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How do global value chains (GVCs) affect a firm's innovation impact? Working as international communities, GVCs are rich in knowledge and resource interchange. The prior literature has focused on knowledge absorbing or internal knowledge transfer within firms for in-house innovation. However, scant research has focused on promoting innovation across interfirm networks in a GVC context. This article develops a new concept of interfirm transformative capacity as a firm's ability to transfer developed technology knowledge across time, space, and firm networks. In this article, we explore three mechanisms of interfirm transformative capacity in GVCs: 1) choosing knowledge intermediaries, 2) transmitting and maintaining knowledge over time and space, and 3) reactivating and synthesizing knowledge. We predict that engagement in a lead firm's GVC, structural holes, and network centrality will affect a focal firm's innovation impact as a result of interfirm transformative capacity. Integrator suppliers have higher innovation impacts than modular suppliers. To test these three mechanisms, we build a novel dataset from a five-year panel of Apple suppliers and their patent impacts. The results support our hypotheses related to the mechanisms of interfirm transformative capacity. Our theoretical elaboration and empirical findings have significant implications for innovation policy within, and governance of, GVCs. [ABSTRACT FROM AUTHOR]

The papers in this special section focus on the ability to integrate evolving incubator models into the organization. Management and organizational science focusing on the complex process of R&D that leads to the subsequent commercialization has come a long way since the days of post-World War II industrial and research laboratories. In this context, the evolution of the incubator can be retraced from the foundational research in the 1950s and 1960s of Researchon-Research—that explored the R&D process in a number of settings to derive and test theories of organization behavior. Since then, we have seen a concentration of research and practice that have spanned a burgeoning range of incubators models and entities that, in some manner, exist to play a role to support and harness new technology-based start-ups. For more than half a century, these third-party entities in the entrepreneurial ecosystem have spread from the United States to Europe and are a well-established worldwide phenomenon. Business incubators have been largely viewed as an essential means to facilitating the process of knowledge transfer and tech-based commercialization through the provision of office infrastructure, laboratories and equipment, business support services, mentoring, and access to entrepreneurial finance and specialist networks for the founders of these embryonic start-ups. [ABSTRACT FROM AUTHOR]

Firms engaged in university–industry collaboration (UIC) desire to advance knowledge and new technologies with their academic partners, however the performance of knowledge creation and transfer is greatly affected by complementarity and compatibility between the firm and academic institute. In practice, many firms assess the appropriateness of academic partners using a broad range of criteria, with high subjectivity. This paper therefore seeks to address this challenge by introducing a systematic approach to help firms determine the appropriateness of academic partners, represented as “matching quality” in this paper. Three facets of matching quality are examined: complementarity of research ability, compatibility in business mindset, and compatibility in relationships. This paper proposes a framework and model for assessing matching quality, along with a case study to demonstrate how the proposed model works. [ABSTRACT FROM AUTHOR]

If we have any hope of achieving sustainability, we, as researchers, need to develop a new perspective on universities and multistakeholder engagement. Stakeholder theory teaches us that engaging stakeholders in specific transactions and interactions can foster the sustainable development. But solving the grand challenge of sustainability requires more. Universities need to see themselves as part of a great network of stakeholders where interactions, knowledge, and data management go beyond the entrepreneurial university paradigm. Hence, in this article, we present Oztel's concept of a fourth-generation university as a launch-point for broadening the discourse on higher education's third mission. We establish a new stream of inquiry through four main propositions for research and technology management. Further, we call for interested scholars to pioneer this field with an inexhaustive list of potential avenues for future research. University managers, researchers, and policymakers should find great insights into the future evolution of sustainable development and its soon-to-be intrinsic place in the fabric of teaching, research, and society. [ABSTRACT FROM AUTHOR]

Domain adaptation has been a fundamental technology for transferring knowledge from a source domain to a target domain. The key issue of domain adaptation is how to reduce the distribution discrepancy between two domains in a proper way such that they can be treated indifferently for learning. In this paper, we propose a novel domain adaptation approach, which can thoroughly explore the data distribution structure of target domain. Specifically, we regard the samples within the same cluster in target domain as a whole rather than individuals and assigns pseudo-labels to the target cluster by class centroid matching. Besides, to exploit the manifold structure information of target data more thoroughly, we further introduce a local manifold self-learning strategy into our proposal to adaptively capture the inherent local connectivity of target samples. An efficient iterative optimization algorithm is designed to solve the objective function of our proposal with theoretical convergence guarantee. In addition to unsupervised domain adaptation, we further extend our method to the semi-supervised scenario including both homogeneous and heterogeneous settings in a direct but elegant way. Extensive experiments on seven benchmark datasets validate the significant superiority of our proposal in both unsupervised and semi-supervised manners. [ABSTRACT FROM AUTHOR]

Breakthroughs in information and power transfer for wireless networks are imperative in order to satisfy the requirement of wireless nodes for energy sustainability. To this end, significant research efforts in academia and industry have been devoted to the design of optimal resource allocation schemes for RF SWIPT networks. The transmit power constraints imposed by safety regulations introduce significant challenges to the improvement of power transfer performance. Therefore, solely relying on RF resources to cope with the expectations of next-generation wireless networks, such as longer device lifetimes and higher data rates, may no longer be possible. Thus, the investigation of technologies complementary to conventional RF SWIPT is of critical importance. In this article, we propose a novel collaborative RF and lightwave power transfer technology for future networks, where both the RF and lightwave bands can be entirely exploited. In this context, we introduce the basic transceiver architecture and four corresponding collaborative communication and power transfer protocols. Finally, key potential future research directions are highlighted. [ABSTRACT FROM AUTHOR]