Search results

Progress in theory building in the field of collaborative networks in manufacturing is preponderantly seen in contributions from disciplines outside manufacturing science. Interdisciplinary research is one way of accelerating the development of appropriate theory for this emerging domain where industrial practice has moved beyond the state of the art of scientific knowledge for establishing workable, competitive solutions. The purpose of this paper is to examine to what extent interdisciplinary research has contributed to a better understanding of collaborative (manufacturing) networks.

To find out more about provenances of on‐going studies, to identify clusters of contributions and to provide direction for future work of researchers in this domain, publications of the past 22 years have been evaluated. To retrieve these contributions, a structured literature review has been undertaken by applying keywords to selected databases and using a strictly defined stepwise procedure. In total, 202 publications of all kinds have been evaluated.

From the analysis of the results, it appears that most interdisciplinary contributions to collaborative (manufacturing) networks rely on one original outside discipline for either developing solutions or advancing theoretical insight. Consequently, and after further analysis, it seems that researchers in collaborative networks hardly resort to multi‐disciplinary approaches, unless “natural”; further advances might arrive from stimulating these multi‐disciplinary avenues rather than sticking to more mono‐disciplinary, and less risky, takes on both applications and theoretical insight. A more detailed investigation of the value of contributions reveals that efforts to make interdisciplinary advances are either difficult or limited. Also, the findings indicate that researchers tend to follow a more “technical” approach to decision making by actors in networks rather than searching for a shift in paradigm.

While setting out these directions for future research and guiding research, this first‐of‐its‐kind review introduces the collaboration model as a systematic approach to collaborative (manufacturing) networks. This model might serve as a reference model to integrate disciplines for addressing the characteristics of Collaborative Networks. Its use in the review led to the finding that typical traits of networks, such as changeability, supplementary assets and decentralisation of decision making, are under‐researched.

Energy conservation and environmental protection industry (ECEPI) is a strategic choice to promote energy conservation and emission reduction, develop green economy and circular economy. However, China’s ECEPI is still in the stage of rapid development and the overall scale is relatively small, what development periods have the ECEPI experienced? This study aims to contribute to a better understanding of collaborative innovation evolution based on social network analysis from the perspective of multi-dimensional proximity.

Methodologically, this study uses social network analysis method to explore the co-evolution of multidimensional collaboration networks. It divides China’s ECEPI into four periods based on national policies from 2001 to 2020. This contribution constructs collaborative innovation networks from geographical, technological and organizational proximity.

The results show that the collaborative innovation network was initially formed in the central region of China, gradually expanded to neighboring cities and the core positions of Beijing, Jiangsu and Guangdong have been continuously consolidated. C02F has been the core of the collaboration networks, and the research focus has gradually shifted from the treatment of wastewater, sewage or sludge to the separation field. Enterprises always occupy a dominant position in the collaboration networks.

This research investigates the dynamic evolution process of collaborative innovation network in China’s ECEPI from the perspective of multidimensional proximity, explores the community structure, important nodes and multidimensional proximity features in the network, expands the research perspective on evolution characteristics of innovative network and the research field of social network analysis. Theoretically, this study enriches collaborative innovation theory, social network theory and multi-dimensional proximity theory.

This paper proposes a multi-layer hybrid decision-making approach to evaluate the capability alternatives for developing a collaborative network to operate in the international market.

The present study is contextualised in the Iranian pistachio export industry. An extensive review of the state-of-the-art literature on supplier collaboration was conducted to identify key capabilities that are essential to establish a collaborative network. The set of defined capabilities were then optimised through interviews with 14 experts from the relevant industry, academics and export authorities. A combination of the fuzzy Delphi method and the best–worst method (BWM) approach was, respectively, used to reduce the number of capability alternatives and assign priority weights to these alternatives. Subsequently, a weighted aggregated sum product assessment method (WASPAS) was employed to rank and evaluate the ability to creating a collaborative network for the export of pistachio.

From the extant literature review, 18 capabilities for the formation of coordination networks in the international markets were identified. Then, the prominent indicators in forming a global network were extracted. After ranking the top pistachio export countries/regions to formalise an efficient collaborative network, it was revealed that although Iran exports approximately 30% of the global market, it falls behind the USA and European Union. The competitors have scored higher in critical criteria, including “trust and commitment”, “strategy and management”, “managerial control and standardization” and “financial resources”.

The proposed hybrid approach encompassing fuzzy Delphi–BWM–WASPAS offers to solve the capability evaluation and selection as well as ranking the possible alternative to formalise a collaborative network in an integrated fashion. This combination of methods is capable to first identify the most important factors, then measuring their importance and eventually rank the possible alternatives. The suggested framework provides an approach to deal with the uncertainty of global collaborative network formation.

Although collaborative research is believed to be an important means of accessing external knowledge, research on whether taking a strategic network position benefits new product development (NPD) is inconclusive. This study aims to unravel the conditions under which taking a strategic position within a collaborative research network is conducive for a firm’s NPD.

Drawing on social network theory, absorptive capacity theory and knowledge recombinant studies, this study examines how strategic network positions (i.e. degree centrality and structural holes) and knowledge base cohesion (i.e. local and global cohesion) in tandem affect a firm’s NPD. A panel data set of 366 firms in the Chinese automobile sector (2002–2010) is empirically analyzed, using the panel negative binomial approach with random effects and several alternate estimation approaches.

This study reveals that, rather than the volume of a firm’s knowledge base, its cohesion determines how it absorbs and uses knowledge accrued from collaborative research for NPD. Specifically, this paper finds that centrally positioned firms have greater NPD when their knowledge bases are locally cohesive, while firms spanning structural holes have more NPD when their knowledge bases are globally cohesive.

Successfully transferring collaborative research outcomes into product innovation is difficult. This study contributes to the literature on strategic network positions and NPD. The findings advance the understanding of knowledge base cohesion’s moderating role in explaining how firms absorb and exploit external knowledge for internal innovation. The findings also have important implications for managers who wish to promote product innovation by engaging in collaborative research with external partners.

Knowledge transfer (KT) has been attracting significant attention from the scientific community. The need to establish collaborative network relationships to achieve effective KT has led to a large volume of studies that attempt to identify how collaborative networks influence KT processes. However, papers, which link KT and networks have not been systematised. This study aims to provide an overview of this academic field and sets an agenda for future research.

The authors followed the preferred reporting items for systematic reviews and meta-analyses method to conduct a systematic review of the literature published in 2000–2020. The authors sourced the sample from the Web of Science and Scopus databases. The authors screened the references under the management and business categories that were published in the first two quartiles of the Journal Citation Report. This search returned 190 impactful papers across the 53 journals that were analysed.

The authors present the main results in two sections. First, this paper elaborates a conceptual model of the field; second, the authors review KT between firms and other agents, which allows us to identify KT flows within and between companies, universities and public institutions.

This paper provides the first systematic review of collaborative networks and KT. Five areas of action are identified for future research and are specified in several research questions. The authors also provide several practical implications. In a world in which more and more dynamic agents coexist, it is important to be aware of the needs of organisations that create and disseminate specific knowledge.

Purpose: Provide insights on how social entrepreneurship (SE) knowledge can be more effectively generated by universities through the entrepreneurial creation and effective management of a knowledge network centered on international collaborative research; illuminate how one such network has enabled Latin American researchers to advance the knowledge and practice frontiers in the hemisphere and globally. Methodology/Approach: Retrospective analysis of the two-decade evolution of the Social Enterprise Knowledge Network, a pioneering international research collaboration (IRC) of Ibero-American management schools. Findings: Documents factors and dynamics enabling the successful creation and operation of international knowledge networks. Analyzes the key mechanisms for capturing synergies in collaborative research. Identifies specific effectiveness determinants for successfully operating an international social enterprise knowledge generation network. Identifies multiple impacts of a knowledge generation network. Research Implications: Advances understanding of IRCs. Provides a model for assessing knowledge network multiple impacts. Identifies a series of future research opportunities and needs. Practical Implications: Provides operational guidance for researchers developing or operating collaborative international knowledge networks. Social Implications: Reveals the value of collaboration in international research and factors that contribute to effective collaboration. Originality/Value: Provides unique retrospective study of an IRC network operated by developing country schools of management. Expands the scope of recent comparative research on SE education to include a set of countries in Ibero-America. Documents an approach to assessing the impacts of a knowledge network. Identifies important areas for advancing future social enterprise research and teaching.

Many studies have investigated how the structure of the collaborative networks of researchers influences the nature of their work, and its outcome. Co-authorship networks (CANs) have been widely looked at as proxies that can help bring understanding to the structure of research collaborative ties. The purpose of this paper is to provide a framework for describing what influences the formation of different research collaboration patterns.

The authors use social network analysis (SNA) to analyze the co-authorship ego networks of the ten most central authors in 24 years of papers (703 papers and 1,118 authors) published in the Proceedings of CASCON, a computer science conference. In order to understand what lead to the formation of the different CANs the authors examined, the authors conducted semi-structured interviews with these authors.

Based on this examination, the authors propose a typology that differentiates three styles of co-authorship: matchmaking, brokerage, and teamwork. The authors also provide quantitative SNA-based measures that can help place researchers’ CAN into one of these proposed categories. Given that many different network measures can describe the collaborative network structure of researchers, the authors believe it is important to identify specific network structures that would be meaningful when studying research collaboration. The proposed typology can offer guidance in choosing the appropriate measures for studying research collaboration.

The results presented in this paper highlight the value of combining SNA analysis with interviews when studying CAN. Moreover, the results show how co-authorship styles can be used to understand the mechanisms leading to the formation of collaborative ties among researchers. The authors discuss several potential implications of these findings for the study of research collaborations.

This research aims to explore the research data ethics governance framework and collaborative network to optimize research data ethics governance practices, to balance the relationship between data development and utilization, open sharing, data security and to reduce the ethical risks that may arise from data sharing and utilization.

This study explores the framework and collaborative network of research data ethics policies by using the UK as an example. 78 policies from the UK government, university, research institution, funding agency, publisher, database, library and third-party organization are obtained. Adopting grounded theory (GT) and social network analysis (SNA), Nvivo12 is used to analyze these samples and summarize the research data ethics governance framework. Ucinet and Netdraw are used to reveal collaborative networks in policy.

Results indicate that the framework covers governance context, subject and measure. The content of governance context contains context description and data ethics issues analysis. Governance subject consists of defining subjects and facilitating their collaboration. Governance measure includes governance guidance and ethics governance initiatives in the data lifecycle. The collaborative network indicates that research institution plays a central role in ethics governance. The core of the governance content are ethics governance initiatives, governance guidance and governance context description.

This research provides new insights for policy analysis by combining GT and SNA methods. Research data ethics and its governance are conceptualized to complete data governance and research ethics theory.

A research data ethics governance framework and collaborative network are revealed, and actionable guidance for addressing essential aspects of research data ethics and multiple subjects to confer their functions in collaborative governance is provided.

This study analyzes policy text using qualitative and quantitative methods, ensuring fine-grained content profiling and improving policy research. A typical research data ethics governance framework is revealed. Various stakeholders' roles and priorities in collaborative governance are explored. These contribute to improving governance policies and governance levels in both theory and practice.

The objective of this paper is to provide a model that could be used to define success in a collaborative network by measuring: partners' contribution, partners' involvement (shown in the health of the relationship between partners), and partners' outcome.

The methodology of this research consists of three stages: review, constructing and testing. Review stage comprised of a critical review of the literature in order to understand the characteristics of collaborative network organisations and the reasons behind the failures in collaborative networks. Construction stage resulted in development of a conceptual metric for managing collaborative networks. Testing stage tested the model through case study in a collaborative networks organisation.

The model shows three kinds of measurements that might influence the success of collaborative networks. The contribution measurement uses Analytical Hierarchy Process approach to measure partners' contribution. Likert scale is also applied to measure the health of the relationships based on key performance indicators of relationship attributes. Analytical with mathematical approach is employed to measure the partners' outcome of the collaborative network.

The model is developed based on analytic strategy and need to be chained to present reality in a particular case(s). This paper presents application of the model into a single collaborative network. The fact that this collaboration has been engaged for more than a year in order to develop a particular product, but it was difficult to identify all outcomes precisely. Further research is required with larger sample sizes and with longer time in collaboration to confirm and enhance the conclusions of this paper.

The model provides a practical way of assessing three network's measurements with respect to their objectives. It also provides a useful mechanism for facilitating a discussion between partners in a network.

This paper contributes to the body of knowledge by developing a methodology for measuring partners' contribution, involvement and outcome in the collaborative network as a system within IDEF0 functional modelling. The paper presents a novel metric for measuring contribution, health and outcome of a collaborative network.

The purpose of this paper is to examine a collaborative non‐profit network which is undergoing organizational change.

The authors present a case study of an employment‐services network in its first year of change, as the network implemented various activities to enhance its performance. A grounded‐theory approach was adopted to study the organizational and collaborative processes within the member‐site and Head‐Office levels.

It was found that member‐site leadership was the critical factor influencing site culture and site performance, and that high‐performing sites were initiating collaborative activities with other sites. Head‐Office leadership also influenced site performance and collaboration, but its initiatives were only moderately successful. The findings also indicate that change efforts should focus on leadership at both the site and network levels, and may need to begin with low‐performing sites.

The paper discusses the implications of leadership on the implementation of collaborative networks in the employment services sector.

The qualitative findings of the study add to, and help to explain, earlier research findings on the questions of how public sector organizations utilize various activities to implement collaborative networks and their impact on managerial practice.