Search Results (1,915)

Dual Carbon Goals are driving transformation in China’s power system, where increased renewable energy penetration is accompanied by heightened fluctuations on the generation and load sides. Energy storage and microgrid coordination have emerged as key solutions. However, existing research faces the challenge of balancing microgrid operations, energy storage services, and the alignment of user demand with stakeholder interests. This paper establishes a tripartite collaborative optimization framework to balance multi-stakeholder interests and enhance system efficiency, assuming fixed energy storage capacity. Centering on a principal-agent game between microgrid operators and consumer aggregators, energy storage service providers are integrated into this dynamic. Microgrid operators set 24-h electricity and heat pricing while adhering to tariff constraints, prompting consumer aggregators to adjust energy consumption and storage strategies accordingly. The KKT conditional method is employed to solve the model, deriving optimal user energy consumption strategies at the lower level while solving marginal pricing equilibrium relationships at the upper level, balancing accuracy with information privacy. The creative contribution of this article lies in the first construction of a tripartite collaborative optimization architecture in which energy storage service providers are embedded in a game of ownership and subordination. It proposes a dynamic coupling mechanism between pricing power, energy consumption decision-making, and energy storage configuration under fixed energy storage capacity constraints, achieving a balance of interests among multiple parties. By building a case study using MATLAB (R2022b), we compare operation costs, benefits, and absorption rates across different scenarios to validate the framework’s effectiveness and provide a reference for engineering applications. Full article

In the context of large-scale renewable energy integration driven by China’s dual-carbon goals, and under distribution network scenarios with continuously increasing shares of wind and photovoltaic generation, this paper proposes a source–grid–load–storage coordinated planning method embedded with a multi-agent game mechanism. First, the interest transmission pathways among distributed generation operators (DGOs), distribution network operators (DNOs), energy storage operators (ESOs), and electricity users are mapped, based on which a profit model is established for each stakeholder. Building on this, a coordinated planning framework for active distribution networks (DN) is developed under the assumption of bounded rationality. Through an evolutionary-game process among DGOs, DNOs, and ESOs, and in combination with user-side demand response, the model jointly determines the optimal network reinforcement scheme as well as the optimal allocation of distributed generation (DG) and energy storage system (ESS) resources. Case studies are then conducted to verify the feasibility and effectiveness of the proposed method. The results demonstrate that the approach enables coordinated planning of DN, DG, and ESS, effectively guides users to participate in demand response, and improves both planning economy and renewable energy accommodation. Moreover, by explicitly capturing the trade-offs among multiple stakeholders through evolutionary-game interactions, the planning outcomes align better with real-world operational characteristics. Full article

This study examines the impact of tax avoidance practices on investment efficiency in Egypt, with particular emphasis on the moderating role of earnings management by exploring whether these tactics reflect managerial opportunism or serve as a mechanism to ease financial constraints. We employ panel data regression to analyze a sample of 58 non-financial firms listed on the Egyptian Exchange (EGX) over the period 2017–2024, yielding 464 firm-year observations. Data are collected from official corporate websites, EGX, and Egypt for Information Dissemination (EGID). Grounded in agency theory, signaling theory, and pecking order theory, this study reveals how conflicts of interest and information asymmetry between managers and stakeholders lead to managerial opportunism. The findings show that tax avoidance undermines the investment efficiency in the Egyptian market. Earnings manipulation further intensified this effect due to the financial statements’ opacity. A closer examination reveals that earnings management exacerbates overinvestment by masking managerial decisions. Conversely, for financially constrained firms with a tendency to underinvest, tax avoidance and earnings management may contribute to improved efficiency by generating internal liquidity and alleviating external financing constraints. These results provide valuable insights for regulators, highlighting that policy should be directed against managerial opportunism and improving transparency, instead of focusing solely on curbing tax avoidance. From an investor perspective, they should closely monitor and understand the tax-planning strategies to ensure they enhance the firm’s value. Full article

Digital technologies have become increasingly crucial during and, after the COVID-19 pandemic, have sparked significant scientific interest around their impact on sustainable well-being. Despite extensive research, conclusive evidence on whether digital technologies enhance or undermine sustainable well-being remains elusive. Saudi Arabia has made significant progress in its technological infrastructure, but comprehending the implications of this progress still poses a challenge. Drawing on the prior literature and grounded in the theoretical perspective of the Capability Approach, this study proposes five dimensions of digital inclusion (accessibility, usability, digital skills, affordability, and connectivity) and examines their collective influence on students’ sustainable well-being, specifically happiness and life satisfaction. This study employs a cross-sectional design, with data collected from 238 university students in Saudi Arabia using convenience sampling. Ten hypotheses were tested using partial least squares structural equation modeling in SmartPLS-4. This study supports the conceptualization of digital inclusion as a multidimensional construct comprising five key dimensions. The results indicate that affordability, usability, connectivity, and digital skills have a substantial impact on happiness, whereas accessibility, usability, connectivity, and digital skills have a considerable effect on life satisfaction. Nonetheless, the correlations between accessibility and happiness, as well as between affordability and life satisfaction, were not found to be supported. This implies that these dimensions might have different effects on the affective and cognitive aspects of sustainable well-being. These results suggest that digital inclusion may play a role in shaping individuals’ interactions with technology and their perceived sustainable well-being. This study proposes and evaluates a strategic framework that may guide efforts to promote digital inclusion and support sustainable well-being among university students. It provides valuable insights for policymakers, educational institutions, and industry stakeholders seeking to enhance digital access and capabilities. The findings highlight the potential value of developing strategies that address students’ digital needs as part of a holistic approach to sustainable well-being. The findings also highlight the importance of viewing digital inclusion as an interconnected framework, rather than as a set of discrete, unrelated factors. By demonstrating how digital inclusion promotes sustainable well-being, this study contributes to the broader sustainability agenda by highlighting digital equity as an essential component of socially sustainable development in the Saudi context. Full article

Real estate constitutes a core segment of the global building and built environment industry, absorbing substantial volumes of international institutional investment capital. Unlisted real estate has featured prominently in the portfolios of global institutional investors. In recent years, global real estate markets have been significantly impacted by rising interest rates, posing a real and significant risk to investors. In response, more tactical asset allocation strategies have been adopted. Investment fund managers and institutional investors seek to rebalance through sector selections and sectoral portfolio diversification when tactical asset allocation strategy may be insufficient in phases of heightened rate volatility. By deploying MSCI US unlisted sector-specific real estate quarterly total returns between March 1999 and June 2024, this research assesses portfolio asset allocation strategy for unlisted sector-specific real estate over both rate-easing and rate-tightening phases to investigate how the structural change shapes portfolio asset allocation strategy resulting from the rising interest rates. Overall, the findings show that unlisted sector-specific real estate played a substantial role in the US institutional mixed-asset portfolios during rate-hike phases in the period before the COVID-19 recession. The allocation to unlisted sector-specific real estate was close to the maximum 10% cap, averaging 9.5% during rate-easing phases but decreasing to 7.5% during rate-tightening phases. At a sector level, unlisted office real estate allocations were higher across constrained mixed-asset and real estate portfolios in rate-tightening phases relative to those in rate-easing phases, while portfolio asset allocations to unlisted real estate sectors were lower in rate-easing phases relative to those in rate-tightening phases. These empirical findings provide real estate investment stakeholders with practical and crucial insights into rebalancing portfolios’ tactical asset allocation strategies for unlisted sector-specific real estate responding to interest rate phases and macro-financial markets, albeit static asset allocation strategies being insufficient in phases of heightened rate volatility. The investment implications of empirical outcomes are identified and further discussed. Full article

Climate-driven sea ice decline is accelerating the commercial use of Arctic routes and raising the need for Green Shipping Corridors that couple decarbonization with safety and ecosystem protection. This study introduces the concept of Arctic Green Maritime Data—environmental, meteorological, operational, and emission datasets generated in polar navigation—and examines how the EU Data Act can serve as a legal–institutional backbone. Using a multilayered integrative analysis, we (i) interpret core provisions on user access, portability, compensation, public-interest requests, cloud switching, and interoperability; (ii) map the Act’s roles of data holder, user, and recipient onto shipping stakeholders; (iii) assess whether polar operational datasets qualify as “data generated through the use of a product”; and (iv) derive a contractual architecture for corridor operations. We propose a three-layer governance model: firm-level instruments (a Standard Arctic Green Maritime Data Transaction Agreement, enterprise data governance architecture, and FRAND (Fair, Reasonable, and Non-Discriminatory) based contracting), association-level tools (industry model terms, public-purpose data protocols, and a neutral data-trust intermediary), and IMO-level integration aligning EU Data Act principles with Polar Code and MARPOL. The analysis showed that structured rights and obligations reduce vendor lock-in, enable safe public-interest data flows (with emergency access and fair compensation), and improve interoperability across clouds and jurisdictions. The results provide implementable pathways for shipping companies to turn Arctic Green Maritime Data into strategic assets while supporting sustainable and resilient green shipping corridor operations. Full article

The aim of this article is to illustrate the actions taken to implement the Rio Capodacqua–Santa Croce River Contract in Central Italy. The aim was to develop this inclusive and voluntary strategic and negotiated planning tool with the aim of protecting and managing water resources, enhancing the river ecosystem and mitigating flood risk, thereby contributing to local development. The participation of municipalities, local authorities, stakeholders and citizens’ associations in this instrument has made it possible to identify the environmental and territorial issues in this area and thus propose actions to resolve them, integrating and coordinating existing plans and programmes and the interests of that territory. These actions were defined through a participatory process involving all those interested in the watercourse and the territory it crosses. Among the proposed actions, priority was given to those offering “sustainable” solutions to certain critical issues, such as pollution of the lower reaches of the river or the essentially anthropogenic threat to the river and riparian habitats widespread in its upper reaches. These habitats, protected by the Natura 2000 network, are home to fish species of great conservation interest, among other things. Finally, flood mitigation works and measures are assessed, as floods are becoming increasingly aggressive due to climate change and are impacting urbanised areas. All these actions have been compared with sustainability objectives to highlight their effectiveness in the current management of a river basin with a view to the future. Full article

Sierra Leone’s water sector faces a “paradox of scarcity in abundance”: despite plentiful natural water resources, access to safe, reliable, and affordable supply remains limited, particularly for vulnerable populations. This paper investigates the governance dynamics and stakeholder relationships that underpin these challenges, drawing on a mixed-methods approach combining desktop research, surveys, and 37 semi-structured interviews. Using stakeholder and social network analysis, the study identifies key actors and their roles, interests, influence, and interdependencies, while also examining systemic barriers across social, technical, economic, environmental, and political dimensions. The findings reveal a highly fragmented governance landscape, characterised by overlapping mandates, donor dependency, weak enforcement, and the marginalisation of community voices. Although recent reforms—including new regulatory institutions, donor-funded infrastructure projects, and community-based initiatives—represent progress, they remain largely piecemeal, reactive, and insufficient to address entrenched structural deficiencies. The paper concludes that Sierra Leone’s water crisis is less a problem of resource scarcity than one of governance. Achieving sustainable water security requires integrated, system-wide reforms that strengthen institutional capacity, enhance coordination, enforce accountability, and embed inclusive stakeholder participation. Full article

Smart charging management systems for electric vehicles (SCMSs) enable the effective management of electric vehicle (EV) charging processes using smart technologies. Numerous SCMS technologies have been available for different stakeholders, e.g., EV drivers, charging station managers, and car manufacturers. Despite the ever-increasing interest in SCMSs, the literature lacks in reusable, standardised architecture design that reduces the effort for the development of quality SCMSs. In this paper, we propose a reference architecture (RA) for SCMSs. Our RA design is based on our comprehensive domain analysis that encompasses the analysis of the existing literature and commercial technologies which have been supported by our survey on EV drivers. In our RA, we provide four different viewpoints. The context viewpoint classifies the potential stakeholders and their roles and responsibilities. The module viewpoint defines the software implementation units and their modules that can be used for implementing any SCMSs. The component and connector viewpoint defines the executing parts of any SCMSs and their organisations into layers. The allocation viewpoint defines how the executable components can be mapped into the physical devices. We validated our RA design via prototyping and surveying to measure the RA’s applicability in real-world scenarios and usability for stakeholders. Full article

The global literature underscores a set of human wellbeing challenges and opportunities for forestland exploitation, albeit the lack of region-specific evidence. This concerns the Congo Basin, the second-largest forest ecosystem in the world. This study uses the case of the Campo Ma’an Landscape to: (i) analyze the challenges linked to the exploitation of forestland resources, and (ii) explore forest resource exploitation opportunities in the landscape. The study employed a random sample of 200 natural resource-dependent households drawn from four study zones—Niete, Campo, Ma’an and Akom II. This was complemented by focus group discussions (n = 4), key informant (n = 6) and expert (n = 6) interviews. The descriptive and inferential analyses led to the following results: First, economic, technical, socio-cultural and institutional challenges affect the sustainable exploitation of forestland resources in the Campo Ma’an Landscape. The economic challenges of forest (B = −0.389, p = 0.01) and land resource exploitation (B = −0.423, p = 0.006) significantly affect sustainable exploitation compared to other challenges, leading to biodiversity loss and deforestation. These constitute a threat to planetary health systems. Almost all households rely on forestland resources for their livelihoods and development, with opportunities for land resource exploitation outweighing those in forest resource exploitation. Protected area management and agriculture are affected owing to competing interests among farmers, conservationists and other land users. Thus, short-term economic gains are prioritized over long-term sustainability, putting the resource landscape at risk of degradation and future uncertainties. Integrated stakeholder engagement, capacity building, and policy revision could enhance the planetary health approach by linking the social, economic and environmental dimensions of forestland resource management. Full article

Aiming at multi-agent interest demands and environmental benefits, a distributionally robust game-theoretic optimization algorithm based on a green certificate–carbon trading mechanism is proposed for uncertain microgrids. At first, correlated wind–solar scenarios are generated using Kernel Density Estimation and copula theory and the probability distribution ambiguity set is constructed combining 1-norm and $\infty$-norm metrics. Subsequently, with gas turbines, renewable energy power producers, and an energy storage unit as game participants, a two-stage distributionally robust game-theoretic optimization scheduling model is established for microgrids considering wind and solar correlation. The algorithm is constructed by integrating a non-cooperative dynamic game with complete information and distributionally robust optimization. It minimizes a linear objective subject to linear matrix inequality (LMI) constraints and adopts the column and constraint generation (C&CG) algorithm to determine the optimal output for each device within the microgrid to enhance its overall system performance. This method ultimately yields a scheduling solution that achieves both equilibrium among multiple stakeholders’ interests and robustness. The simulation result verifies the effectiveness of the proposed method. Full article

Pulpitis is the inflammatory response of the dental pulp to microbial challenge and can range from mild to severe in nature, with severe pulpitis traditionally resulting in pulp removal and root canal treatment (RCT). In the pursuit of more conservative treatments, recent clinical practice guidelines have recommended strategies that preserve the vitality of the dental pulp, rather than RCT, when possible. This has increased the focus on improving the accuracy of pulp diagnosis, which will direct treatment and improve management outcomes. Unfortunately, current point-of-care (PoC) tools are subjective, lack discrimination and rely on the stimulation of pulpal neurons, limiting dentists’ ability to objectively identify the level of inflammation. Molecular biomarker assessment has the potential to dynamically analyse pulpitis and correlate this with inflammatory thresholds and treatment outcomes. Numerous chemokines, cytokines, proteases and growth factors exhibit altered expression during pulpitis and can be collected intraoperatively as part of routine dental treatment. Although current data indicate several markers that could be used as next-generation diagnostic chairside tools for pulpitis, there are currently no commercial kits. Considering the interest in vital pulp treatment, there is an urgent need to engage researchers, industry, dentists and other stakeholders in the development of PoC diagnostic assays for pulpitis. Full article

The retrofit of vacant buildings into sustainable integrated medical and elderly care facilities represents an important pathway for promoting urban regeneration and addressing population aging challenges. However, conflicts of interest among key stakeholders frequently compromise the quality of retrofit and long-term operational sustainability. To address this issue, this study develops a tripartite evolutionary game model comprising investors, builders, and operators to examine the behavioral evolution and cooperative mechanisms of these stakeholders across the investment, construction, and operation phases. Simulations were conducted based on a real-world retrofit project in Lanzhou, China, and the results suggest that: (1) Policy preference or reputational incentives alone appear insufficient to maintain cooperation, whereas their integration with economic incentives can effectively enhance the stability of cooperation among the three parties. (2) Builders exhibit higher sensitivity to penalties than operators, underscoring the pivotal role of the construction phase in ensuring retrofit quality. (3) When investors shift their role from short-term compliance regulation to long-term governance, it is more conducive to promoting operators to provide high-quality services in the long run. This paper proposes several suggestions and countermeasures, to provide practical guidance for the multi-party collaborative governance and sustainable operation of integrated medical and elderly care retrofit projects in China under the background of urban renewal. Full article

This study aimed to assess various social–ecological traps of hilsa shad (Tenualosa ilisha) fisheries and to investigate the factors that significantly impact livelihood adaptation strategies during the ban period, based on fieldwork in coastal fishing communities. To collect empirical data, a total of 247 in-depth interviews were conducted using a semi-structured questionnaire along with six focus group discussions, oral history, and ten key informant interviews in the Chattogram and Patuakhali districts of Bangladesh. A conceptual framework derived from a strategy for reducing poverty, known as the Sustainable Livelihood Approach (SLA), is applied to determine the livelihood outcomes of hilsa fishers. The results showed that low income (<5000 BDT/month), high interest in loans from dadondar (lender) (10–12%) and aratdar (lessor of the vessel) (5%), high harvesting costs, an increasing number of hilsa fishermen, and intergenerational traps (81.78%) are creating social–ecological traps (SETs) in the hilsa fishery. The significant factors affecting the choice of adaptation strategies include family members, training facilities, home ownership, and belonging to a formal society. Apart from fighting against some extreme climate events, negative feedback comes from the absence of cold storage facilities, illegal use of fishing nets, frequent ban seasons, ignorance of conservation laws, limited opportunities for alternative occupations, and poor supply of drinking water. Hilsa fishermen in these regions depended on aratdar and dadondar for their financial support, which resulted in lower prices than the prevailing market prices. To escape from the SETs, this study identifies potential alternatives, such as government–community finance schemes, the promotion of alternative livelihoods, opportunities for technical education of their children, improvement of the local framework, and strong cooperation between local stakeholders and management authorities that are necessary to maintain the sustainability of hilsa fisheries. Full article

Rapid integration of renewable energy sources poses a serious problem to the functionality of microgrids since they are characterized by underlying uncertainties and variability. This paper proposes a multi-stage approach to energy management to overcome these issues in a virtual power plant that combines heterogeneous microgrids. The solution is based on multi-agent deep reinforcement learning to coordinate internal energy pricing, microgrid scheduling, and virtual power plant-level energy storage system management. The proposed model autonomously learns the optimal dynamic pricing strategies based on load and generation dynamics, which is efficient in dealing with operational uncertainties and maintaining microgrid privacy due to its decentralized structure. The efficiency of the proposed solution is tested on comparative simulations based on real-world data, which prove the superiority of the framework to the traditional operation modes, which are isolated microgrids and the energy sharing scenarios. The findings prove that the suggested solution has a dual beneficial impact on both virtual power plant operators and involved microgrids, as it leads to profit enhancement and, at the same time, system stability. This process facilitates the successful balancing of conflicting interests among the stakeholders at a time when the operation is low-carbon. The study offers an overall solution to dealing with complicated multi-microgrids and brings substantial changes in the integration of renewable energy, as well as the distributed management of energy resources. The framework is a scalable model that can be used in the future perspective of power systems with high-renewable penetration to address both economic and operational issues of the contemporary energy grids. Full article