Abstract
Technological breakthroughs, such as the Internet of Things, Big Data repositories, artificial intelligence or additive manufacturing, are triggering a Fourth Industrial Revolution. This new revolution, also known as Industry 4.0, is characterized by the combination of physical and digital worlds in digital ecosystems that connect the different members in the value chain from clients to suppliers and distributors. Companies are redefining their strategies based on this new paradigm to obtain a competitive advantage. They aim to achieve more efficient and flexible productive processes that can produce high-quality products at low costs, investing on mass customization to satisfy their clients. Accordingly, governments are implementing support programs that create a suitable environment for the adoption of technological innovation strategies by the companies. Although some programs may diverge in some objectives, they all aim to promote workers' skills adaptation, technological supply development, and business modernization. The Portuguese Government also released its program for Industry 4.0 support, known as Portugal i4.0, which is intended to stimulate Portuguese economy digitalization. Furthermore, in latest years, it has been supporting projects through European funds mobilizations from Portugal 2020 program. The present study analyses whether companies that received financial support from Portuguese government to implement innovative projects, within the Industry 4.0 paradigm, were able to improve economic and financial performance and competitivity gains. For such purpose, it was applied an inference statistical method to analyse the differences verified in economics and financial indicators between the periods before and after projects implementation in a selected group of companies.

Abstract

Abstract
Three-Dimensional Packing Problems (3D-PPs) can be applied to effectively reduce logistics costs in various areas, such as airline cargo management and warehouse management. In general, 3D-PP studies can be divided into two different streams: those tackling the off-line problem, where full knowledge about items is available beforehand; and those tackling the on-line (real-time) problem, where items arrive one by one and should be packed immediately without having full prior knowledge about them. During the past decades, off-line and online 3D-PPs have been studied in the literature with various constraints and solution approaches. However, and despite the numerous practical applications of on-line problems in real-world situations, most of the literature to date has focused on off-line problems and is quite sparse when it comes to on-line solution methods. In this regard, and despite the different nature of on-line and off-line problems, some approaches can be applied in both environments. Hence, we conducted an in-depth and updated literature review to identify and structure various constraints and solution methods employed by researchers in off-line and on-line 3D-PPs. Building on this, by bringing together the two separate streams of the literature, we identified several off-line approaches that can be adopted in on-line environments. Additionally, we addressed relevant research gaps and ways to bridge them in the future, which can help to develop this research field.

Abstract
As the demand for rural tourism destinations increases, the relevancy of the tourism sector to the overall destination sustainability becomes even more significant, and the existing tourism operators transition their marketing initiatives to a digital nature, it is critical to understand how the global quality of the implemented e-marketing initiatives are impacting rural destinations image and brand equity, how they trigger tourists' intention to visit, and as a consequence foster overall destination sustainability. Hence, a novel conceptual model, drawn on Delone & McLean Information Systems Success model, Tan & Wu model on the relations between destination image and future visit behavior, and on the overall brand equity context presented by Verma, is proposed and the multiple implications on the presented artefact are discussed.

Abstract
Energy efficiency has become a major concern for manufacturing companies not only due to environmental concerns and stringent regulations, but also due to large and incremental energy costs. Energy-efficient scheduling can be effective at improving energy efficiency and thus reducing energy consumption and associated costs, as well as pollutant emissions. This work reviews recent literature on energy-efficient scheduling in job shop manufacturing systems, with a particular focus on metaheuristics. We review 172 papers published between 2013 and 2022, by analyzing the shop floor type, the energy efficiency strategy, the objective function(s), the newly added problem feature(s), and the solution approach(es). We also report on the existing data sets and make them available to the research community. The paper is concluded by pointing out potential directions for future research, namely developing integrated scheduling approaches for interconnected problems, fast metaheuristic methods to respond to dynamic scheduling problems, and hybrid metaheuristic and big data methods for cyber-physical production systems.

Abstract
Maritime transportation has been, historically, a major factor in economic development and prosperity since it enables trade and contacts between nations. The amount of trade through maritime transport has increased drastically; for example, about 90% of the European Union’s external trade and one-third of its internal trade depend on maritime transport. Major ports, typically, incorporate multiple terminals serving containerships, railways, and other forms of hinterland transportation and require interterminal and intraterminal container transport. Many factors influence the productivity and efficiency of ports and hence their economic viability. Moreover, environmental concerns have been leading to stern regulation that requires ports to reduce, for example, greenhouse gas emissions. Therefore, port authorities need to balance economic and ecological objectives in order to ensure sustainable growth and to remain competitive. Once a containership moors at a container terminal, several quay cranes are assigned to the ship to load/unload the containers to/from the ship. Loading activities require the containers to have been previously made available at the quayside, while unloading ones require the containers to be removed from the quayside. The containers are transported between the quayside and the storage yard by a set of vehicles. This chapter addresses the intraterminal container transport scheduling problem by simultaneously scheduling the loading/unloading activities of quay cranes and the transport (between the quayside and the storage yard) activities of vehicles. In addition, the problem includes vehicles with adjustable travelling speed, a characteristic never considered in this context. For this problem, we propose bi-objective mixed-integer linear programming (MILP) models aiming at minimizing the makespan and the total energy consumption simultaneously. Computational experiments are conducted on benchmark instances that we also propose. The computational results show the effectiveness of the MILP models as well as the impact of considering vehicles with adjustable speed, which can reduce the makespan by up to 16.2% and the total energy consumption by up to 2.5%. Finally, we also show that handling unloading and loading activities simultaneously rather than sequentially (the usual practice rule) can improve the makespan by up to 34.5% and the total energy consumption by up to 18.3%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.