Search

The music industry is [still] in a genuine maelstrom. Globalization is affecting this industry more than many other industries and it is primarily induced by developments in Information Technology. The foremost avenue for change is through the institution providing the foundation of the industry - copyright, which [may] be largely disabled. The oddly global and local structure of the music industry [,premised on copyrights, might] be undergoing some fundamental changes. The roles of music publishers and record companies especially [may be] about to alter. In an institutional economic analysis, I will analyze the present situation in this industry, where Information Technology impacts on this system, and how in general the industry is likely to change. [The original article was featured in the May of 2000 issue of First Monday - much has changed since then, but much of my original text still seems to have some validity. What may have changed, however, are the likely prospects for this industry, especially for incumbent firms.] [ABSTRACT FROM AUTHOR]

Recent scholarship has started to recognize the need to understand the role of contracts in processes of circular business model innovation, particularly in Product Service Systems (PSS) business models. Ownership, usage right and risk allocation are key aspects of contract design, all influencing circular business model innovation. However, current knowledge of how contracts support emerging circular business models is limited. In this paper, we address this gap by presenting an in-depth analysis of a case study drawing on data stemming from the Fairphone-as-a-Service project to define key elements for a Circular Service Contract Template. Our findings support the idea that contracts, ownership, and usage right issues strongly influence the core elements of a PSS business model, such as servitization , longevity and modularity. Particularly, evidence from the case study confirmed the presence of tensions between ownership and contractual aspects when attempting to manage the circular business practices. • Key elements in circular economy contracts differ from linear business contracts. • Servitization, longevity and modularity are key aspects of CBMI. • Contractual mechanisms can enable critical CBMI processes in PSS models. • Contracts can be used for strategic purposes in CBMI for PSS models. • Contracts can enhance the applicability and scalability of PSS models. [ABSTRACT FROM AUTHOR]

Digital technologies nowadays play a major role in innovation within the agri-food domain. The evolution of IT systems has currently arrived at a level that involves complex systems integration and business ecosystems in which many stakeholders in different roles are involved. A new paradigm for digital innovation is needed that copes with this increased complexity. This paper presents an empirically informed framework for analysing and designing viable, sustainable digital innovation ecosystems in the agri-food domain. The research is based on a series of European large-scale public-private innovation projects from 2011 to 2021 with a total budget of 73 M€. They involved hundreds of stakeholders that were developing a large number of digital solutions through which a digital innovation ecosystem for agri-food was formed. In a longitudinal study, a conceptual framework was used to analyse these projects and describe how the digital innovation ecosystem has developed. Lessons learnt are translated into a number of design principles and an organizational approach to foster digital innovation ecosystems in agri-food. The conceptual framework consists of 6 key concepts: (i) innovation strategy, (ii) innovation organization, (iii) innovation network that contains (iv) the innovation process and (v) the innovation object and finally (vi) an innovation infrastructure. Along these 6 concepts, lessons learnt and in total 21 design principles are derived from analysing the projects forming a basis for the organizational framework. At the core of this framework is a lean multi-actor approach to trials and use case development interacting with a set of multidisciplinary activities: (i) developing a common technical collaboration infrastructure, (ii) identifying value streams with user engagement, (iii) engaging the right partners and stakeholders at the right time supported by strategic project planning and dynamic management. The most important conclusion is that effective, successful and quick use of appropriate IT in agri-food requires that actors should not be analysed in isolation from both their technological and business environment. Another consequence is that a 'minimal viable ecosystem' only emerges after considerable time, resources and ingenuity is invested and may require outside (government) intervention. Results from this paper can be used both by public and private stakeholders to diagnose and improve digital innovation projects and develop viable, sustainable digital innovation ecosystems in agri-food. [Display omitted] • A data economy for food systems based on data spaces requires understanding and optimizing digital innovation ecosystems. • A conceptual framework is used to analyse the development of large digital innovation ecosystems in agri-food in Europe. • Lessons learnt are translated into design principles and approach to organize digital innovation ecosystems in agri-food. • The core is a lean multi-actor approach in use case development interacting with multidisciplinary activities. • The framework, design principles and approach can be used by stakeholders to foster viable digital innovation ecosystems. [ABSTRACT FROM AUTHOR]

Artificial intelligence-driven drug discovery (AIDD) companies hold significant promise for transforming pharmaceutical development, yet little is known about how they manage partnerships with established pharmaceutical firms. To address this research gap, our study explores how AIDD companies develop and leverage relational capabilities to enhance collaboration effectiveness. Through a case study approach, we focus on four key relational aspects: identifying complementary capabilities, establishing effective governance mechanisms, creating relationship-specific assets, and developing interfirm knowledge-sharing routines. Our findings demonstrate that particularly effective governance of intellectual property is essential for partnership success. We offer actionable recommendations for AIDD companies to strengthen collaborations, thereby contributing to the realization of AI's potential in drug discovery., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

In recent years, the rapid growth of user-generated content has led to much research evaluating the patterns of online information exchange. These studies demonstrate that online communities are valuable data sources which provide rich, longitudinal data that would otherwise be difficult, if not impossible to access. Given the increased research interest, mining and analysing online social networks has become an important research domain, encompassing a variety of approaches. To analyse the large number of observations commonly found in online communities, we propose to first mine the data using a so-called Webscraper and then combine Social Network Analysis (SNA) with Sentiment Analysis to explore both content and relationships. The hands-on approach described in this article is targeted at researchers without a background in technical disciplines. Instead of focusing on some of the specific algorithms that facilitate the mining and analysis of online data, we describe how to use and combine out-of-the-box solutions to collect and analyse the online network data. Moreover, we document the steps taken and present important lessons learnt throughout the process of collecting and analysing data from an online health community with 108,569 registered users who contributed to 197,980 discussions with a total of 484,250 replies. In sum, our method proposes to:•Extract all relevant data from an openly accessible online community using a Webscraper.•Determine and visualise the relationships between users and the properties of the social network as a whole using Social Network Analysis.•Conduct Sentiment Analysis to detect the emotional tone of the online contributions, and to possibly infer further variables from the text such as the personality characteristics of users., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)