Maria Aryblia

Extensive small-ruminant grazing sustains food production on the Mediterranean land with few alternative uses, yet supervision is intermittent and welfare oversight weak. Digital monitoring is expected to close that gap, but detection alone does not produce intervention. In remote rangelands the link is unreliable, so an inference may reach the farmer late, degraded or not at all, and an alert arriving after the animal has moved is not a weaker alert but a different decision. This study develops a human-in-the-loop decision framework in which the delivery state of the link becomes a decision variable rather than a transport detail, coupling technology, farmer behaviour and governance. Constructed through design science research and structured analysis of an EU-funded project’s specifications and evaluation plans, it comprises a seven-layer architecture, a decision-episode schema, a connectivity-aware alert lifecycle, a decision-provenance matrix, and an evidence-maturity classification constraining what may be claimed. Five decision classes from a Cretan sheep and goat pilot instantiate it. After applying it, specification inconsistencies invisible to component-level review surfaced, among which is an alert payload lacking the coordinates, confidence and severity that its own indicators require. The framework is an instantiated specification, not a validated intervention: no detection, delivery, acknowledgement, usability or sustainability outcome is measured.

Energy-intensive industries deploying hybrid renewable energy systems require performance monitoring frameworks that evolve with phased system implementation. This paper introduces the performance and sustainability framework, a simulation-grounded evolution of the sustainability balanced scorecard for longitudinal assessment of renewable energy infrastructure. The framework requires that key performance indicators derive from validated techno-economic simulations, that assessment is repeated at temporal checkpoints corresponding to physical system changes, and that each balanced scorecard perspective includes at least one environmental or circular-economy indicator. The framework is demonstrated in a cheese manufacturing facility in Crete, Greece, where a 38 kW cheese whey biomass generator, 72.2 kW photovoltaic system, and 10 kW wind turbine are deployed over five years. Annual HOMER Pro re-simulations are combined with weighted SWOT scoring to track technical, economic, environmental, and organisational performance. By Year 5, the system achieves an 88.7% electrical renewable fraction, 60.0% gross-operational CO₂-eq reduction, 0.1148 EUR/kWh levelised cost of energy, and 22.3% internal rate of return. The longitudinal trajectory also reveals declining delivered thermal renewable contribution and cheese whey utilisation, exposing operational trade-offs that single-point scorecard assessments would miss. Applicability of the PSF to community-scale governance under ISO 37101:2016 and to renewable energy communities under Directive (EU) 2018/2001 is examined exclusively as a conceptual scaling framework for future research. The present empirical demonstration is restricted to a single-facility case study, and no community-level stakeholder data are collected or analysed.

Digital technologies nowadays provide essential support for companies, making them a priority for businesses and a prominent area of study for researchers. In response to the increasing emphasis on sustainability and resilience, new information systems are developing to meet evolving business needs, namely circular and resilient information systems (CRISs). These systems integrate with traditional ones to optimise key performance indicators (KPIs) related to circularity and resiliency. Despite extensive methodologies for evaluating traditional information systems, systems designed for circularity and resiliency need to be assessed in parallel and in depth. Existing evaluations focus on efficiency and user satisfaction but often neglect the unique demands of circularity and resiliency. This study introduces a novel evaluation methodology for CRISs. Through a case study of an innovative system and the established literature, we address real-life needs and challenges in manufacturing. In particular, the system serves the needs of three distinct case studies: Carbon Fibre-Reinforced Polymer (CFRP) waste utilisation in drone manufacturing, recovery of magnets from Waste Electrical and Electronic Equipment (WEEE), and the repurposing of citrus processing waste into juice by-products. Our methodology is built on the 5W1H method to make our approach context-specific and aligned with each case’s unique requirements, making it also replicable for other industries. Our findings offer insights and a tool for practitioners and researchers to evaluate CRIS performance. The research highlights the importance of a two-fold evaluation approach for CRISs, evaluating both pilot-specific KPIs and the system’s technical performance. Policy implications suggest the need for regulatory frameworks and incentives to support the adoption, as well as evaluation, of CRISs and promote sustainable and resilient industrial practices.

The pandemic has created opportunities which researchers, developers and planners should analyze, capitalize and adapt. How much COVID-19 restrictions affected air quality in Mediterranean tourism destinations? Was there a rebound effect during post-lockdown period? Which was the behavioral change concerning the urban mobility? Noteworthy changes in the air pollutants’ mean concentration on the ground-level have been experienced. The air quality was measured on the ground-level and reviewed concerning CO₂, CO, NO_x, and CH4 under various climate conditions. 5-min air quality and traffic load data were processed from different city spots in a Mediterranean tourism destination. The study examined the impact of State strategies on tackling the COVID-19 spread on both traffic load and air quality employing statistical methods. The obtained results show the lockdown period’s impact on improving air quality. Although there was a minor decrease, the mean CO₂ levels were not significantly affected during the lockdown period. The mean NOx levels during the lockdown period were decreased by 32% compared to the same period in 2019; there is also a 10% decrease in the mean levels of NOx compared to the period before the lockdown. This study related four primary air pollutants (CO₂, CO, NOx, and CH₄), the total number of vehicles, and the total number of tourists. A rebound effect proved during the post lockdown period. The results and the methodology of this research work are replicable as confirmed by other studies for different cities. Abbreviations: Analysis of Variance, ANOVA, Coronavirus Disease 2019, COVID-19; Green House Gases, GHGs; European Commission, EC; European Union, EU; National Aeronautics and Space Administration, NASA.