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Social Networks and New Product Choice

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  • Richards, Timothy J.
  • Allender, William J.
  • Hamilton, Stephen F.

Abstract

Influential individuals in a social network environment are important in shaping preferences for new products. In this study, we adopt an incentive compatible choice-based conjoint analysis approach to generate data on the introduction of a new ice cream product. We use spatial econometric methods to determine how individuals are likely to change their preferences when exposed to the choices of other members in their social network. We find evidence that agents look to others for guidance in their preference for subjective or taste-specific parameters, but rely on own preferences for objectively measured attributes such as price. We also use spatial methods to determine which network-member is the most influential. We find that the most connected member is not necessarily the most influential, and that influence can be determined econometrically.

Suggested Citation

  • Richards, Timothy J. & Allender, William J. & Hamilton, Stephen F., 2012. "Social Networks and New Product Choice," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 124762, Agricultural and Applied Economics Association.
  • Handle: RePEc:ags:aaea12:124762
    DOI: 10.22004/ag.econ.124762
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    Cited by:

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    2. Bonnet, Céline & Richards, Timothy J., 2016. "Models of Consumer Demand for Differentiated Products," TSE Working Papers 16-741, Toulouse School of Economics (TSE).
    3. Bruno Wichmann & Minjie Chen & Wiktor Adamowicz, 2016. "Social Networks and Choice Set Formation in Discrete Choice Models," Econometrics, MDPI, vol. 4(4), pages 1-26, October.
    4. Tavárez, Héctor & Elbakidze, Levan, 2019. "Valuing recreational enhancements in the San Patricio Urban Forest of Puerto Rico: A choice experiment approach," Forest Policy and Economics, Elsevier, vol. 109(C).
    5. Langer, Melissa & Davidson, Kelly A. & McFadden, Brandon & Messer, Kent D., 2020. "Evaluating the Effects of Peer Information and Social Influence on Food Purchase in Social Settings," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304536, Agricultural and Applied Economics Association.
    6. Emiliano Brancaccio & Raffaele Giammetti & Milena Lopreite & Michelangelo Puliga, 2023. "Convergence in solvency and capital centralization: A B‐VAR analysis for high‐income and euro area countries," Metroeconomica, Wiley Blackwell, vol. 74(1), pages 40-73, February.
    7. Habtamu Tilahun Kassahun & Bo Jellesmark Thorsen & Joffre Swait & Jette Bredahl Jacobsen, 2020. "Social Cooperation in the Context of Integrated Private and Common Land Management," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(1), pages 105-136, January.
    8. Bazzani, Claudia & Nayga, Rodolfo M. Jr. & Caputo, Vincenzina & Canavari, Maurizio & Danforth, Diana M., 2016. "On the Use of the BDM Mechanism in Non-Hypothetical Choice Experiments," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235904, Agricultural and Applied Economics Association.
    9. Ozge Dinc‐Cavlak & Ozlem Ozdemir, 2021. "Comparing the willingness to pay through three elicitation mechanisms: An experimental evidence for organic egg product," Agribusiness, John Wiley & Sons, Ltd., vol. 37(4), pages 782-803, October.
    10. Fang, Di & Richards, Timothy, 2016. "New Maize Variety Adoption in Mozambique: A Spatial Approach," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235388, Agricultural and Applied Economics Association.
    11. Maurizio Canavari & Andreas C. Drichoutis & Jayson L. Lusk & Rodolfo M. Nayga, Jr., 2018. "How to run an experimental auction: A review of recent advances," Working Papers 2018-5, Agricultural University of Athens, Department Of Agricultural Economics.
    12. Dubey, Subodh & Sharma, Ishant & Mishra, Sabyasachee & Cats, Oded & Bansal, Prateek, 2022. "A General Framework to Forecast the Adoption of Novel Products: A Case of Autonomous Vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 165(C), pages 63-95.
    13. Miguel Angel de la Llave Montiel & Fernando López, 2020. "Spatial models for online retail churn: Evidence from an online grocery delivery service in Madrid," Papers in Regional Science, Wiley Blackwell, vol. 99(6), pages 1643-1665, December.
    14. Hübler, Michael, 2015. "Labor mobility and technology diffusion: A new concept and its application to rural Southeast Asia," Journal of Asian Economics, Elsevier, vol. 39(C), pages 137-151.
    15. Mulu Debela Ofolsha & Fekadu Beyene Kenee & Dawit Alemu Bimirew & Tesfaye Lemma Tefera & Aseffa Seyoum Wedajo, 2022. "The Effect of Social Networks on Smallholder Farmers’ Decision to Join Farmer-Base Seed Producer Cooperatives (FBSc): The Case of Hararghe, Oromia, Ethiopia," Sustainability, MDPI, vol. 14(10), pages 1-19, May.
    16. Di Fang & Timothy J. Richards, 2018. "New Maize Variety Adoption in Mozambique: A Spatial Approach," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 66(3), pages 469-488, September.
    17. Ashutosh Tiwari & Timothy J. Richards, 2016. "Social Networks and Restaurant Ratings," Agribusiness, John Wiley & Sons, Ltd., vol. 32(2), pages 153-174, April.

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