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This paper aims to analyze the extent to which the influence of external knowledge search activities on firms’ incremental innovation capability, and the moderating roles of the relatedness between the partners’ technological bases and a firm’s network embeddedness in the innovation network.

In this empirical research, the authors collected a sample of patents in the UAV industry over the period of 2004–2018. Then the authors examined the direct role of external knowledge search on firms’ incremental innovation capability and the joint moderating effects of technological proximity and network embeddedness.

We found that external knowledge search in innovation networks positively affects firms’ incremental innovation capability. Moreover, we discovered that high technological proximity to other peers positively strengthens the impact of firms’ external knowledge search on their incremental innovation capability. Finally, the findings suggested that the relationship between a firm’s external knowledge search activities and its incremental innovation capability is stronger for high technological proximity coupled with high network centrality or poor structural holes in innovation networks.

This study adds value to open innovation literature by pointing out a positive relationship between external knowledge search and firm incremental innovation capability. Furthermore, this study reinforces the key joint contingent roles of technological proximity and network embeddedness. This study provides a valuable theoretical framework of incremental innovation capability determinants by connecting the different perspectives.

This paper aims to use the proximity approach of economic geography with its spatial dimension (geographic) and their non-spatial dimensions (social, institutional, cognitive and organizational) to shed light on the determinants of business cooperation with other organizations. It is also examined whetherthis cooperation is a determining factor for business innovation (innovation networks), drawing a distinction between technological and non-technological innovations.

The study has a quantitative approach; it analyzes the case of 312 companies in a cluster of agribusinesses in an emerging economy (Chile). The proposal model and its interrelations are tested with exploratory factor analysis, confirmatory factor analysis and structural equation modeling.

The results show that cognitive-organizational proximity is a positive determinant of business cooperation with other organizations, whereas social and institutional proximity are negative determinants. It is also established that business cooperation is a positive determinant of business innovation. It is more relevant in the case of technological innovation unlike non-technological innovations. In addition, it is noted that business cooperation levels are lower in micro-enterprises, a result that differs from developed countries.

For business managers, it is best to cooperate with companies that are similar in terms of cognitive and organizational levels for innovation. At the same time, it is necessary develop strategies to reduce the social and institutional barriers to cooperation, especially in the agribusiness sector.

The contributions of the study are as follows: an in-depth quantitative examination of the relationships of various non-spatial proximities as determinants of business cooperation; an analysis of whether business cooperation with other organizations is a determining factor for business innovation, distinguishing between technological and non-technological innovation; and testing these relationships in the context of agribusiness in an emerging economy such as Chile’s because most of studies are related to high-tech sector and developed economies.

The paper aims to investigate how proximity dimensions affect the establishment of different knowledge relationships between gatekeepers and other economic actors involved in their knowledge‐based networks.

The methodology is based on an inductive research approach, represented by the explorative case study of the Polytechnic University of Turin. The University's knowledge relationships are identified and distinguished through the analysis of its patent joint‐developments, citations, and R&D projects. Then, for each knowledge relationship, geographical, organizational, and technological proximity between the University and the other economic actors are assessed, adopting suitable proxies.

The data reveal that the University activates collaborative and exploitative relationships with actors characterized by geographical, organizational, and technological proximity. In contrast, collaborative and explorative relationships seem to require actors characterized by more distant technological competencies. Furthermore, the exchange of knowledge by means of non‐collaborative relationships occurs between the University and actors characterized only by technological proximity.

On the basis of this analysis, actors can identify which proximity dimensions assume an important role for activating knowledge flows with gatekeepers. Regarding policy implications, the paper highlights how policy makers should leverage proximities in order to favour and support the exchange of knowledge, hence improving the innovative capability, competitiveness, and attractiveness of regional areas.

This research contributes to shed further light on the nature of the relationships and knowledge flows exchanged by the gatekeepers. In particular, it analyzes how relational attributes can affect the knowledge transfer processes between economic actors.

This research outlines the technological structure of the entire Japanese manufacturing and service industry using the patent information from research and development (R&D) activities to set R&D goals.

By analyzing the technological development capability of individual companies, the direction of the companies' R&D activities and current state of technological fusion between them can be understood. A group of companies participating in a particular product/service market must have the same technological development capabilities. As a result, the ratio of patent applications by a company to the total number of applications in a technical field will be similar across companies. This study uses the inter-company correlation coefficient of the ratio of patent applications by technical field as an index of technological development capability. A total of 167 major companies covering the major industries of Japan were analyzed. The analysis period was 15 years from 2004 to 2018, and the technical fields were rearranged to 42 fields with reference to the International Patent Classification (IPC)-Technology Concordance used by the World Intellectual Property Organization (WIPO). Considering the fluctuation in patent application opportunities, the number of patent applications was collected for at least three years for the analysis of patent applications by technical field, company and industry.

Examining the entire Japanese industry, the research found that chemicals, ceramics, non-ferrous metals and electrical/electronic equipment act as intermediaries between the respective groups and are linked to the transportation equipment, electrical/electronic equipment and information and communication services industries that are currently driving the Japanese economy. However, the technical connections between these groups are relatively loose. Over the last 15 years, the propagation structure of technical knowledge information has not changed. The progress of technological fusion remains within the scope of commerce and is conditioned by commerce.

Studies focusing on the technological development capability between companies and the technological structure of the Japanese manufacturing and service industries are almost non-existent since 2000 when Japan's economic growth slowed. The analytical methods presented in this research can be applied to individual companies to gain an understanding of technical positions of companies and can be useful for planning a technical environment, business or R&D strategy.

The purpose of this paper is to analyze the issue of knowledge transfer in the context of international asymmetric alliances. The objective is mainly to identify the barriers that can impede the knowledge transfer between asymmetric partners and to analyze the solutions adopted to overcome these barriers.

The authors use a qualitative study involving six cases of asymmetric alliances between Tunisian small-and-medium enterprises (SMEs) and European multinational corporations (MNCs).

The results of this research highlight a set of obstacles related to the context of asymmetric alliance itself and the nature of knowledge transferred by partners. The study emphasizes the importance of translation using artefacts by both partners and proximity with its geographical, organizational and technological dimensions to overcome these obstacles.

The investigation of knowledge transfer in asymmetric alliances was based on the role played by only three proximity dimensions (geographical, organizational and technological), while other factors, such as institutional, social and cultural issues, were not considered. Indeed, future research may take these variables into account in studying solutions to overcome knowledge-transfer barriers in asymmetric alliances.

The paper calls the attention of asymmetric alliance managers to the importance of translation to perform work processes, facilitate knowledge transfer and overcome linguistic barriers. Managers should use virtual artefacts to reduce the constraints resulting from their geographical remoteness and to strengthen cooperation. Further, reinforcing geographical, organizational and technological proximity between partners involved in an international alliance is essential to facilitate knowledge transfer, essentially of tacit knowledge, and to accelerate innovation.

This study emphasizes the importance of the simultaneous role of artefacts, translation and proximity in overcoming obstacles related to the asymmetric alliance itself and the nature of knowledge transferred by partners. The results shed light on the issue of knowledge generation in asymmetric alliances.

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

This study aims to investigate the structural characteristics, spatial evolution paths and internal driving mechanisms of the knowledge transfer (KT) network in China’s patent-intensive industries (PIIs). The authors' goal is to provide valuable insights to inform policy-making that fosters the development of relevant industries. The authors also aim to offer a fresh perspective for future spatiotemporal studies on industrial KT and innovation networks.

In this study, the authors analyze the patent transfer (PT) data of listed companies in China’s information and communication technology (ICT) industry, spanning from 2010 to 2021. The authors use social network analysis and the quadratic assignment procedure (QAP) method to explore the problem of China’s PIIs KT from the perspectives of technical characteristics evolution, network and spatial evolution and internal driving mechanisms.

The results indicate that the knowledge fields involved in the PT of China’s ICT industry primarily focus on digital information transmission technology. From 2010 to 2021, the scale of the ICT industry’s KT network expanded rapidly. However, the polarization of industrial knowledge distribution is becoming more serious. QAP regression analysis shows that economic proximity and geographical proximity do not affect KT activities. The similarity of knowledge application capacity, innovation capacity and technology demand categories in various regions has a certain degree of impact on KT in the ICT industry.

The current research on PIIs mainly focuses on measuring economic contributions and innovation efficiency, but less on KT in PIIs. This study explores KT in PIIs from the perspectives of technological characteristics, network and spatial evolution. The authors propose a theoretical framework to understand the internal driving mechanisms of industrial KT networks.

According to the construction literature, the number of projects applying integrated project delivery (IPD) principles is expected to increase in the new-normal era. However, given that the pandemic is not yet fully over, accurate and measurable data are not yet available. Also, there is a lack of empirical studies that could provide guidelines as to the application of IPD principles at the various stages of construction projects. Thus, the goal of this paper is to address this knowledge gap through case studies.

This paper follows a multi-step research methodology, namely, a literature review, case study and focus group discussions in the context of Canadian construction projects.

Based on the conducted literature review and focus group discussions, the authors identified: (1) new challenges in the various stages of the construction projects' life cycle, (2) their related proximity aspects (technological, organizational, geographical and cognitive) and (3) IPD principles that can address the identified challenges within their associated proximities. The results show that IPD relational principles can improve a project's organizational and cognitive proximities, while IPD digital integrative principles can enhance a project's geographical and technological proximities.

This study contributes to the theoretical checklists of challenges that the construction industry has experienced since the beginning of the pandemic, and to the practical guidelines of implementation of IPD principles to meet these challenges. The conducted case studies are timely and relevant, and their results provide new insights for key project stakeholders into the application of IPD to tackle new-normal challenges based on their proximity perspectives.

Despite typically being regarded as “low tech”, the food manufacturing and technology sector is increasingly turning to open innovation practices involving collaboration with universities in order to innovate. Given the broad range of activities undertaken by this sector and the fact that it utilises analytical, synthetic and symbolic knowledge for innovation, it makes an interesting case study on the factors that influence the formation of university–industry (U–I) links. The paper aims to discuss this issue.

Using data from 249 collaborative projects that occurred between UK universities and food manufacturing and technology firms, the analysis utilises a logistic regression model based on a “synthetic counterfactual approach” to modelling the probability a collaborative link will be established with one university and not others.

The results suggest that organisational proximity, conceptualised through the presence of prior ties between actors, has the largest influence on the formation of U–I links. In addition, spatial and technological proximities between actors also have a positive influence on link formation. This result suggests that the specificity of knowledge of the food sector is important in the formation of these U–I links.

The results suggest that the open innovation practices of food manufacturing and technology firms are like other sectors, even though their innovation practices are considered to be different. However, the limitations of the paper mean that these findings may be specific to firms in the food manufacturing and technology sector in the UK.

The food sector is under-represented in empirical studies on university collaboration; this paper addresses this and provides new insights into the formation of these links.

There is little known about investigating the importance of all proximity dimensions simultaneously as a result of geographical proximity on university-industry collaborative innovation. This paper aims to answer the question of how geographically proximate university and industry influence cognitive, social, organizational, institutional and cultural proximity within university-industry joint laboratories and finally, what is the outcome of these interplays on collaborative innovation.

The study uses an exploratory multiple-case study approach. The results are derived from 53 in-depth, semistructured interviews with laboratory directors and representatives from both the company and the university within 8 joint laboratories of Telecom Italia (TIM). The data collection was carried out in 2014 and 2015. The analysis follows a multi-grounded theory approach and relies on a mix of deductive and inductive reasoning with the final goal of theoretical elaboration.

This study finds the role of social and cultural proximity at the individual level as a result of geographical proximity as an enabler of collaborative innovation by triggering mutual learning, trust formation and frequent interactions. Cognitive proximity at the interface level could systematically influence collaborative innovation, while organizational and institutional proximity has marginal roles in facilitating collaborative innovation. The qualitative analysis offers a conceptual framework for proximity dimensions and collaborative innovation within university-industry joint laboratories.

The framework not only advances state-of-the-art university-industry collaboration and proximity dimension but also offers guidance for managers in designing collaborative innovation settings between university and industry.

With this study, the paper advances the understanding beyond solely the relationship between proximity and collaboration and shed light on the interplay between geographical proximity and other proximity dimensions in this context, which has received limited scholarly attention.