Business Research Methods (MBA-II-AKU)

 

RESEARCH

Research in simple terms refers to search for knowledge. It is a scientific and systematic search for information on a particular topic or issue. It is also known as the art of scientific investigation.

According to Redman and Mory define research as a,” Systematized effort to gain new knowledge”. Some people consider research as a movement, a movement from the known to the unknown.

According to Clifford woody, research comprises defining and redefining problems, formulating hypothesis or suggested solutions collecting, organizing and evaluating data, making deductions and reaching conclusions; to determine whether they fit the formulating hypothesis.

 

OBJECTIVES OF RESEARCH

• To understand clearly an observed phenomenon and explain its logic and reason for happening.

• To get insights about the problem.

• To find solutions for a problem.

• To test existing laws or theories.

• To develop new ideas, concepts and theories.

• To test hypothesis of a causal relationship between variables.

 

NATURE OF RESERCH

• It strives to be objective and logical.

• It is based on observable experience or empirical evidence.

• It is characterized by patient and unhurried activity.

• It demands accurate observations, reservations and descriptions.

• It is directed towards the solution of the problem.

• It is carefully recorded and reported.

• It requires expertise.

• It involves gathering new data from primary or first-hand sources or using existing data for new purpose.

 

FEATURES OF RESEARCH

• It means the discovery of new knowledge

• Is essentially an investigation

• Is related with the solution of a problem

• It is based on observation or experimental evidences.

• It demands accurate observation or experimentation.

• In research, the researchers try to find out answers for unsolved questions

• It should be carefully recorded and reported

 

SCOPE OF RESEARCH

 

QUALITIES OF A GOOD RESEARCH

1.     Method of Approach: The researcher should adopt the correct course of action for identifying a problem and then for working on it, to find a solution for that problem.

2.     Knowledge: The researcher should have complete knowledge and information about the field of investigation so that he can go in for correct planning and then application of the correct and efficient methods for selection of the problem and then for solving it.

3.     Qualification: The researcher should have a good background of study, which will facilitate the researcher to have a better knowledge and understanding of the subject.

4.     Motivation: The researcher must be motivated to perform his work. For that, he should have a proper attitude, vision of his own, and an aim with some objectives to achieve something.

5.     Perseverance: Perseverance means to carry on work strongly even though there are certain problems and difficulties in carrying out the work. As a result, researcher should be stable and must have consistent thinking.

6.     Communication Skills: Good Communication skills are required by researcher as he can interact with respondents efficiently and understand their opinions.

7.     Organizational Skills: Researcher should use time management techniques so that work can be completed on time. Whereas maintaining budget, keeping records, filing necessary documents, keeping paper cuttings is needed to carry on work successfully

 

BUSINESS RESEARCH

Business research refers to systematic collection and analysis of data with the purpose of finding answers to problems facing management.

It can be carried out with the objective to explore, to describe or to diagnose a phenomenon. It involves establishing objectives and gathering relevant information to obtain the answer to a business issue and it can be conducted to answer a business-related question, such as: What is the target market of my product? Business research can also be used to solve a business-related problem, such as determining how to decrease the amount of excess inventory on hand.

 

SOCIAL RESEARCH

Social research refers to research conducted by social scientists. It is the scientific investigation conducted in the field of social sciences and also in the behavioral sciences. Social research methods can generally vary along a quantitative/qualitative dimension.

The social science research is a systematic method of exploring, analyzing and conceptualizing social life in order to expand, correct or verify knowledge whether that knowledge aids in the construction of theory or in the practice of an art.

 

EDUCATIONAL RESEARCH

Educational Research is that activity which is directed towards development of a science of behavior in educational situations. The ultimate aim of this research is to provide knowledge that will permit the educator to achieve his goals by most effective methods. Educational research refers to a variety of methods, in which individuals evaluate different aspects of education including, student learning, teaching methods, teacher training, and classroom dynamics”.

 

RESEARCH METHODS VERSUS METHODOLOGY

Research methods include all those techniques/methods that are adopted for conducting research. Thus, research techniques or methods are the methods that the researchers adopt for conducting the research studies.

Research methodology is the way in which research problems are solved systematically. It is a science of studying how research is conducted scientifically. Under it, the researcher acquaints himself/herself with the various steps generally adopted to study a research problem, along with the underlying logic behind them. Hence, it is not only important for the researcher to know the research techniques/methods, but also the scientific approach called methodology.

TYPES OF RESEARCH

1.     Fundamental (or Basic) and Applied Research:

Fundamental research is mainly concerned with generalization with the formulation of a theory. It is research concerning principles or laws or rules. It aims at the achievement of knowledge and truth. Research studies concentrating on some natural phenomenon or relating to pure mathematics are examples of fundamental research. It aims at some theoretical conclusions. It may verify the old theory or establish a new one. It tries to explain the cause-and-effect relationship in social phenomena.

Applied research is concerned with the solution of particular problems. It aims at finding a solution for an immediate problem facing a society or an industrial organization. It is empirical and practical. It is concerned with applied aspects of life. Research to identify social, economic or political trends that may affect a particular institution or the marketing research are examples of applied research.

2.     Descriptive Research and Analytical Research:

Descriptive research includes survey and fact-finding enquiries of different kinds. It describes the state of affairs as it exists at present. The researcher has no control over the variables. He can only report what has happened or what is happening.

Analytical research one has to use facts or information already available and analyses these to make a critical evaluation of the material.

3.     Quantitative Research and Qualitative Research

Quantitative research is applicable to phenomena that are measurable so that they can be expressed in terms of quantity.

Qualitative research is concerned with qualitative phenomenon. Research designed to find out how people feel or what they think about a particular subject is qualitative research.

4.     Conceptual Research and Empirical Research:

Conceptual research is that related to some abstract ideas or theory. It is generally used by philosophers and thinkers to develop new concepts or to interpret existing ones.

Empirical research relies on experience or observation alone. It is data based research coming up with conclusions capable of being verified by observation or experiment.

 

PROCESS OF RESEARCH

1. Formulating the research problem

2. Extensive literature survey

3. Development of working hypothesis

4. Preparing the research design

5. Determining sample design

6. Collecting the data

7. Execution of the project

8. Analysis of data

9. Hypothesis testing

10. Generalizations and interpretation

11. Preparation of the report or presentation of the results, i.e., formal write-up of conclusions reached.

 

1.     Formulating the Research Problem

There are two types of research problems, viz., those which relate to states of nature and those which relate to relationships between variables. At the very outset, the researcher must single out the problem he wants to study, i.e., he must decide the general area of interest or aspect of a subject matter that he would like to inquire into. Essentially, two steps are involved in formulating the research problem, viz., understanding the problem thoroughly, and rephrasing the same into meaningful terms from an analytical point of view. The best way of understanding the problem is to discuss it with one’s own colleagues or with those having some expertise in the matter.

2.     Extensive Literature Survey

Once the problem is formulated, a brief summary of it should be written down.

At this juncture, the researcher should undertake extensive literature survey connected with the problem. For this purpose, the abstracting and indexing journals and published or unpublished bibliographies are the first place to go to.

3.     Development of Working Hypotheses

After the extensive literature survey, researcher should state in clear terms the working hypothesis or hypotheses. The working hypothesis is a tentative assumption made in order to draw out and test its logical or empirical consequences.

The answer is by using the following approach:

(a) Discussions with colleagues and experts about the problem, its origin and the objectives in seeking a solution;

(b) Examination of data and records, if available, concerning the problem for possible trends, peculiarities and other clues;

(c) Review of similar studies in the area or of the studies on similar problems; and

(d) Exploratory personal investigation which involves original field interviews on a limited scale with interested parties and individuals with a view to secure greater insight into the practical aspects of the problem.

4.  Preparing the Research Design:

The research problem having been formulated in clear-cut terms, the researcher will be requiredto prepare a research design, i.e., he will have to state the conceptual structure within which researchwould be conducted. Research purposes may be grouped into fourcategories, viz.,

(i)               Exploration,

(ii)             Description,

(iii)            Diagnosis, and

(iv)            Experimentation.

5.     Determining Sample Design:

All the items under consideration in any field of inquiry constitute a ‘universe’ or ‘population’. A complete enumeration of all the items in the ‘population’ is known as a census inquiry. Even the slightest element of bias in such an inquiry will get larger and larger as the number of observations increases. Moreover, there is no way of checking the element of bias or its extent except through a resurvey or use of sample checks.

6.     Collecting the Data

In dealing with any real-life problem, it is often found that data at hand are inadequate, and hence, it becomes necessary to collect data that are appropriate. There are several ways of collecting the appropriate data which differ considerably in the context of money costs, time and other resources at the disposal of the researcher. Primary data can be collected either through experiment or through survey. If the researcher conducts an experiment, he observes some quantitative measurements, or the data, with the help of which he examines the truth contained in his hypothesis.

7.     Execution of the Project

Execution of the project is a very important step in the research process. If the execution of the project proceeds on correct lines, the data to be collected would be adequate and dependable. The researcher should see that the project is executed in a systematic manner and in time. If the survey is to be conducted by means of structured questionnaires, data can be readily machine-processed. In such a situation, questions as well as the possible answers may be coded. If the data are to be collected through interviewers, arrangements should be made for proper selection and training of the interviewers. The training may be given with the help of instruction manuals which clearly explains the job of the interviewers at each step. Occasional field checks should be made to ensure that the interviewers are doing their assigned job sincerely and efficiently. A careful watch should be kept for unanticipated factors in order to keep the survey as much realistic as possible.

8.     Analysis of Data

After the data have been collected, the researcher turns to the task of analyzing them. The analysis of data requires a number of closely related operations such as establishment of categories, the application of these categories to raw data through coding, tabulation and then drawing statistical inferences. The unwieldy data should necessarily be condensed into a few manageable groups and tables for further analysis. Thus, the researcher should classify the raw data into some purposeful and usable categories.

a. Coding operation is usually done at this stage through which the categories of data aretransformed into symbols that may be tabulated and counted.

b. Tabulation is a part of the technical procedure wherein the classified data are put in the form oftables. The mechanical devices can be made use of at this juncture. A great deal of data, especially inlarge inquiries, is tabulated by computers.

c. Analysis work after tabulation is generally based on the computation of various percentages, coefficients, etc. by applying various well-defined statistical formulae. In the process of analysis, relationships or differences supporting or conflicting with original or new hypotheses should be subjected to tests of significance to determine with what validity data can be said to indicate any conclusion.

9.     Hypothesis Testing

After analyzing the data as stated above, the researcher is in a position to test the hypotheses, if any, he had formulated earlier. Various tests, such as Chi-square test, t-test, F-test, etc. have been developed by statisticians for the purpose. The hypotheses may be tested through the use of one or more of such tests, depending upon the nature and object of research inquiry.

 

Chi-Square Test (χ² test)

·  Purpose: Tests the relationship or independence between two categorical variables.

·  Type of data: Nominal / categorical data (e.g., gender, yes/no, preference).

·  Example: To test whether preference for a soft drink (Coke/Pepsi) is independent of gender (male/female).

·  Interpretation:

o   If the p-value < 0.05 → there is a significant association between the variables.

o   If p-value ≥ 0.05 → no significant association.

 Variants:

·  Chi-square test of independence – checks relationship between two categorical variables.

·  Chi-square goodness-of-fit test – checks if observed data fits an expected distribution.

 

t-Test

·  Purpose: Compares the means of two groups to see if they are significantly different.

·  Type of data: Continuous data (interval/ratio).

·  Example: To test if the average marks of male students differ from female students.

·  Interpretation:

o   If p-value < 0.05 → significant difference in means.

o   If p-value ≥ 0.05 → no significant difference.

Types:

·  One-sample t-test – compares mean of one group against a fixed value (e.g., testing if average height = 160 cm).

·  Independent samples t-test – compares means of two independent groups (e.g., boys vs girls).

·  Paired t-test – compares means of same group before vs after treatment (e.g., weight before and after a diet plan).

 

F-Test

·  Purpose: Compares variances of two or more groups; also used in ANOVA (Analysis of Variance) to compare means across multiple groups.

·  Type of data: Continuous data.

·  Example: To check if the average performance of students in 3 different classes is the same or different.

·  Interpretation:

o   If p-value < 0.05 → at least one group differs significantly.

o   If p-value ≥ 0.05 → no significant difference in group means.

Uses:

·  Variance comparison – tests if two populations have equal variance.

·  ANOVA – uses F-test to check difference in means among more than two groups.

·  Regression analysis – F-test checks whether the overall regression model is significant.

 

10.  Generalizations and Interpretation

If a hypothesis is tested and upheld several times, it may be possible for the researcher to arrive at generalizations, i.e., to build a theory. As a matter of fact, the real value of research lies in its ability to arrive at certain generalizations. If the researcher had no hypothesis to start with, he might seek to explain his findings on the basis of some theory. It is known as interpretation.

11.  Preparation of the Report or the Thesis

Finally, the researcher has to prepare the report of what has been done by him.

A. The layout of the report should be as follows:

(i) The preliminary pages,

(ii) The main text, and

(iii) The end matter.

In its preliminary pages, the report should carry title and date followed by acknowledgements and foreword. Then there should be a table of contents followed by a list of tables and list of graphs and charts, if any, given in the report.

The main text of the report should have the following parts:

(a) Introduction: It should contain a clear statement of the objective of the research and an explanation of the methodology adopted in accomplishing the research. The scope of the study along with various limitations should as well be stated in this part.

(b) Summary of Findings: After introduction, there would appear a statement of findings and recommendations in non-technical language. If the findings are extensive, they should be summarized.

(c) Main Report: The main body of the report should be presented in logical sequence and broken down into readily identifiable sections.

(d) Conclusion: Towards the end of the main text, the researcher should again put down the results of his research clearly and precisely. In fact, it is the final summing up.

At the end of the report, appendices should be enlisted in respect of all technical data. Bibliography, i.e., list of books, journals, reports, etc. consulted, should also be given in the end. Index should also be given specially in a published research report.

B. Report should be written in a concise and objective style in simple language avoiding vague expressions such as ‘it seems,’ ‘there may be’, and the like.

C. Charts and illustrations in the main report should be used only if they present the information more clearly and forcibly.

D. Calculated ‘confidence limits’ must be mentioned and the various constraints experienced in conducting research operations may as well be stated.

 

RESEARCH DESIGN

A research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure. In fact the research design is the conceptual structure within which research is conducted. it constitutes the blueprint for the collection measurement and analysis of data. In keeping the above stated design decisions, one may split the overall research design into the following parts; 1. The sampling design: Which deals with the method of selecting items to be observed for the given study.

2. The above observational design: which relates to the conditions under which the observation is to be made?

3. The statistical Design: which concerns with the question of how many items are to be observed and how the information and data gathered are to be analyzed.

4. The operational design: which deals with the techniques by which the procedures specified in the sampling, statistical and observational design can be carried out.

FEATURES OF THE RESEARCH DESIGN:

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

2. It is an outline that specifies the objectives of the study and the hypothesis Relevant to the research questions.

• It is a blueprint specifying his methods to be adopted for gathering and analyzing data.

4.     It is a scheme defining the domain of generalizability.

SIGNIFICANCE OF RESEARCH DESIGN:

• It may lead in the desired type of study with useful conclusions

• It may lead to more accurate results or help to reduce inaccuracy.

• It may lead to optimum efficiency and reliability.

• It may minimize the wastage of time and beating about the bush.

 

TYPES OF RESEARCH DESIGN

There are different types of research designs. They may be broadly categorized as:

(1) Exploratory Research Design;

(2) Descriptive and Diagnostic Research Design; and

(3) Hypothesis-Testing Research Design.

 

1. Exploratory Research Design:

The Exploratory Research Design is known as formulative research design. The main objective of using such a research design is to formulate a research problem for an in-depth or more precise investigation, or for developing a working hypothesis from an operational aspect. The major purpose of such studies is the discovery of ideas and insights. Therefore, such a research design suitable for such a study should be flexible enough to provide opportunity for considering different dimensions of the problem under study. The following three methods are considered in the context of a research design for such studies. They are

(a) a survey of related literature;

(b) experience survey; and

(c) analysis of ‘insight stimulating’ instances.

2. Descriptive And Diagnostic Research Design: A Descriptive Research Design is concerned with describing the characteristics of a particular individual or a group. Meanwhile, a diagnostic research design determines the frequency with which a variable occurs or its relationship with another variable.

On the other hand, a study that is concerned with specific predictions or with the narration of facts and characteristics related to an individual, group or situation, are instances of descriptive research studies.

The research design must also make appropriate provision for protection against bias and thus maximize reliability, with due regard to the completion of the research study in an economical manner. The research design in such studies should be rigid and not flexible. Besides, it must also focus attention on the following:

a) Formulation of the objectives of the study,

b) Proper designing of the methods of data collection,

c) Sample selection,

d) Data collection,

e) Processing and analysis of the collected data, and

f) Reporting the findings.

3. Hypothesis-Testing Research Design: Hypothesis-Testing Research Designs are those in which the researcher tests the hypothesis of causal relationship between two or more variables. These studies require procedures that would not only decrease bias and enhance reliability, but also facilitate deriving inferences about the causality.

 

 

SAMPLING

Though sampling is not new, the sampling theory has been developed recently. People knew or not but they have been using the sampling technique in their day to day life. For example a house wife tests a small quantity of rice to see whether it has been well cooked and gives the generalized result about the whole rice boiling in the vessel. The result arrived at is most of the times 100% correct. In another example, when a doctor wants to examine the blood for any deficiency, takes only a few drops of blood of the patient and examines. The result arrived at is most of the times correct and represent the whole amount of blood available in the body of the patient. In all these cases, by inspecting a few, they simply believe that the samples give a correct idea about the population. Most of our decision are based on the examination of a few items only i.e. Sample studies.

We may study a sample drawn from the large population and if that sample is adequately representative of the population, we should be able to arrive at valid conclusions.

SAMPLING DEFINITION According to Gerald Hursh “a Sample Design is the theoretical basis and the practical means by which we infer the characteristics of some population by generalizing from the characteristics of relatively few of the units comprising the population”.

STEPS IN SAMPLING DESIGN

 

TYPES OF SAMPLING: SAMPLING METHODS

1. Probability sampling

Probability sampling is a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. All the members have an equal opportunity to be a part of the sample with this selection parameter. Probability sampling is a sampling technique in which researchers choose samples from a larger population using a method based on the theory of probability. This sampling method considers every member of the population and forms samples based on a fixed process.

For example, in a population of 1000 members, every member will have a 1/1000 chance of being selected to be a part of a sample. Probability sampling eliminates bias in the population and gives all members a fair chance to be included in the sample.

A. Simple random sampling

In a simple random sample, every member of the population has an equal chance of being selected. Your sampling frame should include the whole population.

Example: You want to select a simple random sample of 100 employees of Company X. You assign a number to every employee in the company database from 1 to 1000, and use a random number generator to select 100 numbers.

B. Systematic sampling

Systematic sampling is similar to simple random sampling, but it is usually slightly easier to conduct. Every member of the population is listed with a number, but instead of randomly generating numbers, individuals are chosen at regular intervals.

Example: All employees of the company are listed in alphabetical order. From the first 10 numbers, you randomly select a starting point: number 6. From number 6 onwards, every 10th person on the list is selected (6, 16, 26, 36, and so on), and you end up with a sample of 100 people.

C. Stratified sampling

This sampling method is appropriate when the population has mixed characteristics, and you want to ensure that every characteristic is proportionally represented in the sample. You divide the population into subgroups (called strata) based on the relevant characteristic (e.g. gender, age range, income bracket, job role). From the overall proportions of the population, you calculate how many people should be sampled from each subgroup. Then you use random or systematic sampling to select a sample from each subgroup.

Example: The company has 800 female employees and 200 male employees. You want to ensure that the sample reflects the gender balance of the company, so you sort the population into two strata based on gender. Then you use random sampling on each group, selecting 80 women and 20 men, which gives you a representative sample of 100 people.

D. Cluster sampling

Cluster sampling also involves dividing the population into subgroups, but each subgroup should have similar characteristics to the whole sample. Instead of sampling individuals from each subgroup, you randomly select entire subgroups.

Example The company has offices in 10 cities across the country (all with roughly the same number of employees in similar roles). You don’t have the capacity to travel to every office to collect your data, so you use random sampling to select 3 offices – these are your clusters.

 

2. Non-probability sampling

In non-probability sampling, the researcher chooses members for research at random. This sampling method is not a fixed or predefined selection process. This makes it difficult for all elements of a population to have equal opportunities to be included in a sample.

A. Convenience sampling

A convenience sample simply includes the individuals who happen to be most accessible to the researcher.

Example: You are researching opinions about student support services in your university, so after each of your classes, you ask your fellow students to complete a survey on the topic. This is a convenient way to gather data, but as you only surveyed students taking the same classes as you at the same level, the sample is not representative of all the students at your university.

B. Voluntary response sampling

Similar to a convenience sample, a voluntary response sample is mainly based on ease of access. Instead of the researcher choosing participants and directly contacting them, people volunteer themselves (e.g. by responding to a public online survey).

Example: You send out the survey to all students at your university and a lot of students decide to complete it. This can certainly give you some insight into the topic, but the people who responded are more likely to be those who have strong opinions about the student support services, so you can’t be sure that their opinions are representative of all students.

C. Purposive sampling

This type of sampling involves the researcher using their judgement to select a sample that is most useful to the purposes of the research. It is often used in qualitative research, where the researcher wants to gain detailed knowledge about a specific phenomenon rather than make statistical inferences.

Example: You want to know more about the opinions and experiences of disabled students at your university, so you purposefully select a number of students with different support needs in order to gather a varied range of data on their experiences with student services.

D. Snowball sampling

If the population is hard to access, snowball sampling can be used to recruit participants via other participants. The number of people you have access to “snowballs” as you get in contact with more people.

Example: You are researching experiences of homelessness in your city. Since there is no list of all homeless people in the city, probability sampling isn’t possible. You meet one person who agrees to participate in the research, and she puts you in contact with other homeless people that she knows in the area.

 

 

DATA COLLECTION

Data refers to information or facts. Often researcher understands by data only numerical figure. It also includes descriptive facts, non-numerical information, qualitative and quantitative information.

Data could be broadly classified as:

1. Primary Data

2. Secondary Data

1. Primary Data It is known as the data collected for the first time through field survey. Such data are collected with specific set of objectives to assess the current status of any variable studied. Primary data are generally information gathered or generated by the researcher for the purpose of the project immediately at hand. When the data are collected for the first time, the responsibility for their processing also rests with the original investigator.

2. Secondary data It refers to the information or facts already collected. Such data are collected with the objective of understanding the past status of any variable. Secondary data can be obtained internally ie within the firm or external from one or more outside agencies. Secondary data are those which have been collected by some other persons for his purpose and published. They are usually in the shape of finished products.

 

ADVANTAGES OF PRIMARY DATA

1. It provide a firsthand account of the situation. We can observe the phenomenon as it takes place.

2. The information is more reliable as the investigator collects the data himself, he can take all precautions to ensure their reliability

3. These are the logical starting point for research in several disciplines.

4. Primary data are the only way of finding out opinions, personal qualities, attitudes etc.

 

DISADVANTAGES OF PRIMARY DATA

1. Collecting primary data is expensive in terms of both time & money.

2. There is greater scope for researcher bias creeping in unless the research investigator is fair to the respondent and methods of data collection the result of the study will not be reliable.

3. Sample selection is yet another problem.

 

METHODS OF COLLECTING PRIMARY DATA

1. Questionnaire

In this method to pre-printed list of questions arranged in sequence is used to elicit response from the informant.

2. Interview

This is a method in which the investigator and the respondent meet and questions raised are answered and recorded. This method is adopted when personal opinion or view point are to be gathered as a part of data.

3. Observation

A method which requires familiarity and experience, in this method the observer applies his sense organs to note down whatever that he could observe in the field and relate these data to explain some phenomena.

4. Feedback

In the case of some of the consumer goods, the supplier or the manufacturer send the product along with a pre-paid reply cover in which questions on the product and its usage are raised and the customer is required to fill it up and send.

5. Sales force opinion

The sales representatives visit the distributor or the retailers shop to note down the detail of stock movement, availability of items etc which give valuable information.

6. Schedule

This method of data collection is very much like the questionnaire with little difference which lies in the fact that schedules are being filled in by the enumerators who are specially appointed for the purpose.

7. Warranty Card

Warranty Card are usually postal sized card which are used by dealers of consumer durables to collect information regarding their products. The information sought is printed in the form of question on the warranty cards which is placed insided the package along with the product with a request to the consumer to fill in the card and post it back to the dealer.

8. Distributor or store Audit

Distributors get the retail stores audited through salesman and use such information to estimate market size, market share, seasonal purchasing pattern & so on.

 

TYPES OF PRIMARY DATA

1. Structured Observation

When observation takes place strictly in accordance with a plan or a design prepared in advance, it is called structured observation. In such a type the observer decided what to observe what to focus on, who are all to be observed etc.

2. Unstructured Observation

In this type of observation there is no advance designing of what, how, when, who etc of observation. The observer is given the freedom to decide on the spot, to observe everything that is relevant.

3. Participant Observation

 In this, the observer is very much present in the midst of what is observed. He is physically present on the spot to observe and not influencing the activities. It will help him to continuously observe and not everything that is happening around him.

4. Non Participant

Observation In this observer remains detached from whatever is happening around and does involve himself in any activities taking place. He is present only to observe and not to take part in the activities.

5. Controlled Observation

In this case, the observer performs his work in the environment or situation, which is very much planned or designed or set.

6. Uncontrolled Observation

The observer is at freedom to observer whatever is taking place around him in the natural set up.

 

ADVANTAGES OF SECONDARY DATA

1. The information can be collected by incurring the least cost.

2. The time requires for obtaining the information is very less.

3. Most of the secondary data are those published by big institutions. So they contain large quantity of information.

DISADVANTAGES OF SECONDARY DATA

1. Since the secondary data is a result of some other person’s attempt, it need not be suitable for a researcher, who makes use of it.

2. It may be inaccurate and unreliable.

3. It may contain certain errors.

SOURCES OF SECONDARY DATA

1. Official report of the central, state and local government.

2. Official publications of the foreign governments and international bodies like UNO and its subordinate bodies.

3. Reports and publications of Trade Associations, Banks, Cooperative Societies and Similar Semi Government and Autonomous Organizations.

4. Technical journals, News papers, Books, Periodicals, etc

5. Publications of research Organizations, Centers, Institutes, and reports submitted by Economists, Research scholars etc.

DATA COLLECTION METHODS

In this section, the researcher should describe the major methods for collecting data from the subjects. The major methods for obtaining data in a study may include:

1. Personal Interviews

2. Questionnaires

3. Observation techniques

4. Focus Groups

5. Surveys

 

Personal Interview

An interview is a direct face-to-face attempt to obtain reliable and valid measures in the form of verbal responses from one or more respondents.

Advantages

• Allows the interviewer to clarify questions.

• Can be used with young children and illiterates.

• Allow the informants to respond in any manner they see fit.

• Allows the interviewers to observe verbal and non-verbal behavior of the respondents.

Disadvantages

• Unstructured interviews often yield data too difficult to summarize or evaluate.

• Training interviewers, sending them to meet and interview their informants, and evaluating their effectiveness all add to the cost of the study.

 

Questionnaire

A questionnaire is a means of eliciting the feelings, beliefs, experiences, perceptions, or attitudes of some sample of individuals. As a data collecting instrument, it could be structured or unstructured.

Advantages

• Economy - Expense and time involved in training interviewers and sending them to interview are reduced by using questionnaires.

• Uniformity of questions - Each respondent receives the same set of questions phrased in exactly the same way. Questionnaires may, therefore, yield data more comparable than information obtained through an interview.

• Standardization - If the questions are highly structured and the conditions under which they are answered are controlled, then the questionnaire could become standardized.

Disadvantages

• Respondent’s motivation is difficult to assess, affecting the validity of response.

• Unless a random sampling of returns is obtained, those returned completed may represent biased samples.

 

Direct Observation

Direct observation is a measuring instrument used to measure such traits as self-control, cooperativeness, truthfulness, and honesty. In many cases, systematic direct observation of behavior is the most desirable measurement method.

 

Advantages

• It allows planners to get the views in a broad perspective rather than from an isolated point of view.

• Delphi in combination with other tools is a very potent device for teaching people to think about the future of education in much more complex ways than they ordinarily would.

• It is a useful instrument even for a general teaching strategy.

• It is a planning tool, which may aid in probing priorities held by members and constituencies of an organization.

• Delphi saves time and travel, which are required to bring people together for a conference.

• Delphi prevents personality biases from affecting the results.

Disadvantages

• Interpretation of the participants’ responses and the meaning of the importance of the factors in planning are difficult.

• It is unknown how the findings can be generalized to Delphis which cover a 30 year extension into the future.

• Delphi at present can render no rigorous distinction between reasonable judgment and mere guessing.

• It is difficult to determine the amount of bias injected into the results by the person administering the Delphi.

 

Focus Groups Discussion (FGD)

A focus group is an organized discussion session. A panel of people meets for a short duration to exchange ideas, feelings, and experiences on a specific topic. A trained facilitator, using group dynamics principles, guides participants through the meeting. Increasingly used in social and business research, focus group meetings enable a researcher to gain much information in a relatively short period of time

Advantages

• It is a socially oriented research procedure.

• The format allows the moderator to probe.

• Discussions have high face validity.

• Discussions can be relatively low cost.

• The format can provide speedy results.

• Focus groups enable the researcher to increase the sample size of qualitative studies.

Limitations

• The researcher has less control in the group interview as compared to the individual interview. • Data are more difficult to analyze.

• The technique requires carefully trained interviewers.

• Groups can vary considerably.

• Groups are difficult to assemble

• The discussion must be conducted in an environment conducive to conversation.

 

Telephone Surveys –

surveying by telephone is the most popular interviewing method.

Advantages

• People can usually be contacted faster over the telephone than with other methods. If the Interviewers are using CATI (computer-assisted telephone interviewing), the results can be available minutes after completing the last interview.

• You can dial random telephone numbers when you do not have the actual telephone numbers of potential respondents.

Disadvantages

• Many telemarketers have given legitimate research a bad name by claiming to be doing research when they start a sales call. Consequently, many people are reluctant to answer phone interviews and use their answering machines to screen calls.

• The growing number of working- women often means that no one is at home during the day.

• You cannot show or sample products by phone.

 

Mail Surveys

Advantages

• Mail surveys are among the least expensive.

• This is the only kind of survey you can do if you have the names and addresses of the target population, but not their telephone numbers.

• The questionnaire can include pictures - something that is not possible over the phone.

Disadvantages

• Time, mail surveys take longer than other kinds. You will need to wait several weeks after mailing out questionnaires before you can be sure that you have gotten most of the responses.

• In populations of lower educational and literacy levels, response rates to mail surveys are often too small to be useful.

Computer Direct Interviews

These are interviews in which the Interviewees enter their own answers directly into a computer. They can be used at malls, trade shows, offices, and so on.

Advantages

• The virtual elimination of data entry and editing costs.

• You will get more accurate answers to sensitive questions.

• The elimination of interviewer bias. Different interviewers can ask questions in different ways, leading to different results. The computer asks the questions the same way every time.

Disadvantages

• The Interviewees must have access to a computer or one must be provided for them.

• As with mail surveys, computers direct interviews may have serious response rate problems in populations of lower educational and literacy levels. This method may grow in importance as computer use increases.

 

Email Surveys

Email surveys are both very economical and very fast. More people have email than have full Internet access. This makes email a better choice than a Web page survey for some populations.

Advantages

• Speed. An email questionnaire can gather several thousand responses within a day or two.

• There is practically no cost involved once the set up has been completed.

• You can attach pictures and sound files.

Disadvantages

• You must possess (or purchase) a list of email addresses.

• Some people will respond several times or pass questionnaires along to friends to answer. Many programs have no check to eliminate people responding multiple times to bias the results.

 

 

QUALITATIVE vs. QUANTITATIVE RESEARCH

When collecting and analyzing data, quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

1. Quantitative Research

Quantitative research is expressed in numbers and graphs. It is used to test or confirm theories and assumptions. This type of research can be used to establish generalizable facts about a topic. Common quantitative methods include experiments, observations recorded as numbers, and surveys with closed-ended questions.

2. Qualitative Research

Qualitative research is expressed in words. It is used to understand concepts, thoughs or experiences. This type of research enables you to gather in-depth insights on topics that are not well understood. Common qualitative methods include interviews with open-ended questions, observations described in words, and literature reviews that explore concepts and theories.

 

QUESTIONNAIRE

A set of Questions designed to generate the statistical information from a specific demographic needed to accomplish the research objectives.

The questionnaire is probably most used and most abused of the data gathering devices. It is easy to prepare and to administer.

 

CHARACTERISTICS OF GOOD QUESTIONNAIRE

1. It deals with an important or significant topic.

2. Its significance is carefully stated on the questionnaire or on its covering letter.

3. It seeks only that data which cannot be obtained from the resources like books, reports and records.

4. It is as short as possible, only long enough to get the essential data.

5. It is attractive in appearance, nearly arranged and clearly stated or printed.

6. Directions are clear and complete, important terms are clarified.

7. The questions are objective, with no clues, hints or suggestions.

8. Questions are presented in a order from simple to complex.

 

TYPES OF QUESTIONNAIRE

1. Structured Questionnaire (Closed End Questions)

A structured questionnaire is that one which has pre-determined questions with answers. The respondents only tick the correct answer in the short term “yes” or “No”. It is also called pre-coded, closed restricted and categorical questionnaire.

Advantages

1. It is easy and less time consuming.

2. It keeps the respondents in limits.

3. It has objectivity.

Disadvantages

1. Confusion and difficulty in selection.

2. It bounds the respondents.

3. Les possibility of return.

4. Difficulty in reliability.

2. Un-Structured Questionnaire (Open End Questions)

Un-structured questionnaire is that in which pre-determined questions are given but have no answers. These answers are to be structured by the respondents. Open questions are given for the respondents to give answers. In such type of questionnaire, interview b/w the researcher and respondents or face to face conversation takes place. Such types is also called open-ended, unrestricted or non-categorical questionnaire.

For Example

1. Do you know about poverty

2. What are the types of poverty

3. What the factors influence poverty

4. What are the remedies for its solution

Advantages

1. It is more reliable.

2. It is more explanatory.

3. It gives depth of response.

Disadvantages

1. It requires greater efforts.

2. It is more expansible.

3. It risky for an investigator.

4. Less returns by the respondents.

3. Hand Delivered Questionnaire

This is a type of questionnaire in which the investigator himself go to the field and hand over the pre written questions to the respondents. They only tick mark, the correct answers in front of the investigator. It is also called direct questionnaire because the researcher directly distributes the questionnaire among the respondents.

Advantages

1. The researcher have close contact with respondents.

2. Difficult questions are explained by the researcher to the respondents.

3. He explains the purpose of the study.

Disadvantages

1. It is more expensive and costly.

2. It more time consuming.

4. Mailed Questionnaire

Most of the researcher uses that type of questionnaire. In that type the respondents are living in for-flung areas at a distance and the questionnaire is sent to them by post, they fill it and return back to the researcher or concerned department. A particular guide line or instructions list is attached to the questionnaire for the respondent’s guidance.

Advantages

1. It is commonly used.

2. It is useful for the researcher.

3. It is very easy and simple.

4. It saves time and money.

Disadvantages

1. Lack of returns.

2. Research take time due to careless and laziness of the respondents.

3. Lack of skilled respondents.

4. Errors may occur due to misunderstanding of respondents.

 

 

MEASUREMENT

Measurement is the process of observing and recording the observations that are collected as part of research. The recording of the observations may be in terms of numbers or other symbols or characteristics of objects according to certain prescribed rules. The respondents’ characteristics are feelings, attitudes, opinions etc.

Definition of Measurement: Measurement is defined as process of associating numbers or symbols to observations obtained in a research study.

 

SCALING TECHNIQUES

Scaling is the procedure of measuring and assigning the objects to the numbers according to the specified rules.

In other words, the process of locating the measured objects on the continuum, a continuous sequence of numbers to which the objects are assigned is called as scaling.

CHARACTERITICS OF SCALES

1. Distance The characteristic of distance means that absolute differences between the scale descriptors are known and may be expressed in units.

2. Origin The origin characteristic means that the scale has a unique or fixed beginning or true zero point.

3. Description By description we mean the unique labels or descriptors that are used to designate each value of the scale. All scales possess description.

4. Order By order we mean the relative sizes or positions of the descriptors. Order is denoted by descriptors such as greater than, less than, and equal to.

 

LEVELS OF MEASUREMENT SCALES

The level of measurement refers to the relationship among the values that are assigned to the attributes, feelings or opinions for a variable.

 

Primary Scaling Techniques

a) Nominal or Categorical Scale

b) Ordinal Scale

c) Interval Scale

d) Ratio Scale

a. Nominal or categorical Scale

• Simplest level of measurement when data values fit into categories.

• Observations are dichotomous or binary in that the outcome can take on only one of two values: yes or no.

• Mutually exclusive.

• E.g sex of patient(M/F), nationality

 

 

b. Ordinal scale

• When an inherent order occurs among the categories, the observations are said to be measured on an ordinal scale.

• Clinicians often use ordinal scales to determine a patient's amount of risk or the appropriate type of therapy.

• E.g socio-economic class, rank order of a class (1st,2nd, 3rd) VAS (visual analog scale) for pain

 

c. Interval Scale

• Data classified by ranking.

• Quantitative classification .

• Zero point of scale is arbitrary (differences are • meaningful).

• Fahrenheit temp. scale , Time

d. Ratio Scale

• Data classified as the ratio of two numbers.

• Quantitative classification .

• Zero point of scale is absolute (data can be added, subtracted, multiplied, and divided).

• E. g- Kelvin temp. scale, Weight, Height

 

TYPES OF SCALING TECHNIQUES

a. Comparative scale

Comparative scales involve the direct comparison of stimulus objects. Most often, the respondent is asked to compare one brand, product or feature against another. Comparative scale data must be interpreted in relative terms and have only ordinal or rank order properties.

b. Non-comparative scale

In market research, data is collected and measured on either a comparative scale or a non-comparative scale. A comparative scale asks customers to evaluate one product in direct comparison to others. A non-comparative scale evaluates a single product by itself.

Comparative Scales

 In comparative scaling, the respondent is asked to compare one object with another.

The comparative scales can further be divided into the following four types of scaling techniques:

a. Paired Comparison Scale

b. Rank Order Scale

c. Constant Sum Scale, and

d. Q-Sort Scale

 

a. Paired Comparison Scale

This is a comparative scaling technique in which a respondent is presented with two objects at a time and asked to select one object according to some criterion. The data obtained are ordinal in nature.

For Example

 

b. Rank Order Scale

This is another type of comparative scaling technique in which respondents are presented with several items simultaneously and asked to rank them in the order of priority. This is an ordinal scale that describes the favored and un favored objects but does not reveal the distance between the objects.

c. Constant Sum Scale:

In this scale, the respondents are asked to allocate a constant sum of units such as points, rupees among a set of stimulus objects with respect to some criterion. For example, you may wish to determine how important the attributes of price, fragrance, packaging, cleaning power, and lather of a detergent are to consumers. Respondents might be asked to divide a constant sum to indicate the relative importance of the attributes.

d. Q-Sort Scale

This is a comparative Scale that uses a rank order procedure to sort objects based on similarity with respect to some criterion. The important characteristic of this methodology is that it is more important to make comparisons among different responses of a respondent than the responses between different respondents.

 

2. Non-Comparative Scales:

In non-comparative scaling respondents need only evaluate a single object. Their evaluation is independent of the other object which the researcher is studying. The non-comparative scaling techniques can be further divided into:

a. Continuous Rating Scale and

b. Itemized Rating Scale

 

a. Continuous Rating Scale

It is very simple and highly useful. In continuous rating scale, the respondent’s rate the objects by placing a mark at the appropriate position on a continuous line that runs from one extreme of the criterion variable to the other.

b. Itemized Rating Scales:

Itemized rating scale is a scale having numbers of brief descriptions associated with each category. The categories are ordered in terms of scale position and the respondents are required to select one of the limited number of categories that best describes the product, brand, company, or product attribute being rated.

Itemised rating scales is further divided into three parts, namely

i.                 Likert Scale

ii.                Semantic Differential Scale and

iii.              Stapel Scale

i. Likert Scale:

Likert, is extremely popular for measuring attitudes, because, the method is simple to administer. With the Likert Scale, the respondents indicate their own attitudes by checking how strongly they agree or disagree with carefully worded statements that range from very positive to very negative towards the attitudinal object. Respondents generally choose from five alternatives (say strongly agree, agree, neither agree nor disagree, disagree, strongly disagree). A Likert scale may include a number of items or statements.

ii. Semantic Differential Scale:

This is a seven-point rating scale with end points associated with bipolar label’s (such as good and bad, complex and simple) that have semantic meaning. It can be used to find whether a respondent has a positive or negative attitude towards an object.

iii. Staple Scale:

The Staple scale was originally developed to measure the direction and intensity of an attitude simultaneously. Modern versions of the Stapel scale place a single adjective as a substitute for the Semantic differential when it is difficult to create pairs of bipolar adjectives. The modified Stapel scale places a single adjective in the center of an even number of numerical Values.

 

CRITERIA FOR GOOD MEASUREMENTS

There are three measurement of the characteristics for evaluating a measurement tool.

1. Validity

2. Reliability

3. Sensitivity

1. Validity

It is the ability of an instrument to measure what it is supposed to measure. That is, when we ask a question with the hope that we are tapping the concept, how can we be reasonably certain that we are indeed measuring the concept we set to do and not something else?

2. Reliability

The reliability of a measure indicates the extent to which it is without bias (error free) and hence ensures consistent measurement across time and across the various items in the instrument. In other words, the reliability of a measure is an indication of the stability and consistency with which the instrument measures the concept and helps to assess the “goodness” of measure.

3. Stability

The ability of the measure to remain the same over time despite uncontrollable testing conditions or the state of the respondents themselves is indicative of its stability and low vulnerability to changes in the situation.

 

 

 

ATTITUDE MEASUREMENT

Attitude is defined as a way of thinking about something that is expressed through a person's behavior. Attitudes about certain events, experiences, or other people are also made up of our perspective, stance, and opinions.

ATTITUDE MEASUREMENT SCALES

THURSTONE SCALE

It is the method of equal appearing intervals. It is made up of statements about a particular issue, and each statement has a numerical value indicating how favourable or unfavourable it is judged to be. People check each of the statements to which they agree, and a mean score is computed, indicating their attitude.

MULTIDIMENSIONAL SCALING [MDS]  

In earlier scales researchers knew in advance what attitude dimensions are relevant. In MDS computer-based techniques are used to present an object in multidimensional space based on one or more respondent's perceptions towards the object.

MDS helps to answer following questions:

1. What are major attributes of a product class (e.g. soft drinks) which consumers perceive viewing the product and by which they compare different brands.

2. Which brands compete most / least with each other.

3. Would consumers accept a new brand with a combination of characteristic not found in the market.

4. What is consumers ideal (point) combination of attributes

5. What sales / advertising messages are compatible with brand perceptions.

 

OTHER USES OF MULTIDIMENSIONAL SCALING

1. Market segmentation.

2. Perception at different stages of product life cycle.

3. Advertisement media selection.

4. Supplier evaluation of purchase managers.

LIMITATIONS OF MULTIDIMENSIONAL SCALING

1. Definition of 'similarity and preference' imperfect - conceptual problems.

2. Empirical problems in subjective identification of relevant dimensions or bias in data collection

3. Computational problems - Most Computational programs assume linear distance because what is the best distance function is not known.