MGM 322: RESEARCH METHODS

Study Material

 
Lecture 1
Learning Outcomes of the course
 
•      What is research?
•      Need for research
•      Types of Research
•      What is a good research?
 
What is Research?
 
•      Research means a systematic investigation, including research development, testing and evaluation, designed to develop or contribute to generalizable knowledge.
•      Research is disciplined inquiry.
•      The generic characteristics of this kind of inquiry that are useful criteria for shaping and evaluating our research are the following:
Research should be 
 
accessible – a public activity, open to scrutiny by peers
transparent – clear in its structure, process and outcomes
transferable – useful beyond the specific research project, applicable in principles (if not specifics) to other researchers and research contexts.
What is Research?
 
•       Research and experimental development comprises creative work undertaken on a systematic basis in order to increase the stock of knowledge, including knowledge of man, culture and society, and the use of this stock of knowledge to devise new applications.
 
•       Any activity classified as research and experimental development is characterised by originality; it should have investigation as a primary objective and should have the potential to produce results that are sufficiently general for humanity's stock of knowledge (theoretical and/or practical) to be recognisably increased. 
 
Need for research
 
•      To find more information and evidences
 
•      To find solutions for problems
 
•      To make effective decisions
 
Components of Research
 
Types of Research
 
•      Applied Research
        Problem solving - specific
•      Pure Research or Basic Research
        Problem solving – non specific/general
•      Scientific Research
        Systematic, controlled, empirical, and critical investigation of natural phenomena         
        guided by theory and hypothesis 
 
Types of Study
 
•      Business Research:
l   Reporting
l   Descriptive
l   Explanatory
l   Predictive
 
What is a good research?
 
•       Purpose clearly defined
•       Research process detailed
•       Research design thoroughly planned
•       High ethical standards applied
•       Limitations frankly revealed
•       Adequate analysis is made
•       Findings presented unambiguously
•       Conclusions justified
•       Recommendations/suggestion provided for future course of action
•       Researchers experience reflected
 
Questions…?
 
 
Lecture 2
 
Learning Outcomes
 
•       Styles of Thinking
l    Empirical study – observation and experience
l    Rational study – Facts, known laws or basic truth
•       Communication Process
l    Exposition – descriptive statements but no reasons provided
l    Argument – allows us to explain, interpret, defend, challenge and explore meaning
•       Argument: Two types
l    Deduction
l    Induction
 
Types of Arguments
 
•      Deduction: - Conclusive – necessarily follow from the reasons given
l   These reasons said to imply the conclusion and to represent the proof
l   It must be both true and valid
The premises (reason) given for the conclusion must agree with the real world (be true)
 
Types of Argument
 
•      Deduction: Example:
•      Premise 1 – All regular employees can be trusted not to steal
•      Premise 2: John is a regular employee
•      Conclusion: John can be trusted not to steal
 
Types of Argument
 
•      Induction: To induce is to draw a conclusion from one or more particular facts or pieces of evidence.
•      Conclusion explains the facts and facts support the conclusion
•      The conclusion in an induction, however, is merely a hypothesis
 
Types of Argument
 
•       Induction:  Example
l    Suppose you push the light switch in your room and the light fails to go on.
l    This is a fact – the light does not go on.
l    Conclusion: The light bulb has burnt out
l    Reason 1: The light should go on we you push the switch
l    Reason 2: If the bulb is burned out the light will not function
l    However there could be other reasons
l    Therefore the conclusion is a hypothesis (assumption)
 
The Combination:
Induction and Deduction
 
•       Fcat1: Push the light switch and find no light
•       Induction: ask the question “why no light?”
•       Hypothesis: Infer a conclusion (hypothesis) to answer the question “the bulb is burned out” (hypothesis)
•       Deduction: Use this hypothesis to conclude that the light will not go on when you push the switch. Know from experience that a burned out bulb will not light.
•       Refer: Figure 2-2 (page 32)
 
Understanding Theory: Concepts and Connections
 
•      Concept
•      Construct
•      Definition
•      Variables
•      Hypothesis
•      Theory
•      Models
 
Understanding Theory
 
•       Concept: set of characteristics associated with certain events, objects, or situations
        l    Concepts should be clear, commonly shared  and unambiguous
•       Importance to Research: (Concepts should be clear)
l    Estimating a family’s total income.
l   Time period
l   Before or after taxes
l   Head of the family only or all members
l   Income from other sources (salary and wages only of income in kind)
 
Understanding Theory
 
•      Constructs: Abstract Concepts
l  Personality, leadership, motivation, Love
 
l   Example: Refer Figure 2-4
 
 Understanding Theory
•       Definition:
l    To define concepts in the same meaning/synonym
l    Helps reduce confusion
l    Example: Customer, client, patron, buyer, consumer
l    These words might give different meaning in different context, therefore a clear definition is required in a research environment.
l    E.g.. Billion, market, weekend
 
Understanding Theory
 
•       Variables: a symbol to which numbers or values are assigned
l    Dichotomous – having only two values
l   Example: male or female, yes or no, employed or unemployed, married or unmarried
l    Discrete: having different values but whole number
l   Number of students in a class
l    Continuous variable: may take any value (infinite)
l   Exchange rates, income, weight of gold
Understanding Theory
 
•      Independent variable (IV)
•      Dependent variable (DV)
l   Example;
The introduction of the four-day work week (IV) will lead to increased office productivity per worker hour (DV)
Traffic
Performance in exams
 
Understanding Theory
 
•       Proposition: a statement about concepts that may be judged as true or false if it refers to observable phenomena
•       Hypothesis: A proposition tested empirically
l    Descriptive Hypothesis
l    Example: Executives in company Z have a higher than average achievement motivation
l    Relational Hypothesis
l    Example: Foreign cars are perceived by American consumers to be of better quality than domestic cars.
l    Case; American consumers
l    Variables: country of origin, perceived quality (the nature of relationship between the two variables are not specified)
l    Co relational Hypothesis (unspecified relationship)
l    Example: No country specific, no size specific, no quality indicator
l    Explanatory (causal) Hypothesis (predictable relationship): a price reduction in Japanese cars would lead to their increased demand
 A Good Hypothesis
 
•      Adequate for its purpose
•      Testable
•      Better than its rivals
•      Requiring few conditions or assumptions
 
Theory and Models
 
•       Theory: set of interrelated concepts, definitions and propositions that are advanced to explain and predict phenomena (facts)
l    Examples (weather theory page 47)
 
    The difference between theory and hypothesis is based on the level of complexity and abstraction. Theories tend to be abstract and involve multiple variables. Hypotheses tend to be simple, two variable  propositions involving concrete instances.
 
Theory and Models
 
•      Model: a representation of a system that is constructed to study some aspect of that system or the whole system.
 
•      Example: Consumer Buying Behavior Model (AIDA = Awareness, Interest, Desire, and Action)
 
Questions…?
   
 
Lecture 3
 
The Research Process
 
Refer The Research Process Model Handout
 
 
Lecture 4
 
What is a Research Proposal?
 
A proposal is an offer to produce a product or render a service to the potential buyer or sponsor.
The research proposal
presents a problem,
discusses related research efforts,
outlines the data needed for solving the problem, and
shows the design used to gather and analyze the data.
Research proposals may be Internal or External
Sections of a Research Proposal
 
Executive Summary
Problem Statement
Research Objectives
Literature Review
Importance/Benefits of the Study
Scope of the Study
Research Design
Data Analysis
Nature and Form of Results
Qualifications of Researchers
Budget
Schedule
Facilities and Resources Required
Limitations of the Study
Bibliography
Evaluation of a Proposal
 
Does the proposal offer a focused research question? Where a number of aims are stated, is the primary question clearly specified?
 Does the proposal convey evidence that the methodological issues raised by the research question have been thought through. Does the student appreciate what kind of data will be required? Is the proposed methodology justified?
 Does the proposal indicate a familiarity with the appropriate theoretical concepts needed to underpin the project?
 Is discussion of the theoretical concepts supported by reference to the appropriate literature?
 Does the proposal include an appropriate preliminary structure?
 Is there an appreciation of the business issues inherent in the proposal
Questions…?
 
Lecture 5 
 
Research Design
 
Research design is a plan for selecting the sources and types of information used to answer the research question.
 
It is a framework for specifying the relationships among the variables under study.
 
It is a blueprint that outlines each procedure from the hypotheses to the analysis of data.
 
Research Design provides answers for questions like:
 
What techniques will be used to gather data ?
What kind of sampling will be used?
How will time and cost constraints be dealt with ? Etc.
 
Major Types of Research Design
 
1.      Exploratory Studies
 
2.      Descriptive Studies
 
3.      Causal Studies
 
 
Exploratory Studies
 
Through exploration researchers develop concepts more clearly, establish priorities, develop operational definitions, and improve the final research design
 
Exploration helps is
Clarifying management dilemma
Finding the practicality of the study
Saving time, money and effort
 
Techniques of exploration may be Qualitative or Quantitative
 
Secondary Data Analysis
Experience Surveys
Focus Groups
 
Secondary Data Analysis
 
1.Organizations own data archives
2.Prior research studies
3.Published documents like books, journals, periodicals, magazines, government publications
4.Online and electronic sources
 
 
Example:  
•If looking for trends in the copper industry, then search for not only “copper consumption” or  “copper production” but also information about mines and minerals, countries producing copper, information about forecasting techniques, companies dealing in copper etc.
 
  
Experience Surveys
 
Interview experienced people about ideas, issues or aspects of the subject
 
Explore various aspects in a flexible investigation format
 
Example:
  
•When studying an automobile assembly plant, the researcher can find information, through interviews, from:
 
 New employees to the plant
Extremely high/low productive employees
First line supervisors
Managers of the plant
 
  
Focus Groups
 
A panel of 6 to 10 people led by a trained moderator who meet for 90 minutes to 2 hours exchanging ideas, feelings and experiences on a specific topic
 
 
•Highly useful in generation and evaluation of new ideas.
 
•Homogeneity within focus groups should be maintained based on the target population under study
 
•Recording and analysis of information can be done through notepads, audio-visual equipments.
 
 
Trends in Focus Groups include:
 
Telephone Focus Groups
Videoconferencing Focus Groups
Online Focus Groups (BMW Club)
 
 
 Descriptive Studies
 
The objective of a descriptive study is to learn the who, what, when, where, and how of a topic.
 
 E.g. If studying the accounts of people at a bank, the researcher might want to get information about:
 
•Number and types of accounts,
•Size of accounts,
•Number of accounts opened in last six months,
•Number of transactions and their purpose etc.
  
Descriptive studies can help develop hypothesis:
 
E.g. Why do people living far off have accounts in a particular bank
  
Hypothesis 1: They used to live close by when account was opened by them
Hypothesis 2: They live far but work close to the bank
Hypothesis 3: They use internet banking which makes them feel ‘near’ to bank.
 
Causal Studies
 
Seeks to discover the effect that a variable(s) has on another (or other), or why certain outcomes are obtained.
 
A, B AND C LEADS TO Z
B, C AND D LEADS TO Z
C, D AND E LEADS TO Z
A, B AND D DOES NOT LEAD TO Z
 
Thus there is a causal relationship between C and Z
(But there may be other external factors too)
 
 
Causal Relationships
Symmetrical
Reciprocal
Asymmetrical
  
Causal Relationships
 
Symmetrical Relationships : Two variables fluctuate together, not because of changes in the other, but due to some other third factor.
E.g. Low attendance in class and poor participation in college events events due to work pressure among evening students.  
Reciprocal Relationship: Mutual influence over each other
 E.g. Reading an advertisement leads to use of a particular brand, which in turn sensitizes user to notice and read more advertisements of that particular brand.  
Asymmetrical Relationships : Changes in one variable (Independent Variable) is responsible for changes in another variable (Dependent Variable)  
Types of Asymmetrical Relationships  
•Stimulus–Response: A price rise leads to decreased demand
•Property-Disposition: Effects of age (property) on attitude towards saving (disposition)
•Disposition-Behavior: Opinion about brand (disposition) and it’s purchase (behavior)
•Property-Behavior: Stage of family life-cycle (property) and purchase of furniture (behavior)
 
Lecture 6

Research Design Strategies and Measurement
 
§         Measurement
 
§         Scaling
 
§         Sampling
 
 
Measurement
 
What is Measurement?
 
To measure is to discover the extent, dimensions, quantity, or
capacity of something, especially by comparison with a standard.
 
Steps in Measurement
 
•            Select the events you want to measure
•            Use numbers/symbols to represent aspects of the events.
 
E.g. What is your opinion of the styling of the Jaguar Car ?
       Very Desirable  5       4        3   2      1  Very Undesirable
 
 
Errors in Measurement
 
•            The Respondent as an Error Source:  E.g. the respondent may be bored, tired, hungry, getting late for meeting etc.
 
•            Situational Factors: is anonymity being maintained?, where is the research being conducted – at home, in street?, are other people present too?
 
•            The Measurer as a Source of Error: Bias of interviewer, rephrasing of questions, prompting with smiles, nods etc -  encouraging or discouraging responses, data entry errors.
 
•            The Instrument as a Source of Error: confusing, ambiguous, poor printing, limited space, too little/too much choice, color, layout etc.
 
 Good Measurement
 
•            Validity: refers the extent to which a test measures what we actually wish to measure.
 
•            Reliability: accuracy and precision of a measurement
 
•            Practicality: is the research economic, convenient and interpretable. 
 
Weigh Yourself
 
Weigh yourself using a bathroom scale…
 
•            If the scale measures your weight correctly, then it is both reliable and valid.
 
•            If it consistently overweighs you by six pounds, then the scale is reliable but not valid.
 
•            If the scale measures erratically from time to time, then it is not reliable and not valid.
 
•            If you use a kitchen scale for weighing yourself, then it is not even practical, leave alone reliable and valid !!!
 
Scaling 
 
The procedure by which we assign numbers to opinions, attitudes,
and other concepts.
 
Types of Rating Scales (See Handout)
 
•            Dichotomous -  E.g. Yes or No
•            Multiple Choice - E.g. Single, Engaged, Married, Divorced, 
•            Likert Scale - E.g. Strongly disagree, Disagree, Neither agree nor disagree, Agree, Strongly agree
•            Semantic Differential - E.g. Modern ---------------------------- Old Fashioned
•            Importance Scale - E.g. Extremely important, Very important, Somewhat important, Not very important, Not at all important
•            Rating Scale - E.g. Excellent, Very good, Good, Fair, Poor
•            Intention-to-buy Scale - E.g. Definitely buy, Probably buy, Not sure, Probably not buy, Definitely not buy
 
•            Graphic Rating Scale - using various methods like sentence completion, word association, picture completion, thematic apperception test, story completion etc.


Sampling
 
The basic idea of sampling is that by selecting some of the elements in a population, we
may draw conclusions about the entire population.
 
Population: The total collection of elements about which we wish
                    to make some inferences.
 
Census: Counting all the elements in a population. 
•            A good sample has no bias
•            A good sample may have an error that is not more than the
       acceptable limits for the stud’s purpose.
 
 
Types of Sampling
 
Probability Sampling
 
Simple Random Sampling - Each population element has a known & equal chance of being selected in the sample. E.g Lottery
 
Complex Random Sampling:
 
•            Systematic : Every nth item is chosen in the sample, beginning with a random start for the choice of n. E.g. 4, 8, 12, 16…
 
•            Stratified : Divide population into subpopulations (strata) and use simple random on each strata. E.g. UAE divided into seven strata i.e. the seven emirates.
 
•            Cluster : Population is divided into groups, and some groups are randomly selected for study. E.g. Select any two emirates randomly from the seven clusters and study them in detail.
 
•            Double/Sequential/Multiphase: Collect some information by sample and then use this information as the basis for selecting a sub-sample. E.g. Sample of Nissan car owners, sub sample of Nissan car owners who have more than one car. 
 
Non-Probability Sampling
 
Convenience Sampling – Researchers freely choose whomever they find according to their convenience.  E.g. Friends in a class, locality etc.
 
Purposive Sampling – A non-probability sample that conforms to certain
criteria. It includes:
 
•             Judgment Sampling: Researcher selects sample members to conform to some criterion. E.g. Studying problems of employees who faced on-the-job discrimination in a study of labor problems.
 
•             Quota Sampling: Subjects are selected to conform to certain pre-designated control measures that secure a representative cross section of the population. E.g. Studying Skyline college students’ satisfaction, we could divide the population into four quotas – CIW, BAM, BAI, BAT
 
•             Snowball Sampling: referral approach to reach hard-to-find respondents. E.g. Reaching ministers through a reference of another minister. 
 
Questions…?
 
 
Lecture 7
 
Secondary Data Sources
 
Secondary Data - Data gathered and recorded by someone else prior to and for a purpose other than the current project
 
Secondary Data is often:
 
Historical
Already assembled
Needs no access to subjects
 
Advantages of Secondary Data
Inexpensive
Obtained Rapidly
Information is not Otherwise Accessible
 
Disadvantages of Secondary Data
Uncertain Accuracy
Data Not Consistent with Needs
Inappropriate Units of Measurement
Time Period Inappropriate (Outdated/Obsolete)
 
Objectives of Secondary Data Studies
 
Fact Finding
Model Building
Data Based Marketing
 
Fact Finding
Identify consumer behavior
Trend analysis
Environmental scanning
 
Model Building
Market potential
Forecasting sales
Analysis of trade areas
 
Data Based Marketing - Practice of maintaining a customer data base
Names
Addresses
Past purchases
Responses to past efforts
 
 
Data from numerous sources
 
Internal Data
Accounting information
Sales information
Customer complaints
 
External Data
Created, recorded, or generated by an entity other than the researcher’s organization
Government
Trade associations
Newspapers and journals
Libraries
The Internet
Vendors
Producers
Books and periodicals
 
Government sources
Media sources
Commercial sources
 
Market share data companies like A.C. Nielsen provide information about sales volume and brand share over time
 
Demographic and census updates—many organizations supply census updates, in easy-to-use or custom formats
 
Commercial Sources - Attitude and public opinion research—syndicated services report the findings of opinion polls
 
Consumption and purchase behavior data
 
Advertising research—readership and audience data
Secondary Data Collection Example
 
Questions…?
 
 
Lecture 8
 
Data Collection Methods
 
 
        Surveys - asking respondents
        for information using
        verbal or written questioning
 
Gathering Information Via Surveys
 
•       Quick
•       Inexpensive
•       Efficient
•       Accurate
•       Flexible
 
Tree Diagram of Total Survey Error
 
Random Sampling Error - A statistical fluctuation that occurs because of change variation in the elements selected for the sample
 
 
Errors in Data Collection
 
•       Sample bias - when the results of a sample show a persistent tendency to deviate in one direction from the true value of the population parameter
 
 
•       Respondent error - a classification of sample bias resulting from some respondent action or inaction
l  Non-response  bias
l  Response  bias
 
Non-response Bias
•       Nonrespondents - people who refuse to cooperate
•       Not-at-homes
•       Self-selection bias
l  Over-represents extreme positions
l  Under-represents indifference
 
Response Bias - a bias that occurs when respondents tend to answer questions with a certain slant that consciously or unconsciously misrepresents the truth
 
Acquiescence Bias - A category of response bias that results because some individuals tend to agree with all questions or to concur with a particular position. YES YES YES
 
Extremity Bias - A category of response bias that results because response styles vary from person to person; some individuals tend to use extremes when responding to questions.
 
Social Desirability Bias - Bias in responses caused by respondents’ desire, either conscious or unconscious, to gain prestige or appear in a different social role.
 
Interviewer Bias - A response bias that occurs  because the presence of the interviewer influences answers.
 
Auspices Bias - Bias in the responses of subjects caused by the respondents being
influenced by the organization conducting the study.
 
Administrative Error
 
Improper administration of the research task
 
Blunders
Confusion
Neglect           
Omission
 
Interviewer cheating - filling in fake answers or falsifying interviewers
•       Data processing error - incorrect data entry, computer programming, or other procedural errors during the analysis stage.
•       Sample selection error -improper sample design or sampling procedure execution.
•       Interviewer error - field mistakes
 
Time Period for Surveys
•       Cross-sectional
•       Longitudinal
 
  
Cross – Sectional Study
•       A study in which various segments of a population are sampled
•       Data are collected at a single moment in time
 
Longitudinal Study
A survey of respondents at different times, thus allowing analysis of changes over time.
•       Tracking study - compare trends and identify changes
l    consumer satisfaction
 
Consumer Panel
A longitudinal survey of the same sample of individuals or households to record (in a diary) their attitudes, behavior, or purchasing habits over time
 
 
Communicating with Respondents
 
•       Personal interviews
l   Door-to-door
l   Shopping mall intercepts
•       Telephone interviews
•       Self-administered questionnaires
l   Mail Survey
l   E-mail Survey
l   Internet Survey
           
Personal Interviews
 
Door-to-Door Personal Interview
•       Speed - Moderate to fast
•       Geographical flexibility - Limited
•       Respondent cooperation – Excellent
•       Questionnaire length - Long
•       Item non-response - Low
•       Respondent misunderstanding – Low
•       Degree of interviewer influence - High
•       Supervision of interviewers - Moderate
•       Anonymity of respondent – Low
•       Ease of call back or follow-up - Difficult
•       Cost - Highest
•       Special features - Visual materials may be shown  extended probing possible              
 
 
Mall Intercept Personal Interview
•       Speed of Data Collection - Fast
•       Geographical Flexibility - Confined, urban bias
•       Respondent Cooperation - Moderate
•       Versatility of Questioning – Extreme
•       Questionnaire length - Moderate to long
•       Item non-response -Medium
•       Respondent misunderstanding -Lowest
•       Interviewer influence of answers -Highest
•       Supervision of interviewers - Moderate to high
•       Anonymity of respondent - Low
•       Ease of call back or follow-up - Difficult
•       Cost - Moderate to high
•       Special features - Taste test, viewing of TV commercials possible
 
 
Telephone Surveys
•       Speed of Data Collection - Very fast
•       Geographical Flexibility -High
•       Respondent Cooperation - Good
•       Versatility of Questioning - Moderate
•       Questionnaire Length - Moderate
•       Item Non-response -Medium
•       Respondent Misunderstanding - Average
•       Interviewer Influence of Answer - Moderate
•       Interviewers’ Supervision - High with central location
•       Anonymity of respondent - Moderate
•       Ease of call back or follow-up- Easy
•       Cost - Low to moderate
•       Special features - Fieldwork & supervision simplified; Computer-assisted/ Voice activated interviews
 
Self-Administered Questionnaires
Mail Surveys
•       Speed - no control over return of questionnaire; slow
•       Geographical flexibility - High
•       Respondent cooperation - Moderate--poorly designed questionnaire will have low response rate
•       Questionnaire length - Varies
•       Item non-response - High
•       Respondent misunderstanding – no clarification
•       Degree of interviewer influence - None
•       Supervision of interviewers - Not applicable
•       Anonymity of respondent -High
•       Ease of call back or follow-up - Easy, but takes time
•       Cost - Lowest
 
E-Mail Questionnaire Surveys
•       Speed of data collection - Instantaneous
•       Geographic flexibility - worldwide
•       Cheaper distribution and processing costs
•       Flexible, but - Extensive differences in the capabilities of respondents’ computers and e-mail software limit the types of questions and the layout
•       E-mails are not secure and “eavesdropping” can possibly occur
•       Respondent cooperation – is e-mail “spam”?
 
Internet Surveys
 
•       Speed of data collection - Instantaneous
•       Cost effective, worldwide flexibility
•       Respondent cooperation – varies
•       Versatility of questioning - extreme
•       Questionnaire length – flexible
•       Respondent misunderstanding -high
•       Interviewer  influence of answers - none
•       Anonymity of Respondent – anonymous/known
•       Ease of Follow-up – easy if e-mail known
•       Special Features - allows graphics and streaming media but limited internet availability, poor computer skills of people
 
Determine Appropriate Technique
 
There is no best form of survey; each has advantages and disadvantages.
 
•       Is the assistance of an interviewer necessary?
•       Are respondents interested in the issues being investigated?
•       Will cooperation be easily attained?
•       How quickly is the information needed?
•       Will the study require a long and complex questionnaire?
•       How large is the budget?
•       Do Pretesting - A trial run with a group of respondents to iron out fundamental problems in the instructions of survey design
 
Questions…?
 
 

 

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