IDEAS home Printed from
   My bibliography  Save this article

Economics of Free Under Perpetual Licensing: Implications for the Software Industry


  • Marius F. Niculescu

    () (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

  • D. J. Wu

    () (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)


In this paper, we explore the economics of free under perpetual licensing. In particular, we focus on two emerging software business models that involve a free component: feature-limited freemium ( FLF ) and uniform seeding ( S ). Under FLF , the firm offers the basic software version for free, while charging for premium features. Under S , the firm gives away for free the full product to a percentage of the addressable market uniformly across consumer types. We benchmark their performance against a conventional business model under which software is sold as a bundle (labeled as “charge for everything” or CE ) without free offers. In the context of consumer bounded rationality and information asymmetry, we develop a unified two-period consumer valuation learning framework that accounts for both word-of-mouth (WOM) effects and experience-based learning, and use it to compare and contrast the three business models. Under both constant and dynamic pricing, for moderate strength of WOM signals, we derive the equilibria for each model and identify optimality regions. In particular, S is optimal when consumers significantly underestimate the value of functionality and cross-module synergies are weak. When either cross-module synergies are stronger or initial priors are higher, the firm decides between CE and FLF . Furthermore, we identify nontrivial switching dynamics from one optimality region to another depending on the initial consumer beliefs about the value of the embedded functionality. For example, there are regions where, ceteris paribus, FLF is optimal when the prior on premium functionality is either relatively low or high, but not in between. We also demonstrate the robustness of our findings with respect to various parameterizations of cross-module synergies, strength of WOM effects, and number of periods. We find that stronger WOM effects or more periods lead to an expansion of the seeding optimality region in parallel with a decrease in the seeding ratio. Moreover, under CE and dynamic pricing, second period price may be decreasing in the initial consumer valuation beliefs when WOM effects are strong and the prior is relatively low. However, this is not the case under weak WOM effects. We also discuss regions where price skimming and penetration pricing are optimal. Our results provide key managerial insights that are useful to firms in their business model search and implementation.

Suggested Citation

  • Marius F. Niculescu & D. J. Wu, 2014. "Economics of Free Under Perpetual Licensing: Implications for the Software Industry," Information Systems Research, INFORMS, vol. 25(1), pages 173-199, March.
  • Handle: RePEc:inm:orisre:v:25:y:2014:i:1:p:173-199

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Bing Jing, 2011. "Social Learning and Dynamic Pricing of Durable Goods," Marketing Science, INFORMS, vol. 30(5), pages 851-865, September.
    2. Kapil Bawa & Robert Shoemaker, 2004. "The Effects of Free Sample Promotions on Incremental Brand Sales," Marketing Science, INFORMS, vol. 23(3), pages 345-363, November.
    3. Yifan Dou & Marius F. Niculescu & D. J. Wu, 2013. "Engineering Optimal Network Effects via Social Media Features and Seeding in Markets for Digital Goods and Services," Information Systems Research, INFORMS, vol. 24(1), pages 164-185, March.
    4. N. Gregory Mankiw & Ricardo Reis, 2002. "Sticky Information versus Sticky Prices: A Proposal to Replace the New Keynesian Phillips Curve," The Quarterly Journal of Economics, Oxford University Press, vol. 117(4), pages 1295-1328.
    5. Glenn Ellison & Drew Fudenberg, 1995. "Word-of-Mouth Communication and Social Learning," The Quarterly Journal of Economics, Oxford University Press, vol. 110(1), pages 93-125.
    6. Donald Lehmann & Mercedes Esteban-Bravo, 2006. "When giving some away makes sense to jump-start the diffusion process," Marketing Letters, Springer, vol. 17(4), pages 243-254, December.
    7. Kathleen R. Conner, 1995. "Obtaining Strategic Advantage from Being Imitated: When Can Encouraging "Clones" Pay?," Management Science, INFORMS, vol. 41(2), pages 209-225, February.
    8. Yong-Soon Kang & Paul M. Herr, 2006. "Beauty and the Beholder: Toward an Integrative Model of Communication Source Effects," Journal of Consumer Research, Oxford University Press, vol. 33(1), pages 123-130, June.
    9. Marius F. Niculescu & Hyoduk Shin & Seungjin Whang, 2012. "Underlying Consumer Heterogeneity in Markets for Subscription-Based IT Services with Network Effects," Information Systems Research, INFORMS, vol. 23(4), pages 1322-1341, December.
    10. Ramnath K. Chellappa & Shivendu Shivendu, 2005. "Managing Piracy: Pricing and Sampling Strategies for Digital Experience Goods in Vertically Segmented Markets," Information Systems Research, INFORMS, vol. 16(4), pages 400-417, December.
    11. Rubinstein, Ariel, 1993. "On Price Recognition and Computational Complexity in a Monopolistic Model," Journal of Political Economy, University of Chicago Press, vol. 101(3), pages 473-484, June.
    12. D. J. Wu & Min Ding & Lorin M. Hitt, 2013. "IT Implementation Contract Design: Analytical and Experimental Investigation of IT Value, Learning, and Contract Structure," Information Systems Research, INFORMS, vol. 24(3), pages 787-801, September.
    13. Chrysanthos Dellarocas, 2003. "The Digitization of Word of Mouth: Promise and Challenges of Online Feedback Mechanisms," Management Science, INFORMS, vol. 49(10), pages 1407-1424, October.
    14. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    15. Rabik Ar Chatterjee & Jehoshua Eliashberg, 1990. "The Innovation Diffusion Process in a Heterogeneous Population: A Micromodeling Approach," Management Science, INFORMS, vol. 36(9), pages 1057-1079, September.
    16. Mussa, Michael & Rosen, Sherwin, 1978. "Monopoly and product quality," Journal of Economic Theory, Elsevier, vol. 18(2), pages 301-317, August.
    17. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    18. Shin-yi Wu & Pei-yu Chen, 2008. "Versioning and Piracy Control for Digital Information Goods," Operations Research, INFORMS, vol. 56(1), pages 157-172, February.
    19. Hsing Kenneth Cheng & Yipeng Liu, 2012. "Optimal Software Free Trial Strategy: The Impact of Network Externalities and Consumer Uncertainty," Information Systems Research, INFORMS, vol. 23(2), pages 488-504, June.
    20. Stephen Morris & Hyun Song Shin, 2006. "Inertia of Forward-Looking Expectations," American Economic Review, American Economic Association, vol. 96(2), pages 152-157, May.
    21. Shlomo Kalish, 1983. "Monopolist Pricing with Dynamic Demand and Production Cost," Marketing Science, INFORMS, vol. 2(2), pages 135-159.
    22. Amir Heiman & Bruce McWilliams & Zhihua Shen & David Zilberman, 2001. "Learning and Forgetting: Modeling Optimal Product Sampling Over Time," Management Science, INFORMS, vol. 47(4), pages 532-546, April.
    23. Ying-Ju Chen & Sridhar Seshadri, 2007. "Product Development and Pricing Strategy for Information Goods Under Heterogeneous Outside Opportunities," Information Systems Research, INFORMS, vol. 18(2), pages 150-172, June.
    24. Joe A. Dodson, Jr. & Eitan Muller, 1978. "Models of New Product Diffusion Through Advertising and Word-of-Mouth," Management Science, INFORMS, vol. 24(15), pages 1568-1578, November.
    25. Vijay Mahajan & Eitan Muller & Roger A. Kerin, 1984. "Introduction Strategy for New Products with Positive and Negative Word-of-Mouth," Management Science, INFORMS, vol. 30(12), pages 1389-1404, December.
    26. Andrea Galeotti & Sanjeev Goyal, 2009. "Influencing the influencers: a theory of strategic diffusion," RAND Journal of Economics, RAND Corporation, vol. 40(3), pages 509-532.
    27. Dellarocas, Chrysanthos, 2003. "The Digitization of Word-of-mouth: Promise and Challenges of Online Feedback Mechanisms," Working papers 4296-03, Massachusetts Institute of Technology (MIT), Sloan School of Management.
    28. Spiegler, Ran, 2006. "Competition over agents with boundedly rational expectations," Theoretical Economics, Econometric Society, vol. 1(2), pages 207-231, June.
    29. Daniel Kahneman, 2003. "Maps of Bounded Rationality: Psychology for Behavioral Economics," American Economic Review, American Economic Association, vol. 93(5), pages 1449-1475, December.
    30. Shlomo Kalish, 1985. "A New Product Adoption Model with Price, Advertising, and Uncertainty," Management Science, INFORMS, vol. 31(12), pages 1569-1585, December.
    31. Roy Jones & Haim Mendelson, 2011. "Information Goods vs. Industrial Goods: Cost Structure and Competition," Management Science, INFORMS, vol. 57(1), pages 164-176, January.
    32. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, Oxford University Press, vol. 114(1), pages 37-82.
    33. Ariel Rubinstein, 1997. "Modeling Bounded Rationality," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262681005, March.
    34. Hemant K. Bhargava & Vidyanand Choudhary, 2008. "Research Note--When Is Versioning Optimal for Information Goods?," Management Science, INFORMS, vol. 54(5), pages 1029-1035, May.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. repec:spr:binfse:v:61:y:2019:i:2:d:10.1007_s12599-017-0494-0 is not listed on IDEAS
    2. Guofang Nan & Xingtao Li & Zan Zhang & Minqiang Li, 0. "Optimal pricing for new product entry under free strategy," Information Technology and Management, Springer, vol. 0, pages 1-19.
    3. Terrence August & Marius Florin Niculescu & Hyoduk Shin, 2014. "Cloud Implications on Software Network Structure and Security Risks," Information Systems Research, INFORMS, vol. 25(3), pages 489-510, September.
    4. repec:spr:elcore:v:18:y:2018:i:1:d:10.1007_s10660-017-9264-9 is not listed on IDEAS
    5. Shivendu Shivendu & Zhe (James) Zhang, 2015. "Versioning in the Software Industry: Heterogeneous Disutility from Underprovisioning of Functionality," Information Systems Research, INFORMS, vol. 26(4), pages 731-753, December.


    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:25:y:2014:i:1:p:173-199. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Matthew Walls). General contact details of provider: .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.