Abstract
Firms have available many forms of collaboration, including cooperatives or joint ventures, in this way leveraging their market power. Customers, however, are atomic agents with few mechanisms for collaborating, leading to an unbalanced buyer-supplier relationship and economic surpluses that shift to producers. Some group buying websites helped alleviate the problem by offering bulk discounts, but more advancements can be made with the emergence of technologies, such as the blockchain. In this article, we propose a customer-push e-marketplace built on top of Ethereum, where customers can aggregate their proposals, and suppliers try to outcompete each other in reverse auction bids to fulfil the order. Furthermore, smart contracts make it possible to automate many operational activities, such as payment escrows/release upon delivery confirmation, increasing the efficiency along the supply chain. The implementation of this network is expected to improve market efficiency by reducing transaction costs, time delays, and information asymmetry. Furthermore, concepts such as increased bargaining power and economies of scale, and their effects in buyer-supplier relationships, are also explored.

Abstract
Sectorization problems have significant challenges arising from the many objectives that must be optimised simultaneously. Several methods exist to deal with these many-objective optimisation problems, but each has its limitations. This paper analyses an application of Preference Inspired Co-Evolutionary Algorithms, with goal vectors (PICEA-g) to sectorization problems. The method is tested on instances of different size difficulty levels and various configurations for mutation rate and population number. The main purpose is to find the best configuration for PICEA-g to solve sectorization problems. Performance metrics are used to evaluate these configurations regarding the solutions’ spread, convergence, and diversity in the solution space. Several test trials showed that big and medium-sized instances perform better with low mutation rates and large population sizes. The opposite is valid for the small size instances. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The CrossLog project aims to investigate, study, develop and implement an automated and collaborative cross-docking system (aligned with Industry 4.0) capable of moving and managing the flow of products within the warehouse in the fastest and safest way. In CrossLog, the ability to generate intelligent three-dimensional packing patterns is essential to ensure the flexibility and productivity of the cross-docking system while ensuring the stability of the palletised load. In this work, a heuristic solution approach is proposed to generate efficient pallet packing patterns that simultaneously minimise the total number of pallets required and address the balance of weight and volume between pallets. Computational experiments with data from a real company demonstrate the quality of the proposed solution approach.

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
The increasing need to innovate to keep or create competitive advantage and the difficulty in retaining resources that enable innovation, force companies to look for partnerships. Partnering with the appropriate and leading R&D (Research and Development) institutions is critical to be able to innovate. One of the first challenges that emerges when building a collaboration is the selection of organizations to form the consortium. Technology foresight might be an interesting process to start building such partnership, as it helps identify technology opportunities and the entities that lead technology development. This paper uses case research to study the creation and use of a technology foresight process to build new R&D collaborations, while identifying of technology development opportunities. Findings from the case study led to the identification of how the technology foresight process was used to create a new R&D collaboration in the company under study, while identifying what motivated such collaboration and how it was managed. Furthermore, important characteristics of the team responsible for that process and of the process management are highlighted.

Abstract
Technological evolution has continuously driven the development of industries and consequently of society. The fourth industrial revolution consists in the combination of a set of physical and digital technologies that has been changing systems' operations within industries. The pharmaceutical industry has a considerable impact on well-being and has been strongly challenged with this new reality, not only by those that are transversal to all industries but also due to the fact that it is a highly regulated sector, which creates additional barriers for industry 4.0 (I4.0) initiative's implementation. However, it is due to the fact that this revolution provides high growth opportunities to the industry, and consequently for the improvement of population's quality of life, that this topic has been subject to so much research at a global level. This study's main purpose is to understand the impact of I4.0 paradigm implementation in the pharmaceutical industry (mainly in the production area), to analyze the technological readiness of Portuguese pharmaceutical companies to implement I4.0 technologies and to understand the role of the I4.0 paradigm to fight the pandemic situation caused by the COVID-19. To achieve this purpose, an exploratory multiple-case study based on semi-structured interviews was conducted in two Portuguese pharmaceutical companies. It is expected that the results of this work lead to recommendations that help the Portuguese pharmaceutical industry to be better prepared to face the challenges that are coming with this revolution.