Author List: Niculescu, Marius F.; Wu, D. J.;

Information Systems Research, 2014, Volume 25, Issue 1, Page 173-199.

In this paper, we explore the economics of <i>free</i> under perpetual licensing. In particular, we focus on two emerging software business models that involve a free component: <i>feature-limited freemium</i> (<i>FLF</i>) and <i>uniform seeding</i> (<i>S</i>). Under <i>FLF</i>, the firm offers the basic software version for free, while charging for premium features. Under <i>S</i>, the firm gives away for free the full product to a <i>percentage</i> of the addressable market <i>uniformly</i> 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 <i>CE</i>) 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, <i>S</i> 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 <i>CE</i> and <i>FLF</i>. 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, <i>FLF</i> is optimal when the prior on <i>premium</i> 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 <i>CE</i> 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.

Keywords: software;freemium business models;versioning;seeding strategies;product sampling