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Emission permitting (EP) has been widely implemented to regulate point-source wastewater emissions. However, the ways in which local industries respond to an EP intervention and to what extent an EP policy could reduce emissions is subject to great uncertainty and should be investigated. This study develops an agent-based model to examine each individual firm's changing behaviours and the aggregated environmental and economic performance of the local economy. The Baoding Municipality, located upstream of the Baiyangdian Wetland, a core conservation area in the Xiong' An New District, was investigated as a case study. The simulation results showed that the regional industrial economy first fell and then rose. The chemical oxygen demand (COD) emissions of the municipal industrial total showed a downward trend from 2015 to 2025, with an average annual reduction of 1.2% under the current EP policy. The textile and papermaking industries had comparatively large potential for emission reduction, accounting for 43.7% and 22.7% of the total industrial emissions, respectively. The simulation results also showed that over 61.9% of firms changed their approach from take-no-action to proactive pollution control up to 2025. Further, the results verify that total emissions would be expected to decrease significantly with tightening permit limits, while the marginal effects of EP regulation would be expected to decline gradually. As a quantification of EP's effects on both environmental and economic aspects, this study provides valuable insights for the advancement of EP policies through national reform. [ABSTRACT FROM AUTHOR]

This paper aims to analyze the individual's socioeconomic and demographic determinants of financial inclusion and its barriers among for South Asian countries in the lens of existing financial inclusion policy, using World Bank Global Findex database for the period 2011, 2014, 2017, and 2021. We use the Probit regression model to explore the main objective of this study. In addition, we also analyze the trend, pattern, and barriers of financial inclusion for the period 2011- 2021 to identify differences among south Asian countries. Our results reveal that Sri Lanka is the best performer in the inclusivity of financial products as well as removing barriers to financial inclusion in all four periods. While Pakistan and Afghanistan are the least financially included countries, also they failed to remove barriers to financial inclusion. Moreover, our empirical results suggest that individuals who are male, older, wealthier, and more educated are more likely to access financial services, with income and education exerting a higher influence. Further, age shows a non-linear (inverted U-shaped) relationship with financial inclusion indicators. Additionally, we found that individuals having a formal account are the most important indicators of financial inclusion. And the reasons for financial exclusion (i.e., not having an account) are mainly voluntary among South Asian individuals. In fact, it is found that policies like Pradhan Mantri Jan Dhan Yojana for India and National Financial Inclusion Strategy across all South Asian countries play a significant role in accelerating financial inclusion and helping in removing its barriers with different magnitudes. Therefore, our finding stresses the importance of heterogeneous integrated policy measures for the targeted groups of the population, particularly the most vulnerable group among South Asian countries. [ABSTRACT FROM AUTHOR]

In continuation of the previous part, this paper comprehensively focuses on energy, exergy, exergo-economic, and environmental (4E) analyses of two prioritized clean hydrogen (H 2) supply chains pathways. The first scenario relies on domestic demand , involves blue H 2 production and storage using steam methane reforming coupled with carbon capture and storage through H 2 conversion to hydrogen carriers in liquid form (ammonia and methanol) aligned with the existing infrastructure. The second scenario involves green H 2 production from photovoltaic panels as the power source follows by storing H 2 in liquid form which is more suitable to export. The findings indicate that the blue H 2 system outperforms the green H 2 system in terms of energy and exergy, boasting 41.38% and 22.15% compared to 12.16% and 12.75%, respectively. However, when examining economic parameters, the blue H 2 system shows a total cost rate of 1976 US$/h, a net profit of $747.2 million (mn) at the end of its lifetime, and a payback period of approximately nine years. Conversely, the green H 2 system demonstrates economic indicators of a 125.2 $/h as a total cost rate, $1.26 billion (bn) net profit, and an 8.17 year payback period. Moreover, the production cost rates for blue and green H 2 are 1.32 $/kg and 2.55 $/kg, respectively; while the CO 2 emissions rate in the blue H 2 system is 10.71 kg/s. The green H 2 system prevents 19.84 kg/s of CO 2 emissions resulted a significant environmental cost reduction of 2.28 $/kg H 2. This analysis facilitates a thorough comparison of these two clean H 2 production and storage systems, offering insights for policymakers across performance, economic, and environmental dimensions. • A comprehensive 4E analysis was applied for the selected H 2 value chain scenarios. • Blue H 2 scenario is superior economically while environmentally the green one takes precedence. • Carbon credit makes the green H 2 scenario emerges frontrunner utilizing PV solar technology. • Methanol was recognized as the most cost-effective H 2 carrier for storage in Iran. [ABSTRACT FROM AUTHOR]

Considering the different dynamics of the COVID-triggered real shocks and macroeconomic measures during the first two waves of the pandemic, using official quarterly data for 2020 the paper studies how economic support measures have impacted the economic performance of sectors in EU countries. The paper shows that: (1) for all analysed sectoral groups, the economic support measures effects were much smaller than the corresponding non-pharmaceutical interventions impacts; (2) sectoral groups did not receive economic support in proportion to the corresponding nonpharmaceutical interventions; (3) sectoral groups with greater non-pharmaceutical interventions did not receive even systematically bigger effects of the economic support measures; and (4) the net overall effects of the COVID-triggered measures on sectoral value added vary considerably between sectors. By evaluating the potential opportunity costs of the 'flat' economic support activity, the study's results also help to identify measures that could eventually be implemented once the pandemic has ended to mitigate the potential opportunity costs of the sector non-specific implementation of economic support measures, which will become apparent in the recovery period following the pandemic. [ABSTRACT FROM AUTHOR]

• The paper documents developments in Indian economic performance and the role of structural change in this performance. • Manufacturing is dominated by informal labor, which has a deleterious effect on overall manufacturing performance. • Productivity growth is driven by within sector growth, with positive contributions of formal and informal activities to this. • Labor reallocation to the informal segment of the manufacturing sector is growth reducing in the Indian manufacturing sector. • A shift to more productive informal activities across sub-sectors exists, but this doesn't offset the negative within effect. This paper examines the role of structural change in India's performance, and in particular the role of the informal segment in the stagnant growth of the Indian manufacturing sector. Using counterfactual analysis – including a modified shift-share approach – the paper considers to what extent the informal sector can help explain the poor performance of Indian manufacturing over the period 1980-2011. The results suggest that the informal segment of manufacturing has been a drag on overall manufacturing productivity growth, with the informal manufacturing segment unable to provide a productivity bonus when absorbing workers from the agricultural sector. Results from the shift-share analysis indicate that labor reallocation to the informal segment of the manufacturing sector is growth-reducing, with structural change being the main source of this reduction, an effect which in turn is driven by movements of employment within manufacturing sub-sectors. [ABSTRACT FROM AUTHOR]

Over the last two decades global economy and financial markets have seen many crises with an increasing frequency. Many of them were either unexpected or their effects were unpredictable. Therefore, a lot of conventional and popular investment opportunities have shortened or became less attractive for either private or institutional investors leaving a room for new instruments and products to gain popularity. Unlike new volatile and uncertain markets like cryptocurrency, there are potentially more stable processes such as M&A activity, which can be predicted to earn abnormal returns. In this paper, we study various financial and non-financial indicators of acquired and non-acquired companies to provide a set of variables that can describe a company from different perspectives. Next, M&A prediction model is designed. Then, techniques are discovered to increase its explanatory and predictive power, and flexibility making it applicable for different economic environments without being harder to implement it by a potential user. In the end, its efficiency is measured on a real data to compare it with a result of methods found in earlier papers. [ABSTRACT FROM AUTHOR]

• ADA learns preferences from market data and predicts price of newly generated building design. • Integrate ADA with 3D building simulation to study price gain and value at risk. • Changes to Visual Capital identify the exposure and financial sensitivity to land-use change. • Blueprint for integrating economic evaluation within site-selection, design optimization. Uncertainty of spillover effects – including property devaluation - from proposed land-use change elicits opposition to local development. This hinders cities' ability to implement land-use policy aimed at housing affordability and environmental sustainability. The uncertainty arises from the limitation of current methods to quantify both the physical exposure and financial sensitivity to changes in urban environmental characteristics and amenities. Hence, this paper introduces an integrated approach to quantify the direct and indirect effects of a proposed urban development, using parametric modeling, building performance simulation and automated design appraisal (ADA). ADA, a novel aspect of this study, predicts the market price of a generated building design concept within a local urban context. To demonstrate its practical utility, this paper examines property value at risk due to nearby development associated with changes to visual landscape quality. The results shed light on the importance and spatial variability of the price-amenity gradient, identifying properties that are financially at risk to the visual impacts of local development. Beyond building-specific risk modeling for the development planning stage, this work serves as a blueprint for architectural design optimization procedures, in which economic performance is evaluated based on learned preferences derived from financial market data. [ABSTRACT FROM AUTHOR]

For policymakers who intend to make decisions on the policy to stimulate economic growth and enhance job opportunities, business demography statistics serve as important data sources for promoting entrepreneurship, which is a key for the policy. Business demography, which usually consists of annual demographic information such as the number of births, deaths, and survivals of businesses, can be produced from a business register in many countries. In Japan, however, it is difficult to produce business demography directly from the Japanese business resister called Establishment Frame Database because the major data source for the database is the Economic Census, conducted twice every five years. Alternatively, business demography can be estimated using the data of the Economic Census. However, it has been pointed out that short-lived births of businesses are hardly grasped by the estimation using the data of statistical surveys such as the Economic Census at intervals of more than one year. This paper introduces a stochastic model to cope with the above issue and proposes a calculation formula to estimate the number of short-lived births of businesses as well as other demographic indicators of business demography. Then the paper is followed by a numerical example, which proves to overcome the shortcomings of previous methodologies. [ABSTRACT FROM AUTHOR]

Statistical modeling and forecasting are very important for decision-making in any field of life. This paper has two major objectives, namely, statistical modeling and forecasting of real phenomena. For covering the first aim (i.e., statistical modeling), we introduce a new probabilistic model. The new model is introduced by mixing the Dagum distribution with the weighted T X family approach. The proposed model is called the weighted T X Dagum distribution and possesses heavy-tailed characteristics. The new model is illustrated by analyzing real-life data related to Bitcoin prices. To cover the second aim (i.e., forecasting), we take into account six macroeconomic and financial indicators to investigate their impact on Bitcoin prices such as the Adaptive least absolute shrinkage and selection operator (Alasso), elastic net, and minimax concave penalty. After analyzing the data, it is found that Alasso and MCP have retained all the included predictors, except import, while Enet holds all the predictors. The root means square error and mean absolute error associated with MCP are lower than Alasso and Enet, which reveals that MCP fits the data very well as compared to rival methods. [ABSTRACT FROM AUTHOR]

In this "Data, Tools and Replication" paper we adapt the complexity algorithm by Hidalgo and Hausmann (2009) to the financial sector and compute a measure of financial development that is intrinsically linked to its diversity dimension. We then test the impact of financial development on financial stability, economic resilience and growth, focusing on Italy. By employing an index that levers on the diversity dimension of financial development, our findings reveal that higher degrees of financial development translate into a lower financial fragility and a more resilient real economy. Indeed, territories denoted by more diverse and developed financial systems show an increased firm natality rate, a reduced firm mortality rate, and a lower probability of experiencing employment and GDP drops. Finally, higher financial development also spurs economic growth. Results are confirmed at micro-level, and higher levels of financial development and diversity decrease the probability of firms' exit from the market and enhance their investment activity. Our findings unveil the importance of considering the diversity dimension of financial development when investigating its role on economic performance. • Drawing from network theory we calculate a measure of development of financial systems that levers on its diversity dimension. • Using Italian data we investigate whether financial development and diversity improve financial stability, the resilience of the real economy, and economic growth. • We find that more developed and diverse financial systems are more stable. • Benefits extend to the real economy, that shows greater resilience and growth. • Results emerge both in a micro and more aggregated setting. [ABSTRACT FROM AUTHOR]

Understanding the relationship between energy price dynamics and competitiveness is key to the debate on the transition to environmental and economic sustainability. That is particularly the case in emerging economies, where sectors and firms are less mature and more fragile to external shocks. Using a panel of firms in 12 sectors and 11 high and middle-income countries over the years 2002–2013, this paper provides evidence that growing energy prices do not harm and in some cases can even strengthen economic performance. The results suggest that the size and direction of the impact of growing energy prices depends on firms' energy intensity, among other characteristics. This should be taken into account in empirical studies focusing solely on average effects. • A widespread view is that growing energy prices determine a reduction of profits and competitiveness of firms. • This study analyzes the impact of energy prices on performance indicators of firms in developing and emerging countries. • We find that rise in energy prices can trigger innovation, which may compensate the static losses of rising input costs. • The negative impact of energy price changes on performance is stronger for firms with a higher level of energy intensity. [ABSTRACT FROM AUTHOR]

Economic inequality, in terms of income or wealth, is one of the most complex and perplexing challenges of our current capitalist economic system. While the dynamic relationship between income inequality and economic growth has been extensively investigated (since the beginning of the last century), the dynamic link between wealth inequality (or wealth concentration) and economic growth has been largely ignored in the literature, taking more attention in recent years. This paper asserts that the accumulation of non-productive assets/luxury goods is an important determinant of wealth inequality, as well as a determinant of the relationship between wealth inequality and economic growth. In this paper our aim is to show that an increase in wealth inequality is associated with a slowdown in economic growth. In particular, the paper shows that there is a negative relationship between wealth inequality and economic growth in France because poor households own a relatively large fraction of non-productive luxury goods. Nevertheless, this is not the case in the US, which is what explains that such negative relationship is not observed there. We conclude that a redistribution of wealth (from the rich to the poor) is important for attaining a sustained economic growth performance. • This paper contributes to the analysis of economic growth and wealth inequality in France and the United States. • We propose a macroeconomic model that includes both productive and non-productive assets. • Economic growth slows as the aggregate stock of non-productive assets increases as wealth inequality increases. • Redistribution will enrich the poorest households and therefore decrease their propensity to own unproductive assets. • Wealth inequality and economic growth may have a non-linear relationship. [ABSTRACT FROM AUTHOR]

The medium- and long-term operation strategy of the hybrid power system needs to adapt to the continuous changes in the market. This paper presented a medium-term (monthly) operational simulation model and nested it into a long-term (yearly) optimization model. It was solved by the genetic algorithm (GA) to maximize yearly revenue. The planned delivered-electricity to power process constraints were present to improve the optimization efficiency. Using penalty price factor (α) and threshold of exempted punishment for the supply shortage δ to characterize the punishment for supply shortage risk. This framework was applied for a new hybrid power system so-called LCHES-WP (large-scale cascade hydropower energy storage system, wind power, PV power). It can participate in the electricity trading market with a bundled output pattern. The real cascade hydropower stations in Qinghai Province, China, are selected as the case study. In the baseline scenario, the current time of use (TOU) electricity price and punishment level (α = 0.05, δ = 5%) were considered. It reveals that (1) the revenue (baseline scenario, 6.15351 billion CNY) in the bundled output pattern is higher by 45.6% than in the separate output pattern. (2) the economic and technical indicators are sensitive to α , but not to δ. α increases make the punishment stricter, supply shortage risk was significantly reduced due to the probability of the shortage event, the maximum monthly supply shortage ratio and punishment electricity are reduced by up to 22.5 percentage points, 26.7 percentage points, and 1880.1 GWh, respectively. The yearly revenue is reduced by up to 4.7%. the reason is the yearly curtailment is increased and the penalty amount does not change dramatically with the changes in punishment. (3) The α = 0.6 and α = 1.8 can be regarded as demarcation point and upper boundary point for the case of hybrid power system, respectively. It is proposed that when planning a capacity scheme, stakeholders should consider that the demarcation point is higher than the current α. In general, this paper provides a reference for the medium- and long-term operation optimization of the LCHES-WP hybrid power system in the future. • Electricity settlement rule in medium and long term electricity trading is considered. • The monthly operational simulation model was nested in the yearly optimization model. • Bundled output pattern can rise by 45.6% of revenue than the separate output pattern. • The supply shortage risk is significantly reduced by increasing the punishment level. • The penalty amount does not change obviously with the changes in the punishment level. [ABSTRACT FROM AUTHOR]

To fully extract the potential of offshore wind power, the wind farms are built further from mainland and the capacity is growing larger. Low Frequency AC (LFAC) transmission System is a promising solution to the integration of large offshore wind farms in long distance. This paper conducts a comparative economic analysis of LFAC. Compared to 50 Hz High Voltage AC (HVAC) transmission, LFAC can reduce charging current in AC cables to enhance the transmission ability in long distance. Compared to High Voltage DC (HVDC) transmission, LFAC eliminates the large expense of offshore converter station. In addition, the topologies of AC/AC converter in LFAC also influences the economic performance significantly. By designing typical AC/AC converters based on modular multilevel technique in a unified way, this paper performs a full-scale economic comparison in different voltage level, active power and reactive power cases. Furthermore, the economic comparison based on capital cost of HVAC, HVDC and LFAC is comprehensively studied considering different transmission capacity and the AC/AC converter topologies. The economic range of HVAC, LFAC and HVDC application is obtained, and results show that LFAC is suitable for medium distance circumstances (around 80–200 km). The economic range of LFAC expands when power rating increases. • Economic range of HVAC, HVDC and LFAC is analyzed according to their capital cost. • Converter topologies and transmission capacity is considered in the cost of LFAC. • Comprehensive comparison of four AC/AC converter topologies for LFAC is conducted. • A unified method is introduced to design four AC/AC converter topologies. [ABSTRACT FROM AUTHOR]

Systems involving more than one energy source, namely hybrid systems, can be arranged in different configurations and layouts depending on the available or used energy source, application and scale of the system. Despite an increasing awareness and penetration of renewable energy sources at different scales in many countries over the world, the adoption of hybrid and novel renewable systems is relatively scarce, especially at a small scale. This scenario is also presented from the point of view of the research of such systems. Therefore, the scope of the paper is to improve the knowledge regarding small-scale hybrid renewable energy systems performance and operation by investigating a novel trigeneration system based on a biomass fired steam cycle, wind turbine, photovoltaic panels and adsorption chiller. In the proposed system, the thermal energy recovered by the steam cycle is used to match the user thermal demand by means of a storage tank supplying directly heat to the user during winter, and driving the adsorption unit during summer. The electrical energy produced by the steam turbine, photovoltaic field and wind turbine is managed by a control system that integrates a bidirectional connection with the electric grid. The grid allows one to virtually store the electrical energy produced in excess and to recover it in part when needed by the user. In order to assess the system performance, a farm and residential buildings are considered as case study. The proposed system is modelled and dynamically simulated by means of Transient System Simulation software. In the paper, the dynamic operation of the system and the energy and economic performance of the system is assessed. The operation of the system is presented in a daily and monthly basis, while the global performance parameters of the system are reported considering a one-year period. The primary energy saving of the system is above 70% when a reference system based on natural gas, electric chiller and grid is considered. For this scenario, the Simple Pay Back of about 10 years is achieved. The results of the analysis show that the system is feasible from the technical and energy point of view, whereas its economic profitability is significantly affected by its cost and the reference system that is adopted by the user. • Modeling and dynamic simulation was performed with TRNSYS software. • Energy and economic performance of the system was assessed. • Different reference systems are considered for heating. • Primary Energy Saving ratio was between 57.4 and 73.3%. • The minimum Simple Pay Back is about 10 years. [ABSTRACT FROM AUTHOR]

Distributed energy systems are becoming increasingly popular worldwide. The 100% renewable energy system can be an important energy supply alternative to reduce the carbon emissions and address energy shortage, especially for remote areas. However, the performance of 100% renewable energy system (RES) at community level needs further detailed analysis, which is affected by the climates, availability of renewable energy and local energy markets. This paper proposes a design optimization framework of 100% renewable energy systems for low-density communities and investigates the system performance. To investigate the integration and performance of 100% RES, thirty typical cities located in different regions of China were chosen considering different climates, geographical features, and renewable energy distributions. By taking the economic performance as the optimization objective, the optimal design for the 100% RES is obtained, and the energy and economic performance is analyzed. Results show that, under the current energy market conditions, the 100% RES is feasible for low-density communities in most regions of China. The payback periods of the systems in most cities are less than six years. When the cost of PV is reduced by half considering future technological developments, the payback period of a 100% RES can be reduced by 30%–60%. This paper would provide design suggestions and application recommendations in regard to promoting 100% RES in China. • Application of 100% renewable energy system at community level is studied. • 30 zones are selected considering climates, renewable energy sources and markets. • Solar energy and biomass can contribute to over 90% of the total energy supply. • Investment of 100% RES can be paid back in 6 years for most regions. • Payback periods can be reduced by 30%–60% when PV technology is further developed. [ABSTRACT FROM AUTHOR]

• Our paper highlights how and why state capitalism impacts energy democracy and renewable energy deployment. • The timing of the paper is critical because state capitalism is attracting more power and attention around the world. • We conclude that the values of state capitalism contradict with the necessary conditions of creating energy democracy. • We expect a deterioration or slowness in energy democracy diffusion and renewal energy deployment. The current paper highlights the interconnection between the state capitalist system and the concept of energy democracy. Both terms have attracted the attention of scholars because of significant economic, environmental, and political events. Our paper reviews the literature to show that state capitalism and energy democracy cannot exist together because the values of state capitalism contradict the necessary conditions to generate energy democracy. Moreover, globally, Western capitalist countries are failing in terms of their economies and political performance and yet, at the same time, economic performance is shifting toward state capitalism with less importance given to democratic actions. Therefore, we expect a deterioration or slowness in energy democracy diffusion and renewable energy deployment. For state capitalism to generate geographical representation, it needs to use regulations and spread renewable energy technology. [ABSTRACT FROM AUTHOR]

A long tradition in economic theory has seen the real exchange rate (RER) as a key determinant of trade performance. Several empirical studies, however, have found low estimates of macro trade elasticities and, as a result, questioned this argument. In this paper, we show that to understand and estimate the effect of RER on trade performance, it is crucial to explore the existence of heterogeneous responses of individual products to RER movements. Using trade data from Argentina, we employ the Mean Group method to estimate macro trade elasticities by individual products disaggregated at four digits of the SITC; rev.2. We find a wide range of heterogeneous responses of exports and imports to RER movements at the individual product level. We find that the estimated RER-elasticities in differentiated products and labor-intensive manufacturing goods are substantially larger than those of primary and homogeneous products. Based on the estimated elasticities at the product level, we obtain a "low" aggregate RER-elasticity of exports when we weigh them by the country's trade basket. We show that this result is a consequence of Argentina's economic structure, a country whose exports are heavily specialized in primary and homogeneous products. Our results are important because they help build a bridge between two conflicting views in the RER-economic development literature. Even in countries with "low" aggregate macro RER-elasticities, the real exchange rate may be an important variable for economic performance. An undervalued RER may facilitate economic growth by stimulating investment in activities producing more complex/differentiated goods in countries that specialize in the production of primary and homogeneous goods and, as a result, have "low" trade elasticities. This seems to be the case of several countries in Latin America, including Argentina. • We find a wide range of heterogeneous responses of exports and imports to RER movements at the individual product level. • The estimated RER-elasticities in differentiated products and labor-intensive manufacturing goods are substantially larger than those of primary and homogeneous products. • Based on the estimated elasticities at the product level, we obtain a "low" aggregate RER-elasticity of exports when we weigh them by the country's trade basket. • We show that this result is a consequence of Argentina's economic structure, a country whose exports are heavily specialized in primary and homogeneous products. • Our results are important because they help build a bridge between two conflicting views in the RER-economic development literature. Even in countries with "low" aggregate macro RER-elasticities, the real exchange rate may be an important variable for economic performance. [ABSTRACT FROM AUTHOR]

Traditional flat PV heat pumps has low irradiation density, large PV area, and the PV evaporators are always fixed, causing large area occupation and lots of irradiation missing, which limit the application and system efficiency. To solve the problems, a novel concentrated PV-air dual-source heat pump system (CPV-DSHP) was proposed in the previous paper, but the annual performance and economic comparison with flat PV-DSHP (FPV-DSHP) are still blank, which are extremely concerning to researchers. Besides, the paper also fills related content about the impact of irradiation composition on the system performance and economics, as well as the irradiation comparison on tracking CPV and fixed FPV surface. From the calculation of the validated model, it's found that the CPV-DSHP system could capture 6098 MJ and 2213 MJ more solar energy, and produce 282.21 kWh and 100.16 kWh more electricity in Garze and Hefei in a year. The annual concentration efficiency is 82.73 % in Garze where direct irradiation accounts for 68.89 %, which is only 73.15 % in Hefei with 39.84 %.The COP PVT is annually lifted by 0.40 in Garze. Although the two systems could both get payback in 5∼6 years, the CPV-DSHP only shows economic advantages in places with good direct irradiation conditions like Garze. • A novel concentrated PV-air dual-source heat pump system (CPV-DSHP) is presented. • The annual performance and economic comparison in different cities are supplemented. • The CPV-DSHP could produce 282.21 kWh more electricity in Garze in a year. • The annual concentration efficiency is 82.73 % in Garze with better direct irradiation. • Payback time is 5∼6 years but CPV-DSHP only shows economic advantage in Garze. [ABSTRACT FROM AUTHOR]

Forecasting international trade flows is crucial for understanding global economic activity and serving as critical economic indicators used by economists and policymakers with significant implications for respective countries' economic policies. However, this is a challenging task due to the complexity of the relationships between entities involved in international trade. While several approaches have been proposed, knowledge graph-based models have emerged as promising solutions for predicting international trade flows. In this paper, we introduce a synthetic triple-generation algorithm for enhancing downstream tasks in knowledge graph embeddings based on the graph complement. The algorithm identifies missing relationships between entities by exploiting the complement graph and generates high-quality synthetic triples that improve the accuracy of predictions. We validate the generated triples using several knowledge graphs embedding methods and computing metrics. To perform an initial result screening, an international trade scenario is explored, demonstrating the effectiveness of the proposed approach in enhancing the performance of knowledge graph-based models for predicting international trade flows. [ABSTRACT FROM AUTHOR]

In this paper, we look at the interaction of terrorism with immigrants' quality of life (measured by the foreign-born unemployment rate and globalization level) for OECD countries, and its impact on GDP per capita. We find strong evidence that GDP per capita is adversely affected by domestic terrorism. The magnitude of this effect is also substantial: at the sample mean, a one-standard-deviation increase in the number of domestic incidents is found to decrease GDP per capita between 5.7 % and 7.8 % of the sample average depending on the specification used. These results contrast with previous research which finds that transnational terrorism primarily affects these economic indicators. We find strong evidence that when we factor in the interaction of the foreign-born unemployment rate with either type of terrorism, an increase in the foreign-born unemployment rate decreases GDP per capita. On the policy front, we show that peace is valuable, and OECD countries will benefit by adopting policies to reduce the problem of terrorism. We also find that an increase in the foreign-born unemployment rate has a large negative impact on GDP per capita and policies that close the gap between foreign-born and native-born unemployment rates (for example, those aimed at reducing discrimination against immigrants) help the economy. [ABSTRACT FROM AUTHOR]

This paper examines the ordering of economic and financial prospects using a rescaled semivariance below the maximum (SVBMax). This indicator is consistent with stochastic dominance (SD) until order three, but is distinct from any expected utility framework, both in terms of construction and in terms of economic implications, despite an apparent formal similarity with the quadratic expected utility framework. SVBMax is able to deal with economic puzzles such as the restaurant puzzle or Rabin's paradox. SVBMax also provides a consistent alternative performance measure to popular measures such as the Sharpe ratio, the Omega ratio, or lower partial moments with exogenous thresholds. Compared to almost stochastic dominance, SVBMax is devoid of the drawbacks associated with the determination of violation areas. SVBMax can also replace the Aumann-Serrano and Foster-Hart riskiness indicators, which do not conform to third order SD. Further, SVBMax can provide a way of reaching an optimal diversification of stock portfolios. Besides, we also show that SVBMax is consistent with mean-variance-skewness preferences. [ABSTRACT FROM AUTHOR]

Policymakers imposed constraints on public life to contain the Covid-19 pandemic. At the same time, fiscal, monetary and macroprudential policies implemented a large range of expansionary measures to limit the economic consequences of the pandemic and stimulate recovery. In this paper, we assess the response of the equity market as a high-frequency indicator of economic activity to containment and stabilization policies for 29 European economies. We construct indicators of containment and stabilization policies and estimate a range of panel VAR models. The main results are threefold. First, we find that stock markets are highly responsive to containment and stabilization policies. We show that domestic fiscal policy, macroprudential policy as well as monetary policy support the recovery as reflected in the stock market. Second, expansionary fiscal policy conducted at the European level reduces rather raises stock prices. Third, we estimate the model over subsamples and show that the counter-intuitive stock market response to EU policies is driven by the responses in medium- and high-debt countries. These countries' stock markets are also particularly susceptible to monetary policy announcements. [ABSTRACT FROM AUTHOR]

Batch processes usually adopt a two-layer architecture control strategy to reduce the calculation cost while ensuring economic performance. The upper layer in the strategy obtains the nominal optimal reference trajectory by solving an economic optimization problem, while the lower MPC one possesses the task of tracking this trajectory as closely as possible. The disadvantage of this two-layer strategy lies in the lower layer resisting all the disturbance for satisfactory tracking results, regardless of the fact that part of the disturbance will be beneficial to economic performance. In order to realize the economic promotion in batch processes, a batch-to-batch optimization method is proposed in this paper. As an alternative to the traditional lower-layer tracking MPC, the proposed algorithm uses Gaussian process regression to establish a more accurate linear time-varying model and learns the information from the previous batches to obtain a more precise state estimation, thus continuously moving up economics by solving the economic optimization problem. Convergence of the proposed algorithm is proved and simulation is performed to verify the effectiveness of the proposed algorithm on economic performance improvement in comparison with the traditional tracking one. • An economic performance improvement strategy is proposed for batch processes. • Disturbances are utilized instead of being resisted to promote economy. • Gaussian process regression is utilized to compensate for model-plant mismatch. • Kalman filter is adopted to realize an accurate state prediction of the batches. [ABSTRACT FROM AUTHOR]

• Identification of important indicators for process safety. • A comparative study of process safety indicators in developing and developed countries. • Measuring the relative importance of the indicators using the Fuzzy Best Worst Method. Introduction: The importance of safety in high-risk industries such as oil and gas facilities has been reported previously. Process safety performance indicators can provide insight into improving the safety of process industries. This paper aims to rank the process safety indicators (metrics) by Fuzzy Best-Worst Method (FBWM) using the data gathered through a survey. Method: The study uses a structured approach considering the UK Health and Safety Executive (HSE), the Center for Chemical Process Safety (CCPS), and the IOGP (International Association of Oil and Gas Producers) recommendations and guidelines to generate an aggregate set of indicators. It calculates the level of importance of each indicator based on the opinions of experts from Iran and some Western countries. Results: The findings of the study demonstrate that some lagging indicators such as the number of times processes do not proceed as planned due to insufficient staff competence and the number of unexpected disruptions of the process due to failure in instrumentation and alarms are important in process industries in both Iran and Western countries. Western experts identified process safety incident severity rate as an important lagging indicator, whereas Iranian experts considered this as relatively unimportant. In addition, leading indicators such as sufficient process safety training and competency, the desired function of instrumentation and alarms, and proper management of fatigue risk play an important role in enhancing the safety performance of process industries. Experts in Iran viewed permit to work as an important leading indicator, while experts in the West focused on fatigue risk management. Practical Applications: The methodology used in the current study gives a good view to managers and safety professionals in regard to the most important indicators of process safety and allows them to focus more on important process safety indicators. [ABSTRACT FROM AUTHOR]

With the rapid popularization of mobile devices, the mobile crowdsourcing has become a hot topic in order to make full use of the resources of mobile devices. To achieve this goal, it is necessary to design an excellent incentive mechanism to encourage more mobile users to actively undertake crowdsourcing tasks, so as to achieve maximization of certain economic indicators. However, most of the reported incentive mechanisms in the existing literature adopt a centralized platform, which collects the bidding information from workers and task requesters. There is a risk of privacy exposure. In this paper, we design a decentralized auction framework where mobile workers are sellers and task requesters are buyers. This requires each participant to make its own local and independent decision, thereby avoiding centralized processing of task allocation and pricing. Both of them aim to maximize their utilities under the budget constraint. We theoretically prove that our proposed framework is individual rational, budget balanced, truthful, and computationally efficient, and then we conduct a group of numerical simulations to demonstrate its correctness and effectiveness. • We enriched the background in the introduction section. • We added a lot of the latest references. • We refined the language and descriptions to make it more clear. • We added many comparative experiments and figures. [ABSTRACT FROM AUTHOR]

• Evaluate the effect of uncertain operating and market conditions on dispatch planning. • Apply Model Predictive Control (MPC) for dispatch scheduling of CSP plants. • Monte-Carlo simulation is to evaluate the MPC performance for a case-study in Australia. • The plant profitability from electricity sales under spot prices is assessed. The aim at dispatch scheduling for concentrating solar power plants is to utilize thermal storage to maximize profit from electricity generation. The dispatching plan, however, must contend with significant uncertainty in both weather forecasts (particularly solar irradiation) and, in some locations, real-time electricity prices governed by potentially volatile markets. This paper proposes a Model-Predictive Control (MPC) which employs a novel similarity-based forecast for weather variables and exploits the predictions of electricity prices provided by the market operator. A Monte-Carlo simulation is developed to evaluate true performance of the proposed MPC against two benchmarks, with perfect knowledge (PK) forecasts and day-ahead optimized using prototypical weather (DAPW). A case study is performed on a 115 MW Solar Tower plant with 8-hour storage, hypothetically located in South Australia, and operates under either a fixed-price or a real-time spot price scenario. A Monte-Carlo simulation is conducted for 150 tests for January (summer) and August (winter). The results show in fixed-price scenario MPC achieves 82.4 % of optimal profit (i.e. obtained via PK) in January and 72.4 % in August whereas that in DAPW falls to 71.5 % and 56.9 % of optimal, respectively. In the spot market scenario, MPC reaches 71.3 % and 63.6 % of optimal profit in January and August, whereas that for DAPW reaches 61.4 % and 55.1 %, respectively. In conclusion, PK forecast assumption in dispatch planning over-estimates the achievable profit by ∼ 28–40 % particularly in spot market scenario. Moreover, MPC can mitigate the influence of uncertainties on the plant economic performance by 8.5 %–15.5 % compared to DAPW benchmarks. [ABSTRACT FROM AUTHOR]

There has been a strong wave of Eurobond issuances by Africa's frontier market economies since the start of the century. But it is not clear how these issuances have affected economic performance. This paper uses synthetic control experiments to conduct comparative case study analyses of the impacts of Eurobond issuances on economic growth, debt sustainability, and domestic capital markets. Ex post, we compare the trajectories of the relevant macroeconomic outcomes against their synthetically constructed business-as-usual counterfactual in an environment with no Eurobond issuance. The results show that, on average, sovereign Eurobond issuances have led to improvements in per capita GDP in Africa by about 10 percent above the counterfactual, business-as-usual scenario. Although most issuances were within 3 percent of GDP, they potentially led to about 13 percentage point acceleration in the debt-to-GDP ratios after ten years, compared to the counterfactual. Public capital accumulation is, on average, faster in the first two to three years following an issuance in countries with positive correlations. • Eurobond issuances by African sovereigns surged in the 2000s, with over 125 instruments issued by 21 African sovereigns. • We conduct synthetic control experiments, comparing relevant macro-outcomes with their counterfactuals under no issuance. • Eurobond have had a noticeable positive effect on incomes, about 10 percent annual improvement above the counterfactual. • But debt sustainability risks from Eurobond issuances are heightened by 13 percent above the counterfactual within 10 years. • Downside risks from Eurobonds should be actively managed to remain a useful source of financing and development in Africa. [ABSTRACT FROM AUTHOR]

This paper uses a case study of Cornwall to address the question of what new politics of place that counter-urbanisation brings about. Counter-urbanisation to Cornwall in the SW of the UK has been popular for decades. Initially it was perceived as a way to repopulate this remote rural region, and challenge its sparse population distribution. Later it became a neo-endogenous growth tool to attract a creative class of dynamic entrepreneurs, and the population has steadily grown since the 1960s. However, Cornwall remains one of the poorest parts of the UK, and poverty and homelessness are endemic. This paper uses ethnographic data to explore the social and economic impact that this has had on a coastal village, the ways that newer residents are socialized into the community, and how the village has responded to challenges maintaining a vibrant village life. The paper will use the concept of the affective assemblage to explore the different imaginaries that participants hold about Cornwall in general and in the village in particular, as it tries to maintain a cohesive community during processes of rural gentrification. The paper uses the concept of the complex adaptive assemblage to show that although the village will remain over time, the question is about whether the community will be liveable for existing inhabitants, and for those who find themselves vulnerable. Furthermore, although it has raised some economic indicators such as the cost of housing, there has been no subsequent improvement in the economy of Cornwall as a whole, and many of the participants in this study discussed how their move was facilitated by their ability to work remotely, generating productivity elsewhere rather than locally. [ABSTRACT FROM AUTHOR]

In the digital era, digitalization brings great opportunities and challenges for cities' environmental governance and economic growth. However, it is worth noting that the impact of digitalization on cities' green transition has not been studied from the perspective of Metcalfe's Law. This paper uses the principal component method and non-radial directional distance function (NDDF) to calculate the digital development level and the green economic performance of 269 Chinese cities from 2003 to 2019. (1) The empirical findings demonstrate that digitalization has become a strong driver for cities' green economic transformation. (2) Digitalization indirectly promotes green transition through industrial structure optimization and green technological innovation. (3) The heterogeneity results show that the positive effect of digitalization on green development is more obvious in eastern and economically developed cities. (4) Using the partially linear functional-coefficient model (PLFC), this paper studies the non-linear nexus between digitalization and green economic transition from the perspective of Metcalfe's Law. Thus, Metcalfe's law is confirmed in the green transition of Chinese cities. Some policy recommendations are offered for realizing the coordinated development of digitalization and greening of the urban economy. [ABSTRACT FROM AUTHOR]

• With optimal market strategy and DTR, the annual revenue may be 204% of a base case. • Ideal power forecast may not correspond to the best commitment strategy. • Depending on market prices, NPV may be between −441 million € and +9.5 billion €. • Economic benefits of DTR are estimated between 0.7 and 1 billion euros. • Overplanting and DTR may reduce LCOE by 1 €/MWh. The overplanting of an offshore wind farm (OWF) with dynamic thermal ratings (DTR) is a promising solution for enhancing OWF performance. As the overplanted OWF generates an additional energy and DTR ensures its better transfer, the research question is if final OWF profits would be higher than associated costs. While there has been growing attention on this subject in recent years, there is still no research investigating the commitment strategies of overplanted OWFs with DTR. This paper investigates how commitment strategies may affect the economic performance of an overplanted OWF with DTR. The results show that, depending on the day-ahead commitment strategy, the annual revenue of OWFs may theoretically increase by up to 21% even without overplanting nor DTR, and by up to 204 % with overplanting and DTR. However, although commitment strategies, overplanting and DTR may significantly increase annual revenues of an OWF, its net present value (NPV) still heavily depends on market prices. In the presence of low market prices as in 2018, overplanting actually reduces the NPV of an OWF and, under the conditions considered here, keeps its NPV always negative. On the contrary, in the presence of high market prices as in 2022 or feed-in tariffs, the overplanting increases the OWF NPV. In the latter case, the NPV of the overplanted OWF is estimated between 1.5 billion and 9.5 billion euros while the discounted payback period is 3–12 years. The economic benefits of DTR for the overplanted OWF are estimated between 0.7 and 1 billion euros. The paper also shows that the optimal overplanting rate is very different whether the NPV or LCOE are considered. Finally, the paper shows that committing to the actual OWF power production (i.e. assuming a perfect power forecast) does not necessarily result in the highest revenue. [ABSTRACT FROM AUTHOR]

The high cost of operation and maintenance can impede the development of offshore wind turbines (OWTs). With advancements in detection technology, condition-based maintenance (CBM) has emerged as a promising approach to managing maintenance. Numerous CBM polices have been studied to achieve a cost-effective maintenance. However, little research has been conducted on discovering the cost-optimal CBM policy for OWTs. With this motivation, a deep reinforcement learning (DRL) framework for exploring the cost-optimal CBM policy is proposed in this paper. Four CBM policies (i.e. uniform or dynamic inspection interval, and fixed or adaptive repair threshold) are formulated as the Markov decision process model. Two DRL algorithms (deep Q network and proximal policy optimization) are applied to derive the dynamic inspection interval and the adaptive repair threshold. To illustrate this framework, a fatigue OWT component is used as an example. The four policies are optimized under varying conditions to find the cost-optimal CBM policy. Moreover, performance comparison of DRL algorithms is performed. The case study illustrates the advantage of DRL in deriving optimal maintenance policies for fatigue-sensitive OWT components and highlights the interrelationship between maintenance policy and economic performance. This paper concludes by discussing the effect of cost elements on the CBM policies. • A DRL framework is proposed to derive the cost-optimal CBM policy for OWTs. • CBM policies with different inspection intervals and repair thresholds are studied. • The performance of two DRL algorithms is compared under different conditions. [ABSTRACT FROM AUTHOR]

In a companion paper, Ojeda-Rojas et al. (2021) [1] describe a stochastic agent-based simulation (ABS) model of a cow-calf operation on a commercial farm in São Paulo, Brazil. The model's parameterization was based on data collected from two sources: a real beef cattle herd and related scientific literature. Based on the mentioned simulation model, this study aims to assess the economic outcome of 10 different reproductive scenarios: Natural mating only (ONM); one timed artificial insemination (TAI) plus natural mating (NM) (1TAI + NM); two TAI plus NM, with 24, 32, and 40 days between TAI (2TAI/24 + NM, 2TAI/32 + NM, and 2TAI/40 + NM, respectively); three TAI without NM, with 24, 32, and 40 days between TAI (3TAI/24, 3TAI/32, and 3TAI/40, respectively); and three TAI plus NM, with an interval between TAI of 24 (3TAI/24 + NM) and 32 days (3TAI/32 + NM). The simulation was performed on an animal-by-animal basis over a time horizon of 5000 days. Each scenario had 32 farms, and each farm kept up to 400 adult females. According to the scenario, a bull population was composed of 0, 7, or 15 individuals. The outcomes, represented as means ± standard deviations, were assessed after reaching a steady-state (1825 days). The model outcomes showed that the 3TAI/24 + NM scenario resulted in higher incomes (US$ 96,479.19 ± 709.81), whereas the ONM scenario had the lowest incomes (US$ 79,753.37 ± 741.87). The 3TAI/24 + NM (US$ 101.720.63 ± 79.21) and ONM (US$ 90.898.58 ± 59.17) scenarios presented the highest and lowest total operating costs (TOC), respectively. However, when TOC was evaluated per kg of the weaned calf, the highest and lowest costs were associated with the ONM (US$ 2.81 ± 0.03/kg) and 2TAI/24 + NM (US$ 2.17 ± 0,04/kg) scenarios, respectively. Our model suggests that reproductive strategies that use TAI have a better economic performance than those under NM. However, when performing three TAI with an interval of 40 days, the benefit was lower; in some cases, it was even worse than the ONM. Combining TAI with early pregnancy diagnosis resulted in better economic performance than other TAI programs and NM. The 2TAI/24 + NM scenario outperformed the others due to the contrast between its high income and moderate costs. Beef cattle production is a highly complex system. Simulations models, specifically ABS models, could make the decision-making process on complex systems straightforward and effective. Furthermore, ABS models can overcome the limitations of conventional research approaches, such as high costs and long experimentation periods. • A stochastic agent-based model was used to simulate a cow-calf operation. • We evaluate the economic performance of using natural mating alone or with TAI. • The analysis considers the number of TAIs (1, 2, or 3), days between them (24, 32, and 40), and early pregnancy diagnosis. • Combining TAI with early pregnancy diagnosis resulted in a better economic performance. • The 2TAI/24 + NM scenario outperformed the others due to its high income and moderate costs. [ABSTRACT FROM AUTHOR]

• We present a multinomial approach not previously used in the macroeconomic literature for the study of growth and industrial dynamic. • The successful growth dynamic observed during the 1995–2014 period in several emerging economies is very heterogeneous in terms of their industrial transformation. • Developed economies grew slowly and, generally, through episodes of limited industrial transformation. • The relationship between economic fitness and the countries' industrial and growth dynamics generates a path dependency in economic development. • The fitness score of a country –that moves very slowly during one or two decades– establishes the most common sequences of episodes to be observed. When analyzing countries' medium- and long-term economic performance, it is important to study jointly the dynamic of growth and the industrial evolution that determines how the productive structure changes over time. In this paper, we use the Economic Fitness metric to describe the competitiveness of the countries' industrial structure, and classify economic episodes, with five-years windows, to establish how countries grow (i.e., above or below a trend, and with a dynamic or static industrial structure.) We show a complex growth dynamic using data covering two decades (1995–2014) for a large set of countries. This pattern indicates that the observed sequences of spells vary substantially even between countries within the same growth regime (low, medium, and high). Moreover, we find a robust statistical relationship between these spells and Economic Fitness with a multinomial econometric model. In particular, we show that economies with higher fitness are more resilient since episodes of below-average growth and the net disappearance of competitive firms are less likely to happen. [ABSTRACT FROM AUTHOR]

• We assess the sustainability of growth led by government and exports demand. • We verify the stability of public and external debt ratios in an SSM model. • Thirlwall's Law appears as the external constraint growth rate in the long run. • A fiscal policy rule changes the government's share to contain foreign debt. • Simulations suggest the economic performance improves with structural policies. The Sraffian supermultiplier model revealed the role of autonomous demand in economic growth. Nevertheless, the sustainability of growth requires the stability of the financial stocks behind autonomous demand. Growth led by government expenditure and exports is thus stable if both public and external debts are stable. In this paper, we assess the stability of this growth process in a supermultiplier model. The external constraint may appear as a restriction to external indebtedness, imposing an upper limit to growth. Nonetheless, the domestic autonomous expenditure can keep the economy distant from the external constraint. A fiscal policy rule is proposed to contain foreign indebtedness. Simulations support the analytical results, and compare the outcomes of the fiscal policy rule and a structural change policy. Altogether, the model provides stability conditions for growth in an open economy paying its international liabilities in foreign currency. [ABSTRACT FROM AUTHOR]

Internet satellite constellations are expected to play an important role in accommodating the rising global demand for internet access. Such rise in demand, however, is highly uncertain. Staged deployment is an approach that provides flexibility to tackle demand uncertainty by enabling the real option to reconfigure a constellation if demand changes. Advancements in satellite technology have led to the emergence of multi-layered constellations. This opens the opportunity to enhance staged deployment by enabling an additional real option: adding a new layer to a constellation. This real option has no associated reconfiguration costs, and therefore has the potential to reduce the cost of staged systems deployment. This paper proposes a framework to design multi-layer staged deployment systems and analyse their effectiveness in modern mega-constellations under global demand uncertainty. The framework is applied to four case studies based on market projections. Results show that multi-layer staged deployment decreases the expected life-cycle cost (ELCC) by 42.8% compared to optimal traditional single-layer deployment. Multi-layer staged deployment is more cost effective than single-layer staged deployment in all practical cases, which decreases ELCC by 22.9% compared to traditional deployment. Several cost altering mechanisms in staged deployment are identified. The results and analysis provide improved economic performance and better resource utilization, thus contributing in the long term to improved sustainability and market resilience. An accompanying decision support system provides system engineers with valuable insights on how to reduce deployment costs using the proposed multi-layered staged strategy. • Staged mega-satellite constellations deployment provides flexibility to deal with uncertain growing global internet demand. • A proposed framework enables more adaptable, sustainable, and resilient multi-layer staged deployment (MLSD) systems. • Results show 43.1% decrease in expected life-cycle cost (ELCC) compared to traditional design strategies. • Flexible MLSD is 22.9% more cost effective than flexible single-layer staged deployment. • A decision support system provides further insights on design and deployment of flexible MLSD systems. [ABSTRACT FROM AUTHOR]

Recent technological developments make perovskite solar cells (PSCs) particularly suitable for building integrated photovoltaic (BIPV) applications on vertical building envelopes, but the relatively short lifespan of PSCs requires frequent replacement, thereby generating substantial waste. Careful consideration of circularity credentials of this novel technology is therefore essential prior to the extensive implementation of vertical PSCs in building envelopes. This paper provides a circular economy approach for the implementation of PSCs in vertical envelopes and assesses its economic feasibility by life cycle cost analysis in Europe. The process of recycling PSC is developed. The economic performance of PSC envelopes is provided and compared to that of the conventional rigid BIPV system. Uncertainty analysis and sensitivity analysis of economic indicators are then performed to identify the influential parameters. The findings indicate that the PSC envelope has a significant potential for circular BIPV components and that PSCs applied on vertical envelope are economically viable. • LCCA of vertical PSC envelopes with recycling strategy is analyzed in Europe. • Recycling strategy of PSC is explored before diffusion to overcome PSC's short lifespan. • PSC price is the most influential factor for the deviation of LCOE. • PSC envelope has potential to achieve profitability in most regions of Europe. [ABSTRACT FROM AUTHOR]

Food systems are dominated by multiple risks inflicted by their surrounding environments that pose pressures on the continuous and efficient supply of food products. Market dynamics represented by competitive and cooperative behaviors of the system's main players is one of the uncertainties that influence the availability and affordability of food products. Efficient modeling of these risks can assist decision-makers in simulating and predicting future actions that mitigate the impact that market dynamics have on the provision of food products. This paper suggests an Agent-based model-based framework that simulates the behavior and tracks the economic and environmental performances of the tomato supply system in the State of Qatar. It considers three different scenarios representing the current situation of the market in addition to a competitive and a cooperative trade network. Interactions between trade partners are modeled using two game theoretic approaches counting Cournot competition and Cartel collusion. Based on the research findings, a competitive global market can bring economic benefits to Qatar as an importing nation, but this approach also entails substantial water consumption and results in significant environmental emissions. Conversely, collaboration among exporting countries demonstrates a potential 20% reduction in water usage and a 15% decrease in environmental emissions compared to the competitive scenario, offering enhanced environmental performance albeit at higher economic costs. This study provides a prescriptive analysis that enables policymakers to quantify the trade-offs between economic efficiency and environmental sustainability. These insights are crucial for guiding strategic planning for food supply security and environmental conservation. By understanding the implications of market structure changes, policymakers can navigate potential challenges more effectively and develop targeted policy interventions that enhance the resilience of the food supply system against market volatility and environmental impacts. This analysis supports proactive policy-shaping that aligns with their desired outcomes, ensuring a balanced approach to managing economic benefits and environmental considerations. [ABSTRACT FROM AUTHOR]

• Novel ammonia blended natural gas GT-STCC based on dual-temperature CO 2 turbines. • Effect of fuel ammonia blending ratio etc. on thermodynamic performance is studied. • Power generation cost and pollutant emission including CO, CO 2 , NO x are evaluated. • Energy, economic, environment performance trade-off via tri-objective optimization. • GT-STCC shows a 2% higher thermal efficiency, a 12.8% lower cost than GT-sCO 2 -tCO 2. In order to solve the temperature interference problem, this paper proposes a novel ammonia-blended natural gas fueled gas turbine − split transcritical CO 2 cycle (GT-STCC) combined system based on dual-temperature CO 2 turbines. One split stream of CO 2 is pumped to CO 2 heater for recovering GT waste heat, while the other stream is pumped to CO 2 regenerator for utilizing high-temperature CO 2 turbine (HCT) waste heat and driving low-temperature CO 2 turbine (LCT). The sensitivity analysis of system thermodynamic performance with respect to fuel ammonia blending ratio, compressor pressure ratio, heat exchanger effectiveness, LCT CO 2 split ratio, CO 2 evaporation pressure is performed under the same total fuel heat input. In addition, the impacts of key operation parameters on power generation cost (PGC) and pollutant emission, including CO, CO 2 , NO x , are clarified. Energy, environmental and economic performance trade-off is achieved through a tri-objective optimization based on genetic algorithm. The results show that a 50 % increase of fuel ammonia molar blending ratio results in a 1.29 % decrease of total thermal efficiency, a 24.66 % decrease of total normalized pollutant emission, and a 35.71 % increase of power generation cost (PGC) for novel GT-STCC. As compressor pressure ratio or heat exchanger effectiveness changes, the normalized CO 2 and NO x emissions show opposite trends. The PGC and total normalized pollutant emission reach minimums under the same LCT CO 2 split ratio of 0.4, while they obtain minimums at different CO 2 evaporating pressures of 250 bar and 350 bar, respectively. The tri-objective optimization shows that the optimal total system thermal efficiency, total pollutant emission and PGC are 54 %, 0.3149 × 10-1 t/MWh and 0.05176 $/kWh, respectively. Compared to the GT − supercritical CO 2 − transcritical CO 2 cascade system, the novel GT-STCC system is a more promising power system due to its simpler configuration, 2 % higher overall thermal efficiency and 12.8 % lower PGC. [ABSTRACT FROM AUTHOR]

The contribution of good governance to development has been extensively examined; however, the effects of good governance on innovation, a critical factor for achieving sustainable development in the volatility, uncertainty, complexity and ambiguity environment, have received limited attention. This study examines the effects of good governance on innovation and its channel mechanisms. Thus, using a two-way fixed effects regression model, we analyse data from a sample of 112 economies worldwide over the period 2011–2021. We determine that good governance, measured using the worldwide governance indicators, has positive effects on innovation. Moreover, based on the shaping effect of good governance on the external environment, we identify that economic freedom serves as a channel mechanism through which good governance impacts innovation. Furthermore, we observe that compared with advanced economies, the positive effects of good governance on innovation are more significant in samples of emerging markets and developing economies. These findings underscore the mechanisms through which good governance impacts innovation, drawing attention to the shaping effect of good governance on the external environment and offering empirical evidence for economies to enhance economic freedom and promote innovation. • Examining the effects of good governance on innovation • Good governance has a shaping effect on the external environment. • Economic freedom is a channel mechanism for good governance to impact innovation. • The findings of this paper support the scepticism towards the Popper hypothesis. [ABSTRACT FROM AUTHOR]

Yemen witnesses a heinous war and continual conflict that devastates its fragile infrastructure. The country's development indicators devolve significantly, and, among other sectors, higher education and its quality have been imperiled. The objective of this paper is to explore the effects of war on the quality of higher education in Yemen from the standpoint of Yemeni scholars. This qualitative study is based on grounded theory design and used semi-structured in-depth interview methods to collect data from Yemeni scholars within and outside Yemen. The core questions focused on the impact of war, the actions taken by scholars, and the prospects of higher education quality. Seventeen diverse scholars were included in the study. The analysis of data outlined six war-related factors that affect the quality of higher education: attacks on scholars, financial constraints, corruption, human capacity shortage, poor research performance, and lack of physical capacity. Realities are reconstructed through descriptions of the trajectory of the war and its negative consequences on scholars and their endeavors. Quality as a sign of the good functioning of higher education institutions is not an exclusively sectorial issue. Actions and prospects need to fit within frameworks of national reconciliation, regional peace, and frameworks of international cooperation. Further research tackling other dimensions of education quality and including other stakeholders is needed. Rethinking and reforming Yemen's higher education system in its different aspects and challenges, are paths to peacebuilding and the recovery of the country. A roadmap prioritizing this reform is urgently needed. • The devastating effects of war were examined from the perspective of Yemeni scholars. • The endurance of scholars to cope with the situation was exposed, analyzed, and compared with other countries in the region. • A prospect for national, regional, and international actions was suggested. [ABSTRACT FROM AUTHOR]

In this paper, we address the economic performance of Model Predictive Control (MPC) while operating at a backed-off operating point. Operating the plant at a constrained optimal point will often cause constraint violations due to uncertainties such as disturbances and measurement errors, etc. To ensure dynamic feasibility, the concept of economic back-off is used. In this work, we select the set point as the economic back-off point such that the dynamic operating region should have the least variability in the active constrained variables while ensuring the feasibility of other variables. In other words, the dynamic operating region is oriented by the proper design of a controller such that variability in active constrained variables is as low as possible. This controller design can be transformed into equivalent objective function weights of the MPC controller. In this study, we demonstrate that the determined back-off point is optimal for both linear controller and MPC controller when there are no unconstrained degrees of freedom. For the case with unconstrained degrees of freedom, the back-off point determined using the presented approach is optimal only for a linear controller but suboptimal for an MPC controller. Demonstrative case studies are presented to illustrate the economic performance of the MPC controller at the determined economic back-off point. • We proposed an economic back-off formulation for linear discrete-time systems. • We adopted a two-stage iterative solution strategy to determine optimal back-off. • We assess the economic performance of the MPC controller using inverse optimality. • We emphasize the role of unconstrained degrees of freedom in determining back-off. [ABSTRACT FROM AUTHOR]

• Biform games can coordinate supply chains with competition and cooperation relation. • Carbon complementary is a beneficial way to organize the internal carbon trading. • The pareto improvement can be achieved under hybrid carbon trading schemes. • We incorporate the Minimax and Maximin principle and Shapley value into biform game. Cap-and-trade, Certified Emission Reductions (CERs) and Renewable Energy Consumption Obligation (RECO) are three regulatory instruments used by governments to decarbonize supply chains. Integrating these mechanisms creates a Carbon Complementary Supply Chain (CCSC), in which traditional energy manufacturers (TMs) with high emissions can offset their carbon footprint by trading CERs with renewable energy manufacturers (RMs) who develop the CER projects, and compete with RMs. In the downstream, retailers are incentivized to procure more renewable energy products to avoid RECO penalties. Given that all the CCSC members tend to cooperatively invest in the CER project, this paper proposes a novel biform game-based coordination mechanism combining noncooperative and cooperative games to promote CCSC's synergy. The findings show that this mechanism can induce CCSC members to cooperate, achieving Pareto improvement in social welfare, economic performance, and individual profits under specific regulatory intensity thresholds compared to the noncooperative scenario. Our findings contribute to the ongoing debate on the role of carbon regulations in enhancing supply chain performance by providing insights into the contractual relationships among supply chain members and the economic forces at play. [ABSTRACT FROM AUTHOR]

The central environmental protection inspection is an institutional innovation in China that aims to supervise enterprises by monitoring government environmental enforcement. This paper examines the effectiveness of central environmental protection inspection in improving enterprise environmental performance by using a quasi-natural experiment of the first round of central environmental protection inspection. The study reveals that the central environmental protection inspection improves enterprise environmental performance by strengthening local government environmental enforcement and environmental attention. This is evidenced by the increase in enterprise environmental capital expenditure and the decrease in pollution discharge fees. The impact of central environmental protection inspection on enterprise environmental performance is strengthened by local governments' environmental regulation and environmental fiscal expenditure, as well as by public participation. Under the pressure of central environmental protection inspection, heavily polluting enterprises engage in production process improvement and R&D investment, which can improve their economic performance. This can ultimately lead to a competitive advantage for enterprises, promoting a win-win situation for both environmental and economic performance. [ABSTRACT FROM AUTHOR]

The manufacturing industry is facing a major challenge in balancing economic performance with environmental sustainability. To address this challenge, extant research has suggested that servitization could help align these objectives. However, the current evidence base is too scattered for policymakers to act on and support servitization in a targeted manner. Therefore, we conduct a systematic literature review to analyze over 120 research papers to establish the current understanding of the impact of servitization on the environmental and economic performance of a firm, and identify the contextual variables affecting this impact. The study identifies and critically appraises the body of literature that provides the current evidence base on the impact of servitization, the core areas of impact investigated and the methods that are used to establish this impact. Additionally, we conduct a thematic analysis of variables of impact to explore the theoretical perspectives that are used to explain the impact of servitization. Building on these theoretical perspectives we offer concrete propositions to further develop the research on the impact of servitization on environmental and economic performance. [ABSTRACT FROM AUTHOR]

The final geometry of open stopes often diverges from the design, creating unintentional volumes of overbreak and underbreak. Tools, such as the Stability Chart, are used for predicting overbreak, but its limitations regarding the precision of the predictions and the exclusion of underbreak have constrained the benefits of a predictive tool at the design stage. Furthermore, the economic aspects are not integrated when addressing geomechanical stope design. This paper presents how understanding and predicting stope performance at a meter-scale resolution through a multivariate model can be used for assessing the geotechnical (overbreak and underbreak) and economic stope performance. These predictions estimate the magnitude and location of overbreak and underbreak across the design surface, and are used to resolve the expected geometry of the mined void. The incorporation of a predicted mined void with grade values from a block model allows for a comprehensive economic stope performance estimate. This work is a significant step towards a stope design and planning process that minimizes the stability issues, dilution and loss of ore across the stope. As designing for higher ore recovery increases the potential for dilution and vice versa, this approach allows for the value realised from mining a stope to be maximised by quantifying this inherent economic trade-off. The enhanced resolution of both data and predictions has allowed for a more comprehensive evaluation of the predicted stope performance and economic outcomes during the design phase. This marks a notable advancement in the ability to design and plan the optimal stope. • A new probabilistic stope design approach for assessing the expected mining void. • Utilises data at a meter scale resolution and a multivariate model. • A comprehensive evaluation of the predicted overbreak and underbreak. • Incorporation of grade to quantify the economic trade-off of different designs. • It marks a notable advancement in designing and planning the optimal stope. [ABSTRACT FROM AUTHOR]

This paper proposed an innovative hybrid system to generate electricity and fresh water with higher energy efficiency. A subsystem is employed by integrating DCMD and heat pump to recover waste heat of PEMFC to produce fresh water. The thermodynamic and exergoeconomic models are established to evaluate the system comprehensive performance. Compared with the PEMFC alone, the results demonstrated that the proposed hybrid system achieves a 42.07 % increase in energy efficiency and provides 177.86 kg/h of fresh water. The components with high exergy destruction are PEMFC, Relief value, Inverter, Separator 2 and DCMD with the exergy destruction rate of PEMFC stack accounting for 54.55 %. The parametric analysis results indicate that the variation of the membrane filament number, feed and permeate flow rates all have evident impacts on the thermodynamic and economic performances of the hybrid system. The multi-objective optimization is conducted by adopting NSGA-II and three decision-making methods. The optimal solution obtained by AHP-entropy-TOPSIS approach for the net power out, exergy efficiency, WPC, and total exergy cost rate are 96059W, 0.5293, 0.2995 $/m3, and 14.27 $/h, respectively. In addition, the obtained results shown that the simulation times of NSGA-II are significantly reduced from 89.30 to 11.20 h by introducing BP-ANN to improve the simulation efficiency. [ABSTRACT FROM AUTHOR]

This paper compares the performance of conventional and organic fruit farms in Spain, using a set of base indicators to assess their economic and environmental performance on a per hectare basis. Composite indicators are also calculated to measure the overall economic and environmental performance of both production systems. Comparisons are made using propensity score matching to minimize the non-randomization biases caused by structural differences between the samples of conventional (n = 552) and organic (n = 127) fruit farms sourced from the Spanish Farm Accountancy Data Network (RECAN). The results based on per hectare metrics point to modest changes in the performance of farms that converted to organic farming. This is mainly because most converted farms were former conventional farms characterized by lower profitability and less intensive input use, consequently minimizing the effects of the conversion process. Nevertheless, the conversion outcomes exhibit a degree of variability depending on the specific type of fruit production. Economic gains are only discernible in the case of nut farms, whereas fruit and tropical fruit farms tend to yield the most favorable results per hectare from an environmental perspective. • Changes in per hectare performance are assessed when fruit farms convert to organic. • A complete set of economic and environmental base and composite indicators is used. • A matching procedure is implemented to obtain unbiased difference estimators. • Small changes are found in the per hectare performance of farms after conversion. • Mixed results depending on the type of fruit production subsector considered. [ABSTRACT FROM AUTHOR]

This paper explores the relationship between real exchange rate (RER) misalignments and economic fundamentals with respect to the exchange rate regime choice. In a first step, using the technical inefficiency model, we measure RER misalignments and, more specifically, RER overvaluation. In a second step, we assess the effects of the main economic indicators and the choice of a country's exchange rate regime on RER overvaluation. Our empirical findings, based on nonlinear specifications and impulse response functions of Panel Vector Auto Regression (PVAR) estimations, reveal that for developing countries, and during the expansion and peak phases of the business cycle, the floating exchange rate regime may be used as a policy tool to contain the pressure in the exchange rate, and so limit overvaluation. Our findings also reveal that in the context of fixed and intermediate exchange rate regimes, an expansionary monetary policy is an effective tool to stabilize exchange rate fluctuations and mitigate overvaluation. • We estimate exchange rate misalignment by using a semi-parametric approach based on a technical inefficiency model. This approach allows us to address the well-known puzzle that fundamental variables provide little help in predicting changes in exchange rate models. •By means of an impulse response function estimation of the PVAR model, we evaluate the response of both overvaluation and economic fundamentals to different shocks. •Our empirical findings reveal that economic and monetary expansions appear to be associated with lower overvaluations. However, our evaluation of the impact of an increase in growth rate with respect to exchange regimes leads us to conclude that the more flexible the currency regime, the lower the misalignment. [ABSTRACT FROM AUTHOR]

Real-time optimization with persistent parameter adaptation (ropa) is an rto approach, where the steady-state model parameters are updated dynamically using transient measurements. Consequently, we avoid waiting for a steady-state before triggering the optimization cycle, and the steady-state economic optimization can be scheduled at any desired rate. The steady-state wait has been recognized as a fundamental limitation of the traditional rto approach. In this paper, we implement ropa on an experimental rig that emulates a subsea oil well network. For comparison, we also implement traditional and dynamic rto. The experimental results confirm the in-silico findings that ropa 's performance is similar to dynamic rto 's performance with a much lower computational cost. Additionally, we present some guidelines for ropa 's practical implementation and a theoretical analysis of ropa 's convergence properties. [Display omitted] • rto with persistent parameter adaptation (ropa) is implemented on lab scale plant. • Steady-state and dynamic rto are also implemented for comparison. • ropa avoided ss detection and showed economic performance comparable to drto. • Guidelines for the practical implementation of ropa. • An analysis of ropa convergence to the steady-state optimum is carried out. [ABSTRACT FROM AUTHOR]