Search Results (100)

Consumer choices are largely influenced by sustainability, necessitating SMEs from the agri-food sector to strategically address sustainability and innovate their business models. Nonetheless, the challenge for such sustainable leadership lies in maintaining an equilibrium between innovation, sustainability, and financial performance. This study examined how strategic leadership fosters sustainability-oriented innovation within SMEs exemplified by the wine industry. A survey involving 354 German wineries served to analyze a multi-dimensional concept of innovation clusters (early adopters, pragmatists, pioneers, skeptics, conservatives), type of innovation, sustainability orientation, strategic ambitions, and business performance. Exploring the adoption of fungus-resistant grape varieties (FRV) allowed investigating how sustainability transitions to meet EU Green Deal targets are shaped by strategic groups involving strategic positioning and innovation clusters. There was a correlation between stronger sustainability orientation with greater innovation (Means up to 4.39). As per the findings, it was observed that high scores (p < 0.001, η² = 0.144–0.160) in market and process innovation were obtained by early adopters and pioneers. These innovation champions excel in economic and social sustainability (p < 0.001) but nonetheless were found to be financially underperforming (Means 1.97–2.18). Innovations that were applied enhanced innovation scores (η² = 0.128) but did not improve immediate performance. The strongest performance (Mean 2.60) was reported by skeptics though they fared poor in terms of sustainability and innovation. It was also noted that early adopters and pioneers (44–45%) were leading in FRV adoption, while a lag was observed within premium-oriented organizations. These insights may motivate SMEs in their quest for strategic sustainability and allow fine-tuning political and societal measures to achieve a sustainable transition and quantified Green Deal ambitions. It was concluded that long-term positioning was improved by sustainability-driven innovation, however, it would involve short-term performance trade-offs for SMEs. Political support should motivate the sustainable leadership champions to also safeguard profitability. Full article

This study investigates the role of Modern Management Accounting (MMA)—which integrates Strategic Management Accounting (SMA) and Strategic Customer Knowledge (SCK)—in driving Sustainable Competitive Advantage (SCA) and Business Sustainability (BS) in Thai green hotels. Business Sustainability is conceptualized as the achievement of balanced outcomes across economic performance, social responsibility, and environmental stewardship. It addresses a theoretical debate by testing two competing SCA models: a disaggregated model (which separates SCA into Customer Experience Advantage (CEA) and Operational Efficiency Advantage (OEA)) and a holistic model (which treats SCA as a unified construct). Data from 115 certified green hotels were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results revealed a critical distinction between the models. In the disaggregated model, SMA and SCK contributed to both CEA and OEA, but only OEA directly enhanced BS and served as a partial mediator in the relationships from both SMA and SCK to BS, whereas CEA showed no significant mediating effects. Conversely, the holistic model demonstrated that overall SCA served as a partial mediator in the relationships from both SMA and SCK to BS, while also exerting a strong direct effect on BS. The study concludes that achieving business sustainability requires a holistic SCA that integrates both operational efficiency and customer experience, offering a comprehensive framework for strategic management in the hotel industry. These findings underscore the strategic imperative for hotel managers to cultivate an integrated competitive advantage, where superior customer experiences and operational excellence are synergistically managed, to ensure long-term business sustainability. Full article

Two critical research problems emerge in creative education quality management: the framework misalignment problem, where business-oriented performance metrics inadequately assess design creativity and innovation, and the sustainability integration gap, reflecting limited incorporation of environmental and social sustainability dimensions into excellence models. This review article addresses these problems by developing an initial framework that adapts the Baldrige framework for urban design, architecture, art, and design education with integrated sustainability principles. Drawing on literature review and theoretical synthesis, the article proposes a framework that introduces three key epistemological shifts: prioritizing process over product, supporting non-linear and reflective learning pathways, and recognizing tacit, embodied, and experiential knowledge as central to creative education. The framework incorporates the United Nations Sustainable Development Goals (SDGs) as core design challenges and introduces innovative evaluation tools, including portfolios with iterative review processes, community feedback loops, and SDG mapping rubrics. This research contributes to the educational quality management literature by offering a systematic framework that bridges business excellence models with creative education paradigms while positioning sustainability as a core educational objective rather than a peripheral concern. Full article

Water use and water environmental protection exhibit highly complex interactions, and their coupling coordination is essential for long-term urban sustainability. This study analyzes the system structure of water utilization, and constructs a water resources–social economy–water environment (WR-SE-WE) system dynamics model for Tianjin and five policy scenarios (business as usual (BAU), water conservation prioritization (WCP), social–economic advancement (SEA), water environmental protection (WEP), and integrated balanced development (IBD)) are simulated. A coupling coordination degree (CCD) model is employed to evaluate scenario performance. The key results show that Tianjin’s WR-SE-WE CCD keeps increasing but differentiates for different scenarios: IBD consistently outperforms all scenarios, achieving an optimal coupling coordination degree of 0.926 by 2035, while the other scenarios rank SEA (0.920) > WEP (0.902) > BAU (0.880) > WCP (0.874). The indicators’ quantitative results exhibit single-policy scenario trade-offs: WCP maximizes water efficiency and pollution control, but severely constrains social economy, offering a temporary solution. WEP excels in water resources supply but limits GDP growth, serving as an effective interim measure. SEA drives rapid economic expansion but strains resources and delays pollution control, making it suitable for long-term planning. Combining the obstacle degree model, four recommendations are proposed, including implementing cross-sector water governance, accelerating the green industrial transition, prioritizing reclaimed water, and scaling agricultural efficiency. These results provide a scientific basis for promoting high-quality regional development in the future. Full article

Emerging markets face growing pressures to integrate sustainable English business practices while maintaining economic growth, particularly in addressing environmental challenges and achieving carbon neutrality goals. English Financial information extraction becomes crucial for supporting green finance initiatives, Environmental, Social, and Governance (ESG) compliance, and sustainable investment decisions in these markets. This paper presents FinATG, an AI-driven autoregressive framework for extracting sustainability-related English financial information from English texts, specifically designed to support emerging markets in their transition toward sustainable development. The framework addresses the complex challenges of processing ESG reports, green bond disclosures, carbon footprint assessments, and sustainable investment documentation prevalent in emerging economies. FinATG introduces a domain-adaptive span representation method fine-tuned on sustainability-focused English financial corpora, implements constrained decoding mechanisms based on green finance regulations, and integrates FinBERT with autoregressive generation for end-to-end extraction of environmental and governance information. While achieving competitive performance on standard benchmarks, FinATG’s primary contribution lies in its architecture, which prioritizes correctness and compliance for the high-stakes financial domain. Experimental validation demonstrates FinATG’s effectiveness with entity F1 scores of 88.5 and REL F1 scores of 80.2 on standard English datasets, while achieving superior performance (85.7–86.0 entity F1, 73.1–74.0 REL+ F1) on sustainability-focused financial datasets. The framework particularly excels in extracting carbon emission data, green investment relationships, and ESG compliance indicators, achieving average AUC and RGR scores of 0.93 and 0.89 respectively. By automating the extraction of sustainability metrics from complex English financial documents, FinATG supports emerging markets in meeting international ESG standards, facilitating green finance flows, and enhancing transparency in sustainable business practices, ultimately contributing to their sustainable development goals and climate action commitments. Full article

The Internet of Things (IoT) is one of the pivotal technologies driving the digital transformation of industry, business, and personal life. Along with new opportunities, the exponential growth of IoT devices also brings environmental challenges, driven by the increasing accumulation of e-waste. This paper introduces a novel, compact, cubic-shaped rectenna with a 3D-printed composite substrate featuring five identical patches. The design aims to integrate RF energy harvesting technology with eco-friendly materials, enabling its application in powering next-generation sustainable IoT systems. Due to its symmetrical design, each patch antenna achieves a bandwidth of 130 MHz within the frequency range of 2.4 GHz to 2.57 GHz, with a maximum efficiency of 60.5% and an excellent isolation of below −25 dB between adjacent patch antennas. Furthermore, measurements of the rectifier circuit indicate a maximum conversion efficiency of 33%, which is comparable to that of other rectennas made on 3D-printed substrates. The proposed visually unobtrusive design not only enhances compactness but also allows the proposed rectenna to harvest RF energy from nearly all directions. Full article

In today’s volatile market environment, supply chain management (SCM) must address complex challenges such as fluctuating demand, fraud, and delivery delays. This study applies machine learning techniques—Extreme Gradient Boosting (XGBoost) and Recurrent Neural Networks (RNNs)—to optimize demand forecasting, inventory policies, and risk mitigation within a unified framework. XGBoost achieves high forecasting accuracy (MAE = 0.1571, MAPE = 0.48%), while RNNs excel at fraud detection and late delivery prediction (F1-score ≈ 98%). To evaluate models beyond accuracy, we introduce two novel metrics: Cost–Accuracy Efficiency (CAE) and CAE-ESG, which combine predictive performance with cost-efficiency and ESG alignment. These holistic measures support sustainable model selection aligned with the ISO 14001, GRI, and SASB benchmarks; they also demonstrate that, despite lower accuracy, Random Forest achieves the highest CAE-ESG score due to its low complexity and strong ESG profile. We also apply SHAP analysis to improve model interpretability and demonstrate business impact through enhanced Customer Lifetime Value (CLV) and reduced churn. This research offers a practical, interpretable, and sustainability-aware ML framework for supply chains, enabling more resilient, cost-effective, and responsible decision-making. Full article

Management 5.0 represents a new paradigm in business strategy and leadership that integrates sustainability, advanced digital technologies, and human-centered decision-making. The article explores the application of machine learning technologies for forecasting demand for eco-friendly vehicles as a key tool for enhancing manufacturers’ competitiveness. This research supports key UN Sustainable Development Goals (SDGs), including SDG 7 (Clean Energy), SDG 9 (Innovation and Infrastructure), SDG 11 (Sustainable Cities), and SDG 12 (Responsible Consumption). Based on an analysis of the European market from 2019 to 2023 and forecasting through 2027, a comprehensive approach was developed using ARIMA, Prophet, and Random Forest models. Empirical findings indicate that implementing predictive analytics can reduce inventory costs by 18–25% and optimize working capital by 15–20%. Model performance varied by market type: Random Forest excelled in smaller markets, while Prophet delivered strong results in trend-stable environments. The results confirm that accurate demand forecasting, supported by machine learning technologies, creates significant competitive advantages in the era of management 5.0 through production process optimization and improved market positioning. Full article

Corporate Social Responsibility (CSR) and its sustainability-focused communications are now recognized as essential corporate activities. As society increasingly holds firms accountable for their social, environmental, and sustainability impacts, academic interest in CSR communications has similarly grown, with scholars exploring how CSR communication influences stakeholder engagement and corporate strategies. In response to this growing interest, we conducted a systematic literature review utilizing bibliometric analysis to identify and examine publication trends and patterns in CSR and CSR-associated communications, drawing from a robust dataset of 3513 documents extracted from Scopus and Web of Science. The analysis was conducted using the Biblioshiny R package and Excel to ensure methodological precision and analytical depth. We explored the characteristics of publications related to topics such as business, authorship, and journals over a four-decade period spanning from 1984 to 2024. Our results reveal four strategic clusters of CSR disclosure, reflecting a shift from symbolic to strategic and stakeholder-focused communication. Thematic evolution highlights the growing integration of ESG frameworks and digital reporting practices. This study is significant not only in its methodological rigor but also in its timely contribution to the intersection of CSR, sustainability, and strategic communication. Also, this study introduces a new theoretical framework through the CSR strategic disclosure indicator metric, which connects the level of disclosure maturity with the focus on different stakeholder groups. We discuss the implications of our findings not only for future scholarly research in CSR but also for corporate sustainability practitioners who look to academia for insights on emerging trends in CSR and CSR reporting. Full article

Energy storage technology is a critical component in supporting the construction of new power systems and promoting the low-carbon transformation of the energy system. Currently, new energy storage in China is in a pivotal transition phase from research and demonstration to the initial stage of commercialization. However, it still faces numerous challenges, including incomplete business models, inadequate institutional policies, and unclear cost and revenue recovery mechanisms, particularly on the generation and grid sides. Therefore, this paper focuses on grid-side new energy storage technologies, selecting typical operational scenarios to analyze and compare their business models. Based on the lifecycle assessment method and techno-economic theories, the costs and benefits of various new energy storage technologies are compared and analyzed. This study aims to provide rational suggestions and incentive policies to enhance the technological maturity and economic feasibility of grid-side energy storage, improve cost recovery mechanisms, and promote the sustainable development of power grids. The results indicate that grid-side energy storage business models are becoming increasingly diversified, with typical models including shared leasing, spot market arbitrage, capacity price compensation, unilateral dispatch, and bilateral trading. From the perspectives of economic efficiency and technological maturity, lithium-ion batteries exhibit significant advantages in enhancing renewable energy consumption due to their low initial investment, high returns, and fast response. Compressed air and vanadium redox flow batteries excel in long-duration storage and cycle life. While molten salt and hydrogen storage face higher financial risks, they show prominent potential in cross-seasonal storage and low-carbon transformation. The sensitivity analysis indicates that the peak–valley electricity price differential and the unit investment cost of installed capacity are the key variables influencing the economic viability of grid-side energy storage. The charge–discharge efficiency and storage lifespan affect long-term returns, while technological advancements and market optimization are expected to further enhance the economic performance of energy storage systems, promoting their commercial application in electricity markets. Full article

Developing nations like Bangladesh have yet to adopt hybrid (HEVs) or electric vehicles (EVs) for goods carrying, whereas environmental pollution and fuel costs are hitting hard. The electrically powered cars and trucks market promises an excellent opportunity for environmentally friendly transportation. However, these countries’ inadequate infrastructure, substantial initial expenses, and insufficient policies impeding widespread acceptance hold market growth back. This study examines the current status of the electric car market in low- and middle-income developing nations like Bangladesh, focusing on the infrastructure and regulatory framework-related barriers and the aspects of growth promotion. To promote an expanding hybrid and EV ecosystem, this article outlines recent studies and identifies critical regions where support for policy and infrastructural developments is needed. It discusses how developing nations may adapt successful international practices to suit their specific needs. At the same time, the research adopted system dynamics and case study methods to assess the transportation fleet (142 vehicles) of a livestock farm and find the feasibility of adopting HEVs and EVs. Several instances are improving infrastructures for recharging, providing incentives for lowering the adoption process cost, and creating appropriate regulatory structures that promote corporate and consumer involvement. Findings highlight how crucial it is for governments, businesses, customers, and international bodies to collaborate to build an affordable and sustainable EV network. The investigation concludes with recommendations for more research and appropriate regulations that may accelerate the adoption of EVs, reduce their adverse impacts on the environment, and promote economic growth. Full article

Contemporary ports are facing a variety of challenges due to technological advancements, economic pressures, and changing policies. Key issues include the effects of globalization, rapid advancements in information and communication technologies (ICTs), and the changing nature of port services. In order to tackle these challenges and achieve operational excellence, adapt to the shifting of activities, and meet new business demands, smart ports have been proposed as a comprehensive solution. These challenges arise because port success is often measured by traditional metrics such as port size and performance. To accurately assess the intelligence of a port, there is a need for a systematic and scientifically sound smart port evaluation method. This paper provides an overview of the concept of a smart port and develops a multi-criteria assessment framework of port smartness based on neutrosophic cognitive maps (NCMs). The unique and valuable characteristic of NCMs lies in their ability to manage the uncertainty associated with the relationship between two concepts, indicating their effects on each other in neutral states. This structure enables the NCM to provide results with a greater degree of sensitivity than fuzzy cognitive maps (FCMs) and allows for a greater degree of freedom of intuition for an expert to express not only the potential impacts but also the uncertainty associated with those impacts. Our methodology can make decisions using incomplete, uncertain, and inconsistent data during the assessment process, providing a rigorous quantitative framework for the assessment of port “smartness”. The proposed solution has the potential to act as a valuable tool in a group decision support environment and can be used to accelerate an organization’s development, improve productivity, and reinforce efforts to achieve strategic and sustainability objectives. To achieve this, an appropriate framework for such a methodology is demonstrated through an illustrative example offering actionable insights for improving port operations. Full article

Artificial intelligence (AI) is increasingly essential for optimizing energy systems, addressing the growing complexity of energy management, and supporting the integration of diverse renewable sources. This study systematically reviews AI-enabled modeling approaches, highlighting their applications, limitations, and potential in advancing sustainable energy systems while offering insights and a framework for addressing real-world energy challenges. Data-driven models excel in energy demand prediction and resource optimization but face criticism for their “black-box” nature, while mechanism-driven models provide deeper system insights but require significant computation and domain expertise. To bridge the gap between these approaches, hybrid models combine the strengths of both, improving prediction accuracy, adaptability, and overall system optimization. This study discusses the policy background, modeling approaches, and key challenges in AI-enabled energy system modeling. Furthermore, this study highlights how AI-enabled techniques are paving the way for future energy system modeling, including integration and optimization for renewable energy systems, real-time optimization and predictive maintenance through digital twins, advanced demand-side management for optimal energy use, and hybrid simulation of energy markets and business behavior. Full article

(1) Background: With the growing severity of global environmental issues and increasing consumer health consciousness, green consumption has become a prominent focus in both research and practice. However, studies on the mechanisms of health consciousness and environmental awareness influencing the purchase intentions of sports enthusiasts toward sustainable sports products remain relatively limited. This study investigates how health consciousness and environmental awareness impact the green consumption behavior of sports enthusiasts through psychological pathways, including attitude, subjective norm, and perceived behavioral control, aiming to reveal their underlying mechanisms. (2) Methods: Based on the extended Theory of Planned Behavior (TPB), this study developed a theoretical model incorporating health consciousness and environmental awareness. Data were collected via a questionnaire survey, yielding 407 valid responses. The sample was gender-balanced (52.8% male, 47.2% female), predominantly consisting of young individuals aged 26–35 (44.7%) and 18–25 (28.0%), with primary occupations being company employees/managers (46.2%) and students/teachers (25.3%). The collected data were analyzed using SPSS and AMOS software to systematically evaluate the research hypotheses and the model’s applicability. (3) Results: The model exhibited excellent fit indices, with a χ²/df value of 2.129, an RMSEA value of 0.053, an RMR value of 0.029, and GFI, CFI, NFI, and NNFI values all exceeding 0.90, indicating that the model structure adequately explained the relationships among latent variables. All research hypotheses were significantly supported (p < 0.01), demonstrating that health consciousness and environmental awareness not only directly influence purchase intentions but also exert significant indirect effects through attitude, subjective norm, and perceived behavioral control. (4) Conclusions: Health consciousness and environmental awareness are critical drivers of sports enthusiasts’ purchasing behavior for sustainable sports products. This study deepens the understanding of the mechanisms underlying green consumption behavior and offers practical implications for related businesses. Companies should enhance product healthiness and environmental friendliness while optimizing consumer psychological perceptions to increase purchase intentions. Full article

The purpose of this study is to analyze the mission statements of 49 companies listed on the Palestine Exchange (PEX), focusing on their structure and alignment with environmental, social, and governance (ESG) principles. The primary objective of this research was to evaluate the extent to which Palestinian companies embed sustainability issues into their mission statements. This was done with a qualitative research design and a descriptive content analysis method, letting mission statements from different fields be looked at in excellent detail. This analysis offers valuable insights into how Palestinian companies articulate their strategic goals and communicate their commitment to ESG factors. The findings reveal that Palestinian companies demonstrate a clear understanding of sustainability and its relevance to their operations. A lot of companies are also working hard to include sustainability principles in their mission statements. This shows that people are becoming more aware of how important ESG factors are for shaping business strategy and creating long-term value. Full article