St. PETER'S UNIVERSITY
St. Peter’s Institute of Higher Education and Research(Declared Under Section 3 of the UGC Act, 1956) AVADI, CHENNAI - 600 054 TAMIL NADU
STUDY MATERIAL
M.B.A. PROGRAMME
(Code No. 411) (Effective from 2009 - 2010)II SEMESTER
209MBT27
APPLIED RESEARCH METHODS IN MANAGEMENT
St. PETER'S INSTITUTE OF DISTANCE EDUCATION
Recognized by Distance Education Council and Joint Committee of UGC – AICTE - DEC, New Delhi. (Ref. F.No.DEC/SPU/CHN/TN/Recog/09/14 dated 02.04.2009 &
Author: U Bhojanna
Copyright © 2011, U Bhojanna
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PREFACE
St. Peters University has been recognized by the Distance Education Council, and Joint Committee of UGC-AICTE-DEC, for offering various programmes including B.Tech., D.Tech., MBA, MCA and other programmes in Humanities and Sciences through Distance Education mode.
The Methodology of Distance Education includes self-instructional study materials in print form, face-to-face conselling, practical classes, virtual classes in phased manner and end assessment.
The basic support for distance education students lies on the self instructional study materials. Keeping this in mind, the study materials under distance mode are prepared. The main features of the study materials are (1) learning objectives (2) self explanatory study materials unitwise (3) self tests (4) list of references for further studies. The material is prepared in simple English and graded in terms of technical content. It is built upon the pre-requisite knowledge.
Students are advised to study the materials several times and get benefitted. The face-to-face session in the counseling centre will help them to clear their doubts and difficult concepts which they would have faced during the learning process.
Students should remember that self study and sustained motivation are the two important requirements for a successful learning under the distance education mode.
We wish the students to put forth their best efforts to become successful in their chosen field of learning.
Registrar St. Peters University
CONTENTS
Page
Scheme of Examinations vi
Syllabus of Applied Research Methods in Management x
Model Question Paper xi
UNIT I: INTRODUCTION TO RESEARCH
Lesson 1 Research Fundamentals 3
Lesson 2 Research Process: Theoretical Framework and Hypothesis Development 16
Lesson 3 The Research Process: Elements of Research Design 25
UNIT II: EXPERIMENTAL DESIGN
Lesson 4 Experimental Designs 39
Lesson 5 Measurement and Measurement Scales 47
UNIT III: DATA COLLECTION METHOD
Lesson 6 Data Collection Methods 63
Lesson 7 Special Data Source 82
Lesson 8 Sampling 88
UNIT IV: A REFRESHER ON SOME MULTIVARIATE STATISTICAL TECHNIQUES
Lesson 9 Multivariate Statistical Techniques 111
Lesson 10 Application of SPSS Package 124
UNIT V: THE RESEARCH REPORT
Lesson 11 Fundamentals of Report 139
Scheme of Examinations
I SemesterCodeNo. CourseTitle Credit Marks
Theory EA Total
109MBT11 Management Principles & Organisational Behaviour 3 100 100 109MBT12 Economic Analysis for Business Decisions 3 100 100
109MBT13 Statistics for Management 2 100 100
109MBT14 Applied Operation Research for Management 3 100 100 109MBT15 Financial and Management Accounting 3 100 100
109MBT16 Legal Environment of Business 2 100 100
109MBT17 Executive Communication 2 100 100
Total 18 700 700
II Semester
CodeNo. CourseTitle Credit Marks
Theory EA Total
209MBT21 Production & Operation Management 3 100 100
209MBT22 Financial Management Decisions 3 100 100
209MBT23 Marketing for Managers 2 100 100
209MBT24 Human Resource Management 2 100 100
209MBT25 Computer Applications and Management
Information System 2 100 100
209MBT26 Total Quality Management 2 100 100
209MBT27 Applied Research Methods in Management 3 100 100 209MBP01 Computer Lab for Business Administration Record 1 90
10
100
III Semester
CodeNo. CourseTitle Credit Marks
Theory EA Total
309MBT01 International Business Management 3 100 100
309MBT02 Strategic Management 3 100 100
E1*** Electives I 2 100 100
E2*** Electives II 2 100 100
E3*** Electives III 2 100 100
E4*** Elective IV 2 100 100
E5*** Elective V 2 100 100
E6*** Elective VI 2 100 100
Total 18 800 800
*** Any one group of electives from Marketing, Finance, Human Resource Management and System is to be chosen.
IV Semester
CodeNo. CourseTitle Credit Marks
Theory EA Total
409MBT01 Marketing Research and Consumer Behaviour 6 100 100
409MBT02 Entrepreneurship Development 6 100 100
409MBP01 Project and Vivavoce * 6 100 100
Total 18 300 300
LIST OF ELECTIVES
MARKETING ELECTIVESCodeNo. CourseTitle Credit Marks
Theory EA Total
309MBT03 Retail Management 2 100 100
309MBT04 Services Marketing 2 100 100
309MBT05 Advertising and Sales Promotion 2 100 100
309MBT06 International Marketing 2 100 100
309MBT07 Brand Management 2 100 100
309MBT08 Rural and Social Marketing 2 100 100
Total 12 600 600
FINANCE ELECTIVES
CodeNo. CourseTitle Credit Marks
Theory EA Total
309MBT09 Security Analysis and Portfolio Management 2 100 100 309MBT10 Merchant Banking and Financial Services 2 100 100
309MBT11 International Trade Finance 2 100 100
309MBT12 Strategic Financial Management 2 100 100
309MBT13 Corporate Finance 2 100 100
309MBT14 Derivatives Management 2 100 100
HUMAN RESOURCE MANAGEMENT ELECTIVES
CodeNo. CourseTitle Credit Marks
Theory EA Total
309MBT15 Managerial Behaviour and Effectiveness 2 100 100 309MBT16 Organisational Change & Intervention Strategy 2 100 100 309MBT17 Industrial Relations and Labour Welfare 2 100 100
309MBT18 Labour Legislations 2 100 100
309MBT19 Strategic Human Management and Development 2 100 100 309MBT20 Corporate Governance & Corporate Social
Responsibility 2 100 100
Total 12 600 600
SYSTEM ELECTIVES
CodeNo. CourseTitle Credit Marks
Theory EA Total
309MBT21 Software Development 2 100 100
309MBT22 Database Management Systems 2 100 100
309MBT23 Enterprise Resource Planning for Management 2 100 100 309MBT24 Software Project and Quality Management 2 100 100
309MBT25 Decision Support System 2 100 100
309MBT26 Information Technology for Management 2 100 100
209MBT27 APPLIED RESEARCH METHODS IN MANAGEMENT
SyllabusUNIT I: INTRODUCTION TO RESEARCH
The hallmarks of scientific research The building blocks of science in research The research process for applied and basic research The need for theoretical frame work Hypothesis development Hypothesis testing with quantitative data. The research design. The purpose of the study: Exploratory, Descriptive, Hypothesis testing (Analytical and Predictive) Cross sectional and longitudinal studies.
UNIT II: EXPERIMENTAL DESIGN
The laboratory and the field experiment Internal and external validity Factors affecting internal validity. Measurement of variables Scales and measurement of variables Development scales Rating scale and concept in scales being developed. Stability measures.
UNIT III: DATA COLLECTION METHOD
Interviewing questionnaires etc. Secondary sources of data collection. Guidelines for questionnaire design Electronic questionnaire design and surveys. Special data source: Focus group, Static and dynamic data-collection methods and when to use each. Sampling techniques and confidence in determining sample size. Hypothesis testing determination of optimal sample size.
UNIT IV: A REFRESHER ON SOME MULTIVARIATE STATISTICAL TECHNIQUES
15 Factor analysis Cluster analysis Discriminant analysis Multiple regression & correlation Canonical correlation Application of SPSS package.
UNIT V: THE RESEARCH REPORT
The purpose of the written report Concept of audience Basics of written reports. The integral parts of a report The title of a report. The table of content, the synopsis, the introductory section, method of sections of a report, result section Discussion section Recommendation and implementation section.
TEXT BOOKS:
1. Donald R. Cooper and Ramcis S. Schindler, Business Research Methods, Tata McGraw Hill Publishing Company Limited, New Delhi, 2000.
2. C.R. Kothari, Research Methodology, Wishva Prakashan, New Delhi, 2001.
3. Kumar, Bhattacharya, Research Methodology, 2nd Edition, Excel Books, New Delhi.
4. R.Nandha Gopal, K.Arul Rajan, N.Vivek, Research Methods in Business, Excel Books, New Delhi. REFERENCES:
1. Uma Sekaran, Research Methods for Business, John Wiley and Sons Inc., New York, 2000. 2. Donald H.Mc.Burney, Research Methods, Thomson Asia Pvt. Ltd. Singapore, 2002.
3. G.W. Ticehurst and A.J. Veal, Business Research Methods, Longman, 1999. 4. Ranjit Kumar, Research Methodology, Sage Publication, London, New Delhi, 1999.
MODEL QUESTION PAPER
M.B.A. DEGREE EXAMINATIONSSecond Semester
209MBT27 - APPLIED RESEARCH METHODS IN MANAGEMENT (Regulations 2009)
Time: 3 hours Maximum: 100 Marks
Answer ALL the questions
PART A (10 × 2 = 20 Marks)
1. Define research.
2. What do you mean by applied research?
3. Differentiate between dependent and independent variable. 4. What is the method of paired comparisons?
5. What are the two methods of interview? 6. What is hypothesis according to a researcher? 7. What are the different methods of factor analysis? 8. What are the two types of multivariate techniques? 9. What are the contents of preliminary pages? 10. What is a popular report?
PART B (5 × 16 = 80 Marks)
11. (a) What are the different types of research? or (b) Explain the research process in detail.
12. (a) What are the different techniques in scale construction? or
(b) What are the complex random sampling designs? 13. (a) Differentiate between questionnaires and schedules.
or (b) How do you determine the sample size?
14. (a) What are the different variables in multivariate analysis? or
(b) Explain some of the important multivariate analysis. 15. (a) What are the steps in writing report?
or (b) What is the outline of a technical report?
Unit I
LESSON
1
RESEARCH FUNDAMENTALS
STRUCTURE 1.0 Objectives 1.1 Introduction1.2 The Hallmarks of Scientific Research 1.3 The Building Blocks of Science in Research
1.4 The Research Process for Applied and Basic Research 1.4.1 Problem Formulation
1.4.2 Evaluate the Cost of Research
1.4.3 Preparing a List of Needed Information 1.4.4 Decision on Research Design
1.4.5 Data Collection
1.4.6 Select the Sample Types 1.4.7 Determine the Sample Size 1.4.8 Organise the Fieldwork
1.4.9 Analyse the Data and Report Preparation 1.5 Let us Sum up
1.6 Glossary
1.7 Suggested Readings 1.8 Questions
1.0 OBJECTIVES
After studying this lesson, you should be able to:
l Discuss the hallmarks of scientific research
l Explain the building blocks of science in research
l Elucidate upon the research process for applied and basic research
1.1 INTRODUCTION
Research in common man's language refers to "search for Knowledge".
Research is an art of scientific investigation. It is also a systematic design, collection, analysis and reporting the findings & solutions for the marketing problem of a company. Research is required because of the following reasons:
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Applied Research Methods in Management
1. To Identify and Find Solutions to the Problem: To understand the problem in depth Example: "Why is that demand for a product is falling"? "Why is there a business fluctuation once in three years"? By identifying the problem as above, it is easy to collect the relevant data to solve the problem.
2. To Help Making Decisions:Example: Should we maintain the advertising budget same as last year? Research will answer this question.
3. To Find Alternative Strategies: Should we follow pull strategy or push strategy to promote the product.
4. To Develop New Concepts: Example: CRM, Horizontal Marketing, MLM etc.
1.2 THE HALLMARKS OF SCIENTIFIC RESEARCH
The hallmarks or main distinguishing characteristics of scientific research may be listed follows:
1. Purposiveness 2. Rigor
3. Testability 4. Replicability
5. Precision and Confidence 6. Objectivity
7. Generalisability 8. Parsimony
Let us discuss each of them one by one.
1. Purposiveness: The research must have an aim; that is, it should be problem-based, unified and directed. Not pointless and random. A testable hypothesis is normally needed in scientific writing to consolidate purpose of study. This also 'narrows down' the project to a manageable size. (This 'narrowing' is also essential in order to complete the project in a limit time.)
Example:
Consider the following topics:
(a) The environment and the Indian economy
(b) The problem of pollution in the environment and its impact on the Indian economy
(c) The problem of ocean spills and their economic impact on the Indian economy (d) The problem of oil spills and their economic impact on the US economy (e) The 1989 Alaskan Oil and its impact on the US economy
(f) Consequences of the 1989 Alaskan Oil Spill on share prices in the Alaskan economy from 1989 to 2002
(g) Is more narrow and has a clear purpose than (a)-(d).
The first thing that you should do is to formulate a research question that is meaningful, narrow and clear.
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2. Rigour: The project should have sound methodological design. It should be 'scientific' and/or 'logical'. Conclusions must follow from accepted premises defended and tested in the course of the research. One can't base the conclusions on a few interviews with company employees, for example.
In the above example (f) lends to a rigorous approach only if: a number of features of the Alaskan economy only if: a number of features of the Alaskan economy are considered and tested under a range of different conditions and if 'consequences' are measured using a number of independent economic models.
Consider:
v phrasing of research question (see 4. Hypothesis formation, below)
v phrasing of survey questions
v Sample size (how many is needed?)
v cause and effect (which is which?)
v choice of relevant variables.
Rigour is also ensured by an appropriately wide search and discussion of the literature in the area. This not only helps in making the study rigorous by avoiding problems in these areas that others might have made, but it ensures that the study is unique.
3. Isolating Variables: Getting clear about your variables is critical: you must distinguish your dependent variables (the things you are looking at), from the independent variable(s) (things that influence the dependent variable) and the moderating variable(s) (things that modify the relationship between the DV and V) and the intervening variable(s) (things that may turn up after the moderating variable(s) have had their effect(s), but does not change that relationship).
For example, in the previous case given:
v Alaskan share prices are the dependent variables
v The 1989 Alaskan oil spill is the independent variable
v the general influences on Alaskan share prices are moderating variables (e.g.,
the state of the world economy, trade with other countries, etc.)
v Other factors which may normally have an impact on share prices (consumer
sentiment, terrorism, etc.), but need not change the relationship between the DV and the IV might be interviewing variables.
4. Hypothesis Formation: A clear hypothesis (even if not explicitly stated in the dissertation) will ensure that your dissertation has a focus/purpose and direction. It also ensures that you answer a research question of some kind, rather than ramble from one topic to another. The hypothesis(es) are the connecting membranes that holds the research together.
The hypothesis can be in several formats: Conditional statements (if...then):
v If employees are more healthy then they will take sick leave less frequently.
In the non-conditional form:
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It is less clear what constitutes evidence for or against this latter proposition than in the conditional form. The conditional form requires you to actually do something to demonstrate the point. It is not just an unsupported assertion.
Directional statements:
v The greater the stress experienced in the job, the lower the job satisfaction of employees.
Again, like conditional, using directions: 'more than' 'less than', 'negative', 'position' etc., force you to do something to demonstrate the point you are making. It begs justification.
Non-directional statements:
These postulate a relationship between variables, but offer no indication of direction.
v There is a difference between the work ethic values of Australian and Asian
employees.
This also begs clarification and expansion. This may be used in an area where there has not yet been demonstrated that there is a significant relationship between variables, or when studies indicate contradictory findings and where the direction of the relationship is unclear.
5. Testability: The research aim must be testable. It is no good having a clear purpose if it isn't testable. In previous example, the hypothesis (say) that oil spills have an impact on where consumers go shopping is hardly testable (even though it may be true)! How would one test this claim? How would one know that the independent variable was the only factor influencing their choices?
For testability, you might consider using a combination of data sources:
v Statistics
v Surveys
v Literature
v Interviews...etc.
Never use one measurement alone as individually the tests may be misleading. A way of being sure that you have precise data is to use convergent validity as a test. (i.e. use a number of tests of the same data and see if the results of those tests of the same data and see if the results of those tests can be correlated.) This is called triangulation.
6. Replicability: Your research must in principle be able to be repeated by others. This requires:
(a) that the experimental/case aims and procedures are sound;
(b) that the report is written in clear and comprehensible manner so others can follow it
A project which both 'stands alone' as a sound piece of research and can also be repeated by others in other situations is obviously better than one which can't be repeated.
7. Precision and Confidence: "The more precision and confidence we aim for in our research, the more scientific the investigation, and the more useful the results." This simply means that the results must be as close as possible (accurate) to the
7 Research Fundamentals
actual state of affairs that you are studying and that others can rely on those results to a high degree.
These requirements are obviously not static: that's why research needs to be done constantly to improve our knowledge and experimental accuracy in a changing world. For example, the exact reason why people buy trouser braces is somewhat different now to the reasons people bought them three centuries ago (then they were needed to hold trousers up, now they can be just a fashion statement). You may use statistics (e.g., alpha levels) as a measure of significance (confidence) but the precision of your data prior to submitting it to statistical analysis must be constantly reassessed.
8. Objectivity: Conclusions should not be based on subjective/emotional values but the facts resulting from the data analysis. The data should be stripped of personal values and biases. There is no point in doing a serious experiment or case study if the conclusions you make are not based on data, but your pre-judged opinion of what should have happened. (This is circular and self-justifying)
From the point of view of good research design, it is as important to find out, for example, that aerobic activities do not increase cognitive speed in older adults as to find out that they do. Other researchers can then forget this variable and look at something else. A salutary lesson about research is this: "The (researcher) is a mere private in an army pursuing truth".
9. Generalisability: The more that a given research project can be generalised to other situations, the better 'If a researcher's findings that participation in decision making enhances organisational commitment, is found to be true in a variety of managerial, industrial and service organisations and not merely in the one organisation studied by the researcher, then the generalisability of the findings to other organisational settings is widened'.
There is a tension here, of course, with other aims: to aim to complete a project that is both generalisable and also manageably narrow in focus is a tall order. The aim of generalisability is a regulative ideal rather than being essential. If your research project is generalisable as well as narrowly focussed, well and good.
10. Parsimony: Economy of explanation is preferred in research work that you are undertaking. Aim to uncover a small but meaningful result in your work, not something vast and complex. Making a small, simple but significant point forcefully (using a number of independent tests) is better than trying to do too much and over-extending yourself.
1.3 THE BUILDING BLOCKS OF SCIENCE IN
RESEARCH
The application of valid and reliable research methods serves as the building blocks of science in research. It has three distinct characteristics:
Objectivity: The research based on scientific approach should enable the researcher to classify facts accurately and carefully, without any bias.
Accuracy of Measurement: A mere collection and classification of the facts may not be sufficient. One must be able to make observations of their correlation and sequence, which can be derived as a result of imagination and painstaking efforts of the researchers.
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Applied Research Methods in Management
Self Criticism: Scientists should critically examine their own research as they are a group of people who are never sure that they have found the ultimate truth; their studies are exhaustive. If researchers are completely objective, their measurements are accurate and their studies are exhaustive, then their results will be valid and reliable.
Check Your Progress 1
Fill in the blanks:
1. Conclusions should not be based on ... values but the facts resulting from the data analysis.
2. The three main building blocks of science in research are ...,
... and ... .
1.4 THE RESEARCH PROCESS FOR APPLIED AND
BASIC RESEARCH
Until the sixteenth century, human inquiry was primarily based on introspection. The way to know things was to turn inward and use logic to seek the truth. This paradigm had endured for a millennium and was a well-established conceptual framework for understanding the world. The seeker of knowledge was an integral part of the inquiry process. A profound change occurred during the sixteenth and seventeenth centuries. The Scientific Revolution was born. Objectivity became a critical component of the new scientific method. The investigator was an observer, rather than a participant in the inquiry process. A mechanistic view of the universe evolved. We believed that we could understand the whole by performing an examination of the individual parts. Experimentation and deduction became the tools of the scholar. For two hundred years, the new paradigm slowly evolved to become part of the reality framework of society. The research process is a step-by-step process of developing a research paper. As you progress from one step to the next, it is commonly necessary to backup, revise, add additional material or even change your topic completely. This will depend on what you discover during your research. There are many reasons for adjusting your plan. For example, you may find that your topic is too broad and needs to be narrowed, sufficient information resources may not be available, what you learn may not support your thesis, or the size of the project does not fit the requirements.
The research process itself involves identifying, locating, assessing, analysing, and then developing and expressing your ideas. These are the same skills you will need outside the academic world when you write a report or proposal for your boss.
There are nine steps in the research process, that can be followed while designing a research project. They are as follows:
1. Formulate the problem
2. Evaluate the cost of research
3. Prepare the list of information
4. Research design decision
5. Data collection
6. Select the sample type
9 Research Fundamentals
8. Organise the field work
9. Analyse the data and report preparation
Defining the research problem and formulation of hypothesis are the hardest steps in the research process.
1.4.1 Problem Formulation
Problem formulation is the key to research process. For a researcher, problem formulation means converting the management problem to a research problem. In order to attain clarity, the MR manager and researcher must articulate clearly so that perfect understanding of each others is achieved.
While problem is being formulated, the following should be taken into account:
1. Determine the objective of the study.
2. Consider various environment factors.
3. Nature of the problem.
4. State the alternative
1. Determine the objective: Objective may be general or specific. General Would like to know, how effective was the advertising campaign. The above looks like a statement with objective. In reality, it is far from it. There are two ways of finding out the objectives precisely. (a) The researcher should clarify with the MR manager "What effective means". Does effective mean, awareness or does it refer to sales increase or does it mean, it has improved the knowledge of the audience, or the perception of audience about the product. In each of the above circumstances, the questions to be asked from audience varies (b) Another way to find objectives is to find out from the MR Manager, "What action will be taken, given the specified outcome of the study.
Example: If research finding is that, the previous advertisement by the company was indeed ineffective, what course of action the company intends to take (a) Increase the budget for the next Ad (b) Use different appeal (c) Change the media (d) Go to a new agency.
If objectives are proper, research questions will be precise. However we should remember that objectives, do undergo a change.
2. Consider environmental factors: Environmental factors influence the outcome of the research and the decision. Therefore, the researcher must help the client to identify the environmental factors that are relevant.
Example: Assume that the company wants to introduce a new product like Iced tea or frozen green peas or ready to eat chapaties. The following are the environmental factors to be considered:
(a) Purchasing habit of consumers.
(b) Presently, who are the other competitors in the market with same or similar product.
(c) What is the perception of the people about the other products of the company, with respect to price, image of the company.
(d) Size of the market and target audience.
All the above factors could influence the decision. Therefore researcher must work very closely with his client.
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Applied Research Methods in Management
3. Nature of the problem: By understanding the nature of the problem, the researcher can collect relevant data and help suggesting a suitable solution. Every problem is related to either one or more variable. Before starting the data collection, a preliminary investigation of the problem is necessary, for better understanding of the problem. Initial investigation could be, by using focus group of consumers or sales representatives.
If focus group is carried out with consumers, some of the following question will help the researcher to understand the problem better:
(a) Did the customer ever included this company's product in his mental map? (b) If the customer is not buying the companies product, the reasons for the
same.
(c) Why did the customer go to the competitor?
(d) Is the researcher contacting the right target audience?
4. State the alternatives: It is better for the researcher to generate as many alternatives as possible during problem formulation hypothesis.
Example: Whether to introduce a Sachet form of packaging with a view to increase sales. The hypothesis will state that, acceptance of the sachet by the customer will increase the sales by 20%. Thereafter, the test marketing will be conducted before deciding whether to introduce sachet or not. Therefore for every alternative, a hypothesis is to be developed.
1.4.2 Evaluate the Cost of Research
There are several methods to establish the value of research. Some of them are (1) Bayesian approach (2) Simple saving method (3) Return on investment (4) Cost benefit approach etc.
Example: Company 'X' wants to launch a product. The company's intuitive feeling is that, the product failure possibilities is 35%. However, if research is conducted and appropriate data is gathered, the chances of failure can be reduced to 30%. Company also has calculated, that the loss would be Rs. 3,00,000 if product fails. The company has received a quote from MR agency. The cost of research is Rs. 75,000. The question is "Should the company spend this money to conduct research?"
Solution:
Loss without research = 3,00,000 × 0.35 = Rs. 1,05,000 Loss with research = 3,00,000 × 0.30
= Rs. 90,000 Value of research information = 1,05,000 90,000
= Rs. 15,000
Since the value of information namely Rs. 15000 is lower than the cost of research Rs. 75,000, conducting research is not recommended.
1.4.3 Preparing a List of Needed Information
Assume that company 'X' wants to introduce a new product (Tea powder). Before introducing it, the product has to be test marketed. The company needs to know the
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extent of competition, price and quality acceptance from the market. In this context, following are the list of information required.
1. Total demand and company sales:
Example: What is the overall industry demand? What is the share of the competitor? The above information will help the management to estimate overall share and its own shares, in the market.
2. Distribution coverage:
Example: (a) Availability of products at different outlets. (b) Effect of shelf display on sales.
3. Market awareness, attitude and usage:
Example: "What percentage of target population are aware of firm's product"? "Do customers know about the product"? "What is the customers' attitude towards the product"? "What percentage of customers repurchased the product"?
4. Marketing expenditure:
Example: "What has been the marketing expenditure"? "How much was spent on promotion"?
5. Competitors marketing expenditure:
Example: "How much competitor spent, to market a similar product"?
1.4.4 Decision on Research Design
1. Should the research be exploratory or conclusive?
Exploratory research:
Example: "Causes for decline in sales of a specific company's product in a specific territory under a specific salesman".
The researcher may explore all possibilities why sales in falling? (a) Faulty product planning
(b) Higher price (c) Less discount (d) Less availability
(e) Inefficient advertising/salesmanship (f) Poor quality of salesmanship (g) less awareness
Not all factors are responsible for decline in sales.
Conclusive research: Narrow down the option. Only one or two factors are responsible for decline in sales. Therefore zero down, and use judgment and past experience.
2. Who should be interviewed for collecting data: If the study is undertaken to determine whether, children influence the brand, for ready - to eat cereal (corn flakes) purchased by their parents. The researcher must decide, if only adults are to be studied or children are also to be included. The researcher must decide if data
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is to be collected by observation method or by interviewing. If interviewed, "Is it a personal interview or telephonic interview or questionnaire?"
3. Should a few cases be studied or choose a large sample: The researcher may feel that, there are some cases available which are identical and similar in nature. He may decide to use these cases for formulating the initial hypothesis. If suitable cases are not available, then the researcher may decide to choose a large sample. 4. How to incorporate experiment in research: If it is an experiment, "Where and
when measurement should take place?", should be decided.
Example: In a test of advertising copy, the respondents can first be interviewed to measure their present awareness, and their attitudes towards certain brands. Then, they can be shown a pilot version of the proposed advertisement copy, following this, their attitude also is to be measured once again, to see if the proposed copy had any effect on them.
If it is a questionnaire, (a) What are the contents of the questionnaire? (b) What type of questions to be asked? Like pointed questions, general questions etc. (c) In what sequence should it be asked? (d) Should there be a fixed set of alternatives or should it be open ended? (e) Should the purpose be made clear to the respondents or should it be disguised, are to be determined well in advance?
1.4.5 Data Collection
The next step is that of data collection. Data collection is a term used to describe a process of preparing and collecting data for example as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, to pass information on to others. A research study, most often than not, is based on the data collected and the information revealed after processing that data.
1.4.6 Select the Sample Types
The first task is to carefully select "What groups of people or stores are to be sampled". For example, collecting the data from a fast food chain. Here, it is necessary to define what is meant by fast food chain. Also precise geographical location should be mentioned. Next step is to decide whether to choose probability sampling or non probability sampling. Probability sampling is one, in which each element has a known chance of being selected. A non-probability sampling can be convenience or judgment sampling.
1.4.7 Determine the Sample Size
Smaller the sample size, larger the error, vice versa.
Sample size depends up on (a) Accuracy required (b) Time available (c) Cost involved. While selecting the sample, the sample unit has to be clearly specified. Example: Survey on the attitudes towards the use of shampoo with reference to a specific brand, where husbands, wives or combination of all of them are to be surveyed or a specific segment is to be surveyed. Sample size depends on the size of the sample frame/universe.
1.4.8 Organise the Fieldwork
This includes selection, training and evaluating the field sales force to collect the data: (a) How to analysing the field work?
13 Research Fundamentals
(c) How to approach the respondents?
(d) Week, day and time to meet the specific respondents etc., are to be decided.
1.4.9 Analyse the Data and Report Preparation
This involves (a) Editing, (b) Tabulating, (c) Codifying etc.1. The data collected should be scanned, to make sure that it is complete and all the instructions are followed. This process is called editing. Once these forms have been edited, they must be coded.
2. Coding means, assigning numbers to each of the answers, so that they can be analysed.
The final step is called as data tabulation. It is the orderly arrangement of the data in a tabular form. Also at the time of analysing the data, the statistical tests to be used must be finalized such as T-Test, Z-test, Chi-square Test, ANOVA etc.
Check Your Progress 2 Fill in the blanks:
1. There are ... steps in the research process.
2. ... includes selection, training and evaluating the field sales force to collect the data.
Case: Nivea's Foray into the Men's Fairness Cream Market
in India
I
n May 2007, Beiersdorf AG, the German company which owns Nivea, a major global skin and body care brand, launched a new line of products under the 'Nivea for Men' name in India. The launch of the Nivea for Men line in India marked the company's entry into the male grooming segment in the country. In India, Nivea had been primarily known for its moisturising creams.This decision of foray into the men's fairness cream market in India was made after the conducting extensive market research by Nivea as well as the collecting information from the researches made on similar topics by the main players of the same industry. The early 2000s had witnessed an increased interest in personal grooming among men. According to analysts, men were becoming more conscious of their looks, as in the business world as well as in society, a lot rode on how a person presented himself. Surveys carried out by cosmetics companies suggested that a large number of Indian men were using fairness creams that were originally targeted at women.
For example, a study conducted by Emami Industries (Emami) in the early 2000s showed that 29% of the users of fairness creams were men. Going by this trend, companies started developing men's grooming products that went beyond shaving products and deodorants.
In 2005, with the launch of 'Fair and Handsome', Emami became the first company in India to launch a fairness cream exclusively for men. Fair and Handsome was followed in 2006 by Hindustan Lever Limited's (HLL) Fair and Lovely Menz Active, another fairness cream for men. HLL used the brand strength of one of its most popular products, Fair and Lovely, in launching this product. Menz Active was also launched amidst heavy promotion.
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Analysts said that the launch of Menz Active would intensify the competition in the men's fairness products segment. The total size of the grooming products market in India was estimated to be worth Rs. 8.0 billion in 2007.
In its foray into the Indian men's fairness cream market, Nivea took a different approach, targeting a distinct customer segment. According to Nivea India's Managing Director, Kai Boris Bendix (Bendix), the company's target customers were upper and middle class men. On the other hand, Emami and HLL targeted both the urban and rural markets, cutting across the segments.
Bendix also said that his company expected to grow the men's fairness cream market in a different direction, rather than take market share away from competitors. In India, Nivea's share in the cosmetics and toiletries segment stood at 0.2% as of mid-2007. Bendix said that the company was aiming at achieving a 5% market share in India by 2012. It was expected that if these companies' products performed well, then it would encourage several other companies to launch new lines of cosmetics exclusively for men.
Questions
1. Was it correct on part of Nivea to follow suit initiated by Emami and HLL? 2. What basis do you see in Emami coming up with Fair and Handsome and create a
new category altogether?
3. According to your analysis, why do you see Nivea succeeding/failing in its endeavour?
Source: www.icmrindia.org
1.5 LET US SUM UP
Research originates in a decision process. In research process, management problem is converted into a research problem which is the major objective of the study. Research question is further subdivided, covering various facets of the problem that need to be solved. The role and scope of research has greatly increased in the field of business and economy as a whole. The study of research methods provides you with knowledge and skills you need to solve the problems and meet the challenges of today is modern pace of development.
1.6 GLOSSARY
Marketing Research: Marketing research is about researching the whole of a company's marketing process.
Advertising Research: It is a specialised form of marketing research conducted to improve the efficacy of advertising.
Product Research: This looks at what products can be produced with available technology, and what new product innovations near-future technology can develop. Ad Tracking: It is periodic or continuous in-market research to monitor a brand's performance using measures such as brand awareness, brand preference, and product usage.
Concept Testing: To test the acceptance of a concept by target consumers.
Copy Testing: It predicts in-market performance of an ad before it airs by analysing audience levels of attention, brand linkage, motivation, entertainment, and communication, as well as breaking down the ad's flow of attention and flow of emotion.
15 Research Fundamentals Mystery Shopping: An employee or representative of the market research firm
anonymously contacts a salesperson and indicates he or she is shopping for a product. The shopper then records the entire experience.
Exploratory Research: Exploratory research provides insights into and comprehension of an issue or situation.
Check Your Progress: Answers
CYP 11. subjective/emotional
2. objectivity, accuracy of measurement, self criticism CYP 2
1. nine
2. Organising the fieldwork
1.7 SUGGESTED READINGS
S. N. Murthy and U. Bhojanna, Business Research Methods, Excel Books, 2007. Abrams, M.A., Social Surveys and Social Action, London: Heinemann, 1951.
Arthur, Maurice, Philosophy of Scientific Investigation, Baltimore: John Hopkins University Press, 1943.
Bernal, J.D., The Social Function of Science, London: George Routledge and Sons, 1939. Chase, Stuart, The Proper Study of Mankind: An inquiry into the Science of Human Relations, New York, Harper and Row Publishers, 1958.
1.8 QUESTIONS
1. An Indian company dealing in pesticides hires a qualified business management graduate to expand its marketing activities. Most of the current employees of the company are qualified chemists with science background. During their first review meeting the management graduate says that the "company should be involved in market research to get a better perspective of the problem on hand". On hearing this, one of the science graduate laughs and says "There is no such thing as marketing or business research, research is combined to science alone." What would be your response?
2. How does a research help the managers to determine the pattern of consumption? 3. Company 'A' would like to introduce a new product in the market. The research agencies has given an estimation of 5 lakhs and a time period of five months. According the past experience of the company, the probability of earning 10 lakhs is 0.4 and 5 lakhs is 0.3 and loosing 7 lakhs is 0.3. Should the company under take the research?
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LESSON
2
RESEARCH PROCESS: THEORETICAL
FRAMEWORK AND HYPOTHESIS DEVELOPMENT
STRUCTURE2.0 Objectives 2.1 Introduction
2.2 The Need for Theoretical Framework 2.3 Hypothesis: Meaning
2.4 Hypothesis Development
2.5 Hypothesis Testing with Quantitative Data 2.5.1 Logic behind Hypothesis Testing 2.5.2 Type-I Error
2.5.3 Type-II Error
2.5.4 The Testing Procedure 2.6 Let us Sum up
2.7 Glossary
2.8 Suggested Readings 2.9 Questions
2.0 OBJECTIVES
After studying this lesson, you should be able to:
l Describe the need for a theoretical framework in research
l Explain the process of hypothesis development
l Elucidate upon the methodology of hypothesis testing
2.1 INTRODUCTION
Until the sixteenth century, human inquiry was primarily based on introspection. The way to know things was to turn inward and use logic to seek the truth. This paradigm had endured for a millennium and was a well-established conceptual framework for understanding the world. The seeker of knowledge was an integral part of the inquiry process.
A profound change occurred during the sixteenth and seventeenth centuries. Objectivity became a critical component of the new scientific method. The investigator was an
17 Research Process: Theoretical Framework and Hypothesis Development
observer, rather than a participant in the inquiry process. A mechanistic view of the universe evolved. Experimentation and deduction became the tools of the scholar.
2.2 THE NEED FOR THEORETICAL FRAMEWORK
A theoretical framework is a type of intermediate theory that attempts to connect to all aspects of inquiry (e.g., problem definition, purpose, literature review, methodology, data collection and analysis). It is used in research to outline possible courses of action or to present a preferred approach to an idea or thought. A theoretical framework guides the research, determining what things a researcher will measure, and what statistical relationships he/she will look for.
Theoretical frameworks are critical in deductive, theory-testing sorts of studies. In those kinds of studies, the theoretical framework must be very specific and well-thought out. Because theoretical frameworks are potentially so close to empirical inquiry, they take different forms depending upon the research question or problem.
Theoretical frameworks are also important in exploratory studies, where the researcher really doesn't know much about what is going on, and is trying to learn more. There are two reasons why theoretical frameworks are important here.
First, no matter how little the researcher thinks he/she knows about a topic, and how unbiased he/she thinks he/she is, it is impossible for a human being not to have preconceived notions, even if they are of a very general nature. A researcher is always being guided by a theoretical framework, but he/she might not know it. Not knowing what his/her real framework is can be a problem. The framework tends to guide what the researcher notice in an organisation, and what he/she doesn't notice.
2.3 HYPOTHESIS: MEANING
A hypothesis is a tentative proposition relating to certain phenomenon, which the researcher wants to verify when required. If the researcher wants to infer something about the total population from which the sample was taken, statistical methods are used to make inference. We may say that, while a hypothesis is useful, it is not always necessary. Many a time, the researcher is interested in collecting and analysing the data indicating the main characteristics without a hypothesis. Also, a hypothesis may be rejected but can never be accepted except tentatively. Further evidence may prove it wrong. It is wrong to conclude that since hypothesis was not rejected it can be accepted as valid.
2.4 HYPOTHESIS DEVELOPMENT
In each problem considered, the question of interest is simplified into two competing
claims/hypotheses between which we have a choice; the null hypothesis, denoted H0,
against the alternative hypothesis, denoted H1. These two competing claims/hypotheses are not however treated on an equal basis: special consideration is given to the null hypothesis.
We have two common situations:
1. The experiment has been carried out in an attempt to disprove or reject a particular hypothesis, the null hypothesis, thus we give that one priority so it cannot be rejected unless the evidence against it is sufficiently strong. For example,
H0: there is no difference in taste between coke and diet coke against H1: there is a difference.
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2. If one of the two hypotheses is 'simpler' we give it priority so that a more
'complicated' theory is not adopted unless there is sufficient evidence against the simpler one. For example, it is 'simpler' to claim that there is no difference in flavour between coke and diet coke than it is to say that there is a difference. The hypotheses are often statements about population parameters like expected value and variance; for example H0 might be that the expected value of the height of ten year old boys in the Scottish population is not different from that of ten year old girls. A hypothesis might also be a statement about the distributional form of a characteristic of interest, for example that the height of ten year old boys is normally distributed within the Scottish population.
The outcome of a hypothesis test is "Reject H0 in favour of H1" or "Do not reject H0". Null Hypothesis: The null hypothesis, H0, represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved. For example, in a clinical trial of a new drug, the null hypothesis might be that the new drug is no better, on average, than the current drug. We would write:
H0: There is no difference between the two drugs on average.
We give special consideration to the null hypothesis. This is due to the fact that the null hypothesis relates to the statement being tested, whereas the alternative hypothesis relates to the statement to be accepted if/when the null is rejected.
The final conclusion once the test has been carried out is always given in terms of the null hypothesis. We either "Reject H0 in favour of H1" or "Do not reject H0"; we never conclude "Reject H1", or even "Accept H1".
If we conclude "Do not reject H0", this does not necessarily mean that the null hypothesis is true, it only suggests that there is not sufficient evidence against H0 in favour of H1. Rejecting the null hypothesis then, suggests that the alternative hypothesis may be true. Alternative Hypothesis: The alternative hypothesis, H1, is a statement of what a statistical hypothesis test is set up to establish. For example, in a clinical trial of a new drug, the alternative hypothesis might be that the new drug has a different effect, on average, compared to that of the current drug. We would write:
H1: the two drugs have different effects, on average.
The alternative hypothesis might also be that the new drug is better, on average, than the current drug. In this case we would write:
H1: the new drug is better than the current drug, on average.
The final conclusion once the test has been carried out is always given in terms of the null hypothesis. We either "Reject H0 in favour of H1" or "Do not reject H0". We never conclude "Reject H1", or even "Accept H1".
If we conclude "Do not reject H0", this does not necessarily mean that the null hypothesis is true, it only suggests that there is not sufficient evidence against H0 in favour of H1. Rejecting the null hypothesis then, suggests that the alternative hypothesis may be true. Simple Hypothesis: A simple hypothesis is a hypothesis which specifies the population distribution completely.
19 Research Process: Theoretical Framework and Hypothesis Development
Examples
1. H0: X ~ Bi(100,1/2), i.e. p is specified 2. H0: X ~ N(5,20), i.e. µ and σ2 are specified
Composite Hypothesis: A composite hypothesis is a hypothesis which does not specify the population distribution completely.
Examples
1. X ~ Bi(100, p) and H1: p > 0.5
2. X ~ N(0, σ2) and H
1: σ2 unspecified
Check Your Progress 1
Fill in the blanks:
1. The ... hypothesis represents a theory that has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved.
2. A ... hypothesis is a hypothesis which specifies the population distribution completely.
2.5 HYPOTHESIS TESTING WITH QUANTITATIVE
DATA
Inferences on population parameters are often made on the basis of sample observation. In doing so, one has to take the help of certain assumptions or hypothetical values about the characteristics of the population if some such information is available. Such hypothesis about the population is termed as statistical hypothesis and the hypothesis is tested on the basis of sample values. The procedure enables one to decide on a certain hypothesis and test its significance.
Hypothesis testing is largely the product of Ronald Fisher, Jerzy Neyman, Karl Pearson and (son) Egon Pearson. Fisher emphasized rigorous experimental design and methods to extract a result from few samples assuming Gaussian distributions. Neyman (who teamed with the younger Pearson) emphasized mathematical rigor and methods to obtain more results from many samples and a wider range of distributions. Modern hypothesis testing is an (extended) hybrid of the Fisher vs. Neyman/Pearson formulation, methods and terminology developed in the early 20th century.
A statistical test provides a mechanism for making quantitative decisions about a process or processes. The intent is to determine whether there is enough evidence to "reject" a conjecture or hypothesis about the process. The conjecture is called the null hypothesis. Not rejecting may be a good result if we want to continue to act as if we "believe" the null hypothesis is true. Or it may be a disappointing result, possibly indicating we may not yet have enough data to "prove" something by rejecting the null hypothesis.
2.5.1 Logic behind Hypothesis Testing
Statistical hypothesis test is a method of making statistical decisions using experimental data. It is sometimes called confirmatory data analysis, in contrast to exploratory data analysis. In frequency probability, these decisions are almost always made using null-hypothesis tests; that is, ones that answer the question. Assuming that the null
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hypothesis is true, what is the probability of observing a value for the test statistic that is at least as extreme as the value that was actually observed? One use of hypothesis testing is deciding whether experimental results contain enough information to cast doubt on conventional wisdom.
Statistical hypothesis testing is a key technique of frequentist statistical inference, and is widely used but also much criticized. The main alternative to statistical hypothesis testing is Bayesian inference.
The critical region of a hypothesis test is the set of all outcomes which, if they occur, cause the null hypothesis to be rejected in favor of the alternative hypothesis. The critical region is usually denoted by C.
Setting up and testing hypotheses is an essential part of statistical inference. In order to formulate such a test, usually some theory has been put forward, either because it is believed to be true or because it is to be used as a basis for argument, but has not been proved, for example, claiming that a new drug is better than the current drug for treatment of the same symptoms.
2.5.2 Type-I Error
In a hypothesis test, a type I error occurs when the null hypothesis is rejected when it is in fact true; that is, H0 is wrongly rejected.
For example, in a clinical trial of a new drug, the null hypothesis might be that the new drug is no better, on average, than the current drug; i.e.
H0: there is no difference between the two drugs on average.
A type I error would occur if we concluded that the two drugs produced different effects when in fact there was no difference between them.
The following table gives a summary of possible results of any hypothesis test:
Decision
Reject H0 Don't reject H0 Truth H0 Type I Error Right decision
H1 Right decision Type II Error
A type I error is often considered to be more serious, and therefore more important to avoid, than a type II error. The hypothesis test procedure is therefore adjusted so that there is a guaranteed 'low' probability of rejecting the null hypothesis wrongly; this probability is never 0. This probability of a type I error can be precisely computed as P(type I error) = significance level = α
The exact probability of a type II error is generally unknown.
If we do not reject the null hypothesis, it may still be false (a type II error) as the sample may not be big enough to identify the falseness of the null hypothesis (especially if the truth is very close to hypothesis).
For any given set of data, type I and type II errors are inversely related; the smaller the risk of one, the higher the risk of the other.
21 Research Process: Theoretical Framework and Hypothesis Development
2.5.3 Type-II Error
In a hypothesis test, a type II error occurs when the null hypothesis H0, is not rejected when it is in fact false. For example, in a clinical trial of a new drug, the null hypothesis might be that the new drug is no better, on average, than the current drug; i.e.
H0: there is no difference between the two drugs on average.
A type II error would occur if it was concluded that the two drugs produced the same effect, i.e. there is no difference between the two drugs on average, when in fact they produced different ones.
A type II error is frequently due to sample sizes being too small.
The probability of a type II error is generally unknown, but is symbolised by β and
written
P(type II error) = β
A type II error can also be referred to as an error of the second kind.
2.5.4 The Testing Procedure
There are various important steps involved in hypothesis testing. They can be enlisted as under:
1. The first step in any hypothesis testing is to state the relevant hypotheses to be
tested. This is important as mis-stating the hypothesis will make the rest of the process unworthwhile.
2. The second step is to consider the assumptions being made in doing the test; for
example, assumptions about the statistical independence or about the form of the distributions of the observations. This is equally important as invalid assumptions will mean that the results of the test are invalid.
3. The third step is of the computation of the relevant test statistic. The distribution of such a statistic under the null hypothesis can be derived from the assumptions. In standard cases this will be a well-known result. For example the test statistics may follow a Student's t distribution or a Normal Distribution. The distribution of the test statistic partitions the possible values of the estimator into those for which the null-hypothesis is accepted and those for which it is rejected.
4. The next step refers to the comparison of the test-statistic (S) to the relevant
critical values (CV) (obtained from tables in standard cases).
5. Step 5 is to decide to either reject or accept the null hypothesis. The decision rule is to reject the null hypothesis (H0) if S > CV and vice versa.
Check Your Progress 2
Fill in the blanks:
1. Hypothesis testing is the use of statistics to determine the ... that a given hypothesis is true.
2. The smaller the P-value, the stronger the evidence against the ... 3. The usual process of hypothesis testing consists of ... steps.
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Case: Titan's Foray into the Prescription Eyewear Market in India
I
n early 2007, the prescription eyewear market in India was estimated to be worth between Rs 18-20 billion, with around 30 million pieces (frames with glasses) being sold every year. It was also one of the fastest growing consumer segments in the country in the early 2000s, recording an average annual growth rate of around 25%. This segment however, was largely dominated by the unorganised sector, which accounted for 95% of the prescription eyewear business. Firms like Lawrence & Mayo and GKB Opticals were some of the well established representatives of the organised sector in the business, but their presence was limited to only a handful of stores in a few big cities.In early 2007, Lawrence & Mayo had 41 stores in 17 cities across India, while GKB opticals had 31 stores in 9 cities. Most of these stores were located in big cities like Delhi, Kolkata, Mumbai, Chennai, Bangalore, Hyderabad, Pune and Visakhapatnam. In March 2007, Titan Industries (Titan), a joint venture between the Tata Group, a major industrial conglomerate in India, and the Tamil Nadu Industrial Development Corporation (TIDCO), an industrial investment body set up by the Tamil Nadu state government, announced its venture into the prescription eyewear business. Titan was already a well established brand in the watches and jewelry segments in India.
Titan had ventured into the wrist watch segment in 1984, and is thought to have played a major role in transforming watches into fashion accessories in the Indian market. Also, Titan's jewelry brand Tanishq, when it was launched in 1995, was one of the first jewelry brands in India, and rapidly established itself in a segment that was largely dominated by the unorganised sector. Along similar lines, Titan sought to take advantage of the large market for eyewear through its new stores, which were to operate under the name Titan Eye+ (Eye+).
In April 2007, Titan opened two Eye + stores in Bangalore. The company planned to open a total of ten stores spread across Nagpur, Chennai and Bangalore, by the end of the 2007. The plan was to eventually open 150 Eye+ stores and 100 franchisee outlets by 2010. These stores were to be opened mainly in A and B segment towns.
Bhaskar Bhat (Bhat), the Managing Director of Titan said that Titan would be investing Rs 150-200 million initially for setting up the Eye+ stores, and expected revenues of Rs 150 million from the stores in 2007-2008. The company expected the eyewear business to contribute 15 per cent of its total turnover by 2012. It hoped to capture a 20% market share by the same time.
Questions
1. What was the necessity of research for Titan to venture into eyewear market? 2. What hypothesis would have formed the base for the researches done in order to
determine the feasibility of Titan's introduction of the eyewear products?
Source: www.icmrindia.org
2.6 LET US SUM UP
Hypothesis tests are procedures for making rational decisions about the reality of effects. Most decisions require that an individual select a single alternative from a number of possible alternatives. The decision is made without knowing whether or not it is correct; that is, it is based on incomplete information. A rational decision is characterised by the use of a procedure which insures the likelihood or probability that success is incorporated into the decision-making process.
23 Research Process: Theoretical Framework and Hypothesis Development
Hypothesis testing is equivalent to the geometrical concept of hypothesis negation. That is, if one wishes to prove that a (the hypothesis) is true, one first assumes that it isn't true. If it is shown that this assumption is logically impossible, the original hypothesis is proven. In the case of hypothesis testing the hypothesis may never be proven; rather, it is decided that the model of no effects is unlikely enough that the opposite hypothesis, that of real effects, must be true.
2.7 GLOSSARY
Simple Hypothesis: Any hypothesis which specifies the population distribution completely. Composite Hypothesis: Any hypothesis which does not specify the population distribution completely.
Statistical Test: A decision function that takes its values in the set of hypotheses. Region of Acceptance: The set of values for which we fail to reject the null hypothesis. Region of Rejection/Critical Region: The set of values of the test statistic for which the null hypothesis is rejected.
Check Your Progress: Answers
CYP 1 1. null 2. simple CYP 2 1. probability 2. null hypothesis 3. four
2.8 SUGGESTED READINGS
S. N. Murthy and U. Bhojanna, Business Research Methods, Excel Books, 2007. Abrams, M.A., Social Surveys and Social Action, London: Heinemann, 1951.
Arthur, Maurice, Philosophy of Scientific Investigation, Baltimore: John Hopkins University Press, 1943.
Bernal, J.D., The Social Function of Science, London: George Routledge and Sons, 1939. Chase, Stuart, The Proper Study of Mankind: An inquiry into the Science of Human Relations, New York, Harper and Row Publishers, 1958.
2.9 QUESTIONS
1. What hypothesis would you use in the following situation - "an automobile company has manufacturing facility at two different models. The customer wants to know if the mileage given by both the models is the same or not."
2. What hypothesis, test and procedure would you use when an automobile company
has manufacturing facility at two different geographical locations? Each location manufactures two-wheelers of a different model. The customer wants to know if
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the mileage given by both the models is the same or not. Samples of 45 numbers may be taken for this purpose.
3. What hypothesis, test and procedure would you use when a company has 22 sales
executives? They underwent a training programme. The test must evaluate whether the sales performance is unchanged or improved after the training programme. 4. What hypothesis, test and procedure would you use A company has three categories
of managers:
(a) With professional qualifications but without work experience. (b) With professional qualifications accompanied by work experience. (c) Without professional qualifications but with work experience.
LESSON
3
THE RESEARCH PROCESS: ELEMENTS OF
RESEARCH DESIGN
STRUCTURE
3.0 Objectives 3.1 Introduction
3.2 Purpose of the Study 3.2.1 Exploratory Research 3.2.2 Descriptive Research
3.3 Hypothesis Testing: Analytical and Predictive 3.4 Cross-sectional Study 3.5 Longitudinal Study 3.6 Let us Sum up 3.7 Glossary 3.8 Suggested Readings 3.9 Questions
3.0 OBJECTIVES
After studying this lesson, you should be able to:
l Discuss the purpose of various studies
l Describe analytical and predictive hypothesis testing
l Explain cross-sectional and longitudinal studies
3.1 INTRODUCTION
Research design is simply a plan for a study. This is used as a guide in collecting and analysing the data. It can be called a blue print to carry out the study. It is like a plan made by an architect to build the house, if a research is conducted without a blue print, the result is likely to be different from what is expected at the start. The blue print includes:
1. Interviews to be conducted, observations to be made, experiments to be conducted
data analysis to be made.
2. Tools used to collect the data such as questionnaire.
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Research design can be thought of as the structure of research it is the "glue" that holds all of the elements in a research project together. A successful design stems from a collaborative process involving good planning and communication.
3.2 PURPOSE OF THE STUDY
Research is mainly undertaken for the following purposes:
l Exploratory
l Descriptive
Exploratory research is used to seek insights into general nature of the problem. It provides the relevant variable that need to be considered. In this type of research, there is no previous knowledge; research methods are flexible, qualitative and unstructured. The researcher in this method does not know "what he will find".
Descriptive research is a type of research, very widely used in marketing research. Generally in descriptive study there will be a hypothesis, with respect to this hypothesis, we ask questions like size, distribution, etc.
3.2.1 Exploratory Research
This type of research is carried out at the very beginning when the problem is not clear or is vague. In exploratory research, all possible reasons which are very obvious are eliminated, thereby directing the research to proceed further with limited options. The major emphasis in exploratory research is on converting broad, vague problem statements into small, precise sub-problem statements, which is done in order to formulate specific hypothesis. The hypothesis is a statement that specifies, "how two or more variables are related?"
In the early stages of research, we usually lack from sufficient understanding of the problem to formulate a specific hypothesis. Further, there are often several tentative explanations.
Sales decline in a company may be due to:
1. Inefficient service
2. Improper price
3. Inefficient sales force
4. Ineffective promotion
5. Improper quality
The research executives must examine such questions to identify the most useful avenues for further research. Preliminary investigation of this type is called exploratory research. Expert surveys, focus groups, case studies and observation methods are used to conduct the exploratory survey.
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.
27 The Research Process: Elements of Research Design
In this scenario, very little information is available to point out, what is the actual cause of the problem. We can say that the major purpose of exploratory research is to identify the problem more specifically. Therefore, exploratory study is used in the initial stages of research.
Under what circumstances is exploratory study ideal?
The following are the circumstances in which exploratory study would be ideally suited:
1. To gain an insight into the problem.
2. To generate new product ideas.
3. To list all possibilities. Among the several possibilities, we need to prioritize the possibilities.
4. To develop hypothesis occasionally.
5. Exploratory study is also used to increase the analyst's familiarity with the problem. This is particularly true, when the analyst is new to the problem area. Example: A market researcher working for (new entrant) a company for the first time.
6. To establish priorities so that further research can be conducted.
7. Exploratory studies may be used to clarify concepts and help in formulating precise
problems. Example: The management is considering a change in the contract policy, which it hopes, will result in improved satisfaction for channel members.
An exploratory study can be used to clarify the present state of channel members' satisfaction and to develop a method by which satisfaction level of channel members is measured.
8. To pre-test a draft questionnaire.
9
