Search Results (426)

The growing global environmental crisis calls for fundamental transformations in production and consumption systems, but the understanding of how circular economy strategies translate into quantifiable environmental benefits remains fragmented across sectors and geographies. The objective of this study is to synthesize current scientific knowledge on the circular economy as an environmental mitigation strategy, identifying conceptual convergences, methodological patterns, geographic distributions, and critical knowledge gaps. A systematic review combined with a bibliometric analysis of 62 peer-reviewed articles published between 2018 and 2024, retrieved from Scopus, Web of Science, ScienceDirect, Springer Link and Wiley Online Library, was conducted following the PRISMA 2020 guidelines. The results reveal a marked methodological convergence around life cycle assessment, with Europe dominating the scientific output (58% of the corpus). Four complementary conceptual frameworks emerged, emphasizing closed-loop material flows, environmental performance, integration of economic sustainability and business model innovation. The thematic analysis identified bioenergy and waste valorization as the most mature implementation pathways, constituting 23% of the research emphasis. However, critical gaps remain: geographic concentration limits the transferability of knowledge to diverse socioeconomic contexts; social, cultural and behavioral dimensions remain underexplored (12% of publications); and environmental justice considerations receive negligible attention. Crucially, the evidence reveals nonlinear relationships between circularity metrics and environmental outcomes, calling into question automatic benefits assumptions. This review contributes to an integrative synthesis that advances theoretical understanding of circularity-environment relationships while providing evidence-based guidance for researchers, practitioners, and policy makers involved in transitions to the circular economy. Full article

Research laboratories in universities face a complex challenge: they must manage multiple projects, diverse teams, and tight deadlines, often with limited resources. While the business world has long used agile and quality management tools to navigate such complexity, these methods are surprisingly rare in academic research. In this study, we set out to bridge this gap. We implemented a combined management model, blending agile Scrum practices with proven quality tools like the Ishikawa diagram and PDCA cycle, within a pharmaceutical sciences research lab. Over a six-month period, we diagnosed key issues, created a structured action plan, and introduced an online platform to monitor progress continuously. Our approach led to a significant increase in productivity, with 65% of targeted articles being published or submitted and 75% of general lab activities completed. Perhaps just as importantly, communication improved dramatically, and the lab successfully met all its institutional deadlines. We conclude that this hybrid framework is not just a theoretical idea but a practical and powerful innovation. It provides a tangible blueprint for other research groups looking to enhance their productivity, streamline communication, and build a more adaptive and effective research culture in the face of academic complexity. Full article

In today’s dynamic and global business landscape, economic profitability is essential for creating and sustaining competitive advantage. Nevertheless, a critical gap persists in the literature regarding the application of advanced optimization techniques that systematically link operational improvements in the supply chain with strategic financial indicators. Accordingly, this study aims to identify and synthesize the optimization techniques applied to supply chain processes and their impact on economic profitability. To achieve this objective, the PRISMA methodology was employed. A systematic literature review covering the last ten years (2015–2025) was conducted using the Web of Science database. After applying inclusion and exclusion criteria, 35 studies were selected, revealing a growing methodological diversity. Nature-Inspired Algorithms (NIAs) and hybrid approaches (such as MILP combined with Simulation) demonstrate greater capacity to address complex and multi-objective scenarios. Notably, hybrid techniques have been successfully applied to the maximization of Economic Value Added (EVA), a key strategic value indicator. Despite the sophistication of these optimization techniques, the predominant objective remains total cost minimization, often sidelining the direct optimization of strategic indicators such as EVA or the Cash Conversion Cycle (CCC). Additionally, a key research gap was identified in the development of adaptive and resilient models that integrate technologies such as Digital Twins, Blockchain, and Artificial Intelligence to dynamically manage physical and financial disruptions in supply chains. The study concludes by emphasizing the need for a theoretical shift toward models that go beyond cost minimization and focus on real value metrics, as well as the exploration of more accessible solutions for SMEs. This review contributes a reference framework for academics and practitioners to align the most suitable optimization techniques with strategic financial objectives in supply chain management. Full article

To promote green and low-carbon transformation in the transportation sector and achieve the national “dual-carbon” targets, this study examines rooftop photovoltaic (PV) deployment at 12 representative railway stations located on the Qinghai–Tibet Plateau. Using high-resolution solar radiation data, building spatial information, and regional electricity pricing, we develop an integrated analysis framework that combines a PV power-generation simulation, life-cycle cost assessment, and carbon emission reduction evaluation. The model systematically evaluates the power output, economic performance, and emission reduction potential of rooftop PV systems installed on railway station buildings. Two PV array configurations—horizontal angle and optimum tilt angle—together with three business models (T1: all-consumption; T2: all-feed-into-grid; T3: self-consumption with surplus feed-in) are compared. The results indicate that the Qinghai–Tibet Plateau possesses substantial solar energy advantages. Rooftop arrays installed at a horizontal angle significantly increase both installed capacity and lifetime electricity generation, with stations XN and LS producing 523.12 GWh and 300.87 GWh, respectively, values that exceed the corresponding optimum tilt scenarios. In terms of economic performance, the T1 model yields the highest returns, with several stations achieving a lifetime return on investment exceeding 300% over a 25-year period. The T3 model demonstrates strong profit potential at stations such as RKZ and ZN, whereas the T2 model shows the weakest economic viability due to feed-in tariff constraints. Regarding carbon reduction, horizontal systems perform the best, with cumulative CO₂ emission reductions at station XN exceeding 300,000 tonnes of CO₂-equivalent. Overall, the findings highlight the substantial PV development potential of railway station rooftops on the Qinghai–Tibet Plateau. By selecting appropriate installation angles and business models, significant economic benefits and carbon emission reduction outcomes can be achieved, providing practical guidance for renewable-energy utilization in high-altitude transportation infrastructure. Full article

In today’s rapidly evolving business environment, digitalization has emerged not only as a technological trend but also as a strategic imperative. This paper develops a conceptual framework that examines how Industry 4.0 (I4.0) technologies and tools drive strategic innovation and enable the transformation of business models. Based on a systematic literature review, the framework identifies a set of organizational and contextual preconditions (strategic vision, organizational culture, digital skills, infrastructure, financial resources, and regulatory conditions) that can act as either enablers or barriers to innovation. The analysis reveals that these preconditions give rise to two contrasting innovation cycles: a virtuous cycle, where favourable conditions amplify the adoption of digital technologies and foster business model transformation, and a vicious cycle, where unfavourable conditions reinforce technological inertia and hinder strategic development. By integrating insights from innovation management, digital transformation, and business model theory, the framework offers a nuanced understanding of how technology and strategy intersect and provides actionable guidance for managers seeking to move beyond operational improvements toward reimagining value creation, delivery, and capture in the digital age. Full article

The global shift towards sustainable development and low-carbon growth has intensified the need for efficient management of natural resources. This study proposes an integrated economic assessment framework to evaluate how ESG (Environmental, Social, and Governance) integration and circular economy strategies influence resource productivity and long-term economic performance. The research focuses on the water–energy–land nexus as a critical driver of global economic systems. Using a combination of multi-criteria decision analysis (AHP/TOPSIS), material flow analysis (MFA), life-cycle assessment (LCA), and panel econometric modeling on a broad dataset of countries (2018–2023), we examine the relationship between resource efficiency, ESG adoption, and economic competitiveness. The results indicate that circular business models and strong ESG practices significantly reduce resource intensity, enhance total factor productivity, and strengthen economic resilience. Scenario modeling demonstrates that transitioning from linear to circular resource flows can yield substantial economic and ecological benefits, including a ~1–3% rise in GDP and a ~15–20% drop in resource intensity under a high-circularity scenario. These findings provide actionable insights for policymakers and businesses, emphasizing that sustainable resource governance is not only an environmental necessity but also a key driver of global economic transformation. Full article

In today’s rapidly evolving digital landscape, businesses are constantly under pressure to produce high-quality, engaging content for various marketing channels, including blog posts, social media updates, and email campaigns. However, the traditional manual content generation process is often time-consuming, resource-intensive, and inconsistent in maintaining the desired messaging and tone. As a result, the content production process can become a bottleneck, delay marketing campaigns, and reduce organizational agility. Furthermore, manual content generation introduces the risk of inconsistencies in tone, style, and messaging across different platforms and pieces of content. These inconsistencies can confuse the audience and dilute the message. We propose a hybrid approach for content generation based on the integration of Markov Chains with Semantic Technology (CGMCST). Based on the probabilistic nature of Markov chains, this approach allows an automated system to predict sequences of words and phrases, thereby generating coherent and contextually accurate content. Moreover, the application of semantic technology ensures that the generated content is semantically rich and maintains a consistent tone and style. Consistency across all marketing materials strengthens the message and enhances audience engagement. Automated content generation can scale effortlessly to meet increasing demands. The algorithm obtained an entropy of 9.6896 for the stationary distribution, indicating that the model can accurately predict the next word in sequences and generate coherent, contextually appropriate content that supports the efficacy of this novel CGMCST approach. The simulation was executed for a fixed time of 10,000 cycles, considering the weights based on the top three topics. These weights are determined both by the global document index and by term. The stationary distribution of the Markov chain for the top keywords, by stationary probability, includes a stationary distribution of “people” with a 0.004398 stationary distribution. Full article

Traditional approaches to predicting business cycles are limited by their omission of financial variables, which, in turn, leads to failures to signal financial-sector crises and to misestimate the duration and intensity of economic events. This study addresses this challenge by constructing a real-financial activity gap for South Africa and utilising it to predict the occurrence of economic recoveries. The study examines the period from 1970Q1 to 2023Q4, using real GDP, domestic credit, house prices, and share prices. The dynamic factor model and the Hodrick–Prescott filter are employed to construct the real-financial activity gap. The recursive ADF unit root test is used to assess the presence, frequency, and duration of economic recoveries. To validate the results, a Markov switching dynamic regression model is applied. The results reveal that the new gap tends to produce economic recovery predictions that are less frequent but longer in duration. In contrast, predictions based on real GDP lead to more frequent but shorter recoveries. The new gap suggests that financial variables contribute to stabilising growth over extended periods, whereas real GDP reflects quicker but more volatile economic adjustments. The latest gap offers a more stable basis for forecasting recoveries, aiding policymakers in better anticipating and mitigating economic downturns. Accordingly, the output gap and the real-financial activity gap should be used as complements. Full article

Being a crucial barometer of labour market stability, employment successfully predicts changes in business cycles, becoming a relevant indicator to policymakers and economists worldwide. The scope of this paper is to investigate the impact of socioeconomic and demographic factors on the employment rate in the European Union through a spatial approach, as well as to compare pre- and post-pandemic characteristics of European labour markets. A persistent North–South divide in employment was observed among the main findings, with Southern regions having lower employment rates and being more vulnerable to the pandemic shocks than Northern regions. Furthermore, the comparison between the spatial econometric models estimated for 2019 and 2022 showed a significant change in the influences of regional employment performance. These discoveries could be of interest to both governments and corporate decision-makers in order to elaborate knowledgeable policies and strategies regarding the labour force. Full article

The construction phase of buildings contributes significantly to greenhouse gas (GHG) emissions, yet mitigation strategies within the contractor’s scope—particularly those affecting transport, on-site energy use, and waste—remain underexplored in life cycle assessments (LCAs). This study develops a modelling framework to evaluate 20 mitigation strategies targeting modules A4 and A5 of the LCA, using a generalised business-as-usual (BAU) scenario derived from 15 representative archetypes based on 279 built projects and weighted by national construction statistics. Monte Carlo simulations are applied to capture variability in material composition and component distribution, and marginal abatement cost analysis is used to assess cost-effectiveness. The results show that transport-related strategies offer the highest mitigation potential under Danish conditions with minimal or negative costs, while waste strategies provide moderate reductions and often result in net savings. Energy strategies, though impactful in percentage terms, tend to have lower absolute reductions and higher costs. The applicability of strategies varies across building sizes, with economies of scale influencing feasibility. The modelling framework offers a structured basis for comparing mitigation actions by climate benefit and cost-efficiency, supporting strategic planning for low-carbon construction, while recognising that practical implementation depends on project-specific and organisational factors. Full article

This systematic literature review critically examines sustainability challenges and opportunities within fibre-based process industries (e.g., paper and nonwoven), pivotal energy-intensive sectors in the EU. Using an adapted PRISMA guideline, it analyses the evolution of sustainability concepts, key regulatory frameworks (e.g., European Green Deal, Corporate Sustainability Reporting Directive), and established management tools (e.g., ISO 50001, life cycle assessment). The review uncovers critical gaps, including a persistent lack of integrated approaches across environmental, economic, and social dimensions, alongside superficial strategic embedding of sustainability. Furthermore, regulatory fragmentation significantly hinders effective implementation. The study also highlights uneven technology adoption and practical obstacles for circular economy models, largely because sustainability often remains a parallel function rather than a core business driver. Ultimately, transformative sustainability demands integrated, sector-specific strategies, robust data, and strong leadership. This necessitates streamlined regulations, accelerated technology uptake, and enhanced multi-stakeholder collaboration, embedding sustainability into core business models beyond mere compliance. Full article

Although our world produces more than enough food, hunger and malnutrition remain widespread. This is not simply a problem of production—it is about how we manage and organize our food systems. Many researchers and practitioners see food security either as a business challenge to be solved with technical and managerial tools, or as a social movement rooted in justice, sovereignty, and sustainability. These two schools of thought rarely meet, and their disconnect holds back real progress. This paper brings these perspectives together, through the introduction of the “Managerial Architecture of Food Justice”—a new way to think about food management that does not pick sides but aims to transform how food systems are governed. By blending the best of strategic management with values of equity, agency, and ecological stewardship, this framework shows how management practices can help build food systems that are not only resilient and efficient, but also fair and truly sustainable. Grounded in public and collaborative governance theory, this approach provides practical steps for policymakers and food system leaders who want to break the cycle of hunger and injustice. The proposed model supports the Sustainable Development Goals by making sustainability defining features of food security efforts. Full article

Medical cannabis cultivation requires substantial energy for heating, lighting, and climate control. This study evaluates the economic feasibility of an innovative biomass-fired micro-CHP system in a greenhouse facility for medicinal cannabis cultivation. The system comprises an 80 kW_th boiler retrofitted for biomass and a 7 kW_el ORC engine and is assessed against a diesel-boiler Business-As-Usual (BAU) benchmark. Thermal load simulations for two growing periods (1 March–30 June and 1 September–30 December) estimate an annual heating demand of 91,065.20 kWh_th. The micro-CHP system delivers 8195.87 kWh_el per year, exceeding the greenhouse’s 7839.90 kWh_el consumption. Over a 30-year lifespan at a 7% discount rate, Life Cycle Costing yields EUR 196,421.33 for micro-CHP versus EUR 229,468.46 for BAU, a 14.4% reduction. Under all-equity financing, the project achieves an NPV of EUR 59,591.88, IRR of 27.32%, and a DPBP of 12.1 years; with 70% debt financing, NPV rises to EUR 61,211.39 and DPBP shortens to 10.5 years. Levelized Cost of Energy (LCOE) and Heat (LCOH) are EUR 0.122 per kWh_el and EUR 0.062 per kWh_th, respectively. While the LCOE is below the Greek and EU non-household averages (EUR 0.1578 and EUR 0.1515 per kWh_el), the LCOH exceeds the corresponding heat price benchmarks (EUR 0.0401 and EUR 0.0535 per kWh_th). These results indicate that, in the modeled context, biomass-ORC cogeneration can be a financially attractive and lower-carbon option for medicinal cannabis greenhouse operations. Full article

This study investigates the leverage effect and realized volatility (RV) of stocks in the presence of asymmetric jumps across economic expansions and contractions. We extend the heterogeneous autoregressive-realized volatility (HAR-RV) model by incorporating a two-period Markov regime-switching model to capture Taiwan’s economic expansion and contraction. Using Taiwan’s COVID-19 insurance-oversold events as a case–control setting, we compare the asymmetric jump risk effects on RV and realized semivariance (RSV). The results reveal that business cycle (BC) effects offset jump risk impacts, rendering intrinsic jump components statistically insignificant when BC information is omitted. During contraction periods, asymmetric jumps generate stronger negative RSV shocks, amplifying the leverage effect. Moreover, the predictive accuracy of RV critically depends on the prevailing business cycle state. By incorporating BC effects into the model, we recapture significant jump components and enhance volatility forecasting performance. Full article

The industrial motor systems account for 45% of global electricity consumption. A life cycle model is established to quantify the potential environmental benefits of typical adjustable permanent magnet drives (APMDs, 1250 kW) versus variable frequency drives (VFDs) in China. The model covers mining of metals, manufacturing, operation, and recycling phases of APMDs, incorporating empirical data from China’s 3232 coal-fired units. Four scenarios are set up: business-as-usual, moderate, aggressive, and full-retrofit. Key findings demonstrate that APMDs reduce operational energy consumption by 94.5% compared to VFDs through significantly declining frequency conversion losses and cooling requirements. The life cycle carbon emissions of APMDs (29.7 tonnes CO₂_eq) represent merely 5% of VFDs emissions (570 tonnes CO₂_eq), achieving a 95% reduction. Within APMDs’ footprint, recycling contributes a 45% emission offset (−13.3 tonnes CO₂-eq), while operational efficiency drives the majority of the reduction. Sensitivity analysis identifies electricity emission factors, NdFeB production emissions, and metal recycling rates as primary sensitivity drivers (sensitivity index ST = 0.80). Scenario simulations confirm that the aggressive retrofit strategy (covering high- and moderate-potential units) could reduce annual GHG emissions of 3.12 million tonnes CO₂_eq., with corresponding 89% decreases in particulate matter (PM). This research demonstrates that APMDs are an effective pathway for the low-carbon transition in coal power systems. Their large-scale implementation can potentially necessitate breakthroughs in tiered retrofit policies, thereby providing crucial technological support for industrial carbon neutrality. Full article