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With technological innovation elements and the competitive market environment becoming increasingly complex, numerous firms utilize network embeddedness to achieve and sustain innovation. However, empirical research has not conclusively established which form of network embeddedness more effectively facilitates corporate innovation. Drawing on the heterogeneous network resources perspective, this study explores the impact of market network embeddedness, technology network embeddedness and their synergy on the green innovation performance of manufacturing small and medium-sized enterprises (SMEs). Furthermore, it investigates the moderating role of resource orchestration capability in these relationships.

Through an online questionnaire survey of Chinese manufacturing SMEs, 293 sample data were collected, and the hierarchical regression analysis was conducted to test the hypothesis.

The results indicate that market and technology network embeddedness significantly enhance green innovation performance, with the former exerting a more significant impact. Furthermore, the synergy between market and technology network embeddedness positively influences green innovation performance. Additionally, resource orchestration capability strengthens the positive effects of both market and technology network embeddedness on green innovation performance, while the moderating effect of resource orchestration capability on the relationship between the synergy of the two and green innovation performance was insignificant.

The study faced many limitations, such as collecting primary data, which relied on a questionnaire only, using cross-sectional data and examining only manufacturing SMEs.

Based on the heterogeneous network resources perspective and integrating social network theory and resource orchestration theory, this study explores the impact of network embeddedness on the green innovation performance of manufacturing SMEs, which sheds new light on the network embeddedness research framework and also enriches the antecedents of green innovation. In addition, this study provides implications on how manufacturing SMEs effectively utilize network embeddedness and resource orchestration capability to enhance green innovation performance.

This study aims to explore the different effects of inter-community group networks and intra-community group networks on group innovation.

The authors used a pooled panel dataset of 12,111 self-organizing innovation groups in 463 game product creative workshop communities from Steam support to test the hypothesis. The pooled ordinary least squares (OLS) model is used for analyzing the data.

The results show that network constraint is negatively associated with the innovation performance of online groups. The average path length of the inter-community group network negatively moderates the relationship between network constraint and group innovation, while the average path length of the intra-community group network positively moderates the relationship between network constraint and group innovation. In addition, both the network density of inter-community group networks and intra-community group networks can negatively moderate the negative relationship between network constraint and group innovation.

The findings of this study suggest that network structural characteristics of inter-community networks and intra-community networks have different effects on online groups’ product innovation, and therefore, group members should consider their inter- and intra-community connections when choosing other groups to form a collaborative innovation relationship.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image. The authors used three feature extraction methods: handcrafted features, convolutional features and autoencoder features. Subsequently, these features were mapped to contact locations through a contact location regression network. Finally, the network performance was evaluated using spherical fittings of three different radii to further determine the optimal feature extraction method.

This paper aims to estimate contact location from sparse and high-dimensional soft tactile array sensor data using the tactile image.

This research indicates that data collected by probes can be used for contact localization. Introducing a batch normalization layer after the feature extraction stage significantly enhances the model’s generalization performance. Through qualitative and quantitative analyses, the authors conclude that convolutional methods can more accurately estimate contact locations.

The paper provides both qualitative and quantitative analyses of the performance of three contact localization methods across different datasets. To address the challenge of obtaining accurate contact locations in quantitative analysis, an indirect measurement metric is proposed.

The potential of vehicle ad hoc networks (VANETs) to improve driver and passenger safety and security has made them a hot topic in the field of intelligent transportation systems (ITSs). VANETs have different characteristics and system architectures from mobile ad hoc networks (MANETs), with a primary focus on vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. But protecting VANETs from malicious assaults is crucial because they can undermine network security and safety.

The black hole attack is a well-known danger to VANETs. It occurs when a hostile node introduces phony routing tables into the network, potentially damaging it and interfering with communication. A safe ad hoc on-demand distance vector (AODV) routing protocol has been created in response to this issue. By adding cryptographic features for source and target node verification to the route request (RREQ) and route reply (RREP) packets, this protocol improves upon the original AODV routing system.

Through the use of cryptographic-based encryption and decryption techniques, the suggested method fortifies the VANET connection. In addition, other network metrics are taken into account to assess the effectiveness of the secure AODV routing protocol under black hole attacks, including packet loss, end-to-end latency, packet delivery ratio (PDR) and routing request overhead. Results from simulations using an NS-2.33 simulator show how well the suggested fix works to enhance system performance and lessen the effects of black hole assaults on VANETs.

All things considered, the safe AODV routing protocol provides a strong method for improving security and dependability in VANET systems, protecting against malevolent attacks and guaranteeing smooth communication between cars and infrastructure.

An emerging body of literature has pinpointed the role of supply chain structure in influencing the extent to which supply chain members disclose information about their internal practices and performance. Nevertheless, empirical research investigating the effects of firm-level relational embeddedness on network-level transparency still lags. Drawing on social network analysis, this research examines the effect of relational embeddedness on supply chain transparency and the contingent role of digitalization in the context of environmental, social and governance (ESG) information disclosure.

In their empirical analysis, the authors collected secondary data from the Bloomberg database about 2,229 firms and 14,007 ties organized in 107 extended supply chains. The authors employed supplier and customer concentration metrics to measure relational embeddedness and performed multiple econometric models to test the hypothesis.

The authors found a positive effect of supplier concentration on supply chain transparency, but the effect of customer concentration was not significant. Additionally, the digitalization of focal firms reinforced the impact of supplier concentration on supply chain transparency.

The study findings contribute by underscoring the critical effect of relational embeddedness on supply chain transparency, extending prior literature on social network analysis, providing compelling evidence for the intersection of digitalization and supply chain management, and drawing important implications for practices.

This study aims to investigate the relationships between managers’ cognitive styles, dynamic managerial capabilities and firms’ perceived international performance. The study is based on cognitive-experiential self-theory, dynamic managerial capabilities and international entrepreneurship.

Data were collected from 283 managers of small medium enterprises (SMEs) in Türkiye, an emerging economy. The research was conducted using quantitative methods, and Smart partial least squares (PLS) 4 software was used for data analysis. The data were examined through structural equation modelling and mediation analyses.

Findings indicate that rational cognitive styles positively influence managerial human capital, managerial social capital, managerial cognition and perceived international performance. However, the effect of intuitive cognitive styles was confirmed only on managerial cognition. Additionally, it was found that managerial cognition positively affects perceived international performance, whereas managerial social capital has a negative impact. However, the effects of managerial human capital could not be confirmed. Moreover, a full mediation relationship of managerial cognition between intuitive cognitive styles and perceived international performance was identified.

This research carves out a unique niche by synergizing cognitive-experiential self-theory with dynamic managerial capabilities to investigate their conjoined effect on firms’ international performance, an area previously underexplored. Unveiling insights from burgeoning economies like Türkiye enriches the existing body of knowledge, offering substantial contributions to the field of international business.

This study aims to clarify why and when digital business strategy (DBS) helps manufacturing firms generate value co-creation (VC) with different stakeholders in the digital context of China. This study considers external network capability (ENC) and internal network capability (INC) as mediation mechanism, and strategic flexibility (SF) as theoretical boundary.

Questionnaires were used and filled out by executives from manufacturing firms. The manufacturing samples from 289 different fields in China were used for hypothesis testing, and the structural equation model was the main analytical method.

This study found that DBS of manufacturing enterprises has a positive impact on VC. Specifically, DBS affects firm-partner VC and firm-consumer VC through the indirect positive effect of ENC, and affects firm-employee VC through INV. The positive effects of ENC on firm-partner VC and firm-consumer VC, as well as INC on firm-employee VC, are weak at high (or low) SF, and are strongest at moderate SF.

This study provides manufacturing firms with practical insights into why and when they can implement DBS to generate VC, with a particular emphasis on the weighted role of SF.

This study spotlights gaps in the literature on why and when manufacturing firms can reap the benefits of DBS, focusing on one important business outcome – VC. The authors clarify the mediating role of differences in ENC and INC, as well as the inverted U-shaped moderating role of SF.

This study aims to identify research trends and technological evolution in the polymer three-dimensional (3D) printing process that can effectively identify the direction of technological advancement and progress of acceptance in both society and key manufacturing industries.

The Scopus database was used to collect data on polymer 3D printing papers. This study uses bibliometric approach along with network analytic techniques to identify and discuss the most important countries and their scientific collaboration, compares income groups and analyses keyword trends.

It was found that top research production results from heavy investments in research and development. The USA has the highest number of papers among the high-income countries. However, scientific production in the other two income groups is strongly dominated by China and India. Keyword analysis shows that countries with lower incomes in certain areas, such as composite and bioprinting, have fallen behind other groups over time. International collaborations were suggested as mechanisms for those countries to catch up with the current research trends. The evolution of the research field, which started with a focus on 3D printing processes and shifted to printed part designs and their applications, was discussed. The advancement of the research topic suggests that translational research on polymer 3D printing has been led mainly by research production from higher-income countries and countries with large research and development investments.

Previous studies have conducted performance analysis, science mapping and network analysis in the field of 3D printing, but none have focused on global research trends classified by country income. This study has conducted a bibliometric analysis and compared the outputs according to various income levels according to the World Bank classification.

While previous research has demonstrated the positive effects of digital business strategies on operational efficiency, financial performance and value creation, little is known about how such strategies influence innovation performance. To address the gap, this paper aims to investigate the impact of a firm’s digital business strategy on its innovation performance.

Drawing on the dynamic capability view, this study examines the mechanism through which a digital business strategy affects innovation performance. Data were collected from 215 firms in China and analyzed using multiple regression and structural equation modeling.

The empirical analysis reveals that a firm’s digital business strategy has positive impacts on both product and process innovation performance. These impacts are partially mediated by knowledge-based dynamic capability. Additionally, a firm’s digital business strategy interacts positively with its entrepreneurial orientation in facilitating knowledge-based dynamic capability. Moreover, market turbulence enhances the strength of this interaction effect. Therefore, entrepreneurial-oriented firms operating in turbulent markets can benefit more from digital business strategies to enhance their knowledge-based dynamic capabilities and consequently improve their innovation performance.

This study contributes to the understanding of how a firm’s digital business strategy interacts with entrepreneurial orientation in turbulent markets to shape knowledge-based dynamic capability, which in turn enhances the firm’s innovation performance.

Many studies have investigated dynamic positions and their importance, but there is less attention paid to how to enter more central positions. Interorganizational relationships are an important factor in network structural change. In Chinese society, firms allocate significant human, financial and material resources towards cultivating guanxi. The purpose of this study is to explore whether and how the three aspects of guanxi, namely renqing, ganqing and xinyong, can make firms more central, and to examine the mediating role of interaction.

The study used a mixed method to collect data from 256 Chinese Cops (complex product systems) firms. And, hypotheses were tested using SPSS 25.0 and AMOS 26.0.

The results indicate that renqing, ganqing and xinyong have significant positive effects on the increase in centrality, but with varying magnitudes. Additionally, the interaction was found to mediate the relationship between the three aspects of guanxi (renqing, ganqing and xinyong) and the increase in centrality.

The study provides new insights to help firms become more central by combining guanxi (renqing, ganqing and xinyong) with change in centrality, enriching the literature on network dynamics and guanxi-related research. Moreover, the study provides managers with a clear understanding of how to use guanxi to make the firm more central in situations with limited resources.