nep-ipr New Economics Papers
on Intellectual Property Rights
Issue of 2026–03–30
three papers chosen by
Giovanni Battista Ramello, Università di Turino


  1. Innovation and Competition with Imperfect Patent Protection By Marek Dietl; Łukasz Skrok; Bartłomiej Wiśnicki
  2. Color Analytics for Data-Driven Brand Communications By Daria Dzyabura; Renana Peres; Irina Linevich
  3. Spillovers from science By Ralf Martin; Arjun Shah; Anna Valero; Dennis Verhoeven

  1. By: Marek Dietl; Łukasz Skrok; Bartłomiej Wiśnicki
    Abstract: We employ a duopoly model with horizontal differentiation of a product to analyse impact of imperfect patent rights in the form of a patent thicket on market entry and outcomes in a market when a single unit of a good is to be provided, reflecting a competition of two potential suppliers within a tender procedure of a complex product. We show that even under price competition, a treat of litigation coming from the overlap in the patent protection leads to pricing decisions above marginal costs level. Such a situation, on the one hand, is socially costly due to costs linked to fixed costs of market entry of both competitors, but on the other hand, it is not necessarily the most beneficial from the point of view of a buyer. The paper resolves Bertrand paradox in a novel way.
    Keywords: patent thickets, horizontal differentiation, Bertrand paradox
    JEL: D23 K11 L13 O34
    Date: 2025–05
    URL: https://d.repec.org/n?u=RePEc:sgh:kaewps:2025112
  2. By: Daria Dzyabura (New Economic School); Renana Peres (Hebrew University of Jerusalem); Irina Linevich (MIT Sloan School of Management)
    Abstract: Color is an important component in brand visual communication. Firms select brand colors to align with the brand's strategic positioning goals. Despite their importance, brand color decisions are often driven by intuition and trial and error. We introduce BRACE (BRand Attribute and Color Engine), a predictive model and genetic-algorithm based optimization framework, that generates color palettes that reflect combinations of brand characteristics. Using theory on color combinations and color harmonies, the model avoids contradictions across characteristics while maintaining visual harmony. For example, if a brand seeks to be perceived as Friendly and Glamorous, or highly Outdoorsy but not Young, we recommend aesthetically appealing color palettes that best capture these attribute combinations. We validate the algorithm through a series of experiments. We also find that real ads recolored with recommended palettes are rated significantly higher on the intended brand characteristics. We further use topic modeling to provide interpretable insights into the relationships between characteristics and colors, and how these relationships vary across product categories. This paper is a major step towards data-driven brand visual communication that can better align creative choices with communication goals.
    Keywords: Image analytics, branding, color, machine learning, genetic algorithm, topic modeling, brand personality, BRACE. JEL Classifications: M31, M37, C45, C55, D12
    Date: 2025–12
    URL: https://d.repec.org/n?u=RePEc:abo:neswpt:w0292
  3. By: Ralf Martin; Arjun Shah; Anna Valero; Dennis Verhoeven
    Abstract: Quantifying spillovers from scientific knowledge to technology is important for understanding the social returns to science and for designing policy. A key challenge is how to credit scientific work with the value generated in downstream technologies when ideas diffuse through chains of follow-on research. We propose a new measure - Science Rank - that uses the combined patent and paper citation network to assign a share of the private value of patented inventions to the scientific papers they directly or indirectly rely on. Validated against various types of scientific awards, the measure substantially outperforms direct patent-to-paper citation counts in identifying influential science. We document large heterogeneity in spillovers across countries, disciplines, and institutions. The US emerges from our analysis as a powerhouse of science spillovers, benefiting both domestic and foreign technology development. We apply our methodology to examine how different countries and individual institutions contribute to innovation that addresses global challenges such as climate change or more equal economic development. We find that a relatively large share of the total value generated by research in Lower and Middle Income Country (LMIC) feeds into climate change related innovation. We also highlight countries and institutions that are making particular contributions to LMIC innovation.
    Keywords: Technological change, growth, patents, spillovers, climate change, economic development
    Date: 2026–03–18
    URL: https://d.repec.org/n?u=RePEc:cep:cepdps:dp2165

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