Search Results (1,424)

The accelerated growth of e-commerce has intensified the dual challenges of weak infrastructure and carbon emission pressures in last-mile delivery for rural and mountainous regions. As the World Bank calls for integrating carbon market development into national strategies, Truck-Drone Collaborative Delivery (TDCD) has emerged as a critical sustainable solution. However, existing research often overlooks the strict airspace regulations in sensitive border areas. Therefore, this paper proposes a Vehicle Routing Problem with Drones and Mobile Base Stations (VRPDBS) model that explicitly incorporates airspace constraints and mobile hub deployment. We introduce a quantified “Regional Flyability Factor” ($f_k$) to measure the impact of airspace restrictions on routing decisions and solve the problem using a hybrid metaheuristic algorithm. A case study based on real-world data from the Yanbian Korean Autonomous Prefecture reveals that strict airspace compliance imposes an absolute delivery delay of 4–5 h and an operational cost premium of up to 15%, an impact that can be effectively mitigated through a mobile base station mediation strategy. More importantly, multi-scenario sensitivity analysis under carbon price uncertainty indicates that although truck-dominant modes are cost-effective at current low carbon prices, drone-intensive configurations demonstrate superior economic robustness and environmental performance under high carbon price scenarios. This study not only provides a technical framework for green logistics planning in complex airspace but also offers strategic decision support for logistics enterprises to navigate long-term climate policy risks. Full article

The life insurance sector plays a critical role in financial system stability but is inherently exposed to extreme market fluctuations due to long-term liabilities and asset–liability mismatches. This study investigates extreme losses in the growth rates of the JSE Life Insurance Price Index (LIPI) using the Generalised Extreme Value Distribution (GEVD) and the Generalised Pareto Distribution (GPD) under the Extreme Value Theory (EVT) framework. Monthly data from January 2000 to October 2023 were transformed into a loss series, and extreme events were captured using quarterly block maxima and a POT threshold at the 95th percentile. Model parameters were estimated through Maximum Likelihood Estimation, and downside risk was assessed using return levels, Value-at-Risk (VaR), and Tail Value-at-Risk (tVaR). The GEVD model produced a negative shape parameter, consistent with a bounded Weibull-type tail, while the GPD indicated a heavy-tailed distribution. Return level estimates show escalating loss magnitudes and widening uncertainty over longer horizons, reflecting the challenges of projecting rare events. Kupiec backtesting confirms the adequacy and reliability of the GEVD-based VaR across all confidence levels, whereas the GPD underestimates risk at lower thresholds. These findings indicate significant tail risk within the South African life insurance equity segment and underscore the importance of EVT-based risk measures for capital planning and regulatory oversight. The study contributes to financial risk modelling in the life insurance sector and offers practical insights for strengthening solvency assessment and enterprise risk management frameworks. Full article

Based on the panel data of Chinese A-share listed companies from 2012 to 2023, this paper takes the pilot policy of Pilot Zones for Innovative Application of Artificial Intelligence as an exogenous shock, and adopts a multi-period difference-in-differences (DID) model to systematically examine the causal effect of this policy on the quality and efficiency of enterprise innovation and its mechanism of action. It is found that the Pilot Zones for Innovative Application of Artificial Intelligence significantly improve enterprises’ innovation quality and efficiency. Mechanism tests show that the pilot policy enhances enterprise innovation quality and efficiency by driving digital transformation, eliminating information barriers, and upgrading supply chain collaboration. Heterogeneity analysis confirms that the policy dividends are more fully released in non-state-owned enterprises, high-tech enterprises, labor-intensive and technology-intensive enterprises, as well as enterprises located in cities with a higher degree of marketization. In addition, the life-cycle heterogeneity analysis shows that the pilot policy exerts the strongest and most comprehensive innovation-promoting effect on maturity-stage firms, mainly improves innovation efficiency for decline-stage firms, and does not produce significant effects for growth-stage firms. The findings offer practical insights for policymakers and local governments in refining AI-related innovation policies and pilot-zone implementation, and for enterprise managers in strategically adopting AI to strengthen innovation capability and long-term sustainable development. Full article

Digital village construction (DVC) is an important tool for promoting rural revitalization and increasing farmers’ income. This paper selects panel data at the county level and employs the difference-in-differences (DID) method, combined with mediation effect models, heterogeneity tests, and multi-dimensional robustness tests, to systematically explore the impact of DVC on farmers’ income and its internal transmission path. According to the research, the DVC has a positive impact on farmers’ income at the 1% significance level, a conclusion that remains valid after robustness tests such as PSM-DID and substitution of the explained variable. Industrial restructuring, agricultural mechanization, and enterprise agglomeration are positively significant at the 5%, 1%, and 1% levels, respectively, indicating that these three are the core intermediary mechanisms for increasing farmers’ income, promoting farmers’ income growth by releasing structural dividends, efficiency dividends, and agglomeration dividends, respectively. The income-increasing effect of DVC exhibits significant heterogeneity, being positively significant at the 5% and 1% levels in areas with a deep digital divide and non-grain-producing areas, but not significant in areas with a shallow digital divide and major grain-producing areas. Therefore, policy recommendations are to optimize resource allocation, broaden income-increasing pathways, and implement differentiated policies. Full article

Using 29,278 firm-year observations of Chinese A-share listed firms from 2012 to 2023, this study examines whether data assetisation improves corporate investment efficiency and whether bank fintech conditions shape this relationship. Data assetisation refers to the process through which firms transform data resources into economically valuable, governable, and deployable assets. We construct a text-based proxy from annual reports using a Word2Vec-expanded lexicon and further distinguish between own-use and transactional data assets. The study finds: (1) Data assetisation significantly enhances corporate investment efficiency, with self-use data assets demonstrating a stronger driving effect. (2) Mechanism analysis reveals that data assetisation alleviates underinvestment by easing financing constraints and leveraging the “talent effect”. Concurrently, it mitigates overinvestment by reducing agency problems and accelerating digital transformation, thereby enhancing investment efficiency. (3) Heterogeneity tests indicate that the positive impact of data assetisation on investment efficiency is more pronounced among growth-stage enterprises, technology-intensive firms, and companies operating in regions with high bank liquidity. (4) Banking fintech positively moderates the enhancement of corporate investment efficiency through data assetisation, with a more pronounced effect on alleviating underinvestment. However, it may also exacerbate overinvestment. This study contributes to sustainable economic development by improving resource allocation efficiency, reducing capital misallocation, and supporting high-quality, low-waste, and sustainable growth of the real economy. Consequently, enterprises should vigorously develop data assetisation, applying different types of data assets to specific use cases to unlock data dividends. This approach supports the scientific development of corporate investment decisions and enhances investment efficiency, laying a micro-level foundation for sustainable socio-economic development. Full article

This article analyzes the scale, fluctuations and geographical distribution of olive (Olea europaea) cultivation in Palestine over 550 years, from the Late Mamluk period (1300–1517), through the Ottoman era (1517–1917), until the end of the British Mandate in 1947. Although olive oil played a dominant role in the diet and the local economy, there is currently no research that measures and quantifies the number of olive trees or the number of villages and towns that cultivated olive trees and produced olive oil. We reconstruct the agricultural landscape with its vast olive groves and examine the cultural history of olive tree farming, the growth of the olive oil industries and their economic role and importance. The earliest figures we have, that are from the year 1596, show that 400 villages cultivated 1,400,794 olive trees. By 1943, there were 6,053,367 olive trees that were cultivated by 644 villages. We found a strong correlation (R² = 0.96, p < 0.01) between the number of olive trees and the number of villages, indicating that olive oil demand and the olive oil industry align with population size. The research data derives from a variety of medieval local chroniclers, as well as diaries by European, North African and Middle Eastern travelers who provide descriptions of olive groves and the olive oil industry. Among the most important sources are the 1596 Ottoman tax registers. The tax registers are the first document that present clear-cut figures on the numbers of olive trees, olive presses and the names of the villages that cultivated olive groves. The main sources for the last period dealt with in this study are the British Mandate maps (1943), which display the acreage of the different crops across Palestine. The data from the maps is supplemented by two modern works on olive cultivation written by agronomists Assaf Goor (b. 1894) and Ali Nasouh (b. 1906) who were born in Palestine and employed by the British department of agriculture. The analysis of data shows that demands of local and oversea markets; the olive oil soap industry, which was based on the local olive oil; as well as competing agricultural crops like sugarcane, cotton and citrus, contributed to a complex economic structure. Olive tree cultivation did not depend on government investment. Olive groves in Palestine were rain fed, and, except for the harvest, they required relatively few working days a year. Hence, moderate policies (low taxation during periods of drought and low yields) adopted by enterprising local rulers and the central British government created a unique and relatively balanced relationship between rulers and farmers, which encouraged olive cultivation and led to a constant increase in the number of olive trees and the development of the olive oil industry. Full article

Human-centered entrepreneurship considers employee well-being and uses the Sustainable Development Goals as its fundamental pillars. However, existing research predominantly focuses on institutional interventions and fails to provide integrated intelligent solutions for tackling human–machine collaboration issues in the context of digital transformation. Large language models (LLMs) offer potential for affective computing and personalized support, but face critical gaps in ethical governance, privacy protection, and real-time risk intervention in sensitive entrepreneurial contexts. Our proposed Human-Centered Entrepreneurial Intelligent Agent (HCEA) framework achieves the unified optimization of task utility, empathetic expression, and ethical security by integrating a large language model core fine-tuned via a multi-objective hybrid loss function and a cluster of task-specialized intelligent agents. HCEA integrates retrieval-enhanced generation to ensure suggestion accuracy, a hierarchical data governance system for sensitivity-based privacy protection, and an independent risk detection module for real-time intervention and referral. We build the framework by constructing a hybrid entrepreneurial dataset, design the multi-agent architecture of decision support, emotion understanding and ethical risk tracking, and empirically evaluate both comparisons and ablation experiments. The results demonstrate that HCEA outperforms five baseline models across six key metrics, including entrepreneurship guidance relevance, emotion recognition, and high-risk recall. This study contributes to the intersection of digital transformation and sustainable entrepreneurship by providing a technically feasible, ethically grounded intelligent framework that empowers enterprises to reconcile efficiency with human-centric values, advancing SDG 8 (decent work and economic growth) and SDG 9 (industry, innovation, and infrastructure). Full article

Generative artificial intelligence (GenAI) is increasingly portrayed as a transformative technology capable of simultaneously enhancing operational efficiency and enabling strategic growth. Yet small and medium-sized enterprises (SMEs) experience heterogeneous outcomes, suggesting that GenAI does not generate value uniformly across firms. This study develops and empirically informs a contingency framework explaining how distinct GenAI functions relate to differentiated strategic objectives and how technological, organizational, and environmental (TOE) readiness conditions shape this relationship. Using a three-round Delphi study with an interdisciplinary expert panel, including GenAI consultants, corporate managers, legal experts, academic researchers, and public-sector policymakers, we identify six core GenAI functional domains associated with efficiency-oriented and growth-oriented strategies. The findings suggest that operational automation and data intelligence are more strongly associated with efficiency objectives, whereas market intelligence, market testing, linguistic expansion, and idea generation are more closely related to growth objectives, although none is exclusively linked to a single strategic goal. Importantly, TOE readiness is found to play a key role in shaping the extent to which function-specific GenAI deployment translates into realized strategic value, with organizational readiness appearing more prominent than technological or environmental conditions. By shifting the focus from adoption to function-specific strategic alignment and readiness configurations, this study advances understanding of GenAI-enabled strategic value realization and heterogeneous transformation pathways in SMEs. Full article

This study provides a model-based exploratory assessment of the economic impact attributable to coccidiosis within the Turkish broiler sector. Primary data were obtained from 117 commercial enterprises (total capacity: 1,666,000 broilers) across the Mediterranean, Marmara, and Central Anatolia regions during the 2024 production cycle. Epidemiological analysis estimated a disease prevalence of 13% within the sampled population. The economic impact was evaluated using a stochastic modeling framework informed by Monte Carlo simulation and integrated with the Delphi method. Total national financial losses in Türkiye were estimated to reach a mean of $15.1 million in the most likely scenario (with a probabilistic range extending from $3.3 million under optimistic assumptions to $46.3 million under pessimistic conditions). The model-estimated average financial burden per animal was approximately $0.41 (representing an estimated $2.06 per clinically infected bird). Notably, projections suggest that roughly 62% of this economic impact could be attributed to subclinical factors, characterized by a modeled 5% (150 g) reduction in live weight and an estimated 8% (274 g) increase in feed consumption due to impaired Feed Conversion Ratio. The mortality rate within the modeled scenarios was calibrated at 8%. These findings suggest a substantial potential economic burden on the poultry industry. The analysis indicates that the majority of financial losses may stem from subclinical performance declines—specifically, impaired Feed Conversion Ratio and reduced growth—rather than acute mortality. These projections emphasize the urgent need for enhanced preventative strategies and subclinical monitoring to mitigate the estimated economic impact in Türkiye. Full article

Small- and medium-sized commercial banks constitute a fundamental component of the financial system, and their corporate governance plays a critical role in the modernization of financial governance. Over the past two decades, these banks have largely established a modern enterprise framework, typically structured around shareholders’ meetings, boards of directors, supervisory boards, and senior management (SBSS). This governance arrangement has supported sustained institutional growth; however, persistent challenges have emerged, including the accumulation of non-performing assets and the increasing frequency of risk events. These problems cannot be attributed solely to market or operational factors, but are also closely related to limitations in the top-level design and practical functioning of the SBSS governance structure. In particular, a notable gap exists between the original design objectives of the modern enterprise system and its actual governance outcomes in practice. This study adopts an institutional and analytical approach, supported by descriptive regulatory statistics, to examine governance deficiencies in small- and medium-sized commercial banks. By introducing French state-led governance culture as an institutional reference, the paper conceptualizes non-shareholder-centered governance arrangements under strong public involvement and proposes an embedded governance framework emphasizing accountability, supervision, and information integration. Full article

Whether artificial intelligence (AI) can effectively enhance the operational resilience (OR) of enterprises is of great significance for the manufacturing industry to resist risks and achieve sustainable development. Employing a staggered difference-in-differences (DID) model, this paper utilizes data from Chinese A-share listed manufacturing companies from 2012 to 2023 and takes the National Artificial Intelligence Innovative Application Pioneer Zone (AIIAPZ) policy as a quasi-natural experiment to examine the impact of AI applications on the OR of enterprises. The results indicate that AI significantly enhances corporate OR. Mechanism tests reveal that AI promotes OR by reducing management agency conflicts and optimizing supply chain allocation performance. Heterogeneity analysis shows that the enabling effect of AI is more pronounced for enterprises located in the coastal eastern region, those in the growth stage, and those that are technology-intensive and capital-intensive. Further analysis indicates that the improvement in OR effectively reduces corporate operational risk and enhances their capacity for sustainable development. This study provides crucial insights for enterprises to explore synergistic pathways integrating intelligentization and promoting OR under the AIIAPZ framework. Full article

This study investigates the determinants of FinTech adoption and its role in supporting financial inclusion among micro, small, and medium enterprises (MSMEs) in South Sumatra, Indonesia. The analysis applies an extended Unified Theory of Acceptance and Use of Technology (UTAUT) framework that incorporates digital financial literacy, artificial intelligence literacy, green self-identity, and perceived green finance. Data from 632 MSMEs, comprising 377 rural and 255 urban enterprises, were analyzed using partial least squares structural equation modeling (PLS-SEM), multi-group analysis (MGA), and importance performance map analysis (IPMA). The results indicate that facilitating conditions represent the most influential determinant of FinTech adoption among rural MSMEs, while effort expectancy emerges as the dominant factor in urban enterprises. FinTech adoption also significantly strengthens both FinTech continuance intention and financial inclusion across the two groups, highlighting the role of digital financial technologies in promoting inclusive economic development. In addition, the IPMA shows that rural MSMEs place strong emphasis on facilitating conditions as the key driver of FinTech adoption, whereas urban MSMEs prioritize effort expectancy. By extending the UTAUT framework with sustainability-related constructs, this study provides new evidence on how digital financial innovation can support inclusive growth and contribute to Sustainable Development Goal 8. Full article

Integration of informatization and industrialization (IoII) is a pivotal sustainable strategy in China, aimed at industrial modernization and high-quality economic development, which accelerates enterprise digitalization. This paper explores the economic impacts of China’s integration of informatization and industrialization (IoII) policy on enterprises’ environmental, social, and governance (ESG) performance, a core indicator of corporate sustainability. Employing the quasi-natural experiment setting offered by the pilot policy of “Integration of Informatization and Industrialization (IoII)” in China, this paper explores the effects of the IoII on corporate ESG performance through effect analysis, mechanism identification, and heterogeneity test, utilizing the data from A-share listed companies in China. Using the difference-in-differences (DID) analysis, the results suggest that the IoII significantly contributes to improving corporate ESG performance, primarily driven by improvements in the environmental (E) and governance (G) dimensions, while the social (S) dimension is not significantly affected, thereby enhancing long-term sustainability competitiveness. The findings from the mechanism identification indicate that the IoII can promote corporate ESG performance through the three mechanisms: green innovation, corporate governance, and information transparency, all of which underpin sustainable operational practices. The heterogeneity tests reveal that the IoII promotes corporate ESG performance more effectively in high-tech enterprises, non-SOEs, and enterprises with low growth rates, implying differentiated paths for sustainability-driven digital upgrading. By linking industrial digital integration with corporate sustainability, this study enriches the understanding of ESG determinants and provides meaningful implications for sustainability-oriented digital transformation. Full article

In South Africa, both economic and social entrepreneurship have become a game-changing strategy for tackling enduring socioeconomic issues, including inequality, unemployment, and poverty. In contrast to conventional business models that put profit maximisation first, social entrepreneurship combines entrepreneurial tactics with social goals to develop long-lasting solutions for underserved populations. This study examines how social entrepreneurship can be used to address socioeconomic problems in South Africa, highlighting how it can promote inclusive growth and help achieve both national and international development objectives. The study illustrates how social companies use innovation and community participation models to overcome structural impediments such as youth unemployment, healthcare disparities, and limited access to education. It is based on a thorough evaluation of academic literature. The results show that social entrepreneurship fosters social cohesiveness and resilience in marginalised areas in addition to creating job and income opportunities. However, issues including weak finance, insufficient policy frameworks, and a dearth of capacity-building programmes make it difficult for social enterprises to grow and survive. In order to strengthen the social enterprise sector, the study’s conclusion suggests creating supportive ecosystems through impact investments, policy reforms, and educational initiatives. South Africa can expedite its efforts to reduce inequality and achieve sustained socioeconomic transformation by presenting social entrepreneurship as a strategic development tool. Full article

Against the backdrop of climate commitment goal and global warming, this study examines the heterogeneous impacts of Environmental (E), Social (S), and Governance (G) pillars on the financial performance of Chinese new energy vehicle (NEV) firms. Using panel data from 2009 to 2024 and a two-way fixed effects model, we find that all three ESG pillars are significantly associated with financial performance, with Governance exhibiting the strongest effect. Mechanism analyses reveal that government subsidies, analyst attention, and innovation capability mediate the effects of E, S, and G pillars, respectively. Further heterogeneity analysis from the perspective of the firm life cycle reveals stage-dependent effects. The Environmental (E) pillar exerts the most prominent positive effect in the maturity stage; the impact of the Social (S) pillar gradually strengthens and peaks in the decline stage; and the Governance (G) pillar demonstrates stronger driving effects in both the growth and decline stages. This study enriches the literature on ESG value effects by introducing a life cycle perspective and provides empirical evidence for NEV enterprises to formulate differentiated ESG strategies. Full article