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Currently, China’s manufacturing industry chain still faces the danger of chain breakage due to the persistent “lack of technology” issue. The definition and detection of key nodes in the industry chain are significant to the enhancement of the stability of the industry chain. Therefore, detecting the key nodes in the manufacturing industry chain is necessary.

A complex network based on the links amongst listed manufacturing enterprises is built, and the authors analyse the network’s basic characteristics and vulnerability, taking into account the impact of scientific and technological innovation on the stability of the industry chain.

It is found that the high structural characteristic of midstream nodes in the naval architecture and marine engineering equipment industry chain determines their importance to stability, and the key status of upstream nodes is reflected in the weakness of technological innovation. The upstream nodes should focus on improving their independent innovation and R&D capability, whilst the midstream nodes should maintain a close supply–demand cooperation relationship.

The key node detection model for industry chain stability is constructed by considering various factors from the perspective of network and technological innovation. Empirical study is conducted to verify effectiveness of proposed method.

Previous research has analyzed the consequence of network stability; however, little is known about how partner type diversity influence network stability in R&D network. Based on knowledge-based view and social network theory, the purpose of this paper is to unravel the internal mechanisms between partner type diversity and network stability through the mediating role of knowledge recombination in R&D network.

The authors collected an unbalanced panel patent data set from information communication technology industry for the period 1994–2016. Then, the authors tested the different dimensions of partner type variety and its relevance in the R&D network and the mediating role of knowledge recombination through adopting the multiple linear regression.

Results indicate an inverted U-shaped relationship between partner type diversity (variety and relevance) and network stability, whereas knowledge recombination partially mediate these relationships.

From the perspective of R&D networks, this paper explores that there are the under-researched phenomena the antecedent of network stability through nodal attributes (i.e. partner type variety and partner type relevance). Moreover, this paper empirically examined the mediating role of knowledge recombination in the partner type diversity–network stability relationships. The novel perspective allows focal firm to recognize importance of nodal attributes, which are critical to fully excavate the potential capabilities of cooperating partners in R&D network.

The aim of this paper is to characterise the association between business network and the balanced scorecard used by Malaysian small and medium enterprises (SMEs) as a method for assessing firm efficiency. The business network takes into account both the dimensions of stability and efficiency. The business network can help SMEs, with fewer resources to remain competitive. By having a secure business network, the performance of SMEs in Malaysia can be further improved. A business network can facilitate swift coordination amongst distant geographies to create new competitive advantages by accessing market segments, resources as well as building strategic business alliances.

A total of 404 sets of data collected by using stratified random sampling and structured questionnaire as an instrument. The list of SMEs collected from the Malaysia Foreign Trade Growth Corporate Directory (MATRADE) directories. Structural equation modelling (SEM) was utilised to analyse the data.

The findings show that the business network plays a role in the balanced scorecard (BSC) outcomes of Malaysian SMEs.

This article provides the owners and managers with an awareness to rapidly achieve the company's efficiency. Finally, the new article often has some consequences for decision-makers and regulators.

Small and medium-sized enterprises (SMEs), typically with limited resources, strive hard to obtain the trust of ecosystem participants as an orchestrator. Accordingly, the firms do not have sufficient legitimacy to persuade other parties to join their networks. This study aims to investigate how an SME operating in the publishing industry orchestrates ecosystem participants. In particular, the study analyzes how the orchestrating firm stimulates interactions among ecosystem participants.

Case study research with a qualitative approach has been documented as a well-accepted method for investigating complex phenomena and for theory building. Collected data from various informants and different collection techniques are triangulated to ensure validity. Cross-case analysis to identify common patterns is undertaken as the basis for developing a sound conclusion.

The study demonstrated what orchestrating firms should do to foster innovations and how they benefit from other participants in the ecosystem. The analysis identified the orchestrator's four roles: entrepreneurship networks, knowledge activation, innovation intermediary and network leadership. Among the four roles, there are interrelationships, and to some degree, these overlap. The orchestrating firm must emerge into the ecosystem and work together with all members of the ecosystem. Managers of the orchestrating firm and network members should collaborate to find the most beneficial configuration for all ecosystem participants.

This research is limited to the knowledge-intensive publishing industry. The use of specific industries closely related to innovation provides an advantage in the way that enables researchers to conduct depth analysis, but at the expense of generalizability, and therefore, future research can analyze different industries.

This study focuses on networks as the unit of analysis. Previous studies assumed individual firms as the unit of analysis and ignored the fact that companies interact with other companies when pursuing open innovation. The study focuses on the interactions between actors as the unit of analysis and on the role of orchestrators undertaken by an SME.

This paper aims to explore how a shared service centre (SSC) is mobilised in a power-dominant context of a Chinese state-owned enterprise (SOE). Specifically, it examines the mobilisation of SSC within this multi-divisional SOE, the role and dynamics of actors involved and the influence of changes in the integrated information system (IIS) during the mobilisation process.

The study follows a qualitative case study methodology. The authors draw on actor-network theory to examine the network and translation processes constructed in mobilising SSC in the chosen SOE. The data sources of this study were collected through semi-structured interviews, observations and documentary reviews.

The mobilisation of SSC is not a linear process but rather a “spiral” interplay through continuous interactions and compromises between human and non-human actors. Power gave the core actor as an orchestrator legitimacy and formality to reduce resistance and obstruction in translation for the mobilisation of SSC. The changes in IIS appear to facilitate the interaction between the heterogeneous actors.

This case study contributes towards understanding the mobilisation of SSC in a power-dominant context by highlighting the impact of changes in IIS and the details of the mobilisation of SSC in terms of the role played by both the individual actors and the technology.

This study provides a broader understanding of the interactions of the heterogeneous actors for mobilising SSC in a power-dominant context. More importantly, the study inspires future research into examining how SSC practices unfold and how the changes in IIS influence the mobilisation of SSC.

A circular economy (CE) is an economic system that tries to eliminate waste and continually use resources. Due to growing environmental concerns, supply chain (SC) design should be based on the CE considerations. In addition, responding and satisfying customers are the challenges managers constantly encounter. This study aims to improve the design of an agile closed-loop supply chain (CLSC) from the CE point of view.

In this research, a new multi-stage, multi-product and multi-period design of a CLSC network under uncertainty is proposed that aligns with the goals of CE and SC participants. Recycling of goods is an important part of the CLSC. Therefore, a multi-objective mixed-integer linear programming model (MILP) is proposed to formulate the problem. Besides, a robust counterpart of multi-objective MILP is offered based on robust optimization to cope with the uncertainty of parameters. Finally, the proposed model is solved using the e-constraint method.

The proposed model aims to provide the strategic choice of economic order to the suppliers and third-party logistic companies. The present study, which is carried out using a numerical example and sensitivity analysis, provides a robust model and solution methodology that are effective and applicable in CE-related problems.

This study shows how all upstream and downstream units of the SC network must work integrated to meet customer needs considering the CE context.

The main goal of the CE is to optimize resources, reduce the use of raw materials, and revitalize waste by recycling. In this study, a comprehensive model that can consider both SC design and CE necessities is developed that considers all SC participants.

Innovativeness is crucial for industrial cluster firms to gain sustained competitive advantage. This study aims to investigate the effects of inter-firm coopetition on firm innovativeness within a cluster and examines the moderating role of institutional support.

This research adopts an empirical survey method using multi-source data from 181 industrial cluster firms. Regression is used to test the hypotheses of this study.

The results show that cooperation and constructive conflict promote firm innovativeness, while destructive conflict is detrimental to firm innovativeness. Moreover, the study also finds that cooperation interacts with both types of conflict to affect firm innovativeness, where cooperation and constructive conflict interact negatively on firm innovativeness, while cooperation and destructive conflict interact positively on firm innovativeness. In addition, institutional support weakens the effects of cooperation and destructive conflict on innovativeness, respectively, but has no significant moderating effect on the relationship between constructive conflict and innovativeness.

These findings enrich the current research on coopetition. The interaction effects of cooperation and both types of conflict on innovativeness deepen the concept of coopetition and responds to the call to further explore the interaction effects within coopetition. The moderating role of institutional support fills a gap in the empirical research on the role of institutional factors affecting coopetition on innovation and also provides valuable suggestions for firm managers and governments in industrial clusters.

This study aims to investigate the importance and effect of asymmetric technological collaborations’ key success factors in developing countries. The number of collaborations between large enterprises and SMEs, known as asymmetric technological collaborations (ATC) is growing considerably. But this asymmetry in itself can increase the number and intensity of collaboration challenges. So far, limited studies have been conducted on the stability of ATCs, and most of them have been in the context of developed countries. Meanwhile, studying the strength and stability of collaboration in the nano industry with growing market value and increasing newcomers is of particular importance.

Here, with bionic engineering approach, we used chemistry for the first time to identify the main stability factors of ATCs and build our hypotheses and research model. To this end, we introduced the factors affecting the stability of the dative chemical bond as a bionic counterpart of corporate venture capital (CVC), which is a type of ATC, and proposed 4 hypotheses. We used structural equation modeling (SEM) with partial least squares (PLS) method to examine the hypothesized relationships.

The analysis of survey questionnaire data from 26 asymmetric collaborations in Iran’s nanotechnology industry shows that “learning of the acceptor company” with a negative effect, “network ties” and “development of the collaboration host region” with a positive effect and “diversity in the collaboration portfolio” with an inverted U-shaped effect are the most influential factors in the stability and continuity of CVCs, respectively.

The findings of this research can be the beginning of a broad path leading to exploring and getting inspiration from chemistry to analyze management issues.

Considering the frequency of extreme events, enhancing the global financial system's stability has become crucial. This study aims to investigate the contagion effects of extreme risk events in the international commodity market on China's financial industry. It highlights the significance of comprehending the origins, severity and potential impacts of extreme risks within China's financial market.

This study uses the tail-event driven network risk (TENET) model to construct a tail risk spillover network between China's financial market and the international commodity market. Combining with the characteristics of the network, this study employs an autoregressive distributed lag (ARDL) model to examine the factors influencing systemic risks in China's financial market and to explore the early identification of indicators for systemic risks in China's financial market.

The research reveals a strong tail risk contagion effect between China's financial market and the international commodity market, with a more pronounced impact from the latter to the former. Industrial raw materials, food, metals, oils, livestock and textiles notably influence China's currency market. The systemic risk in China's financial market is driven by systemic risks in the international commodity market and network centrality and can be accurately predicted with the ARDL-error correction model (ECM) model. Based on these, Chinese regulatory authorities can establish a monitoring and early warning mechanism to promptly identify contagion signs, issue timely warnings and adjust regulatory measures.

This study provides new insights into predicting systemic risk in China's financial market by revealing the tail risk spillover network structure between China's financial and international commodity markets.

The purpose of this study is to analyze the dynamic changes of the arms trade network not only from the network structure but also the influence mechanism from the aspects of the economy, politics, security, strategy and transaction costs.

The study employs the Temporal Exponential Random Graph Model and the Separable Temporal Exponential Random Graph Model to analyze the endogenous network structure effect, the attribute effect and the exogenous network effect of 47 major arms trading countries from 2015 to 2020.

The results show that the international arms trade market is unevenly distributed, and there are great differences in military technology. There is a fixed hierarchical structure in the arms trade, but the rise of emerging countries is expected to break this situation. In international arms trade relations, economic forces dominate, followed by political, security and strategic factors.

Economic and political factors play an important role in the arms trade. Therefore, countries should strive to improve their economic strength and military technology. Also, countries should increase political mutual trust and gain a foothold in the industrial chain of arms production to enhance their military power.

The contribution of this paper is to analyze the special trade area of arms trade from a dynamic network perspective by incorporating economic, political, security, strategic and transaction cost factors together into the TERGM and STERGM models.