Knowledge utilisation drivers in technological M&As

Prediction and visualization of Mergers and Acquisitions using Economic Complexity

Mergers and Acquisitions represent important forms of business deals, both because of the volumes involved in the transactions and because of the role of the innovation activity of companies. Nevertheless, Economic Complexity methods have not been applied to the study of this field. By considering the patent activity of about one thousand companies, we develop a method to predict future acquisitions by assuming that companies deal more frequently with technologically related ones. We address both the problem of predicting a pair of companies for a future deal and that of finding a target company given an acquirer. We compare different forecasting methodologies, including machine learning and network-based algorithms, showing that a simple angular distance with the addition of the industry sector information outperforms the other approaches. Finally, we present the Continuous Company Space, a two-dimensional representation of firms to visualize their technological proximity and possible deals. Companies and policymakers can use this approach to identify companies most likely to pursue deals or explore possible innovation strategies.

Reconfiguring the firm’s core technological portfolio through open innovation: focusing on technological M&A

Purpose

The purpose of this study is to investigate the effects of open innovation, especially focusing on technological M&A, on subsequent innovation and changes to the firm’s core technological portfolio.

Design/methodology/approach

The study suggests three types of core technological areas, based on prior focus and experience in technological categories. These are 1) the existing core area, in which the acquirer firm retains its knowledge and expertise, 2) the enhanced core area, where knowledge and expertise in the acquirer firm’s insufficient areas are strengthened, and 3) the new core area, i.e. new knowledge fields in which the acquirer firm ventures into. The study then analyzes the effects of two key knowledge characteristics of the target firm, similarity and complementarity, on post-M&A innovation outcomes in each of the three core technological areas.

Findings

The results confirm that while none of the investigated knowledge characteristics of the target firm is advantageous for post-M&A innovation outcomes in existing core areas, similarity of the target firm does facilitate post-M&A innovation outcomes in enhanced core areas. Moreover, the results confirm that complementarity of the target firm is beneficial for post-M&A innovation outcomes in new core areas.

Originality/value

The study explains the reconfiguration mechanism of a firm’s core technological portfolio. It also suggests an extended framework to analyze innovation outcomes in more detail. Moreover, the study helps to explain why most M&As result in failure.

Is high-quality knowledge always beneficial? Knowledge overlap and innovation performance in technological mergers and acquisitions

This research analyses the effects of the knowledge overlap between acquirer and target firms on the performance of technological mergers and acquisitions (M&As). Extending previous research that has focused on the quantitative characteristics of knowledge, this research introduces a framework capturing the effects of both the quantity and quality of knowledge in overlapped and nonoverlapped parts of the knowledge base on subsequent innovation performance. Analyzing a data set of 192 technological M&As of 162 high-technology firms from 2001 to 2009, the results show that a high quality of overlapped knowledge has a positive effect on subsequent innovation performance, while the effect is negative for nonoverlapped knowledge quality. In addition, this research investigates the influence of the knowledge quantity on subsequent innovation performance. The implication of this research is that the knowledge overlap in technological M&As is essential for acquiring high-quality knowledge from the target firm and for improving innovation performance.

How to interact with knowledge-intensive business services: A multiple case study of small and medium manufacturing enterprises in China

Empirical support for the process and mechanism of interactions with knowledge-intensive business services (KIBS) is scarce, particularly with regard to small and medium manufacturing enterprises (SMMEs). Our study investigated how four SMMEs in China’s electrical appliance industry cluster attained high performance through interactions with KIBS. For our research, knowledge integration can be understood as knowledge identification, knowledge accession, and knowledge utilization. We investigated the mechanism involved in interactions between SMMEs and KIBS by tentative multiple case studies, and found that interactions with technology-based KIBS improved the performance of SMMEs by influencing their knowledge accession and knowledge utilization. Interactions with traditional professional KIBS, however, mainly influence SMMEs’ knowledge identification and knowledge accession. technology-based KIBS generally acts as a knowledge source and professional KIBS as a knowledge bridge for SMMEs. Interaction with technology-based KIBS is a kind of complementary interaction, while interaction with professional KIBS is a kind of supplementary interaction.