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  1. The interdependence of intellectual property and sales in the manufacturing industry
    evidence from the triangle of patents, trademarks, and sales
    Author: Lambrecht, Darius; Block, Jörn; Neuenkirch, Matthias; Steinmetz, Holger; Willeke, Tom
    Published: [2023]
    Publisher:  Universität Trier, Trier

    Firms often struggle with the successful commercialization of innovations, and there is a need for reliable predictors. Prior research suggests that intellectual property (IP) rights play a key role in the commercialization of innovations. However,... more

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    Location:
    ZBW - Leibniz-Informationszentrum Wirtschaft, Standort Kiel
    Signature:
    DS 434
    Inter-library loan:
    No inter-library loan

     

    Firms often struggle with the successful commercialization of innovations, and there is a need for reliable predictors. Prior research suggests that intellectual property (IP) rights play a key role in the commercialization of innovations. However, to what extent can IP rights be used to predict successful commercialization of innovations in the manufacturing industry? Our paper studies the role of patents and trademarks and their complementary and substitutive relationships to predict commercialization success as measured by sales. We also analyze potential reciprocal relationships between commercial success and IP rights. The relationships are explored in a panel dataset of 2,617 German Mittelstand firms over a 10-year period. The results of a panel vector autoregressive model show a short-lived positive effect of patents on sales growth and vice versa. However, no significant effects are found between trademarks and sales growth. Finally, a positive and complementary relationship between patents and trademarks is documented.

     
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    Source: Union catalogues
    Language: English
    Media type: Book
    Format: Online
    Other identifier:
    hdl: 10419/283461
    Series: Research papers in economics ; no. 23, 10
    Subjects: Innovation; Commercialization; Patents; Trademarks; Panel Vector Autoregression
    Scope: 1 Online-Ressource (circa 36 Seiten), Illustrationen