Gil Appel, Barak Libai and Eitan Muller (2017), "On the Monetary Impact of Fashion Design Piracy."
July 2017. Read paper.  
We combine data collected on the growth of fashion items with industry statistics, to create a formal analysis and simulations of the monetary impact of a design pirated item (“knockoff”). We distinguish between three effects: Substitution, acceleration and uniqueness and find that while uniqueness emerged as having a stronger negative effect on the original’s profitability than the positive effect of acceleration, the difference between the two is relatively small. However, the negative effect of uniqueness is considerably larger than that of substitution. This is of particular interest given that industry groups have consistently concentrated on the damage caused by substitution.

Eitan Muller and Renana Peres (2017), "The Effect of Social Networks Structure on Innovation Performance:
A Review and Directions for Research."
June 2017. Read paper.
Borrowing from the field of industrial organization in economics, defined as the effect of market structure on market performance, we review the effect of social network structure on innovation performance. Specifically we discuss the effects of  (1) global characteristics of the network: average degree, degree distribution, clustering, & degree assortativity; (2) dyadic relationships: tie strength & embeddedness; (3) individual characteristics: opinion leadership & susceptibility; and (4) location in the social network: degree centrality, closeness centrality & betweenness centrality. Overall, we find that growth is particularly effective in networks that demonstrate the "3 Cs": cohesive (high mutual influence among its members), connected (high number of ties), and concise (low redundancy).

Daria Dzyabura, Srikanth Jagabathula and Eitan Muller (2017), "Accounting for Discrepancies between Online and Offline Product Evaluations."
March 2017. Read paper.
Most preference-elicitation methods that are used to design products and predict market shares, such as conjoint analysis, are conducted online. However, many firms sell their products offline, or through a mixed online-offline channel. In this paper, we demonstrate that large discrepancies can exist between attribute partworths when evaluating physical products versus online descriptions. We propose the following two-step solution for accurate estimation: (1) a data-collection method that combines an online study completed by a large number of respondents with an offline study completed by a small subset of the respondents, and (2) a statistical data-fusion method to estimate offline parameters by combining the online and the offline data. 

Eyal Bialogorsky, Amir Heiman and Eitan Muller (2017), "Branding and the Ravages of Time: The Effect of Time on the Brand Premiums of Automobiles."
March 2017. Read paper.
We present a dynamic analytical model and empirical study of durable goods market with status consciousness of some consumers and show that as the importance of status increases, price of the used product decreases faster. We then use data on prices of new and used cars including the car’s age; its usage (distance driven); its external condition, and its status (premium vs. standard) for 21 twin car pairs, to estimate the deprecation in car values. The main result is that a premium car’s age depreciation is much higher than that of the standard car (controlling for their respective mileages and initial prices). This demonstrates that the true cost of owning a premium car is not just its initial high price, but the faster depreciation of the car’s intangible value over its lifetime.

Gil Appel, Barak Libai, Eitan Muller and Roni Shachar (2016), "Stickiness and the Monetization of Apps."
September 2016. Read paper.
Though free apps dominate mobile markets, firms struggle to monetize such products and make profits, relying on revenues from two sources: paying consumers, and paying advertisers. Accordingly, we introduce a two-period model in which a firm offers an app in two versions: Consumers can download a free version that includes ads, or a paid version without ads. While consumers have some prior knowledge about their fit with the app, they remain uncertain about their exact match-utility unless they are using it. We show that as stickiness increases, so do prices and ad intensity, and the firm’s earning from the paid version increases monotonically. However, its earnings from advertising initially increase, then drop.

Gil Appel, Barak Libai and Eitan Muller (2016), "Growth and Popularity in Markets for Free Digital Products."
June 2016. Read paper.
We demonstrate how free digital products growth dynamics differ from those observed for conventional new products, using a large-scale dataset that documents the growth of close to 60,000 free digital products, and supported by an additional growth analysis of thousands of mobile apps. Free digital products display three distinct patterns of growth: bell-shaped pattern (“Diffuse”); exponential-type decline (“Slide”); and a combination of the two (“Slide and Diffuse”). We show a robust relationship between free digital products popularity and growth patterns. We further show how free digital products-related growth phenomena help explain the patterns that emerge, and elucidate the need to adapt our knowledge on new product growth and its modeling to the world of free digital products.



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