Abstract
The relevance of the tourism industry to the overall sustainability of rural territories grows along with the demand for rural tourism destinations. Likewise, as the digital transition of rural tour operators takes place, their marketing initiatives also evolve towards a digital nature, which is why it is crucial to comprehend how the overall calibre of these activities might affect the perception of rural places, while also motivating tourists' travel intentions and, as a result, promoting the general sustainability of the destination. Thus, in this paper, we propose a novel conceptual model based on Delone and McLean's representative model of Information Systems Success Model, on Tan and Wu's arguments on tourism destinations' image relationship with tourists' visit intentions, and also on Verma's tourism destination brand equity concept. To validate the proposed model, an online focus group was developed involving several specialists whose opinions and perspectives corroborated the potential adequacy of the proposed artefact and, consequently, assumed its contribution and value. From this validation process, it was possible to highlight that digital marketing initiatives' overall quality influences both rural destinations' image and tourists' intention to visit these territories, that a positive image will trigger tourists' visit behaviour, and that these behaviours represent a valuable asset to rural destinations' global sustainability.

Abstract
Sectorization is the division of a large area, territory or network into smaller parts considering one or more objectives. Dynamic sectorization deals with situations where it is convenient to discretize the time horizon in a certain number of periods. The decisions will not be isolated, and they will consider the past. The application areas are diverse and increasing due to uncertain times. This work proposes a conceptualization of dynamic sectorization and applies it to a distribution problem with variable demand. Furthermore, Genetic Algorithm is used to obtain solutions for the problem since it has several criteria; Analytical Hierarchy Process is used for the weighting procedure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Este trabalho analisa o processo de servitização de diferentes fornecedores na cadeia produtiva do café no Brasil. Foi realizada uma revisão da literatura sobre sistemas produto-serviço (SPS) para estabelecer uma estrutura para identificar a tipologia de serviços no setor agrícola. Os resultados destacaram que a prestação de serviços "menos avançados" não é uma condição necessária para que a empresa ofereça serviços "mais avançados". Entretanto, as características das propriedades rurais parecem afetar o número de serviços associados aos fornecedores de máquinas. Os resultados ajudam os gerentes desse setor a identificar as ofertas de serviços e ampliam a discussão sobre servitização, ao abranger um setor pouco explorado.

Abstract
This work addresses a variant of the job shop scheduling problem in which jobs need to be transported to the machines processing their operations by a limited number of vehicles. Given that vehicles must deliver the jobs to the machines for processing and that machines need to finish processing the jobs before they can be transported, machine scheduling and vehicle scheduling are intertwined. A coordi-nated approach that solves these interrelated problems simultaneously improves the overall performance of the manufacturing system. In the current competitive business environment, and integrated approach is imperative as it boosts cost savings and on-time deliveries. Hence, the job shop scheduling problem with transport resources (JSPT) requires scheduling production operations and transport tasks simultane-ously. The JSPT is studied considering the minimization of two alternative performance metrics, namely: makespan and exit time. Optimal solutions are found by a mixed integer linear programming (MILP) model. However, since integrated production and transportation scheduling is very complex, the MILP model can only handle small-sized problem instances. To find good quality solutions in reasonable com-putation times, we propose a hybrid particle swarm optimization and simulated annealing algorithm (PSOSA). Furthermore, we derive a fast lower bounding procedure that can be used to evaluate the perfor-mance of the heuristic solutions for larger instances. Extensive computational experiments are conducted on 73 benchmark instances, for each of the two performance metrics, to assess the efficacy and efficiency of the proposed PSOSA algorithm. These experiments show that the PSOSA outperforms state-of-the-art solution approaches and is very robust.(c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ )

Abstract
Fire has major impacts on forest ecosystems, with heightened relevance in a Mediterranean country such as Portugal, which within Europe features the highest number of wildfires and the second larger burnt area. After each significant wildfire, the Portuguese Institute for Nature Conservation and Forests (ICNF) assesses the main environmental impacts and proposes emergency stabilisation measures following specific regulations. This study seeks to improve such assessments by using a data triangulation approach to characterise the impacts of wildfires on ecosystem services in the country. First, a systematic literature review is performed to identify the scientific studies that address the issue. Next, a document analysis of all the emergency stabilisation reports and technical reports available on ICNF's website is performed. Finally, a survey of experts' perceptions on the topic completes the analysis. The Economics of Ecosystems and Biodiversity definitions of ecosystem services were employed to compare the different findings. The results indicate that the experts perceive wildfires to significantly impact all ecosystem services, even though the literature has so far only focused on 12 of them, and ICNF has so far only focused on 7 in its reports. The potential underlying motives are discussed. In particular, some important impacts identified in the literature, as is the case of Climate regulation, a topic of the highest priority in the European environmental agenda, have not so far been a topic of focus in ICNF's reports, which suggests relevant opportunities for enhancing its reporting process in the future.

Abstract
In the last few years, the industrial, scientific, and technological fields have been subject to a revolutionary process of digitalization and automation called Industry 4.0. Its implementation has been successful mainly in the economic field of sustainability, while the environmental field has been gaining more attention from researchers recently. However, the social scope of Industry 4.0 is still somewhat neglected by researchers and organizations. This research aimed to study Industry 4.0 and sustainability themes using data science, by incorporating open data and open-source tools to achieve sustainable Industry 4.0. To that end, a quantitative analysis based on open data was developed using open-source software in order to study Industry 4.0 and sustainability trends. The main results show that manufacturing is a relevant value-added activity in the worldwide economy; that, foreseeing the importance of Industry 4.0, countries in America, Asia, Europe, and Oceania are incorporating technological principles of Industry 4.0 in their cities, creating so-called smart cities; and that the industries that invest most in technology are computers and electronics, pharmaceuticals, transport equipment, and IT (information technology) services. Furthermore, the G7 countries have a prevalent positive trend for the migration of technological and social skills toward sustainability, as it relates to the social pillar, and to Industry 4.0. Finally, on the global scale, a positive correlation between data openness and happiness was found.