store-by-store basis. Competitors like Wal-Mart would love to have such information available.;It would provide a guide for their own profitable market entry and store expansion decisions.;To see the process that might be undertaken to develop a better understanding of product;demand conditions, consider the hypothetical example of Columbia Drugstores, Inc., based in;Seattle, Washington. Assume Columbia operates a chain of 30 drugstores in the Pacific;Northwest. During recent years, the company has become increasingly concerned with the longrun implications of competition from a new type of competitor, the so-called superstore.;To measure the effects of superstore competition on current profitability, Columbia asked;you to conduct a statistical analysis of the company?s profitability in its various markets. To net;out size-related influences, profitability was measured by Columbia?s gross profit margin, or;earnings before interest and taxes divided by sales. Columbia provided you with proprietary;company profit, advertising, and sales data covering the last year for its 30 stores, along with;public trade association and Census Bureau data concerning the number and relative size;distribution of competitors in each market, among other market characteristics.;You have decided to conduct a regression-based analysis of the various factors thought to;affect Columbia?s profitability. To aid you in this process, Columbia created the accompanying;spreadsheet entitled ?Case_Data.xlsx.? The data contained in this spreadsheet are described as;follows, where the variable name (as it appears in the spreadsheet) is in italics.;The variable Store Number identifies a particular Columbia drugstore. The dependent;variable is Profit Margin, which as stated before, is Columbia?s gross profit margin. The;following independent variables are thought to affect Columbia?s profitability. The variable;Market Share is the relative size of leading competitors in a store?s market, measured at the;Standard Metropolitan Statistical Area (SMSA) level. Columbia?s market share in each area is;expected to have a positive effect on profitability. The Market Concentration Ratio, measured as;the combined market share of the four largest competitors in any given market, is expected to;have a negative effect on Columbia?s profitability given the stiff competition from large, well-;financed rivals. Both Capital Intensity, measured by the ratio of the book value of assets to;sales, and Advertising Intensity, measured by the advertising-to-sales ratio, are expected to exert;positive influences on profitability. Growth, measured by the geometric mean rate of change in;total disposable income in each market, is expected to have a positive influence on Columbia?s;profitability, because some disequilibrium in industry demand and supply conditions is often;observed in rapidly growing areas. Finally, to gauge the profit implications of superstore;competition, the variable Superstore Dummy takes the value of ?1? if Columbia faced superstore;competition in a particular store?s market and ?0? otherwise.;Assignment;In five-to-seven pages of double-spaced writing in a Word document, answer the following;questions;1. Based on the text above, build a multiple linear regression population model to analyze;the impact of the preceding determinants on Columbia?s profitability. What is the;multiple linear regression population equation? What are the assumptions underlying the;model?;2. Using Excel and the accompanying dataset, estimate the population model. Copy and;paste your Excel output into your Word document.;3. Based on the Excel output, what is the estimated regression equation?;4. Interpret all coefficient estimates. Identify the significance level for all of these;estimates. Are any of the independent variables likely to actually influence Columbia?s;profitability? Are your estimates consistent or inconsistent with the a priori conjunctures;found in the article? (E.g., advertising intensity is thought, a priori, to increase profit;margin. Does your coefficient on advertising intensity and its associated p-value suggest;that it is directly correlated with profit margin?);5. What portion of the variability in profit margin is explained by variability in the;independent variables? Is the estimated regression equation a good fit for explaining;profit margin?;6. Based on the estimate of the coefficient on Superstore Dummy and its associated p-value;do you believe that superstores pose a threat to Columbia?s profitability? Expand on the;theoretical foundation for this conclusion, i.e., why would the existence of competitor;superstores affect Columbia?s profitability?


Paper#19229 | Written in 18-Jul-2015

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