MARKET RESEARCH

Research Design

OBSERVATION Broad area of

Research Interest Identified

OBSERVATION Broad area of

Research Interest Identified

Theoretical Framework and Hypothesis Development

Source: Research Methods for Business, Uma Sekaran

PRELIMINARY DATA

GATHERINGSInterviewing

Literature Survey

PRELIMINARY DATA

GATHERINGSInterviewing

Literature Survey

PROBLEM DEFINITION

Research Problem

Delineated

PROBLEM DEFINITION

Research Problem

Delineated

THEORETICALFRAMEWORKTHEORETICALFRAMEWORK GENERATIO

N OF HYPOTHESIS

SCIENTIFIC

RESEARCH DESIGN

DATA COLLECTION

ANALYSIS, AND INTERPRETATION

DATA COLLECTION

ANALYSIS, AND INTERPRETATION

DEDUCTION Hypotheses

Substantiated?Research Question

answered?

DEDUCTION Hypotheses

Substantiated?Research Question

answered?

Report Writing

Report Presentation

Decision Making

1

Variables already

identified and labeled

Variables already

identified and labeled

2

34

5 6 7

8

9 10 11NoYes

Research DesignIntroduction• The design of the research project is a creative plan to

obtain the necessary information in the best way possible.

• The correct design saves time and money and will result in valid and reliable information.

• It is expected that the market researcher should be equipped with the technical knowledge to design research projects that will provide a wide variety of marketing information to key decision-makers.

• A range of required design skills are covered under this topic.

Research Design

Research DesignResearch Design:A research design is the operational plan for executing a marketing research project. It describes the steps necessary to obtain the information needed to structure or solve marketing problems and reduce decision-making risk.Typically, creating a research design involves the following tasks:

• 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 or some other type of

data collection instrument• Specify the sampling process and sample size• Develop a data analysis plan

Research DesignExploratory Versus Conclusive Research

Research designs may be broadly classified as exploratory or conclusive

• Exploratory research is also known as qualitative research • Conclusive research is the same as quantitative research

Exploratory research is intended to develop an understanding of the problems motivating the research. It has following characteristics:– The information needed is only loosely defined at this stage, and the

research process is flexible and relatively unstructured. – The sample is usually small and not statistically representative. – The primary data are non-numerical (for example, transcripts of in-

depth interviews or focus group sessions) and are analyzed qualitatively.

– Exploratory research findings are not conclusive but are often essential to the construction of a valid conclusive research design.

Research DesignExploratory Research

An Exploratory research or study is undertaken when not much is known about the situation at hand, or no information is available on how similar problems or research issues have been solved in the past.In such cases, extensive preliminary work needs to be done to gain familiarity with the phenomena in the situation, and understand what is occurring.In certain qualitative studies where data is collected through observation or interviews are exploratory in nature. Based on that further research work either exploratory or conclusive are taken

Research DesignExploratory Research:

Exploratory research searches are for insights and understanding about a problem

It is most useful when researchers lack the information needed to define variables and hypotheses suitable for statistical research.

Exploratory research methods include:– Interviews with experts, which are usually with a small number of

individuals and very open-ended.– Pilot surveys, which are relatively structured interviews with small

samples of respondents conducted prior to the implementation of a large-scale quantitative investigation.

– Analysis of secondary data.– Qualitative research, which is usually conducted via focus group

discussions or as in-person/telephone in-depth interviews.

Research Design

Exploratory Research Example:

Manager Marketing of a fruit juice making firm is curious to know the choice preference of its consumers from lower income groups. Earlier the product was target to upper middle or higher income groups. There is a little information about this population segments and there are difference in opinions about the taste and development process. The manager’s curiosity can be satisfied only by an exploratory research study. This can be done through interviewing the people from the lower income group, studying the economic, education, and social conditions, upbringing, cultural values and son.

Research DesignConclusive Research

Studies that engage in hypothesis testing usually explain the nature of certain relationships, or establish the differences among groups or the independence of two or more factors in a situation.

• The objective of conclusive research is to test hypotheses about well-defined, quantifiable problems.

• Conclusive research is based on large, representative samples, and the data obtained are subjected to statistical analysis.

• The findings are conclusive in that their generalizability, validity, and reliability are sufficiently high enough to help managers make decisions with a good understanding of risks and benefits.

• Conclusive research designs may be descriptive (providing data that describes something) or causal (providing data that defines cause-and-effect relationships).

Research DesignConclusive ResearchExamples:

Research DesignDescriptive Research: An Overview• Descriptive research is a type of conclusive research design. The

function of descriptive research is to describe something, usually the characteristics or attributes of a specific market.

• Descriptive research begins with the statement of testable hypotheses. This requirement makes descriptive research less open-ended and more narrowly focused than exploratory research.

• Large samples are needed to ensure that descriptive research findings are representative.

• Most marketing research studies involve descriptive research. Typical data sources include: Surveys -- Survey methods include telephone interviewing, in-person interviewing,

mail surveys, and electronic interviewing (e-mail, Internet). Observation -- Observational methods include personal observations, mechanical

observations (e.g., television "people meters"), and audits.

Research DesignDescriptive Research: An Overview

Research DesignDescriptive Research: Cross-Sectional Designs• Cross-sectional studies are a common form of descriptive

marketing research. Cross-sectional research designs allow the researchers to collect information from a given sample one time, providing information about a specific "cross-section" or moment of this population's history.

• Single cross-sectional designs use only one set of respondents from the target population.

• Multiple cross-sectional designs take two or more samples of respondents, and information from each sample is obtained at different points in time (e.g., pre/post studies and tracking studies use multiple cross-sectional designs).

Research DesignDescriptive Research: Cross-Sectional Designs;Example

Research DesignDescriptive Research: Longitudinal Designs• Longitudinal designs measure a sample repeatedly. Unlike a

cross-sectional design, the researcher collects data from the same respondents over an extended period. While a cross-sectional design captures the variables of interest at a single moment in time, a longitudinal study provides a series of snapshots that allows the researcher to understand how situations and attitudes evolve over time.

• The term "panel" is often used synonymously with "longitudinal design." A panel is a sample of respondents, generally households, who agree to provide information at specified intervals. Most panels are maintained by syndicated firms, and respondents receive gifts, coupons, information, or cash as compensation for their involvement in the research project.

Research DesignDescriptive Research: Longitudinal Designs:Example:

Research DesignType of Investigation:Causal:• The study in which the researcher wants to delineate the

cause of one or more problems is called a causal study. • The goal of causal research is to demonstrate cause-and-

effect relationships. • Marketing managers constantly rely on assumptions

about causal relationships in their decision-making. • If these assumptions are unwarranted, the results can be

costly. For example, the common belief that lowering prices will increase sales and market share does not apply to every situation and could lead to losses of revenue if acted on without justification.

Research DesignType of Investigation:Causal• Like descriptive research, causal research is structured by

hypothesis testing. While descriptive research assesses the degree of association between variables, through causal research it is possible to generalize about causes and effects. It requires a design in which the causal or independent variables can be controlled and systematically manipulated. The researcher measures the effects of this manipulation on one or more dependent variables and can then make inferences about causality.

• Causal research designs are typically experimental and reflect the extension of the classic scientific method to marketing problems.

Research DesignType of Investigation:Correlational:• When researchers is interested in delineating the important

variables associated with the problem, the study is called correlational study.

• It is mere establishment of relationship of one or more variables with the problems.

Example:A causal study question:Does smoking cause cancer?A correlational study question:Are smoking and cancer related?OR

Are smoking, and chewing gutka or meethi chalia associated with cancer? If so which of these contributes most to variance in the dependent variables?

Research DesignType of Investigation:Example:

Fears of earthquake in Kashmir and adjacent areas were instrumental (i.e. causal) in an unprecedented number of house-owners in that region taking out an insurance policy.

Strict application of property taxes, recession, land grabbing and the predicted law and order situation considerable slowed down the business of real estate in Karachi.

Research DesignReserchers Interference in Causal and Correlational Studies:

The extent of interference by the researcher with the normal/ natural situation has a direct bearing on whether the study undertaken is causal or correlational.A correlational study is conducted in the natural environment with minimum interference by the researcher. In cause-and-effect studies the researcher tries to manipulate the certain variables so as to study the effect of such manipulation on the dependent variable of interest.

MINIMAL INTERFERENCEMODERATE INTERFERENCEEXCESSIVE INTERFERENCE

Research DesignReserchers Interference in Causal and Correlational Studies:Minimal Interference:

Research DesignReserchers Interference in Causal and Correlational Studies:Moderate Interference:

Research DesignReserchers Interference in Causal and Correlational Studies:Excessive Interference:

Research DesignPrimary Versus Secondary Data• Primary data are generated by a researcher in the process of

studying a specific problem. Collecting primary data can be expensive and slow.

• Secondary data have been collected for purposes other than the researcher's immediate need. These data can be located quickly and usually inexpensively. The disadvantages are that the usefulness of secondary data may be limited for the problem at hand. The applicability, accuracy, reliability, and validity of the secondary data must be critically assessed.

• Sources of secondary data in Pakistan??????

Research DesignSources Of Primary Data• Primary data may be qualitative or quantitative. The

distinction between qualitative and quantitative data parallels the distinction between exploratory and conclusive research methods discussed earlier.

• Qualitative data are usually verbal and are often collected through focus groups, interviews (sometimes called in-depth interviews or IDIs), or projective techniques.

• Quantitative primary data are gathered through surveys, observation, or experimentation.

Research DesignSelecting An Appropriate Research Design• Exploratory, descriptive, and causal research are convenient as major

classifications of research designs, but the boundaries between these classifications are not hard and fast. A research project can require several types of research design, depending on the problem being studied.The following guidelines can help:– If the problem is vague or not well understood, exploratory research is the

best first step.– Exploratory research should usually be followed by descriptive or causal

research. – Some research projects do not require initial exploratory research, depending

on how well the problem can be specified. Research on a problem that is well-understood and clearly defined might begin with descriptive or causal research.

– Exploratory research can also follow descriptive or causal research. For example, if the findings of descriptive or causal research are ambiguous, exploratory research may provide insights to help clarify their meaning

Research DesignPotential Sources Of Error• Research designs are vulnerable to several potential sources of error.

These include errors of omission and errors of commission. Errors of omission include sampling coverage and non-response. Errors of commission are response errors (due to the researcher,

interviewer, or respondent).• Since any of these can prevent research findings from providing a sound

basis for decisions, it's important in the design process to anticipate and try to control as many sources of error as possible.

• The total error is the variation or gap between the researcher's interpretation of data and the actual conditions the data represent. More technically, in a quantitative study, total error is the difference between the actual mean value of the variable of interest in the population and the estimated mean value reported in the marketing research project.

Research DesignPotential Sources Of Error

The total error includes both random sampling error and non-sampling error.

• Random sampling error happens when the chosen sample selected is not representative of the population being studied.

• Non-sampling errors can be random or nonrandom. Possible causes include poor problem definition, an inappropriate approach to the problem, errors in the design of measurement scales, questionnaires, and interviews, or errors in preparing and analyzing data. Non-response errors and response errors are also forms of non-sampling error.

Research DesignPotential Sources Of Error• Whenever some of the respondents in the sample do not

respond, the study is subject to some measure of non-response error. Non-response in consumer research usually occurs when respondents refuse to participate or are not at home Non-response will make the resulting sample different from the intended sample (as defined by demographics such as age, gender, income, etc.). If non-respondents differ from the respondents in terms of their potential responses, the data are biased. If large enough, non-response error can lower validity to such an extent that conclusions based on the data are likely to be wrong.

• If respondents give inaccurate answers, if interviewers erroneously record answers, or if researchers analyze the answers improperly, response errors result.

Research DesignReliability and Validity in Marketing Research

RELIABILITY• Reliability is the degree to which a procedure produces the

same results if repeated. Measurements are reliable to the extent they are free from random error (e.g., measurement error which occurs from random differences between respondents or measurement situations).

• Techniques for evaluating reliability include the test-retest and alternative forms methods.

Research DesignReliability and Validity in Marketing Research

VALIDITY• A measurement instrument is said to be valid when

differences in measurements reflect true differences among the objects being measured, rather than random error or systematic error (e.g., error that affects the observed score in the same way each time the measurement is made).

• In research design, the most important consideration is often construct validity, which addresses the question of what construct or characteristic the study is, in fact, measuring. In other words, are the variables as defined in the study actually useful measures of meaningful characteristics of the population?

Research DesignRelationship Between Reliability and Validity• A measure must be reliable to be valid, but just because it is

reliable does not automatically make it valid. Consider this example: You step on your bathroom scale three times in succession and you receive three different measures of your weight. The scale is neither reliable nor valid—it is not accurately measuring your weight. But if each time you weighed yourself it read 10 pounds, then the scale is reliable but not valid (unless you truly weighed 10 pounds).

Research DesignCross-Cultural And International Marketing Research• Due to cultural and other environmental differences a given

research design may not be appropriate in every country, even when the same problem is being investigated.

• For example, different methods are required to determine household attitudes toward major appliances in the United States and Saudi Arabia. In the United States, exploratory research could involve focus groups that included both male and female heads of households. However, given the traditional culture of Saudi Arabia, mixed-sex focus groups could produce response errors because women might not express themselves freely in the presence of men. A better design for this situation would use one-on-one interviews with both male and female heads of households.