Research Design PDF
Document Details
Uploaded by BrandNewOwl
Tags
Summary
This document provides an overview of research design, focusing on exploratory, descriptive, and causal research methods in marketing. It explains different types of research designs, such as cross-sectional and longitudinal studies. The document also discusses the various components of a research design, including the definition, phases, measurement, sampling, and data analysis.
Full Transcript
Chapter Three Research Design 3-2 Research Design: Definition A research design is a framework or blueprint of research methods and techniques chosen by a researcher conducting the marketing research project. It details...
Chapter Three Research Design 3-2 Research Design: Definition A research design is a framework or blueprint of research methods and techniques chosen by a researcher conducting the marketing research project. It details the procedures necessary for obtaining the information needed to structure or solve marketing research problems. Components of a Research 3-3 Design Define the information needed Design the exploratory, descriptive, and/or causal phases of the research Specify the measurement and scaling procedures Construct and pretest a questionnaire (interviewing form) or an appropriate form for data collection Specify the sampling process and sample size Develop a plan of data analysis A Classification of Marketing Research 3-4 Designs Fig. 3.1 Research Design Exploratory Conclusive Research Design Research Design Descriptive Causal Research Research Cross-Sectional Longitudinal Design Design Single Cross- Multiple Cross- Sectional Design Sectional Design Exploratory & Conclusive Research 3-5 Differences Table 3.1 Exploratory Conclusive Objective: To provide insights and To test specific hypotheses and understanding. examine relationships. Character- Information needed is defined Information needed is clearly istics: only loosely. Research process defined. Research process is is flexible and unstructured. formal and structured. Sample is Sample is small and non- large and representative. Data representative. Analysis of analysis is quantitative. primary data is qualitative. Findings Tentative. Conclusive. /Results: Outcome: Generally followed by further Findings used as input into exploratory or conclusive decision making. research. A Comparison of Basic Research 3-6 Designs Table 3.2 Exploratory Descriptive Causal Objective: Discovery of ideas Describe market Determine cause and insights characteristics or and effect functions relationships Characteristics: Flexible, versatile Marked by the prior Manipulation of formulation of one or more specific hypotheses independent variables Often the front Preplanned and end of total structured design Control of other research design mediating variables Expert surveys Secondary data Methods: Pilot surveys Surveys Experiments Secondary data Panels Qualitative Observation and research other data 3-7 Uses of Exploratory Research Formulate a problem or define a problem more precisely Gain insights for developing an approach to the problem Identify alternative courses of action Develop hypotheses Isolate key variables and relationships for further examination Establish priorities for further research 3-8 Methods of Exploratory Research Survey of experts Pilot surveys Secondary data analyzed in a qualitative way Qualitative research 3-9 Use of Descriptive Research To describe the characteristics of relevant groups, such as consumers, salespeople, organizations, or market areas. To estimate the percentage of units in a specified population exhibiting a certain behavior. To determine the perceptions of product characteristics. To determine the degree to which marketing variables are associated. 3-10 The Six W’s Who What When Where Why Way 3-11 Methods of Descriptive Research Secondary data analyzed in a quantitative as opposed to a qualitative manner Surveys Panels Observational and other data 3-12 Cross-sectional Designs Involve the collection of information from any given sample of population elements only once. In single cross-sectional designs, there is only one sample of respondents and information is obtained from this sample only once. In multiple cross-sectional designs, there are two or more samples of respondents, and information from each sample is obtained only once. Often, information from different samples is obtained at different times. Cohort analysis consists of a series of surveys conducted at appropriate time intervals, where the cohort serves as the basic unit of analysis. A cohort is a group of respondents who experience the same event within the same time interval. Consumption of Various Soft Drinks 3-13 by Various Age Cohorts Table 3.3 Percentage consuming on a typical Age day 1950 1960 1969 1979 8-19 52.9 62.6 73.2 81.0 20-29 45.2 60.7 76.0 75.8 C8 30-39 33.9 46.6 67.7 71.4 C7 40-49 23.2 40.8 58.6 67.8 C6 50+ 18.1 28.8 50.0 51.9 C5 C1 C2 C3 C4 C1: cohort born prior to 1900 C5: cohort born 1931-40 C2: cohort born 1901-10 C6: cohort born 1940-49 C3: cohort born 1911-20 C7: cohort born 1950-59 C4: cohort born 1921-30 C8: cohort born 1960-69 3-14 Longitudinal Designs A fixed sample (or samples) of population elements is measured repeatedly on the same variables A longitudinal design differs from a cross- sectional design in that the sample or samples remain the same over time, thus providing a series of pictures, which when viewed together, portray a vivid illustration of the situation and the changes that are taking place over time. of 3-15 Longitudinal and Cross-Sectional Designs Table 3.4 Evaluatio Cross-Sectional Longitudinal n Criteria Design Design Detecting Change - + Large amount of data - + collection - + Accuracy + - Representative Sampling + - Response bias Note: A “+” indicates a relative advantage over the other design, whereas a “-” indicates a relative disadvantage. 3-16 Uses of Casual Research To understand which variables are the cause (independent variables) and which variables are the effect (dependent variables) of a phenomenon To determine the nature of the relationship between the causal variables and the effect to be predicted METHOD: Experiments Potential Sources of Error in 3-17 Research Designs Fig. 3.2 Total Error Random Non-sampling Sampling Error Error Response Non-response Error Error Researcher Interviewer Respondent Error Error Error Surrogate Information Error Respondent Selection Error Inability Error Measurement Error Questioning Error Unwillingness Error Population Definition Error Recording Error Sampling Frame Error Cheating Error Data Analysis Error 3-18 Errors in Marketing Research The total error is the variation between the true mean value in the population of the variable of interest and the observed mean value obtained in the marketing research project. Random sampling error is the variation between the true mean value for the population and the true mean value for the original sample. Non-sampling errors can be attributed to sources other than sampling, and they may be random or nonrandom: including errors in problem definition, approach, scales, questionnaire design, interviewing methods, and data preparation and analysis. Non-sampling errors consist of non- response errors and response errors. 3-19 Errors in Marketing Research Non-response error arises when some of the respondents included in the sample do not respond. Response error arises when respondents give inaccurate answers or their answers are misrecorded or misanalyzed. 3-20 Marketing Research Proposal Executive Summary Background Problem Definition/Objectives of the Research Approach to the Problem Research Design Fieldwork/Data Collection Data Analysis Reporting Cost and Time Appendices