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The purpose of this paper is to investigate the impact of two dimensions of technological relatedness, namely technological similarity and complementarity, on collaborative performance, plus the mediating role of collaboration network stickiness and the moderating role of partner expertise and geographical distance in interfirm collaboration contexts.

This study takes Chinese Scientific and Technological Achievements (STA) of inter-firm collaboration in five high-tech fields in 2010–2020 as the sample and uses OLS regression to test the hypothesis.

Technological similarity and complementarity positively affect collaborative performance. Partner expertise negatively moderates the relationship between similarity, complementarity and collaborative performance. Geographical distance positively moderates the relationship between similarity and collaborative performance while negatively moderates that between complementarity and collaborative performance. Collaboration network stickiness partly mediates the relationship between similarity and collaborative performance.

This study expands literature on inter-firm collaboration, especially research on the antecedents of collaborative performance. Moreover, this study not only compensates for lack of empirical analysis in partner selection research, but also utilizes second-hand data to enhance the objectivity of analysis. Additionally, we enrich the research on the moderating role of partner expertise and geographical distance as well as the mediating role of collaboration network stickiness.

The purpose of this paper is to define co-exploitation, co-exploration, and alliance ambidexterity from the perspective of organizational learning; to analyze how knowledge bases, structural arrangements, and control mechanisms of R&D alliances influence co-exploitation and co-exploration; and to discuss how to achieve alliance ambidexterity by managing paradoxes around knowledge bases, structural arrangements, and control mechanisms.

This is a conceptual paper focussing on how to balance exploitation and exploration at the alliance level through managing three paradoxes of cooperation: similarity vs complementarity, integration vs modularity, and contracts vs trust.

While technological similarity, structural integration, and contracts are more likely to promote co-exploitation, technological complementarity, structural modularity, and trust are more likely to facilitate co-exploration. Alliance ambidexterity, which is beneficial for alliance performance, derives from either the combination of technological complementarity, structural integration, and contracts, or the combination of technological similarity, structural modularity, and trust temporally.

Researchers should analyze the possibility of building alliance ambidexterity in other types of interorganizational relationships, and find other possible antecedents of interorganizational learning.

Managers should not simply treat R&D alliances as one of exploratory interorganizational relationships, but pay equal attention to co-exploitation and co-exploration. To achieve this balance, practitioners should combine technological complementarity with structural integration and contracts, or integrate technological similarity with structural modularity and trust.

This paper is one of the first contributions that analyze how an R&D alliance could gain its ambidexterity through the management of nested cooperation paradoxes.

The convergence of industries exposes the involved firms to various challenges. In such a setting, a firm's response time becomes key to its future success. Hence, different approaches to anticipating convergence have been developed in the recent past. So far, especially IPC co-classification patent analyses have been successfully applied in different industry settings to anticipate convergence on a broader industry/technology level. Here, the aim is to develop a concept to anticipate convergence even in small samples, simultaneously providing more detailed information on its origin and direction.

The authors assigned 326 US-patents on phytosterols to four different technological fields and measured the semantic similarity of the patents from the different technological fields. Finally, they compared these results to those of an IPC co-classification analysis of the same patent sample.

An increasing semantic similarity of food and pharmaceutical patents and personal care and pharmaceutical patents over time could be regarded as an indicator of convergence. The IPC co-classification analyses proved to be unsuitable for finding evidence for convergence here.

Semantic analyses provide the opportunity to analyze convergence processes in greater detail, even if only limited data are available. However, IPC co-classification analyses are still relevant in analyzing large amounts of data. The appropriateness of the semantic similarity approach requires verification, e.g. by applying it to other convergence settings.

Starting from the model of the initiation and evolution of inter-firm knowledge transfer in R&D relationships developed by Faems et al. (2007), the purpose of this paper is to refine and improve this model, assessing its reliability in a different and wider context and extending it according to the outcomes.

A multiple case-study approach was implemented, examining 34 dyadic inter-firm R&D relationships. This methodology suited the research goal of exploring the validity of a model in an area where little data or theory exists.

The theoretical model proposed by Faems et al. (2007) was improved, confirming the adequacy of the overall structure of their intuition and highlighting several differences in terms of factors that lead to the dissolution of R&D relationships. These differences mainly refer to partners’ similarities before starting R&D relationships, co-opetition situations, knowledge leakage/opportunistic behavior and reputation issues.

This work is the first to investigate two open research gaps related to the model of the initiation and evolution of inter-firm knowledge transfer in R&D relationships: the need for additional case studies in other contexts to develop a more general theory and the lack of research incorporating issues such as relational capital between partners, governance form and alliance scope in an integrated analysis.

The purpose of this study is to investigate whether repeated alliances between two members of a patent pool boost enterprise innovation. Furthermore, this paper intends to determine whether the innovation performance becomes higher or lower based on the partnership characteristics.

In this empirical study, hierarchical regression is used to analyze the longitudinal data obtained from 12 patent pools managed by MPEG LA during a time period ranging from 2006 to 2018. The members of patent pools comprise research institutions, firms and universities. Research analyses are performed based on a sample of 68,400 member pairs who had established repeated alliances. The information regarding such pairs is gathered from public databases.

Repeated alliances positively correlate with enterprise innovation performance in patent pools; this performance is higher when the two enterprises have exploratory collaborations. Conversely, the performance is lower when the partners have a similar technology base and are engaged in a technological competition (competitive learning and patent litigation). Moreover, the performance is lower when one partner demonstrates higher network centrality and richer structural holes than the other partner.

Patent pools play an instrumental role in eliminating patent-licensing barriers, thereby allowing mutual acquisition of complementary technologies, and cooperatively strengthening technology development. From the perspective of theories of coopetition, knowledge management and social network, this study explores the impact of patent pools on enterprise innovation performance and ascertains the moderating roles of technology coopetition, technology similarity and network position, thereby expanding the scope of innovation effect in the context of patent pools.

While earlier acquisition research often focused on either the acquirer or the target side of analysis, recent work has increasingly emphasized the need to understand the dyadic interrelationship between the target and the acquirer. This review aims at synthesizing research progress in the area of target–acquirer interrelationships and understanding what questions remain unanswered. The author organizes this review into three dimensions of target–acquirer interrelationship: (a) their relative attributes (what both parties are relative to each other), (b) their connections (what both parties have with each other), and (c) their interactions (what both parties do to each other). Based on the review, the author then identifies critical research gaps and opportunities for developing a more comprehensive understanding of the interrelationship between the target and the acquirer in acquisitions.

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.

The purpose of this paper is to explore the effects of mergers and acquisitions (M&As) on innovation and profitability in large European firms.

Using information from a unique micro-longitudinal database of top European R&D investors and information from the European Commission (EC) Merger Control Authority, dynamic panel estimations with firm-level fixed effects are performed. Moreover, the paper presents a qualitative case study of a merger in the European electronic and electrical equipment industry.

The analysis of a sample of 562 M&As authorized by the EC Merger Control Authority shows that mergers positively influence the R&D intensity and profitability of top companies in the European Union over the period 2004–2012. Furthermore, empirical evidence shows that the timing and magnitude of these effects differs. In particular, the positive effect of mergers on R&D intensity is found for the short and large term while they influence profitability only in the large term.

This paper makes several contributions. First, unlike other studies on this topic, it investigates the effects of M&As using firm-level panel data on the top 1,000 European R&D companies instead of only examining a case study. Second, a unique data set has been used, which collects information on large European firms from the European Industrial R&D Investment Scoreboard and the EC antitrust authority. Finally, the paper accounts for the casual link between innovation effort and profitability when evaluating the potential effect of M&As on the R&D intensity and profitability of large European firms.

This study aims to measure the moderating effect of geographical and organizational proximity by focusing on readily available Chinese regional economic data over a five-year period.

The authors used multilevel regression analysis to analyze the relationship.

Results show that increasing government investment in research and development (R&D) can improve innovation performance during this period, organizational proximity and geographic proximity have a positive moderate effect on the relationship between R&D investment and Innovation performance.

This study enriches the existing theories on government innovation input and output from the perspective of regional differences and provides meaningful guidance for current Chinese regional innovation policies.

Strategic technology partnering (STP) is considered to be significant for the access to novel technologies that are unknown to organisations. However, the performance heterogeneities within organisations can be explained by STP capabilities. Hence, the purpose of this paper is threefold: first, to provide a classificatory framework by categorising the various STP capabilities; second, to draw conclusions from the analysis of the empirical findings; and third, to guide further publications and identify future research needs.

The present paper adopts a systematic literature review (SLR) methodology. In this research, the extant empirical research on STP capabilities will first be classified and integrated within a classificatory framework. Lastly, the review insights will provide methodological suggestions along with theoretical themes for future research that have not been yet explored.

The study findings show that there is a strong need for a clear and unified terminology for the distinctive capabilities of STP and research has mainly highlighted certain common capabilities while other essential ones lack analysis. The SLR further reveals that most research has been quantitative in nature relying on secondary database research.

This SLR provides a thorough overview of prior research on STP capabilities investigating 65 articles published in highly ranked peer-reviewed journals, spanning a 22-year period from 1992 to 2014. In sum, his review structures extant STP capabilities literature into a proposed classificatory framework referred to as “CLONT-framework” and highlights its critical importance in strategic management and innovation research from a theoretical, empirical, and practical point of view.