Marius Florin Niculescu

Engineering Optimal Network Effects via Social Media Features and Seeding in Markets for Digital Goods and Services

Firms nowadays are increasingly proactive in trying to strategically capitalize on consumer networks and social interactions. In this paper, we complement an emerging body of research on the engineering of word-of-mouth effects by exploring a different angle through which firms can strategically exploit the value-generation potential of the user network. Namely, we consider how software firms should optimize the strength of network effects at utility level by adjusting the level of embedded social media features in tandem with the right market seeding and pricing strategies in the presence of seeding disutility. We explore two opposing seeding cost models where seeding-induced disutility can be either positively or negatively correlated with customer type. We consider both complete and incomplete information scenarios for the firm. Under complete information, we uncover a complementarity relationship between seeding and building social media features that holds for both disutility models. When the cost of any of these actions increases, rather than compensating by a stronger action on the other dimension to restore the overall level of network effects, the firm will actually scale back on the other initiative as well. Under incomplete information, this complementarity holds when seeding disutility is negatively correlated with customer type but may not always hold in the other disutility model, potentially leading to fundamentally different optimal strategies. We also discuss how our insights apply to asymmetric networks.

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

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 freemiumFLF and uniform seedingS. 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.

Cloud Implications on Software Network Structure and Security Risks

By software vendors offering, via the cloud, software-as-a-service SaaS versions of traditionally on-premises application software, security risks associated with usage become more diversified. This can greatly increase the value associated with the software. In an environment where negative security externalities are present and users make complex consumption and patching decisions, we construct a model that clarifies whether and how SaaS versions should be offered by vendors. We find that the existence of version-specific security externalities is sufficient to warrant a versioned outcome, which has been shown to be suboptimal in the absence of security risks. In high security-loss environments, we find that SaaS should be geared to the middle tier of the consumer market if patching costs and the quality of the SaaS offering are high, and geared to the lower tier otherwise. In the former case, when security risk associated with each version is endogenously determined by consumption choices, strategic interactions between the vendor and consumers may cause a higher tier consumer segment to prefer a lower inherent quality product. Relative to on-premises benchmarks, we find that software diversification leads to lower average security losses for users when patching costs are high. However, when patching costs are low, surprisingly, average security losses can increase as a result of SaaS offerings and lead to lower consumer surplus. We also investigate the vendors security investment decision and establish that, as the market becomes riskier, the vendor tends to increase investments in an on-premises version and decrease investments in a SaaS version. On the other hand, in low security-loss environments, we find that SaaS is optimally targeted to a lower tier of the consumer market, average security losses decrease, and consumer surplus increases as a result. Security investments increase for both software versions as risk increases in these environments.

Research Note---Codiffusion of Wireless Voice and Data Services: An Empirical Analysis of the Japanese Mobile Telecommunications Market

Wireless telecommunications have become over time a ubiquitous tool that not only sustains our increasing need for flexibility and efficiency, but also provides new ways to access and experience both utilitarian and hedonic information goods and services. This paper explores the parallel market evolution of the two main categories of wireless services---voice and data---in leading technology markets, inspecting the differences and complex interactions between the associated adoption processes. We propose a model that addresses specific individual characteristics of these two services and the stand-alone/add-on relationship between them. In particular, we acknowledge the distinction between the nonoverlapping classes of basic consumers, who only subscribe to voice plans, and sophisticated consumers, who adopt both services. We also account for the fact that, unlike voice services, data services rapidly evolved over time due to factors such as interface improvement, gradual technological advances in data transmission speed and security, and the increase in volume and diversity of the content and services ported to mobile Internet. Moreover, we consider the time gap between the market introduction of these services and allow for different corresponding consumer learning curves. We test our model on the Japanese wireless market. The empirical analysis reveals several interesting results. In addition to an expected one-way effect of voice on data adoption at the market potential level, we do find two-way codiffusion effects at the speed of adoption level. We also observe that basic consumers impact the adoption of wireless voice services in a stronger way compared to sophisticated consumers. This, in turn, leads to a decreasing average marginal network effect of voice subscribers on the adoption of wireless voice services. Furthermore, we find that the willingness of voice consumers to consider adopting data services is positively related to both time and penetration of 3G-capable handsets among voice subscribers.

Underlying Consumer Heterogeneity in Markets for Subscription-Based IT Services with Network Effects

In this paper we explore the underlying consumer heterogeneity in competitive markets for subscription-based information technology services that exhibit network effects. Insights into consumer heterogeneity with respect to a given service are paramount in forecasting future subscriptions, understanding the impact of price and information dissemination on market penetration growth, and predicting the adoption path for complementary products that target the same customers as the original service. Employing a continuous-time utility model, we capture the behavior of a continuum of consumers who are differentiated by their intrinsic valuations from using the service. We study service subscription patterns under both perfect and imperfect information dissemination. In each case, we first specify the conditions under which consumer rational behavior supported by the utility model can explain a general observed adoption path, and if so, we explicitly derive the analytical closed-form expression for the consumer valuation distribution. We further explore the impact of awareness and distribution skewness on adoption. In particular, we highlight the practical forecasting importance of understanding the information dissemination process in the market as observed past adoption may be explained by several distinct awareness and heterogeneity scenarios that may lead to divergent adoption paths in the future. Moreover, we show that in the later part of the service lifecycle the subscription decision for new customers can be driven predominantly by information dissemination instead of further price markdowns. We also extend our results to time-varying consumer valuation scenarios. Furthermore, based on our framework, we advance a set of heuristic methods to be applied to discrete-time real industry data for estimation and forecasting purposes. In an empirical exercise, we apply our methodology to the Japanese mobile voice services market and provide relevant managerial insights from the analysis.

The Influence of Software Process Maturity and Customer Error Reporting on Software Release and Pricing

Software producers are making greater use of customer error reporting to discover defects and improve the quality of their products. We study how software development differences among producers e.g., varying levels of process maturity and software class and functionality differences e.g., operating system versus productivity software affect how these producers coordinate software release timing and pricing to optimally harness error reporting contributions from users. In settings where prices are fixed, we characterize the optimal release time and demonstrate why in some cases it can actually be preferable to delay release when customer error reporting rates increase. The manner in which a firms optimal release time responds to increases in software functionality critically hinges on whether the added functionality enhances or dilutes user error reporting; in both cases, the effect of added functionality on release timing can go in either direction, depending on both firm and product market characteristics. For example, when processing costs are relatively large compared with goodwill costs, firms with lower process maturity will release earlier when per-module error reporting contributions become diluted and release later when these contributions become enhanced. We also examine how a firm adapts price with changes in error reporting levels and software functionality, and finally, we provide implications of how beta testing influences release timing. This paper was accepted by Lorin Hitt, information systems.

Optimal Consumer Network Structure Formation under Network Effects: Seeds Controllability and Visibility

Understanding the process of software adoption is of paramount importance to software start-ups. We study a monopolistic seller’s optimal consumer network structure formation (seeding, segmentation, sequencing, and pricing strategies) under network effects. We demonstrate the importance of adoption sequencing as well as controllability over the seeding process to seller’s profit, consumer surplus, and social welfare. Under multi-pricing, full information, and full control over the seeding process, with both multiplicative and additive forms of network effects, we show that all segments contain only paying customers except the first one, which contains both seeded and paying customers; and segments are opened in order of the customer valuation. Further, the seller’s optimal strategy is socially optimal. Under single-pricing and limited seeding control, worst case seeding (where all seeds go to the high-valuation customers) leads to higher social welfare and consumer surplus than uniform seeding, as the former covers a larger portion of the market while charging a lower price. In the case of random seeding with limited control, we identify an optimal strategy and conditions under which the optimal price is not affected by the randomness of seeding.

Strategic Intellectual Property Sharing: Competition on an Open Technology Platform Under Network Effects

In this paper, we explore the strategic decision of an incumbent to open a proprietary technology platform to allow same-side co-opetition in a market characterized by network effects. We propose a game-theoretic model that analytically conceptualizes the interplay among the degree of same-side platform openness, the absorptive capacity of the entrant, and the intensity of network effects. Our analysis uncovers interesting new results. First, when entrant product quality is exogenous, under very strong network effects, the incumbent closes the technology. Moreover, we discuss various interesting open-platform co-opetition outcomes that arise under a fully covered market. When the entrant chooses the quality level and the incumbent is strategic in its platform opening decision, we find that intense network effects make new players shun the market, so intellectual property (IP) sharing is not possible in equilibrium. When the network effects are of intermediate intensity, the incumbent opens the technology ...