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The aim of this research is to elucidate the correlation between open innovation, digital strategies and networking in enhancing agricultural enterprises within the new perspective of Agrifood 5.0. As such, it contributes to making businesses more competitive, especially in the Italian agricultural sector, where small and medium-sized enterprises are highly fragmented. Numerous studies have asserted that the competitiveness of actors operating within a specific territory is closely linked to local identity and image enhancement. Agricultural organizations are undergoing a profound transformation, with technological assets emerging as catalysts for new synergies. Advanced technologies such as robotics, the Internet of Things (IoT) and automation (AI) are emerging as differentiating elements capable of further advancing the agricultural sector, transitioning it from Agrifood 4.0 to Agrifood 5.0. The empirical analysis of the research shows a positive correlation between a collaborative attitude and a propensity for innovation. Indeed, the data demonstrated that digital strategies and open innovation positively influence competitiveness in agricultural SMEs.

The methodology employed in this study is mixed, incorporating both qualitative and quantitative approaches. The quantitative aspect involves analysis of the dataset from the Italian Statistical Institute (ISTAT) through logistic regression, while the qualitative component entails analysis of semi-structured interviews conducted with a sample of 174 agricultural cooperatives in southern Italian regions (Campania). This approach allows for a comprehensive understanding of the research topic, capturing both numerical trends and nuanced insights from interviews.

After analyzing the data from the 7th General Census of Agriculture conducted by ISTAT, a clear understanding of the sector has emerged, revealing several potential research avenues. It is evident that innovation in the agricultural sector is often driven by the largest and best-capitalized production entities, primarily located in Italy. Conversely, smaller agricultural entities can benefit from networking as new technological assets act as catalysts for new synergies, innovation and competitiveness.

Enhancing the relational contribution within the network and humanizing a fragmented sector are crucial elements for promoting open innovation. Network structuring facilitates the transmission of managerial knowledge, contributing to an overall increase in the intellectual and relational capital of the agricultural sector. These factors, combined with open innovation, enhance the competitiveness of individual firms and elevate the brand of the entire sector, creating a conducive environment for transitioning toward Agrifood 5.0. This transition is characterized by increased interconnection, continuous innovation and overall prosperity. Specific studies on this topic are lacking in Italy, particularly in the southern regions. Therefore, this contribution focuses on investigating the Campania region.

The novelty of this study lies in its investigation of the relationship between agricultural enterprises and innovation in the context of enterprises networking strategies (i.e. associationism and/or cooperation), promoting competitiveness. The limitations of this study are related to the dimension of the sample selected and its relationship with other productive sectors.

To exploit collaboration-driven innovation, in recent years, many government-sponsored innovation programs and mentor services have emerged. These services support an effective exchange of knowledge among innovation actors, including innovation mentors and enable mentor connectedness as an important factor to develop and sustain effective innovation mentors’ community of practice (CoP). The purpose of this paper is to examine the degree of connectedness in an innovation mentor CoP.

In this study, the innovation mentors CoP as part of a national innovation program is considered a network. The connectedness and assortative mixing of this CoP and the effects of these two on each other were examined by using social network measures, including component analysis, the giant component (GC) and assortativity.

The authors provide the analytical interconnectedness results for both the GC and the whole network with network analysis and assortativity measurements of three attributes of mentors (institution, title and degrees). The degree of correlation of community for the GC shows preferential attachment between high-ranking and low-ranking mentors, while preferential attachment was not observed for the whole network. The correlation coefficient for the institution attribute has the highest value for GC, while the title has the highest value for the whole network.

The study is one of the early attempts to apply social network analysis for an innovation mentor CoP. This study reveals the criticality of evaluating the GC and the whole network separately and provides a number of research and practical directions that will contribute to the development of the innovation mentor CoP.

This study aims to investigate the influence of network power on exploratory and exploitative innovation and examines the moderating effects of power distance and procedural justice on these untested relationships.

This study uses survey data collected from firms in China and explores the influential mechanisms of network power, power distance and procedural justice in firm innovation.

This study empirically shows that network power has an inverted U-shaped effect on exploratory and exploitative innovation. Power distance weakens the effect of network power on exploratory and exploitative innovation, and procedural justice enhances the effect of network power on exploratory and exploitative innovation.

This study extends resource dependence theory and contributes to the literature on innovation management. Future studies should use different collection channels or research methods to provide more evidence for model promotion. In addition, the dynamic power game among network members and the roles of other mediators or moderators warrant further consideration.

Managers should exercise power strategies properly and ensure that their innovation income exceeds expenditures. Managers need to pay serious attention to power distance and procedural justice in the network and formulate suitable cooperation strategies based on actual conditions.

This study applies the resource dependence theory to investigate the influence of network power on exploratory and exploitative innovation. In addition, the moderating roles of power distance and procedural justice in the above relationships, which have rarely been discussed in previous studies, were tested.

In the context of open innovation, more and more enterprises are leveraging innovation networks to drive disruptive innovation performance, but there is no consensus on the relationship between network embeddedness and enterprise disruptive innovation performance. This paper aims to systematically explore the relationship between them.

This paper constructs a multi-level network embeddedness model and uses 58 independent studies as samples to explore the relationship between multi-level network embeddedness and enterprise disruptive innovation performance by meta-analysis.

First, network embeddedness at the enterprise and regional levels will promote the improvement of disruptive innovation performance. Although industrial relationship embeddedness will promote the improvement of disruptive innovation performance, its structural embeddedness will bring negative effects. Second, in terms of mediating effect, policy-oriented support will promote the relationship between network embeddedness and disruptive innovation performance at the enterprise and industry levels. Compared with large enterprises, small- and medium-sized enterprises will have more advantages in the performance of multi-level network embedding and disruptive innovation performance. Under the subjective performance measurement method, the promotion effect of multi-level network embedding is more prominent.

This study enriches the theoretical research of network embeddedness and disruptive innovation and provides management enlightenment for the network embeddedness strategy of enterprise disruptive innovation. Limited by data samples and article length, future research can further expand literature samples to test the stability of variable relationships and test the moderating effects of more internal and external factors.

First, it constructs a theoretical analysis model of “point-line-surface” multi-level network embedding and disruptive innovation performance of enterprises and expands the theoretical analysis framework of network embedding and disruptive innovation performance. The second is to explore the influence mechanism of multi-level network embeddedness and enterprise disruptive innovation performance. Third, it deepens the theoretical understanding of the moderating variables of the impact of network embeddedness and enterprise disruptive innovation performance.

The relationship between cooperative R&D network embeddedness and firm innovation resilience is understudied. This paper seeks to answer the questions of whether and how embedding in cooperative R&D networks improve digital firms’ innovation resilience.

Based upon social capital theory, this paper proposes a conceptual model with several hypotheses. The empirical analysis is based on a sample of 2,908 observations from 2005 to 2022. We measure firm innovation resilience by drawing on economic resilience and use LSM tests to assess the effect of cooperative R&D network position on innovation resilience.

The results indicate that cooperative R&D network centrality has a positive impact on firm innovation resilience and that the structural holes of the cooperative R&D network have an inverted U-shaped relationship with firm innovation resilience. Moreover, technological turbulence negatively moderates the relationship between centrality and firm innovation resilience while also steepening the inverted U-shaped relationship between structural holes and firm innovation resilience. Market turbulence positively moderates the relationship between centrality and firm innovation resilience. However, the moderating effect of market turbulence on the inverted U-shaped relationship between structural holes and firm innovation resilience is not significant.

Innovators' knowledge needs, bounded rationality, interests, and even organizational environments change over time, thus prompting them to constantly seek new opportunities to exchange and integrate knowledge, meet new beneficial partners, maintain beneficial cooperation, or terminate unhelpful cooperation. The utility of the network structure has dynamic characteristics. Only by considering the dynamics of the network can research on the mechanism of network structure be more complete, accurate and convincing. Therefore, future research can pay more attention to the relationship between dynamic networks and firm innovation resilience.

Firms should actively embed themselves in the cooperative R&D network and occupy a beneficial network position. By joining the cooperative R&D network, firms can gain resource advantages and enhance their ability to resist external shocks and improve innovation resilience.

This research advances our understanding of the antecedents of firm innovation resilience through the lens of organizational cooperation and uncovers the boundary conditions under which network embeddedness influences innovation resilience, thereby further enriching the theoretical framework of innovation resilience.

As sustainable performance has a central role in the small and medium enterprises (SMEs) performance literature, this study aims to examine the influence of networking capabilities in enhancing sustainable performance through knowledge workers’ productivity and digital innovation. It also examines the sequential mediating role of knowledge workers’ productivity and digital innovation on networking capabilities and SMEs’ sustainable performance relationship.

Data were collected from 308 knowledge workers in the information technology sector and analyzed using the Hayes Process Macro bootstrapping method to test the proposed hypotheses.

Results indicate that knowledge workers’ productivity and digital innovation individually and sequentially mediate the relationship between networking capabilities and SME’s sustainable (economic and environmental) performance, surprisingly, they do not act as a mediator between networking capability and SME’s social performance. SMEs should prioritize investments in the professional development of their knowledge workers through training and skill enhancement programs. This investment equips knowledge workers with the tools to effectively use the knowledge and resources acquired through networking. Thus, knowledge workers may improve performance by using these resources to tackle challenges.

Although this research focused on this specific context, it is prudent to acknowledge that additional factors may also exert influence on sustainable performance within SMEs, factors that managers may consider when making decisions. Methodologically, the cross-sectional design of this research poses a potential limitation, as it does not allow for the complete elimination of endogeneity concerns. However, it is worth noting that scholars have endorsed the use of cross-sectional data in cases where management researchers aim to expand beyond well-documented and longitudinal data sets.

This research offers practical recommendations for SMEs to improve their sustainable performance through networking. SMEs should seek partnerships with complementary knowledge to improve operations and for other performance-oriented benefits.

This study adds significantly to the literature on sustainable SME performance by studying the interdependent effects of networking capabilities. It also represents the individual and sequential mediation mechanism that links networking capabilities to SME success through knowledge worker productivity and digital innovation.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

Positive effect of knowledge sharing (KS) on innovation has come to the fore and government-supported innovation and mentoring communities or mentor networks have become widespread. This article aims to examine the community connectedness and mentors' preferences for professional competency-based KS of such innovation community of practice networks (CoPNs).

The paper constructs a directed weighted CoPN model with a node-attribute-based novel fingerprint edge weights. Based on the CoPN, Social Network Analysis (SNA) metrics and measures including Giant Component (GC) were proposed and analyzed to identify mentors' connectedness preferences. The fingerprint was proposed as a novel binarized node attribute of competence. Jaccard similarity of fingerprints was proposed as edge weights to reveal correlations between competences and preferences for KS.

The work opted to conduct a survey of 28 innovation mentors to measure a CoPN. Both a name generator question and a second set of questions were employed to invite respondents to name their collaborators and indicate their professional competence. SNA metrics result in differing values for GC and the rest, which lead us to focus on GC to reveal salient metrics of connectedness. Jaccard similarity analysis results on GC demonstrate that mentors collaborate in an interdisciplinary manner.

Based on the CoPN, the methods proposed may be effective in predicting preferred relationships for interdisciplinary collaborations, providing the managers with an analytical decision support tool for KS in practice.

Online open innovation platforms provide opportunities for product users to participate in the innovation process and contribute their ideas to the platform. Nonetheless, they also present a significant challenge for platform managers, who select high-quality innovations from a massive collection of information with diverse quality.

In this study, the authors employed a machine learning method to automatically collect a real dataset of 2,276 innovations and 30,004 detailed comments from the online platform of IdeaExchange and then conducted empirical experiments to verify the study hypothesis.

Results show that extraversion, conscientiousness and openness to experience positively and directly influenced the quality of their innovation. Furthermore, an individual's social network position mediated among extraversion, neuroticism, conscientiousness and openness to experience and the quality of an innovation.

Results showed that extraversion, conscientiousness and openness to experience positively and directly influenced the quality of their innovation. Furthermore, an individual's social network position mediated among extraversion, neuroticism, conscientiousness, openness to experience and the quality of innovations.

This study combined the Big Five personality traits theory and social network theory to examine the association between user intrinsic personality traits, social network position and the quality of their innovative ideas in the context of online innovation platforms. Additionally, the findings provide new insights for platform managers on how to select high-quality innovation information by considering user personality traits and their social network position.

This study aims to explore the relationship between network position and innovation under major environmental turbulence.

The authors use a difference-in-differences identification approach using the 2009 Industry Revitalization Plan in response to the global financial crisis as a natural experiment with a sample of Chinese listed firms from 2001 to 2017.

The findings show that a major environmental turbulence can facilitate firm innovation, and firms that occupy central positions in the interlock network show worse innovation performance while firms with high brokerage show better innovation performance.

The literature on environmental implication has largely focused on the threats and overlooked the potential opportunities. Moreover, social network literature has elaborated on the benefits and constraints of network positions from a static perspective but largely overlooked their implications facing environmental change. By exploring the bright side of major environmental turbulence and including this factor as a key contingency in exploring the effects of centrality and brokerage, this study integrates external environmental context with social network research and provides empirical evidence responding to the call for more attention to network dynamics and extends our understanding of the context-contingent network effects on firm innovation.