IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v54y2008i1p56-70.html
   My bibliography  Save this article

Generating Objectives: Can Decision Makers Articulate What They Want?

Author

Listed:
  • Samuel D. Bond

    (College of Management, Georgia Institute of Technology, Atlanta, Georgia 30318)

  • Kurt A. Carlson

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

  • Ralph L. Keeney

    (Fuqua School of Business, Duke University, Durham, North Carolina 27708)

Abstract

Objectives have long been considered a basis for sound decision making. This research examines the ability of decision makers to generate self-relevant objectives for consequential decisions. In three empirical studies, participants consistently omitted nearly half of the objectives that they later identified as personally relevant. More surprisingly, omitted objectives were perceived to be almost as important as those generated by participants on their own. These empirical results were replicated in a real-world case study of strategic decision making at a high-tech firm. Overall, our research suggests that decision makers are considerably deficient in utilizing personal knowledge and values to form objectives for the decisions they face.

Suggested Citation

  • Samuel D. Bond & Kurt A. Carlson & Ralph L. Keeney, 2008. "Generating Objectives: Can Decision Makers Articulate What They Want?," Management Science, INFORMS, vol. 54(1), pages 56-70, January.
    • Handle: RePEc:inm:ormnsc:v:54:y:2008:i:1:p:56-70
    DOI: 10.1287/mnsc.1070.0754
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.1070.0754
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.1070.0754?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Craig R. Fox & Robert T. Clemen, 2005. "Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior," Management Science, INFORMS, vol. 51(9), pages 1417-1432, September.
    2. Payne, John W & Bettman, James R & Schkade, David A, 1999. "Measuring Constructed Preferences: Towards a Building Code," Journal of Risk and Uncertainty, Springer, vol. 19(1-3), pages 243-270, December.
    3. Leon, Orfelio G., 1999. "Value-Focused Thinking versus Alternative-Focused Thinking: Effects on Generation of Objectives," Organizational Behavior and Human Decision Processes, Elsevier, vol. 80(3), pages 213-227, December.
    4. Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 69(1), pages 99-118.
    5. Lussier, Denis A & Olshavsky, Richard W, 1979. "Task Complexity and Contingent Processing in Brand Choice," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 6(2), pages 154-165, Se.
    6. Bettman, James R & Luce, Mary Frances & Payne, John W, 1998. "Constructive Consumer Choice Processes," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 25(3), pages 187-217, December.
    7. Diane L. Rulke & Joseph Galaskiewicz, 2000. "Distribution of Knowledge, Group Network Structure, and Group Performance," Management Science, INFORMS, vol. 46(5), pages 612-625, May.
    8. Ralph L. Keeney, 1999. "Developing a Foundation for Strategy at Seagate Software," Interfaces, INFORMS, vol. 29(6), pages 4-15, December.
    9. Baron, Jonathan, 1997. "Confusion of Relative and Absolute Risk in Valuation," Journal of Risk and Uncertainty, Springer, vol. 14(3), pages 301-309, May-June.
    10. Timothy J. Gilbride & Greg M. Allenby, 2004. "A Choice Model with Conjunctive, Disjunctive, and Compensatory Screening Rules," Marketing Science, INFORMS, vol. 23(3), pages 391-406, October.
    11. Clemen, Robert T., 1989. "Combining forecasts: A review and annotated bibliography," International Journal of Forecasting, Elsevier, vol. 5(4), pages 559-583.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shao, Wei & Lye, Ashley & Rundle-Thiele, Sharyn, 2009. "Different strokes for different folks: A method to accommodate decision -making heterogeneity," Journal of Retailing and Consumer Services, Elsevier, vol. 16(6), pages 495-501.
    2. Song Lin & Juanjuan Zhang & John R. Hauser, 2015. "Learning from Experience, Simply," Marketing Science, INFORMS, vol. 34(1), pages 1-19, January.
    3. Joonwook Park & Wayne DeSarbo & John Liechty, 2008. "A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 451-472, September.
    4. Heiman, Amir & Lowengart, Oded, 2011. "The effects of information about health hazards in food on consumers' choice process," Journal of Econometrics, Elsevier, vol. 162(1), pages 140-147, May.
    5. Mueller, Michel G. & de Haan, Peter, 2009. "How much do incentives affect car purchase? Agent-based microsimulation of consumer choice of new cars--Part I: Model structure, simulation of bounded rationality, and model validation," Energy Policy, Elsevier, vol. 37(3), pages 1072-1082, March.
    6. Loibl, Cäzilia & Kraybill, David S. & DeMay, Sara Wackler, 2011. "Accounting for the role of habit in regular saving," Journal of Economic Psychology, Elsevier, vol. 32(4), pages 581-592, August.
    7. Kaye-Blake, William & Abell, Walter L. & Zellman, Eva, 2009. "Respondents’ ignoring of attribute information in a choice modelling survey," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 53(4), pages 1-18.
    8. Michel Wedel & Rik Pieters & Ralf Lans, 2023. "Modeling Eye Movements During Decision Making: A Review," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 697-729, June.
    9. Joffre Swait & Fred Feinberg, 2014. "Deciding how to decide: an agenda for multi-stage choice modelling research in marketing," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 26, pages 649-660, Edward Elgar Publishing.
    10. Zuschke, Nick, 2020. "An analysis of process-tracing research on consumer decision-making," Journal of Business Research, Elsevier, vol. 111(C), pages 305-320.
    11. Timothy J. Gilbride & Greg M. Allenby, 2006. "Estimating Heterogeneous EBA and Economic Screening Rule Choice Models," Marketing Science, INFORMS, vol. 25(5), pages 494-509, September.
    12. Araña, Jorge E. & León, Carmelo J. & Hanemann, Michael W., 2008. "Emotions and decision rules in discrete choice experiments for valuing health care programmes for the elderly," Journal of Health Economics, Elsevier, vol. 27(3), pages 753-769, May.
    13. Hyowon Kim & Dong Soo Kim & Greg M. Allenby, 2020. "Benefit Formation and Enhancement," Quantitative Marketing and Economics (QME), Springer, vol. 18(4), pages 419-468, December.
    14. Martinovici, A., 2019. "Revealing attention - how eye movements predict brand choice and moment of choice," Other publications TiSEM 7dca38a5-9f78-4aee-bd81-c, Tilburg University, School of Economics and Management.
    15. James Agarwal & Wayne DeSarbo & Naresh K. Malhotra & Vithala Rao, 2015. "An Interdisciplinary Review of Research in Conjoint Analysis: Recent Developments and Directions for Future Research," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(1), pages 19-40, March.
    16. Charles Cunningham & Ken Deal & Yvonne Chen, 2010. "Adaptive Choice-Based Conjoint Analysis," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 3(4), pages 257-273, December.
    17. Ary José A. de Souza-Jr. & Flávio Terto, 2021. "The propensity to adaptation under the new era of climate changes," Working Papers REM 2021/0167, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    18. Crawford, Gregory S. & Griffith, Rachel & Iaria, Alessandro, 2021. "A survey of preference estimation with unobserved choice set heterogeneity," Journal of Econometrics, Elsevier, vol. 222(1), pages 4-43.
    19. Peter Stüttgen & Peter Boatwright & Robert T. Monroe, 2012. "A Satisficing Choice Model," Marketing Science, INFORMS, vol. 31(6), pages 878-899, November.
    20. Pantelis P. Analytis & Amit Kothiyal & Konstantinos Katsikopoulos, 2014. "Multi-attribute utility models as cognitive search engines," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 9(5), pages 403-419, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:54:y:2008:i:1:p:56-70. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.