course goals identify/isolate central research questions (2) come up with a suitable research method (3) collect survey or archival data (4) perform basic statistical analysis (5) make recommendations that are business sound While these research skills can be applied across several fields of study, we will apply them primarily to the 4Ps of marketing (price, promotion, place, product, and distribution), branding, and the market segmentation concept.

Definition of Marketing Research Marketing research is the systematic and objective identification, collection, analysis, dissemination, and use of information for the purpose of improving decision making related to the identification and solution of problems and opportunities in marketing.

Figure 1.4 The Marketing Research Process Step 1: Defining the Problem Step 2: Developing an Approach to the Problem Step 3: Formulating a Research Design Step 4: Doing Field Work or Collecting Data Step 5: Preparing and Analyzing Data Step 6: Preparing and Presenting the Report

Figure 2.4 Conducting a Problem Audit History of the Problem Alternative Courses of Action Available to DM Criteria for Evaluating Alternative Courses Nature of Potential Actions Based on Research Information Needed to Answer the DM’s Questions How Will Each Item of Information Be Used by the DM? Corporate Decision-Making Culture

Figure 3.4 A Classification of Market Research Designs Exploratory Research Design Conclusive Research Design Descriptive Research Causal Research Cross-Sectional Design Longitudinal Design

Primary vs. Secondary Data Primary data are originated by a researcher for the specific purpose of addressing the problem at hand. The collection of primary data involves all six steps of the marketing research process (Chapter 1). Secondary data are data which have already been collected for purposes other than the problem at hand. These data can be located quickly and inexpensively.

Figure 5.3 A Classification of Syndicated Services Unit of Measurement Households/ Consumers Institutions

Figure 5.4 A Classification of Syndicated Services: Household/Consumers Figure 5.4 A Classification of Syndicated Services: Household/Consumers Household/Consumers Electronic Scanner Services Consumer Panels Surveys Volume Tracking Data Purchase Psychographic & Lifestyles Scanner Panels Media Advertising Evaluation Scanner Panels with Cable TV General

Figure 6.3 A Classification of Marketing Research Data Secondary Data Primary Data Quantitative Data Qualitative Data Causal Descriptive Survey Data Observational and Other Data Experimental Data

Figure 6.4 A Classification of Qualitative Research Procedures Direct (Nondisguised) Indirect (disguised) Focus Groups Depth Interviews Projective Techniques Association Techniques Completion Techniques Construction Techniques Expressive Techniques

Figure 9.3 Primary Scales of Measurement Nominal Scale Ratio Scale Ordinal Scale Interval Scale

Figure 9.5 A Classification of Scaling Techniques Noncomparative Scales Comparative Scales Itemized Rating Scales Continuous Rating Scales Paired Comparison Constant Sum Rank Order Likert Stapel Semantic Differential

Chapter 11 Outline Information Needed Interviewing Method 3) Individual Question Content 4) Inability and Unwillingness 5) Question Structure Question Wording Proper Question Order 8) ID Form & Layout 9) Reproduce Questionnaire 10) Eliminate Bugs by Pretesting © 2005 J.M.H.

Figure 12.7 Non-probability Sampling Techniques Convenience Sampling Judgmental Sampling Quota Sampling Snowball Sampling

Figure 12.8 Probability Sampling Techniques Simple Random Sampling Systematic Sampling Stratified Sampling Cluster Sampling

Definitions and Symbols Parameter: Statistic: Finite Population Correction null hypothesis alternative hypothesis Precision level: Confidence interval: Confidence level: A null hypothesis may be rejected, but it can never be accepted based on a single test. In classical hypothesis testing, there is no way to determine whether the null hypothesis is true. In marketing research, the null hypothesis is formulated in such a way that its rejection leads to the acceptance of the desired conclusion. The alternative hypothesis represents the conclusion for which evidence is sought.

Product Moment Correlation The product moment correlation, r, summarizes the strength of association between two metric (interval or ratio scaled) variables, say X and Y. It is an index used to determine whether a linear or straight-line relationship exists between X and Y. As it was originally proposed by Karl Pearson, it is also known as the Pearson correlation coefficient. It is also referred to as simple correlation, bivariate correlation, or merely the correlation coefficient.

Product Moment Correlation r varies between -1.0 and +1.0. The correlation coefficient between two variables will be the same regardless of their underlying units of measurement.

Conducting One-way Analysis of Variance Decompose the Total Variation The total variation in Y, denoted by SSy, can be decomposed into two components:   SSy = SSbetween + SSwithin where the subscripts between and within refer to the categories of X. SSbetween is the variation in Y related to the variation in the means of the categories of X. For this reason, SSbetween is also denoted as SSx. SSwithin is the variation in Y related to the variation within each category of X. SSwithin is not accounted for by X. Therefore it is referred to as SSerror.

. . . . . . . Figure 18.4 A Nonlinear Relationship for Which r = 0 6 5 3 2 . 1 -3 -2 -1 1 2 3

Regression Analysis Regression analysis is used in the following ways: Determine whether the independent variables explain a significant variation in the dependent variable: whether a relationship exists. Determine how much of the variation in the dependent variable can be explained by the independent variables: strength of the relationship. Determine the structure or form of the relationship: the mathematical equation relating the independent and dependent variables. Predict the values of the dependent variable. Control for other independent variables when evaluating the contributions of a specific variable or set of variables. Regression analysis is concerned with the nature and degree of association between variables and does not imply or assume any causality.

Conducting Bivariate Regression Analysis Fig. 18.5 Plot the Scatter Diagram Formulate the General Model Estimate the Parameters Estimate Standardized Regression Coefficients Test for Significance Determine the Strength and Significance of Association Check Prediction Accuracy Examine the Residuals Refine the Model

Plot of Attitude with Duration 9 Attitude 6 3 2.25 4.5 6.75 9 11.25 13.5 15.75 18 Duration of Car Ownership Figure 18.3

Table 18.2 Bivariate Regression

Product Moment Correlation The product moment correlation, r, summarizes the strength of association between two metric (interval or ratio scaled) variables, say X and Y. It is an index used to determine whether a linear or straight-line relationship exists between X and Y. As it was originally proposed by Karl Pearson, it is also known as the Pearson correlation coefficient. It is also referred to as simple correlation, bivariate correlation, or merely the correlation coefficient.

Factor Analysis What is a factor What is a cluster What is a factor loading - min loading ROT Benefits of using factors in regression Negatives of using factors in regression What is a cluster Agglomeration schedule usage ROT 2 ways to cluster -visually versus quantitatively Benefits of K-Means clusters Benefits of Hierarchical clusters

Conclusion Although understanding ethical diversity is good, accepting all forms of ethical diversity is neither good for organizations nor the societies in which they are embedded.

On Ethics a) Within your circles of influence, you have a responsibility to encourage and guide the development of other’s ethical behavior—we are a society. Be Bold. Be Brave. b) Ethics can—and should—be taught. c) By nature of your being in this room, you have been endowed through the moral courage of another to develop your own personal moral code—strengthen it. d) Everything is not relative. There are rights and wrongs. Ponder them, incorporate them into your life, and protect them from philosophies that will tear them apart. e) Most ethical problems arise from selfishness. Two part solution: * Don’t go into unnecessary debt. * Give service.