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It is a framework or plan or Blueprint developed to control the collection of data is called research design.

Research design is an absolute essentiality in research irrespective of the type of research (e.g., exploratory or descriptive), as it ensures that the data collected is appropriate, economical and accurate.

RESEARCH DESIGN

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A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to research purpose with economy in procedure.

A research design is a conceptual structure within which research is conducted; it constitutes the blue print for the collection, measurement and analysis of data.Meaning

An activity and time based plan.

A plan always based on the research question.

A guide for selecting sources and types of information.

A framework for specifying the relationship among the studys variable.

A procedural outline for every research activity.

What is the study about?

Why is the study being made?

Where will the study be carried out?

What type of data is required?

Where can the required data be found?

What time period the study includes?

What will be the sample design?

What techniques of data collection to be used?

How will the data be analyzed?

In what style the report be prepared?Components of research design

It is a plan that specifies the sources and types of information relevant to the research problem.

It is a strategy specifying which approach will be used for gathering and analyzing the data.

It includes the time and cost budget since most studies are done under these two constraints.

important features of research design

Research design must, contain

A clear statement of the research problem;

Procedures and techniques to be used for gathering information;

The population to be studied; and

Methods to be used in processing and

Analyzing data. important features of research design

Research Design is needed because it facilitates the smooth sailing of the various research operations, thereby making research as efficient as possible yielding maximal information with minimal expenditure of effort, time and money.

Need for research design

It stands for advance planning of the methods in collecting relevant data and techniques to be used in their analysis, keeping in view the objective of the research and the availability of staff, time and money.

The design helps the researcher to organize his ideas in a form whereby it will be possible for him to look for flaws and inadequacies.Need for research design

FEATURES OF GOOD DESIGNA good design is often characterized by flexible, appropriate, efficient and economical. The design which minimizes bias and maximizes the reliability of the data collected and analyzed is considered a good design. The design which gives the smallest experimental error is supposed to be the best design in many investigations. A research design which yields maximal information and provides an opportunity for considering many different aspects of a problem is considered most appropriate and efficient design in respect of many research problems.The question of good design is related to the purpose or objective of the research problem and also with the nature of the problem to be studied.One single design cannot serve the purpose of all types of research problems.

VARIABLES

A concept which can take on different quantitative values is called variables. As such concepts like weight, height, income are all examples of variables.

Continuous Variables - Age is an example Non Continuous Variables - Number of children Dependent & Independent VariablesEg. For instance height depends upon age, then Height is a dependant variable and Age is an independent variable.

The Independent Variable (IV) is the causal variable The Dependent Variable (DV) is the effect variable

Extraneous VariablesIndependent variables that are not related to the purpose of the study, but may affect the dependant variable are termed as extraneous variable.

Multiple VariablesYou are interested in finding out which color, type, and smell of flowers are preferred by butterflies for pollination. Control

Basic Research Objectives and Research Design

To gain background information, to define terms, to clarify problems and develop hypotheses, to establish research priorities, to develop questions to be answered- ExploratoryTo describe and measure marketing phenomena at a point in time- DescriptiveTo determine causality, test hypotheses, to make if-then statements, to answer questions-Causal

Types of Research Design

Exploratory Research Design

Exploratory research is conducted to explore a problem at its preliminary stage, to get some basic idea about the solution at preliminary stage of a research study.

It is most commonly unstructured, informal research i.e. undertaken to gain background information about the general nature of the research problem.

The major purpose of exploratory research to identify the problem more specifically.

Exploratory study is used in the initial stages of research.

In the early stage of research, we usually lack from sufficient understanding of the problem to formulate a specific hypothesis. Further, there are often several tentative explanations.

Example: Sales are down because our prices are too high, our dealers or sales representatives are not doing a good job, Our advertisement is weak and so on. In this scenario, very little information is available to point out, what is the actual cause of the problem.

Under what circumstances is exploratory study ideal?

To gain an insight into the problemTo generate new product ideasTo list all possibilities. Among the several possibilities, we need to prioritize the possibilities which seem likely.To develop hypothesis occasionally.To establish priorities so that further research can be conducted.To pre-test a draft questionnaire.

Example, a shirt manufacturer sponsored a survey to find the percentage of executives purchasing different sizes a shirt. The researcher was asked to record the sizes 36, 38, 40, 42, 44 as indicated by the executives. The exploratory survey indicated that quite a good percentage of executives indicated the size as 39 and 41 (which were either imported or tailor made). This information led to change the questionnaire to include these options.

Exploratory Research Methods

Literature SearchThis refers to referring to a literature to develop a new hypothesis. The literature referred are trade journals, professional journals, market research finding publications, statistical publications etc.

Example: Suppose a problem is Why are sales down? This can quickly be analysed with the help of published data which should indicate whether the problem is an industry problem or a firm problem. Three possibilities exist to formulate the hypothesis.

The companys market share has declined but industrys figures are normal.The industry is declining and hence the companys market share is also declining.The industrys share is going up but the companys share is declining.

Experience survey An exploratory research technique in which individuals who are knowledgeable about particular research problem are surveyed.When we interview persons in an experience survey, we should seek their ideas about important issues or aspects of the subject and discover what is important across the subjects range of knowledge.

What is being done?What has been tried in the past without success?How have things changed?What problems areas and barriers can be seen?Who is involved in decisions and what roles does person play?

Focus groupMost widely used technique.

In a focus group, a small number of individuals are brought together to study and talk about some topic of interest.

The discussion is co-ordinated by a moderator.

The group usually is of 8-12 persons.

While selecting these persons, care to be taken to see that they should have a common background and have similar experiences in buying.

This is required because there should not be a conflict among the group members on the common issues that are being discussed.

Focus groups should be taped (audio) or videoed. Videoing can be more difficult and intrusive but is often worthwhile.

Permission of the participants should always be sought for taping/ videoing.

The following should be the characteristics of a moderator/ facilitator: ListeningMemoryEncouragementLearningSensitivityIntelligenceKindly firm

Case studiesAnalyzing a selected case sometimes gives an insight into the problem which is being researched.

Case histories of companies which have undergone a similar situation may be available.

These studies are well studied to carry out exploratory research. However the result of investigation of case histories are always considered suggestive, rather than conclusive.

CONCLUSIVE RESEARCHThis is a research having clearly defined objectives.

In this type of research, specific courses of action are taken to solve the problem.

Conclusive research are of two types.

Descriptive researchIt concerned with describing the characteristics of a particular individual , group , frequency of occurrence.

Researcher must able to define clearly, what he wants to measure and must find adequate methods for measuring it along with the clear cut definition of population

Descriptive research is undertaken to provide answers to questions of who, what, where, when, why and how.

Descriptive research studies are those studies which are concerned with describing the characteristics of a particular individual, or a group.

When to use descriptive study?

To determine the characteristics of market such asSize of the marketBuying power of the consumerProducing usage patternTo find out the market share for the productTo track the performance of a brandTo determine the association of the two variable such as Ad and salesTo make a prediction. We might be interested in sales forecasting for the next three years, so that we can plan for training of new sales representatives.To estimate the proportion of people in a specific population, who behave in a particular way? Example: What percentage of population in a particular geographical location would be shopping in a particular shop?

Adjective typifying the researchIllustrative questionWhoWho has been most consistent batsman among Sachin, Dravid and Ganguly in the test matches?WhichWhich is the cricket ground where maximum number of centuries have been scored?Which are the companies that have declared more than 50% dividend for the year 2010-2011?WhatWhat is the average salary offered to MBA students with marketing specialisation? WhereWhere the responses to a particular advertisement were most favourable, among all the major cities where the test marketing was carried out?WhenWhen did the manufacturing process go out of controlHow (Much, Many)How much productivity increased in an organisation after a training to the employees?How many Mutual funds have paid more than 10% dividend for their Tax Saver Scheme.

Longitudinal study

These are the studies in which an event or occurrence is measured again and again over a period of time.

This is also known as Time Series Study. Through longitudinal study, the researcher comes to know how the market changes over time.Longitudinal studies are quite poplar in social and behavioural sciences, socio economic research, banking and finance etc.

Examples areExperiment pattern over a period of time of an individual or group of individuals. R& D Expenditure by a sector of companies like pharmaceuticals etc.

Quality of Life parameters of a state or a country.Longitudinal research relies on panel data and panel methods.

It involves fixing a panel consisting of fixed sample of subjects that are measured repeatedly.

The panel members are those who have agreed to provide information at a specific interval over an extended period.

For example, data obtained from panels formed to provide information on market shares are based on an extended period of time, but also allow the researcher to examine changes in market share over time. New members may be included in the panel as an when there is a dropout of the existing members or to maintain representativeness.

Two types of panel are

Advantages of Longitudinal studies

Discover trends and patterns of change

Locate the times when the trend or pattern changed - it might lead to investigating the factors that cased the change.

Cross sectional studyThese are the studies that are conducted over a group of companies or organizations over the same point of time. Such research makes observations at one and the same point of time for all the entities under study.

Example: Placement offers to MBA students of 2011 batch at all IIMs.P/E ratio of all automobiles companies as on 31st March 2012Conducting opinion poll on a particular day

The major advantage of cross-sectional research is that data can be collected on many entities of different kinds in a short span of time. Since the data is collected at one point of time, it can be easily collected at LOWER COST.

Cross sectional study is that it is cheaper and faster to conduct such a study. The main disadvantage of such study is that it reveals little as how to how the changes occur. Cross sectional design may be either single or multiple cross sectional design depending on the number of samples drawn from a population.

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.

EXPERIMENTAL RESEARCH OR CASUAL RESEARCH

The casual research is concerned with finding the root cause of a symptom.

For example, if the sale of a product is declining, or if customers prefer a product over other similar product(s), one may like to know the cause(s) for the same.

Thus, this type of study encompasses situations where we study the impact or influence of one factor (cause) on some other factor (effect). The influencing factors could be one or more than one.

Some of the examples of casual research are

The factors influencing buying behaviour of customers.

The factors influencing the motivating of an employee.Advertising expenses is the cause (called independent variable) and

Sales (called dependent variable) is the effect.Casual variables is also called explanatory variable as it explains the effect or impact on the dependent variable.

Experimental ResearchAn experiment is defined as manipulating (changing values/situations) one or more independent variables to see how the dependent variable(s) is/are affected, while also controlling the affects of additional extraneous variables.

Independent variables: those over which the researcher has control and wishes to manipulate i.e. package size, ad copy, price.

Dependent variables: those over which the researcher has little to no direct control, but has a strong interest in testing i.e. sales, profit, market share.

Extraneous variables: those that may effect a dependent variable but are not independent variables.

TYPES OF EXPERIMENTS

Basic principles of experimental designs

The principle of Replication

The principle of Randomization

The Principle of Local control

Types of Experiment Research Design

VALIDITY OF RESEARCH DESIGN

Validity refers to the strength and the accuracy of a research design. Two types of validity in a research design viz.

Internal Validity

Internal validity describes the ability of the research design to unambiguously (clearly) test the research hypothesis. Internal validity refers to the extent to which one can accurately state that the independent variable is responsible for the observed effect in the dependent variable and no other variable is responsible for the effect.

If the effect on dependent variable is only due to variation in the independent variable, then we may conclude that the internal validity is achieved.

Threats of internal validity

History

History refers to the events that are beyond the control of the experiment.

These events may change the attitude of the respondents irrespective of whether the independent variable is changed or not.

Thus it is impossible to determine whether any change on the dependent variable is due to the independent variable or the historical event.

Maturation

History refers to the events that are beyond the control of the experiment.

These events may change the attitude of the respondents irrespective of whether the independent variable is changed or not.

Thus it is impossible to determine whether any change on the dependent variable is due to the independent variable or the historical event.

Testing

Repeatedly measuring the participants may lead to bias. Participants may remember the correct answers or may be conditioned to know that they are being tested.

Selection of respondentsThe inappropriate selection of respondents may lead to bias in experiemental design. If the selected respondents are not uniform, inadvertent randomization may take place leading to bias.Statistical regressionThe statistical regression refers to the bias that may crop in due to some respondents giving extreme responses. This bias is known as error sum of squares in statistical regression analysis.

Experimental MortalityThis can occur when the respondents drop out during the experiment especially in the experiment involving pre test and post test. The same respondents who take up the pre-test may not be available for the post-test. This results in excluding the entire pre test data from the analysis dropped out respondents.

Instrument change (instrumentality)

The instrument used during the testing process can change the experiment. This also refers to observers being more concentrated or primed, or having unconsciously changed the criteria they use to make judgments.

EXTERNAL VALIDITY

External validity is related to generalisability of the findings/results. It refers to the degree of generalisability of the conclusions to other situations.

In other words, external validity is the degree to which the conclusions in the study for a given population could be made applicable to other populations or other situations.

Meaning A business research study, involves study of characteristics of an individual/item/unit entity etc. These characteristics are represented by variables.

As the name suggests a variable changes values for different individual/item at the same time Example: Income of individuals for the year 2009-10, prices of stocks on a day) or for the same individual/item at different time (income for an individual, sales of a company).VARIABLES IN RESEARCH

Independent variable

Dependent variable

Moderating variable

Intervening variable

Extraneous variable

Continuous variable

Non-continuous/Discrete variableTYPES OF VARIABLES

The process of assigning numbers to objects or observations, the level of measurement being a function of the rules under which the numbers are assigned.

It is easy to assign numbers in respect of properties of some objects, but it is relatively difficult in respect of others. For instance, measuring such things as social conformity, intelligence, or marital adjustment is much less obvious and requires much closer attention than measuring physical weight, biological age or a persons financial assets. MEASUREMENT AND SCALING TECHNIQUES

In other words, properties like weight, height, etc., can be measured directly with some standard unit of measurement, but it is not that easy to measure properties like motivation to succeed, ability to stand stress and the like.MEASUREMENT AND SCALING TECHNIQUES

Measurement Scales

A qualitative scale without order is called nominal scale.

Nominal scale is the least powerful level of measurement.

It indicates no order or distance relationship and has no arithmetic origin.

A nominal scale simply describes differences between things by assigning them to categories.

Nominal data are, thus, counted data.Nominal scale

In research activities a YES/NO scale is nominal.

It has no order and there is no distance between YES and NO.

The statistics which can be used with nominal scales are in the non-parametric group.

ModeCross tabulation - with chi-square

Nominal scale

Example: The terms we use for colours. The colour of bike is a nominal measure. Which colour will you prefer for a bike? could be blue, black, red, etc. One may number these colours as 1, 2, 3 etc in any sequence i.e. this scale neither has any specific order nor it has any value.

Ordinal ScaleWith ordinal scales, it is the order of the values is whats important and significant, but the differences between each one is not really known.

Like in a competition. A qualitative scale with order is called an ordinal scale. This scale posses the properties of distinctive classification and order.

Ordinal Scale Rank as a measure is always considered as ordinal.

The difference between any two ranks is not necessarily equal. The difference between first and second rank does not connote the same differential.

For example in a class of students, the highest mark is 95, next highest is 85 and the next is 84, converting marks into ranks will lead to 1, 2 and 3.

Incidentally, it may be noted that the difference in the performance of the 1st ranker and 2nd ranker is not the same as the 2nd ranker and 3rd ranker.

Statistics tool applied in Ordinal scale Ordinal data would use non-parametric statistics. These would include:

Median and mode

Rank order correlation

Non-parametric analysis of variance

Modelling techniques can also be used with ordinal data.

Interval ScaleInterval scales are numeric scales in which we know not only the order, but also the exact differences between the values.

The classic example of an interval scale isCelsiustemperature because the difference between each value is the same. For example, the difference between 60 and 50 degrees is a measurable 10 degrees, as is the difference between 80 and 70 degrees. Time is another good example of an interval scale in which theincrementsare known, consistent, and measurable.

Central tendencycan be measured by mode, median, or mean; standard deviation can also be calculated.This is a quantitative scale of measure without a fixed or true zero. For example, there is no such thing as no temperature.

Without a true zero, it is impossible to compute ratios. With interval data, we can add and subtract, but cannot multiply or divide. Confused? Ok, consider this: 10 degrees + 10 degrees = 20 degrees. No problem there. 20 degrees is not twice as hot as 10 degrees, however, because there is no such thing as no temperature when it comes to the Celsius scale.

When you are asked to rate your satisfaction with a piece of software on a 5 point scale, from Dissatisfied to Satisfied, you are using an interval scale.

Statistical tools Interval scale data would use parametric statistical techniques:

Mean and standard deviationCorrelation rRegression

Analysis of varianceFactor analysisAdvanced multivariate and modelling techniques.

Ratio scalesRatio scales have an absolute or true zero of measurement. We can conceive of an absolute zero of length and absolute zero of time.

Ratio scales represents the actual amount of variables. Measures of physical dimensions such as height, weight, distance etc are examples.

All statistical techniques are usable with ratio scales.

Multiplication and division can be used with this scale but not with other scales.

Geometric and Harmonic means can be used as measure of central tendency and coefficients of variation also be calculated.

Scaling

Scaling has been defined as a procedure for the assignment of numbers (or other symbols) to a property of objects in order to impart some of the characteristics of numbers to the properties in question.

The number assigning procedures or the scaling procedures may be broadly classified on one or more of the following bases: (a) Subject orientation; (b) Response form; (c) Degree of subjectivity; (d) Scale properties; (e) Number of dimensions and (f) Scale construction techniques.

Selection or construction of a measurement scale requires decision in the following six key areas:

Study objective

Response form

Degree of preference

Data properties

Number of Dimensions

Scale construction

Construction of measurement scales

Arbitrary scales are developed on ad hoc (unplanned) basis. It is largely based on researchers own subjective selection of items. Several items, which are appropriate and unambiguous to the theme of study, may be selected.

Each item is scored from 1 to 5 depending on the responses obtained. The results are then totaled.

Arbitrary scales are easy to develop, inexpensive and highly specific to the theme of the study.

The major limitation is that the design approach is subjective.Arbitrary scales

In consensus scale the items are selected by a panel of judges after evaluation on the basis of some criteria like

Relevance to the topic area

The risk of ambiguity and

The level of attitude represented by the items.Consensus Scaling

This scale is rarely used for measuring Organizational concepts - because of time.

One of Consensus scale is The Thurstone Equal Appearing Interval Scale by using a pile of cardConsensus Scaling

This approach is widely known asThurstonequal appearing Interval Scale. The procedure followed in construction of the scale is described belowStep: 1 A large number of items/statements expressing different degree of favorableness towards an object relating to the subject of the study, usually more than twenty are collected by the researcher.

Step: 2 A panel of judges evaluates the statements. The statements are written in the card.

Step: 3 The judges sort each card into one of the 11 piles representing the degree of favorableness the statement expresses.

Step: 4 The sorting yields a composite position for each of the items. In case of disagreement between the judges the item is discarded.Step: 5 For the items that are retained median scale value between one and eleven is assigned.Step: 6 A final selection of statements is made on the basis of the median score. Of the 11 piles 3 are identified by the judges as favourable , unfavourable and neutral. The eight intermediate piles are unlabelled.

Theitemized rating scaleis a 5 point or 7 point scale with anchors provided for each item and the respondent states the appropriate number on the side of each item or circles the relevant number against each item. The responses to the items are then summated.This uses an interval scale. Example is shown below; indicate your response number on the line for each item.1234 5Very Unlikely UnlikelyNeither UnlikelyLikely Very Likely nor likelyItem Analysis scaling

I like to take more responsibility -----

If additional responsibility is not provided I will be dissatisfied -----I am interested in a job which provides me more salary -----

Step :1 Discriminates between those persons whose score is high and those whose total score is low. Step :2 It involves calculating the mean score for each scale item among the low scorers and high scorers. The item means between the high-score group and the low-score group are then tested for significance by calculatingtvalues.Step :3 Finally the items that have the greatesttvalues are selected for inclusion in the final scales.Item Analysis scaling

Summated scales consist of a number of statements which express either favourable or unfavourable attitude towards an object to which the respondents is required to react. The respondents indicate the agreement or disagreement with each of the statement.

Each response is given a numerical score and the total is obtained to measure the respondents attitude. Summated scales or Likert scalesare developed by the item analysis approach.

Procedure for developing a Likert type scale

A large number of statements relevant to the object being studied is collected.

The statement expresses definite favourableness or unfavourableness towards the subject.

A trial test can be conducted with a small group of respondents who form part of the final study. The agreement or disagreement towards each statement is obtained on a five-point scale.

The response is scored in such a way that the response indicating the most favorable attitude is given the highest score of 5 and the most unfavorable attitude is given the lowest score 1.

5. The total score of each respondent is obtained by adding the score for each individual statement.6. The next step is to array the total scores and find out those statements, which have a high discriminatory power. For this purpose the researcher may select some part of the highest and the lowest total scores, for eg, top 25 percent and bottom 25 percent.

7. These two extreme groups are interpreted to represent the most favourable and the least favourable attitudes and are used as criterion groups by which to evaluate individual statements.

Thus the statements, which consistently correlate with low favourability and with high favorability, are identified.

Advantages of Likert scale

It is relatively easy to construct, considered to be more reliable and less time consuming.

Disadvantages of Likert scale

One of the major limitations is that the scale simply examine whether respondents are more or less favourable towards the subject under study, but it cannot reveal how much more or less they are.

There is no basis for belief that the five positions indicated on the scale are equally spaced.

Cumulative scales consist of series of statements to which a respondent expresses his agreement or disagreement. An individual whose attitude is at a certain point in a cumulative scale will answer favourably all the items on one side of this point and answer unfavourably all the items on the other side of this point.

The individuals score is arrived at by counting the number of points concerning the number of statements answered favourably.

Cumulative scales

If the total score is known it is easy to estimate the respondent does answer to individual statements constitute the cumulative scales.

A major scale of this type is the Guttmans scalogram.Scalogram analysisrefers to the procedure for determining whether a set of items forms a one-dimensional scale.

A scale is one dimensional if the responses fall into a pattern in which endorsement of the item reflecting the extreme position results also in endorsing all items, which are less extreme.

Factor scales includes a variety of techniques that been developed to address two issues viz, the problem of dealing with the universe of content that is multi dimensional and the problem of uncovering the underlying dimensions that has not been identified by the exploratory research.

Factor scales are developed through factor analysis or on the basis of inter correlations of items, which indicate the common factor responsible for the relationships between items.

Factor scales

Semantic Differential Scale

Multidimensional scaling (MDS)

Different types of factor analysis

Semantic Differential Scale

Developed by Charles E.Osgood, G.J. Suchi and P.H. Tannenbaum (1957),

It is an attempt to measure the psychological meanings of an object to an individual.

This scale is based on the presumption that an object can have different dimensions of connotative meanings which can be located in multidimensional space.

This scaling consists of a set of bipolar rating scales, usually of 7 points, by which one or more respondents rate one or more concepts on each scale item.

3210-3-2-1(E) SuccessfulUn Successful(P) SevereLenient(P) Heavy (A) Hot(E) Progressive(P) Strong(A) ActiveLightCold RegressiveWeakPassiveFor instances, the S.D scale items for analyzing candidates for leadership position May be shown as under:

Candidates for leadership position may be compared and score them from -3 to +3 on the basis of the above stated scales. The letters E,P, A stands for

E EvaluationP PotencyA Activity

Written along the left side are not written in actual scale. The numeric values shown are also not written in actual scale.

Osgood and others conclude that Semantic space is multidimensional rather than unidimensional.

The semantic differential has several advantages. It produces interval data. It is an efficient and easy way to elicit responses from a large sample.The attitudes can be measured both in terms of direction and intensity. The total set of responses provides a comprehensive picture of the meaning of an object. It is a standardized technique which can be easily repeated and at the same time escapes many problems of response distortion.

Multidimensional scaling

Multidimensional scaling is relatively more complicated scaling device which can be used to scale objects, individuals or both with a minimum of information.It enables to provide visual impression of the relationship between variables.

The MDS enables the researcher to study the perceptual structure of a set of stimuli and the cognitive process underlying the development of this structure.

It enables perceptual mapping in a multidimensional space.

Multidimensional scaling

For example if respondents are asked to identify similar products among a group of products and if product X and Y are similar,MDS technique will position X and Y in such a way that the distance between them in multidimensional space is shorter than that between any two other objects.

However MDS is not widely used because of the computational complications involved.

Validity and Reliability of an instrument or TESTS OF SOUND MEASUREMENT

Test of Validity

Content validity; Criterion-related validity and Construct validity.

Test of Reliability

3. Test of Practicality