Focal Firms as Technological Gatakeepers within Industrial Districts Knowledge Creation and Dissemination in the Italian Packaging Machinery Industry

Despite the diffusion of communication tools and boundary spanning technologies, knowledge flows in innovation processes retain a distinct localized nature in many industries and geographical clusters emerge as critical areas to foster technological diffusion. In this paper we focus on the role of focal firms in industrial clusters as “gatekeepers” introducing external technological novelties in the cluster and enacting new useful knowledge production locally, thus enhancing international competitive capabilities of all firms in the cluster. We analyze a longitudinal dataset of 720 patents 1 Corresponding Author www.druid.dk granted by USPTO between 1990 and 2003 to firms in the automatic packaging machinery industrial district of Emilia-Romagna in Northern Italy, and a matched-sample to control for the uneven geographical distribution of R&D and patenting activities. Our results show that firms within the cluster use local knowledge to a greater extent and more rapidly than knowledge from the outside than it would be expected given the geographic distribution of innovative activity in the industry. Moreover, focal firms use external knowledge to a greater extent than other firms operating in the cluster, and other (non focal) firms within the cluster use knowledge from focal firms to a greater extent than would be expected given the geographic distribution of innovative activity in the industry. Implications for research on the geographical distribution of innovation activities are discussed.Innovation processes, Knowledge flows, Geographical clusters

Technology upgrading of middle income economies: A new approach and results

We explore issues of measurement for technology upgrading of the economies moving from middle to high-income status. In exploring this issue, we apply theoretically relevant and empirically grounded middle level conceptual and statistical framework based on three dimensions: (i) Intensity (ii) breadth of technological upgrading, and (iii) technology and knowledge exchange. As an outcome, we construct a three-pronged composite indicator of technology upgrading based on 35 indicators which reflect different drivers and patterns of technology upgrading of countries at different income levels. We show that technology upgrading of middle-income economies is distinctively different from that of low and high-income economies. Our results suggest the existence of middle-income trap in technology upgrading - i.e. countries' technology upgrading activities are not reflected in their income levels. Based on the simple statistical analysis we show that the middle-income trap is present in all three aspects of technology upgrading, but their importance varies across different aspects. A trap seems to be higher for 'breadth' of technology upgrading than for 'intensity' of technology upgrading and is by far the highest for the dimension of knowledge and technology interaction with the global economy. Finally, our research shows that technology upgrading is a multidimensional process and that it would be methodologically wrong to aim for an aggregate index

A Network Theory of Patentability

Patent law is built upon a fundamental premise: only significant inventions receive patent protection while minor improvements remain in the public domain. This premise is indispensable for maintaining an optimal balance between incentivizing new innovation and providing public access to existing innovation. Despite its importance, the doctrine that performs this gatekeeping role—nonobviousness— has long remained indeterminate and vague. Judicial opinions have struggled to articulate both what makes an invention significant (or nonobvious) and how to measure nonobviousness in specific cases. These difficulties are due in large part to the existence of two clashing theoretical frameworks, cognitive and economic, that have vied for prominence in justifying nonobviousness. Neither framework, however, has generated doctrinal tests that can be easily and consistently applied. This Article draws on a novel approach—network theory—to answer both the conceptual question (what is a nonobvious invention?) and the measurement question (how do we determine nonobviousness in specific cases?). First, it shows that what is missing in current conceptual definitions of nonobviousness is an underlying theory of innovation. It then supplies this missing piece. Building upon insights from network science, we model innovation as a process of search and recombination of existing knowledge. Distant searches that combine disparate or weakly connected portions of social and information networks tend to produce high-impact, new ideas that open novel innovation trajectories. Distant searches also tend to be costly and risky. In contrast, local searches tend to result in incremental innovation that is more routine, less costly, and less risky. From a network theory perspective, then, the goal of nonobviousness should be to reward, and therefore to incentivize, those risky distant searches and recombinations that produce the most socially significant innovations. By emphasizing factors specific to the structure of innovation—namely, the risks and costs of the search and recombination process—a network approach complements and deepens current economic understandings of nonobviousness. Second, based on our network theory of innovation, we develop an empirical, algorithmic measure of patentability—what we term a patent’s “network nonobviousness score” (NNOS). We harness data from US patent records to calculate the distance between the technical knowledge areas recombined in any given invention (or patent), allowing us to assign each patent a specific NNOS. We propose a doctrinal framework that incorporates an invention’s NNOS to nonobviousness determinations both at the examination phase and during patent litigation. Our use of network science to develop a legal algorithm is a methodological innovation in law, with implications for broader debates about computational law. We illustrate how differences in algorithm design can lead to different nonobviousness outcomes, and discuss how to mitigate the negative impact of black box algorithms

Early identification of important patents through network centrality

One of the most challenging problems in technological forecasting is to identify as early as possible those technologies that have the potential to lead to radical changes in our society. In this paper, we use the US patent citation network (1926-2010) to test our ability to early identify a list of historically significant patents through citation network analysis. We show that in order to effectively uncover these patents shortly after they are issued, we need to go beyond raw citation counts and take into account both the citation network topology and temporal information. In particular, an age-normalized measure of patent centrality, called rescaled PageRank, allows us to identify the significant patents earlier than citation count and PageRank score. In addition, we find that while high-impact patents tend to rely on other high-impact patents in a similar way as scientific papers, the patents' citation dynamics is significantly slower than that of papers, which makes the early identification of significant patents more challenging than that of significant papers.Comment: 14 page

Revisiting the Dynamics of Knowledge Spillover in Interfirm Alliances: Studies on Learning and Protection of Proprietary Knowledge in International Settings

This dissertation studies how firms cope with new challenges in absorbing and protecting knowledge from alliance partners. Chapter one examines how firms from emerging economies that assumed the “student” role in their prior alliances reverse roles and transition to the “teacher” role, while learning how to protect their own knowledge from spillover to prospective partners. It reveals that firms vicariously learn their partners’ knowledge protection practices to improve their own knowledge protection in subsequent alliances. Thereby it shows that learning and knowledge protection are interdependent activities not only within the same alliance but also across successive alliances. Chapter two studies how national innovation systems in the home countries of firms and their partners, respectively, influence firms’ knowledge acquisition from alliance partners. Whereas prior studies separately consider national systems and alliances, this study juxtaposes these aspects, showing that differences in national innovation systems help explain variability in firms’ learning. Finally, chapter three examines how knowledge spillover to an alliance partner can enable the firm to gain value as it observes its partner’s use of the spilled knowledge. It demonstrates that knowledge spillovers to partners can facilitate learning, as long as these spillovers do not become excessive, and if the partner recombines the firm’s spilled knowledge in non-redundant ways. Together, these studies contribute to the literature on learning in alliances by offering a new understanding of the dynamics of knowledge accumulation and protection

Strategically Poised: Balancing, Learning, and Innovating in Coopetition Three Essays on the Interplay Between Competition and Cooperation

This research dissertation explores the firm strategy of coopetition, a neologism denoting simultaneous cooperation and competition. Theoretical development and empirical investigations are conducted to tease out the tradeoff and tension of the coopetition strategy. First, I theorize the socio-cognitive aspects in balancing competition and cooperation between firms. Second, I investigate firm learning experience in strategic alliances and patent searches as the antecedents to coopetition. Third, I examine the contingency effects of multiple network embeddedness on the relation between coopetition pursuits and innovation performance. This research dissertation explores the firm strategy of coopetition, a neologism denoting simultaneous cooperation and competition. Coopetition as a phenomenon has accrued prominence in practice, with economic actors placing a higher emphasis on constructing positive sum scenarios with competing partners. However, strategic management scholarship lacks clarity in explaining how the tensions and tradeoffs associated with coopetition may influence the formulation and the implication of coopetition. With a theoretical and empirical focus on the benefits and caveats of coopetition, this dissertation elucidates coopetition from three angles. First, I theorize the socio-cognitive aspects in balancing competition and cooperation between firms. Second, I investigate firm learning experience in strategic alliances and patent searches as the antecedents to coopetition. Third, I examine the contingency effects of multiple network embeddedness on the relation between coopetition pursuits and innovation performance. The empirical setting of my dissertation research is technology-driven industries, because firms in this setting show high heterogeneity in the key theoretical foci (i.e. coopetition, learning, interorganizational relations, and innovation). The firm sample includes U.S. public firms in multiple high-tech industries (i.e. pharmaceuticals, computers and peripheral equipment, electronics and electronic components, aerospace and aircraft, telecommunication, and medical devices). I construct a panel data with firm-year observations of financial records, alliance and M&A records, and patent records from 1987 to 2006 to test my hypotheses

Effects of knowledge spillovers between competitors on patent quality: what patent citations reveal about a global duopoly

This paper analyses the effects on patent quality of a type of spillovers arising from the disclosure of patent information by firms engaged in competition in a global duopoly. Both firms are involved in producing new technologies and they do not cooperate on joint patents. In this context, we explored whether the disclosure of crucial knowledge in the patents of one of the firms affects the patent quality of its respective competitor. The empirical methodology relies on forward citations as an indicator of quality, and backward citations to the competitor as a measure of spillovers. We estimated several count models with a sample of 7750 patent families (divided into subsamples) owned by two large companies, Airbus and Boeing. Our econometric findings show that, for technologies in which the two firms account for the majority of the global patents, neither of the firms in the duopoly was able to harness spillovers from the rival to improve the quality of its patents. However, knowledge from the competitor becomes relevant, at least for one of the focal firms, in explaining patent quality of other technologies in which the two firms do not exert a dominant position.This work was supported by the Spanish Ministry of Economy, Industry and Competitiveness [Grant Number ECO2016-79436-R], [AEI/FEDER/UE]. Previous versions of the paper were presented at the 2018 Technology Transfer Society Annual Conference (Valencia), the 2019 International Open and User Innovation Conference (Utretcht), and the 2019 annual International Conference on Economics and Security (Madrid). The authors express their thanks to colleagues at these conferences for their helpful suggestions. The authors are also very grateful to two anonymous reviewers for their constructive and insightful comments