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Online Advertising and Real Estate sales: evidence from the Housing Market

Author

Listed:
  • Xiuzhi Zhang

    (Renmin University of China)

  • Ying Zhang

    (University of Auckland)

  • Zhijie Lin

    (Tsinghua University)

Abstract

Despite the popular use of online advertising by marketers, little is known about its role in the real estate market. This research aims to investigate how online advertising affects the sales of new houses and explores potential contingent factors and the underlying mechanism. Based on a rich secondary data set and econometric models, we find that online advertising increases the sales of new houses, and the effect is stronger with lower housing prices, higher residential incomes, and lower-tier cities. Additionally, the mechanism is that advertising generates an impact via processes, such as lowering housing prices, attracting more immigrants, and reducing emigration. Lastly, the spillover effect of online advertising may not exist in the housing market. We discuss theoretical contributions and important implications to practitioners and policy makers.

Suggested Citation

  • Xiuzhi Zhang & Ying Zhang & Zhijie Lin, 2023. "Online Advertising and Real Estate sales: evidence from the Housing Market," Electronic Commerce Research, Springer, vol. 23(1), pages 605-622, March.
    • Handle: RePEc:spr:elcore:v:23:y:2023:i:1:d:10.1007_s10660-022-09584-2
    DOI: 10.1007/s10660-022-09584-2
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    References listed on IDEAS

    as
    1. De Liu & Jianqing Chen & Andrew B. Whinston, 2010. "Ex Ante Information and the Design of Keyword Auctions," Information Systems Research, INFORMS, vol. 21(1), pages 133-153, March.
    2. Ji Wu & Haichuan Zhao & Haipeng (Allan) Chen, 2021. "Coupons or Free Shipping? Effects of Price Promotion Strategies on Online Review Ratings," Information Systems Research, INFORMS, vol. 32(2), pages 633-652, June.
    3. Robert C. Blattberg & Abel P. Jeuland, 1981. "A Micromodeling Approach to Investigate the Advertising-Sales Relationship," Management Science, INFORMS, vol. 27(9), pages 988-1005, September.
    4. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, April.
    5. Lorin M. Hitt, 1999. "Information Technology and Firm Boundaries: Evidence from Panel Data," Information Systems Research, INFORMS, vol. 10(2), pages 134-149, June.
    6. Bayer, Emanuel & Srinivasan, Shuba & Riedl, Edward J. & Skiera, Bernd, 2020. "The impact of online display advertising and paid search advertising relative to offline advertising on firm performance and firm value," International Journal of Research in Marketing, Elsevier, vol. 37(4), pages 789-804.
    7. Francesco Decarolis & Maris Goldmanis & Antonio Penta, 2020. "Marketing Agencies and Collusive Bidding in Online Ad Auctions," Management Science, INFORMS, vol. 66(10), pages 4433-4454, October.
    8. Robert B. Ekelund & Franklin G. Mixon & Rand W. Ressler, 1995. "Advertising and information: an empirical study of search, experience and credence goods," Journal of Economic Studies, Emerald Group Publishing, vol. 22(2), pages 33-43, May.
    9. Krainer, John, 2001. "A Theory of Liquidity in Residential Real Estate Markets," Journal of Urban Economics, Elsevier, vol. 49(1), pages 32-53, January.
    10. Leung, Charles, 2004. "Macroeconomics and housing: a review of the literature," Journal of Housing Economics, Elsevier, vol. 13(4), pages 249-267, December.
    11. Xiaomeng Du & Meng Su & Xiaoquan (Michael) Zhang & Xiaona Zheng, 2017. "Bidding for Multiple Keywords in Sponsored Search Advertising: Keyword Categories and Match Types," Information Systems Research, INFORMS, vol. 28(4), pages 711-722, December.
    12. Ashish Agarwal & Tridas Mukhopadhyay, 2016. "The Impact of Competing Ads on Click Performance in Sponsored Search," Information Systems Research, INFORMS, vol. 27(3), pages 538-557.
    13. Ashish Agarwal & Kartik Hosanagar & Michael D. Smith, 2015. "Do Organic Results Help or Hurt Sponsored Search Performance?," Information Systems Research, INFORMS, vol. 26(4), pages 695-713, December.
    14. Clara H. Mulder, 2006. "Population and housing," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 15(13), pages 401-412.
    15. Haoyan Sun & Ming Fan & Yong Tan, 2020. "An Empirical Analysis of Seller Advertising Strategies in an Online Marketplace," Information Systems Research, INFORMS, vol. 31(1), pages 37-56, March.
    16. Juan Feng & Jinhong Xie, 2012. "Research Note ---Performance-Based Advertising: Advertising as Signals of Product Quality," Information Systems Research, INFORMS, vol. 23(3-part-2), pages 1030-1041, September.
    17. Yu (Jeffrey) Hu & Jiwoong Shin & Zhulei Tang, 2016. "Incentive Problems in Performance-Based Online Advertising Pricing: Cost per Click vs. Cost per Action," Management Science, INFORMS, vol. 62(7), pages 2022-2038, July.
    18. Nelson, Philip, 1974. "Advertising as Information," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 729-754, July/Aug..
    19. Vilma Todri & Anindya Ghose & Param Vir Singh, 2020. "Trade-Offs in Online Advertising: Advertising Effectiveness and Annoyance Dynamics Across the Purchase Funnel," Information Systems Research, INFORMS, vol. 31(1), pages 102-125, March.
    20. Kevin J. Boudreau & Lars B. Jeppesen, 2015. "Unpaid crowd complementors: The platform network effect mirage," Strategic Management Journal, Wiley Blackwell, vol. 36(12), pages 1761-1777, December.
    21. Avi Goldfarb & Catherine Tucker, 2011. "Search Engine Advertising: Channel Substitution When Pricing Ads to Context," Management Science, INFORMS, vol. 57(3), pages 458-470, March.
    22. Erik Brynjolfsson & Lorin Hitt, 1996. "Paradox Lost? Firm-Level Evidence on the Returns to Information Systems Spending," Management Science, INFORMS, vol. 42(4), pages 541-558, April.
    23. Theodore Groves & Yongmiao Hong & John McMillan & Barry Naughton, 1994. "Autonomy and Incentives in Chinese State Enterprises," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 109(1), pages 183-209.
    24. Hollis, Nigel, 2005. "Ten Years of Learning on How Online Advertising Builds Brands," Journal of Advertising Research, Cambridge University Press, vol. 45(2), pages 255-268, June.
    25. Jeffrey M. Wooldridge, 2015. "Control Function Methods in Applied Econometrics," Journal of Human Resources, University of Wisconsin Press, vol. 50(2), pages 420-445.
    26. Frank M. Bass & Norris Bruce & Sumit Majumdar & B. P. S. Murthi, 2007. "Wearout Effects of Different Advertising Themes: A Dynamic Bayesian Model of the Advertising-Sales Relationship," Marketing Science, INFORMS, vol. 26(2), pages 179-195, 03-04.
    27. Shijie Lu & Sha Yang, 2017. "Investigating the Spillover Effect of Keyword Market Entry in Sponsored Search Advertising," Marketing Science, INFORMS, vol. 36(6), pages 976-998, November.
    28. Lizhen Xu & Jason A. Duan & Andrew Whinston, 2014. "Path to Purchase: A Mutually Exciting Point Process Model for Online Advertising and Conversion," Management Science, INFORMS, vol. 60(6), pages 1392-1412, June.
    29. C. Clark & Ulrich Doraszelski & Michaela Draganska, 2009. "The effect of advertising on brand awareness and perceived quality: An empirical investigation using panel data," Quantitative Marketing and Economics (QME), Springer, vol. 7(2), pages 207-236, June.
    30. Sha Yang & Anindya Ghose, 2010. "Analyzing the Relationship Between Organic and Sponsored Search Advertising: Positive, Negative, or Zero Interdependence?," Marketing Science, INFORMS, vol. 29(4), pages 602-623, 07-08.
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