Knowledge that Transforms

Can the way firms account for R&D shape how they innovate? We exploit Japan's pre-2000 elective R&D accounting regime—allowing firms to choose between expensing and capitalization—and its 2000 transition to mandated expensing to examine how accounting treatment shapes innovation outcomes. Using forward citations and patent applications to measure innovation quality and patenting volume across 967 Japanese firms, we find that under the elective regime, capitalized R&D is positively associated with innovation quality while expensed R&D is positively associated with patenting volume. Following the 2000 mandate, the elimination of the capitalization option leads former capitalizers to intensify patenting as a substitute disclosure mechanism, increasing applications without corresponding improvements in innovation quality. Their patenting behavior converges with always-expensing firms, reflecting an accounting-driven homogenization of innovation disclosure. These findings suggest that uniform expensing obscures economically meaningful differences in innovation activity, with implications for ongoing R&D accounting reforms at FASB and IASB.

As societal challenges loom larger, discoveries are in greater demand, and evaluating the impact of publicly funded programs attracts increasing attention. We contribute to this debate by focusing on the spatial influence of scientific discoveries funded through grants targeting frontier research. Our dataset includes information on 6671 EU ERC-funded projects between 2007 and 2016, 172,683 scientific publications generated by these grants, and 34,513 patents citing such publications. Building on linkages between scientific papers and patents via non-patent literature citations, we use the project as the unit of analysis and employ a two-stage regression model to examine the probability that ERC-funded publications are cited by patents and how these citations diffuse across space and time. The analyses on our final sample of 4977 ERC-funded projects, generating 151,574 publications that are cited by 34,007 patents confirmed our hypothesis that higher quality research leads to a broader and faster geographical diffusion and partially confirm the hypotheses that diffusion paths and speed differ by applicants, although these differences do not always show the same patters. Moreover, we also find that c) projects generating scientific output (publications) and technological outputs (patents) diffuse more broadly and faster; and d) projects led by more mobile and scientifically productive scientists diffuse more broadly and faster; We discuss these findings and show how they enhance and extend our understanding of the impact of science and its implications for policymakers and innovation scholars.

Innovation failure is widespread yet remains difficult to theorize. While much existing research treats failure as an event attributable to internal mismanagement, systemic imperfections or a combination of both, more recent work emphasizes its processual and relational character. Building on this latter stream, this paper reconceptualize innovation failure as a dynamic and socially mediated process that unfolds across interrelated innovation journeys within an innovation field. Rather than asking why innovations fail, we examine how failure experiences are constituted in practice, how actors respond to them, and how these responses accumulate over time to shape innovation field dynamics. Empirically, we analyze responses to the common setback of a discontinued clinical trial in the field of antibiotic innovation in the face of increasing antimicrobial resistance. We identify three typical responses (reviving, shifting, giving up) elicited by such a setback and find that in their interaction these responses produce an increasingly constraining structure that affects innovation activities in the field. We conceptualize this dynamic as cascading failure, a process through which successive and recursive responses to setbacks transform innovation expectations into constraints for further innovation. The concept of cascading failure explains why the discourse of a “broken market” and an “empty pipeline” that charactersises antibiotic innovation has become so persistent and perfomative.

We use a rich dataset of Spanish manufacturing firms from 1990 to 2016 to shed light on how automation in a high-income country affects trade and multinational activity involving lower-income countries. We exploit variation in firm exposure to robotics inventions over time, as measured using ex ante task specialization and the tasks described in new robotics patents. We show that the deployment of robots in Spanish firms had a positive impact on their offshoring to lower-income countries. For firms that had not yet offshored production to lower-income countries, robot adoption caused them to start newly doing so. By contrast, for firms that were already offshoring to lower-income countries, robot adoption had no effect on their offshoring.

This paper sets out to develop a unified theoretical framework integrating von Hippel user innovation and Schumpeterian industrial dynamics through a relatively simple agent-based model (ABM). The model reproduces known stylised facts, and it also generates some important theoretical results to explain the transition from community-phase to market-phase innovation, that neither paradigm addresses on its own. In our model, as user innovators develop the technology for their own use, complementary interactions with producers also begin to form. These firms seek market opportunity and require a certain minimum scale of operations before they enter. Where firms enter, they bring scale and often further innovate, which in turn, recursively feeds back into user innovation. In this way, von Hippel and Schumpeterian innovation co-evolve. Our ABM provides a formal and endogenous framework to understand these coevolutionary processes, generating theoretical results about the conditions under which it occurs. Specifically, the model simulations explore how two structural key parameters: users' attribute requirement thresholds and the degree of local sticky information , shape this co-evolutionary process. The simulations show that: (i) community fragmentation driven by high information stickiness may impede viable producer entry even when user demand exists; (ii) medium values for user attribute requirement thresholds generate a competitive advantage for pioneering firms landed at the center of the attribute space and; (iii) the industrial dynamics that emerge from user communities reproduce the Schumpeterian stylised facts, thereby providing a unifying bridge between the two paradigms. These theoretical findings have direct implications for innovation policy: (i) policy should monitor community coherence as an early signal for specific viable commercialization; (ii) a policy model that addresses information stickiness will be necessarily context-dependent and, (iii) the attribute requirement threshold suggests that producer entry strategies should be attuned to the distribution of user requirement heterogeneity.

Global sustainability challenges demand large, rapid and systemic transformation of the systems that underpin modern life. Disruption is increasingly discussed as a trigger of these transformations, but the drivers of disruption have remained unclear. While much of the existing literature focuses on technological innovation as a potential driver, limited although growing attention has been paid to non-technological sources. This paper explores business model innovation as a non-technological driver of disruptive sustainability. We define disruptive sustainability as far-reaching changes in more than one dimension of socio-technical systems, triggered by a high-intensity effect, towards realising environmental, social and economic goals. We conduct a theorizing review of academic literature on the last mile in low-income and lower-middle income countries. We develop an explanatory model of how interdependencies between business model innovation components drive disruptive sustainability by re-defining the problem-solution nexus at different depths. Our contributions are threefold. First, we expand the conceptualization of disruptive sustainability by unpacking the crucial aspect of depth of change. We suggest that disruptions can trigger shallow, medium or deep change within and across dimensions of socio-technical systems. Second, we explain how the interdependencies between different business model innovation components drive disruptive sustainability by changing the problem-solution nexus at different depths. Third, based on these contributions, we develop a tool which guides stakeholders in driving disruptive sustainability in three distinct steps linked to different degrees of depth.

Drawing on the resource provision perspective within resource dependence theory, we argue that academic directors significantly enhance firms' capacity for science-based breakthrough innovations. This study also engages with a central debate in innovation research: whether external resources and internal capabilities function as complements or substitutes. Using panel data from 991 U.S. publicly listed innovative firms, we find that the presence of academic directors is positively associated with science-based breakthrough innovation, particularly in firms with a strong publication record. This supports the complementary relationship between external scientific expertise and internal R&D capabilities. Robustness checks—including instrumental variable analysis and natural experiments involving the sudden deaths of academic directors—reinforce our findings. These results offer new insights into how strategic leadership can leverage external academic expertise to drive transformative innovation.

To safeguard long-term value creation and capture, incumbent firms face growing pressure to pursue corporate climate adaptation and resilience strategies. Given the pivotal role of top managers in driving adaptive change, this study examines how top management teams' human capital shapes firms' engagement in climate adaptation and resilience across different organizational and environmental contexts. Drawing on the attention-based view, we argue that science, technology, engineering, and mathematics (STEM) education directs managerial attention toward climate-related risks and opportunities, prioritizing climate adaptation and resilience responses over competing strategic concerns. We further theorize that this relationship is contingent on firms' inventiveness, their exposure to physical climate hazards, and climate change sentiment expressed by financial stakeholders. Depending on these contexts, STEM-educated top management team members are particularly valuable in processing climate-related information, developing corporate climate adaptation and resilience strategies that reconfigure existing business models and value chains, and mobilizing organizational support for their implementation. Analyzing data from the Carbon Disclosure Project from large, listed U.S. firms from 2013 to 2020, we find empirical support for our hypotheses. Additional analyses show that STEM education is more strongly associated with engagement in climate adaptation and resilience than other educational backgrounds and that its association varies across STEM subfields. Our findings advance understanding of how executive cognition and attention-directing contexts jointly shape firms' responses to climate-related challenges and highlight the role of STEM expertise in enabling disruptive, sustainability-oriented transformation. We also derive implications for executive hiring, leadership development, and climate-related policy design.