Abstract
Today, organisations suffer a tremendous pressure to become more agile, efficient, profitable and dynamic. The market presents itself as an area of severe competition, where the margin between success and failure is becoming tenuous. Some authors have noticed the importance of meaningful and reliable information as a prerequisite of successful management and high-quality decision-making. Multiple factors, in the business environment were shown to cause impact in the organisational performance, such as the market attractiveness, the resources availability, clockspeed-industry, the environmental predictability, decision velocity and market opportunity discovery. The purpose of developing this research work was essentially to respond the following questions: Can the organisation improve performance by monitoring the market dynamics, by compiling information for the strategic positioning identification and market opportunities discovery? Can the information gathered agile the decision-making and the strategic alignment with the market? The market attractiveness index calculation phase intends to quantify the data collected from the multiple indicators, and then determine an index, for each market in the evaluation process. This technique is divided in three main steps, which consist of: (1) Calculating the mass density by category (Macro-Environment, Micro-Environment and Organisation), followed by (2) the product calculation of each category by the main market and, finally, (3) the prioritization of the different markets in study. The development of a methodology for assessing the market attractiveness is considered to be very relevant in the global market scenario. It can help organisations to gain a greater awareness of market dynamics, speed up the decision process and increase its consistency, thus enabling the strategic alignment and the improvement of the organisational performance.

Abstract
Several e-business frameworks are currently available, which are aimed at modelling e-business. The aim of this article is to analyse and compare relevant industry-neutral and industry-specific e-business frameworks currently in use, emphasising their strengths and weaknesses towards seamless interoperability in a collaborative networked environment. Their main differences and similarities are underlined based on an analytical model for e-business frameworks comparison. The applicability of the Analytic Hierarchy Process multi-criteria method in e-business frameworks selection is discussed. These analytical approaches are then illustrated with two real cases from industry.

Abstract
The advances in information and communication technologies and economic factors impelled organizations to engage in new forms of collaboration, such as collaborative networks. They require adequate frameworks, architectures, tools and platforms to support interoperability among heterogeneous and geographically distributed organizations. Despite the high number of research projects in this area, existing tools and infrastructures, this objective has not been totally achieved. The aim of this research work is to advance the research in the area of interoperability in collaborative networks. A conceptual framework towards seamless interoperability in a collaborative-competitive economic networked environment is described, which comprises six elements: (1) a messaging service: (2) a collaboration profile/agreement definition and management service; (3) five clusters of collaborative activities: (4) a centralized repository; (5) a set of business documents and a set of contracting documents; (6) a performance assessment service. The functionality of the conceptual framework proposed is illustrated with a real implementation case targeting the footwear industry. The proposed conceptual framework is then compared with relevant e-business frameworks.

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 organization that pools the core competencies of its member enterprises and exploits fast changing market opportunities. The success of such an organization is strongly dependent on its composition, and the selection of partners becomes therefore a crucial issue. This problem is particularly difficult because of the uncertainties related to information, market dynamics, customer expectations and technology speed up. In this paper we propose an integrated approach to rank alternative VE configurations in business environments with uncertainty, using an extension of the TOPSIS method for fuzzy data, improved through the use of a stochastic multiobjective tabu search meta-heuristic. Preliminary computational results clearly demonstrate the potential of this approach for practical application.

Abstract
This paper presents an innovative approach to support the definition of strategies for the design of alternative configurations of hospital supply chains. This approach was developed around a hybrid Tabu Search / Variable Neighbourhood Search metaheuristic, that uses several neighbourhood structures. The flexibility of the procedure allows its application to supply chains with different topologies and atypical cost characteristics. A preliminary computational experience shows the approach potential in solving large scale supply chain configuration problems. The future incorporation of this approach in a broader Decision Support System (DSS) will provide a tool that can significantly contribute to an increase of healthcare supply chains efficiency and encourage the establishment of collaborative partnerships between their members.