Dynamic Collaborative Networks Research Articles

SLE2: The Improved Social Learning Evolution Model of Cloud Manufacturing Service Ecosystem

As a new form of manufacturing in the industrial Internet era, cloud manufacturing service ecosystem (CMSE) can meet complex customization needs through a dynamic collaborative network between cloud manufacturing services. The source of cloud manufacturing service is social, and such sociality aggravates the uncertainty and dynamics of CMSE. This poses new challenges to the analysis of CMSE's evolution. The existing model social learning evolution (SLE) model only analyzes manufacturing service ecosystem from the perspective of individuals and lacks research on the organizational structure among individuals. In this article, we propose the improved model (SLE2) from a system perspective, which reconstructed the three layers of the SLE model: the individual layer describes the learning and evolution characteristics of service agents; the organization layer describes the competition and cooperation among service agents; and the social layer describes the value-driven social network operation mode. Finally, the article verifies that the SLE2 model is effective through computational experimental results.

What are the economic costs of biological invasions? A complex topic requiring international and interdisciplinary expertise

Biological invasions can cause substantial economic losses and expenses for management, as well as harm biodiversity, ecosystem services and human well-being. A comprehensive assessment of the economic costs of invasions is a challenging but essential prerequisite for efficient and sustainable management of invasive alien species. Indeed, these costs were shown to be inherently heterogeneous and complex to determine, and substantial knowledge gaps prevent a full understanding of their nature and distribution. Hence, the development of a still-missing global, standard framework for assessing and deciphering invasion costs is essential to identify effective management approaches and optimise legislation. The recent advent of the InvaCost database – the first comprehensive and harmonised compilation of the economic costs associated with biological invasions worldwide – offers unique opportunities to investigate these complex and diverse costs at different scales. Insights provided by such a dataset are likely to be greatest when a diverse range of experience and expertise are combined. For this purpose, an international and multidisciplinary workshop was held from 12th to 15th November 2019 near Paris (France) to launch several project papers based on the data available in InvaCost. Here, we highlight how the innovative research arising from this workshop offers a major step forward in invasion science. We collectively identified five core research opportunities that InvaCost can help to address: (i) decipher how existing costs of invasions are actually distributed in human society; (ii) bridge taxonomic and geographic gaps identified in the costs currently estimated; (iii) harmonise terminology and reporting of costs through a consensual and interdisciplinary framework; (iv) develop innovative methodological approaches to deal with cost estimations and assessments; and (v) provide cost-based information and tools for applied management of invasions. Moreover, we attribute part of the success of the workshop to its consideration of diversity, equity and societal engagement, which increased research efficiency, creativity and productivity. This workshop provides a strong foundation for substantially advancing our knowledge of invasion impacts, fosters the establishment of a dynamic collaborative network on the topic of invasion economics, and highlights new key features for future scientific meetings.

Detecting rising stars in dynamic collaborative networks

Abstract In today's complex academic environment the process of performance evaluation of scholars is becoming increasingly difficult. Evaluation committees often need to search in several repositories in order to deliver their evaluation summary report for an individual. However, it is extremely difficult to infer performance indicators that pertain to the evolution and the dynamics of a scholar. In this paper we propose a novel computational methodology based on unsupervised machine learning that can act as an important tool at the hands of evaluation committees of individual scholars. The suggested methodology compiles a list of several key performance indicators (features) for each scholar and monitors them over time. All these indicators are used in a clustering framework which groups the scholars into categories by automatically discovering the optimal number of clusters using clustering validity metrics. A profile of each scholar can then be inferred through the labeling of the clusters with the used performance indicators. These labels can ultimately act as the main profile characteristics of the individuals that belong to that cluster. Our empirical analysis gives emphasis on the “rising stars” who demonstrate the biggest improvement over time across all of the key performance indicators (KPIs), and can also be employed for the profiling of scholar groups.

A Technological Solution to Provide Integrated and Process-Oriented Care Services in Healthcare Organizations

Integrated health services are characterized by a high degree of collaboration and communication among health professionals, as well as a merge of political, administrative, and technical actions, which can allow the sharing of information among healthcare team members (physicians, nurses, managers, and other stakeholders) related to patient care, and access to hospital infrastructure and technology, within a patient-centered approach. In this paper, we propose a technological solution based on software agents, which allows supporting the management of collaborative processes in environments of dynamic collaborative networks. We present a methodology for coordinating healthcare services through collaborative processes to enable organizations providing integrated care services and continuous process improvements. This methodology includes methods based on Model-Driven Development, which enable the generation of executable process models and the code of the process-oriented agents, derived from conceptual models of collaborative processes. The methodology and methods are implemented and automated by software agents that enable the generation of the technological solution, at run-time on the platform. Furthermore, we propose an agent-based platform that enables organizations to negotiate collaboration agreements in electronic format to establish collaborative networks, as well as a definition of the collaborative processes to be executed. In this way, the proposed agent-based platform allows collaborations among heterogeneous and autonomous healthcare organizations focusing on the process-oriented integration, enabling us to provide integrated healthcare services.

Buyer–supplier relationship and optimisation model in a dynamic collaborative network with shortages allowed

To remain competitive, enterprises must build and manage product/service customisation and dynamic collaborative networks to respond to market needs in a flexible manner with competitive price and high product/service quality. This study deals with the emerging research problem of optimally dynamic combined decisions: retail price, stock depletion time/service level (SL) and replenishment schedule/quantity in a decentralised two-echelon perishable product collaborative network comprising a single supplier and a single retailer (buyer) over a finite multi-period planning horizon. Analytical solutions are derived using calculus with dynamic programming under two different trading policies, namely retailer-managed inventory with price-only (RMIPO) mode and vendor-managed inventory with consignment contract (VMICC) mode. In both models, shortages are allowed and are fully backlogged. The validity of the proposed approach is demonstrated using the case of a simple supply chain comprising a regional seafood supplier and a local branch store of a national retail chain. The results show that the VMICC policy yields lower retail price, larger replenishment quantity, higher SL and greater channel-wide profit than the RMIPO policy and achieves a win-win situation for both parties in the supply chain. Additionally, consumers benefit from lower retail price and higher SL in the VMICC policy.

University entrepreneurship in South Africa: Developments in technology transfer practices

Although formalised practices of technology transfer at research institutions are well established in many developed countries, these practices are still very much in their infancy in South Africa. The country is however currently focused on improving technology transfer activities and measuring the performance thereof, as exemplified by the recent implementation of a new intellectual property act. In support of the latter and in an effort to obtain an accurate overview of the status quo of technology transfer in South Africa, it was decided to evaluate organisational structures and key factors determining successful technology transfer at 13 publicly funded research institutions. It is recommended that technology transfer practices in South Africa be further strengthened through the expansion of dynamic collaborative networks and communities of practice. Crucial to these objectives is the development of appropriate metrics for measuring the successes and impact of technology transfer, taking into account the socio-economic and institutional specificities in South Africa.