Abstract
This paper focuses on the identification of collaborative strategies and practices adopted by companies of the fashion industry in the management of customized offerings (both products and services) along their supply chain (SC). A multiple case study approach is applied and four companies (both medium and large) were interviewed. The cross-case analysis enabled mapping the cases following two dimensions: type of market asking for the customization (B2B vs. B2C) and scope of customization (products vs. services). The analysis highlights the practices and processes related to the customization, the enabling technologies adopted, and the actors involved by a focal company in the collaboration (both in upstream and downstream networks) to offer the product or service that meet customer needs.

Abstract
The innovation and digitalization of the industry is happening triggered by the Industry 4.0 and Industrial Internet-of-Things (IIoT) paradigm. Enterprises are following the trend of digital transformation and are fostering projects that enable a higher comprehension of I4.0 solutions to answer their needs. The IIoT platforms have been a central component for industrial systems architectures to enable interoperability and data flow within industrial settings. However, the digitalization process has all sorts of shortcomings associated to them, and in the SME's this transformation has been slow to none. In this work we showcase a proof of concept of an IIoT platform that intends to simplify the digitalization process in SME's, based on the Portuguese footwear industry cluster.

Abstract
In the current industrial revolution, additive manufacturing (AM) embodies a promising technology that can enhance the effectiveness, adaptability, and competitiveness of supply chains (SCs). Moreover, it facilitates the development of distributed SCs, thereby enhancing product availability, inventory levels, and lead time. However, the wide adoption of AM in industrial SCs creates various challenges, leading to new difficulties for SC design. In this context, this article proposes a new design approach to AM SCs using optimization methods. More specifically, the proposed approach, comprising the p-median and mixed-integer linear programming models, considers the decision of deploying productive resources (3-D printers) in specific locations of generic spare part SCs. The approach was evaluated in a real-world use case of an elevator maintenance service provider. The obtained results demonstrated the promising capabilities of the proposed design approach in managing the challenges arising from the forthcoming widespread use of 3-D printers in manufacturing SCs.

Abstract
We discuss the concept of FPGA-unfriendliness, the property of certain algorithms, programs, or domains which may limit their applicability to FPGAs. Specifically, we look at graph analysis, which has recently seen increased interest in combination with High-Level Synthesis, but has yet to find great success compared to established acceleration mechanisms. To this end, we make use of Xilinx's Vitis Graph Library to implement Single-Source Shortest Paths (SSSP) and PageRank (PR), and present a custom kernel written from the ground up for Distinctiveness Centrality (DC, a novel graph centrality measure). We use public datasets to test these implementations, and analyse power consumption and execution time. Our comparisons against published data for GPU and CPU execution show FPGA slowdowns in execution time between around 18.5x and 328x for SSSP, and around 1.8x and 195x for PR, respectively. In some instances, we obtained FPGA speedups versus CPU of up to 2.5x for PR. Regarding DC, results show speedups from 0.1x to 3.5x, and energy efficiency increases from 0.8x to 6x. Lastly, we provide some insights regarding the applicability of FPGAs in FPGA-unfriendly domains, and comment on the future as FPGA and HLS technology advances.

Abstract
Continuous Integration and Deployment in the robotics domain is still underutilized when compared to other fields of software development. Also, conventional testing techniques used in CI/CD pipelines are usually not enough to fully test a robotic project in its integrity. In this paper, an analysis is made regarding the usage of CI/CD techniques in robotic related repositories to both verify the veracity of these statements, as well as finding their causes. Additionally, a novel approach in the scope of CI/CD is explored, making use of cloud-based technologies to add additional automated simulation tests to the pipeline and integrate them with ease in the development of robotic software. Finally, the proposed approach is showcased in an industrial application.

Abstract
The application of big data analytics in all fields of research is a critical driver for the competitiveness of all countries in the modern world. Currently, governments and industry generate large amounts of data driven by record keeping, compliance, regulations, data privacy, and dynamic requirements, and thus there is a need to create better mechanisms to analyse data, and hence support organizational development, as well as providing aid to policymakers’ decision-making processes. In this context, there are emerging disruptive opportunities because of Big Data: new business models, and vertical industry segments will emerge through shared relationships with all the stakeholders, and big data analytics is a major asset to support these dynamic relationships. This book was developed with the objective of analysing some of those challenges while at the same time providing a perspective of the potential of big data analytics, and the importance that analytics have for managers and for policymakers, to help define new strategies and new public policies, respectively. The book is focused on different sectors of activity (i.e. the Health sector, Public Administration, the Education sector, among others), and on different economic dimensions (i.e. Entrepreneurship, and Innovation) and links big data analytics to different fields of research, such as artificial intelligence and other emergent technologies; which are challenging organisations, governments, and societies, with the need to face the new imperative of being prepared for the very uncertain and tremendously complex future - in which big data analytics will play a very decisive and active role.