Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls

39 Pages Posted: 31 Jul 2017 Last revised: 17 Jun 2018

Haris Krijestorac

University of Texas at Austin, Red McCombs School of Business, Students

Rajiv Garg

University of Texas at Austin - Department of Information, Risk and Operations Management

Vijay Mahajan

University of Texas at Austin - Department of Information, Risk and Operations Management

Frenkel Ter Hofstede

University of Texas at Austin - Red McCombs School of Business

Date Written: July 31, 2017

Abstract

To inform product release and distribution strategies, research has analyzed cross-market spillovers in new product adoption. However, models that examine these effects for digital and viral media are still evolving. Given increasing resistance to advertising, many of today’s firms seek to promote their own viral content to generate brand awareness. Unfortunately, a key shortcoming of virality is its ephemeral nature. To gain insight into sustaining the popularity of viral content, we develop a quasi-experimental model that estimates the spillover created by introducing a piece of content onto a new platform on its consumption in a focal platform. We propose that by introducing their content to the audience of a new platform, firms can generate additional word-of-mouth (WOM), which may affect consumption within an initial platform. We estimate our model using data on 381 viral videos viewed on 26 platforms (e.g., YouTube, Vimeo), and we observe how consumption of videos on an initial “lead” platform is affected by their subsequent introduction onto “lag” platforms. This backward spillover is estimated as follows: for each multi-platform video, we compare its view growth after being added to a new platform to that of a synthetic control based on similar single-platform videos. Analysis of 289 such spillovers reveals that cross-platform spillover is positive, persistent, bursty, and strongest in the first 48 days. We also find that spillover is stronger for larger platforms, foreign platforms, and platforms that achieve peak WOM more quickly. Delaying a video’s introduction onto a lag platform affects spillover concavely, while its introduction onto additional lag platforms shows diminishing returns. Implications are discussed for platforms and marketers.

Keywords: spillover effect, quasi-experiments, synthetic control, information diffusion, viral marketing

Suggested Citation

Krijestorac, Haris and Garg, Rajiv and Mahajan, Vijay and Ter Hofstede, Frenkel, Cross-Platform Spillover Effects in Consumption of Viral Content: A Quasi-Experimental Analysis Using Synthetic Controls (July 31, 2017). Available at SSRN: https://ssrn.com/abstract=3011533 or http://dx.doi.org/10.2139/ssrn.3011533

Haris Krijestorac (Contact Author)

University of Texas at Austin, Red McCombs School of Business, Students ( email )

Austin, TX
United States

Rajiv Garg

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

CBA 5.202
Austin, TX 78712
United States

HOME PAGE: http://www.RajivGarg.org

Vijay Mahajan

University of Texas at Austin - Department of Information, Risk and Operations Management ( email )

Red McCombs School of Business
2100 Speedway, #B6600
Austin, TX 78712
United States

Frenkel Ter Hofstede

University of Texas at Austin - Red McCombs School of Business ( email )

Austin, TX 78712
United States

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