Business Research Methods (CURMCS223)

M. SIKWILA

CONTACT: 0736024908March, 2015

Introduction

The need to do research or an Inquiry is varied. But the main ones include:

a) Adding to knowledgeb) Evaluation of existing knowledge and explain

furtherc) Answer Questionsd) Test theories or hypothesise) Find solutions to problems

Way of understanding the World Phenomenon

We can understand how things work in three ways:

• Experience• Reasoning• Research_____________

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Experience• Draw on individual accumulation of body of

knowledge and skills obtained through contact with facts and events in your environment.

• Consult those with experience (experts)• Using experience you could come up with

hypothesis and questions about the real world.

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Reasoning:Type of reasoning1. Deductive reasoning2. Inductive reasoning3. Inductive – deductive reasoning

Deductive Reasoning

Deductive Reasoning (Aristote)This approach follows logic: For examples• All human beings walk on two legs• John is a human being• Subsequently John walks on two legs.

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• All plants revolve round the Sun and Earth revolves round the Sun the earth is a planet.

• Thus, we move from general; logically to a particular case.

• Valid conclusions are deduced from valid premises.

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The deductive reasoning lost its importance because it was noticed that it was not related to observation and experience. This makes it more of a mental exercise. In the deductive reasoning empirical evidence as a basis of proof is superseded by authority or mental reasoning only. This kind of reasoning had and adverse effect on science.

Observation basis of science

• Francis Bacon (1600c) argued that deductive reasoning was not objective, but promoted preconceived ideas and these in turn biased the conclusion.

Inductive Reasoning

• Francis Bacon proposed inductive reasoning• This kind of reasoning leads to hypotheses

formation and generalization of individual case.

• Collect data and confront it with theory, this will maintain complete objectivity.

• The inductive reasoning demands empirical evidence for verification.

Inductive – Deductive Reasoning

• The Inductive – Deductive approach led to:1. The suggestion of hypotheses2. The logical development of these hypotheses3. The clarification and interpretation of

scientific findings and their synthesis into a conceptual framework.

Research (discovery of Truth)

There are many definition as to what research is. However, no definition is 100% correct. The most important thing is to understand the concept and apply it correctly.

Kerlinger, F.N. (2000) define research as” The systematic, controlled, empirical and critical investigation of hypothetical propositions about the presumed relations among natural phenomena”.

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• Others use the concept of research to refer to the process of using scientific methods to expand knowledge in a particular field of study.

• The research approach also employs inductive – deductive approach.

• Research is self correcting• Uses accepted scientific method• Can be disapproved by other professions, i.e.

Findings. Incorrect results will be found out and rejected or corrected.

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• Research is a combination of both experience and reasoning and is the most successful approach to the discovery of truth.

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Assumptions: Social Reality (Burrel & Morgan, 1979)

Assumption1. Ontological Kind – Internal or external to an

individual2. Epistemological kind – Concern basis of

knowledge its nature & form how it can be acquired and how communicated to other human beings. Epistemological assumption – tell us which knowledge can be acquired or obtained through experience.

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• Knowledge of social behaviour – is either hard or soft – If hard –need observation (natural science). If soft –subjective and cannot follow natural science.

• If knowledge is hard it is referred to as positivist and follow natural science. Soft knowledge is referred to as anti-positivist.

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3. Concern Human nature (assumption): The relationship between human beings and their environment. Human beings are both subject and object of study (social science).

• Human beings respond mechanically to environment

• Human beings are initiators of their own actions.

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• Are human beings controllers of environment or controlled by environment.

• Determinism - Voluntarism (extremes)Most social scientist-take the middle road.These three assumptions lead to choice of

methodology.

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4. Methodology – All the previous assumptions have implications for methodology or methodological concerns of the researcher.

Researchers (hard-objective) follow-experiments, surveys, positivist approach.

(soft-subjective) follow- anti-positivist approach.

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Stages of searching for the truth:1. Theological stage (primitive to explain behaviour

in terms of spiritual or supernatural terms/entities 2.Metalphysical stage (modification of uses abstractions or forces/depersonalize beings of earlier theology

3. Positive stage (observation and reasoning as a means of understanding behaviour. Scientific description, observation and experiments.

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• “The central belief of the logical positivists is that the meaning of a statement is, or is given by, the method of verification – It follows from this that unverifiable statements are held to be meaningless, the utterances of traditional metaphysics and theology being included this class”

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• Methodological procedures of natural science may be directly applied to the social sciences – positivism here implies a particular stance concerning the social scientist as an observer of social reality.

• End results of social scientist can be interpreted just like that of natural science.

• Positivism-involves a definite view of the social scientist as analyst or interpreter of his subject matter.

Features of Positivism - Method

“Assumptions and Nature of Science”1. Determinism – Events have causes (this link can be

studied – event determined by other circumstances) a law should be there because of universe has order, follow them & you will be able to predict & control.

2. Empiricism – That which is variable by observation; and evidence, data yielding proof or strong confirmation in probability terms of a theory or hypothesis in a research setting.

Five steps in the process of empirical science

a) Experience – starting point of scientific elementary level

b) Classification – Data arrangementc) Quantification – analysis using mathematical

meansd) Discovery of relationships among phenomenone) Approximation to the truth – science proceeds

by gradual approximation to the truth.

What is Science

Static & dynamic view of science:Static – science is an activity that contributes

systematised information to the world.Scientist discover new knowledge and add to

existing knowledge. Science is thus seen as an accumulation of body of findings, the emphasis being chiefly on the present state of knowledge and adding to it. Dynamic view – takes the above plus discovery that scientist make.

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• Model implies Theory: Used interchangeably both are seen as explanatory devices or schemes having a broadly conceptual framework. Theory is provisional – does not cover everything – can be modified.

The Tools of Science

• Concepts and the hypothesis:1. Concepts: Express generalisation from

particulars e.g. Democracy, achievement, etc. Each one is a word representing an idea or concept. Concepts give meaning to the real world. Your ability to think and comprehend the world we live in depends on the command of concepts.

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2. Hypothesis – cause and effect or educated guess. If you have a problem form a hypothesis.

Hypotheses & concepts play a crucial part in the scientific method.

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3. Principle of parsimony – Explain in the economic way. Simple theory is to be preferred to a complex one.

4. Generality – start with observation of particular, the scientist generalize his findings to world at large.

The Scientific Method

• A scientific approach involves standards and procedures for demonstrating the empirical way and its findings. Standards and procedures are methods.

The Research Process and Procedure (Start of the process)

1. Definition of concepts method and methodology.

• A method is an instrument, tactic, for collecting data, solving problems and arriving at new knowledge information.

• Methodology is a strategy: a term often very loosely used in business to describe the way in which professions proceed in their analysis of a problem.

continue2. Research ProcessTo follow a certain acceptable research process

is important for your findings to be acceptable or valid. Accepted procedures should be followed, for example:

1. The formulation of the problem of study and deciding on the focus.

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• Before you start doing your research work, you need to be clear on:

Subject matter, background informationWhat is it that you would like to do i.e. Focus.• State the problem clearly. A clear and precise

formulation of the problem will assist you in later phases of the investigation.

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• Degree of clarity in formulating a problem depends on:

i. Complexity of the problemii. Amount of information already known about

the problem.

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2. Choice of Units and variables to be analyzed and confronted with data.

a. Unit of Analysisb. Variable of analysisExample:Problem of analysis “Income distribution among

workers in the agricultural sector.

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• We are interested in “workers in the agricultural sector”. Hence object of investigation is “workers in the agricultural sector” is the Unit of analysis.

• ‘Income distribution’ is the particular characteristic that we are interested in. Hence: the variable of our analysis.

• Workers (Fixed). Income received- variable.

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• The focal point of the study is always the unit of analysis.

3. Objective(s) or aim(s) of the study.Having stated the problem – the objectives of

your research should be clearly stated, should be achievable and not too many.

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4. Significance of the study to the society• Explain how your subject is useful or why it is

important that this subject should be studied.• Who has an interest in your research results• What do we know already about the topic.• How will this research add to practice, policy

and knowledge.

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5. Research Questions, HypothesisHypothesis statement:Hypothesis is a statement indicating a

relationship or its absence, between two or more of the chosen variables and stated in a way as to carry clear implication for testing. There are two types of hypotheses : a) Null hypothesis and Alternate. Null implies no relationship and this is what you are testing.

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Some ideas on the formulation of questions or hypothesis:

(1) It is important to choose an area that you know or are familiar with.

(2) Widen your experience (reading widely on your chosen subject to start with.

For example: If you are interested in agricultural finance of small farmers, also read about the large commercial farmers.

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• This will help in improving your questions/hypotheses.

(3) Brainstorm – to start with (i.e. How your questions or hypothesis should be stated)

(4) Do not allow a method/technique to lead you into deciding on your question(s)/hypotheses.

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5. The hypotheses should assist in choosing of an appropriate research strategy and method for your research.

6. Put emphasis on the statistical hypotheses, the Null form

7. Whatever, hypothesis you formulate, should be testable statistically. So be sure about the form of causality, positive or negative relationship of variables.

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8. Hypothesis should be brief and clear as to what is it to be tasted.

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9. Your hypothesis should clearly state the relationship between two or more variables that you intend to analyse.

10. You should have a reason based on general theory, why the hypothesis should be tested.

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11. On the basis of the research findings or evidence, the hypothesis is accepted or rejected, then link it with original problem objectives and questions.

12. Literature review , theory/previous studies._______________

Methodology (what strategy) and methods of data collection

• Research strategy refers to the general approach that you choose for your research.

• The traditional strategies used in collection of data include:

1. Case study2. Survey3. Experiments

Characteristics of a case study

• All case studies involve undertaking some applied Analysis

• Most case studies involve fieldwork• In most cases the material from a case study is

original

Characteristics of a Survey

• Surveys involve selection of samples and collection of data from a defined or known population. The format in surveys is standard.

• Surveys obtain data at a given point in time (cross-section), and the reasons for collecting data, vary, depending on the requirements of the investigation.

Characteristics of Experiments

The main features of experimental research strategy is that the researcher/or investigators changes or controls one variable and then observe the effect of the changes or controls one variable and then observe the effect of the changes on another variable of interest.

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• Example, take a sample from a known population and carry out the experiment by controlling certain variables and observe the reaction on the chosen sample.

Given a function: Y = Y(x); a change in value of ‘x’ and observe the effects of the change in value of ‘Y’.

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Call ‘x’ independent variable and ‘Y’ the dependent variable.

Response stimulusDependent variable Independent

variable At this stage of the research process mention

the (instrument(s) to be used to collect data.

Collection of data

Data is collected from a known populationa) ‘Censuses survey’ collect population datab) ‘Sample survey’ collect sample dataThe data is of two types the secondary data

which is already collected and documented and the primary data, which is a new data that the investigator collects

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• Recall the generality assumption, from the sample survey we generalise to the population from which the sample is drawn.

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Types of data

• Qualitative type: This kind of data or information is non-numerical. It assist the researcher in explaining the numerical data

• Quantitative data: This kind of data is in numerical form and can be used in statistical analysis.

Data Processing

The data collected need to be processed. There are many ways of processing data such as:

Classification of observationsCoding of observations – coding is the process

of assigning code values E.G. 385 -9, 311 to the various alternative answers to survey questions either when constructing the questionnaire (pre-coding) or after data collection (post-coding).

Discussion Issues

• Are assumptions necessary in Research? Discuss.

• Discuss the significance of all steps in a research process.

Data Processing

The data collected need to be processed. There are many ways of processing data, these include:

Classification of observations through;• Coding of observationsFor example:If female adult 02If male adult 01

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If female child 03If male child 04This is the kind of coding that can assist in

classification of data. Coding is usually done at the questionnaire or interview level.

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The researcher after fieldwork make notes or rearranges the data in a way that will be easy to analyse. The investigator may need to expand on the information collected, for example, data tape recorded need to be processed.

Analysis of data

The process of data analysis entail three activities:

• Data reduction (coding, etc)• Data display, i.e., display data in graphic

formats such as matrices, charts, figures, graphs and tables.

• Conclusion drawing/ verification

Dealing with data

• Scatter diagrams• Correlation Analysis• Regression Analysis (linear relationships)• Other statistical tests of hypotheses.

Data Interpretation

This stage of research process can be combined with data analysis. Data interpretation links the real world phenomena with the theory. It brings out the significance of the data

Statistical methods such as regression analysis using correlation are used.

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Regression analysis and significance of the relationship, should be supported (backed) by relationship derived from tables, simple two-way graphs. This will show if relationships are consistent with the theory.

Writing of Research Report

A good well presented report will be acceptable to examiners than a poorly presented one, but with good material.

• Use of your report:1) A project/ dissertation can be submitted for

you degree2) Part of it can be sent to professional journal3) You could produce a book

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4) Any other group that might be interested in your work could ask you to present or publish your work

_____Some of the things to note in your final report.In your final report mention the problems

experienced and the possible causes.

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• Review other surveys or finished and published reports

• The report should state the objectives of the project and the whole research process leading to the final conclusion

• Indicate your contribution to the subject or discipline. What is the importance of your results to the policy maker.

Conclusion (end of research process)

The conclusion sums up the research work touches on the main points and make the final statement about your research. It makes the reader to understand the purpose of the research. The conclusion should be brief and to the point.

Historical Research

Historical research deals with ex post information. Literature review in a scientific research could be viewed as historical.

Cohen & Manion (1990) define historical research as the systematic, and objective location, evaluation of evidence in order to establish facts and draw conclusions about past events.

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• In business and industrial sectors it is, perhaps, important to understand, the industrial history of a people. How did the present industrial set up come about. Historical research brings benefit to the sector and assist in solving some problems of historical nature. Helps in understanding between, for example, politics and industrial production or for example, the lack of factor of production such as capital.

Development Research

• Development research deals with descriptive research as opposed to experimental research. Descriptive research deals with what has occurred, while experimental research make things to happen. Most of the research and investigation in business and economics describes what has already happened.

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• The objective being to examine behaviour and choice of individuals, groups and institutions. In doing so the researcher describes contrast, classifies, analyses and interpret the events.

Three Types of Descriptive Research

1) Longitudinal 2) Cross – Sectional3) Trend or prediction4) The three types of research described

present relationships among variables and changes in relationships overtime.

Terminology of Developmental Research

Longitudinal – describe studies done overtime and deal with human development.

Example: From development economicsa. Traditionalb. Transitionalc. Take – offd. Maturitye. High Mass Consumption

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Another example: In marketing – Product life Cycle: Sales over Time

a) Development stageb) Introduction stagec) Growth staged) Maturity stagee) Decline stage

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In agriculture: Agricultural Development1. Traditional2. Feudal3. Commercial

Cross - Sectional

Different respondents are studied at the same time. There could be a series of these cross –sectional studies if the researcher wishes to compare. A cross –sectional study produces a Snapshot of a population at a chosen time, for example, national census of a group of enterprises.

Trend Study

Where selected factors are studied continuously, i.e., weekly, monthly or yearly, the term trend study is often used.

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SURVEYS

Surveys gather cross – sectional data, i.e. Data is obtained at a particular point in time with a view of:

a) Describing the nature of existing conditionsb) Identifying standards against which existing

conditions can be compared.c) Determining the relationships that exist

between specific events

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Large – scale or small – scale surveys all use similar data collection techniques. For example, structured or semi – structured interviews, self – completing or postal questionnaires. There are no limits to cases covered by surveys.

Survey Preliminary studies (Plan)

The planning of survey is a combination of technical and organizational decision.

Questions to ask• What population coverage to aim at?• What information to seek?• How to go about collecting this information?• How to process and interpret results?

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Sample design (methodology) decided in the light of:• What is practically feasible• What is theoretically desirable• Accuracy of results• Cost, time and labour involved• Type of sampling• Type of data collection• Methods of tabulation• Miscellaneous items

Preliminary plan of a survey

1. Statement on: Objective(s) or purpose of the enquiry.

• Clear statement in detail• Methods to be used• Why the survey, what questions it will cover

or answer• What results expected• How the information will be used.

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2. Population• Define population targeted• Geographical, etc• Covered fully or partially• Method of selecting respondents• Sample in a statistical sense• Sample frame list

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Sample frame: A listing that should include all those in the population to be sampled and exclude all those who are not in the population.

• How will you deal with non-response• Follow up approach

Collection of Data

• The collection of data will depend on the size of survey

QuestionnairesPlan how to structure and phrase your

questionnaires.ErrorsEvery stage of survey can lead to errors or errors

are made.

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For example:• Sampling error• Interviewing• Questions• Editing• Coding• TabulationAnticipate likely sources of error and size.

Fieldwork

• Central stage of survey and will depend on the quality of interviews.

Processing & Analysis• Questionnaire – check on : Omissions• Statistical Calculation• Editing scheme is necessary• Tabulation plan• Method of analysis

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Timing & Cost• Timing of investigation• No holidays etc.• When are the results needed• Estimate Cost

Pre-test and Pilot Survey

• To find out the re-action of people to your questionnaires or interviews

• Pilot survey – a small scale replica of the main survey

Pilot Study Provides:

1) Adequacy of the sampling frame2) Variability within the population to be

surveyed3) Non-response rate to be expected4) Suitability of data collection methods5) Are the questions adequate: ease of

questions, layout, similarities, clarity, do the answers meet your objectives.

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6) Are instruments clear7) Codes – for pre- coded questions are they

clear to you.8) Cost and time spent – and how well are you

organized in the field.9) Approach to the respondents10)After pilot – Improve on your plan.

Survey Sampling Design

Type of sample DesignBias is one of the sampling problem that an

investigator may encounter.• For a given sample design, the estimator is the

method of estimating the population parameter from the sample.

Estimator: Is the sample arithmetic mean

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• Example: E(b) hat estimator of the population parameter “ b”.

• Bias• E(b) hat = b ; implies unbiased estimator of ‘b’• E(b) hat b; implies biased estimator of

‘b’

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• For any sample design if the expected value of the estimator is equal to the population parameter then estimator is unbiased if not equal to population parameter, it is biased.

• The difference between the expected value and the true population value is termed the bias.

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• Bias = (‘b’ hat) – b• Bias: The tendency for some extraneous

factors to affect the answers to survey questions or the survey results in general, in a systematic way, so that results are “pushed” or “pulled” in some specific direction.

Decision Errors

• Generally the purpose of statistical inference is to make an educated guess about what exists in the population when only a small subset of cases from the population has been studied. Since the decision is a guess, it might be wrong.

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• Type 1 error occurs when a null hypothesis is rejected when it is in fact true.

• Type 11 error occurs when the null hypothesis is accepted when it is, in fact false.

• Given the validity of the null hypothesis, the probability that it is erroneously rejected by

these procedures equals, α , the significance level.

Causes of Bias

Three factor that might cause bias include:1) Non – random method(s) used to select a

sample, in such cases there is a likelihood of subjectivity.

2) Incomplete or inaccurate sampling Frame from which a sample is selected.

3) Non – response of those included in the sample –which mean the sample will not be representative of the population.

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• Bias through sampling method can be avoided by using random method

• A good sampling design should use a random method. Note that there are two main types of sampling: random or probability sampling and non-probability sampling.

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• In general, a random or probability method of choosing a sample is defined as that which allow each of the members of the targeted population a calculable probability of being included in the sample.

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a) Unrestricted Random Sampling: Give an equal chance to every member of the population of being selected. However, in unrestricted random sampling the investigator has to replace the members selected. Hence, unrestricted random sampling, is sampling with replacement. It is therefore, likely that a member may be selected more than once.

Simple Random Probability Sampling

• The simple random sampling is done without replacement. Subsequently, no member can be selected more than once in any given sample. In a simple random probability sampling each member of the population has a chance of being included in the sample.

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Examples of Simple Random Sampling1) Tickets mixed in a basket pick one this

represent a simple random sampling.2) Pick every nth member of the population,

this represents a simple random sampling

Methods of Ensuring Randomness in Selection of Survey Samples

1) Lottery Method:Number the population and represent

it with marked balls: 1 to nPlace the balls in a wheel or something

that mixes- then select required sample.

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2) Use random numbers (table):Population numbered: 1 to Z; then sample

members are selected from the table in a systematic fashion.

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• In practice use random numbers:Example. Handout (tables) Random tableDraw a sample of size 10 from 100 small scale

businesses.Get a list of Business you want to investigate

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1. Set the three digit numbers:001, 002, 003, 004, .......010, 099-1002. Go to Random tables3. Along the column choose a number in digits

of three below 101 until you get your sample4. Jump the repeat numbers.

SYSTEMATIC SAMPLING

Another method of sampling: Suppose you have 6000 small scale businesses and you want a sample of 300

300/6000 = 1/201 – 20 pick any number at random between 1 –

20 and then every firm after 20th is picked. • This is not a simple random sampling because

originally the 6000 were not randomly picked and 1 – 20 is not randomly picked.

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• The difference between the simple random sampling and systematic sampling is that in the systematic sampling the members are not given equal chance of being included in the sample. Once you pick the first number the others are picked systematically or follow.

STRATISFIED RANDOM SAMPLING

In a stratified random sampling the population is divided into groups or strata.

For example:• Small scale firms (Businesses)• Middle scale firms (Businesses)• Large scale firms (Businesses)The random sampling then take place

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Within the stratum.• Stratified random sampling with a uniform

sampling fraction tends to have greater precision than simple random sampling. Because of the small size of the stratum.

Proportionate stratified Sample Design

• In stratified sampling we do not require that the sampling fraction be the same or uniform for each stratum. But whenever the sampling fraction is the same for each stratum, we refer to this as a proportionate stratified sampling.

Cluster Sampling

The cluster Sampling is ideal when the population is large and widely dispersed. The researcher avoids long distance and at the same time affords adequate information in order to generalize to the rest on the population.

In a cluster sampling the population is divided into cluster or groups. The cluster units are chosen at a random.

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Multi-Stage Sampling• the use of multi-stage cuts down on cost.• Studies of very large population, such as a

whole country, usually involve multi-stage sampling. Multi-stage sampling are an extension of cluster sampling. The samples are selected in stages. It implies taking samples from samples. The sampling is done at random.

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Example 1.Stage 1 10 Industrial AreasStage 2 100 Firms from the areasStage 3 10 specific FirmsExample 2.Provinces Y Districts Y villages or towns Yindividuals

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Example 3.No of Schools Y No of classes Y No of pupils

Non-Probability Sampling

Non-probability sampling it is frequently used in practice in spite of its limitations.

• Convenience and lower costs per case are its chief advantages

• Common statistical techniques which assume a random sample should not be used in non-probability samples

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The main types of non-probability sampling are:1. Convenience or Accidental, 2. Quota, 3.

Purposive, 4. Dimensional, 5. Snow ball sampling

Convenience Sampling

This kind of sampling chooses individuals who are near and these then constitute the respondents. For example, firms near to the researcher can be chosen and form the required sample.

Quota Sampling

It is similar to stratified sampling. But in Quota sampling respondents are not randomly chosen. In a Quota sampling, a population is divided into a Quota which in the case of firms it could be small-scale and large –scale firms a quota for each group could then be chosen

Purposive Sampling

The researcher picks the respondents to be included in the sample, using his/her judgement as to which respondents to be included.

Dimensional Sampling

This is an extension of Quota sampling it involves studying the population and knowing the composition of the population. The researcher then includes in the sample all factors of the population. Within a group you might want to know certain attributes and attitudes. It is the differences within the group.

Snowball Sampling

The researcher knows the characteristics required. On a small group the researcher then use this group as a representative and to help the researcher to get or identify others to be included in the sample, in turn, these people lead the researcher to others, until the required sample is obtained.

Tutorial Question

• Discuss the advantages and disadvantages of random probability sampling and non-probability sampling for each sampling method discussed in class.

CASE STUDY

Case studies are based on observation of the characteristics of the phenomenon or individual unit to be studied or researched. For example, a firm, a specific project, a community. These cases are not chosen through a formal sampling process, but by judgemental and a typical relevant case is chosen. The aim of a case study is to do an in-depth analysis of the unit. From the study of the unit generalization is established for the population from which the unit is drawn.

Types of observation: case study

• Participant observation: In a participant observation the researcher (observer) takes part in the activity required to be observed.

• For example, join the business for one year or work in a project that you wish to study. Join the community or firm in order to get an insight of the organization.

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• Although observation is the main methodological strategy, various research instruments or methods of collecting information or data are used, depending on whichever is appropriate, for example; interviews, questionnaires.

TUTORIAL WORK

1. A researcher (enumerator) used a single questionnaire for both smallholder farmers in an estimation of agricultural production. Comment on the use of the instrument in the exercise.

2. Discuss the significance of inductive and deductive reasoning in the development of a scientific research method?

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3. Briefly mention and discuss three kinds of bias related to sampling design.

4. Explain in detail giving examples the assumption of Epistemology and methodology in the nature for social sciences.