Abstract
Business Continuity Management (BCM) is critical for organizations to mitigate disruptions and maintain operations, yet many struggle with fragmented and non-standardized self-assessment tools. Existing frameworks often lack holistic integration, focusing narrowly on isolated components like cyber resilience or risk management, which limits their ability to evaluate BCM maturity comprehensively. This research addresses this gap by proposing a structured Self-Assessment System designed to unify BCM components into an adaptable, standards-aligned methodology. Grounded in Design Science Research, the system integrates a BCM Model comprising eight components and 118 activities, each evaluated through weighted questions to quantify organizational preparedness. The methodology enables organizations to conduct rapid as-is assessments using a 0-100 scoring mechanism with visual indicators (red/yellow/green), benchmark progress over time and against peers, and align with international standards (e.g., ISO 22301, ITIL) while accommodating unique organizational constraints. Demonstrated via focus groups and semi-structured interviews with 10 organizations, the system proved effective in enhancing top management commitment, prioritizing resource allocation, and streamlining BCM implementation-particularly for SMEs with limited resources. Key contributions include a reusable self-assessment tool adaptable to any BCM framework, empirical validation of its utility in identifying weaknesses and guiding continuous improvement, and a pathway from initial assessment to advanced measurement via the Plan-Do-Check-Act cycle. By bridging the gap between theoretical standards and practical application, this research offers a scalable solution for organizations to systematically evaluate and improve BCM resilience.

Abstract
[No abstract available]

Abstract
This paper fits in the theory of international agreements by studying the success of stable coalitions of agents seeking the preservation of a public good. Extending Baliga and Maskin, we consider a model of N homogeneous agents with quasi-linear utilities of the form u(j) (r(j); r) = r(alpha) - r(j), where r is the aggregate contribution and the exponent alpha is the elasticity of the gross utility. When the value of the elasticity alpha increases in its natural range (0, 1), we prove the following five main results in the formation of stable coalitions: (i) the gap of cooperation, characterized as the ratio of the welfare of the grand coalition to the welfare of the competitive singleton coalition grows to infinity, which we interpret as a measure of the urge or need to save the public good; (ii) the size of stable coalitions increases from 1 up to N; (iii) the ratio of the welfare of stable coalitions to the welfare of the competitive singleton coalition grows to infinity; (iv) the ratio of the welfare of stable coalitions to the welfare of the grand coalition decreases (a lot), up to when the number of members of the stable coalition is approximately N/e and after that it increases (a lot); and (v) the growth of stable coalitions occurs with a much greater loss of the coalition members when compared with free-riders. Result (v) has two major drawbacks: (a) A priori, it is difficult to convince agents to be members of the stable coalition and (b) together with results (i) and (iv), it explains and leads to the pessimistic Barrett's paradox of cooperation, even in a case not much considered in the literature: The ratio of the welfare of the stable coalitions against the welfare of the grand coalition is small, even in the extreme case where there are few (or a single) free-riders and the gap of cooperation is large. Optimistically, result (iii) shows that stable coalitions do much better than the competitive singleton coalition. Furthermore, result (ii) proves that the paradox of cooperation is resolved for larger values of.. so that the grand coalition is stabilized.

Abstract
In the era of Industry 4.0, fault tolerance is essential for maintaining the robustness and resilience of industrial systems facing unforeseen or undesirable disturbances. Current methodologies for fault tolerance stages namely, detection, diagnosis, and recovery, do not correspond with the accelerated technological evolution pace over the past two decades. Driven by the advent of digital technologies such as Internet of Things, cloud and edge computing, and artificial intelligence, associated with enhanced computational processing and communication capabilities, local or monolithic centralized fault tolerance methodologies are out of sync with contemporary and future systems. Consequently, these methodologies are limited in achieving the maximum benefits enabled by the integration of these technologies, such as accuracy and performance improvements. Accordingly, in this paper, a collaborative fault tolerance methodology for cyber-physical systems, named Collaborative Fault * (CF*), is proposed. The proposed methodology takes advantage of the inherent data analysis and communication capabilities of cyber-physical components. The proposed methodology is based on multi-agent system principles, where key components are self-fault tolerant, and adopts collaborative and distributed intelligence behavior when necessary to improve its fault tolerance capabilities. Experiments were conducted focusing on the fault detection stage for temperature and humidity sensors in warehouse racks. The experimental results confirmed the accuracy and performance improvements under CF* compared with the local methodology and competitiveness when compared with a centralized approach.

Abstract
[No abstract available]

Abstract
This paper presents a full-year hourly district emobility model and its integration into a Positive Energy District simulation and assessment model including building operation, use and embodied energy and emissions. The aim of this work is to model the operation and energy flexibility potential of an EV fleet in a district through mono- and bi-directional charging and enable its assessment in terms of self-utilization of local and volatile regional RES surpluses. Results of example residential, office, school and supermarket use cases show an increase in self-utilization of local PV of up to 30% due to EV inclusion, even if PV installation size exceeds legal building code requirements by a factor of two to four. Bi-Directional charging can cut annual grid electricity by up to 30% but require an increase in battery full equivalent cycles of 20%. © 2025 Elsevier B.V., All rights reserved.