::
::     Which candidate will you ‘buy’?     Conjoint Analysis, from marketing studies to electoral research     Janko Hočev...
:: Agenda  Part I.  • Intro to Conjoint Analysis      - Idea      - History      - Flavors  Part II.  • Conjoint Analysis ...
::     Part I.     Intro to Conjoint Analysis               Ask people what they want, and they say, “the best of everythi...
::     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.               ...
::     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.               ...
::     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.               ...
::      John     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.     ...
::      Mary     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.     ...
::      Bubba     Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008.    ...
::           Romantic                                       3,9               Sexy                                      3,...
::     • Ask Direct Questions about preference:         -   What brand do you prefer?         -   What Interest Rate would...
:: CA Idea  • People cannot reliably express how they weight separate features of the    product/service  • But can evalua...
:: CA Short History  • Based on the work by:       - Luce & Tukey in 60‟s             Luce, D. & J. Tukey ,1964. Simultane...
:: Two broad types of CA  • “Traditional” CA      - uses data collected from sequential ratings, rankings or graded (rated...
:: CA Terminology  • Attribute       - A feature of product/service: Brand, Price, Pack type,...  • Attribute Level       ...
:: Design  • Orthogonality:      - each level appears an equal number of times with every other level of different        ...
:: CA Research Process  • Identify attributes that underlie consumer preferences for products/services.  • Select levels o...
:: CA Data Analysis  • Parameter estimates      - OLS      - MNL (HB)  • Simulations      -   First choice rule      -   P...
:: Basic Flavors  • CVA – Conjoint Value Analysis (traditional)      -   One or two full profile concepts      -   One des...
:: Basic Flavors  • ACA – Adaptive Conjoint Analysis      -   Two partial profile concepts      -   Concepts complexity ma...
:: Starting point                    22
:: Starting point                    23
:: Paired comparison section                               24
:: Calibration part                      25
::     • CBC – Choice Based Conjoint         -   Two or more concepts         -   Full or partial profile         -   Mult...
:: A Choice Task                   27
:: Alternative specific                          28
:: Partial profile                     29
:: What can we do with Conjoint data?  • Base case predictions linked with descriptive data       - who chooses what?  • G...
::     Part II.     Conjoint Analysis in the context of political research            Case studies:            Slovenian p...
:: The premise  • The outcome of presidential or party contest is influenced by many factors       - party identification,...
::     Slovenian parliamentary elections 2000           Client: The Mladina Magazine
:: Slovenian parliamentary elections 2000  • Determine issues relative importance to voters, the most and least popular   ...
:: Slovenian parliamentary elections 2000  5 attributes & a total of 14 levels:  • History:                               ...
:: Slovenian parliamentary elections 2000   Relative importance of issues                            Lustration           ...
-50,0                                                                               -40,0                                 ...
:: Slovenian parliamentary elections 2000  • Max – Min horse race      - Max purchase likelihood = 62,43%      - Min purch...
10                                                                                             12                         ...
:: Slovenian parliamentary elections 2000  • Issues positions to avoid / to put out       - Where? (geography, not really ...
::     Slovenian presidential elections 2002           Client: FDV
:: Slovenian presidential elections 2002  • Determine issues relative importance to voters, the most and least popular    ...
:: Slovenian presidential elections 2002  Political issues:                                       Demographic profile:  3 ...
:: Slovenian presidential elections 2002    Relative importance of issues                                 Relative importa...
-40,0                                                                                                         -20,0       ...
:: Slovenian presidential elections 2002   Winner Max purchase likelihood = 62,67%, ABS % gain / loss     0,0             ...
:: Slovenian presidential elections 2002  Official result (2nd round)  • J. Drnovšek = 56,54 %  • B. Brezigar = 43,46 %  S...
::     “Life is one big conjoint analysis . . . one tradeoff      after another.”     – Paul E. Green                     ...
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2009 which candidate will you buy cj v3.0 summer school in methods and techniques ljubljana 2009

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2009 which candidate will you buy cj v3.0 summer school in methods and techniques ljubljana 2009

  1. 1. ::
  2. 2. :: Which candidate will you ‘buy’? Conjoint Analysis, from marketing studies to electoral research Janko Hočevar & Toni Gril Summer School in Methods and Techniques 2009
  3. 3. :: Agenda Part I. • Intro to Conjoint Analysis - Idea - History - Flavors Part II. • Conjoint Analysis in the context of political research • Case studies: - Slovenian parliamentary elections 2000 - Slovenian presidential elections 2002 • Q&A 3
  4. 4. :: Part I. Intro to Conjoint Analysis Ask people what they want, and they say, “the best of everything”. Ask them what they would like to spend, and they say, “a little as possible”. – Bryan K. Orme
  5. 5. :: Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 5
  6. 6. :: Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 6
  7. 7. :: Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 7
  8. 8. :: John Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 8
  9. 9. :: Mary Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 9
  10. 10. :: Bubba Slide borrowed from: Batsell R., Chrzan K., Baggett S., SawtoothSoftware Conference, Barcelona 2008. 10
  11. 11. :: Romantic 3,9 Sexy 3,8 Entertaining 4,4 Exciting 4,2 Calm 4,6 Laid back 4,2 Outdoorsy 4,2 Family-Oriented 4,5 Fancy 4,0 1 2 3 4 5 • Bias toward high importance in ratings • Lack of discrimination • Different respondents use the scale differently 11
  12. 12. :: • Ask Direct Questions about preference: - What brand do you prefer? - What Interest Rate would you like? - What Annual Fee would you like? - What Credit Limit would you like? • Answers often trivial and unenlightening (e.g. respondents prefer low fees to high fees, higher credit limits to low credit limits) 12
  13. 13. :: CA Idea • People cannot reliably express how they weight separate features of the product/service • But can evaluate the overall desirability of a complex product/service profile – a more realistic approach - Based on a function of the value of its separate (yet conjoined) parts • We can break product/services into features (attributes & their levels) • Based on how people evaluate the combined features (profiles) we can deduce the preference scores people might have assigned to individual features of the product/service - That are the result of those overall evaluations • A back-door, decompositional approach for estimating people‟s preferences, rather than an explicit approach of simply asking people to rate, rank, .. separate features 13
  14. 14. :: CA Short History • Based on the work by: - Luce & Tukey in 60‟s Luce, D. & J. Tukey ,1964. Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psycchology - McFadden in 70‟s - Discrete choice methods McFadden, D. 1974. Conditional logit analysis of qualitative choice behavior. In P. Zarembka (ed.), Frontiers in Econometrics, pp. 105-142. New York: Academic Press. • Early 70s - work of P. Green: Green, P. & V. Rao 1971, August. Conjoint measurement for quantifying judgemental data. Journal of Marketing Research - work of R. Johnson: • Johnson, R. 1974, May. Trade-off analysis of consumer values. Journal of Marketing Research • 80‟s - Green & Wind: application of conjoint analysis to help Marriott design its new Couryard Hotel • S. Herman & Bretton-Clark software released software system - R. Johnson (at Sawtooth Software) released a software system Adaptive Conjoint Analysis (ACA) • 90‟s - Discrete Choice overtakes Traditional Conjoint methods • Commercial software released (SawtoothSoftware CBC) • Application of of hierarchical Bayes (HB) methods to estimate individual-level models from discrete choice data (led by G. Allenby of the Ohio State University) • 00‟s and beyond - Maximum-Difference Scaling - Adaptive Choice Based Conjoint (ACBC) software released by SawtoothSoftware in 2009 14
  15. 15. :: Two broad types of CA • “Traditional” CA - uses data collected from sequential ratings, rankings or graded (rated) paired comparisons followed by an analysis using simple linear models - Use of “choice simulators” to predict individuals‟ preferences and choices • No Choices are observed • Choice-based Conjoint Analysis (CBC). - uses data collected from a series of choices (from “choice sets”), followed by an analysis using probabilistic choice models. - Use of choice simulators to predict individuals‟ preferences and choices • Choices are observed 15
  16. 16. :: CA Terminology • Attribute - A feature of product/service: Brand, Price, Pack type,... • Attribute Level - A value or range of variation for an attribute: • Coca Cola, Pepsi,..., 0.5€, 0.6€,..., 0,33 l Can, 0,5 l Plastic Bottle • Profile / Concept - A combination of attribute levels: Coca-Cola at 0.5€ in a 0,33 l Can • Design - the attribute combinations that make up product/service profiles/concepts and how those profiles/concepts are combined within tasks. 16
  17. 17. :: Design • Orthogonality: - each level appears an equal number of times with every other level of different attributes. (zero correlation between pairs of attributes) • Level Balance: - within each attribute, each level appears an equal number of times. • Minimal Overlap: - achieve maximum variation across levels of an attribute within a (choice) task (try not to repeat a level). • Designs which are orthogonal and balanced are optimally efficient. • In the real world: well-balanced, "nearly orthogonal“ designs 17
  18. 18. :: CA Research Process • Identify attributes that underlie consumer preferences for products/services. • Select levels or values of each attribute to represent ranges of variation in real markets • Create product or service profiles generated from some type of experimental design • Administer to a sample of respondents • Analyze the data - Relative importance - Utilities or Part-Worths - Simulations - Optimizations 18
  19. 19. :: CA Data Analysis • Parameter estimates - OLS - MNL (HB) • Simulations - First choice rule - Purchase Likelihood - Share of Preference - Randomized First Choice 19
  20. 20. :: Basic Flavors • CVA – Conjoint Value Analysis (traditional) - One or two full profile concepts - One design / experiment - Rating - OLS - Individual parameter estimation 20
  21. 21. :: Basic Flavors • ACA – Adaptive Conjoint Analysis - Two partial profile concepts - Concepts complexity manipulation - Unique individual design / experiment - Starting point from direct (self-explicated) input - Rating - OLS - Individual parameter estimation 21
  22. 22. :: Starting point 22
  23. 23. :: Starting point 23
  24. 24. :: Paired comparison section 24
  25. 25. :: Calibration part 25
  26. 26. :: • CBC – Choice Based Conjoint - Two or more concepts - Full or partial profile - Multiple designs / experiments - Alternative specific designs - Fixed / Constant alternatives • (e.i. I wouldn‟t buy anything; I‟d stay with my current service; NONE) - Choices, allocations (Constant Sum allocation) - Group / Semi-individual parameter estimation (MNL HB) 26
  27. 27. :: A Choice Task 27
  28. 28. :: Alternative specific 28
  29. 29. :: Partial profile 29
  30. 30. :: What can we do with Conjoint data? • Base case predictions linked with descriptive data - who chooses what? • Great input for segmentation (cluster analysis, latent class,...) • Simulations (what if?) - Sensitivity analysis (what if? systematically) • Optimizations (best configurations) • A simulator mimics a certain situation, that may or may not happen in reality (like a flight simulator). • The purpose is to estimate the probable effects of products/services. • For this, the simulator needs input - Data to describe the situation (scenario definition) - Data on how consumers react (utilities from conjoint) - Definition of the calculation • Changing (part of) this data will result in new scenarios and new output 30
  31. 31. :: Part II. Conjoint Analysis in the context of political research Case studies: Slovenian parliamentary elections 2000 Slovenian presidential elections 2002
  32. 32. :: The premise • The outcome of presidential or party contest is influenced by many factors - party identification, candidate personality, campaign strategy and tactics, financing, etc. • In a real „purchase situation‟, „consumers‟ do not make choices based on a single attribute. Consumers examine a range of features or attributes and then make judgments or trade-offs to determine their final purchase choice. • This is just as true for the „choice‟ made in political situations, such as assessing the viability of a candidate, determining the support of various political, economic, social issues. Product: • Candidate (not „branded‟) / Political Party (not „branded‟ but with issues positions) • Political Parties / Candidates are: - Managed as Products/Services - Advertised as Poroduct/Services - Communicated as Products/Services 32
  33. 33. :: Slovenian parliamentary elections 2000 Client: The Mladina Magazine
  34. 34. :: Slovenian parliamentary elections 2000 • Determine issues relative importance to voters, the most and least popular position on each issue, the impact of a given position on voting behavior, and the relative strength of different candidate profiles. • To do that, we asked each respondent to rate a series of hypothetical pair of candidates who have either a „liberal‟, „centrist‟, or „conservative‟ position on each of 5 issue categories. • Issues were the subject of debate in the campaign, and the position descriptions were determined from positions that the candidates have actually taken and were exposed in the media. • C.A.T.I., n = 601 • ACA 34
  35. 35. :: Slovenian parliamentary elections 2000 5 attributes & a total of 14 levels: • History: • Welfare - Past injustices are settled, what is important - Every single individual should take care of is the future his/hers social welfare (health care, pension - There is no future unless we settle past welfare,...) injustices - The state and every single individual should - The future must be a priority, but we must take care of social welfare never forget the past injustices - The state should take care of the whole social welfare of its citizens • Roman-Catholic church • Lustration - RCC should be included in the political - Those who were appointed to management decision making positions by the former political system, - RCC should be consulted only with the should stay there if they are capable and essential political issues qualified - RCC must be excluded from political sphere - We should remove all those who were appointed to management positions by the • Equalitarianism former political system - The state should determine maximum wage of all managers in all companies - The state should determine maximum wage only of managers in state owned companies • 10 pair - The state should not interfere with managers • 2 attributes in pair wages 35
  36. 36. :: Slovenian parliamentary elections 2000 Relative importance of issues Lustration 15,5% Welfare 22,9% Equalitarianism 19,7% Roman-Catholic church 21,6% History 20,3% 36
  37. 37. -50,0 -40,0 -30,0 -20,0 -10,0 0,0 10,0 20,0 30,0 Past injustices are settled, future is important 2,6 There is no future -20,4 History The future must be a priority 17,8 Utilities / Part Worths RCC should be included -22,7 RCC should be consulted 8,3 RCC must be excluded 14,4 Roman-Catholic church The state should determine maximum wage -0,3 :: Slovenian parliamentary elections 2000 The state should determine maximum wage only state owned companies 9,5 Equalitarianism The state should not interfere -9,2 Every single individual should take care -39,9 The state and every single individual should take care 19,7 The state should take care of the Welfare whole social welfare 20,1 Stay if they are capable and qualified 20,9 Lustration We should remove all37 -20,9
  38. 38. :: Slovenian parliamentary elections 2000 • Max – Min horse race - Max purchase likelihood = 62,43% - Min purchase likelihood = 20,47% - Max : Min | 80,6% : 19,4% 38
  39. 39. 10 12 0 2 4 6 8 -16 -14 -12 -10 -8 -6 -4 -2 0 Past Past injustices injustices are settled, are settled, 2,58 -3,63 There is no There is no future 0 future The future -8,62 The future History History must be a must be a 0 priority 5,4 priority RCC RCC should be should be 0 included included -8,44 RCC RCC should be should be Min = 20,47%, ABS % gain / loss Max = 62,43%, ABS % gain / loss consulted consulted 4,55 -1,87 RCC must RCC must be be 0 excluded excluded 5,36 Roman-Catholic church Roman-Catholic church The state The state should should determine determine 1,95 -1,82 The state The state :: Slovenian parliamentary elections 2000 should should 0 determine determine 2,66 The state The state should not should not 0 Equalitarianism Equalitarianism interfere interfere -4,15 Every Every single single 0 individual individual -13,5 The state The state and every and every single single 9,89 -0,11 The state The state Welfare Welfare should take should take 0 care of the care of the 10,31 Stay if they Stay if they are capable are 0 and capable 6,8 We should We should Lustration Lustration remove all 0 remove all39 -10,16
  40. 40. :: Slovenian parliamentary elections 2000 • Issues positions to avoid / to put out - Where? (geography, not really applicable in Slovenia), to whom? (gender, age,...) ... • Voter‟s profile • (Respondent) Party identification profile • Handling “don‟t knows” or “refused to answer” modalities 40
  41. 41. :: Slovenian presidential elections 2002 Client: FDV
  42. 42. :: Slovenian presidential elections 2002 • Determine issues relative importance to voters, the most and least popular position on each issue, the impact of a given position on voting behavior, and the relative strength of different candidate profiles. - To do that, we asked each respondent to rate a series of hypothetical pair of candidates who have either a „liberal‟, „centrist‟, or „conservative‟ position on each of four issue categories. - Issues were the subject of debate in the campaign, and the position descriptions were determined from positions that the candidates have actually taken and were exposed in the media. • Determine relative importance of demographic characteristics of a presidential candidate and the impact on voting behavior. - To do that, we asked each respondent to rate a series of hypothetical pair of candidates described with demographic characteristics. • C.A.T.I., issues n = 750, demo n = 786 • ACA 42
  43. 43. :: Slovenian presidential elections 2002 Political issues: Demographic profile: 3 attributes & a total of 7 levels: 3 attributes & a total of 8 levels • History: • Gender - Past injustices are settled, what is important - Male is the future - Female - There is no future unless we settle past • Age injustices - 40 yrs or younger • Roman-Catholic church - Between 40 and 60 yrs old - RCC should take active part in the political - Older than 60 yrs decision making • Background - RCC should be consulted only with the - In Politics essential political issues - In Economy - RCC must be excluded from political sphere - In other profession (health, science, culture, • Foreign policy education, sport,...) - Joining NATO, EU and to open way for foreign investments takes careful • 12 pair consideration of every step we make • 2 / 3 attributes in pair - There should be no hesitation with joining NATO, EU and to open way for foreign investments • 10 pair • 2 / 3 attributes in pair 43
  44. 44. :: Slovenian presidential elections 2002 Relative importance of issues Relative importance of demo Gender Background 17,1% Roman-Catholic 37,7% church History 46,0% 29,5% Foreign policy Age 24,5% 45,2% 44
  45. 45. -40,0 -20,0 0,0 20,0 40,0 60,0 80,0 Past injustices are settled, future is important 26,1 There is no future History -26,1 RCC should take active part -33,3 RCC should be consulted Issue Utilities / Part Worths -24,8 RCC must be excluded 58,2 Roman-Catholic church NATO, EU, ... Careful consideration of every step 25,9 NATO, EU,... No hesitation Foreign policy :: Slovenian presidential elections 2002 -25,9 -60,0 -40,0 -20,0 0,0 20,0 40,0 60,0 Male 7,1 Female Gender -7,1 40 yrs or younger -10,2 Between 40 and 60 yrs old 51,5 Age Older than 60 yrs -41,3 In Politics -0,3 In Economy 19,745 Background Demo Utilities / Part Worths In other profession -19,4
  46. 46. :: Slovenian presidential elections 2002 Winner Max purchase likelihood = 62,67%, ABS % gain / loss 0,0 0,0 0,0 0,0 -2,0 -3,0 -4,0 -4,1 -6,0 -8,0 -7,1 -10,0 -12,0 -11,2 -14,0 -16,0 -16,5 -18,0 Male Female 40 yrs or Between 40 Older than In Politics In Economy In other younger and 60 yrs 60 yrs profession old Gender Age Background Male – Female horse race (same profile; 40-60 yrs old, background in economy) - Randomized First Choice rule: • Male : Female | 52,9% : 47,1% 46
  47. 47. :: Slovenian presidential elections 2002 Official result (2nd round) • J. Drnovšek = 56,54 % • B. Brezigar = 43,46 % Simulation: • J. Drnovšek (Male, 40-60 yrs old, background in politics): 56,20% • B. Brezigar (Female, 40-60 yrs old, background in other profession /public prosecutor/): 43,80% 47
  48. 48. :: “Life is one big conjoint analysis . . . one tradeoff after another.” – Paul E. Green 48

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