Abstract
The paper proposes a Flexibility Requirements Model and a Factory Templates Framework to support the dynamic Virtual Organization decision-makers in order to reach effective response to the emergent business opportunities ensuring profitability. Through the construction and analysis of the flexibility requirements model, the network managers can achieve and conceive better strategies to model and breed new dynamic VOs. This paper also presents the leagility concept as a new paradigm fit to equip the network management with a hybrid approach that better tackle the performance challenges imposed by the new and competitive business environments.

Abstract
The design, production and distribution of small series of health fashionable goods for specific target groups of wide impact in terms of market for the European industry as elderly, disables, diabetics and obese people represents a challenging opportunity for European companies which are asked to supply the demand with affordable price and eco-compatible products. Added to this challenge, textile, clothing and footwear manufactures seek for innovative collaborative networking solutions that could provide an entire digital life-cycle for the products and services required by the market. Aligned with this need, the EU CoReNet project aims to design and develop a new smart collaborative consumer-driven framework with the related services and components. This paper addresses the multidisciplinary complexity of customer-oriented and eco-friendly networks for health fashionable goods in particular addressing business requirements analysis, value chain issues, co-planning production and co-design topics in collaborative business processes tailored for high variability of the consumers demand and expectations.

Abstract
This paper aims to explore the performance alignment in collaborative network environments. It has been stated that performance management based on data collection and the evaluation of key performance indicators (KPIs) may not be effective due to the different indicators and measurement systems in place for the various participants in a collaborative network (CN). Therefore, measuring the strategic and inter-organizational alignment based on key alignment indicators (KAIs) can be an excellent alternative to improve performance evaluation systems. This approach has led to the exploration of the performance prediction paradigm and develops tools to estimate a performance and evaluate the degree of alignment by creating instances of a future performance in collaborative networks.

Abstract
In this paper we present a Decision Support System (DSS) to deal with the partner selection problem taking place in the formation or re-organization of a Virtual Enterprise (VE). This DSS is based on a multi-criteria model and handles several types of data (numerical, interval, linguistic and binary). This approach is used to facilitate the expression of the decision maker's preferences and assessments about the potential partners and can be performed individually or by group. The system also allows the assignment of a degree of confidence to each linguistic statement. the operation of the DSS is structured in two phases. In the first phase it determines the set of non-dominated alternatives (potential VEs) through the use of meta-heuristics. The second phase ranks the alternatives for a possible network of enterprises configuring the VE. This is achieved through a procedure based on linguistic analysis and distance measures.

Abstract
Partner selection in virtual enterprises (VE) can be viewed as a multi-criteria decision making problem that involves assessing trade-offs between conflicting tangible and intangible criteria. In general, this is a very complex problem due to the dynamic topology of the network, the large number of alternatives and the different types of criteria. In this paper we propose an exploratory process to help the decision-maker obtain knowledge about the network in order to identify the criteria and the companies that best suit the needs of each particular project. This process involves a multi-objective tabu search metaheuristic designed to find a good approximation of the Pareto front, and a fuzzy TOPSIS algorithm to rank the alternative VE configurations. In the exploratory phase we apply clustering analysis to confine the search according to the decision-maker beliefs, and case base reasoning, an artificial intelligence approach, to totally or partially construct VEs by reusing past experiences. Preliminary computational results clearly demonstrate the potential of the approach for practical application.

Abstract
A virtual enterprise (VE) is a temporary organisation that pools member enterprises core competencies and exploits fast changing market opportunities. VEs offer new opportunities to companies operating with a growing number of participants (consumers, vendors, partners and others) in a global business environment. The success of such an organisation is strongly dependent on its composition, and the selection of partners therefore becomes a crucial issue. Partner selection can be viewed as a multi-criteria decision making problem that involves assessing trade-offs between conflicting tangible and intangible criteria, and stating preferences based on incomplete or non-available information. In general, this is a very complex problem due to the large number of alternatives and criteria of different types (quantitative, qualitative and stochastic). In this paper we propose an integrated approach to rank alternative VE configurations using an extension of TOPSIS (a technique for ordering preferences by similarity to an ideal solution) for fuzzy data, improved through the use of a tabu search meta-heuristic. A sensitivity analysis is also presented. Preliminary computational results clearly demonstrate the potential of the approach for practical application.