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on Innovation |
| By: | Moleka, Pitshou Basikabio |
| Abstract: | In an era of rapid technological advancements, complex global challenges, and intense market competition, the ability to generate and scale innovative solutions has become a critical imperative for organizations, policymakers, and societies worldwide. However, the existing academic landscape has lacked a cohesive, multidisciplinary framework for comprehensively understanding the multifaceted nature of innovation. Innovationology, a newly established scientific discipline, aims to address this gap by providing a unifying, transdisciplinary approach to the study and practice of transformative innovation. This comprehensive article introduces Innovationology as a cutting-edge science that integrates insights from diverse fields, including management, psychology, sociology, economics, and technology studies. Innovationology posits that innovation is a multilayered, context-dependent phenomenon, shaped by the intricate interplay of individual, team, organizational, and ecosystem-level factors. By synthesizing the latest theoretical advancements and empirical evidence, this article presents a holistic model of Innovationology that illuminates the key determinants of radical, game-changing innovations capable of disrupting existing industries and creating new market spaces. The article delves deep into the individual cognitive, behavioral, and motivational drivers of innovativeness, the team dynamics and organizational structures that foster collaborative innovation, and the ecosystem-level characteristics that catalyze the emergence and scaling of transformative innovations. Importantly, the article explores the crucial role of contextual factors, such as socio-cultural norms, institutional support, and resource availability, in shaping innovation outcomes. This article also establishes the epistemological foundations of Innovationology, grounding it in a transdisciplinary, holistic, and pragmatic approach to knowledge generation. Innovationology embraces a pluralistic epistemology that acknowledges the complexity and context-dependence of innovation, drawing on diverse methodological approaches to capture the multifaceted nature of this phenomenon. Furthermore, the article outlines the object of Innovationology, which is to provide a comprehensive, evidence-based understanding of the drivers, processes, and outcomes of transformative innovation. Innovationology seeks to elucidate the multilevel determinants of innovation, the dynamic interplay between various factors, and the contextual influences that shape innovation trajectories. By establishing a unifying, transdisciplinary framework, Innovationology aims to bridge the gap between innovation theory and practice, empowering a wide range of stakeholders to unlock the transformative potential of innovation. Importantly, this article outlines the practical applications of Innovationology, providing comprehensive strategies and evidence-based interventions for cultivating innovative mindsets, designing innovation-conducive organizational systems, and navigating the challenges of innovative ecosystems. The implications of Innovationology for entrepreneurs, corporate leaders, policymakers, and innovation scholars are discussed in detail. By establishing Innovationology as a distinct, authoritative scientific discipline, this article sets the foundation for a more holistic, context-sensitive understanding of innovation and its multifaceted drivers. The insights generated by this new science can empower global organizations, institutions, and policymakers to address the complex, interconnected challenges of the 21st century through the strategic deployment of transformative innovations. |
| Date: | 2024–09–10 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:f3scj_v1 |
| By: | Carleton, Tamara; Cockayne, William |
| Abstract: | A rise of government funding agencies dedicated to radical innovation has occurred in recent years. When launching bold and ambitious programs marked by radical uncertainty and unknowable outcomes, how do innovation-funding organizations deliberately provoke risk-taking behavior in potential applicants? This study focuses on the interplay between risk perception and decision making for deliberate high-risk decisions. We compare the language used in 81 public funding calls and new program solicitations from four US government funding entities, which comprise DARPA (Defense Advanced Research Projects Agency), the Defense Innovation Unit, the NASA Innovative Advanced Concepts program, and ARPA-H. A list of potential signal phrases was derived, indicating a spectrum of corresponding risk levels for an innovation opportunity. A survey with 92 evaluators validated that certain keywords served as provocations to trigger risk taking in the pursuit of transformative breakthroughs and frontier science. Our work contributes to a lexicon of signal phrases for provoking and communicating innovation, especially for far-reaching programs. More broadly, understanding the impact of language on decision making under high-risk conditions can inform national innovation policy and strategy for other funding organizations seeking to induce scientific and technological advancement in the United States and globally. |
| Date: | 2025–01–20 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:aqgf8_v1 |
| By: | Vivarelli, Marco (Università Cattolica del Sacro Cuore); Arenas Díaz, Guillermo (Catholic University Milan) |
| Abstract: | The relationship between technology and employment has long been a topic of debate. This issue is even more pertinent today as the global economy undergoes a technological revolution driven by automation and the widespread adoption of Artificial Intelligence. The primary objective of this paper is to provide insights into the relationship between innovation and employment by proposing a conceptual framework and by discussing the state of the art of the debates and analyses surrounding this topic. |
| Keywords: | technology, employment, compensation theory, AI, robot |
| JEL: | O33 |
| Date: | 2025–02 |
| URL: | https://d.repec.org/n?u=RePEc:iza:izadps:dp17686 |
| By: | Siddharth, L.; Luo, Jianxi |
| Abstract: | Design and innovation processes primarily generate knowledge upon retrieving and synthesising knowledge of existing artefacts. Understanding the basis of knowledge governing these processes is essential for theoretical and practical advances, especially with the growing inclusion of Large-Language Models (LLMs) and their generative capabilities to support knowledge-intensive tasks. In this research, we analyse a large, stratified sample of patented artefact descriptions spanning the total technology space. Upon representing these descriptions as knowledge graphs, i.e., collections of entities and relationships, we investigate the linguistic and structural foundations through frequency distribution and motif discovery approaches. From the linguistic perspective, we identify the generalisable syntaxes that show how most entities and relationships are constructed at the term level. From the structural perspective, we discover motifs, i.e., statistically dominant 3-node and 4-node subgraph patterns, that show how entities and relationships are combined at a local level in artefact descriptions. Upon examining the subgraphs within these motifs, we understand that artefact descriptions primarily capture the design hierarchy of artefacts. We also find that natural language descriptions do not capture sufficiently precise knowledge at a local level, which can be a limiting factor for relevant innovation research and practice. Moreover, our findings are expected to guide LLMs in generating knowledge pertinent to domain-specific design environments, to inform structuring schemes for future knowledge management systems, and to advance design and innovation theories on knowledge synthesis. |
| Date: | 2024–12–26 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:ncqz3_v1 |
| By: | World Bank Group |
| Keywords: | Science and Technology Development-Innovation Science and Technology Development-Technology Innovation Macroeconomics and Economic Growth-Economic Growth Governance-E-Government |
| Date: | 2024–12 |
| URL: | https://d.repec.org/n?u=RePEc:wbk:wboper:42500 |
| By: | Antonin Bergeaud (CEPR - Center for Economic Policy Research, Centre de recherche de la Banque de France - Banque de France); Arthur Guillouzouic (PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, IPP - Institut des politiques publiques, Sciences Po - Sciences Po) |
| Abstract: | Following Bergeaud et al. (2022), we construct a new measure of proximity between industrial sectors and public research laboratories. Using this measure, we explore the underlying network of knowledge linkages between scientific fields and industrial sectors in France. We show empirically that there exists a significant negative correlation between the geographical distance between firms and laboratories and their scientific proximity, suggesting strongly localized spillovers. Moreover, we uncover some important differences by field, stronger than when using standard patent-based measures of proximity. |
| Keywords: | Knowledge Spillovers, Technological Distance, Public Laboratories |
| Date: | 2024–03 |
| URL: | https://d.repec.org/n?u=RePEc:hal:journl:hal-04938250 |
| By: | Moleka, Pitshou Basikabio |
| Abstract: | In an age of unprecedented global complexity, interconnectedness, and urgency, the inadequacy of traditional, reductionist models of knowledge production has become glaringly apparent. This pioneering, landmark article offers a sweeping, paradigm-shifting exploration of the revolutionary emergence of "Mode 4" knowledge production - a fundamental reconceptualization of the epistemological, organizational, and methodological foundations of the research enterprise. Drawing on cutting-edge theoretical frameworks and a vast corpus of rigorous empirical evidence, this work argues that Mode 4 represents a transformative leap towards a more collaborative, transdisciplinary, and adaptive approach to knowledge creation - one that holds the potential to catalyze a profound and lasting transformation in the way we conceive of, organize, and mobilize research to address the complex, interconnected challenges facing our world. At the heart of this paradigm shift lies the groundbreaking "decuple helix" framework, which expands the scope of stakeholder engagement and knowledge co-creation to incorporate a comprehensive range of actors, from academia and industry to marginalized communities, the natural environment, and international organizations. This article delves deeply into the multifaceted roles and invaluable contributions of this diverse array of stakeholders, demonstrating how their active integration can unlock the transformative power of collaborative, values-oriented research and innovation. Furthermore, the paper provides a comprehensive example of how Mode 4 knowledge production concepts could be implemented using cutting edge innovationology research. By drawing on a rich tapestry of theoretical foundations, including complexity theory, quantum physics, humanities, social sciences, spirituality, and the arts, innovationology exemplifies the transdisciplinary ethos at the core of this paradigm shift. The article delves deeply into the collaborative co-creation, iterative and adaptive methodologies, and holistic, values-driven vision that define this groundbreaking transdisciplinary science. However, this work also candidly explores the significant institutional, methodological, equity-related, and scalability challenges that continue to hinder the widespread adoption and implementation of the Mode 4 and decuple helix frameworks. In doing so, it charts a course forward, outlining a comprehensive set of practical implications and recommendations to address these barriers and unlock the transformative potential of these emerging paradigms. Ultimately, this article offers a sweeping, cohesive, and visionary analysis of the revolutionary emergence of Mode 4 knowledge production and the decuple helix framework - positioning itself as a landmark contribution that has the potential to catalyze a profound transformation in the way we conceive of, organize, and mobilize research for a sustainable and equitable future. With its groundbreaking insights, bold vision, and rigorous interdisciplinary foundation, this work stands as a clarion call for a new era of collaborative, transdisciplinary knowledge production that can truly address the complex, interconnected crises facing our world. |
| Date: | 2024–11–04 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:6nc3p_v1 |
| By: | Kapoor, Amita; Singh, Narotam; Chaudhary, Vaibhav; Singh, Nimisha; Soni, Neha |
| Abstract: | This paper explores the transformative impact of Generative AI (GenAI) on the business landscape, examining its role in reshaping traditional business models, intensifying market competition, and fostering innovation. By applying the principles of Neo-Schumpeterian economics, the research analyses how GenAI is driving a new wave of "creative destruction, " leading to the emergence of novel business paradigms and value propositions. This research incorporates a novel AI-augmented SPAR-4-SLR framework as a key component, offering a systematic and innovative approach to analysing the rapidly evolving GenAI domain. By leveraging co-occurrence network analysis and LLM-based evaluation, this methodology identifies interdisciplinary trends and highlights diverse applications of GenAI. Beyond this, the study extends its scope to explore insights from internet-scraped data, Twitter analytics, and company reports, providing a comprehensive understanding of how GenAI is transforming businesses. This multi-faceted approach underscores GenAI's profound impact across industries such as technology, healthcare, and education, revealing its role in enhancing operational efficiency, driving product and service innovation, and creating new revenue streams. However, the deployment of GenAI also presents significant challenges, including ethical concerns, regulatory demands, and the risk of job displacement. By addressing the multifarious nature of GenAI, this paper provides valuable insights for business leaders, policymakers, and researchers, guiding them towards a balanced and responsible integration of this transformative technology. Ultimately, GenAI is not merely a technological advancement but a driver of profound change, heralding a future where creativity, efficiency, and growth are redefined. |
| Date: | 2024–11–20 |
| URL: | https://d.repec.org/n?u=RePEc:osf:osfxxx:khptm_v1 |