Abstract
Sectorization is the process of grouping a set of previously defined basic units (points or small areas) into a fixed number of sectors. Sectorization is also known in the literature as districting or territory design, and is usually performed to optimize one or more criteria regarding the geographic characteristics of the territory and the planning purposes of sectors. The most common criteria are equilibrium, compactness and contiguity, which can be measured in many ways. Sectorization is similar to clustering but with a different motivation. Both aggregate smaller units into groups. But, while clustering strives for inner similarity of data, sectorization aims at outer homogeneity [1]. In clustering, groups should be very different from each other, and similar points are classified in the same cluster. In sectorization, groups should be very similar to each other, and therefore very different points can be grouped in the same sector. We classify sectorization problems into four types: basic sectorization, sectorization with service centers, resectorization, and dynamic sectorization. A Decision Support System for Sectorization, D3S, is being developed to deal with these four types of problems. Multi-objective genetic algorithms were implemented in D3S using Python, and a user-friendly web interface was developed using Django. Several applications can be solved with D3S, such as political districting, sales territory design, delivery service zones, and assignment of fire stations and health services to the population.

Abstract
The process of migrating from a monolithic to a microservices based architecture is currently described as a form of modernizing applications. The core principles of microservices, which mostly reside in achieving loose coupling between the services, highly depend on the implementation approaches used. Being microservices a complete change of paradigm that contrasts with the traditional way of developing software, the current lack of established principles often results in implementations that conflict with its alleged benefits. Given its distributed nature, performance is affected, but specific implementation patterns can further impact it. This paper aims to address the impact that microservices-based solutions, featuring different implementation patterns, have on performance and how it compares with monolithic applications. To do so, benchmarks are conducted over one application developed following a traditional monolithic approach, and two equivalent microservices-based implementations featuring distinct inter-service communication mechanisms and data management methodologies.

Abstract

Abstract
Electric mobility with all of its advantages has gained momentum during the last decade with increasing utilization by many sectors of the society. However, professional fleets' operators (e.g. taxis) are still conservative in switching to this new mobility paradigm in many parts of the world. In this paper, we empirically evaluate whether electric vehicles together with conventional charging stations could replace current internal combustion engine vehicles for taxi mobility and study the implications for the taxi business. To perform this study, we resort to a detailed mobility dataset of a taxi fleet collected in a mid-sized European city. The results provide a first indication that such transition towards electric mobility is feasible for the vast majority of the vehicles of the fleet and that simple AC chargers at taxi stands could suffice to provide the necessary range autonomy.

Abstract
This research establishes the relationship between the digital channels that organizations use to communicate with their audience and the stages of the consumer buying decision process in online stores. Researchers have not treated this relationship in much detail and little-known empirical research has focused on exploring relationships between the two subjects. Establishing this relationship is of crucial importance for organizations and consumers, as it ensures organizations use the digital channels that consumers want. A literature review of digital channels and consumer behavior models was performed, which allowed us to define which are the digital channels and to identify the different models of consumer behavior appropriate for the digital age. A quantitative methodology was used, supported on a questionnaire that allowed us to find out which digital channels are the most appropriate for each stage of the buying decision process. The results show that consumers use more than one digital channel at each stage of the buying decision process and for each stage, a set of digital channels is identifiable that is most preferred. In light of the above, those who are responsible for defining the digital marketing strategy know what types of content they should produce for each digital channel, allowing them to guarantee efficiency in the use of resources while ensuring that consumers get what they want.

Abstract
The Brazilian oil industry is facing a period of significant techno-economic challenges to meet the increase in reserves and production in ultra-deep waters. The subsea production system is an essential technological frontier to ensure the technical and economic viability of oil fields. Thus, the use of digital technologies fits in with these goals and already shows promising results, which stimulate companies in the development of digitalization. For this, the main aim of this chapter is to investigate the role of digital transformation to the subsea productive system of the Brazilian oil industry. By using the analytical and theoretical framework of innovation system, the author explores the relevance, capacity, and strategy developed for the use of digital transformation into subsea production system activities. It was possible to identify the critical features of techno-economic development and conclude that despite the existing capacity, coordination, interactions, and funding are issues to be promoted and improved.