Secondary Data, Literature Reviews, and Hypotheses Chapter 3 Secondary Data, Literature Reviews, and Hypotheses McGraw-Hill/Irwin Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.

Learning Objectives Understand the nature and role of secondary data Describe how to conduct a literature review Identify sources of internal and external secondary data Discuss conceptualization and its role in model development Understand hypotheses and independent and dependent variables

Nature, Scope, and Role of Secondary Data Secondary data: Data not gathered for the immediate study at hand but for some other purpose Internal secondary data: Data collected by the individual company for accounting purposes or marketing activity reports External secondary data: Data collected by outside agencies such as the federal government, trade associations, or periodicals

Nature, Scope, and Role of Secondary Data Secondary data research has gained substantial importance in marketing research with: Increased emphasis on business and competitive intelligence Ever-increasing availability of information from online sources Used to examine marketing problems because of relative speed and cost-effectiveness of obtaining the data

What is a Literature Review? It is a comprehensive examination of available information that is related to. your research topic Can help clarify and define the research problem and research questions Can suggest research hypotheses to investigate Can identify scales to measure variables and research methodologies that have been used successfully to study similar topics

Criteria Used to Evaluate Secondary Data Sources Purpose Accuracy Consistency Credibility Methodology Bias

Exhibit 3.1 - Key Descriptive Variables Sought in Secondary Data Search

Exhibit 3.2 - Common Sources of Internal Secondary Data

Exhibit 3.3 - Additional Sources of Secondary Data

External Sources of Secondary Data Primary sources of external secondary data: Popular sources Scholarly sources Government sources North American Industry Classification System (NAICS): A system that codes numerical industrial listings designed to promote uniformity in data reporting procedures for the U.S. government

Exhibit 3.5 - Common Government Documents Used as Secondary Data Sources

External Sources of Secondary Data Commercial sources Syndicated (or commercial) data Consumer panels Media panels Store audits

Synthesizing Secondary Research for the Literature Review Divergent perspectives and findings need to be included Differences between findings of studies include estimates of descriptive data Three major causes of discrepancies in online retail estimates Inclusion (or not) of travel spending Methodological differences Some degree of sampling error

Developing a Conceptual Model Literature reviews can help conceptualize a model that summarizes the relationships you hope to predict Elements required to conceptualize and test a model: Variables Constructs Relationships

Variable Construct Relationships Independent Variable An observable item that is used as a measure on a questionnaire Construct An unobservable concept that is measured by a group of related variables Relationships Associations between two or more variables Independent Variable The variable or construct that predicts or explains the outcome variable of interest Dependent Variable The variable or construct researchers are seeking to explain

Developing Hypotheses and Drawing Conceptual Models Two types of hypotheses: Descriptive hypotheses Causal hypotheses

Descriptive Hypotheses Possible answers to a specific applied research problem Its development involves: Reviewing the research problem or opportunity Writing down the questions that flow from the research problem or opportunity Brainstorming possible answers to the research questions

Causal Hypotheses Theoretical statements about relationships between variables Two hypotheses can formally be stated: Hypothesis 1: Higher spending on advertising leads to higher sales Hypothesis 2: Higher prices lead to lower sales

Causal Hypotheses Positive relationship: An association between two variables in which they increase or decrease together Negative relationship: An association between two variables in which one increases while the other decreases

Characteristics of Good Hypotheses Follow from research questions Written clearly and simply Must be testable

Conceptualization Development of a model that shows variables and hypothesized or proposed relationships between variables Involves: Identifying the variables for your research Specifying hypotheses and relationships Preparing a diagram (conceptual model) that visually represents the relationships you will study

Process of Conceptualization Identify variables for research Specify hypotheses and relationships Prepare a diagram that represents the relationships visually

Exhibit 3.8 - A Model of New Technology Adoption

Hypothesis Testing Hypothesis: An empirically testable though yet unproven statement developed in order to explain phenomena Null hypothesis: A statistical hypothesis that is tested for possible rejection under the assumption that it is true Alternative hypothesis: The hypothesis contrary to the null hypothesis, it usually suggests that two variables are related

Hypothesis Testing A null hypothesis refers to a population parameter, not a sample statistic Parameter: The true value of a variable Sample statistic: The value of a variable that is estimated from a sample

Marketing Research in Action: The Santa Fe Grill Mexican Restaurant Should the owners of the Santa Fe Grill Mexican restaurant go back and restate their questions? If “no,” why not? If “yes,” why? Suggest how the research questions could be restated.

Marketing Research in Action: The Santa Fe Grill Mexican Restaurant Regarding the owners’ desire to understand the interrelationships between customer satisfaction, restaurant store image, and customer loyalty, develop a set of hypotheses that might be used to investigate these interrelationships.