Business research


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Business research

  1. 1. Business Research & Field Survey Professor B. P. Singh Chairman Delhi School of Professional Studies & Research Formerly, Head & Dean Faculty of Commerce & Business Delhi School of Economics University of Delhi, Delhi 1
  2. 2. Agenda for Presentation • • • • • • • Business Research: Concept Determining When To Conduct Research Some Important Distinctions Research Process Sources of Data Questionnaire Method Measurement and Scaling 2
  3. 3. Cont…. • • • • Criteria for Good Measurement Sampling Criteria for Good Research Application of Research in: – Finance – Human Resource – Marketing – Production & Operations Management 3
  4. 4. Business Research • An organized, systematic, data based, critical, objective, scientific enquiry or investigation into a specific problem, undertaken with the purpose of finding answers or solutions to it. 4
  5. 5. Determining when to conduct Research 5
  6. 6. Quantitative vs. Qualitative • Quantitative Research: – Use numbers, statistics, emphasis on measurement, precision, prediction • Qualitative Research: – Emphasis on verbal descriptions – Reflect the world as seen by participant (Focus on the ‘lived experience’ of participant) – Use word-for-word quotations when reporting findings – Typically employs small samples 6
  7. 7. Descriptive vs. Explanatory • Descriptive: goal is to describe some aspect of society – Census: description of entire population – Sample: a small portion of the population who are selected to represent the population • Explanatory: goal is to explain relationships – E.g.: why is that females who select gender non-traditional careers come from higher socio-economic backgrounds 7
  8. 8. Basic vs. Applied • Basic Research: – Attempts to expand the limits of knowledge – Not directly involved in the solution to a pragmatic problem • Applied Research: – Conducted when a decision must be made about a specific real-life problem 8
  9. 9. Research Process 9
  10. 10. Sources of Data DATA SOURCES PRIMARY METHODS SECONDARY METHODS INTERNAL Fully Processed Need Further Analysis EXTERNAL Published Electronic Database Syndicated Sources 10
  11. 11. Classification of data • Primary data is original, problem or project specific, and collected for the specific objectives and needs spelt out by the researcher. The authenticity and relevance is reasonably high. • Secondary data is information that is not topical or research specific and has been collected and compiled by some other researcher or investigative body. It is recorded and published in a structured format. 11
  12. 12. Uses of secondary data Problem identification and formulation stage: past data and information on the topic under study. Can be extremely useful in developing a conceptual framework for investigation. Hypotheses designing: earlier work done on the topic and market data as well as industry trends and market facts could help in developing assumptions that can be translated into testable hypotheses for the study. 12
  13. 13. Cont…. Sampling considerations: respondent-related databases are important sources of respondent statistics and relevant contact details. Primary base: can be used to design questionnaires for the primary study. Validation and authentication board: earlier records and studies as well as data pools can also be used to support or validate the information collected through primary sources. 13
  14. 14. Internal data sources Company records: historical as well as current manufacturing information, process and policy documents Employee records: demographic data sets, performance appraisals & grievance data Sales data: cash register receipts, salespersons call records, sales invoices and sales reports Other sources: customer databases, CRM 14
  15. 15. External data sources • Published data: data that is in or on public domains, which could be compiled by public or private sources Government sources: census data, other documented and available government publications Other data sources: essentially nongovernment sources like books, periodicals, guides and directories, Indices and standardized non-government statistical data 15
  16. 16. Qualitative vs Quantitative Methods of Data Collection Research stage Study objective Qualitative Quantitative Exploratory, Definite, conclusive & investigative predictive Research design Loosely structured Structured, controlled conditions Sampling plan Small samples Large/representative samples Type of Loosely structured Formatted & approach structured Data analysis Textual & non- Statistically tested & statistical authenticated Study Explanatory & Conclusive & action deliverables supportive oriented 16
  17. 17. Questionnaire Method This is the simplest and most often used method of primary data collection There is a pre-determined set of questions in a sequential format Is designed to suit the respondent’s understanding and language command Can be conducted to collect useful data from a large population in a short duration of time 17
  18. 18. Cont…. • The spelt out research objectives need to be converted into specific questions • It must be designed to engage the respondent and encourage meaningful response • The questions should be designed in simple language and be self-explanatory 18
  19. 19. Converting the research objectives into information areas Research Research Questions Objectives Variables to be studied What is the nature of plastic bag usage amongst the people in the NCR (National Capital Region)? Usage behavior Demographic details •Disposal of plastic bags •To identify the different used of plastic bags •To find our the method of disposal of plastic bags •To find out what is the level of consciousness that people have about the environment Information (Primary Required) •Uses of Plastic bags Population to be studied Consumers Relations
  20. 20. Cont…. Research Questions Research Objectives Variables to be studied Information (Primary Required) What is the •To find out Environmental •Respondent level of whether they consciousness attitudes and environment understand Effect of perceptions consciousnes how plastic Plastic bag towards the s amongst bags can be usage environment them? harmful for •Perception the about the environment impact of plastic bags •To identify strategies to on the discontinue environment plastic bag usage Population to be studied Consumer Retailer
  21. 21. Cont…. Research Questions What measures can be taken to encourage people not to use plastic bags? Research Objectives Variables to Information be studied (Primary Required) Corporation indicative laws (if any) measures for Attitudinal encouraging change the general strategies public to discontinue the use of plastic bags Population to be studied Policy maker consumer retail
  22. 22. Questionnaire Administration • Physical characteristics of the questionnaire • Pilot testing the questionnaire • Preparing the final draft of the questionnaire • Administering the questionnaire 22
  23. 23. Questionnaire Method Advantages • Adaptability • Assurance of anonymity • Cost- & time-effective Disadvantages • Limited applicability • Skewed sample • Return ratio • Clarification • Spontaneity of response • Scope of coverage 23
  24. 24. Meaning of Measurement and Scaling Measurement: The term ‘measurement’ means assigning numbers or some other symbols to the characteristics of certain objects. When numbers are used, the researcher must have a rule for assigning a number to an observation in a way that provides an accurate description. Scaling: Scaling is an extension of measurement. Scaling involves creating a continuum on which measurements on objects are located. 24
  25. 25. Types of Measurement Scale Nominal scale: there must be distinct classes but these classes have no quantitative properties. Therefore no comparison can be made in terms of one being higher category than the other. Example: there are two classes for the variable gender – males and females. There are no quantitative properties for this variable or these classes and, therefore, gender is a nominal variable. Country of origin, gender, married or single. 25
  26. 26. Cont…. Ordinal scale: these are distinct classes but these classes have a natural ordering or ranking. The differences can be ordered on the basis of magnitude. For example: final position of horses in a race is an ordinal variable. The horses finish first, second, third, forth, and so on. The difference between first and second is not necessarily equivalent to the difference between second and third, or between third and fourth. 26
  27. 27. Cont…. Interval scale: it is possible to compare difference in magnitude, but importantly the zero point does not have a natural meaning. It captures the properties of nominal and ordinal scales – used by most psychological test. Designates and equal-interval ordering – The distance between, for example, a 1 or a 2 is the same as the distance between a 4 or a 5. 27
  28. 28. Cont…. Example: Celsius temperature is an interval variable. It is meaningful to say that 25 degrees celsius is 3 degree hotter than 22 degrees celsius, and that 17 degrees celsius is the same amount hotter (3 degrees) than 14 degrees celsius. Notice, however, that 0 degree celsius does not have a natural meaning. That is, 0 degree celsius does not mean the absence of heat! 28
  29. 29. Cont…. Ratio scale: captures the properties of the other types of scales, but also contains a true zero, which represents the absence of the quality being measured. Example: heart beats per minute has a very natural zero point. Zero means no heart beats. Weight (in grams) is also a ratio variable. Again, the zero value is meaningful, zero means the absence of weight. 29
  30. 30. Criteria for good measurement Reliability Reliability is concerned with consistency of the instrument. A reliable test is one that yields consistent scores when a person takes the test two alternative forms of the test or when an individual takes the same test on two or more different occasions. 30
  31. 31. Cont…. Validity The validity of a scale refers to the ability to measure what it is supposed to measure and the extent to which it predicts outcomes. 31
  32. 32. Sampling • Population: Population refers to any group of people or objects that form the subject of study in a particular survey and are similar in one or more ways. • Sampling frame: Sampling frame comprises all the elements of a population with proper identification that is available to us for selection at any stage of sampling. • Sample: It is a subset of the population. It comprises only some elements of the population. 32
  33. 33. Cont…. • Sampling unit: A sampling unit is a single member of the sample. • Sampling: It is a process of selecting an adequate number of elements from the population so that the study of the sample will not only help in understanding the characteristics of the population but will also enable us to generalize the results. • Census (or complete enumeration): An examination of each and every element of the population is called census or complete enumeration. 33
  34. 34. Sampling & Non-Sampling Errors Sampling error: This error arises when a sample is not representative of the population. Non-sampling error: This error arises not because a sample is not a representative of the population but because of other reasons. Some of these reasons are listed below: Plain lying by the respondent. The error can arise while transferring the data from the questionnaire to the spreadsheet on the computer. There can be errors at the time of coding, tabulation and computation. Population of the study is not properly defined. Respondent may refuse to be part of the study. There may be a sampling frame error. 34
  35. 35. Sampling Design Probability Sampling Design - Probability sampling designs are used in conclusive research. In a probability sampling design, each and every element of the population has a known chance of being selected in the sample. Types of Probability Sampling Design Simple random sampling Systematic sampling Stratified random sampling Cluster sampling 35
  36. 36. Cont…. Non-probability Sampling Designs - In case of nonprobability sampling design, the elements of the population do not have any known chance of being selected in the sample. Types of Non-Probability Sampling Design Convenience sampling Judgemental sampling Snowball sampling or chain-referral sampling Quota sampling 36
  37. 37. Criteria For Research MUST have: a clearly stated research purpose/ objective MUST have: a sequential plan of execution MUST have: a logical and explicitly stated justification for the selected methods MUST have: an unbiased and neutral method of conduct and reporting MUST have: complete transparency and ethical conduction of the research process MUST have: provision for being reliable & replicable 37
  38. 38. Research Applications In Marketing • Market & consumer analysis • Product research • Pricing research • Promotional research • Place research 38
  39. 39. Research Applications In Finance • Asset pricing, capital markets and corporate finance • Financial derivatives and credit risk modeling research • Market-based accounting research • Auditing and accountability • Other areas: financial forecasting, behavioural finance, volatility analysis 39
  40. 40. Research Applications In Human Resources Training & development studies Selection and staffing studies Performance appraisal–design and evaluation Organization planning and development Incentive and benefits studies Emerging areas–critical factor analysis, employer branding studies 40
  41. 41. Research Applications In Production & Operations Management Operation planning and design Demand forecasting and demand estimation Process planning Project management and maintenance effectiveness studies Logistics and supply chain-design and evaluation Quality estimations and assurance studies 41
  42. 42. Thank You All For the Patient Listening ! For Further Queries Contact us at : 42