Search Results (355)

This study analyses the potential of using sunflower husks as an energy source by producing bio-pellets and evaluating their combustion process in residential settings. As one of the leading sunflower producers in the European Union, Bulgaria generates significant agricultural residues with high, yet underutilized, energy potential. This study employs a combination of experimental data and numerical modelling aided by ANSYS 2024 R1 to analyse the combustion of sunflower husk pellets in a hot water boiler. The importance of balanced air distribution for achieving optimal combustion, reduced emissions, and enhanced thermal efficiency is emphasized by the results of a comparison of two air supply regimes. It was found that a secondary air-dominated air supply regime results in a more uniform temperature field and a higher degree of oxidation of combustible components. These findings not only confirm the technical feasibility of sunflower husk pellets but also highlight their commercial potential as a sustainable, low-cost energy solution for agricultural enterprises and rural heating providers. The research indicates that there are business-to-business (B2B) market opportunities for biomass producers, boiler manufacturers, and energy distributors who wish to align themselves with EU green energy policies and the growing demand for solutions that support the circular economy. Full article

From the perspective of credit ratings, this paper studies the impact of air pollution on corporate credit costs and the impact mechanism. Based on 2007–2022 data on A-share listed companies in the Chinese capital market, this paper uses a two-way fixed effects model to examine the impact of air pollution on corporate credit costs and the impact mechanism. The results show that air pollution increases the credit costs for enterprises because air pollution affects the sentiment of rating analysts, leading them to give more pessimistic credit ratings to enterprises located in areas with severe air pollution. The moderating effect analysis reveals that the effect of air pollution on the increase in corporate credit costs is more pronounced for high-polluting industries, manufacturing industries, and regions with weaker bank competition. Further analysis reveals that in the face of rising credit costs caused by air pollution, enterprises tend to adopt a combination strategy of increasing commercial credit financing and reducing the commercial credit supply to cope. Although this response behavior alleviates corporations’ own financial pressure, it may have a negative effect on supply chain stability. This paper provides new evidence that reveals that air pollution is an implicit cost in the capital market, enriching research in the fields of environmental governance and capital markets. Full article

This paper focuses on regeneration projects in ‘first-generation’ seaside resorts in England from the perspective of those leading and managing such projects. There have been numerous recent initiatives intended to revive seaside resorts and enable them to regain competitiveness, but limited analysis of what is necessary for such regeneration projects to be successful. This paper contributes to debates about the role of critical success factors (CSFs) in regeneration by identifying issues that apply to the specific context of seaside resorts. In-depth interviews were undertaken with ten managers responsible for individual projects focusing on the CSFs necessary for regeneration projects to succeed. Four such factors were identified: (1) the need to secure appropriate funding (and associated difficulties); (2) the importance of involving stakeholders (particularly the local authority and local community); (3) the need for a strong business plan (which must evolve as the project progresses); and (4) the importance of considering best practices elsewhere. The importance of each success factor varied by the sector (public/commercial/third) leading the regeneration initiative and varied at different stages of a regeneration project. These findings have practical implications for local authorities, commercial enterprises, and third-sector bodies in seaside destinations. Full article

Increasing mechanical design complexity and volume, particularly in component-based manufacturing, require scalable, traceable, and efficient design processes. In this research, a modular in-house automation platform using Autodesk Inventor’s Application Programming Interface (API) and Visual Basic for Applications (VBA) is developed to automate recurrent tasks such as CAD file generation, drawing production, structured archiving, and cost estimation. The proposed framework was implemented and tested on three real-world case studies in a turbocharger reconditioning unit with varying degrees of automation. Findings indicate remarkable time savings of up to 90% in certain documentation tasks with improved consistency, traceability, and reduced manual intervention. Moreover, the system also facilitated automatic generation of metadata-rich Excel and Word documents, allowing centralized documentation and access to data. In comparison with commercial automation software, the solution is flexible, cost-effective, and responsive to project changes and thus suitable for small and medium enterprises. Though automation reduced workload and rendered the system more reliable, some limitations remain, especially in fully removing engineering judgment, especially in complex design scenarios. Overall, this study investigates how API-based automation can significantly increase productivity and data integrity in CAD-intensive environments and explores future integration opportunities using AI and other CAD software. Full article

The real estate market significantly influences individual lives, corporate decisions, and national economic sustainability. Therefore, constructing a data-driven, interpretable real estate market prediction model is essential. It can clarify each factor’s role in housing prices and transactions, offering a scientific basis for market regulation and enterprise investment decisions. This study comprehensively measures the evolution trends of the real estate markets in Beijing, Shanghai, Guangzhou, and Shenzhen, China, from 2003 to 2022 through three dimensions. Then, various machine learning methods and interpretability methods like SHAP values are used to explore the impact of supply, demand, policies, and expectations on the real estate market of China’s first-tier cities. The results reveal the following: (1) In terms of commercial housing sales area, adequate housing supply, robust medical services, and high population density boost the sales area, while demand for small units reflects buyers’ balance between affordability and education. (2) In terms of commercial housing average sales price, growth is driven by education investment, population density, and income, with loan interest rates serving as a stabilizing tool. (3) In terms of commercial housing sales amount, educational expenditure, general public budget expenditure, and real estate development investment amount drive revenue, while the five-year loan benchmark interest rate is the primary inhibitory factor. These findings highlight the divergent impacts of supply, demand, policy, and expectation factors across different market dimensions, offering critical insights for enterprise investment strategies. Full article

Sustainable rural development seeks to balance social, economic, and environmental needs in rural areas, improving the quality of life of communities and the long-term protection of natural resources. Indigenous local solutions give place to grassroots entrepreneurial initiatives, which together with associative and economic integration are key factors for agricultural production, transformation of products, self-consumption, and commercialization. This study was done in Hñähñu communities with the aim to test if participative workshops based on detonating questions are an effective approach for developing entrepreneurship agriculture initiatives of self-managed social enterprises. The initiatives were proposed by the communities to solve local problems. Three initiatives arose: (1) a community seed bank of local species associated with the Milpa including agave; (2) reforestation with agave to produce agave shoots, leaves, and sap; and (3) a company to produce agave-sap syrup. The participants, based on their traditional knowledge, developed the projects, including economic evaluation, risk analysis, and environmental aspects. Some impacts are the conservation of soil and endangered landraces, accessibility to quality seeds not commercially available, building of local organizational and entrepreneurial capacities, strengthening the community, improving the family’s income, recovery of traditional agroecological techniques, and conservation of agrobiodiversity. In conclusion, the methodology is effective for the Indigenous communities to develop initiatives for sustainable self-managed social enterprises. Full article

In order to mitigate the risks of losing key personnel and their innate tacit knowledge resources, this paper explored a framework for reducing knowledge loss in South African public sector enterprises (PSEs) through the integration of knowledge management (KM) and human resource management (HRM) strategies. The study used a quantitative research design, administering survey questionnaires to 585 randomly selected employees in three South African PSEs. The survey yielded a 25% response rate and was analysed using Statistical Analysis Software, resulting in a Cronbach alpha of 0.94. The findings of the exploratory factor analysis showed that a framework for reducing knowledge loss can be developed by integrating HRM practices and focusing on seven factors: knowledge loss recognition, knowledge management practices, human resource training, organisational culture, recruitment practices, employee retention, and organisational barriers. Three important components constitute the developed framework for knowledge loss minimization. Tacit knowledge loss was recognised as a critical strategic issue based on the results of the chi-square test for independence and logistic regression. This realisation, along with control and intervention variables, created the three main components of the framework. This paper explored the Knowledge Loss Reduction framework, focusing on South African PSEs as a case, to help organisations address the complex tacit knowledge loss prevalent in public and commercial firms worldwide. It contributes to the knowledge-based view, focusing on knowledge-absorptive and -retentive capacities and praxis in knowledge (risk) management and human resource management. Full article

This paper critically examines the consequences of land grabs for livelihoods and agrarian change, based on a case study of rubber plantations in ethnic minorities in the uplands in Northwest Vietnam. Building upon Scoones’ agrarian political economy of livelihood framework, an integrated conceptual framework of a ‘livelihood pathway’ is developed to analyze the impact of rubber plantation land grabs on livelihoods and the agrarian political economy. Drawing on qualitative analysis and survey data from 205 households across six villages inhabited by Thai, Hmong, and Kho Mu communities, this study finds that rubber plantation land grabs have led to differentiated livelihood strategies—ranging from subsistence farming and wage labor to commercial agriculture—shaped by each group’s socioeconomic status, political connections, and access to resources. Consequently, the land grabbing undertaken by a domestic state-owned enterprise has caused the emergence of a set of distinctive livelihood pathways within a complex web of intersections across class and ethnicity in the upland area. This study concludes by arguing that an integrated conceptual framework of a ‘livelihood pathway’ offers a useful tool for analyzing the long-term socio-political consequences of land grabbing in similar contexts across developing countries and beyond. Full article

In modern digital transactions involving government agencies, financial institutions, and commercial enterprises, reliable identity verification is essential to ensure security and trust. Traditional methods, such as submitting photocopies of ID cards, are increasingly susceptible to identity theft and fraud. To address these challenges, this study proposes a novel and robust identity verification framework that integrates super-resolution preprocessing, a convolutional neural network (CNN), and Monte Carlo dropout-based Bayesian uncertainty estimation for enhanced facial recognition in electronic know your customer (e-KYC) processes. The key contribution of this research lies in its ability to handle low-resolution and degraded facial images simulating real-world conditions where image quality is inconsistent while providing confidence-aware predictions to support transparent and risk-aware decision making. The proposed model is trained on facial images resized to 24 × 24 pixels, with a super-resolution module enhancing feature clarity prior to classification. By incorporating Monte Carlo dropout, the system estimates predictive uncertainty, addressing critical limitations of conventional black-box deep learning models. Experimental evaluations confirmed the effectiveness of the framework, achieving a classification accuracy of 99.7%, precision of 99.2%, recall of 99.3%, and an AUC score of 99.5% under standard testing conditions. The model also demonstrated strong robustness against noise and image blur, maintaining reliable performance even under challenging input conditions. In addition, the proposed system is designed to comply with international digital identity standards, including the Identity Assurance Level (IAL) and Authenticator Assurance Level (AAL), ensuring practical applicability in regulated environments. Overall, this research contributes a scalable, secure, and interpretable solution that advances the application of deep learning and uncertainty modeling in real-world e-KYC systems. Full article

This entry proposes an integrative approach to assessing market power in airport retail environments that highlights the impact of strategic and operational factors on the performance of the enterprise in a regulated and restrictive commercial environment. Using the Analytic Hierarchy Process (AHP), this entry discerns and quantifies important factors determining market power using weights that include price flexibility, consumer conduct, brand value, technological uptake rate, and barriers to entry. To support this qualitative analysis, this entry combines a quantitative countervailing power model (CP_A/E) and a market penetration model (MP_E/A) to determine the levels of retailer penetration in airport authorities and passenger markets. The integration of these models makes it possible to perform a multivariate analysis of market domination, geographical interdependence, and bargaining power. The findings highlight the configurational complexity in strategic positioning in terms of organizational size, dependence levels, and digital preparedness and provide actionable information for airport managers, concession planners, and policymakers determined to maximize lease deals and improve commercial performance in the face of changing risk profiles. Full article

Millions of tons of slag and clinker can be found in the dumps of enterprises across the Republic of Kazakhstan. The goal of this project is to create a technology that conserves energy in waste treatment. The novelty of the work is the discovery of a new phenomenon, which shows that in the melt layer, there are two reactions opposite in direction and intensity: slow reactions of the decomposition of complex components into simple molecules and rapid responses of the formation of complex components from simple molecules. The dominance of one of the two reactions affects the process’s fuel consumption. Using this phenomenon, a melting reactor was created, which will reduce specific fuel consumption by 3–4 times compared to a Waelz kiln. It is shown that using a new method of CO₂ decarbonization by zinc, it is possible to ensure the production of zinc sublimates and cast stone products and the full neutralization of CO₂. The lowest market potential only for Achisai dump clinker would be around USD 125,600,000 if the cost of commercial clinker sublimates is USD 800/t. The expected net profit would be USD 4,466,039/y. Full article

Electric aviation is the future development direction of aviation industry technology. Electric vertical take-off and landing aircraft(eVTOL) is an important carrier of electric aviation, whose technology research and development, processing and manufacturing, airworthiness certification and industrialization boom have been set off around the world. The electric propulsion technology has achieved rapid development as the key technology of eVTOL. Aiming at the demand for high torque density and high reliability of electric propulsion system, the paper analyzed the technical indexes of electric motor products of domestic and foreign benchmark enterprises. The key technologies such as motor integration, new electromagnetic topology, lightweight structure design, and high efficiency cooling is studied. It is pointed out that in order to pursue the high torque density and fault-tolerance performance, the integrated precise modeling of motor and controller, advanced materials and manufacturing technology are the development trend of the electric propulsion technology. The breakthrough of eVTOL electric propulsion technology can accelerate the commercial operation of civil eVTOL and promote the development of new quality productive forces. Full article

Superior electricity-optimized business ecosystems (EOBEs) have evolved into pivotal determinants in catalyzing industrial–commercial prosperity. The access to electricity index (AEI) constitutes a valid instrument for assessing the EOBE. To realize the accurate evaluation of EOBE and the root cause tracing of its changes, this paper constructs a new analytical model for evaluating and monitoring changes in EOBE. First, this paper constructs a new evaluation model of EOBE based on the Business Ready (B-READY) evaluation system, considering three factors: the power regulatory quality, the public service level, and the enterprises’ gain power efficiency. Then, the model uses the raw data collected to calculate a score for AEI to enable an accurate assessment of EOBE. Next, this paper uses a priori assessment to extract the coupling features of indicators and combines the time series features and policy features to construct the feature matrix. Finally, the characteristic contribution was analyzed using support vector regression (SVR) and Shapley’s additive interpretation (SHAP) value. The experiment shows that the factors affecting the change in AEI are time series features, policy features, and coupling features in decreasing order of importance. This study provides reference cases and improvement ideas for the assessment and optimization of EOBE. Full article

Heating and cooling are the main concerns across a wide range of sectors, including residential buildings, industrial facilities, transportation and commercial enterprises. This being the case, a continuous rise in the cost of energy demands more effective ways to conserve energy. Heat pump (HP) systems provide the one of the best possible solutions to this problem as they offer an economical and energy-efficient system. In this review, HP systems are overviewed as energy-efficient and cost-effective solutions, focusing on their characteristic properties but also on enhancements, novel techniques and the use of heat exchangers (HXs), and microchannel heat exchangers (MCHEs) in these systems, as well as their development in recent years and their limitations. The main factors contributing to variations in the performance of HP systems are temperature and humidity in the ambient atmosphere. The present study is expected to support numerical and experimental performance analysis, and design miniaturisation via MCHEs. Unique designs or manufacturing techniques in MCHEs; various configurations in HP systems, depending on their load and environmental conditions; various nanofluids; and a comparison of nanofluids with different base metals are presented and discussed. Comparisons between various MCHEs and their respective limitations provide evidence-based guidelines for technology selection and designs for optimised operation at given environmental and load conditions. Full article

In Building Information Modeling (BIM)-driven collaboration, the workflow for information management utilizes a Common Data Environment (CDE). The core idea of a CDE is to serve as a single source of truth, enabling efficient coordination among diverse stakeholders. Nevertheless, investigations into employing CDEs to manage projects reveal that procuring commercial CDE solutions is too expensive and functionally redundant for small and medium-sized enterprises (SMEs) and small research organizations, and there is a lack of experience in using CDE tools. Consequently, this study aimed to provide a cheap and lightweight alternative. It proposes a three-layered CDE framework: decentralized databases enabling work in distinct software environments; resource description framework (RDF)-based metadata facilitating seamless data communication; and microservices enabling data collection and reorganization via standardized APIs and query languages. We also apply the CDE framework to structural life cycle assessment (LCA). The results show that a lightweight CDE solution is achievable using tools like the bcfOWL ontology, RESTful APIs, and ASP.NET 6 Clean architecture. This paper offers a scalable framework that reduces infrastructure complexity while allowing users the freedom to integrate diverse tools and APIs for customized information management workflows. This paper’s CDE architecture surpasses traditional commercial software in terms of its flexibility and scalability, facilitating broader CDE applications in the construction industry. Full article