IDEAS home Printed from https://ideas.repec.org/a/inm/orisre/v33y2022i3p809-823.html
   My bibliography  Save this article

Second Screening—The Influence of Concurrent TV Consumption on Online Shopping Behavior

Author

Listed:
  • Oliver Hinz

    (Goethe University Frankfurt, Faculty of Economics and Business, 60323 Frankfurt am Main, Germany)

  • Shawndra Hill

    (Columbia University, Columbia Business School, Marketing Division, New York, New York 10027)

  • Amit Sharma

    (Microsoft Research India, Bangalore, Karnataka 560001, India)

Abstract

The practice of using a “second screen” while concurrently watching television (TV) has become a widespread phenomenon. Whereas work on multitasking suggests that TV consumption may lead to lower online sales, research in the area of impulse buying suggests the opposite. In this paper, we study the impact of concurrent TV consumption on online shopping behavior and try to understand this conflict. Our first study analyzes the impact of TV consumption on online shopping behavior at the aggregate level using a panel of 100,000 U.S. customers over a period of 24 months. We address potential endogeneity problems with an instrumental variable approach. Our second study proposes a novel approach to realizing individual-level analysis over thousands of consumers and products. Examining massive amounts of data, we identify a sample of consumers who watched a certain TV show and who were simultaneously doing online shopping at Amazon.com. We then compare their shopping behavior on the day of the TV show to their shopping behavior one week prior. Both studies reveal that whereas TV consumption is correlated with a higher likelihood of online shopping in general, the causal effect of TV watching differs with respect to the complexity of the products purchased. If a TV program appeals to a large TV audience, then this results in fewer immediate sales of high-complexity products (1% increase in TV consumption leads to −2.2% sales) and more sales of low-complexity products (1% increase in TV consumption leads to +8.8% sales).

Suggested Citation

  • Oliver Hinz & Shawndra Hill & Amit Sharma, 2022. "Second Screening—The Influence of Concurrent TV Consumption on Online Shopping Behavior," Information Systems Research, INFORMS, vol. 33(3), pages 809-823, September.
    • Handle: RePEc:inm:orisre:v:33:y:2022:i:3:p:809-823
    DOI: 10.1287/isre.2021.1099
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/isre.2021.1099
    Download Restriction: no
    File URL: https://libkey.io/10.1287/isre.2021.1099?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. Kleibergen, Frank & Paap, Richard, 2006. "Generalized reduced rank tests using the singular value decomposition," Journal of Econometrics, Elsevier, vol. 133(1), pages 97-126, July.
    2. Mitchell Lovett & Renana Peres & Ron Shachar, 2014. "A Data Set of Brands and Their Characteristics," Marketing Science, INFORMS, vol. 33(4), pages 609-617, July.
    3. Hall, Alastair R & Rudebusch, Glenn D & Wilcox, David W, 1996. "Judging Instrument Relevance in Instrumental Variables Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 37(2), pages 283-298, May.
    4. Jura Liaukonyte & Thales Teixeira & Kenneth C. Wilbur, 2015. "Television Advertising and Online Shopping," Marketing Science, INFORMS, vol. 34(3), pages 311-330, May.
    5. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
    6. Bart J. Bronnenberg & Jun B. Kim & Carl F. Mela, 2016. "Zooming In on Choice: How Do Consumers Search for Cameras Online?," Marketing Science, INFORMS, vol. 35(5), pages 693-712, September.
    7. Jeffrey L. Jenkins & Bonnie Brinton Anderson & Anthony Vance & C. Brock Kirwan & David Eargle, 2016. "More Harm Than Good? How Messages That Interrupt Can Make Us Vulnerable," Information Systems Research, INFORMS, vol. 27(4), pages 880-896, December.
    Full references (including those not matched with items on IDEAS)

    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. Beth L. Fossen & Girish Mallapragada & Anwesha De, 2021. "Impact of Political Television Advertisements on Viewers’ Response to Subsequent Advertisements," Marketing Science, INFORMS, vol. 40(2), pages 305-324, March.
    2. Luo, Anita & Baker, Andrew & Donthu, Naveen, 2019. "Capturing dynamics in the value for brand recommendations from word-of-mouth conversations," Journal of Business Research, Elsevier, vol. 104(C), pages 247-260.
    3. Aniket A. Kawatkar & Joel W. Hay & William Stohl & Michael B. Nichol, 2013. "Incremental Expenditure Of Biologic Disease Modifying Antirheumatic Treatment Using Instrumental Variables In Panel Data," Health Economics, John Wiley & Sons, Ltd., vol. 22(7), pages 807-823, July.
    4. Beth L. Fossen & David A. Schweidel, 2019. "Measuring the Impact of Product Placement with Brand-Related Social Media Conversations and Website Traffic," Marketing Science, INFORMS, vol. 38(3), pages 481-499, May.
    5. Vilma Todri, 2022. "Frontiers: The Impact of Ad-Blockers on Online Consumer Behavior," Marketing Science, INFORMS, vol. 41(1), pages 7-18, January.
    6. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/generalized method of moments estimation and testing," Stata Journal, StataCorp LP, vol. 7(4), pages 465-506, December.
    7. Christopher F Baum & Mark E. Schaffer & Steven Stillman, 2007. "Enhanced routines for instrumental variables/GMM estimation and testing," Boston College Working Papers in Economics 667, Boston College Department of Economics, revised 05 Sep 2007.
    8. Košak, Marko & Li, Shaofang & Lončarski, Igor & Marinč, Matej, 2015. "Quality of bank capital and bank lending behavior during the global financial crisis," International Review of Financial Analysis, Elsevier, vol. 37(C), pages 168-183.
    9. Murray Michael P., 2017. "Linear Model IV Estimation When Instruments Are Many or Weak," Journal of Econometric Methods, De Gruyter, vol. 6(1), pages 1-22, January.
    10. Arturas Juodis, 2013. "Cointegration Testing in Panel VAR Models Under Partial Identification and Spatial Dependence," UvA-Econometrics Working Papers 13-08, Universiteit van Amsterdam, Dept. of Econometrics.
    11. Vieira, Flávio & MacDonald, Ronald & Damasceno, Aderbal, 2012. "The role of institutions in cross-section income and panel data growth models: A deeper investigation on the weakness and proliferation of instruments," Journal of Comparative Economics, Elsevier, vol. 40(1), pages 127-140.
    12. Torgler, Benno & Schneider, Friedrich & Schaltegger, Christoph A., 2007. "With or Against the People? The Impact of a Bottom-Up Approach on Tax Morale and the Shadow Economy," Berkeley Olin Program in Law & Economics, Working Paper Series qt6331x6vz, Berkeley Olin Program in Law & Economics.
    13. William Arbour, 2021. "Can Recidivism be Prevented from Behind Bars? Evidence from a Behavioral Program," Working Papers tecipa-683, University of Toronto, Department of Economics.
    14. MacDonald, Peter, 2013. "Labour substitution and the scope for military outsourcing," MPRA Paper 46688, University Library of Munich, Germany.
    15. Aziz Barhmi & Omar Hajaji, 2023. "Multidisciplinary Approach to Supply Chain Resilience: Conceptualization and Scale Development," Central European Business Review, Prague University of Economics and Business, vol. 2023(5), pages 43-69.
    16. Pengyu Zhu, 2013. "Telecommuting, Household Commute and Location Choice," Urban Studies, Urban Studies Journal Limited, vol. 50(12), pages 2441-2459, September.
    17. Morosan, Cristian, 2016. "An empirical examination of U.S. travelers’ intentions to use biometric e-gates in airports," Journal of Air Transport Management, Elsevier, vol. 55(C), pages 120-128.
    18. Neslin, Scott A., 2022. "The omnichannel continuum: Integrating online and offline channels along the customer journey," Journal of Retailing, Elsevier, vol. 98(1), pages 111-132.
    19. David S. Lee & Justin McCrary & Marcelo J. Moreira & Jack Porter, 2022. "Valid t-Ratio Inference for IV," American Economic Review, American Economic Association, vol. 112(10), pages 3260-3290, October.
    20. Maarten A. Allers & Corine Hoeben, 2010. "Effects of Unit-Based Garbage Pricing: A Differences-in-Differences Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 45(3), pages 405-428, March.

    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:inm:orisre:v:33:y:2022:i:3:p:809-823. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.