Purpose This study aims to explore the potential of entrepreneurship through acquisition (ETA) in the underexplored sector of small and medium-sized web-based businesses, addressing the succession crisis in industrialized nations and offering insights into the digital ETA landscape. Design/methodology/approach The research uses a qualitative approach, conducting in-depth interviews with 19 established website owners from diverse backgrounds and industries. The study investigates their business models, selling motivations and characteristics to provide insights for potential buyers in the digital ETA space. Findings Web-based small and medium-sized enterprises (SMEs) present unique opportunities for ETA, characterized by lower initial investment, higher scalability and diverse revenue streams. Key considerations for buyers include understanding seller motivations, evaluating niche focus and assessing the impact of emerging technologies such as artificial intelligence on content creation and search engine optimization. The findings also highlight the importance of authenticity and user engagement in maintaining website value. Practical implications The findings offer valuable insights for entrepreneurs considering ETA in the digital space, highlighting critical factors for success, potential risks and mitigation strategies in acquiring web-based businesses. Originality/value This paper bridges a significant gap in ETA literature by focusing on web-based SMEs, which have previously been overlooked despite their growing importance in the digital economy. It provides a comprehensive analysis of relevant factors when evaluating web-based businesses in the context of ETA, particularly in light of technological advancements and changing online landscapes.

Purpose In this study, we investigate how capability in managing intellectual property may be treated as a type of “dynamic capability,” and we seek to understand how, when it is linked to the new technology development capability of a complex technological organization, these two types of dynamic capabilities may coevolve. Design/methodology/approach We conducted a longitudinal empirical case study of Airbus, incorporating an abductive research methodology that required investigating theory and empirical data concurrently and iteratively. The data, ranging over a period of two decades from 2000 to 2021, was collected from four different sources, including interviews, internal company documents, publicly available information and patent data. Findings Our main findings are that the capabilities and roles of the Intellectual Property function in Airbus and their interaction with the company's Technology function have indeed influenced the overall innovation strategy of the organization, and that three coevolutionary phases may be identified in the interactive development of the two functions. Research limitations/implications Our investigation into how new technology development and intellectual property (IP) management capabilities coevolve within complex technological organizations, exemplified by Airbus, provides significant theoretical and practical implications. Theoretically, it enhances understanding of capability co-development dynamics in complex organizations, particularly in strategic IP management. Practically, it suggests aligning IP strategy with overall corporate objectives and optimizing organizational structures to promote collaboration and efficiency across IP and technology teams. This alignment may foster innovation, maximize the value of intellectual assets and strengthen collaborations, positioning organizations for long-term success in competitive landscapes. Originality/value This study makes a fresh contribution to the innovation studies literature by showing how if intellectual property management is treated as a core function of a complex technological organization – rather than simply as a vehicle for protecting new inventions and products after the fact or simply as a constituent part of the organization's legal function – it may contribute proactively to the organization's technological innovation performance. We also address the current gap in the academic literature for a clear understanding of the processes by which different function-specific dynamic capabilities may coevolve in a complex organization operating as part of a dynamic and complex adaptive system.

Any quasi-probability representation of a no-signaling system – including quantum systems – can be simulated via a purely classical scheme by allowing signed events and a cancellation procedure. This raises a fundamental question: What properties of the non-classical system does such a classical simulation fail to replicate? We answer by using large deviation theory to show that the probability of a large fluctuation under the classical simulation can be strictly greater than under the actual non-classical system. The key finding driving our result is that negativity in probability relaxes the data processing inequality of information theory. We propose this potential large deviation stability of quantum (and no-signaling) systems as a novel form of quantum advantage.

Adopting AI-based solutions is now widely regarded as an essential consideration in organisations’ innovation strategies. For healthcare institutions, such solutions are an especially promising means to address societal and organisational challenges, including rising demand combined with shortages of qualified staff. The technology may enhance the efficiency of, for example, detecting diseases and planning treatments, which are time-consuming when executed manually. However, empirical research related to how AI can be effectively adopted in healthcare to harness these opportunities remains scarce. To address this gap, we conduct an exploratory multiple case study comprising 13 cases in the radiotherapy domain. Taking over an adoption theory perspective, we uncover that organisational, environmental, technological and individual factors are decisive for effective adoption of AI and contribute to the emergence of efficiency gains and standardisation. Our analysis reveals that organisational factors such as pursuing a dedicated innovation strategy within the radiotherapy department as well as a holistic AI implementation strategy are most crucial. In determining and relating the identified relevant factors, we contribute to adoption theory and AI-enabled value creation in healthcare. Further, we advise managers of healthcare institutions on how to effectively adopt AI to overcome challenges at organisational and societal levels.

The Future Combat Air System (FCAS), a sixth-generation advanced combat aircraft, is assumed to be the largest European defence development and production programme of the 21st century and a core pillar of European cooperation in the defence sector. The 2017-initiated collaboration programme is led by Germany and France, with Spain and Belgium joining as partners, and is a who-is-who of the largest European defence companies, including Airbus Defence and Space, Thales, Safran, MBDA, and MTU. While such defence programmes have significant military, political, industrial, and economic impacts, the economic dimension in terms of economic costs and benefits is often under-represented in academic discussions. As the FCAS is still a nascent programme, only rough estimates of the total programme cost are available, and assumptions range from €100 bn to more than a trillion. With our research, we aim to contribute to the academic discussion by estimating the true economic costs and benefits of the FCAS. We use a mixed approach of data triangulation by cross-checking open source intelligence (OSINT) with expert interviews to estimate the full programme life-cycle costs. Furthermore, we estimate its economic impact on the European gross value added, employment, and tax by utilising an input – output (IO) model.