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Is online newspaper advertising cannibalizing print advertising?

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  • Shrihari Sridhar

    (Pennsylvania State University)

  • Srinivasaraghavan Sriram

    (University of Michigan)

Abstract

During the past decade, the newspaper industry experienced significant erosion of revenues, predominantly in print advertising. The concomitant increase in the less rewarding online advertising has been unable to make up for this loss. As a result, for every $1 increase in online advertising between 2005 and 2011, newspapers lost $22 in print advertising. While it is conceivable that the overall change in the advertising landscape (such as the growth of targeted search advertising), contributed to the decline in print advertising, it is not clear whether the growth in online newspaper advertising aggravated or alleviated this global trend. We investigate this concern by studying how advertisers reallocate their media budgets over time between the online and print media within a newspaper. We perform our empirical analysis using unique panel data on account-level advertising expenditures in a Top 50 US newspaper from 2005 through 2011. After accounting for cross-sectional heterogeneity among advertisers and some factors that possibly drove both print and online newspaper advertising, we find a negative relationship between the ad spending in these two media options. Therefore, advertisers exhibit a higher propensity to decrease print spending when they increase their online spending compared to the scenario when online spending either remains unchanged or even decreases. Since we do not rely on exclusion restrictions, we cannot rule out residual factors that drove both print and online advertising and thus contaminated this relationship. However, such potentially confounding factors (e.g., change in total media budget) are likely to have induced a positive correlation between print and online advertising. Therefore, the negative relationship that we recover is suggestive of advertisers perceiving print and online newspaper advertising as substitutes. This, in turn, implies that the growth in online newspaper advertising exacerbated the overall decline in print advertising. Overall, we attribute 7-17 % of the decline in print newspaper advertising revenues between 2005 and 2011 to the growth of online newspaper advertising. We conclude that cannibalization should be a credible consideration in the marketing decisions of the newspaper. However, since a large portion of print advertising revenue decline also occured for advertisers who never purchased online advertising from the newspaper, cannibalization within the newspaper is not solely responsible for the downward trajectory of print advertising.

Suggested Citation

  • Shrihari Sridhar & Srinivasaraghavan Sriram, 2015. "Is online newspaper advertising cannibalizing print advertising?," Quantitative Marketing and Economics (QME), Springer, vol. 13(4), pages 283-318, December.
    • Handle: RePEc:kap:qmktec:v:13:y:2015:i:4:d:10.1007_s11129-015-9160-3
    DOI: 10.1007/s11129-015-9160-3
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    References listed on IDEAS

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    4. Adithya Pattabhiramaiah & Eric Overby & Lizhen Xu, 2022. "Spillovers from Online Engagement: How a Newspaper Subscriber’s Activation of Digital Paywall Access Affects Her Retention and Subscription Revenue," Management Science, INFORMS, vol. 68(5), pages 3528-3548, May.

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    More about this item

    Keywords

    Advertising; Newspapers; Cannibalization; Offline vs. online advertising; Econometric models;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • M37 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Advertising
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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