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Year 12/2014 
Issue 22

Conjoint Analysis As A Measurement Method Of Preferences For Delayed Lotteries – Research Announcement

Marcin Czupryna
Uniwersytet Ekonomiczny w Krakowie

Elżbieta Kubińska
Uniwersytet Ekonomiczny w Krakowie

Łukasz Markiewicz
Akademia Leona Koźmińskiego

12/2014 (22) Decyzje

DOI 10.7206/DEC.1733-0092.34

Abstract

The major purpose of the paper is considering the possibility of using conjoint analysis in postponed lotteries research. The role of conjoint measurement theory in mathematical psychology is reviewed. Next, the conjoint data analysis method is elaborated; this method is derived from conjoint measurement theory and it is very popular in market research. The focus is on two versions: traditional Conjoint Value Analysis (CVA) and Choice-Based Conjoint (CBC). The results of this research show that changes in the scope of the likelihood of payment, rather than changes in the dimension of deferral, more strongly determine the choices made.

References

  1. Allenby, G.M., Arora, N., Ginter, J.L. (1995). Incorporating Prior Knowledge into the Analysis of Conjoint Studies. Journal of Marketing Research, 32(2), 152–162. DOI: 10.2307/3152044 [Google Scholar]
  2. Appelt, K., Hardisty, D., Weber, E. (2011). Asymmetric discounting of gains and losses: A query theory account. Journal of Risk and Uncertainty, 43(2), 107–126. DOI: 10.1007/s11166-011-9125-1 [Google Scholar]
  3. Bąk, A. (2013a). Retrieved 23.10.2013, from http://keii.ue.wroc.pl/conjoint/ [Google Scholar]
  4. Bąk, A. (2013b). Mikroekonometryczne metody badania preferencji konsumentów z wykorzystaniem programu R. Warszawa: Wydawnictwo C.H. Beck. [Google Scholar]
  5. Białek, M., Sawicki, P. (2014). Can taking the perspective of an expert debias human decisions? The case for risky and delayed gains. Frontiers in Psychology, 5. DOI: 10.3389/fpsyg.2014.00989 [Google Scholar]
  6. Białek, M., Markiewicz, Ł., Sawicki, P. (2015). Introducing conjoint analysis method into delayed lotteries studies: Its validity and time stability are higher than in adjusting. Front. Psychol. 6:23. doi: 10.3389/fpsyg.2015.00023 [Google Scholar]
  7. Chib, S. (2011). Introduction to simulation and MCMC methods. In Geweke, J., Koop, G., van Dijk, H. (Eds.), The Oxford Handbook of Bayesian Econometrics (pp. 183–217). New York: Oxford University Press. [Google Scholar]
  8. Cliff, N. (1992). Abstract measurement theory and the revolution that never happened. Psychological Science, 3(3), 186–190. [Google Scholar]
  9. Debreu, G. (1960). Topological methods in cardinal utility theory. In Arrow, K.J., Karlin, S., Suppes, P. (Eds.), Mathematical methods in the social sciences (Vol. 1959). Stanford: Stanford University Press. [Google Scholar]
  10. Gino, F., Sharek, Z., Moore, D.A. (2011). Keeping the illusion of control under control: Ceilings, fl oors, and imperfect calibration. Organizational Behavior and Human Decision Processes, [Google Scholar]
  11. (2), 104–114. DOI: http://dx.doi.org/10.1016/j.obhdp.2010.10.002 [Google Scholar]
  12. Green, L., Myerson, J., Ostaszewski, P. (1999). Amount of reward has opposite effects on the discounting of delayed and probabilistic outcomes. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25(2), 418–427. DOI: 10.1037/0278-7393.25.2.418 [Google Scholar]
  13. Green, P.E., Rao, V.R. (1971). Conjoint Measurement for Quantifying Judgmental Data. Journal of [Google Scholar]
  14. Marketing Research, 8(3), 355–363. DOI: 10.2307/3149575 [Google Scholar]
  15. Holt, C.A., Laury, S.K. (2002). Risk aversion and incentive effects. American Economic Review, 1644–1655. [Google Scholar]
  16. Huber, J. (2004). Conjoint analysis: how we got here and where we are (An Update). Sawtooth Software Conference. from http://www.sawtoothsoftware.com/download/techpap/howwegot2.pdf [Google Scholar]
  17. Ida, T., Goto, R. (2009a). Interdependency among addictive behaviours and time/risk preferences: Discrete choice model analysis of smoking, drinking, and gambling. Journal of Economic Psychology, 30(4), 608-621. DOI: http://dx.doi.org/10.1016/j.joep.2009.05.003 [Google Scholar]
  18. Ida, T., Goto, R. (2009b). Simultaneous measurement of time and risk preferences: Stated preference discrete choice modeling analysis depending on smoking behavior. International Economic Review, 50(4), 1169–1182. DOI: 10.1111/j.1468-2354.2009.00564.x [Google Scholar]
  19. Johnson, E.J., Häubl, G., Keinan, A. (2007). Aspects of endowment: A query theory of value construction. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33(3), 461–474. DOI: 10.1037/0278-7393.33.3.461 [Google Scholar]
  20. Johnson, R.M. (2000). Understanding HB: An Intuitive Approach. https://sawtoothsoftware.com/ download/techpap/undhb.pdf [Google Scholar]
  21. Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux. [Google Scholar]
  22. Keren, G., Roelofsma, P. (1995). Immediacy and Certainty in Intertemporal Choice. Organizational Behavior and Human Decision Processes, 63(3), 287–297. DOI: http://dx.doi.org/10.1006/ obhd.1995.1080 [Google Scholar]
  23. Krantz, D.H. (1964). Conjoint measurement: The Luce-Tukey axiomatization and some extensions. Journal of Mathematical Psychology, 1(2), 248–277. DOI: http://dx.doi.org/10.1016/00222496(64)90003-3 [Google Scholar]
  24. Krantz, D.H., Luce, R.D., Suppes, P., Tversky, A. (1971). Foundations of Measurement: Additive and Polynomial Representations (Vol. 1): Academic Press New York. [Google Scholar]
  25. Krantz, D.H., Tversky, A. (1971). Conjoint-measurement analysis of composition rules in psychology. Psychological review, 78(2), 151. [Google Scholar]
  26. Kuhfeld, W.F., Tobias, R.D., Garratt, M. (1994). Effi cient Experimental Design with Marketing Research Applications. Journal of Marketing Research, 31(4), 545–557. DOI: 10.2307/3151882 [Google Scholar]
  27. Langer, E.J. (1975). The illusion of control. Journal of Personality and Social Psychology, 32(2), 311–328. [Google Scholar]
  28. Luce, R.D. (1966). Two extensions of conjoint measurement. Journal of Mathematical Psychology, 3(2), 348–370. DOI: http://dx.doi.org/10.1016/0022-2496(66)90019-8 [Google Scholar]
  29. Luce, R.D., Tukey, J.W. (1964). Simultaneous conjoint measurement: A new type of fundamental measurement. Journal of Mathematical Psychology, 1(1), 1–27. DOI: http://dx.doi.org/10.1016/00222496(64)90015-X [Google Scholar]
  30. Luce, R.D., Weber, E.U. (1986). An axiomatic theory of conjoint, expected risk. Journal of Mathematical Psychology, 30(2), 188–205. DOI: http://dx.doi.org/10.1016/0022-2496(86)90013-1 [Google Scholar]
  31. Markiewicz, Ł. (2012). Wykorzystanie metody conjoint do identyfi kacji wag decyzyjnych w procesie ustalania wymiaru kary sądowej. Nieopublikowany manuskrypt. Akademia Leona Koźmińskiego. Warszawa. [Google Scholar]
  32. Markiewicz, Ł., Markiewicz-Żuchowska, A. (2012). Skłonności poznawcze sędziego wpływające na wysokość wymierzonej kary. Decyzje, 18, 49–81. [Google Scholar]
  33. Markowitz, H. (1952). Portfolio Selection. The Journal of Finance, 7(1), 77–91. [Google Scholar]
  34. Myerson, J., Green, L., Scott Hanson, J., Holt, D.D., Estle, S. J. (2003). Discounting delayed and probabilistic rewards: Processes and traits. Journal of Economic Psychology, 24(5), 619–635. DOI: http://dx.doi.org/10.1016/S0167-4870(03)00005-9. [Google Scholar]
  35. Nowakowska, M. (1975). Psychologia ilościowa z elementami naukometrii: wybrane zagadnienia metodologiczne. Warszawa: Państwowe Wydawnictwo Naukowe. [Google Scholar]
  36. Orme, B.K. (2010). Getting Started with Conjoint Analysis: Strategies for Product Design and Pricing Research. Second Edition. Madison, Wis.: Research Publishers LLC. [Google Scholar]
  37. Osman, M. (2004). An evaluation of dual-process theories of reasoning. Psychonomic Bulletin & Review, 11(6), 988–1010. DOI: 10.3758/BF03196730 [Google Scholar]
  38. Ostaszewski, P. (1996). The relation between temperament and rate of temporal discounting. European [Google Scholar]
  39. Journal of Personality, 10(3), 161–172. DOI: 10.1002/(SICI)1099-0984(199609)10:3<161::AIDPER259>3.0.CO;2-R [Google Scholar]
  40. Ostaszewski, P. (2007). Wartość wzmocnień odroczonych i niepewnych z perspektywy analizy zachowania. Warszawa: Wydaw. Instytutu Psychologii PAN. [Google Scholar]
  41. Palenik, M. (2012). Kiedy może wystąpić ujemna stopa dyskontowa? Decyzje, 18, 83–104. [Google Scholar]
  42. Palenik, M. (2014). Atrakcyjność gier losowych a niechęć do ich odroczenia w czasie. Psychologia Ekonomiczna (5), 64–80. [Google Scholar]
  43. Penconek, M. (2001). Badania cenowe. Marketing w Praktyce, 10, 18–21. [Google Scholar]
  44. Rachlin, H., Logue, A.W., Gibbon, J., Frankel, M. (1986). Cognition and behavior in studies of choice. Psychological review, 93(1), 33–45. DOI: 10.1037/0033-295X.93.1.33 [Google Scholar]
  45. Rachlin, H., Raineri, A., Cross, D. (1991). Subjective probability and delay. Journal of the Experimental Analysis of Behavior, 55(2), 233–244. DOI: 10.1901/jeab.1991.55-233 [Google Scholar]
  46. Roskies, R. (1965). A measurement axiomatization for an essentially multiplicative representation of two factors. Journal of Mathematical Psychology, 2(2), 266–276. DOI: http://dx.doi. org/10.1016/0022-2496(65)90005-2 [Google Scholar]
  47. Rottenstreich, Y., Hsee, C.K. (2001). Money, Kisses, and Electric Shocks: On the Affective Psychology of Risk. Psychological Science, 12(3), 185–190. DOI: 10.1111/1467-9280.00334 [Google Scholar]
  48. Sawicki, P. (2013). Dyskontowanie odroczonych i niepewnych wypłat (nieopublikowana praca doktorska). (PhD.), Akademia Leona Koźmińskiego, Warszawa. [Google Scholar]
  49. Sawtooth Software, I. (2006, 26 January 2006). The Sawtooth Software Market Simulator (A Supplement to the CBC v2.6 Manual) Orem, Utah. [Google Scholar]
  50. Sawtooth Software, I. (2012). A Full-Profi le Conjoint Analysis System From Sawtooth Software. Version 3. Sequim, WA. [Google Scholar]
  51. Sawtooth Software, I. (2013). The CBC System for Choice-Based Conjoint Analysis. Version 8 https://sawtoothsoftware.com/download/techpap/cbctech.pdf [Google Scholar]
  52. Scott, D. (1964). Measurement structures and linear inequalities. Journal of Mathematical Psychology, 1(2), 233–247. DOI: http://dx.doi.org/10.1016/0022-2496(64)90002-1 [Google Scholar]
  53. Tsukayama, E., Duckworth, A.L. (2010). Domain-specifi c temporal discounting and temptation. Judgment and Decision Making, 5(2), 72–82. [Google Scholar]
  54. Tversky, A. (1967). A general theory of polynomial conjoint measurement. Journal of Mathematical [Google Scholar]
  55. Psychology, 4(1), 1–20. DOI: http://dx.doi.org/10.1016/0022-2496(67)90039-9 [Google Scholar]
  56. Tyszka, T. (2010). Decyzje. Perspektywa psychologiczna i ekonomiczna. In Brzeziński, J. (Ed.), Wykłady z psychologii. (Vol. 16, pp. 299–327). Warszawa: Wydawnictwo Naukowe SCHOLAR. [Google Scholar]
  57. Tyszka, T., Sawicki, P. (2011). Affective and Cognitive Factors Infl uencing Sensitivity to Probabilistic Information. Risk Analysis, 31(11), 1832–1845. DOI: 10.1111/j.1539-6924.2011.01644. [Google Scholar]
  58. Vanderveldt, A., Green, L., and Myerson, J. (2015). Discounting of monetary rewards that are both delayed and probabilistic: Delay and probability combine multiplicatively, not additively. Journal of Experimental Psychology: Learning, Memory, and Cognition 41, 148-162. doi: 10.1037/ xlm0000029. [Google Scholar]
  59. Von Neumann, J., Morgenstern, O. (1947). Theory of games and economic behavior. New York: Princeton university press Princeton. [Google Scholar]
  60. Walesiak, M., Bąk, A. (2000). Conjoint analysis w badaniach marketingowych. Wrocław: Wydawnictwo Akademii Ekonomicznej im. Oskara Langego. [Google Scholar]
  61. Wąsowicz-Kiryło, G. (1994). Conjoint analysis: metody badań i analizy danych. Przegląd Psychologiczny, 37(1-2), 167–173. [Google Scholar]
  62. Wąsowicz-Kiryło, G., Styśko-Kunkowska, M. (2011). Attributes of Nutritional Information Labelling that Determine Attractiveness of Labels and Correctness of Inferences Made About Food Healthfulness. Procedia - Social and Behavioral Sciences, 30(0), 722–728. DOI: http://dx.doi. org/10.1016/j.sbspro.2011.10.141 [Google Scholar]
  63. Weatherly, J.N. (2014). On several factors that control rates of discounting. Behavioural Processes, 104(0), 84–90. DOI: http://dx.doi.org/10.1016/j.beproc.2014.01.020 [Google Scholar]
  64. Weatherly, J.N., Petros, T.V., Jónsdóttir, H.L., Derenne, A., Miller, J.C. (2014). Probability alters delay discounting, but delay does not alter probability discounting. The Psychological Record, 1–9. DOI: 10.1007/s40732-014-0102-3 [Google Scholar]
  65. Weber, E.U. (1988). A descriptive measure of risk. Acta Psychologica, 69(2), 185-203. DOI: http:// dx.doi.org/10.1016/0001-6918(88)90006-6 [Google Scholar]
  66. Weber, E.U., Bottom, W.P. (1990). An empirical evaluation of the transitivity, monotonicity, accounting, and conjoint axioms for perceived risk. Organizational Behavior and Human Decision Processes, 45(2), 253–275. DOI: http://dx.doi.org/10.1016/0749-5978(90)90014-Z [Google Scholar]
  67. Weber, E.U., Johnson, E.J., Milch, K.F., Chang, H., Brodscholl, J.C., Goldstein, D.G. (2007). Asymmetric Discounting in Intertemporal Choice: A Query-Theory Account. Psychological Science, 18(6), 516–523. DOI: 10.1111/j.1467-9280.2007.01932.x [Google Scholar]
  68. Yi, R., de la Piedad, X., Bickel, W.K. (2006). The combined effects of delay and probability in discounting. Behavioural Processes, 73(2), 149–155. DOI: http://dx.doi.org/10.1016/j.beproc.2006.05.001 [Google Scholar]
  69. Zielonka, P., Sawicki, P., Weron, R. (2009). Discounting of delayed payoffs (Rzecz o dyskontowaniu odroczonych wypłat). Decyzje, 11, 49–70. [Google Scholar]

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Conjoint Analysis As A Measurement Method Of Preferences For Delayed Lotteries – Research Announcement. (2014). Conjoint Analysis As A Measurement Method Of Preferences For Delayed Lotteries – Research Announcement. Decyzje, (22), 71-99. https://doi.org/ 10.7206/DEC.1733-0092.34 (Original work published 12/2014AD)

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“Conjoint Analysis As A Measurement Method Of Preferences For Delayed Lotteries – Research Announcement”. 12/2014AD. Decyzje, no. 22, 2014, pp. 71-99.

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“Conjoint Analysis As A Measurement Method Of Preferences For Delayed Lotteries – Research Announcement”. Decyzje, Decyzje, no. 22 (2014): 71-99. doi: 10.7206/DEC.1733-0092.34 .