Search Results (246)

This paper seeks to establish the impact of university experiential learning programs on small- to medium-sized enterprises while emphasizing the benefit to rural workforce development and sustainable manufacturing practices. Data were collected from diverse partners of Louisiana State University’s experiential learning program over the last 7 years to illustrate the types of recommendations and implementation statistics for sustainable manufacturing practices. The study found that rural enterprises favored the adoption of short-term, high-saving solutions to mitigate the impact of utility costs resulting from geographical isolation, while there was low implementation of long-term, large investment projects. This highlighted the practical feasibility of a project over a focus on long-term sustainability plans, which require significant capital investment, management planning, and employee training. This study outlines a university-led experiential learning program’s engagement through academic–industrial partnerships that serve student development and the economic advancement of small- to medium-sized enterprises. The data can direct future incentive opportunities for sustainability projects that have more immediate payback, to increase the adoption rate in rural facilities. The larger implication provides a framework and validation that can support the development of similar programs for extension and enterprise engagement to impact sustainable manufacturing practices. Full article

Environmental policy helps policymakers and researchers understand the process and expected effects of policy before the policies are fully implemented. This study aims to estimate the effects of resource-conserving and environmentally friendly policy implemented in the Wuhan metropolitan area and Changsha–Zhuzhou–Xiangtan urban agglomeration. The synthetic control method is employed as an estimation method. The results show that policy has positive impacts on economic development and SO₂ emission reduction in the pilot regions but cannot improve wastewater treatment. Compared to large cities, medium-sized and small cities are more sensitive to policies since the large cities have transferred a large number of enterprises with high energy consumption and high emissions to the surrounding medium-sized and small cities. The study also finds that the Wuhan metropolitan area reduces pollution emissions through increasing environmental investment and the efficiency of resource allocation. In the Changsha–Zhuzhou–Xiangtan urban agglomeration, policy triggers green technology innovation to improve the environment and boost the economy. Full article

A common challenge faced by global wood-processing enterprises (WPEs) is their frequent exposure to external shocks. The improvement of regional financial development (RFD) may help WPEs enhance their resilience, thereby enabling them to mitigate external shocks. Against this backdrop, it is worth investigating whether RFD’s improvement can enhance WPEs’ resilience. However, the literature that addresses this issue is scarce. Based on the data of WPEs in mainland China from 2008 to 2016, we evaluate RFD’s effect on WPEs’ resilience. The findings are as follows: RFD can positively affect WPEs’ resilience, and multi-dimensional stability tests confirm the robustness of this result. RFD produces indirect positive effects by enhancing WPEs’ financing capacity and reducing their financing costs. Heterogeneity tests reveal that the RFD’s positive effect manifests in three distinct wood-processing sub-sectors. Crucially, its impact proves significantly greater on small and micro WPEs than on medium and large-sized ones. Furthermore, the positive effects are stronger for WPEs located in central and western provinces and non-municipal districts versus those situated in eastern provinces and municipal districts. Compared with technology- and capital-intensive WPEs, labor-intensive ones benefit more from RFD’s improvement. Full article

Small and medium-sized enterprises (SMEs) face growing challenges in optimizing their sustainable supply chains because of fragmented logistics data and changing regulatory requirements. In particular, globally operating manufacturing SMEs often lack suitable tools, resulting in manual data collection and making reliable accounting and benchmarking of transport emissions in lifecycle assessments (LCAs) time-consuming and difficult to scale. This paper introduces a novel hybrid AI-supported knowledge graph (KG) which combines large language models (LLMs) with graph-based optimization to automate industrial supply chain route enrichment, completion, and emissions analysis. The proposed solution automatically resolves transportation gaps through generative AI and programming interfaces to create optimal routes for cost, time, and emission determination. The application merges separate routes into a single multi-modal network which allows users to evaluate sustainability against operational performance. A case study shows the capabilities in simplifying data collection for emissions reporting, therefore reducing manual effort and empowering SMEs to align logistics decisions with Industry 5.0 sustainability goals. Full article

As we move toward a more digitalized and interconnected world, new cybersecurity challenges emerge. While most related research has focused on large companies, this study aims to fill a gap in the literature by exploring cybersecurity issues in small and medium-sized enterprises (SMEs), particularly in relation to nontechnical, soft-skill, and intellectual capital aspects. This study examines the interplay between cybersecurity awareness and perception and ownership structure in SMEs in the Silesian region of Poland. Unlike the majority of cybersecurity literature, our focus is on how ownership structure influences cybersecurity perception. We surveyed 200 SMEs at random within the respective region and utilized hierarchical and simple linear regression analyses to assess the relationships between these factors and financial performance. Our results indicate that larger enterprises and those without a family-owned structure exhibit significantly greater levels of cybersecurity. Additionally, we found a positive correlation between cybersecurity and a firm’s financial performance and overall health. These findings underscore the importance of cybersecurity awareness and practices for the growth and stability of SMEs. Full article

At the steelmaking temperature, carbon has a strong deoxidation ability. Under the vacuum condition, its deoxidation ability can be further improved, and it can become a stronger deoxidation element than aluminum. The product of carbon deoxygenation is CO, which floats up and detaches from the molten steel in the form of bubbles and does not produce oxide inclusions. Under normal pressure, replacing aluminum with carbon to complete partial deoxidation tasks can not only reduce the generation of inclusions and alleviate the pressure of removing inclusions, but also reduce the consumption of aluminum and save deoxidation costs. In this study, the carbon deoxidation process after the converter was investigated. Firstly, the timing of carbon addition was determined through thermodynamic calculations, and it was found that, in oxygen-enriched molten steel, the priority of the reaction of the deoxidation element was [Al] > [Si] > [C] > [Mn]. Through the carbon and oxygen balance calculation, it is known that the carbon deoxidation effect is greatly affected by the carbon content of the molten steel; for low-carbon steel, carbon can be used for pre-deoxygenation, whereas for medium-carbon and high-carbon steel, carbon can complete most of the deoxidation tasks. Finally, with 45 steel as the research object, the carbon deoxidation process was designed and tested in industry. The results showed that, compared with the aluminum deoxidation process, the number of inclusions in the billet casting of the carbon deoxidation process was reduced by 68.8%, and the carbon deoxidation process had fewer large-sized inclusions in the billet casting. In addition, the carbon deoxidation process uses carbon powder instead of the aluminum block for deoxidation during steel tapping from the converter. The deoxidant cost is reduced by CNY 15.47/ton of steel. From a comprehensive point of view, the application of carbon deoxidation after the converter can reduce aluminum consumption and improve the cleanliness of steel, which is an important way for enterprises to reduce costs and increase efficiency. Full article

Despite the transformative potential of artificial intelligence (AI), small and medium-sized enterprises (SMEs) continue to face significant challenges in its effective adoption. While prior studies have emphasized strategic benefits and readiness models, there remains a lack of operational guidance tailored to SME realities—particularly regarding implementation barriers, resource constraints, and emerging demands for responsible AI use. This study presents an analysis of AI adoption in SMEs by integrating the technology–organization–environment (TOE) framework with selected attributes from the diffusion of innovations (DOI) theory to examine adoption dynamics through a dual structural and perceptual lens. Empirical insights from sectoral and regional contexts are also incorporated. Ten critical challenges are identified and analyzed across the TOE dimensions, ranging from data access and skill shortages to cultural resistance, infrastructure limitations, and weak governance practices. Notably, the framework is expanded to incorporate responsible AI governance and democratized access to generative AI—particularly open-weight large language models (LLMs) such as LLaMA, DeepSeek-R1, Mistral, and FALCON—as emerging technological and ethical imperatives. Each challenge is paired with actionable, context-sensitive solutions. The paper is a structured, literature-based conceptual analysis enriched by empirical case study insights. As a key contribution, it introduces a structured, six-phase roadmap methodology to guide SMEs through AI adoption—offering step-by-step recommendations aligned with technological, organizational, and strategic readiness. While this roadmap is conceptual and has yet to be validated through field data, it sets a foundation for future diagnostic tools and practical assessments. The resulting study bridges theoretical insight and implementation strategy—empowering inclusive, responsible, and scalable AI transformation in SMEs. By offering both analytical clarity and practical relevance, this study contributes to a more grounded understanding of AI integration and calls for policies, ecosystems, and leadership models that support SMEs in adopting AI not merely as a tool, but as a strategic enabler of sustainable and inclusive innovation. Full article

Categorization of enterprises by size provides a fundamental understanding of the composition of the business environment. Small, medium-sized, and large enterprises play a significant role in the national economy through the execution of specific business activities. In their pursuit of enhancing the efficiency of individual business processes and mitigating the risks associated with these activities, enterprises may implement various ISO standards, including quality management, environmental management, occupational health and safety (OSH), or corporate social responsibility (CSR) systems. The sources published to date do not clearly explain the mutual relationship that arises when implementing multiple ISO standards that prioritize different activities within a single enterprise. This gap is particularly evident in the context of small enterprises, which often do not have the obligation or capacity to implement ISO standards. This study addresses this research gap by identifying the relationship between implemented ISO standards, priority activities in the risk management process, and the person responsible for these activities. The objective of this article is to examine the relationship of dependency between specific ISO standards and the priority activity in risk management. Furthermore, the study seeks to determine whether the degree of implementation of ISO standards influences the selection of the person responsible for risk management. Additionally, it examines whether dependence exists between the priority activity in risk management and the specific person responsible for risk management. The authors provide statistical hypothesis testing based on data from a nationwide survey conducted across all enterprise size categories. The results obtained from this study confirm the presence of a dependency between the degree of ISO standards implementation and the priority activity in risk management across all enterprise size categories. However, a statistically significant dependency between the degree of implementation of ISO standards and the person responsible for risk management was not confirmed in large companies. The dependency between the selection of the person responsible for risk management and the priority activity in risk management was confirmed only in small enterprises. Full article

The escalating scale and sophistication of cyber threats compel enterprises to urgently adopt data-driven security analytics. This systematic literature review, adhering to the PRISMA protocol, rigorously synthesizes current knowledge by analyzing 65 peer-reviewed studies (2013–2023) from six major databases on enterprise-level cybersecurity analytics. Our findings reveal a significant industry-wide transition from traditional signature-based tools towards advanced cloud-enabled, big-data and artificial intelligence-powered techniques, where machine learning and graph-based models are increasingly prominent in recent works. While large organizations in finance, Information and Communication Technology, and critical utilities spearhead adoption, dedicated research focusing on small and medium-sized enterprises (SMEs) remains notably limited. Ten thematic observations encapsulate key adoption drivers, an evolving preference for proactive and predictive security strategies, the critical role of heterogeneous log and network data, and persistent implementation challenges-notably data integration, skills shortages, and cost. Furthermore, this review identifies crucial open research avenues, including the development of real-time scalable analytics, unified policy languages, and critically needed SME-oriented solutions. Collectively, these insights provide a robust evidence base to inform future research trajectories and guide the practical deployment of effective cybersecurity analytics in diverse enterprise settings. Full article

This article addresses a topic of critical importance globally, particularly in the context of the ongoing energy crisis, climate change, and efforts to transition towards sustainable energy systems. A growing environmental awareness among consumers, along with changing regulations on energy efficiency, forces companies to adapt their products and services to meet new market demands. Eco-innovations, such as energy-efficient technologies and environmentally friendly materials, can respond to the increasing demand for products with a lower carbon footprint and reduced energy consumption. Using structural equation modelling, our study aimed to evaluate the significance of selected determinants of enterprise activities aimed at innovations that yield environmental benefits. The analysis focused on the scale of the benefits obtained due to these innovations (e.g., reduced material or water use per unit of output, reduced energy use, reduced CO₂ footprint, reduction in pollution, or recycling of waste) and during the consumption or use of goods or services by the end user (e.g., energy savings, facilitated recycling, or extended product life). The empirical data source was a database of anonymised individual data from Statistics Poland. The database comprised 8544 industrial enterprises employing 10 or more people, of which 2714 introduced eco-innovations. To verify the hypothetical relationships between variables, we proposed a structural equation modelling method. The structural model estimates indicated that requirements arising from current and future regulations, pressure from high operational costs and administrative formalities, and reputation and incentives had a positive and statistically significant impact on the scale of benefits obtained due to these eco-innovations. The assessment of the importance of factors determining the introduction of eco-innovations differed slightly between companies of different sizes. For large enterprises, the key determinants were incentives, reputation, and law requirements. For medium-sized enterprises, incentives and reputation were the most influential. For small enterprises, reputation was the primary determinant, followed closely by pressure and incentives at a similar level. Full article

The energy market in the European Union is dominated by large energy companies. However, the liberalization of this market, the removal of market barriers, and the encouragement of small companies to enter the market are creating new conditions and changing the structure of companies. In addition to large energy companies, a significant number of small entities are also emerging. The aim of this research is to analyze the relationship between the size of energy companies and their technical efficiency. This analysis was carried out for the period 2019–2023. In order to assess the efficiency of the researched energy companies, the Data Envelopment Analysis (DEA) method was employed. The analyzed enterprises were divided into three groups: small (IA), medium (IB), and large (II). The following economic categories were adopted as the division criteria: 1. net sales revenue; 2. operating costs; 3. fixed assets. The findings of our study suggest that small and medium-sized energy companies can exhibit levels of efficiency that are comparable to those of larger enterprises. This result suggests that companies of different sizes can coexist in the energy market. The results obtained are not completely conclusive, as statistically significant differences in technical efficiency (TE) were recorded in 2021 and 2022 but only between small enterprises (IA) and medium-sized enterprises (IB). This study highlights the potential of small energy companies to contribute effectively to Poland’s energy sector and suggests that supporting their development could enhance energy security and market competition. However, many energy companies—regardless of size—exhibited low levels of efficiency, underlining the need for deeper investigation into the sources of inefficiency. Full article

Corporate social responsibility (CSR) disclosure plays a pivotal role in mitigating “blue” (labor standard) and “green” (environmental standard) trade barriers, optimizing the foreign trade ecosystem, fostering sustainable development of export-oriented enterprises, and advancing societal welfare objectives—all critical to maintaining high-quality social order in China. Grounded in institutional and strategic management theories, this study systematically investigates the effects of CSR disclosure on corporate export performance, focusing on mediating and moderating mechanisms, and conducts rigorous empirical testing using comprehensive firm-level CSR disclosure data from Chinese listed companies. The results reveal the following key findings: (1) CSR disclosure positively influences corporate exports; (2) enterprise financing capacity and innovation output serve as dual mediating mechanisms, through which CSR disclosure enhances export performance by improving access to external capital and stimulating product/service innovation; (3) environmental regulations amplify the export-promoting effect of CSR disclosure, indicating that institutional environmental constraints incentivize firms to leverage disclosure as a strategic response to global sustainability demands; (4) heterogeneity analysis reveals that large enterprises derive the strongest export benefits from CSR disclosure, followed by medium-sized and small enterprises; and (5) private enterprises exhibit significantly greater export gains from CSR disclosure compared to state-owned enterprises. These results underscore the context-specific and multi-dimensional nature of CSR disclosure’s impact on exports, highlighting how firm size and ownership structure shape the efficacy of disclosure strategies in global markets. This study contributes to both academic literature on corporate sustainability and practical policy by demonstrating how strategic CSR disclosure can serve as a tool for overcoming institutional barriers and enhancing international competitiveness. Full article

This paper introduces a novel framework for addressing domain adaptation challenges in large language models (LLMs), emphasising privacy-preserving synthetic data generation and efficient fine-tuning. The proposed framework employs a multi-stage approach that includes document ingestion, relevance assessment, and automated dataset creation. This process reduces the need for extensive technical expertise while safeguarding data privacy. We evaluate the framework’s performance on domain-specific tasks in fields such as biobanking and public health, demonstrating that models fine-tuned using our method achieve results comparable to larger proprietary models. Crucially, these models maintain their general instruction-following capabilities, even when adapted to specialised domains, as shown through experiments with 7B and 8B parameter LLMs. Key components of the framework include continuous pre-training, supervised fine-tuning (SFT), and reinforcement learning methods such as direct preference optimisation (DPO), which together provide a flexible and configurable solution for deploying LLMs. The framework supports both local models and API-based solutions, making it scalable and accessible. By enabling privacy-preserving, domain-specific adaptation without requiring extensive expertise, this framework represents a significant step forward in the deployment of LLMs for specialised applications. The framework significantly lowers the barrier to domain adaptation for small- and medium-sized enterprises (SMEs), enabling them to utilise the power of LLMs without requiring extensive resources or technical expertise. Full article

Driven by the path of ecological transition, municipal solid waste management is now more than ever at the center of debates on the most efficient delivery methods. Although competition policy advocates subdivision into lots to facilitate medium-sized enterprise participation, in some cases—notably when substantial investments are required to achieve circular economy and sustainable development goals—a single-operator model may prove more efficient. Using a mixed research approach that integrates empirical evidence and market analysis, this study examines the relevance of cost curves, transaction costs, and market structure in determining the optimal service delivery model. The findings indicate that for large cities, consolidating MSW management services under a single contract yields significant cost advantages due to economies of scale and scope and is better suited to supporting the investments necessary for circular economy objectives. Practical implications for local policymakers highlight the need to assess utility sector policies carefully. Decisions at the local level should account for the interplay between the economic environment and the role of industrialization and economies of scale in fostering sustainable development. We suggest policymakers design policies that balance market efficiency with equitable access to services while also considering the scale of service provision, as it influences sustainability and economic resilience. Full article

Customer relationship management (CRM) is a key factor driving innovation and organizational growth. The present study investigated the relationship between data-driven CRM (DDCRM) and innovation in Taiwan. We developed a research model involving CRM theory, innovation theory, and the technology adoption model (TAM) theory to account for the cultural and organizational contexts of Taiwan and investigate this relationship. The study distributed questionnaires to employees and stakeholders within Taiwanese firms to understand their firms’ innovation and CRM practices. The results indicate that technology adoption and organizational culture have mediating effects and industry dynamics and organizational size have moderating effects on the relationship between DDCRM and innovation. That is, adopting new technology and having an organizational culture that supports innovation and company-wide collaboration can enhance the effects of implementing DDCRM practices. In addition, certain industries (e.g., the technology industry) are more likely to effectively leverage DDCRM practices to drive innovation, and although large organizations have more resources and can therefore more easily implement CRM systems, small and medium-sized enterprises (SMEs) can more quickly adapt and innovate on the basis of CRM insights. These findings highlight the importance of DDCRM in driving innovation and reveal key factors influencing the effectiveness of CRM in doing so. The study features comprehensive suggestions of operable strategies and measures for Taiwanese SMEs, hopefully assisting them in gaining a market advantage and elevating their innovation capabilities by leveraging DDCRM practices. Full article