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Small-scale artisanal fisheries perform great economic, social, cultural, and ecological roles worldwide. For fishers in adverse scenarios, resorting to alternatives such sustainable tourism is widely proposed. In this study, we investigate the long-term sustainability (1998–2020) of a small-scale artisanal fishery in Northeast Brazil, where transformations including intense coastal development, the establishment of a marine protected area, and the expansion of tourism occurred in addition to the region's economic growth and the global trend of technological advancements. This study aims to understand how this fishery has changed over the last two decades while investigating a range of possible threats for its survival. Results demonstrated the impacts of technological innovation on fishing practices, such as the use of spearguns and small outboard motors; an increase in opportunistic fishing associated with a growing coastal population; fading of certain traditional fishing practices that often require fishers with greater experience; a shift for a fishery made up of more opportunistic amateur fishers, as artisanal, small-scale fishers switched to other income sources such as tourism. Although there are benefits from those transformations, which include the possibility of an alternative source of income and the use of technology, fisheries traditions have been affected negatively in terms of social and cultural aspects, and traditional fishing communities are left vulnerable in the absence of national fishery monitoring programs, reliable fishing data, and institutional instability. Local initiatives and empowerment of traditional fishing communities to strengthen fisher identity and participation in fisheries policy decision-making should be strongly encouraged. [ABSTRACT FROM AUTHOR]

Wide field, high sensitivity, high resolution, wide bandwidth, and polarization components are constantly pursued by CO molecular line surveys at millimeter wavelengths. Several key science cases that could be focused on by future large-scale molecular surveys have been identified upon the current progress of molecular surveys. A conceptual design for the new-generation multi-beam receiver system is proposed. Combined with the latest technical progress, the key technical solutions to realize the scheme are explained. The new design aims at a receiving scale of 100 beams. Following the newly developed hybrid planar integration technology, a new dual polarization receiving function is realized while inheriting the sideband separation mixing mode. On the basis of multi-line receiving configuration, each receiving sideband is expanded to 8 GHz. Judged from the existing technologies and the newest progress, this conceptual design scheme is fully achievable. Compared with the existing millimeter wave multi-beam receiving equipment, the comprehensive receiving capacity of the new generation millimeter wave multi-beam receiving system is estimated to increase by a factor of 89–178. This design is expected to bring another evolutionary progress for millimeter wave multi-beam receiving capability. [ABSTRACT FROM AUTHOR]

For many SMEs innovation is essential to survive in a dynamically changing environment. Technological progress, including in particular the more intense use of digital technologies, increasingly pushes companies to take a fresh look at innovation and also indicates the need for changes in approach in the strategy adopted in order to become and stay innovative and competitive. New management approaches, flexibility of operations as well as product- and service-related innovativeness determines SMEs survival and development. As service SMEs start to compete more openly, rather than locally, their owners and managers have to stay alert and ready for changes. As digitization is beginning the factor which strongly influence how innovation processes are or can be implemented, also service SMEs should be actively aware of how digital transformation affects their environment. Emerging digital tools that aim to support the innovation process also influence its possible modifications, bringing a number of possible benefits and optimisations. The main objective of this paper is to expand the understanding of innovation process digitalization level and intensity in service SMEs, based on the pilot study conducted at the end of 2021 in Poland. The analysis was performed in relation to innovation process model, that included its six general stages. The results summarise the digitalisation score of the sample of 350 companies representing various service sector, and present the overview of innovating digitally practices in reference to general engagement in innovation process. The conclusions are drawn in regards to type and scope of digital tools used to facilitate respective activities included in the innovation management. [ABSTRACT FROM AUTHOR]

The study discusses the subject matter of sureties and guarantees granted by the State Treasury and their importance in implementing new technical and technological solutions and investment projects in which sureties and guarantees granted by the State Treasury are applied, emphasizing their relationship with new technical and technological solutions. An analysis of these issues leads to a conclusion that the technical and technological progress lies at the axiological basis of the surety-guarantee system which has been operating in Poland for a few decades. The research is narrowed down to projects that implement new technical and technological solutions. The paper primarily makes use of two research methods, that is an analysis of the law in force and an analytical investigation. These methods are applied to examine relevant literature, current legislative acts and statistical data contained in information on State Treasury sureties and guarantees granted in 2016-2020. The study takes account of the legal status in force on 30 April 2022 [ABSTRACT FROM AUTHOR]

Crowd counting that aims to estimate the crowd density has recently made significant progress but remains an unsolved problem due to several challenges. In this paper, we propose an Attentive Encoder-Decoder Network (AEDNet) to overcome the notorious scale-variation problem in crowd counting. Our major contributions can be summarized in three aspects. First, we design an Attentive Feature Refinement (AFR) block in the encoder to adaptively extract multi-scale features. AFR compares the spatial information in different scales through the attention mechanism and then adaptively assign importance weights to each point, which highlights the distinctive roles in multi-scale feature extraction. Second, we develop a Separable Non-local Fusion (SNF) block in the decoder with the self-attention mechanism to aggregate multi-scale features from different layers, which not only achieves the sufficient feature fusion by capturing long-range dependencies, but also vastly reduces the computation cost compared to the original non-local operation. Third, we propose a Regional MSE (R-MSE) loss to tackle the pixel-isolation problems in regular MSE loss. To demonstrate the effectiveness of the proposed AEDNet, we conduct extensive experiments on four widely-used crowd counting datasets, and our AEDNet consistently achieves the state-of-the-art performance. [ABSTRACT FROM AUTHOR]

The development of new sequencing platforms, technologies, and bioinformatics tools in the past decade fostered key discoveries in human genomics. Among the most recent sequencing technologies, nanopore sequencing (NS) has caught the interest of researchers for its intriguing potential and flexibility. This up-to-date review highlights the recent application of NS in the hematology field, focusing on progress and challenges of the technological approaches employed for the identification of pathologic alterations. The molecular and analytic pipelines developed for the analysis of the whole-genome, target regions, and transcriptomics provide a proof of evidence of the unparalleled amount of information that could be retrieved by an innovative approach based on long-read sequencing. Since the longer a read is, the more overlap it has with other reads, third generation sequencing technology facilitates the assembly of genomic regions and could resolve complex and wide structural variants or regions enriched for repetitive elements. Nanopore sequencing (NS) provides significant advantages for whole-genome studies and, thanks to the ability to span huge regions, it could be exploited to screen specific genes of pathologic relevance affected by unknown rearrangements (i.e., F8 , BCR-ABL) or composed of repetitive elements and high GC content (i.e., CEBPA , FLT3). Owing to the nature of NS technology, the ability to direct sequence-untouched nucleic acids minimizes the bias associated with PCR amplification and enables the simultaneous detection of nucleotide sequence and the epigenetic changes of the template. The rapid workflow required to prepare NS libraries, along with the possibility to set real-time data analysis, allows retrieval of information of clinical utility at whole-genome and target region level in a unique reaction in 24/48 h. [ABSTRACT FROM AUTHOR]

• Changes in productivity of small and large firms of automotive industry are analyzed. • The 2008-09 crisis impacted on productivity by reducing technological progress. • The consequences of the crisis were more severe for SMEs. • Suitable policies may be based on environmental regulation, incentive schemes and support to R&D investments. This paper analyzes the changes in productivity of small and large firms operating in the automotive industry in France, Italy and Spain, occurred during the pre-crisis (2001-2008) and post-crisis (2009-2014) periods. To this aim, the Malmquist index as a measure of total factor productivity (TFP) variation is computed, by using the non-parametric technique DEA, integrated by a bootstrap technique proposed by Simar and Wilson (1999). The analysis allows distinguishing among different possible sources of TFP changes, i.e. pure technical efficiency change, scale efficiency change and technological change. The latter comes up to be the main channel through which the global crisis negatively impacted on productivity, presumably by hampering the primary engines of technological change, i.e. research, innovation and investment through reduced availability of financial resources for SMEs, worsened perspectives for firm growth and greater concentration in selected geographical areas of investments by parent companies. [ABSTRACT FROM AUTHOR]

• Behavioral asymmetry between workers and rentiers impacts the decisions of the agents in relation to consumption, savings and capital stock. • A micro-based aggregate version of Kalecki's aphorism was obtained. • Income distribution does not change significantly even though workers leave a bequest. • Confirmation of the results obtained by Baranzini in a two-class life-cycle model in continuous time. • Growth and income distribution; bequest effect on the capital accumulation; Kalecki's aphorism. This article shows how the behavioral asymmetry between workers and rentiers, whether in relation to the possibility of inheriting (or not) assets, or in relation to the magnitude of the inherited assets, impacts the decisions of the agents in relation to consumption, savings and capital stock. An alternative approach to the Baranzini (1991) model is presented for the continuous case, allowing technical progress and introducing behavioral differences between rentiers and workers, not only from the point of view of their initial endowments but also from their preferences. The technical-conceptual framework of the present approach extends Baranzini's original model by emphasizing how agents incorporate the assets into their constraints. A micro-based version of Kalecki's famous aphorism is also obtained. [ABSTRACT FROM AUTHOR]

The main objective of this study is to measure the productivity growth of universities across the Taiwan Strait. This study uses the global metafrontier Malmquist framework and considers university quality to estimate productivity changes in higher education institutions (HEIs) on both sides of the strait during the period between 2008 and 2014. The results show that China's HEIs enjoyed productivity growth of 1.24% per year. Technical progress contributed the most to this growth during the study period because public universities in China received significant funding and strong support from the government to improve teaching quality, thus achieving significant technical progress. Similar observations are found for Taiwan's public universities. These universities, on average, reflect good performance in both the teaching and the research components. However, private HEIs in Taiwan are less productive relative to their counterparts. It is not surprising that the regression in productivity among private HEIs is mainly the result of lower student enrollment, an insufficient number of publications, and low research funding. As a result, Taiwan's HEIs on average experienced a 0.10% decline in productivity per year during the study period. Private HEIs in Taiwan should pay greater attention to the quality of their universities to attract more local and international students. An increase in the quality of a university appears to not only improve technical efficiency but also increase productivity. [ABSTRACT FROM AUTHOR]

In the last decade, we witnessed significant technological advancements that had huge impacts across all different aspect of everyday life. Innovative technologies present important topics that need to be overseen from their early beginnings to be able to capture their breakthrough and prepare organizations for needed transitions. This research tries to detect weak signals of emerging technologies based on scientific articles published over the last decade covering several categories. To capture emerging technology trends, topics, we propose a method we refer to as "Carbon-dating Articles with Transformer Series". The name references the Radiocarbon dating (also referred to as carbon dating) method for determining the age of an object containing organic material by using the properties of radiocarbon, a radioactive isotope of carbon. In our method, we take advantage of the state-of-the-art transformer-based architectures in Natural Language Processing (NLP). A time-series of NLP models is trained to recognize new topics (adding fresh "radio-active" isotopes), while slowly forgetting past topics ("isotope half-life"). Using the trained time-series NLP models, scientific article signatures (i.e., text sequences) can be measured and positioned in time. We believe our "Carbon-dating Articles with Transformer Series" method can give valuable insights about when topics emerge and are picked-up by the larger community, timing of (published) articles presenting progressive research versus repeating research, and the bigger picture when combined with other insights like affiliations with nations, organizations, or academics. [ABSTRACT FROM AUTHOR]

This study aims to measure the relationship between technological progress, renewable energy, and green economic growth (GEG). This study uses a data envelopment analysis (DEA) estimation method to evaluate the association between government expenditure on research and development (R&D), renewable energy deployment, and GEG in the Economic Community of West African States (ECOWAS) between 1990 and 2018. The estimates revealed an inconsistent GEG indicator in the analysis, suggesting the lesser impact disposition of public policy. In addition, the energy efficiency ratio of ECOWAS sub-region is under 0.50, implying energy poverty in the sub-region. Many people do not have sufficient energy to heat and cool their homes to enough temperature and meet their basic needs and energy security concerns. This research discovered that a percentage growth increase in renewable energy deployment results in a 3.2% increase in growth in sustainable performance. Alongside an essential effect of one percentage point growth in R&D expenditure boosts economic system sustainable performance to 4.4% combined with a supported effect of one percent. This research reveals that the ECOWAS government expenditure on human resources and R&D of sustainable energy resources would result in a low carbon growth via an advanced technological production process; nevertheless, the impacts are varied in the various countries in ECOWAS. • The study applies a longitudinal dataset of the Economic Community of West African States (ECOWAS). • The energy efficiency ratio of the ECOWAS sub-region is under 0.50, implying energy poverty. • Many people don't have access to sufficient and affordable modern energy. • A 1% increase in renewable energy deployment growth results in a 3.2% increase in growth of sustainable performance. • More investment in R&D of sustainable energy resources results in a low-carbon economic growth in ECOWAS. [ABSTRACT FROM AUTHOR]

[Display omitted] • Triple emulsion droplet-based microfluidic synthesis for micromotors aimed at micro/nanoplastics removal. • Combination of glucose oxidase and catalase catalysts for consuming an eco-friendly fuel, glucose. • Efficient capture of plastics at the bubble/water interface, leveraging their inherent high surface tension. • Demonstration of reusability through consecutive cycles of plastic capture with minimal degradation in efficiency. Plastics, which are pivotal in modern technological progress and have a broad range of applications, now pose a significant environmental and health risk globally. Despite their detrimental environmental effects, there is a lack in research on effective plastic removal and treatment strategies. Addressing this urgent issue necessitates the development of innovative and efficient materials and methods for removing plastics from contaminated environments. In this study, we utilized a microfluidic technique to create novel and eco-friendly asymmetrically structured micromotors made of glucose oxidase (GOx)/catalase (Cat) embedded in polyethylene glycol diacrylate (PEGDA). These micromotors are specifically engineered to efficiently remove substantial amounts of plastics from ecosystems. The microfluidic process enabled the production of micromotors with uniform yet asymmetric shapes through aqueous two-phase separation and UV polymerization. By incorporating functional nanomaterials, these micromotors can be customized for specific wastewater treatment needs. Our design utilizes GOx and Cat to consume glucose as fuel, generating oxygen microbubbles. These bubbles not only propel the micromotors but also capture suspended plastic nano/micro-particles, effectively removing them from aquatic environments. The high surface tension of the bubbles allows for the entrapment of plastics at their interface, facilitating their removal from the water. In addition, non-toxic nature of these GOx/Cat PEGDA micromotors makes them especially suitable for environmental remediation and biological applications, addressing the urgent need for environmentally benign solutions to plastic pollution. [ABSTRACT FROM AUTHOR]

Considered high-energy intensive, Pakistan's industrial sector has seen an upwelling in its energy use, reaching 19.74 million tons of oil equivalents in 2021, which is about 37% of Pakistan's total energy consumption. This has made the industry a major contributor to CO 2 emissions and related contaminants. This research has tried to analyze the possibilities for factor substitution between energy and non-energy factors in the industrial sector by applying a trans-log production function. For the multicollinearity problem, ridge regression was used. The results show that (i) all the inputs are increasing return to scale; (ii) the measured substitution elasticity between gas-coal and oil-gas is about 0.901 and 0.953, while capital-oil, capital-gas, capital-coal, and labor-oil stands at 1.231, 1.088, 1.045, and 1.404. This is a strong sign that allocating more capital and labor to Pakistan's industrial sector instead of energy will be dynamic for sustainable development. (iii) oil-electricity consumption and electricity add to only a little share of energy by 0.378 because oil import has declined (about 15%) as a whole and imported electricity increased (5.53%), which gives the potential for primary interest, and (iv) technological progress is estimated between −0.051 and + 0.03 between energy inputs. The input of coal vs gas is a faster substitute with their relative difference in technological progress, while coal vs electricity also presents evidence of convergence. Our findings recommend robust policies, technological advancements, and industrial engagement for fostering energy efficiency towards a sustainable production system and contributing to an environmentally aware and efficient economy. • Energy substitution and technical progress in industrial sector is analyzed. • Energy and non-energy are estimated using a trans-log production function. • All the inputs are increasing return to scale. • Substitution elasticity between gas, oil, coal and capital stands at growing trend. • Coal vs gas is a faster substitute with relative difference in technical progress. [ABSTRACT FROM AUTHOR]

Innovation infrastructure (INN) compatible with industrial carbon emissions (ICE) reduction is crucial for peaking carbon emissions in the industrial sector. However, INN in China requires urgent strengthening. We elucidate the inverted U-shaped correlation between INN and ICE based on an expanded endogenous growth model, then empirically verify the nonlinear correlation between the two and its effect mechanism using data from 30 provinces in China from 2012 to 2022. The findings present that the correlation between INN and ICE exhibits an inverted U-shaped characteristic. The inverted U-shaped effect of INN on ICE mainly comes from major science and technology infrastructure, as well as science and education infrastructure. Virtual agglomeration, technology progress, energy structure optimization and industrial structure adjustment are vital mechanisms by which INN reduces ICE. However, the ambiguity surrounding data rights and the prevalence of digital platform monopolies impede the potential of virtual agglomeration to diminish ICE. Furthermore, there is also an inverted U-shaped correlation between INN and ICE in geographically adjacent areas. [Display omitted] • An expanded endogenous growth model is constructed. • The index system of innovation infrastructure (INN) is established. • The effect mechanism of INN on industrial carbon emissions (ICE) is investigated. • INN has a significant spatial spillover effect on ICE in geographically adjacent areas. • Promoting INN construction to fully leverage the role of reducing ICE. [ABSTRACT FROM AUTHOR]

Biosensor research has long focused on achieving the lowest possible Limits of Detection (LOD), driving significant advances in sensitivity and opening up new possibilities in analysis. However, this intense focus on low LODs may not always meet the practical needs or suit the actual uses of these devices. While technological improvements are impressive, they can sometimes overlook important factors such as detection range, ease of use, and market readiness, which are vital for biosensors to be effective in real-world applications. This review advocates for a balanced approach to biosensor development, emphasizing the need to align technological advancements with practical utility. We delve into various applications, including the detection of cancer biomarkers, pathology-related biomarkers, and illicit drugs, illustrating the critical role of LOD within these contexts. By considering clinical needs and broader design aspects like cost-effectiveness, sustainability, and regulatory compliance, we argue that integrating technical progress with practicality will enhance the impact of biosensors. Such an approach ensures that biosensors are not only technically sound but also widely useable and beneficial in real-world applications. Addressing the diverse analytical parameters alongside user expectations and market demands will likely maximize the real-world impact of biosensors. [Display omitted] • Rethinking the prominence of LOD in biosensor success evaluation. • Addressing the trade-off between detection range and low LOD. • Importance of clinically significant detection ranges for biosensors. • Balancing sensitivity with simplicity and cost-effectiveness. • Emphasis on practical deployment and real-world applicability. [ABSTRACT FROM AUTHOR]

This article examines the impact of economic growth on Vietnam's marine fisheries and the effectiveness of government policies in promoting sustainability. Despite impressive economic growth, environmental concerns have become urgent and require serious consideration in Vietnam. The Vietnamese government has implemented policies to reduce over-exploitation in coastal areas and improve the efficiency of offshore fishing, but unsustainable practices and illegal fishing remain significant problems. This study examines the effects of transitioning from a centrally-planned economy to a 'socialist-oriented' market economy on the productivity and efficiency of Vietnam's marine fisheries. The main focus is on productivity changes, with additional consideration given to technical progress, environmental changes, and management practices. The findings shed light on the complex relationships between economic development, environmental sustainability, and marine fisheries in Vietnam. The study highlights the importance of sustainable practices and effective government policies in promoting the sustainability of the country's marine fisheries. This article provides valuable insights for policymakers and stakeholders concerned with the sustainability of marine resources in Vietnam and beyond. • Transition to a socialist-oriented market economy impacts Vietnam's marine fisheries. • Catch growth depends on labor and fishing capacity, with labor having a slight advantage. • Environmental factors and scale effects adversely affect total factor productivity (TFP) growth. • Urgent measures are needed to promote the sustainability of the country's marine fisheries. [ABSTRACT FROM AUTHOR]

• Evaluated the static and dynamic impacts of dual-pilot cities on carbon productivity. • Assessed the synergistic effects of dual-pilot cities on carbon productivity. • Analyzed the heterogeneous effects of pilot city implementation sequence. • Dual-pilot cities have enhanced urban carbon productivity. • Dual-pilot cities boost carbon productivity more than single-city models. The combination integration of urban development models (CUDM) emerges as pivotal in aligning economic development with achieving the "dual-carbon" goals. However, existing studies often overlook CUDM's potential for carbon emissions reduction. Multi-period DID models exhibit excellent performance in mitigating endogeneity and eliminating omitted variables. This study examines the impact of the combination integration of innovative and smart city development models (CISDM) on urban carbon productivity, employing a multi-period DID model with data spanning 2006–2019 from Chinese cities. The results indicate that: (1) CISDM significantly enhances urban carbon productivity by 0.2064 units, primarily driven by innovation-induced technological advancements and structural effects. (2) CISDM yields a significant synergistic effect on urban carbon productivity. Compared to single pilot cities, CISDM significantly increases a city's carbon productivity by 0.1854 units. This effect is particularly noticeable when prioritizing "smart" initiatives over innovation. (3) The effect of the CISDM on carbon productivity varies according to city characteristics. While environmental regulations amplify CISDM's positive impact, resource-based cities struggle to harness its effective. This study underscores the potential of leveraging CUDM to promote "dual-carbon" objectives, providing valuable insights for policy synergies. [ABSTRACT FROM AUTHOR]

In recent years, the technological advancements embodied by digital technology have received significant attention from policymakers and researchers because of their profound impacts on the economy and society. In particular, the relationship between digital technology and employment continues to be a subject of considerable debate. This article focuses on the microperspective, and the causal effects and mechanisms of corporate digital transformation on labour employment are examined. With the use of data on Chinese A-share manufacturing companies from 2008– to 2019, text analysis is employed in this study to construct a comprehensive index of corporate digital transformation. We utilise a combination of fixed effects models, difference-in-differences (DiD) models, and instrumental variable methods and demonstrate that digital transformation stimulates enterprise labour demand, a conclusion that remains valid after multiple endogeneity tests and robustness assessments. The heterogeneous results indicate that nonstate-owned enterprises (non-SOEs), nonhigh-tech enterprises, enterprises with low financing constraints, and small enterprises exhibit greater employment creation effects through digital transformation. Mechanistic analysis suggests that digital transformation increases enterprise employment by increasing operational and management efficiency, profitability, and labour productivity levels. Further exploration reveals that digital transformation increases the demand for labour with varying skills and human capital upgrading in enterprises. This article, through the lens of digital technology, enriches the body of research on the nexus between technological progress and employment, provides novel insights into employment fluctuations under the digital paradigm, and outlines significant implications for countries balancing digital economy development, employment growth, and social stability. • The digital transformation of enterprises has a job-creating effect on employment and promotes employment stability. • Reduces operational costs, enhances profitability, and boosts labour productivity are the primary channels of effect. • The use of digital technology in China's manufacturing sector has facilitated the upgrading of companies' human capital. • The employment creation effect of corporate digital transformation exhibits asymmetry across different types of enterprises. [ABSTRACT FROM AUTHOR]

This study introduces a novel production network model to analyze how digital transformation influences different sectors within the government. Unlike previous research, which often views digital government as a singular entity, our approach dissects the specific impact of digital transformation on various government departments and their contributions to overall governmental efficiency. By employing text analysis and empirical models, we assess the degree of digital transformation across government departments from 2012 to 2022, revealing that such transformations enhance governmental efficiency. Furthermore, our findings highlight the critical role of coordinated digital transformation efforts in amplifying overall efficiency. This research not only provides a fresh theoretical framework for understanding digital government but also offers actionable recommendations for optimizing resource allocation and strategizing digital initiatives to drive governmental progress. • The impact of digital transformation in government departments • Digital transformation enhances government efficiency. • Textual analysis measures digital transformation. • High coordination significantly boosts efficiency. [ABSTRACT FROM AUTHOR]

Sustainable Development Goals (SDGs) and the challenges in attaining these goals are always an eye-catching research theme for academics, politicians, and stakeholders around the world. Subjective well-being (SWB) is one of the central SDGs but is under-researched so far. Addressing this concern is crucial to maintaining societal welfare and promoting the realization of a sustainable future. Hence, this study explores the determinants of SWB with a particular focus on technological advancement and environmental damage. The paper examines SWB determinants in six South Asian nations from 2005 to 2022 using the cross-sectional augmented auto-regressive distributed lag model. The conclusions demonstrated that technology advancement improved SWB in the long term. Meanwhile, environmental deterioration has no appreciable short-term effects and harms SWB in the long term. This study adds to the field by examining how technological advancement and environmental deterioration explain SWB in South Asian economies. The study recommends policies that aim at improving innovations and reducing CO 2 emissions. [Display omitted] • Technological advancement and environmental hazards substantially influence SWB. • The study is based on macro data (2005–2022) obtained from South Asian economies. • Technological advancement contributes to well-being and offers a brighter future. • Environmental hazards deteriorate the fragile fabric of human well-being. • South Asian economies should reconsider their innovation and environmental policies. [ABSTRACT FROM AUTHOR]

Dynamic organizations actively capitalize on social responsibility (CSR) and environmental recovery strategies, considering social and ecological challenges. However, how CSR-committed firms respond to changing environmental technologies and sense critical social and environmental trends is unknown. This study examines the role of CSR in developing green dynamic capabilities (GDC) of organizations, including resource reconfiguration, integration, and environmental insight capabilities, and it explains whether they strengthen organizational green technological innovation (GTI) performance. Specifically, it takes green transformational leadership (GTL) as the moderating variable in the relationship between GDC and GTI. The data collected from 295 manufacturing managers analyzed through linear regression and structural equation modeling indicated that CSR-committed firms have significant capability to integrate and reconfigure green resources and environment insight capability, leading toward improved GTI. The study establishes that GTL bolsters the relationship between resource integration and environmental insights aspects of GDC and GTI; while insignificant relationship exists for resource reconfiguration. Considering their pivotal green transformative role, it suggests that organizational leaders should prioritize sustainability, inspire vision, empower employees, and foster a culture of innovation to leverage the organizational GDC to boost GTI and concludes with policy implications. • CSR positively contributes to RIC, RRC, and EIC aspects of GDC. • CSR initiatives result in improved firms' GTI performance. • RIC, RRC, and EIC make a significant positive impact on GTI. • Green transformational leadership (GTL) positively moderates between RIC, GTI, and EIC and GTI. • GTL has an insignificant moderating impact on RRC and GTI. [ABSTRACT FROM AUTHOR]

Governing firms' R&D manipulation is crucial amid the prevalent opportunism during innovation in emerging economies. This study employs data on listed companies in China from 2010 to 2021 and uses the Golden Tax Project III as a quasi-natural experiment to estimate the effect of digital tax administration (DTA) on R&D manipulation via a dual machine learning model. Based on the capability, opportunity, and motivation-behavior (COM-B) theoretical framework, we explore the key pathways and identify the heterogeneous effects of DTA on various R&D manipulation motivations and directions. The results indicate the following: (1) DTA can regulate firms' R&D manipulation behavior and incentivize innovation quality and diversity. (2) DTA reduces R&D manipulation by enhancing accounting information quality and transmission efficiency in capital markets (internal and external information channels), strengthening tax audits (external monitoring channels), and curbing managerial self-interest and tax avoidance motives (internal motivation channels). (3) The DTA primarily functions as a governance instrument to address manipulation in various directions driven by tax avoidance and executive self-interest motives. These findings offer valuable insights for exploring governance models to address R&D manipulation in emerging economies. • The effects of digital tax administration (DTA) on R&D manipulation are explored. • DTA can govern R&D manipulation and improve innovation quality and diversity. • Exploring mechanisms under COM-B framework: information, oversight, and motivation • It identifies directional changes in R&D manipulation under diverse motivations. [ABSTRACT FROM AUTHOR]

The accurate forecasting of coal power overcapacity in China has significant impact on the promotion of the dual carbon strategy. However, due to the complexity of the causes of coal power overcapacity, existing forecasting methods are unable to comprehensively identify influencing factors and incorporate them into forecasting models. Given this, we propose a text-based framework for forecasting coal power overcapacity. Specifically, a topic model and a sentiment analysis method are used to identifies and quantifies the influencing factors from policies and news texts of coal power and its related industries. In addition, under the dual carbon target, the development trend of coal power overcapacity under different environmental constraint scenarios was examined. The empirical test shows that the performance of the forecasting models based on the text data of the related industries is better than that based on the text data of the single coal power industry and the numerical data of the single objective variable, and the changes in capacity of the upstream and alternative industries and the industrial policy support of the downstream industries are the main causes of overcapacity. The scenario forecasting results indicate that the coal power overcapacity scale shows an upward trend from 2021 to 2060. • A hybrid forecasting method considering imbalance and unequal importance of text is built. • A data combination method with data source, type complementary and related impact is proposed. • The causal mechanism of coal power overcapacity from an industrial correlation perspective is clarified. • The multi-source heterogeneous data improves more forecasting performance than model selection. • A comprehensive and focused list of influential factors of overcapacity is obtained. [ABSTRACT FROM AUTHOR]

Conservation agriculture (CA) represents a paradigm shift towards more sustainable and climate-smart intensification of smallholder farming systems in southern Africa. This can only be achieved with reasonably fast, widespread, and sustained adoption of CA. However, many farmers are slow to adopt CA and when they do, they often do not continue using it and eventually dis-adopt. We combine duration models and quantile regression models to study how long farmers take to adopt conservation agriculture once they are trained; and to assess the distributional effects of the drivers of the persistence of adoption once a farmer adopts. Both models account for self-selection which makes adoption endogenous. We find that, on average, farmers take four years to adopt once trained and that there is a congruence between factors that reduce the duration to adoption and those that increase the persistence of adoption. Access to CA extension and credit, labor availability, education and hosting demonstrations increase the speed of adoption by 13–28 %. The duration from the first training, access to extension services, and farming experience increase the persistence of adoption, especially in the initial years. The findings point to the need for implementing multi-year CA promotional programs with medium-term time horizons that should prioritize enhanced training through community-embedded demonstrations and learning sites, and digital extension for extended reach. • We study how long farmers take to adopt CA once trained among true adopters. • And for how long they persist in adoption once they adopt. • We use duration and quantile regression models with selection. • Demonstrations, extension, and training speed up and lengthen CA adoption. • Findings call for investments in long-term, farmer led demonstrations and training. [ABSTRACT FROM AUTHOR]

Scarcity is an essential issue in service marketing. This study examined scarcity in a game-theoretic setting. It focused on the role of customer evaluations, through satisfaction ratings, on a technology-enabled peer-to-peer sharing economy platform in achieving stable provider–user matching. The model shows that an appropriate market design employing a user-proposing version of Gale and Shapley's (1962) deferred acceptance algorithm for a ride-sharing platform where many users approach a few providers can help avoid congestion and ensure stable matching. To manage scarcity, the model uses a customer satisfaction rating system that modifies the widely used batch matching algorithm by matching highly rated riders much faster than their low-rated peers. A platform's ability to offer time-bound stable matching for highly-rated users during scarcity is likely to help it maintain a competitive edge. • Role of satisfaction rating to address scarcity and congestion is explored. • Satisfaction rating is embedded in batch matching algorithm. • User-proposing form of deferred acceptance algorithm is used for stable match. • Right market design ensures stable matching for peer-to-peer ride-sharing. [ABSTRACT FROM AUTHOR]

This paper presents a novel business model design tool called Future ecosystem business model (FEBM). The FEBM aims to address the lack of managerial tools linking business models, foresight, and ecosystem strategizing in the context of systemic technological changes, as those characterizing the sustainability transition in a multi-level perspective. The tool has been shaped through a design science approach building on a structured review of the literature. A field test was conducted through a case study to test the proposed tool. The empirical context was that of a publicly funded project in the field of electrofuels (efuels). The project foresaw the development and integration of several technologies, whose adoption was likely to have significant implications within and across industries. The proposed approach contributes to the literature on business model design in the context of technology-driven transformations characterized by high uncertainty and interdependence, such as those related to the sustainability transition. Strategy and innovation managers may find in the proposed FEBM tool an actionable approach to shape decision-making against far-reaching technological and societal challenges. • The Future Ecosystem Business Model (FEBM) tool is presented. • The tool integrates foresight and ecosystem logic in business model design. • The tool can be applied in the context of systemic technological changes, as those characterizing the sustainability transition. • The tool is designed through design science research. • A field test is conducted in the field of electrofuels (efuels). [ABSTRACT FROM AUTHOR]

Over the past two decades, the market for patent transfers (PT) has experienced substantial growth in China, driven by the expansion of main relationship types, including inter-firm, industry-university-research (IUR), and individual-to-firm PTs. This growth raises critical questions regarding the influence of these diverse PT types on regional innovation. Utilizing data mining on 1,914,750 PT events, this study constructs panel data models for China's 31 provinces from 2011 to 2020, investigating the presence, dimensions, effect decomposition, and threshold determinations of PTs on regional innovation. Findings reveal heterogeneous impacts of PT types on innovation, with individual-to-firm PT being most effective and IUR PTs the least. Among the dimensions of impact, PT strength demonstrates the most circumscribed promotional effect, predominantly within patent inflows, and particularly hinders IUR PTs due to market frictions. The importance of PT breadth mainly appears in patent outflows, suggesting geographic expansion of PT enhances innovation remuneration, critical for sustaining innovation momentum in hub provinces. PT depth uniformly affects innovation across all PT categories irrespective of patent inflows or outflows, underscoring the significance of diversified technology transfers. A universal observation across PT types is that surpassing regional thresholds of digitalization significantly amplifies the promotion of PT on regional innovation. • Uncover how different types of patent transfer (PT) impact regional innovation. • Impact dimensions are delineated into strength, breadth, and depth to reveal the potentials and challenges of each PT type. • Individual-to-firm PT significantly boost innovation, whereas industry-university-research PT have the minimal effect. • Inbound strength, outbound breadth, and both inbound and outbound depth of PT drive regional innovation. • The single threshold effect regarding regional digitalization is found. [ABSTRACT FROM AUTHOR]

Although skepticism is involved in technical change and scientific revolutions, surprisingly, the literature lacks a systematic analysis of the different forms, causes, and roles of skepticism in the diffusion of innovation. This paper defines, identifies and models different types and causes of skepticism and their role in technology adoption. The paper identifies and studies: skepticism involving the characteristics of the technology and the producer; skepticism that induces to disbelieve market signal; and comparative skepticism i.e., skepticism produced by an unbalance relationship between the perceived complexity of the problem and the solution. Among the theoretical findings of the paper and regarding skepticism on market signals, we found that the non-differentiability and oscillation of diffusion rates occur if individuals use the information on diffusion rates as proxy of the probability of technology working and modify this probability according to their skepticism. • Although scepticism is involved in technical change, general analysis of the different forms, causes and role of scepticism in innovation diffusion do not exist. • We developed a dynamic model of decision-making and innovation diffusion that incorporates technology diffusion and trust/scepticism. • Scepticism modifies market signals. • The model contributes to understanding mechanisms behind technology adoption and diffusion: adoption delay, adoption without social interaction, and oscillation of diffusion rates. [ABSTRACT FROM AUTHOR]

There is confusion surrounding the concept of industrial ecosystems (IEs). This research therefore presents a systematic literature review on the subject of industrial ecosystems and outlines several paths for future research. The paper defines the key characteristics of IEs, identifies three perplexity drivers that contribute to the conceptual ambiguity of IEs, proposes a four-tier integrative IE framework that outlines the core components of IE research, and presents a conceptual model that clarifies how synergetic effects emerge, leading to IE transformation. Articles are categorized into four categories (industrial symbiosis, metabolism, architecture, and orchestration) from which ten propositions are delineated. The study encourages researchers to tap into several areas from the view that this is a broad, but still rather unexplored area of research with high relevance for policy. • Establishes boundary conditions for IE by identifying main characteristics. • Discusses three perplexity drivers causing conceptual ambiguity in IE research. • Provides an IE four-tier integrative framework linking fragmented IE research. • Presents a conceptual model elucidating how synergetic effects emerge in IEs. • Provides propositions for how IE synergies result in industrial transformation. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of the use of industrial robots on labor income shares at both the theoretical and empirical levels. On the theoretical side, the role of induced technological progress, the creation of new tasks, and the penetration of industrial robots on labor income shares are systematically explored by incorporating industrial robots into task models and endogenizing the task induced technological progress. Empirically, industrial robot penetration at the regional level in China is constructed from the industrial robots data released by the International Federation of Robotics (IFR), which is matched with Chinese A-share listed companies in 2011–2019, and the causal strategy of Bartik-style instrumental variables is used to analyze the impact of the penetration of industrial robots and task induced technological progress on the share of labor income. The study shows that the penetration of industrial robots significantly increases the share of labor income, but the task induced technological progress reduces the share of labor income, and that the impact of the penetration of industrial robots varies significantly external financing dependence, ownership, and regions. From the perspective of the impact mechanism, robot penetration increase the levels of inputs complementarity and hence reduce the elasticity of substitution between robots and labor. Meanwhile, robots can effectively increase the wage level of the labor force, thus increasing the labor income share. The findings of this paper provide a decision-making reference for how industrial robots can better serve human beings in the new era so that workers can share the fruits of economic development. • It presents a theoretical model integrating robots into profit-maximizing tasks to assess their impact on labor income share. • Robot penetration affects labor income share across external financing dependence, ownership, and regions. • Increased robot penetration raises the labor share through effects on the elasticity of substitution and wages. [ABSTRACT FROM AUTHOR]

This study examines the socio-economic factors influencing material efficiency in over 100 countries from 1970 to 2016, amidst growing material consumption and environmental concerns. It assesses material efficiency using production and consumption metrics, revealing four distinct trajectories reflecting diverse economic and demographic contexts. The research shows that globally, economic growth and technological advancement significantly enhance material efficiency. However, the effects of such factors vary greatly by income, human development level, and aging demographics. As countries advance in income and human development, and as their populations age, the beneficial effect of economic growth on material efficiency diminishes. Conversely, the positive impact of technological progress intensifies with higher levels of human development. Moreover, as societies age, population growth shifts from hindering to promoting material efficiency, especially in "super-aged" societies. The findings highlight the need for context-specific strategies for material efficiency, acknowledging the unique stages of development and demographics of each country. [Display omitted] [ABSTRACT FROM AUTHOR]

Cities play a pivotal role in achieving 'Carbon Peak' and 'Carbon Neutrality' objectives through the implementation of strategies aimed at mitigating environmental risks. While the environmental impacts of industrial production activities have been widely examined, the nuances of their internal structures remain obscure. This study delves into the industrial sector across the 'thirteen urban agglomerations (TUAs)' in mainland China, covering the years 2006–2016, by developing a comprehensive (source-specific and variable-specific) decomposition framework for Malmquist productivity index. The framework is utilized to discern whether efficiency changes or technological advancements drive productivity growth, considering input/output variables such as capital and labor. Findings show that the average annual environmental productivity gain during the examined period was 2.6 %, suggesting a general enhancement in productivity within TUAs' industrial sectors. A detailed breakdown of productivity changes indicates that a combined contribution of 1.8 % to environmental productivity growth stemmed from energy use and pollutant variables, with emissions of industrial sulfur dioxide being the most significant at 0.9 %. Conversely, the 'catch-up effect,' or environmental efficiency change, was negative (−0.2 %), indicating the TUAs' inability to emulate the productivity levels of more advanced areas. Industrial energy use and capital inputs were the primary contributors to this negative trend, each accounting for a −0.2 % impact. The results underscore the importance of facilitating technology transfers from more developed to less advanced regions, especially regarding renewable energy and capital investment, to bolster environmental performance and productivity in the TUAs' industrial sectors. [Display omitted] • Variable-specific and source-specific decomposition is applied. • The average annual productivity gains between 2006 and 2016 were 2.6 %. • The catch-up effect in TUAs cities during the same period was negative (−0.2 %). • End-of-pipe regulations or source control can be opted. • Technological upgrading or technological transfer can be opted. [ABSTRACT FROM AUTHOR]

• Combustion-based manufacturing needs innovative solutions to drastically reduce carbon emissions. • Digital twin technology can improve the efficiency and reduce emissions of industrial furnaces. • Digital twins can revolutionize all lifecycle phases of furnaces, from design optimization to online control. • This technology facilitates the transition of furnaces to zero-carbon fuels, aiding environmental sustainability. • It is crucial to develop standardized frameworks and enhance the reliability of digital twin models. The energy-intensive industry, heavily reliant on heat generation processes, faces the critical challenge of drastically reducing greenhouse gas emissions. This study reviews the potential of digital twin technology in decarbonizing combustion-dependent manufacturing processes. While primarily focusing on scholarly articles, our analysis may not cover all current industrial practices and digital twin implementations. This paper highlights challenges and opportunities in deploying practical digital twins for industrial furnaces within the Industry 4.0 framework. Digital twins, integrating real-time simulation models with predictive capabilities, aim to enhance industrial furnaces' design, operation, and maintenance by combining high-fidelity simulations with data-driven modelling techniques. The findings indicate that digital twins can facilitate the transition to furnace electrification and adopting zero-carbon fuels, significantly reducing emissions and optimizing overall furnace performance. However, challenges like model reliability and high upfront investments in IT and connectivity infrastructures limit their widespread adoption. Despite these limitations, ongoing technological advancements predict a rapid expansion of digital twin applications in industrial furnaces, making them indispensable for achieving decarbonization goals in energy-intensive industries. [ABSTRACT FROM AUTHOR]

This paper compares the macroeconomic impacts of different decarbonization storylines until 2050 using two Computable General Equilibrium models. The modeling shocks are harmonized across models to simulate four decarbonization scenarios through three main drivers: technical development, societal attitude, and policies. The study explores the contribution of each of these drivers to the European decarbonization. The results show that the decarbonization scenarios have moderate effects on GDP; decarbonization scenarios rather result in sectoral shifts. The impact of temperature on labor productivity minimally alters expected growth levels, since larger differences in temperature between the scenarios are only expected to occur in 2100, not yet in 2050. Electricity demand is increasing in all scenarios, particularly with stronger political guidance leading to additional tax and subsidy measures to encourage the use of electricity and discourage fossil-based fuels. When society is a driving factor, it is found that circular business models result in an increase in the service industry but might have a slightly negative impact on overall growth due to stronger spillover effects linked to the manufacturing industry. Technology appears to be the only driver to facilitate decarbonization while maintaining steady economic growth. • We address the macroeconomic effects of five climate scenarios using two CGE models. • We focus on the effects of changes in society, technology, and policy. • We incorporate climate change effects through labor productivity. • Effect of decarbonization on GDP is moderate under given technological improvement. • Decarbonization scenarios result in relatively large sectoral shifts. [ABSTRACT FROM AUTHOR]

The maritime industry is constantly facing new challenges and technological advancements, making the adaptation of innovative solutions like digital twins a bridge enhancing safety and efficiency between theoretical models and real-world maritime applications. Digital twin simulators for complex dynamic operation systems such as shipboard cranes, allow the operators to practice demanding operations in a risk-free immersive environment with various scenarios. This paper presents the process of developing a digital twin-based simulation tool designed for shipboard crane operations. It is based on co-simulation using the Functional Mock-up Interface (FMI) standard. This allows for the integration of the operation scenarios with different physical domain models, including such as the ship, environmental forces, hydraulic power systems, and controllers. In addition, the digital twin has opened up new opportunities for the optimization of maritime systems. It can be used to identify the optimal operating conditions, predict potential risks, and provide onboard support to the operator. A demo crane digital twin is implemented for the Palfinger crane on the Gunnerus research vessel with system validation via a series of marine operations being real-time monitored by the Remote Control Center (RCC). • Co-simulation technology based on the FMI standard integrating the operation scenarios with different physical domain models. • Real-time ship-crane operations monitored by Remote Control Center lying in the collection, transmission, and storage of sensor data for IoT solutions. • System validation using sensor data and offshore pre-operation varying the environmental parameters in demanding operations. [ABSTRACT FROM AUTHOR]

The ever-changing global economy and sudden global public health events have posed challenges to financial resilience worldwide. As its important role in maintaining domestic economic stability, safeguarding national security, and enhancing international status, financial resilience has long been widely studied. However, few studies have empirically explored how technological progress affects financial resilience. Based on data from 30 provinces in China, this study adopts a panel two-way fixed effect model to identify the impact of technological progress on financial resilience and the underlying mechanisms. Results show that technological progress can significantly enhance financial resilience, and this impact is stronger in provinces with large population size, high employment proportion in the tertiary sector, high social consumption capacity, and provinces located in Central China. Further, technological progress have a positive impact on financial resilience through increased asset liquidity and government intervention. • Technological progress can significantly promote financial resilience. • This impact has heterogenetiy in provinces with different population, employment, consumption and geographical location. • Technological progress can enhance financial resilience through increased asset liquidity and government intervention. [ABSTRACT FROM AUTHOR]

[Display omitted] • MXenes-based hydrogels are incredible candidates for biomedical applications. • Synthetic approaches on MXene-based hydrogels have been discussed. • Applications of MXene-based hydrogels for bio-imaging, biosensors, bone regeneration, and drug delivery are outlined. • Challenges and future directions pertaining to MXenes-based hydrogels are addressed. Biomaterials have shown noticeable technical progress due to the emergence of 2D substances. The nanomaterial known as 'MXene' is a 2D ceramic-based substance made up of transition-metallic carbides, nitrides, and carbonitrides. It is derived via a porcelain 'MAX' phase by removing the 'A' component by carving. MXene was developed as a superior alternative to traditional biological materials, overcoming their limitations. Despite possessing significant characteristics such as a large area of coverage, biocompatibility, water-holding capacity, metal-based conductance, and the capacity to adjust its dimensions, the utilization of MXene is limited in the field of biomedicine owing to its instability in biological niches, inability to endure and regulate pharmaceutical release, and inadequate biological degradation. These drawbacks have prompted the exploration of MXene/Polymer nanocomposites as an alternative. Polymers may be functionalized due to the presence of specific groups on the exterior of MXenes. These nanocomposites, which are polymers customized with MXene, have exceptional characteristics such as an excellent rate of converting light into heat, the ability to target malignant cells selectively, reactivity to external forces, susceptibility to ions, enhanced bactericidal activities, and similar attributes. This review focuses on the novel instances of polymer-functionalized MXene materials used in the growing field of clinical uses. These applications encompass regulated and prolonged administration of medications, antibacterial agents, precise biosensors, broadened imaging for diagnosis, and regeneration of bones. [ABSTRACT FROM AUTHOR]

This research evaluates the effects of performance benchmarking for public utilities using the Australian experience, providing empirical support for the significance of mechanism design in implementing revenue-cap regulation. We estimate the efficiency and productivity of Australian electricity distribution providers by utilizing the meta-frontier framework with panel data covering the period from 2007 to 2021. Our findings indicate that introducing benchmarking has facilitated technological progress and reduced efficiency gaps among companies. However, there is no statistically significant difference in the average efficiency between the periods before and after the reform, potentially due to strategic behavior exhibited by network service providers. • The average efficiency levels of AustralianDNSP in period of before- and after- 2012 reform are 0.9230 and 0.9280 respectively. • The introduction of benchmarking technique in 2012 promoted the technological progress. • The strategical behaviors of network service providers has led to no statistically significant improvement in efficiency. • We divide Australian DNSPs′ inefficiency in the two sub-periods into cost gap inefficiency and management inefficiency. [ABSTRACT FROM AUTHOR]

Advancing sustainable energy technologies (SET) is crucial for achieving carbon neutrality and effectively addressing climate change. Unlike most studies that focus on individual sustainable energy policies, this research constructs a recursive computable general equilibrium (CGE) model with comprehensive sustainable energy modules to analyze the macroeconomic effects of multiple policies related to SET advancement. Covering 8 regions, 13 energy sectors, and 37 intermediate input sectors, the study evaluates the economic and ecological impacts of various SET advancement scenarios from a global economic perspective, aiming for consistent carbon reduction. The findings reveal that : (1) SET implementation reduces electricity costs for residents, optimizes industrial structure, decreases fossil fuel usage, enhances energy use structure, and lowers carbon taxes; (2) the collective impact of renewable energies surpasses that of individual sources, with newer renewables like wind and solar power outperforming traditional ones such as hydropower and nuclear power; and (3) advancements in alternative energy technology have had diverse effects on the global energy environment and economic development. Based on these conclusions, we recommend that: (1) prioritizing the development of solar and wind power in the short term; (2) optimizing SET advancement mechanisms to support progress, including enhancing the market-based price formation for sustainable energy generation and promoting technological innovation and cost reduction; (3) encouraging a synergistic transformation of renewable energy with coal, gas power, and other sources to maximize policy synergies. • A recursive CGE model is constructed, featuring detailed renewable energy modules. • Renewable energy technologies significantly reduce carbon emissions. • The impacts of various renewable energy sources show heterogeneity. • Sole reliance on renewable energy cannot achieve carbon neutrality. • Rural residents stand to benefit greatly from advances in renewable energy technology. [ABSTRACT FROM AUTHOR]

This paper delves into the integration of Intelligent Process Automation within the domain of business continuity auditing, with a focus on the Portuguese banking sector. In an era marked by rapid technological advancement, organizations are increasingly leveraging automation to reinforce operational efficiency and realize substantial cost savings. Concurrently, auditors play a pivotal role in ensuring seamless transitions amid technological transformations to safeguard business continuity. This research endeavors to bridge the realms of business continuity and intelligent automation, culminating in a comprehensive application that streamlines the audit process. The implemented solution encompasses the automation of critical audit activities, including communication, information requests, and final report submissions, liberating auditors from the chains of repetitive tasks. The incorporation of business intelligence augments this automation framework, enabling a meticulous analysis of key performance indicators within the audit department. This ensures a continuous evaluation of the efficacy of the Annual Audit Plan. Empirical validation of this initiative was achieved through surveys conducted with audit teams from four prominent Portuguese banks. The results unequivocally affirm the potential benefits of this implementation, extending invaluable support to management in the decision-making process, while concurrently alleviating auditors of routine tasks inherent to the audit process. This study not only underscores the transformative potential of intelligent process automation in the audit domain but also offers a replicable framework for organizations seeking to fortify their business continuity efforts through technological integration. The findings hold implications for businesses navigating the dynamic intersection of technology and audit practices, providing a blueprint for harnessing automation for enhanced operational resilience. [ABSTRACT FROM AUTHOR]

Cities are constantly dynamics, but emerge the stability of urban systems as evidenced by robust urban scaling. Both properties serve as necessary perspectives for understanding the evolution of cities and the complexity of urban systems. However, the evolution trends and mechanisms behind the above relationships, particularly concerning geographic processes, remain to be explored in depth. In this study, the dynamic fluctuations within individual cities and the macro-stability of the evolution of urban systems over the past two decades are systematically demonstrated. Subsequently, associations between urban systems and individual cities are established on the basis of micro- and macro-dynamic mechanisms. The trajectory of individual cities can be divided into scaled–driven growth (SG) and urban excess growth (EG). The former is the result of scaling effects within the system, while the latter is affected by global external effects. Taking as examples urban built-up area and social productions, the evolution pathways that vary from different attributes are analyzed. The results indicate that urban built-up area is more affected by scaling effects whereas social productions is driven more by global external effects. Moreover, we examine the driving forces and mechanism of EG from the aspects of economic development level, technological and economic progress, industrial structure and regional policy through an empirical analysis. This study provides a nuanced understanding of the trends and pathways of urban land–population system from the perspective of complex urban systems and holism to deepen the understanding for general properties of cities and co-evolution for urban population size and land expansion. • Coupling the micro-dynamics of cities and macro-stability of urban systems to study the trends and pathway of urban evolution. • The trajectory of urban temporal growth of individual cities can be divided into scale-driven growth and excess growth. • Interactions within the urban land-population system approximately reappear a scale-driven evolution pathway more closely than social production. • Urban excess growth is related to the external effects of macro environment such as macro-economic environment and regional policy. [ABSTRACT FROM AUTHOR]

Technological advancements have significantly progressed and innovated across various industries. However, these advancements have also led to an increase in cyberattacks using malware. Researchers have developed diverse techniques to detect and classify malware, including a visualization-based approach that converts suspicious files into color or grayscale images, eliminating the need for domain-specific expertise. Nonetheless, converting files to color and grayscale images may result in the loss of texture details due to noise, adversely affecting the performance of machine learning models. The aim of this study is to present to assess the texture features and noise contributions of the red, green, and blue channels in color images. We propose a novel method to enhance model performance in terms of accuracy, precision, recall, f1-score, memory utilization, and computing cost during testing and training. This study introduces an approach involves separating color channels into individual red, green, and blue datasets and using various Discrete Wavelet Transform levels to reduce dimensions and remove noise. The extracted texture characteristics are then used as input for machine learning classifiers for training and prediction. Through comprehensive evaluation, we compare the performance of grayscale images with that of the red, green, and blue datasets. The results show that grayscale images significantly lose critical textural artifacts and perform worse than the color channels. Notably, employing extra tree classifiers yielded the best results, achieving an accuracy of 98.37%, precision of 98.64%, recall of 97.60%, and an f1-score of 98.04% with the red channel of color dataset. [ABSTRACT FROM AUTHOR]

• Calculate the land ecological security (LES) index at the city level. • Analyze the relationship between green finance (GF) and LES. • Synthetic DID is applied to assess the impact of the GF on LES. • Examine the transmission mechanisms of GF effects on LES As the phenomenon of ecological degradation increases, there is a growing body of research related to green finance, but no papers evaluating the link between it and land ecological security. Thus, this research calculates land ecological security using data from 158 cities in China's major grain-producing regions from 2012 to 2020. Taking China's green finance policy as an example, it applies the synthetic difference-in-difference method to analyze green finance's impact on land ecological security. The conclusions show that, first, green financial policy implementation has contributed to the improvement of land ecological security by 0.154 units. This result still holds after a series of robustness tests such as parallel trend tests, dynamic effects tests, and placebo tests. Second, mechanism analysis finds that green finance affects land ecological security through three paths: agricultural scale management, agricultural technological progress, and eco-industrialization. Third, in terms of the sub-dimension of eco-industrialization, green finance promotes domestic tourism revenues, agriculture, forestry, and animal husbandry, while its impact on international tourism revenues and fisheries is not significant. The results herein confirm the role of green finance in securing ecological security of land. Future research will further enrich the indicator system of land ecological security as well as excavate the boundary conditions for green finance in order to promote land ecological security. [ABSTRACT FROM AUTHOR]

Transport infrastructure is an important source of carbon emissions, and different transport infrastructure have varying impacts on urban carbon emissions, which has been lacking in previous research. This study selects 273 cities in China from 2005 to 2020 and applied the spatial Durbin model and mediation effect model to empirically examine the direct impact effects, spatial spillover effects, scale and regional heterogeneity, and indirect pathways of highways, high-speed railways, and urban rail on urban carbon emissions. The results shows that: (1) Overall, high-speed railways have a significant reducing effect on carbon emissions, while highways and urban rail have the opposite effect. (2) Considering spatial spillover effects, highways and high-speed railways can promote carbon emissions reduction in neighboring areas, while urban rail has the opposite effect. (3) For scale heterogeneity, urban rail can reduce carbon emissions in mega-cities, while highways and high-speed railways have the opposite effect. For regional heterogeneity, all three types of transport infrastructure can reduce carbon emissions in western cities, but increase urban carbon emissions in eastern and central regions. (4) Industrial upgrading, technological progress, and population agglomeration are all pathways through which transport infrastructure indirectly affects carbon emissions, but their effects vary for different transport infrastructure. • Urban rail can reduce carbon emissions in mega-cities, while highways and high-speed railways have the opposite effect. • Transportation infrastructure has a significant spatial spillover effect on urban carbon emissions. • Transportation infrastructure has significant differences in carbon emissions across cities of different scales and regions. • The indirect impact path is industrial structure upgrading, technological progress, and population agglomeration. [ABSTRACT FROM AUTHOR]

In recent decades, the use of fossil fuels has had a harsh impact on the climate, and the frequency and intensity of various extreme weather events have increased, which has triggered an increased the use of renewable energy sources and reflection on technological advances. Many countries are trying to promote renewable energy to reduce their impact on climate change, but the impact of national energy policies in the climate risk framework remains poorly understood. Based on the panel data of 84 developed/developing countries around the world from 2006 to 2019, this paper studies and analyzes the impact of renewable energy use on climate risk. The study found that the increase in the proportion of renewable energy use can reduce the climate risk, and this result is still robust after undergoing robustness tests such as changing variables, samples, and research methods. The findings offer an important solution for European countries, where climate risks are most acute. The heterogeneity analysis shows that the higher the level of economic development, population density and the lower the level of incorruptibility, the weaker the inhibitory effect of renewable energy use on climate risk. The mechanism analysis also shows that the increase in the proportion of renewable energy use can reduce climate risk by reducing carbon dioxide (CO 2), methane (CH 4), nitrogen monoxide (NO), PM2.5 emissions, and the proportion of fossil fuel use, but it does not reduce climate risk by increasing biodiversity. In particular, we find that technological progress has not played a role in the use of renewable energy to reduce climate risk, breaking the stereotype. The policy recommendation of this paper is that under the increasing pressure of climate change, the transition to clean energy is an indispensable option, and the need to accelerate the energy transition becomes more urgent. There is a greater need to further protect biodiversity and enhance technological progress. • The increase in the proportion of renewable energy use can reduce the climate risk. • The mechanism is to reduce CO 2 , CH 4 , NO, PM2.5 emissions and fossil fuels use. • The use of renewable energy cannot reduce climate risks by increasing biodiversity. • The impact of renewable energy use on climate risk is heterogeneous. • Technological progress has not played a role in the use of renewable energy to reduce climate risk. [ABSTRACT FROM AUTHOR]

Digital infrastructure serves as a crucial foundation for development in the era of the digital economy. In light of this, this paper takes digital infrastructure construction as its focal point. Utilizing Python technology and the Meta-frontier non-radial directional distance function to calculate the level of digital infrastructure construction and industrial energy efficiency. It then employs a dynamic panel data model to analyze the impact effects and mechanisms of digital infrastructure construction on industrial energy efficiency. Additionally, threshold models and modified gravity models are employed to explore the nonlinear effects and spatial impacts of digital infrastructure construction on industrial energy efficiency. The research findings reveal that the enhancement of digital infrastructure significantly improves industrial energy efficiency. Moreover, indicate a shift in the impact of digital infrastructure construction on industrial energy efficiency from inhibitory to promotional as the level of digital infrastructure construction increases. The mechanism of this effect suggests that digital infrastructure construction can promote the improvement of industrial energy efficiency through green technological innovation and the advancement of industrial structure. Further analysis shows that the spatial network characteristics of digital infrastructure construction notably elevate the level of industrial energy utilization efficiency. This study provides practical policy implications for sustainable development. • Digital infrastructure construction markedly enhances industrial energy efficiency. • There is a non-linear picture of the impact of digital infrastructure construction on industrial energy efficiency. • The effects of green technology innovation and advanced industrial structure are crucial channels. [ABSTRACT FROM AUTHOR]

As a zero-carbon energy, hydrogen energy is widey recognized as playing an important role in reducing carbon emissions and addressing climate change. Considering the resource and industrial conditions in China, the coal-to-hydrogen coupled with carbon capture and storage (CTHCCS) may be a necessary choice in the early stage of low-carbon hydrogen energy development. This study used real option models to analyze the investment benefits of the representative CTHCCS technology at the national and regional levels in the current and future development scenarios in China, and discusses the impact of uncertainties in carbon price, technological progress, and policy incentives on the CTHCCS investment. The results show that (1) The opportunity for immediate investment in the CTHCCS is not available in China unless the cost of carbon capture and storage (CCS) technology decreases and the carbon price increases significantly. (2) The current CTHCCS investment critical carbon price is 353.3 RMB/t, which will decrease by 45.0%, 73.9% and 57.3% when using the initial investment subsidy, carbon emission reduction subsidy and clean fuel subsidy, respectively. (3) The CTHCCS presents a relatively high investment benefit in Xinjiang, Inner Mongolia, and Shaanxi, highlighting that these areas are key pioneers for "blue hydrogen" production in China. • The real option model is used to evaluate investment decisions for CTHCCS projects. • Uncertainty of carbon price, technology progress and policy subsidy are considered. • Carbon price of 353.3 RMB/t could trigger immediate investment for CTHCCS projects. • Policy incentives lead to a 45–74 % reduction in the CTHCCS critical carbon price. • Xinjiang and Inner Mongolia could be priority areas for blue hydrogen production. [ABSTRACT FROM AUTHOR]

The chemical industry is one of the fundamental industries of economic development. Coordinating the relationship between economic growth and carbon emissions (EGCE) is crucial in realizing the carbon neutrality target. The Tapio model and decomposition models are used to assess the degree of decoupling within the Chinese chemical industry and identify pivotal factors impeding progress. The energy efficiency decomposition model explores the crux of failure to achieve strong decoupling. This framework further decomposed the energy intensity to uncover how technical efficiency, technological progress, and input substitution changes affect energy intensity and CO 2 emission. The paper found that the EGCE of the chemical industry were stable in a weak decoupling mode from 2009 to 2019. The reliance on technological progress to reduce energy intensity and emissions is insufficient (accounting for only 18.2%), far below the cumulative contribution from economic growth (accounting for 57.76%), which has become the crux of the strong decoupling failure. Technological advancements drive energy substitution for labour, resulting in 244.41 Mt of cumulative carbon emissions. The improper factor input allocation hinders the desired reduction in energy intensity and carbon emissions. A series of policy implications are proposed based on the insights derived from the decomposition analysis to foster sustainable practices in the chemical industry. [Display omitted] • This study focuses on the decoupling in chemical industry. • The decoupling between economic growth and carbon emissions (EGCE) is explored. • The reasons for the failure of strong decoupling from technical perspective are tested. • The decoupling between EGCE of chemical industry was in a weak decoupling mode. • Technological progress accelerated the substitution of energy for labour. [ABSTRACT FROM AUTHOR]

Membrane-based operations, especially pressure-driven membrane operations, are today well-established procedures for various applications in the wine industry thanks to their intrinsic properties and undoubted advantages over traditional methods. Emerging membrane processes, such as pervaporation, electrodialysis and osmotic distillation, forward osmosis, membrane contactors, offer new and interesting perspectives to improve quality and develop new products without compromising organoleptic properties. This review provides a comprehensive overview on the use of membrane operations in wine processing. A bibliometric and scientometric analysis has been done to provide the current advances dealing with the application of these operations in different steps of wine manufacture, including clarification, stabilization, concentration, acidification, deacidification and dealcoholization. The current challenges and perspectives are highlighted to guide further advancements of membrane technology in this field. The use of conventional and emerging membrane systems offers interesting opportunities to improve and optimize current practices of the wine processing industry. Considerable progress has been done concerning the development of low-fouling materials, identification of wine molecules responsible for membrane fouling and methods to mitigate such phenomenon in the clarification of wines by microfiltration membranes. Technological progress in electrodialysis makes this process a very attractive method for tartrate stabilization, acidification and deacidification of wines. Different conventional and emerging membrane processes offer valid post-fermentation strategies to remove ethanol in wines while preserving their original characteristics. The global results provide interesting perspectives for a wider implementation of membrane processes in the winemaking industry and to redesign the traditional vinification process under the process intensification strategy. • An overview of membrane technology in wine processing is presented. • Bibliometric and scientometric analysis provide current advances of membrane technology in the field. • Conventional and emerging membrane processes are analyzed. • Current challenges and perspectives are highlighted to guide further advancements. • Interesting perspectives of global results for redesigning the traditional vinification process. [ABSTRACT FROM AUTHOR]