Abstract
This paper investigates the relationship between students' performance and the type of school attended during upper secondary education. The performance of three different types of schools (Liceo, Technical and Professional schools) in four Italian macroregions (North West, North East, Centre, South & Islands) is investigated. A benchmarking analysis of the variability in students' performance among regions (within macroregions) for cohorts of students attending Liceo is also conducted. The data was collected at the student level from the Italian Institute for the Evaluation of Education System (INVALSI), for the academic year 2017/18. Families with higher socio-economic status may self-select into Liceo, so a direct comparison with vocational schools could lead to biased conclusions regarding the impact of school type on student performance. To overcome this limitation, we used a Propensity Score Matching approach prior to the estimation of efficiency. A pseudo-Malmquist index, based on a metafrontier and satisfying the circular property, is developed. It enables comparing the location of the best-practice frontier for each type of school and the spread in the educational efficiency of the students attending each type of school. Thus, best performance of a given school type corresponds to the combined effect of these two aspects. This study is an interesting starting point to challenge the stereotypes that persist in Italy, especially concerning general and vocational studies and geographic differences in educational achievements.

Abstract
The storage policy has a tremendous impact on the efficiency of order-picking operations, which can account for up to 50% of operating costs. The coronavirus pandemic has reinforced the importance of managers making the right operational decisions, namely regarding the definition of the storage policy. It is therefore important to consider handling constraints. This article is inspired by a Portuguese retail company and it considers two handling constraints: weight and shape. We define the location of products by using a zero-one quadratic assignment model. In this model, in addition to the demand and similarity, we considered the weight and shape of the products. We used both weight and shape parameters to set products with similar shapes together, placing aside products with odd shapes. Our analysis shows that the inclusion of the shape and weight into the problem improved the current operations. We found that our method allowed for a reduction of up to 24% in the picking distance, a percentage higher than the one that only considers weight constraints. The inclusion of the shape parameter into the study enabled the company to increase the flow and efficiency of the order-picking operations. Thus, it can be an asset for other warehouses.

Abstract
This paper proposes a multi-objective mixed-integer linear programming to model a cold chain with complementary operations on a hierarchical hub network. Central hubs are linked to each other in the first level of the network and to the star network of the lower-level hubs. As for a case study, different hub levels provide various refreshing or freezing operations to keep the perishable goods fresh along the network. Disruption is formulated by the consideration of stochastic demand and multi-level freshness time windows. Regarding the solution, a genetic algorithm is also developed and compared for competing the large-sized networks.

Abstract
The scarcity of resources is one of the main concerns for the present and the future of the environment and society. The "load factor" in logistic transport has a great potential for improvement, especially in the last-mile deliveries, as the transport of goods is largely fragmented between several small companies using small vehicles. This paper investigates the potential for collaboration to increase efficiency in urban logistics. Based on an overview of the concepts and initiatives regarding vertical and horizontal collaboration, a research agenda is proposed.

Abstract
Grasping the intricacy and diversity of complex systems dealing with ever-growing amounts of data is essential to public and private institutions' continuous improvement. Composite indicators (CIs) emerge as aggregators of key performance indicators, providing a single measure that reflects those multidimensional performance aspects. One way to build such measures is based on the use of data envelopment analysis (DEA). Several DEA models can be used to generate CIs. Still, not many of them can deal concurrently with desirable and undesirable outputs, and incorporate the decision-making actors' preference information. Based on the directional 'Benefit-of-the-Doubt' model, we propose a novel approach consisting of the simultaneous use of weight restrictions and an artificial target reached via a range directional vector. The resulting CI assesses the Portuguese public hospitals' performance under two perspectives of hospital activity: users and providers. In the end, managerial and policy implications are withdrawn from the results of this study conducted in cooperation with the Portuguese Ministry of Health.

Abstract
The manufacturing industry faces a new revolution, grounded on the intense digitalization of assets and industrial processes and the increasing computation capabilities imposed by the new data-driven digital architectures. This reality has been promoting the Digital Twin (DT) concept and its importance on the industrial companies' business models. However, with these new opportunities, also new threads may rise, mainly related to industrial data protection and sovereignty. Therefore, this research paper will demonstrate the International Data Spaces (IDS) reference model's application to overcome these limitations. Following a pilot study with a Portuguese machine manufacturing company, this paper will demonstrate the development of a cutting and bending machines DT, leveraged on an IDS infrastructure for interoperability, for the plastic and metal industry and its importance to introduce this machine manufacturing company in a new B2B marketplace from the EU project Market 4.0.