IDEAS home Printed from https://ideas.repec.org/a/sae/envirb/v35y2008i6p1055-1069.html
   My bibliography  Save this article

A Discrete-Choice Approach to Modeling Social Influence on Individual Decision Making

Author

Listed:
  • Antonio Páez
  • Darren M Scott
  • Erik Volz

    (Department of Integrative Biology, University of Texas at Austin, 1 University Station C0930 Austin, TX 78712, USA)

Abstract

Individual decision making is commonly studied using discrete choice models. Models of this type are applied extensively to the study of travel behavior, residential location, and employment decisions, among other topics of interest. A notable characteristic of the underlying economic theory is the assumption that individuals seek to maximize utility on the basis of their personal attributes and the attributes of the alternatives available to them. This approach ignores the interrelated nature of decision making in social situations—in other words, the role that social structures play in shaping behavior. In this paper we describe a multinomial discrete choice approach to analyzing individual behavior in social situations where position in a social network may encourage or discourage different courses of action. By means of a simulation example, we explore some properties of the model, in particular the effect of network topology.

Suggested Citation

  • Antonio Páez & Darren M Scott & Erik Volz, 2008. "A Discrete-Choice Approach to Modeling Social Influence on Individual Decision Making," Environment and Planning B, , vol. 35(6), pages 1055-1069, December.
  • Handle: RePEc:sae:envirb:v:35:y:2008:i:6:p:1055-1069
    DOI: 10.1068/b3320t
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1068/b3320t
    Download Restriction: no

    File URL: https://libkey.io/10.1068/b3320t?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. Harrison, David Jr. & Rubinfeld, Daniel L., 1978. "Hedonic housing prices and the demand for clean air," Journal of Environmental Economics and Management, Elsevier, vol. 5(1), pages 81-102, March.
    2. Bhat, Chandra R. & Guo, Jessica, 2004. "A mixed spatially correlated logit model: formulation and application to residential choice modeling," Transportation Research Part B: Methodological, Elsevier, vol. 38(2), pages 147-168, February.
    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. López, Fernando A. & Páez, Antonio & Carrasco, Juan A. & Ruminot, Natalia A., 2017. "Vulnerability of nodes under controlled network topology and flow autocorrelation conditions," Journal of Transport Geography, Elsevier, vol. 59(C), pages 77-87.
    2. Chih-Hao Wang & Hongwei Dong, 2017. "Responding to the Drought: A Spatial Statistical Approach to Investigating Residential Water Consumption in Fresno, California," Sustainability, MDPI, vol. 9(2), pages 1-15, February.
    3. Lin, Tao & Wang, Donggen & Zhou, Meng, 2018. "Residential relocation and changes in travel behavior: what is the role of social context change?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 111(C), pages 360-374.
    4. Di Porto Edoardo & Revelli Federico, 2009. "Central Command, Local Hazard and the Race to the Top," Department of Economics and Statistics Cognetti de Martiis. Working Papers 200909, University of Turin.
    5. Wang, Xiaokun (Cara) & Kockelman, Kara M. & Lemp, Jason D., 2012. "The dynamic spatial multinomial probit model: analysis of land use change using parcel-level data," Journal of Transport Geography, Elsevier, vol. 24(C), pages 77-88.
    6. Smirnov, Oleg A. & Egan, Kevin J., 2012. "Spatial random utility model with an application to recreation demand," Economic Modelling, Elsevier, vol. 29(1), pages 72-78.
    7. Wang, Chih-Hao & Akar, Gulsah & Guldmann, Jean-Michel, 2015. "Do your neighbors affect your bicycling choice? A spatial probit model for bicycling to The Ohio State University," Journal of Transport Geography, Elsevier, vol. 42(C), pages 122-130.
    8. Pike, Susan & Lubell, Mark, 2018. "The conditional effects of social influence in transportation mode choice," Research in Transportation Economics, Elsevier, vol. 68(C), pages 2-10.
    9. Wei, Fangfang & Jia, Ning & Ma, Shoufeng, 2016. "Day-to-day traffic dynamics considering social interaction: From individual route choice behavior to a network flow model," Transportation Research Part B: Methodological, Elsevier, vol. 94(C), pages 335-354.
    10. Maness, Michael & Cirillo, Cinzia & Dugundji, Elenna R., 2015. "Generalized behavioral framework for choice models of social influence: Behavioral and data concerns in travel behavior," Journal of Transport Geography, Elsevier, vol. 46(C), pages 137-150.
    11. Smirnov, Oleg A., 2010. "Modeling spatial discrete choice," Regional Science and Urban Economics, Elsevier, vol. 40(5), pages 292-298, September.
    12. Kowald, Matthias & van den Berg, Pauline & Frei, Andreas & Carrasco, Juan-Antonio & Arentze, Theo & Axhausen, Kay & Mok, Diana & Timmermans, Harry & Wellman, Barry, 2013. "Distance patterns of personal networks in four countries: a comparative study," Journal of Transport Geography, Elsevier, vol. 31(C), pages 236-248.
    13. Shen, Yu & de Abreu e Silva, João & Martínez, Luis Miguel, 2014. "Assessing High-Speed Rail’s impacts on land cover change in large urban areas based on spatial mixed logit methods: a case study of Madrid Atocha railway station from 1990 to 2006," Journal of Transport Geography, Elsevier, vol. 41(C), pages 184-196.
    14. Pan, Xiaofeng & Rasouli, Soora & Timmermans, Harry, 2019. "Modeling social influence using sequential stated adaptation experiments: A study of city trip itinerary choice," Transportation Research Part A: Policy and Practice, Elsevier, vol. 130(C), pages 652-672.

    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. Jianhong Shi & Qian Yang & Xiongya Li & Weixing Song, 2017. "Effects of measurement error on a class of single-index varying coefficient regression models," Computational Statistics, Springer, vol. 32(3), pages 977-1001, September.
    2. Villalonga, Belen, 2004. "Intangible resources, Tobin's q, and sustainability of performance differences," Journal of Economic Behavior & Organization, Elsevier, vol. 54(2), pages 205-230, June.
    3. Singh, Abhilash C. & Faghih Imani, Ahmadreza & Sivakumar, Aruna & Luna Xi, Yang & Miller, Eric J., 2024. "A joint analysis of accessibility and household trip frequencies by travel mode," Transportation Research Part A: Policy and Practice, Elsevier, vol. 181(C).
    4. Weiss, Adam & Habib, Khandker Nurul, 2017. "Examining the difference between park and ride and kiss and ride station choices using a spatially weighted error correlation (SWEC) discrete choice model," Journal of Transport Geography, Elsevier, vol. 59(C), pages 111-119.
    5. Brockmeier, M., 1991. "Entwicklung und Aufhebung von Reinheitsgeboten im Nahrungsmittelbereich – Analyse und Bewertung," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 27.
    6. Gopalakrishnan, Raja & Guevara, C. Angelo & Ben-Akiva, Moshe, 2020. "Combining multiple imputation and control function methods to deal with missing data and endogeneity in discrete-choice models," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 45-57.
    7. Miller, Steve & Startz, Richard, 2019. "Feasible generalized least squares using support vector regression," Economics Letters, Elsevier, vol. 175(C), pages 28-31.
    8. Umberto Amato & Anestis Antoniadis & Italia De Feis & Irene Gijbels, 2021. "Penalised robust estimators for sparse and high-dimensional linear models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(1), pages 1-48, March.
    9. Prendergast, Luke A. & Li Wai Suen, Connie, 2011. "A new and practical influence measure for subsets of covariance matrix sample principal components with applications to high dimensional datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 752-764, January.
    10. Tizheng Li & Xiaojuan Kang, 2022. "Variable selection of higher-order partially linear spatial autoregressive model with a diverging number of parameters," Statistical Papers, Springer, vol. 63(1), pages 243-285, February.
    11. Deac Dan Stelian & Schebesch Klaus Bruno, 2018. "Market Forecasts and Client Behavioral Data: Towards Finding Adequate Model Complexity," Studia Universitatis „Vasile Goldis” Arad – Economics Series, Sciendo, vol. 28(3), pages 50-75, September.
    12. Chandra Bhat & Ipek Sener, 2009. "A copula-based closed-form binary logit choice model for accommodating spatial correlation across observational units," Journal of Geographical Systems, Springer, vol. 11(3), pages 243-272, September.
    13. Juan Ignacio Zoloa, 2020. "Noise pollution and housing markets: A spatial hedonic analysis for La Plata City," Ensayos de Política Económica, Departamento de Investigación Francisco Valsecchi, Facultad de Ciencias Económicas, Pontificia Universidad Católica Argentina., vol. 3(2), pages 129-152, Octubre.
    14. Cheng, Tsung-Chi, 2012. "On simultaneously identifying outliers and heteroscedasticity without specific form," Computational Statistics & Data Analysis, Elsevier, vol. 56(7), pages 2258-2272.
    15. Bodhisattva Sen & Mary Meyer, 2017. "Testing against a linear regression model using ideas from shape-restricted estimation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(2), pages 423-448, March.
    16. Benítez-Peña, Sandra & Blanquero, Rafael & Carrizosa, Emilio & Ramírez-Cobo, Pepa, 2024. "Cost-sensitive probabilistic predictions for support vector machines," European Journal of Operational Research, Elsevier, vol. 314(1), pages 268-279.
    17. repec:wyi:journl:002176 is not listed on IDEAS
    18. Steve Gibbons & Stephan Heblich & Esther Lho & Christopher Timmins, 2016. "Fear of Fracking? The Impact of the Shale Gas Exploration on House Prices in Britain," SERC Discussion Papers 0207, Centre for Economic Performance, LSE.
    19. Sanying Feng & Liugen Xue, 2014. "Bias-corrected statistical inference for partially linear varying coefficient errors-in-variables models with restricted condition," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 66(1), pages 121-140, February.
    20. Takafumi Kato, 2020. "Likelihood-based strategies for estimating unknown parameters and predicting missing data in the simultaneous autoregressive model," Journal of Geographical Systems, Springer, vol. 22(1), pages 143-176, January.
    21. Y Nguyen CAO, 2021. "Modeling Logistic Enterprise Re-Location Decision By A Nested Logit Model," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 49-57, June.

    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:envirb:v:35:y:2008:i:6:p:1055-1069. 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: .

    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.