Negotiation Support and Risk Reduction in Collaborative Networks

Part 2: Collaborative Enterprise NetworksInternational audienceIn face of the current economic turbulence, companies face new challenges. In order to respond to new business opportunities, it is crucial that companies attain strategic alliances so that they can obtain or maintain market competiveness. The formation of alliances and partnerships for collaborative problem solving is of extreme importance, being therefore essential to understand their structures and requirements. To overcome a number of difficulties that may appear in the formation of such alliances, it is necessary to properly model the elements that constitute the alliance agreements through a suitable negotiation support environment that besides the basic functionalities of data storage and alerts can also conduct the entire negotiation process making it traceable. In this context, this paper presents the main requirements of an electronic negotiation support environment in a collaborative network, identifies the main risk sources and drivers in collaborations, and analyses how a negotiation support system can help in reducing the potential risk in collaboration

Collective Emotions Supervision in the Product-Servicing Networks

Part 2: Collaborative Enterprise NetworksInternational audienceThe GloNet network is an agile virtual enterprise environment for networks of SMEs involved in highly customized and service-enhanced products through end-to-end collaboration with customers and local suppliers (co-creation) in the solar park construction sector. A challenge that arises in this network is the effective management of the interactions among participating organizations and their customers. Some participants’ problems, that are not solvable with the working hard procedures of the project execution, might arise leading to some potential tension. Most of the times this tension is a result of soft “emotional” issues experienced in the collaboration “environment”. Considering these challenges and having in mind enhancing the quality of the interactions between the involved participating organizations, this paper describes a scenario for supervising collective emotions in the GloNet network context

Simulation model to estimate emotions in collaborative networks

This work has been funded in part by the Center of Technology and Systems and the Portuguese FCT-PEST program UID/EEA/00066/2019 (Impactor project), and partly by the GloNet project funded by the European Commission.In recent years, the research on collaborative networks has been pointing to the need to put more emphasis on the social interactions of its participants, along with technical features, as a potential direction to finding solutions to prevent failures and potential conflicts. In this context, a modelling framework called Collaborative EMOtion modelling framework (C-EMO), conceived for appraising the collaborative network emotions that might be present in a collaborative networked environment, is presented, and an implementation approach, based on system dynamics and agentbased simulation modelling techniques, for estimating both the collaborative network emotional state and each member's emotions, is described. The work is divided in two parts: the first considers the design of the models and the second comprises the transformation of these conceptual models into a computer model, providing the proposed simulation model. In order to validate the simulation model, and taking into consideration the novelty of the research area, experiments are undertaken in different scenarios representing several aspects of a collaborative environment and a sensitivity analysis and discussion of the results is performed.publishe

Assessment of sustainable collaboration in collaborative business ecosystems

Advances in information and communication technologies and, more specifically, in artificial intelligence resulted in more intelligent systems, which, in the business world, particularly in collaborative business ecosystems, can lead to a more streamlined, effective, and sustainable processes. Following the design science research method, this article presents a simulation model, which includes a performance assessment and influence mechanism to evaluate and influence the collaboration of the organisations in a business ecosystem. The establishment of adequate performance indicators to assess the organisations can act as an influencing factor of their behaviour, contributing to enhancing their performance and improving the ecosystem collaboration sustainability. As such, several scenarios are presented shaping the simulation model with actual data gathered from three IT industry organisations running in the same business ecosystem, assessed by a set of proposed performance indicators. The resulting outcomes show that the collaboration can be measured, and the organisations' behaviour can be influenced by varying the weights of the performance indicators adopted by the CBE manager.info:eu-repo/semantics/publishedVersio

Elements of a methodology to assess the alignment of core-values in collaborative networks

Collaborative networks are typically formed by heterogeneous and autonomous entities, and thus it is natural that each member has its own set of core-values. Since these values somehow drive the behaviour of the involved entities, the ability to quickly identify partners with compatible or common core-values represents an important element for the success of collaborative networks. However, tools to assess or measure the level of alignment of core-values are lacking. Since the concept of 'alignment' in this context is still ill-defined and shows a multifaceted nature, three perspectives are discussed. The first one uses a causal maps approach in order to capture, structure, and represent the influence relationships among core-values. This representation provides the basis to measure the alignment in terms of the structural similarity and influence among value systems. The second perspective considers the compatibility and incompatibility among core-values in order to define the alignment level. Under this perspective we propose a fuzzy inference system to estimate the alignment level, since this approach allows dealing with variables that are vaguely defined, and whose inter-relationships are difficult to define. Another advantage provided by this method is the possibility to incorporate expert human judgment in the definition of the alignment level. The last perspective uses a belief Bayesian network method, and was selected in order to assess the alignment level based on members' past behaviour. An example of application is presented where the details of each method are discussed

A method to analyse the alignment of core values in collaborative networked organisations

Since collaborative networked organisations are usually formed by independent and heterogeneous entities, it is natural that each member holds his own set of values, and that conflicts among partners might emerge because of some misalignment of values. In contrast, it is often stated in literature that the alignment between the value systems of members involved in collaborative processes is a prerequisite for successful co-working. As a result, the issue of core value alignment in collaborative networks started to attract attention. However, methods to analyse such alignment are lacking mainly because the concept of 'alignment' in this context is still ill defined and shows a multifaceted nature. As a contribution to the area, this article introduces an approach based on causal models and graph theory for the analysis of core value alignment in collaborative networks. The potential application of the approach is then discussed in the virtual organisations' breeding environment context

Collaborative Networks in Industry and the role of PRO-VE

Camarinha-Matos, LM. (2014). Collaborative Networks in Industry and the role of PRO-VE. International Journal of Production Management and Engineering. 2(2):53-56. doi:10.4995/ijpme.2014.3031SWORD535622Camarinha-Matos, L M, Collaborative Networks: A Mechanism for Enterprise Agility and Resilience In: Enterprise Interoperability VI (K. Maertins et al. Eds.), Springer, 2014, pp. 3-11.Camarinha-Matos, L. M., Afsarmanesh, H., Galeano, N., & Molina, A. (2009). Collaborative networked organizations – Concepts and practice in manufacturing enterprises. Computers & Industrial Engineering, 57(1), 46-60. doi:10.1016/j.cie.2008.11.024Camarinha-Matos, L. M., & Afsarmanesh, H. (2005). Collaborative networks: a new scientific discipline. Journal of Intelligent Manufacturing, 16(4-5), 439-452. doi:10.1007/s10845-005-1656-3Kühnle, H., & Dekkers, R. (2012). Some thoughts on interdisciplinarity in collaborative networks’ research and manufacturing sciences. Journal of Manufacturing Technology Management, 23(8), 961-975. doi:10.1108/1741038121127682

Simulation-Based Decision Support System for Energy Efficiency in Buildings Retrofitting

Funding Information: This research was developed under project EnPROVE (Energy Consumption Prediction with Building Usage Measurements for Software-Based Decision Support) funded by the European Union’s Seventh Framework Programme (Grant agreement ID: 248061). Partial support was also given by the Portuguese “Fundação para a Ciência e Tecnologia (FCT)” through the project UIDB/00066/2020 (Center of Technology and Systems, CTS). Publisher Copyright: © 2022 by the authors.The implementation of building retrofitting processes targeting higher energy efficiency is greatly influenced by the investor’s expectations regarding the return on investment. The baseline of this work is the assumption that it is possible to improve the predictability of the post-retrofit scenario, both in energy and financial terms, using data gathered on how a building is being used by its occupants. The proposed approach relies on simulation to estimate the impact of available energy-efficient solutions on future energy consumption, using actual usage data. Data on building usage are collected by a wireless sensor network, installed in the building for a minimum period that is established by the methodology. The energy simulation of several alternative retrofit scenarios is then the basis for the decision support process to help the investor directing the financial resources, based on both tangible and intangible criteria. The overall process is supported by a software platform developed in the scope of the EnPROVE project. The platform includes building audit, energy consumption prediction, and decision support. The decision support follows a benefits, opportunities, costs, and risks (BOCR) analysis based on the analytic hierarchy process (AHP). The proposed methodology and platform were tested and validated in a real business case, also within the scope of the project, demonstrating the expected benefits of alternative retrofit solutions focusing on lighting and thermal comfort.publishersversionpublishe

Technological Innovation for the Internet of Things: 4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013, Costa de Caparica, Portugal, April 15-17, 2013. Proceedings

International audienceBook Front Matter of AICT 39

The Role of Collaborative Networks in Sustainability

http://www.springerlink.com/content/978-3-642-15960-2#section=791431&page=1International audienc