BUSINESS RESEARCH METHODS

BUSINESS RESEARCH METHODSMBA FALL 2014AgendaResearch ProcessStrategies of InquiryData Collection MethodsSampling techniquesEthics in ResearchStages in a Research Process1.Select Topic/Identify the problem 2.Literature Review 3.Decide Research Question(s)/Problem definition4. Develop Conceptual Framework & Operationalise5. Plan Research Design6.Decide Research Method7.Conduct Research8. Report FindingsPlan Research DesignA Framework for DesignResearch Design & MethodologyQualitative DesignsEthnographyGrounded TheoryCase StudyAction research

Quantitative DesignsExperimentsSurveys

Mix Methods DesignsSequential ConcurrentQuantitative Design & MethodologiesQuantitative Research MethodologiesQuantitative DesignsExperimentsSurveys

Quantitative ResearchSurvey is the most common and popular strategy in business and management research. It allows the collection of large amount of data from a sizeable population in a highly economical way.It provides description of trends, opinions and attitudes of a population by studying a sample of that population in a standardized way.The intent is to generalize from a sample to population.

Experimental Research when researcher controls the environment of the subjects and measures the effect of that controlled change/experimental treatment.

Subjects are divided into two groups control group and experimental group.Experimental ResearchExperimental designs are used to establish cause and effect relationship.

To establish that X causes Y, all three of the following conditions must be met:Both X and Y should covary.X should precede Y. In other words there should be a time sequence in which the two occur.No other factor should possibly cause the change in dependent variable Y.

Experimental ResearchIndependent variable Its value may be altered or changed independently of any other variable

Dependent variable A variable whose value has changed due to the manipulation of independent variable.

Exogenous Variables are the ones that also influence the dependent variable. They confound (or contaminate) cause and effect relationship.

Variables in ExperimentsX Experimental treatmentO1 - Observation 1 or measurement 1 of the dependent variable.O2 Observation 2 or measurement 2 of the dependent variable.R - Random assignment of subjects to experimental and control group.

Treatment group O1 X O2Control group O1 O2Experimental Research DesignsTwo ways to control contaminating exogenous/extraneous variables is

Matching Groups

RandomizationControlling the Exogenous VariablesMatching Groups

One way to control the contaminating variables is match various groups by picking the confounding characteristics and deliberately spreading them across groups such that each group will have a similar mix of individuals.

Controlling the Exogenous VariablesRandomization

Another way to control the contaminating variables is to assign individuals randomly to the groups. That is any member would have a known and equal chance of being assigned to any of the groups.Controlling the Exogenous VariablesOne-shot design - X O1

Based on one group, one treatment and one measurement.Weakest of all experimental designs.Does not measure any cause-effect relationship because we do not have a control group to compare with.

E.g. You measure the effect of a promotion campaign (treatment) on sales (measurement) of a product.

Quasi-experimental DesignsOne group pre-test-post-test design O1 X O2

Permits comparison of pre and post treatment results.

E.g. At the beginning of the semester a test (measurement) is conducted to measure students knowledge on of Research methods and then after 24 lectures (treatment) a test (measurement) is conducted to test subjects knowledge.

Quasi-experimental DesignsStatic group design Treatment groupX O1Control group O1 It has two groups experimental group and control group.Groups are not randomly chosen and may already exist. Experimental group is measured after it is exposed to treatment and control group is measured without having exposed to treatment.E.g. A policy (treatment) is introduced in one branch of a company and its outcome is measured and compared with the employees in another branch who are not exposed to this treatment.

Quasi-experimental Design19Sampling StrategiesSampling is the process of selection of subjects/elements in a population, we may want to draw conclusion about the entire population.

Census study - Investigation of all individual elements that make up a population

SamplingRepresentative Sample is one that is representative of the population.If so is the case we can generalize our findings from the sample to the population.

Biased Sample is one that is not representative of the population.SamplingProbability Sampling

Non-probability SamplingTwo Major Categories of SamplingProbability Sampling are those methods that can be relied on to produce a sample that is close to representative.

Using these methods all the elements have a known, not necessarily equal chance of being included in the sample.

Probability SamplingNon-probability Sampling are those methods that may produce a representative sample, you cant rely on it to do so (Precision & confidence cannot be obtained).

Using these methods the probability of an element being included in the sample is unknown.

Non-probability SamplingSimple Random Sampling

Systematic Random Sampling

Stratified Sampling

Cluster Sampling

Multi-stage SamplingProbability Sampling MethodsEach member of the population has an equally likely chance of being selected in a sample.E.g. If a sample of 30 is to be selected from a population of 300 then every member has a 1 in 10 chance of being selected.

Study objects are selected by use of random numbers, either from tables available or by generating them on a computer.Simple Random SamplingAn initial starting point is randomly selected and then every nth number on the list is selected.

Often can be more representative since it cuts across the population.

Systematic Random SamplingList should be random in character not in a systematic pattern.

Disadvantage list of population rarely exists.Sample may be scattered over wide geographic locationRandom SamplingA sampling technique designed to ensure that subgroups or strata are fairly represented.

Sometimes population is made up of subgroups or strata of specific characteristics (e.g. gender, class level, ethnicity).

Population is divided into groups or strata and then subsample are drawn randomly from each stratum.Stratified SamplingCluster sampling involves using participants that are already part of a group or cluster.

Groups or clusters are selected at random to be studied. (whole cluster is studied)

E.g. students of FAST-NU at Lahore campus.Economical and allows larger number ofobservations

Cluster SamplingMulti-stage sampling is using more than one probability sampling techniques.

E.g. combining cluster and random sampling.Multi-stage SamplingConvenience Sampling

Quota Sampling

Judgment Sampling

Snowball SamplingNon-probability SamplingAlso called haphazard or accidental sampling.

The sampling procedure of obtaining the people or units that are most conveniently available.

Generally used to obtain a large number of completed questionnaire quickly and economically.

If using convenience sampling them remember projecting results beyond that sample is inappropriate.

Convenience SamplingQuota Sampling a technique to ensure that various subgroups in a population are represented on pertinent sample characteristics to the extent investigator desires.

E.g. study the customer satisfaction with each of the mobile network users.Quota SamplingSample obtained on judgment & experience of researcherAlso known as purposive sampling.

Gross dependence on researcher expertise

Good for small samples only

Error increase with sample size

Judgment SamplingA variety of procedures.

Initial respondents are selected by judgment.

Additional respondents are obtained from information provided by the initial respondents (referral).

Snowball Sampling