How does open innovation affect firms’ innovative performance

Effects of open innovation strategies on innovation performance of SMEs: evidence from China

Purpose

The purpose of this study is to investigate the relationships between two types of open innovation (OI) strategies (OI breadth and depth) and innovation performance of small- and medium-sized enterprises (SMEs) in China. The study examines how firms’ absorptive capacity and government institutional support affect these relationships.

Design/methodology/approach

Survey data from 236 manufacturing SMEs in China were used to test the proposed model using hierarchical regression analysis.

Findings

The results show that both OI breadth and depth are positively related to innovation performance of SMEs. Moreover, this study finds that realized absorptive capacity serves as a mediator in the relationships between OI breadth and depth and innovation performance. The potential absorptive capacity and government institutional support moderate the relationship between OI breadth and innovation performance.

Originality/value

The effectiveness of OI strategies is significantly different among SMEs. One possible explanation is that SMEs adopt different types of OI strategies. Another is that a firm’s absorptive capacity and government institutional support may influence the effectiveness of OI. This study integrates these two possible reasons by investigating the effect of the interplay between different OI strategies, absorptive capacity and government institutional support on SMEs’ innovation performance. This study enriches the research on the relationships between OI strategies and innovation performance of SMEs in the Chinese context.

Effect of network embeddedness on innovation performance of small and medium-sized enterprises

Purpose

The purpose of this study was to identify if network embeddedness and innovation performance relationship, which has been largely studied in multinational enterprises (MNEs) and large corporations, was also applicable in the context of small and medium-sized enterprises (SMEs). Secondly, the authors also sought to identify the moderating role of innovation openness in the relationship between network embeddedness and SMEs' innovation performance.

Design/methodology/approach

Empirical analysis was based on 388 SMEs in Ghana. Various validity and reliability checks were conducted before the presentation of the actual analysis, which was conducted using the structural equation modeling in Amos (v.23).

Findings

Findings revealed that, in the context of SMEs, network embeddedness had significant positive effect on innovation performance. The authors further identified that SMEs with both high levels of network embeddedness and innovation openness had a much higher performance in their innovation, compared to SMEs that relied solely on network embeddedness.

Research limitations/implications

The current study found innovation openness to further strengthen the relationship between network embeddedness and SMEs' innovation performance. The relationship between network embedded and SME's innovation could, however, be mediated by knowledge transfer mechanisms, so future studies should pay particular attention to the mediating mechanisms.

Practical implications

Management of SMEs is advised to develop conducive organizational structures, such as trust, openness to collaboration and so on, for effective innovative knowledge transfer and transformation.

Originality/value

Past research studies on network embeddedness and innovation performance have dominantly resided in MNE and large corporations. This current study extends the body of knowledge by extending the network embeddedness and innovation performance research studies to SME context.

The double-edged sword of external search in collaboration networks: embeddedness in knowledge networks as moderators

Purpose

The purpose of this paper is to analyze the inverted U-shaped relationship between external search in the collaboration network and firm innovation outcomes. It also seeks to explore whether these curvilinear relationships are moderated by the network centrality and structural holes in the knowledge network.

Design/methodology/approach

In this empirical research, the authors collected a sample of patents in the smartphone industry over the period of 2000-2017. Then the authors examined the direct roles of external search breadth and depth in the collaboration network and the moderating role of network embeddedness in the knowledge network by using negative binomial regression.

Findings

Results found that external search in the collaboration network contributes more to firm innovation outcomes when the breadth and depth of the external search are moderate rather than high or low. Furthermore, both network centrality and structural holes in the knowledge network have positive effects on the external search breadth – innovation outcomes and external search depth – innovation outcomes relationships.

Research limitations/implications

The authors collected the patent data within the single industry and excluded other types of industries. This may limit the generalization of the findings.

Practical implications

The paper has practical implications for adopting appropriate search strategies in the collaboration network and developing a better understanding of the effect of network embeddedness in the knowledge network on firm innovation outcomes. The findings suggest future directions for technology-intensive industries to improve their innovation output.

Originality/value

This study adds value to open innovation literature by pointing out a curvilinear relationship (inverted U-shaped) between external search breadth/depth and innovation outcomes in collaboration networks, in contrast to studies focused on firms’ external collaboration strategies in a certain industry context. Furthermore, this study reinforces the key contingent role of embeddedness in knowledge networks. This study provides a valuable theoretical framework of innovation outcome determinants by connecting the network perspective of open innovation theory with an embeddedness view.