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The purpose of this paper is to develop the concept of a high performance alliance macro-culture as a multilevel construct reflective of resilient collaborative systems of exchange within strategic alliances and explores the distinct capabilities of this multilevel approach in predicting alliance outcomes.

The hypotheses developed in this study are tested using primary data collected from 650 members of 15 non-profit organizations in two multi-organizational collaborative networks. Considering the multilevel nature of the study the structural hypotheses are tested using a multilevel confirmatory factor analysis and the predictive hypotheses are tested using multilevel structural equation modeling.

All but one structural hypothesis are supported and all predictive hypotheses are supported suggesting that a multilevel macro-cultural conceptualization is effective in exploring the relationship between collaborative exchange systems and their outcomes.

Limitations stem from the generalizability of the data collected as the alliances formed by non-profit firms may not be wholly reflective of the alliance structures and goals of other firm types.

This study primarily contributes to multilevel study of strategic alliances and the study of collaborative norms and structures of allied groupings. The results of this study lend support to the importance of taking a network governance perspective and illustrate the limitations of traditional single-level approaches when studying interfirm collaborative networks and structural resilience therein.

The purpose of this paper is to examine how a performance measurement system (PMS) can be designed for a collaborative network and to identify which factors affect such a design.

This is a single-case study of a collaborative network. The data have been collected from semi-structured interviews conducted during 2008-2009 and after the design process in 2010 and 2012, respectively.

The research results present a five-step process model for designing a PMS for a collaborative network. The findings show that a participatory development style that enhances socialisation, the positive development of a network culture and an outside facilitator all have beneficial effects on the design process.

The practical contribution of this study is related to knowledge about the PMS design process for a collaborative network to support its measurement-related development projects. This knowledge involves the phases of such a process as well as the various factors supporting or hindering it.

The study presents a PMS design process for the case network, which can be utilised in other collaborative networks in a similar context. It also highlights the most essential practical experiences related to this process.

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.

Although prior studies have identified several technologies related to Industry 4.0 and their individual potential, it is still unclear how these technologies could be integrated to achieve better results. Based on this, we propose several collaborative networks combining technologies associated with Industry 4.0.

A literature review was performed using a research model to support the evaluation and identification of key and collaborative technologies related to Industry 4.0. We examined these technologies using hierarchical cluster analysis and principal components analysis, based on their characteristics.

The study identified big data, cloud computing, the internet of Things and cyber-physical systems as key technologies for Industry 4.0, and a further eight collaborative technologies that are strongly related to industrial performance. We found five collaborative networks with distinct goals in the context of Industry 4.0: (1) smart manufacturing; (2) technological platforms; (3) market reactiveness; (4) smart products and (5) flexibility.

The findings allowed us to create five pathways for future work on Industry 4.0 technologies via collaborative networks. In practice, this will help managers to improve their focus on priorities regarding the implementation of Industry 4.0 technologies.

This study provides insights into how to establish links between technologies through collaborative networks for certain purposes. In addition, we propose five future directions for these collaborative networks that require further investigation by researchers.

Governance network managers are charged with triggering and sustaining collaborative dynamics, but often struggle to do so because they come from and interact with hierarchical and competitive organizations and systems. Thus, an important step toward effectively managing governance networks is to clarify collaborative dynamics. While the recently proposed collaborative governance regime (CGR) model provides a good start, it lacks both the conceptual clarity and parsimony needed in a useful analytical tool. This theoretical chapter uses the logic model framework to assess and reorganize the CGR model and then amends it using Follett’s theory of integrative process to provide a parsimonious understanding of collaborative dynamics, as opposed to authoritative coordination or negotiated cooperation. Uniquely, Follett draws from political and organizational theory practically grounded in the study of civic and business groups to frame the manner in which integrative process permeates collaboration. We argue that the disposition, style of relating, and mode of association in her integrative method foster collaborative dynamics while avoiding the counterproductive characteristics of hierarchy and competition. We develop an alternative logic model for studying collaborative dynamics that clarifies and defines these dynamics for future operationalization and empirical study.

The aim of this paper is to propose a genetic algorithms approach to develop a collaborative supply chain network, i.e. a supply chain network with genetic algorithms embedded (GA‐SCN), so as to increase the efficiency and effectiveness of a supply chain network.

The methodologies of the GA‐SCN are illustrated through a case study of a supply chain network of a Hong Kong lamp manufacturing company involving 10 entities, whose roles range from suppliers, purchasers, designers and manufacturers, to sales and distributors. A GA‐SCN is developed according to the information provided by the company, the performance results in the case study are discussed, and the concepts of network analysis are then introduced to analyze the equivalence structure of the developed GA‐SCN.

The genetic algorithms approach is a suitable approach for developing an efficient and effective supply chain network in terms of shortening the processing time and reducing operating time in the network: the processing time and operating cost are reduced by around 45 percent and 35 percent per order, respectively, in the case study.

This paper is the first known study to apply genetic algorithms for the development of a collaborative supply chain network to increase the competitiveness of a supply chain.

This paper seeks to propose an overall model of collaborative forecasting for networked manufacturing enterprises.

Contributions by several authors to collaborative forecasting have been analysed from different viewpoints. A collaborative‐forecasting model for networked manufacturing enterprises has been proposed and validated by means of a simulation study.

This model significantly reduces the inventory levels of the whole network and improves customer service.

Simulation experiments were done with the enterprise network herein described. Future research will include the simulation of more complex enterprise network scenarios with different characteristics.

The model can be implemented node‐to‐node, since not all the companies in the network have to participate, thus facilitating implementation and propagation throughout the network.

The paper proposes a new structured planning and forecasting collaboration model for networked manufacturing enterprises.

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.

The purpose of this paper is to propose the Collaborative Search System that attempts to achieve collaboration by implicitly identifying and reflecting search behaviour of collaborators in an academic network that is automatically and dynamically formed. By using the constructed Collaborative Hit Matrix (CHM), results are obtained that are based on the search behaviour and earned preferences of specialist communities of researchers, which are relevant to the user's need and reduce the time spent on bad links.

By using the Digital Bibliography Library Project (DBLP), the research communities are formed implicitly and dynamically based on the users’ research presence in the search environment and in the publication scenario, which is also used to assign users’ roles and establish links between the users. The CHM, to store the hit count and hit list of page results for queries, is also constructed and updated after every search session to enhance the collaborative search among the researchers.

The implicit researchers community formation, the assignment and dynamic updating of roles of the researchers based on research, search presence and search behaviour on the web as well as the usage of these roles during Collaborative Web Search have highly improved the relevancy of results. The CHM that holds the collaborative responses provided by the researchers on the search query results to support searching distinguishes this system from others. Thus the proposed system considerably improves the relevancy and reduces the time spent on bad links, thus improving recall and precision.

The research findings illustrate the better performance of the system, by connecting researchers working in the same field and allowing them to help each other in a web search environment.