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Land use conflicts are intensifying in Northern Sweden due to the increasing global demand for resources coupled with the green transition. In line with this, a thorough understanding of land use conflicts in the area is becoming necessary as economic activities expand and newer ones are developed. Hence, this paper aims to provide a systematic literature review of research on land use conflicts specific to Northern Sweden, focusing on various economic activities such as forestry, mining, tourism, energy sector and reindeer husbandry. Additionally, we aim to determine lessons learned and suggested ways forward based on a systematic review. We used Scopus and Web of Science on June 2023 and through descriptive statistical analysis of 33 articles, we summarized research trends and gaps. We found three main typologies of conflicts and five main themes of suggested ways forward. Recommendations agree that there should be a broader understanding of the underlying interests of the stakeholders; and there should be an inclusive, more participatory approach to discussing potential solutions, not to create an agreement but to come to an understanding. Beyond academic insights, the findings hold practical relevance for shaping effective land use policies. This paper offers valuable lessons that extend beyond the local context, informing broader discussions and policy considerations for sustainable land management in the larger Arctic setting, where similar challenges and resource demands are unfolding. [ABSTRACT FROM AUTHOR]

As the EU strives to achieve its climate goals, it is becoming increasingly crucial to understand the complex relationships between economic activity, energy consumption, and carbon emissions. In this context, our paper aims to investigate the correlation between carbon emissions, energy consumption, and economic development. To fulfill our aim, we have used Eurostat and OECD data for the EU-27 member states for a period of 13 years (2010–2022), using a linear regression as the main analysis method. Our results have shown that there is a strong correlation between demand-based and production-based CO2 emissions as well as between production-based CO2 emissions and final energy consumption, while at the same time, our findings have shown that there is no direct correlation between energy consumption and economic development, aligning our study with the neutrality hypothesis of the energy growth nexus. This paper expands the ongoing discussion on sustainable development and climate change mitigation by conducting a thorough analysis of the EU-27 countries over a span of thirteen years. The results emphasize the need for integrated strategies that address both production and consumption emissions, emphasize the vital role of energy efficiency, and raise questions about the effectiveness of increasing energy consumption to enhance economic productivity or CO2 efficiency. [ABSTRACT FROM AUTHOR]

Micro and large-sized enterprises are important elements to enhance the economic growth of any country, and even more so for developing countries such as Mexico. These enterprises highly contribute to job generation, competitiveness, and gross domestic product, factors that are important for the developing of a nation. The aim of this paper is to study the impact of human capital investments in the efficiency of the 21 economic activity subsectors for micro and large-sized enterprises in the Mexican manufacturing industry between 2009–2021. The database come from Mexico Annual Manufacturing Industry Survey. Four Data Envelopment Analysis models are developed to study the relationship between annual average working days, annual average wages, and annual average investment in training with average sales per year. Data indicate that, most of the micro-sized enterprises of the Mexican manufacturing sector do not invest in human capital training, contrary to their large-sized enterprises. The results show that investing in human capital training increase sales and wages in micro-sized enterprises of the Mexican manufacturing industry, but it is not evident in large-size enterprises of the Mexican manufacturing industry. The calculation of the economic activity subsectors efficiencies using the developed Data Envelopment Analysis models indicate that all the economic activity subsectors with scale efficiency equal to one optimally invest, and the average amount of investments in human capital training needed to increase the global and pure technical efficiencies of the others are calculated with the developed Data Envelopment Analysis models. In the three main economic activity subsectors of the Mexican manufacturing industry, a significant increase—in 83.33% of cases—in wages and salaries is seen in both micro and large-sized enterprises. Particularly, the results indicate that the Chemical industry economic activity subsectors show the highest efficiency in both micro and large-sized enterprises when the human capital training variable is present. This paper demonstrates the importance of investing in human capital to enhance the efficiency of micro and large-sized enterprises. [ABSTRACT FROM AUTHOR]

Economic activities' efficiency represents the level of performance that uses the lowest quantity of inputs to achieve the highest possible amount of output. This paper presents the process of calculating the relative efficiency of separate non-financial activities in an economy using the DEA methodology. The purpose of this paper was to create the DEA model for monitoring the relative efficiency of individual non-financial activities of the economy. The purpose was achieved through the realization of two objectives. The first one included the determination of the relative efficiency of the above-mentioned activities in the period from 2002 to 2020 using the data from non-financial entities in the Republic of Croatia. The second objective consisted of ranking the economic activities according to their relative efficiency. An output variable that measures the efficiency was presented using the return on assets, while the total debt to EBITDA, EBITDA per employee, assets turnover and human capital efficiency were used as input variables. Research results indicate that the DEA methodology could be used as an economic activity's relative efficiency measurement tool, giving the possibility to rank it according to its relative efficiency using the accounting ratios. Research results show that service sectors' economic activities were the most efficient ones according to the lower assets engagement and the respective sources of financing that dominate. The highest average relative efficiency in 19 years was scored using wholesale, retail and repair activities as well as information, communication and education. The lowest average relative efficiency was achieved in construction, water supply, sewerage, waste management and remediation activities as well as accommodation and food service activities, which is the consequence of their low level of activity and profitability and high indebtedness in the analyzed period. The relative efficiency scores calculated using the DEA methodology could be used as a benchmark for companies on a micro level, while on the macro level decision-makers can obtain a deeper insight into the relative efficiency of the nonfinancial activities. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, we present the zooarchaeological and taphonomic study of a new Bronze Age site in the inland of the Iberian Peninsula. This study represents a significant contribution within the studied area, as it analyses the Pista de Motos faunal collection, one of the few representative samples from this period. This paper significantly contributes to completing the scarce information available for the Bronze Archaeology in the Middle Tagus Valley, located inland of the Iberian Peninsula. The Bronze Age zooarchaeological research for the interior and other regions of the Iberian Peninsula is currently limited. Despite several sites with known zooarchaeological profiles from the period, the main issue is that most of these derive from fragmentary and unrepresentative faunal records or are biased profiles from old excavations. New work has yielded novel zooarchaeological results in recent years that could help fill the existing zooarchaeological information gap in the Iberian inland, particularly in the Middle Tagus Valley. However, these projects are in the initial research stages and have not published much of their results. This paper presents the zooarchaeological profile of the Pista de Motos Bronze Age site to help fill this information gap. It analyses the taxonomic representation, skeletal profiles, and human activity patterns associated with faunal use. These observations suggest that animal exploitation at the site followed two primary purposes. One was linked to economic activities, mainly to obtain meat, milk, wool, or animal labour. The other was probably associated with symbolic-ritual practices suggested by the complete animal burials in some excavated units. We contextualise these interpretations with evidence from other Bronze Age sites in the Middle Tagus Valley. Finally, the paper assesses to what extent Pista de Motos is a relevant site for the zooarchaeology of the Bronze Age in the Iberian inland. [ABSTRACT FROM AUTHOR]

Timely and accurate rainfall prediction is crucial to social life and economic activities. Because of the influence of numerous factors on rainfall, making precise predictions is challenging. In this study, the northern Xinjiang region of China is selected as the research area. Based on the pattern of rainfall in the local area and the needs of real life, rainfall is divided into four levels, namely 'no rain', 'light rain', 'moderate rain', and 'heavy rain and above', for rainfall levels nowcasting. To solve the problem that the existing model can only extract a single time dependence and cause the loss of some valuable information in rainfall data, a prediction model named DFFNet, which is based on dual-branch feature fusion, is proposed in this paper. The two branches of the model are composed of Transformer and CNN, which are used to extract time dependence and feature interaction in meteorological data, respectively. The features extracted from the two branches are fused for prediction. To verify the performance of DFFNet, the India public rainfall dataset and some sub-datasets in the UEA dataset are chosen for comparison. Compared with the baseline models, DFFNet achieves the best prediction performance on all the selected datasets; compared with the single-branch model, the training time consumption of DFFNet on the two rainfall datasets is reduced by 21% and 9.6%, respectively, and it has a faster convergence speed. The experimental results show that it has certain theoretical value and application value for the study of rainfall nowcasting. [ABSTRACT FROM AUTHOR]

The objective of this study was to conduct a detailed analysis of the available flow series in the Chiriquí Viejo River basin in Panama. This paper examines the patterns of variation within these series and calculates various hydrological indexes indicative of the region's hydrology. Utilizing advanced hydrological indexes within the Chiriquí Viejo River basin in Panama, which spans an area of 1376 km2 and supports an estimated population of 100,000 inhabitants, analytical methods were employed to compute indexes such as the Daily Flow Variation Index (QVAR), the Slope of the Flow Duration Curve (R2FDC), the Hydrological Regulation Index (IRH), and the average duration of low (DLQ75) and high (DHQ25) flow pulses. The results indicate moderate flow variability (QVAR of 0.72) and a Hydrological Regulation Index (IRH) of 2.32, signifying a moderate capacity for flow regulation. Notably, low flow events (DLQ75) lasted approximately 3.73 days, while high flow events (DHQ25) lasted around 4.08 days. The study highlights a significant capacity to respond to extreme events, with maximum annual flows reaching 80.25 m3/s and minimum flows dropping to 3.01 m3/s. Despite the significant contribution of the basin to hydroelectric power generation and other economic activities, there is an observed need for sustainable management that accommodates hydrological fluctuations and promotes resource conservation. The conclusions indicate that these findings are critical for future planning and conservation strategies in the region, emphasizing the importance of integrating multidisciplinary approaches for Hydro-Social Sustainability. This novel and holistic approach underscores the interdependence between hydrological dynamics, socio-economic activities, and environmental sustainability, aiming to ensure the long-term resilience of the Chiriquí Viejo basin and its communities. [ABSTRACT FROM AUTHOR]

The existence of fluctuations is part of the narrative, especially when there is a slowdown (or worse, a contraction) in economic activity. The presence of long waves with a period of about 50 years as proposed by Kondratieff is one of the most controversial and fascinating theories about economic cycles. This paper analyses both the original Kondratieff data (from which the hypothesis started) and a dataset that includes GDP per capita for several significant countries. By applying the wavelet analysis (WA), the main objective of the paper is to understand whether it is plausible to support the existence of periodic fluctuations consistent with long cycles theory. The outcomes for Kondratieff's original dataset do not show the presence of a coherent periodicity for most cases. The same conclusion can be drawn for all the GDP per capita series. [ABSTRACT FROM AUTHOR]

Background: There is a growing need for logistics professionals in different positions and with different competencies. The key question is how to attract and retain a highly skilled workforce. The purpose of this research is to determine what factors and how they affect employee's satisfaction and loyalty in the logistics sector in the Serbian market; Methods: The impact of company size, primary business activity and employee position on labor loyalty and fluctuation were examined. The research hypotheses were tested on the basis of data obtained from a web survey that included 270 respondents from different industrial sectors in the Serbian market. Linear regression was used for hypothesis testing; Results: The results showed, among other things, that salary and advancement possibility are the main motives for changing jobs. The importance of basic professional knowledge acquired at the faculty for employment and working in various companies was confirmed; Conclusions: There are no papers in the literature that investigate job satisfaction and employee turnover in the logistics market. The results of this research, on the one hand, provide useful and accurate information for decision-making in order to improve the situation in the observed market, while on the other hand, provide an excellent basis for future research. [ABSTRACT FROM AUTHOR]

As a new concept for systematically evaluating ecosystem services, Gross Ecosystem Product (GEP) provides an effective means to comprehensively reveal the overall status of the ecosystem, the impact of economic activities on the ecological environment, and the effectiveness of ecological protection efforts. GEP accounting has been conducted in various regions; however, GEP's application in natural reserves still requires further exploration. Taking the Qinling Mountains as the research area, this paper aims to assess the relationship between GEP and economic development on the basis of the GEP accounting system. The results indicated that: (1) From 2010 to 2020, GEP tended to increase continuously and exhibited a distribution pattern with high value regions in the east and west, and low value regions in the north and south. (2) Over the years, the coupling coordination degree between GEP and GDP was in a consistent upward trend. In 2020, a good coupling coordination state between GEP and GDP was achieved in most districts and counties. (3) With the relative development between GEP and GDP, the social economy of most districts and counties lagged behind GEP in 2010. The number of districts and counties lagging in GEP in 2020 increased, while the number of regions with a balanced development of GEP and GDP was still relatively discouraging. (4) In general, elevation, contagion, temperature, population density, and precipitation were the main drivers of coupling coordination degree between GEP and GDP. If the relationship between economic development and ecological environmental protection can be reasonably balanced, it will further promote the sustainable development of nature reserves, and provide a scientific basis for sustainable policy-making in other similar areas. [ABSTRACT FROM AUTHOR]

Potash fertilizer production is one of the most important economic activities. Historically, potash mining has had a significant impact on the environment, often with catastrophic consequences. The purpose of this paper is to summarize the results of studies on the environmental impact of potash mining using the example of the Verkhnekamskoe potash deposit. The deposit is located in the central part of the Solikamsk depression in the Pre-Ural foredeep (Perm Krai, Russia). All the main features and problems of underground mining of water-soluble ores and potassium fertilizer production are considered using the example of one of the world's largest potash deposits. This paper looks into the specifics of the material composition of waste, its disposal, underground mining issues associated with the solubility of salts, and the risks of groundwater inflow into the mine workings, which causes flooding of mines. The results of all surveys show that potash mining affects the atmosphere, surface water, groundwater, soil, and vegetation. The most effective measure to reduce the adverse environmental impact of potash mining at the Verkhnekamskoe Deposit is hydraulic backfilling of mine chambers, which protects the underground mines from flooding, minimizes ground subsidence, and reduces the area of potash waste. [ABSTRACT FROM AUTHOR]

The emission of air pollutants from energy production and consumption is a major cause of environmental problems. In addition, urbanisation and CO2 emissions have become major environmental concerns that are closely related to climate change and sustainable economic growth. The purpose of this paper is to investigate the long-run relationship among CO2 emissions, energy consumption, economic activities, and management issues for Turkey for the period between 1980 and 2021. The STIRPAT hypothesis and the environmental Kuznets curve (EKC) hypothesis were employed by using dynamic conditional correlation (DCC) and ARDL bound methodologies for these goals. The findings indicate that there is a long-run relationship between variables of the STIRPAT model. The coefficient of economic expansion and energy consumption affected CO2 emissions positively, which means that energy consumption and the expansion of economic activity have significant effects on environmental degradation. Those results are also confirmed by the environmental Kuznets curve (EKC) model. In addition, the N-shaped environmental Kuznets curve (EKC) is developed for Turkey. The DCC model also shows that economic growth increases CO2 emissions significantly, and energy productivity can be considered for decreasing CO2 emissions. [ABSTRACT FROM AUTHOR]

Cities enhance the efficiency of green development among themselves through their borrowing population, economic activities density and advanced functions, but the positive green effect of the borrowing size is affected by the city size. Using panel data of 280 prefecture-level cities in China for the period 2009–2019, this paper measures the borrowing size in three dimensions, namely the borrowing population size, borrowing economic activity density and borrowing advanced functions, and uses the super efficiency slacks-based measure (SBM) model, including non-desired outputs, to measure the urban green development efficiency. After that, this paper empirically examines the effect of the borrowing size on the urban green development efficiency in the Chinese urban network using a double-fixed-effect model. A panel threshold regression with city size as the threshold variable is conducted to evaluate the nonlinear relationship quantitatively between the borrowing size and urban green development efficiency. The results show that all three dimensions of the borrowing size have positive effects on the urban green development efficiency. There is a significant double-threshold effect between the borrowing size and urban green development efficiency; under the threshold of the city size, there is a U-shaped relationship between the borrowing population size, borrowing advanced functions and urban green development efficiency, whereas there is an inverted U-shaped relationship between the borrowing economic activity density and urban green development efficiency. Accordingly, this paper argues that government should pay attention to the role of the borrowing size in promoting urban green development efficiency and reasonably expand the city size. [ABSTRACT FROM AUTHOR]

Despite its immense natural resources, Angola struggles to significantly improve its economy to reduce poverty. Carbon emissions have been increasing over the years, even though the country plans to reduce them by 35% by 2030. This paper attempts to assess the carbon emissions of several sectors (industries, transport, services, and residences) on economic growth, intending to find a balance between environmental protection that requires carbon emissions reduction and economic development that may add to environmental degradation. The study employed time series data on GDP, CO2, CH4, and N2O covering 1971 to 2021 and ARDL and ECM models. This is the first study at the state level in Angola on the relationship between economic development and environmental sustainability considering methane and nitrous oxide emissions. Additionally, the paper assesses the responses of GDP to deviation shock of GDP, CO2, CH4, and N2O by 2032. Phillip Perron and Augmented Dickey-Fuller tests showed that all the data are stationary at the first difference, favoring the application of the ARDL model to explore the short and long-run relationships. The result reveals that methane from agricultural activities and carbon emissions from the building sector and public services contribute to economic growth, whereas carbon emissions from industrial heat systems, non-renewable electricity production, and manufacturing industries harm economic growth. However, no relationship exists between nitrous oxide emissions and economic development. In addition, impulse response function estimates show that appropriate investments can sustain economic development over the years. Therefore, the country should diversify its economy and avoid polluting fuel sources, such as coal. Raising renewable energy's proportion in the total energy mix can support growth while considering the environmental quality. Investments in skills training, academic projects in renewable energy technologies development, agriculture mechanization, and sustainable job creation are recommended. Additionally, investing in quality seeds adapted to climate realities might help lessen climate change's adverse effects and promote growth. Manure manufacturing processes must be improved to reduce agriculture and livestock's methane and nitrous oxide emissions. The country's leaders are encouraged to promote raw material processing industries while insisting on reducing carbon emissions. [ABSTRACT FROM AUTHOR]

Cryptocurrencies and their market capitalisation have experienced vibrant growth in the last few years. Their total market cap is more than USD 858 billion as of the date of writing and is growing, with nearly 21,984 tradeable cryptos in 530 exchanges. It is emerging as one of the biggest threats to the traditional fundraising market. The issue of the industry's long-term viability and steady expansion is of paramount importance. Even though unsustainable and uneven growth could help boost economic activity in the short term, it would be detrimental in the long run because of the risk of extinction. This paper is one of the first attempts to identify the factors contributing to the growth of the cryptocurrency market and their effects. This paper is based on the hybrid MCDM methodology of research and uses fuzzy–ISM (interpretive structural modelling). This method is divided into three phases: identification, expert opinion, and interpretation. Sixteen factors were chosen from the previous literature and suggestions from industry professionals. Seven barriers have been framed based on the fuzzy–ISM analysis to better understand the impacts of and interrelationships among the identified barriers. The factors are further classified using fuzzy MICMAC into four major categories based on the drive power and dependence power extracted from the fuzzy matrix. This paper explains the importance of all identified factors as enablers of the acceptance of cryptocurrencies for investment and fundraising. [ABSTRACT FROM AUTHOR]

Background: In this paper, a new closed-loop supply chain (CLSC) network model, including economic, social and environmental goals, is designed. This paper's primary purpose is to meet customers' uncertain demands in different scenarios where the new robust-fuzzy-probabilistic method has been used to estimate the exact demand. Furthermore, strategic and tactical decisions, such as vehicle routing, facility location and optimal flow allocation in the CLSC network, are considered, and features such as queuing system in product distribution and time window in product delivery are considered. Methods: To solve the problem, NSGA II and MOPSO have been used. Results: The results of solving numerical examples in larger sizes show that as the environmental effects decrease and the social effects increase, the design costs of the total supply chain network (SCN) increase. Moreover, the NSGA II is more efficient than the MOPSO in problem-solving and achieving comparison indicators. Conclusions: The results of sensitivity analysis show that with increasing network uncertainty rate, the total costs of the SCN, the amount of greenhouse gas emissions and the maximum vehicle traffic time increase. [ABSTRACT FROM AUTHOR]

Today, the location of a business is more important than ever, as it contributes to its consolidation in the market and, in parallel, to the economic development of a city. Over the years, the theories about the optimal location of a business have undergone various changes, both financial and spatial. On the other hand, economic geography, as a discipline that studies the distribution of economic activities as well as the interactions between them, is also an important tool for the analysis of urban/spatial and business processes. This paper finds the optimal locations of economic activities through the combination of theories of economic geography and spatial analysis, for the sake of reducing urban shrinkage and increasing the resilience of businesses and cities. The analysis of this paper proved that the areas that are most exposed to urban shrinkage are the least central areas. Urban shopping centers, despite the large percentage of closed stores, continue due to their centrality to attracting more new businesses. The calculation of the optimal location of the economic activity showed that the optimal location depends on the financial sector itself but also on the economic activities that open or close over time in this region. In this way, an answer is sought regarding the way in which each region and its economic identity can influence a city’s future development and resilience. Thus, through this analysis, cities are able to control and strengthen their economic landscapes, vulnerable as they are in difficult times, and to implement policies in specific urban units, with a view to the prosperity of their economic activities. [ABSTRACT FROM AUTHOR]

The effects of various geopolitical tensions, conflicts between countries and the global post-pandemic COVID-19 have caused an acceleration in the price level in many countries around the world. This research focuses on Mexico since its monetary policy has created intricate interactions between inflation and growth in the short and long term, maintaining recently one of the highest real interest rates in Latin America (on average 5.75% vs. the US 2.3%). This paper examines the asymmetric link between the National Consumer Price Index and the Global Economic Activity Index in Mexico during the period 1994–2023. To do this, a Nonlinear Autoregressive Distributed Delay (NARDL) model is used with monthly data, which will allow the relationship between both variables to be more adequately investigated. The main empirical finding is that upward or downward shocks to the consumer price index have caused different effects in magnitude and sign on economic growth over time. Finally, several reasonable, practical, and feasible recommendations are provided for the design of the monetary policy considering non-linear effects. [ABSTRACT FROM AUTHOR]

The purpose of this paper was to examine the differences in using agricultural entrepreneurship support and how it relates to characteristics such as the agrarian structure, socioeconomic development level, and land use across the Polish territory. The analyses were carried out at the district (poviat) level which is an intermediate administrative unit. This study found that the decisions on co-financing the measures dedicated to non-agricultural economic activity heavily depended on the agrarian structure. The highest levels of activity were witnessed in districts where the agrarian structure was particularly fragmented. [ABSTRACT FROM AUTHOR]

Apple orchards, as an important center of economic activity in forestry special crops, can achieve yield prediction and automated harvesting by detecting and locating apples. Small apples, occlusion, dim lighting at night, blurriness, cluttered backgrounds, and other complex scenes significantly affect the automatic harvesting and yield estimation of apples. To address these issues, this study proposes an apple detection algorithm, "YOLOv5-ACS (Apple in Complex Scenes)", based on YOLOv5s. Firstly, the space-to-depth-conv module is introduced to avoid information loss, and a squeeze-and-excitation block is added in C3 to learn more important information. Secondly, the context augmentation module is incorporated to enrich the context information of the feature pyramid network. By combining the shallow features of the backbone P2, the low-level features of the object are retained. Finally, the addition of the context aggregation block and CoordConv aggregates the spatial context pixel by pixel, perceives the spatial information of the feature map, and enhances the semantic information and global perceptual ability of the object. We conducted comparative tests in various complex scenarios and validated the robustness of YOLOv5-ACS. The method achieved 98.3% and 74.3% for mAP@0.5 and mAP@0.5:0.95, respectively, demonstrating excellent detection capabilities. This paper creates a complex scene dataset of apples on trees and designs an improved model, which can provide accurate recognition and positioning for automatic harvesting robots to improve production efficiency. [ABSTRACT FROM AUTHOR]

Mining and quarrying were important economic activities in Europe in past centuries, but during the 20th century, raw materials became vital to societal development. Mining has been subject to fluctuations related to wars, economic crises, and advances in environmental rights. A series of events led some European countries, such as Spain, to assume a leading position in the market for certain raw materials, such as tungsten. However, most of Europe's mines have been abandoned. This paper considers several postindustrial heritage sites that can used to illustrate how metal and stone were extracted in past centuries. Such sites have become a tourist attraction in the context of heritage in some countries. This area in western Spain, which contains ancestral quarries that helped build the architectural heritage of UNESCO World Heritage Cities and artisanal mines that contributed to building the economy of an extremely poor population, has a story to tell. All these mines and quarries can be used to explain the cultural heritage of the area as part of a postindustrial heritage landscape. [ABSTRACT FROM AUTHOR]

This paper investigates whether business cycles cause financial cycles or vice versa. We also assess whether the US plays a leading role in causing the domestic business and financial cycles of other countries. The literature has established that business and financial cycles are linked through several channels such as credit constraints, the real effects of financial information and the reversal of overoptimistic expectations. Our analysis evaluates the direction of Granger causality using a novel approach based on the mixed-frequency vector autoregression model for the G7 countries. Our approach exploits the fact that real economic activity measured by industrial production is observed at a higher frequency than aggregate credit. We find strong evidence of bidirectional causality between the business and financial cycles, especially in recessions. Furthermore, the US is a global leader since the US business cycle significantly affects other countries' business cycles, especially in terms of expansions. [ABSTRACT FROM AUTHOR]

Economic activities are directly supported by the natural environment, and in this context, it has become crucial to analyse the phenomenon of decoupling economic growth from environmental degradation. The negative effects of economic activities on the environment are clearly visible, and understanding how to separate economic growth from environmental harm is of utmost importance. This paper aims to study the degree of the decoupling of economic growth, measured by GDP, from environmental degradation, quantified through CO2 and HFCs emissions, at the level of each EU27 country in the periods 2008–2012 and 2013–2020. In the analysis, graphical representations and statistical tests were utilised. In the first period, most of the EU27 countries registered negative levels for the variables considered, placing them into the negative coupling stage. In the second period, the evolution of the decoupling process was visible in all the countries, enabling them to make a significant transition to the relative or absolute stages. Overall, the Nordic countries could be observed as examples of best practices, managing to achieve the most desired stage of decoupling, i.e., the absolute one. These results are important for a wide range of stakeholders implicated in the preparation of programs, projects and policies dedicated to achieving economic growth in a sustainable manner. [ABSTRACT FROM AUTHOR]

Canary Island date palms (Phoenix canariensis) have been planted as a landscaping feature plant throughout warm, temperate, and subtropical climates. The physical amenity provisioning of this species (shade effects, microclimate amelioration, water usage, etc.) has so far not been systematically assessed. This paper reports on temperature and humidity measurements in both a suburban and a rural location in SE Australia. The study demonstrates the effects of the palm canopy as regulator of humidity and provider of shade and, thus, amenity values in urban landscape settings. Drawing on published energy savings and growth requirements of the plant, the paper argues that Canary Island date palms are landscaping plants suitable to ameliorate the microclimate in urban neighborhoods with varied socio-economic conditions. [ABSTRACT FROM AUTHOR]

This paper focuses on the context of the Autonomous Province of Trento in Northern Italy, which has hosted common regime institutions that manage collective mountain properties daily since the 13th century. These institutions operate in the most significant part of the territory and adapt their routines to emerging challenges. From different scientific perspectives (economic, anthropological, and architectural), we analyzed how this method has been actualized as the most effective management of local resources, generating opportunities for commoners, new citizens, and external users. This includes the exposure of the communities to novel economic activities, adaptation of the internal normative and planning systems, and reflection on how to combine natural resources with local needs and global scenarios. [ABSTRACT FROM AUTHOR]

The development of cloud technologies enables companies to actively implement technologies for cost management and risk reduction in their financial and economic activities. The use of cloud-based models of risk management in the financial and economic activities of the enterprise will help small and medium-sized companies in the agro-industrial sector in Russia to make structural and strategic changes, as well as discover new opportunities for business expansion. The purpose of the study is to develop models for cost management and reduction of risks in the financial and economic activities of companies based on the OLAP technology for application in Russian agro-industrial enterprises. The study employs a qualitative approach based on the case study methodology. The paper discloses and substantiates the authors' conceptual model of a cost management system that allows executives to make decisions proceeding from four types of cost prices. The distinguishing feature of the management system is the use of a digital twin, which makes it possible to manage risks at the early stages of decision-making. The application of OLAP systems improves the quality of analysis and visualization methods as part of the cost management system. In addition, the study provides practical insight into how the applied model will help small and medium-sized agro-industrial enterprises to develop different business vision strategies based on cost reduction, manage the level of risk at the early stages of decision-making, and analyze information from a geographically dispersed logistics chain of divisions (production facilities, warehouses, stores). [ABSTRACT FROM AUTHOR]

Archaeological research at Ojców castle has yielded important information about life in that medieval castle. The results of zooarchaeological analyses presented in this paper complement the archaeological research, adding to our knowledge of the diet of the castle inhabitants from the time of establishment of the castle until the final residents. Zooarchaeological research is also complemented by data from older settlement phases on the castle hill, directly related to the Lusatian culture in the early Iron Age. The great variability of remains from mammals, birds, and fish and the taphonomic features of bones found in the different chronological strata of the castle's courtyard reflect the diverse economic activities that took place in particular times and spaces. [ABSTRACT FROM AUTHOR]

The territory of the Crimean Peninsula is extensively subject to economic activities. In this connection, there is an ever-increasing impact on the environment. The present paper presents an analysis of the transformation of the area of the largest river basins of the northwestern slope of the Crimean Mountains (basins of the Zapadnyy Bulganak, Alma, Kacha, Belbek, and Chernaya rivers). For this purpose, various indicators characterizing the transformation of the area were calculated: coefficient of anthropogenic transformation; land degradation index; urbanity index; level of anthropogenic transformation; coefficient of absolute and relative intensities of ecological and economic land use distribution. The results show that the anthropogenic transformation of the area defined by the basins of the Zapadnyy Bulganak, Alma, Kacha, Belbek, and Chernaya rivers increases from the southeast to the northwest as the absolute height decreases, and when moving from river source to mouth. Among the basins under consideration, anthropogenic transformation is greatest In the Zapadnyy Bulganak River basin and lowest in the Chernaya River basin. Among the basins under consideration, anthropogenic transformation decreases from north to south in the following order: Zapadnyy Bulganak River basin, Alma River basin, Kacha River basin, Belbek River basin, Chernaya River basin. This is due to reduced impacts of economic activity within each respective basin. [ABSTRACT FROM AUTHOR]

The main objective of this study is to demonstrate that opportunities to support the poor marginalised Roma communities (MRCs) by creating opportunities for their active participation in tourism development have been under-ultilised to date. In particular, the application of a pro-poor tourism (PPT) approach is an advantage that allows the cultural specificities of the MRCs to be exploited for their own development. A risk factor for successful implementation is the considerable differentiation within Roma communities. This study analyses the approaches of 65 municipalities of the Central Spiš region to the development of PPT as an option for poverty reduction in the MRCs in Slovakia. Based on the analysis of the local preconditions for tourism development, the specific potential for the development of Roma culture and the traditional economic activities, human resources, and the degree of segregation, we show that there is no universal solution that would be applicable in all communities. The limited possibilities to obtain relevant data determined the analysis options we used. Therefore, we used a mixed-method approach, in which we subjected the quantitative data to qualitative analysis based on interviews with the mayors of the communities being studied. Four assumptions were verified in the aforementioned way: (1) the MRCs in villages in the immediate vicinity of developed tourist centres show a higher level of activity in relation to their own development; (2) Roma who are active in small-scale farming will also be more active in maintaining other traditional craft activities, typical for Roma communities in Slovakia, forming the basis for the development of their own PPT product; (3) the activity of NGO's focusing on the development of the local MRC's is not a guarantee for the development of PPT activities in the villages; and finally that (4) the high level of segregation of marginalised Roma communities is a major obstacle for the implementation of PPT. This paper concludes with a typology of municipalities in relation to the preconditions for the development of PPT, which can be considered as a contribution to the discussion on the possibilities of a differentiated approach to PPT development strategies at the level of municipalities with the numerous MRC's. [ABSTRACT FROM AUTHOR]

We examine the impact of the global economic activity, oil supply, oil-specific consumption demand, and oil inventory demand shocks on the expected aggregate skewness of the United States (US) economy, obtained based on a data-rich environment involving 211 macroeconomic and financial variables in the quarterly period of 1975:Q1 to 2022:Q2. We find that positive oil supply and global economic activity shocks increase the expected macroeconomic skewness in a statistically significant way, with the effects being relatively more pronounced in the lower regime of the aggregate skewness factor, i.e., when the US is witnessing downside risks. Interestingly, oil-specific consumption demand and oil inventory demand shocks contain no predictive ability for the overall expected skewness. With skewness being a metric for policymakers to communicate their beliefs about the path of future risks, our results have important implications for policy decisions. [ABSTRACT FROM AUTHOR]

This paper presents the findings of a study on the impact of the transformation of a road transport corridor on the form of a functio-spatial structure, as determined by the placement of significant economic activity sites within this corridor. The investigation of relations and interdependencies in the development of the road transport system and development structure transformation processes allowed for the identification of tendencies in the shaping of space, as well as for building models that reflect the transformation of the road corridor under study. The study focused on a fragment of the road transport corridor between Kraków and Bochnia (called the "Kraków East–Bochnia" corridor), as a distinctive case of contemporary transformations of the functio-spatial structure that happen under the influence of the construction and opening of a section of highway A4. The study was based on original field work, a review of the literature and an analysis of applicable planning documents. GIS tools, cartographic resources and satellite images were also used. The transformation of the area under investigation and the increase in its accessibility due to the presence of the highway pointed to the area's high attractiveness in terms of real estate development—especially at nodal sites along the linkages that connected the highway with other elements of the road corridor. The relationships between the completed highway section and the previous road layout are crucial to the emergence of economic activity sites and areas, and thus lead to a transformation of developed space following a new spatial model. [ABSTRACT FROM AUTHOR]

This paper addresses the extensive structural changes of the Rhenish coal-mining area in Germany. Coal mining was and still is a relevant economic activity throughout Europe and is the focus of many political and societal debates, as well as research activities in the Rhenish coal-mining area. The project DAZWISCHEN followed the concept of evidence-based planning and therefore identified, by means of a GIS-based analysis, the structural changes within the Rhenish coal-mining area for the conflicting thematic clusters for settlement development and open space. Moreover, we investigated the complex multi-level governance that the region is characterized by. The results suggest an increased pressure on blue and green infrastructure by new urban development, especially in the northern part of the Rhenish coal-mining area. On the other hand, the southern part of the Rhenish coal-mining area will be more likely to undergo a process towards an increase in green infrastructure. Thus, the future development of the whole area is segregated in two different development trends in the north and south parts. The complex governance structure in the Rhenish coal-mining area requires an in-depth view of the ongoing working processes in the development of ideas and visions for regional mission statements of different planning areas, levels, and network partners in a real-life laboratory. [ABSTRACT FROM AUTHOR]

This paper investigates hydro-meteorological hazards faced by Sri Lanka, a lower-middle-income island country in Asia. It provides a case study of a major hydro-meteorological disaster incident that resulted in one of the largest landslides in the history of the country, the Post-Disaster Needs Assessment (PDNA) process, and the national disaster response. Rainfall and flood inundation data are provided for the whole country. The fact that data are held by several government agencies (namely Department of Meteorology, Department of Irrigation, and NBRO), somewhat coordinated by the Disaster Management Center (DMC) is shown. The need for more streamlined coordination of hydro-met data with online access of data for researchers is emphasized. The flood disaster situation and disaster declaration of the Western Province (which contributes nearly 40% of the GDP) is looked at, and evidence is presented to recommend a smaller governance unit for future disaster declarations, in order to bring aid to the places where it is needed and leaving other areas of the province to carry on with the normal economic activity. An example of the use of climate change scenarios in rainfall prediction is provided from a developed island nation (New Zealand). The need for Sri Lanka to increase its spending for hydro-met services (both infrastructure and skills) is highlighted (the global norm being 0.02 of GDP), as the return on such investment is tenfold. [ABSTRACT FROM AUTHOR]

Relatedness is a key concept in economic complexity, since the assessment of the similarity between industrial sectors enables policymakers to design optimal development strategies. However, among the different ways to quantify relatedness, a measure that takes explicitly into account the time correlation structure of exports is still lacking. In this paper, we introduce an asymmetric definition of relatedness by using statistically significant partial correlations between the exports of economic sectors and we apply it to a recently introduced database that integrates the export of physical goods with the export of services. Our asymmetric relatedness is obtained by generalising a recently introduced correlation-filtering algorithm, the partial correlation planar graph, in order to allow its application on multi-sample and multi-variate datasets, and in particular, bipartite temporal networks. The result is a network of economic activities whose links represent the respective influence in terms of temporal correlations; we also compute the statistical confidence of the edges in the network via an adapted bootstrapping procedure. We find that the underlying influence structure of the system leads to the formation of intuitively-related clusters of economic sectors in the network, and to a relatively strong assortative mixing of sectors according to their complexity. Moreover, hub nodes tend to form more robust connections than those in the periphery. [ABSTRACT FROM AUTHOR]

(1) Background: Cross-border venture capital (VC) investments play an important role in the scaling up of high-growth companies. However, policymakers worry that foreign VC investments transfer the majority of economic activity to the investor country. On the one hand, start-ups welcome the foreign capital, expertise, and networks that accompany cross-border investments. On the other hand, policymakers are concerned that cross-border investments predominantly benefit foreign economies and fail to develop the local entrepreneurial ecosystem. This paper describes a framework for how policymakers can develop a set of policies toward cross-border VC investments. (2) Methods: The paper examines available data and trends about the role of cross-border investing, focusing on Europe, Israel, and Canada. Then, the paper explains the underlying economic challenges and develops a policy framework. (3) Results: The analysis shows that in addition to policies that aim to attract foreign investors, there are also important policies for the development of the domestic VC market. The analysis encompasses policies that are both financial and non-financial in nature. (4) Conclusions: A core insight for policymakers is to retain a balance of initiatives, attracting foreign investors while simultaneously making sure to strengthen the country's domestic VC industry and innovation ecosystem. The mix of policies will adjust as the domestic ecosystem matures. [ABSTRACT FROM AUTHOR]

To improve the controllability of the electric power output and the economic performance of a large-scale wind farm, an auxiliary energy storage system is required. This paper deals with the rule of planning reasonable energy storage power and capacity based on the historical annual mean wind speed data, the probability density of the pulsating wind power output, and the warranted firm power provided by the wind farm. Specifically, the evaluation index of the fluctuation degree of the firm power is defined in order to optimize the planned energy storage capacity. After that, the firm power escalation affected by the energy storage power and the conversion rate of the storage device are quantitatively evaluated. All of these analyses contribute in a significant way towards determining the acceptable energy conversion rate with the condition of limited energy storage space of a wind-storage hybrid power system. The proposed evaluation method of the firm power escalation is verified by MatLab simulation results. [ABSTRACT FROM AUTHOR]

The present article analyzes the technological advancement and innovations related to drilling operations. It covers the review of currently proven and emerging technologies that could mitigate the drilling operational deficiencies and instabilities that could hinder operational performance activities and the economic part of drilling development with great effort to minimize their environmental footprint. Drilling system design and operations are among the major aspects and cost-effective endeavors of the oil and gas industries, which are therefore technology dependent. They are also considered to be among the most expensive operations in the world, as they require huge expenses daily. Drilling success, depending on prevalent conditions, is a function of several general factors. These include the selection of the best technologies and tools, procedural optimization, concrete problem-solving, accurate prediction, and rapid decision-making. Consequently, any sorts of tools or advanced technologies that can improve the time-efficient operational and economic performance of drilling activities are essential and demanded. The paper provides a review of available technologies and developmental innovations based on both company-based and academic research-enabled drilling solutions over the past 5 years in the field of drilling systems and technological design. The paper further highlighted potential technologies that could be tapped in from other industries and could possibly be adopted by pushing the conventional boundaries of drilling operations. [ABSTRACT FROM AUTHOR]

Rivers are among the main sources of marine litter, especially for semi-isolated sea areas with high populations and intense economic activity. The semi-isolated Black Sea located in the Eastern Europe is an example of such an area, whose watershed basin is under high anthropogenic pressure. In this study, we report the results of the first long-term monitoring program of floating litter at several rivers inflowing to the northeastern part of the Black Sea. We describe the main characteristics of registered marine litter, including the distribution of its type and size. Based on the obtained results, we reveal the relation between river discharge rate and the litter flux for the considered rivers. Using this relation extended to all rivers of the study area, we assess the total annual flux of riverine litter to the northeastern part of the Black Sea. [ABSTRACT FROM AUTHOR]

Multi-objective optimization problems (MOPs) constitute a vital component in the field of mathematical optimization and operations research. The multi-objective evolutionary algorithm based on decomposition (MOEA/D) decomposes a MOP into a set of single-objective subproblems and approximates the true Pareto front (PF) by optimizing these subproblems in a collaborative manner. However, most existing MOEA/Ds maintain population diversity by limiting the replacement region or scale, which come at the cost of decreasing convergence. To better balance convergence and diversity, we introduce auction theory into algorithm design and propose an auction-based matching (ABM) mechanism to coordinate the replacement procedure in MOEA/D. In the ABM mechanism, each subproblem can be associated with its preferred individual in a competitive manner by simulating the auction process in economic activities. The integration of ABM into MOEA/D forms the proposed MOEA/D-ABM. Furthermore, to make the appropriate distribution of weight vectors, a modified adjustment strategy is utilized to adaptively adjust the weight vectors during the evolution process, where the trigger timing is determined by the convergence activity of the population. Finally, MOEA/D-ABM is compared with six state-of-the-art multi-objective evolutionary algorithms (MOEAs) on some benchmark problems with two to ten objectives. The experimental results show the competitiveness of MOEA/D-ABM in the performance of diversity and convergence. They also demonstrate that the use of the ABM mechanism can greatly improve the convergence rate of the algorithm. [ABSTRACT FROM AUTHOR]

The northeastern Red Sea (Saudi Arabia) is currently being transformed to become a global hub of economic activity and tourism. This transformation requires the development of pristine coastal areas into populated and dynamic settlements. At the same time, the northern Red Sea is considered a climate refuge for corals in changing climate conditions, and efforts to preserve and protect marine biodiversity are being proposed. Accordingly, foraminifers are an efficient tool to assess and monitor their associated coral reefs' health. This study reports a modern-day health assessment of the corals of Shushah Island (Saudi Arabia) in the northeastern Red Sea as a reference for future monitoring as inferred by applying the FoRAM Index method. In general, our results revealed healthy conditions conducive to coral growth, yet some precautions and regular assessments are recommended. [ABSTRACT FROM AUTHOR]

To satisfy human needs and desires, it is necessary to produce goods and services that require the use of some production factors, such as labor, capital, and energy, among others. Nowadays, energy is a key production factor for economic activity in all countries. The main objective of this paper is to analyze the relationship between energy, economic growth, urbanization, and financial development in the country-members of the North American Free Trade Agreement (NAFTA) during the period of 1971–2015. Panel data Econometric methods are applied in this research, namely cross-section dependence (Pesaran test), unit root (Cross-sectional Augmented Dickey Fuller and Cross-sectional Im, Pesaran, and Shin tests), cointegration (Kao and Fisher–Johansen tests), and heterogeneous causality (Hurlin and Dumitrescu test). The results achieved in this research demonstrate that the variables of this model are characterized by a cross-section dependence, and they are integrated in order one. An equilibrium or long-term relationship between them exists. By means of the Fully Modified OLS and Dynamic OLS estimators it this demonstrated that there is a positive relationship between GDP and EC, while there is a negative relationship between FD, CPI, URB, and TO and EC. The economic policy recommendations drawn from this investigation are that financial development promotion, urbanization, and trade openness may contribute to reducing energy consumption in these countries. [ABSTRACT FROM AUTHOR]

China is a fascinating country in Asia, the second-largest economy in the world, with incredible economic growth and development in the last two decades. In addition, China has dramatically enjoyed a disciplined and successful financial integration with the region and the world in the same period. As such, it is interesting to examine a potential link between economic growth and financial integration in this most populous country. This paper was conducted to identify whether financial integration fosters Chinese economic growth. The Auto-Regressive Distributed Lags (ARDL) model is selected, utilizing the most updated data on a globalization (or integration) index. Two distinct aspects of financial integration, the de facto (proxied for economic activities) and the de jure (proxied for the Government policies leading to integration), are considered in this paper. We apply an econometric technique, using yearly aggregated data, to examine a long-term co-integration and a causal relationship between financial integration and economic growth in China. Findings from this paper indicate a long-term co-integration between financial integration de facto and economic growth in China. The bidirectional causality between financial integration and economic growth in China is also confirmed using the Granger causality test. [ABSTRACT FROM AUTHOR]

This study proposes a method for classifying economic activity descriptors to match Nomenclature of Economic Activities (NACE) codes, employing a blend of machine learning techniques and expert evaluation. By leveraging natural language processing (NLP) methods to vectorize activity descriptors and utilizing genetic algorithm (GA) optimization to fine-tune hyperparameters in multi-class classifiers like Naive Bayes, Decision Trees, Random Forests, and Multilayer Perceptrons, our aim is to boost the accuracy and reliability of an economic classification system. This system faces challenges due to the absence of precise target labels in the dataset. Hence, it is essential to initially check the accuracy of utilized methods based on expert evaluations using a small dataset before generalizing to a larger one. [ABSTRACT FROM AUTHOR]

The importance of assessing and estimating the impact of the COVID-19 pandemic on financial markets and economic activity has attracted the interest of researchers and practitioners in recent years. The proposed study aims to explore the pandemic's impact on the economic activity of six Euro area economies. A class of dynamic panel data models and their corresponding Seemingly Unrelated Regression (SUR) models are developed and applied to model the economic activity of six Eurozone countries. This class of models allows for common and country-specific covariates to affect the real growth, as well as for cross-sectional dependence in the error processes. Estimation and inference for this class of panel models are based on both Bayesian and classical techniques. Our findings reveal that significant heterogeneity exists among the different economies with respect to the explanatory/predictive factors. The impact of the COVID-19 pandemic varied across the Euro area economies under study. Nonetheless, the outbreak of the COVID-19 pandemic profoundly affected real economic activity across all regions and countries. As an exogenous shock of such magnitude, it caused a sharp increase in overall uncertainty that spread quickly across all sectors of the global economy. [ABSTRACT FROM AUTHOR]

Based on Thermodynamics and its well-established First and Second Laws, this work presents and explores their economics counterparts, introducing new concepts, variables, and equations. This includes, among others, the economic counterparts of temperature, reversibility and irreversibility, and entropy and entropy generation resulting from economic irreversibility. The meaning of the new concepts, variables, equations, and their messages are introduced and discussed considering simple yet relevant economic processes. The economic counterparts of the First and Second Law balance equations are set in addition to the base concepts and Laws. These are effective and valuable tools for the analysis of economic processes. Observations from selected economic activities are analyzed using the new concepts, variables, and equations. [ABSTRACT FROM AUTHOR]

With the increase in the world population and economic activity, the production of sewage sludge has grown, and its management has become an environmental problem. The most traditional method of managing sewage sludge is to dispose of it in landfills and on farmland. One way to valorize sewage sludge is to use thermochemical conversion processes to produce added-value products such as biochar, biofuels, and renewable gases. However, due to the high moisture content, thermochemical conversion using processes such as pyrolysis and traditional gasification involves multiple pre-treatment processes such as material drying. Hydrothermal thermochemical processes usually require high pressures, which pose many challenges to their application on a large scale. In this work, the advantages and disadvantages of the different existing thermochemical processes for the recovery of sewage sludge were analyzed, as well as the resulting industrial and environmental challenges. A SWOT analysis was carried out to assess the different thermochemical processes in terms of technical feasibility, economic viability, and broader market considerations. [ABSTRACT FROM AUTHOR]

China's High-tech Industrial Development Zones (HTZ) are industrial agglomeration areas established by the local government to foster economic innovation. As springboards for cities to implement innovation-driven development strategies, HTZs have significant spillover and driving effects on urban ecological innovation. Based on panel data taken from 215 cities between 2003 and 2016, this paper empirically analyzes the impact of HTZ construction and its mechanisms as they pertain to urban ecological innovation. This analysis is framed by the double difference model and the intermediary effect model. It found that HTZ construction can effectively enhance urban ecological innovation, and formidably promote ecological innovation in central and eastern cities, as well as cities with superior scientific and educational resources. The intermediary mechanism analysis revealed that HTZs result in a policy depression effect, which may promote the agglomeration of urban innovation factors (including high-quality talents and investment), thereby bolstering urban ecological innovation. Moreover, HTZs' investment agglomeration effect is primarily responsible for driving urban ecological innovation. Indeed, the HTZ construction may not only promote the local ecological innovation, but also have a significant spillover effect on the ecological innovation activities of other cities in the province. [ABSTRACT FROM AUTHOR]

The role of agricultural transport costs in core-periphery structures has habitually been ignored in New Economic Geography (NEG) models. This is due to the convention of treating the agricultural good as the numéraire, thus implying that agricultural transportation costs are assumed to be zero in these models. For more than three decades, this has been the standard setting in spatial equilibrium analysis. This paper examines the effects of agricultural transport costs on the spatial organisation of regional structures in Peru. In doing so, Krugman's formulation of iceberg transport costs is modified to introduce agricultural transport costs into the dynamic of the NEG models. We use exploratory spatial flow data analysis methods and non-spatial and spatial origin-destination flow models to explore how the regional spatial structure changes when real transportation data for agricultural goods are included into the iceberg transport costs formulation. We show that agricultural transport costs generate flows that are systematically associated with flows to or from nearby regions generating thus the emergence of spatial spillovers across Peruvian regions. The results of the paper support the contention that NEG models have overshadowed the role of agricultural transport costs in determining the spatial configuration of economic activities. [ABSTRACT FROM AUTHOR]

Understanding land use functions (LUFs) value is critical for implementing sustainable land resources management and optimizing territorial space in China. However, existing research insufficiently portrays the contributions of land use to economic activity and people's well-being. To address this crucial absence, this paper attempts to clarify the connotation of LUFs' value and the logic of LUFs' optimization under the national territorial space planning system by applying the "demand–function–value" integrated framework. Based on this framework and taking Zhangjiakou City as a case study, we classified LUFs into economic, social, and ecological functions. Then, we assessed the monetary value of LUFs at the grid level using spatialization and environmental economics methods. Besides, we analyzed the evolutionary characteristics of LUFs and their diversity and dominance. The results showed that the total value of economic, social, and ecological LUFs increased continuously between 1990 and 2015. Spatially, the ecological function showed an opposite pattern to that of social and economic functions. Additionally, the dominant role shifted from ecological function to social function, and the dominant functional combination changed from ELP-ENS-ST to SP-ENS-ELT over this period. Lastly, this paper proposes that policymakers identify and optimize ecological–production–living space through LUFs' value assessment and coordination. The results provide a new methodological insight into the assessment and coordination of LUFs and adaptive land use management. [ABSTRACT FROM AUTHOR]