Abstract
This chapter aims to contribute to the understanding of how artificial intelligence (AI) technologies can promote increased business revenues, cost reductions, and enhanced customer experience, as well as society's well-being in a sustainable way. However, these AI benefits also come with risks and challenges concerning organizations, the environment, customers, and society, which need further investigation. This chapter also examines and discusses how AI can either enable or inhibit the delivery of the goals recognized in the UN 2030 Agenda for Sustainable Business Models Development. In this chapter, the authors conduct a bibliometric review of the emerging literature on artificial intelligence (AI) technolo¬gies implications on sustainable business models (SBM), in the perspective of Sustainable Development Goals (SDGs) and investigate research spanning the areas of AI, and SDGs within the economic group. The authors examine an effective sample of 69 publications from 49 different journals, 225 different institutions, and 47 different countries. On the basis of the bibliometric analysis, this study selected the most significant published sources and examined the changes that have occurred in the conceptual framework of AI and SBM in light of SDGs research. This chapter makes some significant contributions to the literature by presenting a detailed bibliometric analysis of the research on the impacts of AI on SBM, enhancing the understanding of the knowledge structure of this research topic and helping to identify key knowledge gaps and future challenges. © 2024, IGI Global. All rights reserved.

Abstract
Food waste poses a significant challenge to the sustainability of traditional food production systems, prompting global efforts to combat waste throughout the supply chain. Sustainable food production emerges as a critical concept in response to increasing concerns about environmental degradation and the need for alternative protein sources driven by global population growth. In this context, insect production offers a promising solution by converting low-value organic waste into nutrient-rich products, thus reducing waste and environmental impact. This paper addresses the urgent need for sustainable and efficient food production systems by introducing a facility location problem within the network design of insect production. The objective is to develop methods to scale insect-derived product production by identifying optimal locations with the best conditions for establishing insect production facilities. Emphasis is placed on connecting suppliers with production, highlighting the critical role suppliers and their by-products play in promoting a sustainable industry. Instances were generated to assess model performance, including supplier and facility locations, by-product availability and selection. Varying by-product availability yielded different optimization outcomes. The experiments results offered insights into the model's behavior under different conditions. The results shown that varying the composition of substrate had a major implication on the augment of costs compared to varying the by-product availability.

Abstract
Pickup and delivery problems are frequently encountered problems in transport companies. This paper presents a variant of the homogeneous vehicle, single-to-single Pickup and Delivery Problem with Time Windows, where several vehicles must fulfill transport requests from pickup nodes to delivery nodes, called missions, with associated service level agreements (SLA). A mathematical programming model is proposed to tackle this variant, focused on optimizing the allocation and sequencing of missions to be executed by autonomous vehicles. Numerical experiments are performed comparing instances with missions with long and short SLAs. The results show that the model takes longer to find the optimal solution when the missions have short SLAs and increased difficulty in meeting them if the number of vehicles is limited.

Abstract
Lot-sizing and scheduling in a job shop environment is a fundamental problem that appears in many industrial settings. The problem is very complex, and solutions are often needed fast. Although many solution methods have been proposed, with increasingly better results, their computational times are not suitable for decision-makers who want solutions instantly. Therefore, we propose a novel greedy heuristic to efficiently generate production plans and schedules of good quality. The main innovation of our approach represents the incorporation of a simulation-based technique, which directly generates schedules while simultaneously determining lot sizes. By utilising priority rules, this unique feature enables us to address the complexity of job shop scheduling environments and ensures the feasibility of the resulting schedules. Using a selection of well-known rules from the literature, experiments on a variety of shop configurations and complexities showed that the proposed heuristic is able to obtain solutions with an average gap to Cplex of 4.12%. To further improve the proposed heuristic, a cooperative coevolutionary genetic programming-based hyper-heuristic has been developed. The average gap to Cplex was reduced up to 1.92%. These solutions are generated in a small fraction of a second, regardless of the size of the instance.

Abstract
The main objective of this study is to detect signs of under-invoicing by applying Benford's law to the Portuguese restaurant sector during the COVID-19 pandemic, in the context of government support policies. Between 2020 and 2021, the State adopted several measures to provide additional support to companies that have seen a significant decrease in their activity, namely, a reduction of at least 25% in turnover. A literature review was carried out focusing on the impact of the COVID-19 pandemic on the companies under analysis, the support measures adopted by the State and, finally, a survey of the theoretical component relating to the application of Benford's law in accounting. The data were collected from the Iberian Balance Sheet Analysis System database for 2019, 2020, and 2021. After analysing the data, significant deviations are observed in several digits, practically for all the compliance tests, both in the analysis of the first digit test and in the analysis of the first two digits test. The results therefore show signs of under-invoicing in 2020 by the analysed companies, which suffered, on average, a 79% reduction in turnover.

Abstract
Background: With the emergence of eHealth and mHealth, the use of mental health apps has increased significantly as an accessible and convenient approach as an adjunct to promoting well-being and mental health. There are several apps available that can assist with mental health monitoring and management, each with specific features to meet different needs. The intersection of mental health and cyber technology presents a number of critical legal and ethical issues. As mental health monitoring apps and devices become more integrated into clinical practice, cybersecurity takes on paramount importance. Objective: To address the ethical and legal aspects of health cybersecurity related to applications in mental health monitoring and management. Methods: We carried out a thematic synthesis of the best scientific evidence. Results: These tools have the potential to significantly improve access to and quality of care for users with mental health conditions, but they also raise substantial concerns about privacy and informed consent.  Cybersecurity in mental health is not only a matter of technology, but also of human rights. The protection of sensitive mental health information is critical, and legal and ethical measures to safeguard this information must be implemented in a robust and transparent manner. Conclusion: the use of information technologies and mobile devices is now part of the clinical reality and its future perspectives. It is important to mention that while these apps can be helpful for self-care and mental well-being management, they are not a substitute for the advice and support of a qualified mental health professional (psychologist or psychiatrist). As we move into the digital age, it is imperative that mental health monitoring and management apps are developed and used responsibly, ensuring the safety, dignity, and well-being of users.