IDEAS home Printed from https://ideas.repec.org/a/sae/jocore/v25y1981i2p301-327.html
   My bibliography  Save this article

Conjoint Analysis of Negotiator Preferences

Author

Listed:
  • Leonard Greenhalg

    (The Amos Tuck School of Business Administration Dartmouth College)

  • Scott A. Neslin

    (The Amos Tuck School of Business Administration Dartmouth College)

Abstract

Negotiator preferences are a universal element of conflict resolution theories, but have posed problems of operationalization which have hampered empirical verification and development of the theories. Conjoint analysis is proposed as a method for assessing the preferences of negotiators and their constituencies generally, and union, management, and employee preferences in a collective bargaining context, specifically. The technique is useful to researchers and practitioners in that it is easier to apply than Von Neumann-Morgenstern (1947) utility theory, and provides more information than simple issueprioritizing techniques. Conjoint analysis is used to analyze a simulated contract negotiation and shown to be both practical and valid. The technique is described and assessed; research and practical application are suggested in the areas of contract negotiation and third party intervention. An application of the technique for testing the Nash (1953) model of bargaining is included as an illustration of the technique's usefulness.

Suggested Citation

  • Leonard Greenhalg & Scott A. Neslin, 1981. "Conjoint Analysis of Negotiator Preferences," Journal of Conflict Resolution, Peace Science Society (International), vol. 25(2), pages 301-327, June.
  • Handle: RePEc:sae:jocore:v:25:y:1981:i:2:p:301-327
    DOI: 10.1177/002200278102500205
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/002200278102500205
    Download Restriction: no

    File URL: https://libkey.io/10.1177/002200278102500205?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. Nash, John, 1953. "Two-Person Cooperative Games," Econometrica, Econometric Society, vol. 21(1), pages 128-140, April.
    2. John R. Hauser & Steven M. Shugan, 1977. "Efficient Measurement of Consumer Preference Functions: A General Theory for Intensity of Preference," Discussion Papers 285, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    3. Green, Paul E & Devita, Michael T, 1975. "An Interaction Model of Consumer Utility," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 2(2), pages 146-153, Se.
    4. Barnett R. Parker & V. Srinivasan, 1976. "A Consumer Preference Approach to the Planning of Rural Primary Health-Care Facilities," Operations Research, INFORMS, vol. 24(5), pages 991-1025, October.
    5. Green, Paul E & Srinivasan, V, 1978. "Conjoint Analysis in Consumer Research: Issues and Outlook," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(2), pages 103-123, Se.
    6. Hauser, John R & Urban, Glen L, 1979. "Assessment of Attribute Importances and Consumer Utility Functions: von Neumann-Morgenstern Theory Applied to Consumer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 5(4), pages 251-262, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Alice F. Stuhlmacher & Mary Kay Stevenson, 1997. "Using Policy Modeling to Describe the Negotiation Exchange," Group Decision and Negotiation, Springer, vol. 6(4), pages 317-337, July.

    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. Geoffrey N. Soutar & Norman F. Dufty & Lawson K. Savery, 1986. "Examining Perceptions of and Preferences for Different Wage Systems: A Joint Space Approach," Australian Journal of Management, Australian School of Business, vol. 11(1), pages 97-115, June.
    2. Stirling Bryan & Lisa Gold & Rob Sheldon & Martin Buxton, 2000. "Preference measurement using conjoint methods: an empirical investigation of reliability," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 385-395, July.
    3. John R. Hauser & Steven Shugan, 1978. "Intensity Measures of Consumer Preferences," Discussion Papers 291, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    4. Milena Pavlova & Wim Groot & Godefridus Merode, 2005. "An Application of Rating Conjoint Analysis to Study the Importance of Quality-, Access- and Price-attributes to Health Care Consumers," Economic Change and Restructuring, Springer, vol. 37(3), pages 267-286, September.
    5. Wiegand, S., 1993. "Die Conjoint-Analyse als Instrument zur Nutzenmessung – Ergebnisse einer Befragung in den neuen Bundesländern," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 29.
    6. Zhu, Wei & Timmermans, Harry, 2010. "Modeling simplifying information processing strategies in conjoint experiments," Transportation Research Part B: Methodological, Elsevier, vol. 44(6), pages 764-780, July.
    7. Winfried Steiner & Harald Hruschka, 2002. "A Probabilistic One-Step Approach to the Optimal Product Line Design Problem Using Conjoint and Cost Data," Review of Marketing Science Working Papers 1-4-1003, Berkeley Electronic Press.
    8. Merja Halme & Kari Linden & Kimmo Kääriä, 2009. "Patients’ Preferences for Generic and Branded Over-the-Counter Medicines," The Patient: Patient-Centered Outcomes Research, Springer;International Academy of Health Preference Research, vol. 2(4), pages 243-255, December.
    9. Federico Di Pace & Matthias Hertweck, 2019. "Labor Market Frictions, Monetary Policy, and Durable Goods," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 274-304, April.
    10. Li, Hui & Xu, Yunjie & Huang, Lihua, 2021. "When less is more? The contingent effect of product supply limitation in the release of new electronic products," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    11. Bergantiños, Gustavo & Vidal-Puga, Juan, 2010. "Realizing fair outcomes in minimum cost spanning tree problems through non-cooperative mechanisms," European Journal of Operational Research, Elsevier, vol. 201(3), pages 811-820, March.
    12. Guth, Werner & Ritzberger, Klaus & van Damme, Eric, 2004. "On the Nash bargaining solution with noise," European Economic Review, Elsevier, vol. 48(3), pages 697-713, June.
    13. Haaijer, Marinus E., 1996. "Predictions in conjoint choice experiments : the x-factor probit model," Research Report 96B22, University of Groningen, Research Institute SOM (Systems, Organisations and Management).
    14. Fandel, Günter & Giese, Anke & Mohn, Brigitte, 2012. "Measuring synergy effects of a Public Social Private Partnership (PSPP) project," International Journal of Production Economics, Elsevier, vol. 140(2), pages 815-824.
    15. Volodymyr Babich & Simone Marinesi & Gerry Tsoukalas, 2021. "Does Crowdfunding Benefit Entrepreneurs and Venture Capital Investors?," Manufacturing & Service Operations Management, INFORMS, vol. 23(2), pages 508-524, March.
    16. Zhigang Cao, 2011. "Remarks on Bargaining and Cooperation in Strategic Form Games," Discussion Paper Series dp565, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    17. Ley, Eduardo, 2006. "Statistical inference as a bargaining game," Economics Letters, Elsevier, vol. 93(1), pages 142-149, October.
    18. Maria Montero & Alex Possajennikov, 2021. "An Adaptive Model of Demand Adjustment in Weighted Majority Games," Games, MDPI, vol. 13(1), pages 1-17, December.
    19. Yu, Shasha & Lei, Ming & Deng, Honghui, 2023. "Evaluation to fixed-sum-outputs DMUs by non-oriented equilibrium efficient frontier DEA approach with Nash bargaining-based selection," Omega, Elsevier, vol. 115(C).
    20. van Damme, E.E.C., 1995. "Game theory : The next stage," Other publications TiSEM 7779b0f9-bef5-45c7-ae6b-7, Tilburg University, School of Economics and Management.

    More about this item

    Statistics

    Access and download statistics

    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:sae:jocore:v:25:y:1981:i:2:p:301-327. 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: SAGE Publications (email available below). General contact details of provider: http://pss.la.psu.edu/ .

    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.