Conjoint by idrees iugc


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Conjoint by idrees iugc

  1. 1. What is conjoint analysis?<br />Conjoint Analysis is an advanced multivariate technique that helps to identify what value most in making decisions.<br />1<br />
  2. 2. Dependence model<br />2<br />Y = X 1 +X2+X3+……….+Xn<br />Dependent variable=(nonmetric or metric) <br />Independent variable(nonmetric)<br />
  3. 3. The flexibility and uniqueness of conjoint analysis arise primarily from the following:<br />An ability to accommodate either a metric or a nonmetric dependent variable<br />The use of only categorical predictor variables<br />Quite general assumptions about the relationships of independent variables with the depend­ent variable<br />As we will see in the following sections, conjoint analysis provides the researcher with substantial insight into the composition of consumer preferences while maintaining a high degree of realism.<br />3<br />
  4. 4. Hypothetical example of conjoint analysis<br />Analysis for hypothetical product with three attribute.<br />4<br />
  5. 5. Stimuli Description And Respondent Ranking For Conjoint Analysis Of Industrial Cleanser Example<br />5<br />
  6. 6. Calculation of part worth<br />Step#1:square the deviation<br />Step#2:calculate the standardizing value<br />Step#3:standerdize each square<br />Step#4:estimate the part worth<br />6<br />
  7. 7. Average ranks and deviations for respondent 1 and 2<br />7<br />
  8. 8. Average ranks and deviations for respondent 1 and 2<br />8<br />
  9. 9. 9<br />
  10. 10. The managerial use of conjoint analysis<br />Define the object<br />Show the relative contribution<br />use estimate of consumer<br />Isolate group of potential customer<br />Identify marketing opportunities<br />10<br />
  11. 11. OBJECTIVES<br />11<br />11<br />
  12. 12. Today it is used in….<br />Social sciences and applied sciences including<br />marketing, product management, and operations research. It is used frequently in testing customer acceptance of new product designs, in assessing the appeal of advertisements and in service design. It has been used in product positioning, <br />12<br />
  13. 13. Research question: To what extent does each component (factor) contribute to the total utility of a product?Total utility = Sum of all partial utilitiesData base of the Conjoint Analysis are preferences of the interviewed subject Important application: Design of a new product according to the requirements of the market<br />13<br />
  14. 14. 14<br />
  15. 15. Advantages of conjoint analysis<br />estimates psychological tradeoffs that consumers make when evaluating several attributes together <br />measures preferences at the individual level <br />uncovers real or hidden drivers which may not be apparent to the respondent themselves <br />realistic choice or shopping task <br />able to use physical objects <br />if appropriately designed, the ability to model interactions between attributes can be used to develop needs based segmentation<br />15<br />
  16. 16. Disadvantages of conjoint analysis<br />designing conjoint studies can be complex <br />with too many options, respondents resort to simplification strategies <br />difficult to use for product positioning research because there is no procedure for converting perceptions about actual features to perceptions about a reduced set of underlying features <br />respondents are unable to articulate attitudes toward new categories, or may feel forced to think about issues they would otherwise not give much thought to <br />poorly designed studies may over-value emotional/preference variables and undervalue concrete variables <br />does not take into account the number items per purchase so it can give a poor reading of market share <br />16<br />
  17. 17. STAGE 1: THE OBJECTIVES OF CONJOINT ANALYSIS<br />To determine the contributions of predictor variables and their levels in the determination of consumer preferences. <br />To establish a valid model of consumer judgments. <br />Defining the total Utility of the Object<br />Specifying the Determinant Factors<br />17<br />
  18. 18. STAGE 2: THE DESIGN OF A CONJOINT ANALYSIS<br />Selecting a Conjoint Analysis Methodology<br />Traditional conjoint analysis<br />Adaptive conjoint method <br />Choice-based conjoint approach <br />18<br />
  19. 19. 19<br />
  20. 20. STAGE 3: ASSUMPTIONS OF CONJOINT ANALYSIS<br />Normality,<br /> Homoscedasticity,<br /> Independence <br />20<br />
  21. 21. STAGE 4: ESTIMATING THE CONJOINT MODEL AND ASSESSING OVERALL FIT<br />Selecting an estimation technique<br />Traditional estimation approaches <br />Extensions to the basic estimation process <br />21<br />
  22. 22. Estimated Part-Worths<br />22<br />
  23. 23. STAGE 5: INTERPRETING THE RESULTS<br />Examining the Estimated Part-Worths<br />ENSURING PRACTICAL RELEVANCE <br />Factors Contributing to Reversals. <br />Identifying Reversals<br />Assessing the Relative Importance of Attributes<br />23<br />