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The relationship between consumer characteristics and willingness to pay for general online content: Implications for content providers considering subscription-based business models

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  • Girish Punj

Abstract

An increasing number of digital content providers are considering ways to charge consumers for content that was previously free. A key question for these companies is whether a change in business model from one that is advertising-based to one that is subscription-based likely to generate more revenue? Hence, the purpose of the research is to profile consumers who are more likely to pay for online content and estimate the amount they are likely to pay. Data from a nationally representative probability sample of 755 internet users are used to estimate the model. The results indicate that while the estimated amount paid for digital content is related to income and education, willingness to pay is more related to age and gender. The findings have important implications for digital content providers who are evaluating the possibility of shifting from an advertising supported content-for-free model to a subscription supported pay-for-content business model. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Girish Punj, 2015. "The relationship between consumer characteristics and willingness to pay for general online content: Implications for content providers considering subscription-based business models," Marketing Letters, Springer, vol. 26(2), pages 175-186, June.
  • Handle: RePEc:kap:mktlet:v:26:y:2015:i:2:p:175-186
    DOI: 10.1007/s11002-013-9273-y
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    References listed on IDEAS

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    1. Stigler, George J., 2011. "Economics of Information," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 5, pages 35-49.
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    2. Stephanie Lang & Giulia Minnucci & Matthias Mueller & Michael P. Schlaile, 2023. "The Role of Consumers in Business Model Innovations for a Sustainable Circular Bioeconomy," Sustainability, MDPI, vol. 15(12), pages 1-19, June.
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    4. Jin Li & Kwok Fai Tso & Fangtao Liu, 2017. "Profit earning and monetary loss bidding in online entertainment shopping: the impacts of bidding patterns and characteristics," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(1), pages 77-90, February.
    5. Bray, J. & De Silva Kanakaratne, M. & Dragouni, M. & Douglas, J., 2021. "Thinking inside the box: An empirical exploration of subscription retailing," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    6. Raphaël Maucuer & Alexandre Renaud & Sébastien Ronteau & Laurent Muzellec, 2022. "What can we learn from marketers? A bibliometric analysis of the marketing literature on business model research," Post-Print hal-03718522, HAL.
    7. Man-, ZuyiKeunZuyi Wang & Takagi, Chifumi & Kim, Man-Keun & Chung, Anh, 2022. "Uncover Drivers Influencing Consumers' WTP Using Machine Learning: Case of Organic Coffee in Taiwan," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322150, Agricultural and Applied Economics Association.
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    9. Zhang, Mingli & Zhang, Yan & Zhao, Lu & Li, Xiaoyong, 2020. "What drives online course sales? Signaling effects of user-generated information in the paid knowledge market," Journal of Business Research, Elsevier, vol. 118(C), pages 389-397.

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