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Optimized supply chains, both economically as well as environmentally, are significant instruments to be adopted by companies if they want to succeed in the current competitive world. However, without the support of decision tools to help, at least approximately, the integration of these two aspects in the company’s decision making such aim is difficult to reach. The purpose of this study is to develop a mixed integer linear programming model (MILP), which allows the optimization of closed loop supply chains, considering not only economical aspects, but also environmental ones. The model developed was applied to a Portuguese company where their logistic network structure was redesigned.

The efficient design and operation of supply chains with return flows represent a major optimization challenge, given the high number of factors involved and their intricate interactions. In particular, the quality level of the return products has strong economic and societal implications and depends greatly on the type of product (glass, paper, electronic, oil, etc) and on the degree of consumers’ readiness, frequently promoted by various kinds of awareness raising campaigns. A multi-product multi-period model was previously developed by the authors [1] for the closed-loop supply chain (CLSC) design and planning, where strategic and tactical decisions were comprehensively considered. This model is now being extended to handle the uncertainty related to the quality of the returned products, which at this stage is modeled by a two-stage scenario-based stochastic approach. General strategies to solve optimization problems involving uncertainty tend to exhibit poor computational performance, due to the problem NP-hard complexity, which tends to worsen with the problem size. Therefore and, in addition, a model performance solution enhancement is also being explored. To increase the efficiency of the solution approach, an alternative representation to some of the integer variables employed in the mathematical formulation was developed, which is tested by means of computational experiments being performed on illustrative real sized examples.

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Service Orientation has been an extensively used approach to model the services Collaborative Networks' (CN) members are willing to provide to customers. The evolution of this paradigm has followed an improvement path since its early forms. Nevertheless bottlenecks still exist, namely in what concerns: 1) a gap between the business and the information and communication technology perspectives; 2) an adequate Quality of Service (QoS) assessment mechanism for the CN context. As a contribution to these issues, this paper proposes: 1) the creation of a collaborative Service Ecosystem, introducing pro-activeness elements towards an auto-initiative representation of CN member's services; 2) the introduction of a QoS mechanism needed to facilitate the assessment of services in a CN context.

Within a Collaborative Business Ecosystem context, as the network evolves, the competition between members increases and, as a consequence, members face the challenge to improve the chances their services have to be selected. On the other hand, the distance between Business Services and “Computational Services” is still a bottleneck for the automation of service provision. This paper extends the Pro-Active Service Entity Framework, proposing a mechanism to improve the service selection chances, based on the refinement of a Quality of Service concept for this context, and introduces a new class of actors for the framework – the intermediaries, needed to shorten the distance between Business and Computational perspectives.

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Supply chains ({SC)} in an attempt to be more competitive, are adopting new management paradigm. Among these paradigms there are four that deserve particular mention because of their importance to better {SC} performance: lean, agile, resilient and green. The main objective of this paper is to propose a conceptual model for a lean, agile, resilience and green {SC}, with the purpose of improving their operational, economic and environmental performance. In this attempt a set of {SC} management practices, which were named {LARG} practices, and several performance measures are suggested. This model is based in the literature review about the four {SC} management paradigms and also {SC} performance measurement. Among the suggested {LARG} practices the ones influencing more the {SC} performance are the just in time and also the supplier relationships. Also the {SC} performance measures with more {LARG} practices influencing them are the inventory levels and the time, that is, the {SC's} operational performance is the most affected.

The objective of this study was to analyse the behaviour of prestress strand anchorages by bonding with an epoxy adhesive for structural strengthening use. Pull-out and push-in tests were carried out on 15·2 mm diameter prestress steel strands sealed in 18 mm diameter holes with several embedment lengths, complemented by long-term tests. Experimental results are presented and compared with theoretical results regarding maximum pull-out and transmittable loads and also draw-in results. Theoretical results are obtained by solving the governing equation of the bond phenomenon adopting a non-linear local bond/slip law derived from pull-out tests with short embedment length. The study shows that it is reasonable to assume an average constant bond stress for anchorage design with the studied epoxy adhesive in the range of the studied values of anchor embedment length and diameter. The average values for bond stress to be used for determining the maximum pull-out and transmittable loads were found to be 12·0 and 5·2 MPa, respectively. Experimental draw-in values show a great variability, and so determining transmission length based on draw-in values may lead to a false perception that the transmission length is very variable.

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Domain Specific Languages (DSLs) are claimed to increment productivity, while reducing the required maintenance and programming expertise. In this context, DSLs usability is a key factor for its successful adoption.

In this paper, we propose a systematic approach based on User Interfaces Experimental validation techniques to assess the impact of the introduction of DSLs on the productivity of domain experts. To illustrate this evaluation approach we present a case study of a DSL for High Energy Physics (HEP).

The DSL on this case study, called Pheasant (PHysicist’s EAsy Analysis Tool), is assessed in contrast with a pre-existing baseline, using General Purpose Languages (GPLs) such as C++. The comparison combines quantitative and qualitative data, collected with users from a real-world setting. Our assessment includes Physicists with programming experience with two profiles; ones with no experience with the previous framework used in the project and other experienced.

This work’s contribution highlights the problem of the absence of systematic approaches for experimental validation of DSLs. It also illustrates how an experimental approach can be used in the context of a DSL evaluation during the Software Languages Engineering activity, with respect to its impact on effectiveness and efficiency.

Purpose –This paper aims to propose a resilience index to assess the company ability to avoid and minimize the negative effects of supply chain disturbances.
Design/methodology/approach – An inductive research approach was used to develop a resilience assessment model. In a first stage, to collect empirical data, an exploratory case study was performed in seven companies’ belong to different positions in the Portuguese automotive supply chain. Next, a resilience index was derived from the case study main findings. In a final stage, the index was then tested using a case study approach in the automotive supply chain.
Findings – It was found that managers do not associate supply chain disturbances to a particular type of events, but with the negative effects that events provoke. The results also suggest that the resilience strategies they used are dependent on the type of supply chain disturbances negative effects. These empirical findings were used to develop a supply chain resilience assessment model and two resilience indexes: resilience index of “on time delivery” to “capacity shortage” and resilience index of “on time delivery” to “materials shortage”.
Research limitations/implications – This paper has the limitations common to all case studies, such as the subjectivity of the analysis and results generalization. Since only the automotive sector was studied, the findings are not universally applicable across different industry sectors in various countries.
Originality/value – The study contributes to the existing literature by empirically investigating the main effects of supply chain disturbances and how companies can increase supply chain resilience. It also suggests a way to evaluate companies’ resilience after a disturbance occurrence and identifies a set of supply chain state variables to improve supply chain resilience.