Economic Evaluation Index Research Articles

Connections and Spatial Network Structure of the Tourism Economy in Beijing–Tianjin–Hebei: A Social Network Perspective

In the context of the coordinated development of Beijing–Tianjin–Hebei, examining the spatial connections and network structure characteristics of the tourism economy holds substantial theoretical and practical significance. This study constructs a tourism economic quality evaluation index system from four dimensions and optimizes the tourism economic gravity model by incorporating time distance and weight factors to dynamically simulate the intensity of tourism economic spatial connection (ITESC). Based on the new perspective of relational data, social network analysis is employed to investigate the spatial correlation network characteristics and group structure changes in the tourism economy within the Beijing–Tianjin–Hebei urban agglomeration (BTHUA). The results demonstrate a significant improvement in overall tourism economic quality from 2013 to 2022, with the average quality increasing from 0.128 in 2013 to 0.157 in 2022. Tourism economic spatial connections are prevalent among cities, exhibiting heterogeneous characteristics, characterized by density in the north and relatively sparse in the south. The network cohesion of ITESC strengthens, and the network structure evolves from a highly centralized to a multi-centralized configuration, with increasingly frequent cooperation and interaction in tourism between cities. Beijing, Tianjin, and Shijiazhuang occupy central positions in the network, exhibiting strong ITESC and a high degree of connectivity, generating a significant “trickle-down effect” on peripheral cities. Consequently, strengthening ITESC between peripheral cities and core areas, as well as enhancing the bidirectional spillover of tourism development between cities, is crucial for the future sustainable and coordinated development of tourism in the BTHUA.

Spatio-Temporal Evolution and Driving Factors of Tourism Economic Resilience in the Yili River Valley

The tourism economy plays an essential role in supporting and driving tourism development. Therefore, studying its resilience is crucial for promoting sustainable and high-quality tourism development. The purpose of this study is to construct a tourism economic resilience evaluation index system and assess the tourism economic resilience of 10 counties and cities in the Ili River Valley from 2010 to 2019 using the entropy weight TOPSIS method. The results show that (1) the tourism economic resilience shows a “W”-shaped time-series dynamic development trend, especially a decline in 2012–2013 and 2015–2016; (2) the spatial pattern shows a non-equilibrium characteristic, with the northwestern part of the valley represented by Yining City showing a high level of resilience, and the central to southeastern counties and cities showing a lower level of resilience; (3) the spatio-temporal evolution steadily points to “northwest–southeast”, and there are five toughness convergence clubs, with obvious stability and neighborhood effects; (4) and the analysis of the driving factors shows that the number of employees in the tertiary industry, especially the input of high-quality talents, is crucial to improving the quality of services, strengthening the ability to withstand risks and the potential for development, and its impact is significant. These results provide an important reference for the formulation of tourism development strategies and promote the sustainable development of tourism.

Research on the optimization of the clean heating system for regional residential buildings based on the multi-objective optimization strategy

For the residential building district heating (RBDH) system, choosing the appropriate combination of heat sources according to local conditions is the key to improving economic efficiency. In this study, three climatic regions in China were selected, namely, a hot summer and cold winter region, cold region, and severe cold region. Among them, Nanjing, Tianjin, and Shenyang were selected as typical representative cities in the hot summer and cold winter region, cold region, and severe cold region, respectively. Taking the levelized cost of heat (LCOH) as the economic evaluation index and considering the carbon emission cost of the system operation, the energy consumption and the CO2 emissions were analyzed. TRNSYS software was used to simulate and analyze the system performance. The multi-objective optimization based on a genetic algorithm was proposed to optimize system parameters. From an economic point of view, the SA system was suitable for the hot summer and cold winter region, the SAS system was suitable for the cold region, and the SE system was suitable for the severe cold region. The operation control strategy based on quality adjustment can reduce heating energy consumption and maintain indoor temperatures at approximately 20°C. The proportion of clean energy heating in the optimized heating system decreased after the multi-objective optimization strategy. However, the initial investment and maintenance costs of the system were reduced, which reduced the LOCH of the system. Therefore, the multi-objective optimization strategy can effectively reduce the heating costs.

Communication network robust routing optimization in an integrated energy cyber–physical system based on a random denial-of-service attack

The integration of power grids and communication networks in smart grids enhances system safety and reliability but also exposes vulnerabilities to network attacks, such as Denial-of-Service (DoS) attacks targeting communication networks. A multi-index evaluation approach is proposed to optimize routing modes in integrated energy cyber-physical systems (IECPS) considering potential failures from attacks. Security and economic service evaluation indexes are incorporated to quantify the significance of information flow routing. An optimization model for electric, heat, and gas routing in worst-case scenarios is formulated and solved using a column and constraint generation algorithm. The optimized routing method effectively circumvents specified attack areas, reducing the correlation degree of communication links within the attack area. Comparison with single-service optimization methods demonstrates the superiority of the proposed approach in mitigating the impact of network attacks on IECPS. The study highlights the importance of considering security and economic factors in optimizing routing modes to enhance the resilience of integrated energy cyber-physical systems against network attacks, particularly DoS attacks on communication networks. The evaluation index approach presented in this study provides a comprehensive method for assessing the importance of communication links in IECPS and optimizing routing modes to improve system robustness and reliability in the face of network attacks.

Evaluating the Feasibility of Low-Carbon Technology in the Sustainable Economic Development of Electricity Using Generative Adversarial Networks

Abstract Electricity occupies a central position in energy strategy, and the low-carbon development of the power industry is an important guarantee for achieving sustainable development and carbon dioxide reduction goals. Orderly carrying out low-carbon technology transformation and innovation in electricity, ultimately achieving the goal of sustainable development of the power industry, has strong practical significance. Therefore, this article conducts a feasibility analysis of using generative adversarial networks to evaluate low-carbon technologies in the sustainable economic development of electricity. Firstly, the background of the theory of technological and economic evaluation was analysed and used as a theoretical basis. Secondly, an adversarial network was generated for the study of low-carbon emissions in the power industry, and an evaluation system for low-carbon technology in the sustainable economic development of electricity was constructed. The study showed that the preliminary economic evaluation index system and comprehensive benefit evaluation model for low-carbon technology transformation projects in electricity established in this article have feasibility and reliability for systematic analysis and evaluation of actual projects.

Digitization and carbon emissions: how does the development of China's digital economy affect carbon intensity?

The digital economy and the pursuit of carbon peak and carbon neutrality have emerged as crucial focal points for China's future development. However, the intricate relationship between the digital economy and carbon intensity remains uncertain. Based on the construction of the digital economy evaluation index system, using panel data for 30 provinces in China from 2011 to 2019, this study estimates the impact of the digital economy development on carbon intensity by adopting the system-generalized method of moments (SYS-GMM) technique. The results show that the digital economy can effectively reduce the carbon intensity. This conclusion was supported by robustness tests. However, the carbon emission reduction effect of the digital economy exhibits heterogeneity with respect to the digital economy dimensions and regions. In addition to digital industrialization and industrial digitization reducing the carbon intensity, the digital economy development carrier has an inverted U-shaped nonlinear relationship with carbon intensity. Additionally, the digital economy has a more obvious inhibitory effect on carbon intensity in the eastern region. Most importantly, besides the mediating effects of technological progress and financial development, this paper finds that the digital economy can increase carbon intensity through human capital accumulation. These conclusions provide a certain scientific basis for the effective implementation of China's digital economy and carbon peak and carbon-neutral development strategy.

Measuring and Analyzing the Resilience of China’s Coastal Marine Economy

Abstract Marine economic resilience can reflect the stability and health of the marine economic system and plays an important role in guiding regional marine economic development. Starting from the formation mechanism of marine economic toughness, the article establishes a marine economic toughness evaluation index system, selects marine economic data from 11 coastal regions from 2012 to 2022 as the research object, adopts the CRITIC-entropy weight method to solve the index weights, and measures the marine economic toughness using the TOPSIS model We introduce the kernel density estimation to explore the spatio-temporal evolution trend of marine economic toughness, use the barrier diagnostic factor to study the barrier degree of marine economic toughness and combine it with the OLS regression to analyze the influencing factors of marine economic toughness. In 2012-2022, Guangdong’s marine economic toughness score was 0.377, which is 2.25 times higher than that of Guangxi. Furthermore, various regions’ marine economic toughness shows a yearly upward trend. The kernel density curve of marine economic toughness is broad peak—sharp peak—broad peak; the obstacle factor of marine economic toughness is mainly adaptive capacity and renewal capacity; its obstacle degree is 0.383 and 0.374, respectively; and the marine economic toughness of the sea area will increase by 0.238% when the level of marine scientific research is increased by 1%. Optimizing the policy system and embracing technological innovation are inevitable choices to enhance the marine economy’s resilience in coastal areas.

The economic and environmental dividends of the digital development strategy: Evidence from Chinese cities

Digital development is critical for achieving coordinated regional economic growth, energy conservation, and emissions reduction, which makes it a viable method for achieving carbon neutrality and peaks. This study investigates the impact of the digital economy on urban total factor productivity and carbon emissions, as well as its mechanism, from 2011 to 2019 by developing a digital economy evaluation index system. We find that the growth of the digital economy can increase urban total factor productivity while lowering carbon emissions and also has a significant spatial spillover effect on regional economic growth, energy conservation, and emissions reduction. The main influencing mechanism is that the digital economy accelerates marketization by encouraging industrial structure upgrades and technological progress, which results in higher total factor productivity and lower energy consumption. In terms of the spatial distribution, the digital economy promotes total factor productivity more in the central and western regions and large cities and promotes carbon emission reduction less in the eastern regions and smaller cities. The findings extend the benefits of the digital economy beyond economic and social welfare benefits and serve as a model for achieving a win–win situation in terms of both economic growth and carbon emissions reduction.

A pragmatic retrofitting approach to enhancing the thermal, energy and economic performance of an educational building: a case study in Malaysia

Abstract Building retrofit procedures play a crucial role in improving the energy performance and economic indicators of a building. In this context, an energy audit is typically recommended, but it is seldom used as a comprehensive approach due to the complexity and associated costs. This article aims to conduct a holistic energy audit approach for a university building in Malaysia, with the objective of diagnosing energy efficiency deficiencies, identifying areas of energy waste and proposing practical retrofit measures accordingly. The approach involved multiple stages, including measurements, surveys and simulation work. Eight energy-saving measures were proposed, targeting improvements in envelope elements, cooling and lighting systems, and operation and control. The Design-Builder software was utilized for energy simulation, assessing the annual energy savings. Economic evaluation indices, such as net present value and simple payback period, were used to assess the economic feasibility of the measures. The results demonstrated significant potential for energy reduction, with each measure achieving annual energy reductions ranging from 2% to 18%, and a cumulative impact of 41% on annual energy consumption when combined. The investment payback period for the energy-saving measures varied from 0.8 to 8.9 years, with a payback period of 3.9 years for the combined energy-saving measures. Furthermore, the net present value was positive, indicating the economic feasibility of investing in the proposed energy-saving measures. These findings provide valuable energy-saving opportunities that can be applied to improve similar buildings on the university campus.

Thermoeconomic analysis and multiple parameter optimization of a combined heat and power plant based on molten salt heat storage

The global energy supply is transitioning to sustainable, low-carbon energy. Power-to-heat technology with molten salt thermal energy storage (TES) is a potential way to accommodate renewable power, and the stored heat can be converted to heat and electricity for residential heating and power supply with a combined heat and power plant (CHP). In this study, a CHP-TES system with valley electricity as the input energy source is proposed. Thermodynamic models are developed, and an economic evaluation index is established by considering electricity price, heat price, TES scale, and CHP layout. Then, multiparameter optimization of the proposed CHP-TES system is conducted with the genetic algorithm, and the energy-exergy-economic feasibilities of the system are evaluated. The CHP-TES system can operate under CHP and condensing modes in heating and non-heating periods, and its output power can be regulated during peak and valley load time, respectively. The exergy efficiency of the CHP-TES system is 45.07% and 36.67% in condensing modes with the peak and valley output power, respectively. The exergy efficiency of the CHP-TES system is 46.16% and 42.96% in CHP modes with the peak and valley output power, respectively. The exergy is mainly destructed in the electric heater, which accounts for over 65% of the total exergy loss in all operation modes. The equipment investment of the TES, steam generator, and CHP systems account for 87.59%, 3.53%, and 8.88% of the total, respectively. The electric heater takes the largest portion of the total equipment investment, which accounts for 37.99%. When the peak-valley electricity price changes from 0.121 $ kWh−1 to 0.259 $ kWh−1, the net present value increases from $592 million to $5.79 billion.

A Decision-Making Method for Design Schemes Based on Intuitionistic Fuzzy Sets and Prospect Theory

Conceptual design is a key link in the process of complex product design, and it is very important to select the appropriate design scheme; however, there are many types and inaccuracies of the evaluation data, and there is a problem of mutual influence between the evaluation criteria, which leads to unreliable decision making of the optimal solution. In order to solve this problem, a decision-making method based on intuitionistic fuzzy sets (IFS) and prospect theory is proposed. This method can be used for symmetric and asymmetric evaluation data. The evaluation data are classified according to different expression types and unified using intuitionistic fuzzy numbers. The intuitionistic fuzzy prospect value of decision information is calculated using prospect theory, and the prospect transformation of decision information is completed. At the same time, the Gray Relational Analysis (GRA) method and the Criteria Importance Though Intercriteria Correlation (CRITIC) method are used to calculate the subjective and objective weights of the technical and economic evaluation indexes of the product, and the combination weights are given; then, based on the evidence theory, the basic probability distribution of the evidence chain of all conceptual design schemes is synthesized, and the comprehensive prospect evaluation results of the schemes are obtained to complete the optimization of the conceptual design schemes. Finally, the effectiveness of the proposed method is verified by the conceptual design of the chip removal system of the deep hole machining machine tool. This work provides a promising method for decision makers to optimize the design scheme and provides insights into multi-objective decision-making problems.

Trade Openness, Digital Economy and Spatial Spillover ---An empirical study based on China's provincial panel data

Based on panel data of 31 provinces in China from year 2010 to 2020, this paper constructs a provincial digital economy evaluation index system to measure the digital economy development. Under the framework of static and dynamic spatial panel models, this paper empirically studies the spatial effects of China's provincial trade openness on the development of digital economy. The results show that China's provincial trade openness has obvious positive and spatial effects on the development of digital economy, and the local trade openness has a sustainable driving effect on its own digital development, but not sustainable for the neighboring region. Moreover, the influence of the eastern regional trade openness on the digital economy shows a spatial diffusion pattern in the short and long term, while that of the central and western regions shows a spatial siphon effect pattern.

Heat loss optimization and economic evaluation of a new fourth generation district heating triple pipe system

In response to the heat loss caused by the temperature difference between the heating pipes and external environment during the pipe transportation, heat contradiction between the total heat loss of the piping system and heat transfer between tubes, as well as economic balance between the cost of heat loss and cost of material loss. Based on TOTS (Two-supply/One-return, triple pipe structure) heat loss theory of the fourth-generation district heating system, this paper optimizes structure of pipes by setting dimensionless characteristic parameters θ and β. Finally, a mathematical model is proposed to calculate economic efficiency of pipeline network by considering the cost of initial construction material loss and operation heat loss of the pipe. Results show that, from energy perspective, comprehensive heat as system energy consumption evaluation index is positively correlated with θ, decreases first and then increases as β increases. Total heat loss of system dominates comprehensive heat. Lowest comprehensive heat of system is 18.12 w/m for θ of 0.1945 and β of 0.0739. From economic perspective, total system loss cost as system economic evaluation index is positively correlated with both θ and β. Total system heat loss cost dominates total system loss cost. Lowest total system loss cost is $29.39/m for θ of 0.1945 and β of 0.0509.

Can Data Elements Promote the High-Quality Development of China’s Economy?

In recent years, the digital economy, with data as the key production factor, has developed rapidly and become the driving force of China’s high-quality economic development. The relationship between data factors and high-quality economic development has gradually become a key topic of academic research. Based on the panel data of 30 provincial-level regions in China from 2014–2021, this study first constructs the proposed data factors and economic high-quality development evaluation indexes, respectively, by using the entropy weight method, and empirically analyzes whether data factors can promote economic high-quality development by using regression models. The results demonstrate the following: (1) Data elements play an important driving role in high-quality economic growth, and they have become an important engine for sustainable economic growth. (2) The development level of data elements has a stable growth rate and obvious regional differences, showing a pattern of “strong in the east and weak in the west, strong in the south and weak in the north”. (3) The degree of influence of data elements on different dimensions of high-quality economic development is inconsistent, with a greater influence on coordinated development, green development, and innovation development, while the effect on open development is not obvious. The above findings provide a reference and scientific basis for countries to formulate relevant policies to fully release the vitality of data elements and promote high-quality economic development.

The Dynamic Evolution of the Digital Economy and Its Impact on the Urban Green Innovation Development from the Perspective of Driving Force—Taking China’s Yangtze River Economic Belt Cities as an Example

The digital economy is an essential driving force supporting high-quality green development. Based on the panel data of cities in China’s Yangtze River from 2011 to 2020, this paper builds the digital economy evaluation index system from the five driving forces of market demand, information application, innovative development, industrial foundation, and the policy system. The Kernel density function, Moran index, and spatial econometric model are used to investigate the spatial and temporal evolution of the digital economy, as well as its driving effect and spatial effect on urban green innovation development. The results show that: (1) In China’s Yangtze River economic belt, the gap and the urban spatial dependence of the urban digital economy development are increasing; (2) The digital economy directly drives urban green innovation development, and also indirectly drives it by stimulating intra-city industrial structure upgrading and inter-city knowledge spillover, both of which have significant structural and regional differences; (3) Through the spatial spillover effect, it affects the urban green innovation development in its’ own city and in the surrounding ones, varying according to urban administrative levels and urban development types. The results provide a theoretical and practical reference for future policy formation to support high-quality green innovation development and fully utilize the driving force of the digital economy.

Spatial and temporal variation of economic resilience and its drivers: Evidence from Chinese cities

Based on panel data of 282 cities in China from 2005 to 2019, this paper constructs an economic resilience evaluation index system in three dimensions and applies the entropy value method to measure it. The two-stage nested Thiel index, kernel density estimation and geographic detector methods are also used to explore the characteristics of their spatial and temporal divergence and their driving factors. We find that the economic resilience of Chinese cities has increased rapidly over the sample period, but with significant spatial variation, with the intra-provincial variation being the main source of the overall variation. Without considering the spatial conditions, the economic resilience of cities has a strong stability. In the case of spatial conditions, spatial factors have a significant impact on cities with low economic resilience, but not on cities with high economic resilience. Differences in technological innovation capabilities are a key driver of spatial divergence in the economic resilience of Chinese cities. The interaction of any two factors enhances their respective effects on the spatial differentiation of economic resilience in Chinese cities. Based on the above findings, cities should actively explore targeted and differentiated ways to improve economic resilience based on their comparative advantages, accelerate the construction of a collaborative improvement mechanism for urban economic resilience, and support the collaborative improvement of urban economic resilience in China. Our findings provide a useful reference for promoting the concerted improvement of economic resilience in Chinese cities.

The analysis of enterprise economic benefit evaluation model based on network marketing

The comprehensive evaluation of enterprise economic benefits is the core content of enterprise diagnosis and has been the focus of domestic and foreign enterprise management circles. In thorough statistical evaluation, establishing a set of scientific and economic benefit index systems and evaluation methods is of great significance. This paper briefly introduces the design principles of the economic benefit evaluation index, analyzes the shortcomings and improvement measures of the current enterprise economic benefit evaluation system in China, and puts forward the indexes that should be added on the basis of the current index system. At the same time, the main methods for comprehensive evaluation of enterprise economic benefits are also proposed.

An auxiliary design system for industrial heat supply system considering carbon reduction benefit

Decarbonization of industrial process heating plays a crucial role in China’s carbon neutrality strategy. Traditionally, industrial users make decision on heat supply system design based solely on economy, with little regard for carbon emission. This study proposes an auxiliary design system to help the designers choosing proper industrial heating supply scheme considering carbon reduction benefit. Through traversal the existing scheme database, all feasible solutions are screen out and then evaluated by calculating an proposed comprehensive economy evaluation index. The comprehensive economy evaluation index takes carbon reduction as revenue since industry users will be able to trade their carbon emission rights at the carbon markets though CCER programs in the future. Future carbon price given by the carbon price prediction module is used to calculate the revenue user can get from carbon reduction. Grid emission factor prediction module makes prediction for changing grid emission factor, which is also involved in the evaluation to consider the benefit from continuously increasing green power in the future. A case study is given with heating demand data of a food factory to shown that the proposed method can reflect the value of carbon reduction, which helps to promote low-carbon technologies in the future.

A low-carbon optimization design method for building roof insulation using comprehensive economic analysis model and evaluation index

The building industry plays an important role in economic and social development, but it is also a major source of carbon emissions. However, to date, there is no mature design theory for low-carbon buildings. In this paper, a low-carbon optimization design method is presented for roof insulation using carbon emissions assessment method, comprehensive economic analysis model, and evaluation index. The traditional economic analysis model is extended to cope with carbon emissions of insulation, and a new comprehensiveeconomic analysis model is developed to evaluate economic performances of insulation. Moreover, a balanced index consisting of a carbon reduction factorand an additional economic inputs factor is proposed to assess carbon reduction of insulation. The validation results show that carbon emission cost can apparently improve economic performances of insulation. The economic benefits of insulation increase gradually with an increase in the service life. The ranking of balanced indexes of insulation in the low-temperature granary roof concerned is recycled EPS > recycled XPS > non-recycled EPS > non-recycled XPS > recycled RW > recycled PU > non-recycled RW > non-recycled PU. The low-carbon optimization design method presented can provide a useful tool in the low-carbon design of roof insulation in real buildings conveniently.

Heterogeneous Azeotropic Extractive Coupled Heat Pump Distillation for Triethylamine‐Dichloromethane‐Acetone‐Water

AbstractThere are three kinds of binary azeotropes and one kind of a near‐boiling compound with clamping zone characteristics in the triethylamine‐dichloromethane‐acetone‐water system, which belongs to complex quaternary systems. A four‐column distillation process of heterogeneous azeotropic extraction for the separation of the system was designed, simulated, and optimized to obtain more suitable process parameters and energy consumption distribution of each column. On this basis, taking the total annual cost (TAC) as the comprehensive economic evaluation index and CO2 emission as the environmental evaluation index, the thermal integration technology and mechanical vapor recompression (MVR) heat pump technology were applied to the energy‐saving research of the distillation process for the system. The results indicate that compared with the conventional four‐column heterogeneous azeotropic extractive distillation process, the thermal integration distillation process and single‐column MVR heat pump coupled thermal integration distillation process can save energy consumption and TAC, and it can reduce CO2 emission.