Regional Economic Evaluation Research Articles

Regional economic assessment of a novel place-based model for sustainable food systems

Several actions from both the environmental and human viewpoints have already been made to meet the sustainability goals targeted at food systems. Still, new place-based ideas to improve sustainability are needed. Agroecological symbiosis (AES), a novel food system model, is an example of a suggested system-level change to attain sustainability targets; it is a symbiosis of food production and processing using renewable energy that uses its own feedstock. AES has already been found advantageous from the ecological and biophysical viewpoints, but a regional economic evaluation of the model is still lacking. Thus, the aim of our paper is to assess the regional economic impact of a possible systemic change in the food system using the network of agroecological symbiosis (NAES) as an example. We applied scenarios representing different ways of moving towards envisioned NAES models in Mäntsälä, Finland, and a computable general equilibrium model to evaluate the regional economic impact. According to our results, both regional economy and employment would increase, and the regional production base would diversify with NAES implementation applied to the region, but the extent of the benefits varies between scenarios. The scenario that includes change in both public and private food demand, production of bioenergy and utilization of by-products would cause the largest impacts. However, realizing NAES requires investments that may influence the actual implementation of such models. Nonetheless, a change towards NAES can promote an economically and spatially just transition to sustainability, as NAES seems to be economically most beneficial for rural areas.

Coupling Analysis of the Road-Network Spatiotemporal Distribution and the Economy in B&R Countries Based on GIS

The Belt and Road (B&R) is a new strategy and measure for China to extend its opening up. To explore the influence of the spatiotemporal distribution of the national road network along the B&R on economic growth, this paper adopts the subjective and objective integrated weighting method to build a regional economic evaluation model, a transportation network evaluation model, and an economy–transportation coupling coordination degree model (E-T model). We also quantitatively analyze and evaluate the coordinated development of the economy and transportation in the countries along the B&R. Our results show that: (1) There are some differences in the comprehensive scores of economic level and transportation network in different countries, and the B&R has promoted the general economic and transportation level of various countries. (2) Approximately 84% of the countries have not reached a good coordination level, and the regional differences are significant, which indicates that the overall economic and transportation coupling coordination needs to be improved. (3) In recent years, driven by the B&R, the coupling coordination of approximately 30% of the countries has improved significantly. Therefore, the B&R not only has a positive impact on the economy and transportation of countries along the belt but also plays an important role in coordinating the economic and transportation development of countries, which is of great strategic significance.

Evaluating the performance of LBSM data to estimate the gross domestic product of China at multiple scales: A comparison with NPP-VIIRS nighttime light data

Regional economic development evaluation is essential for understanding social and environmental issues. Although the nighttime light (NTL) data have been proved to be effective in economic estimation, it cannot reflect the human activities that occur during the daytime. Recently, with the widespread use of smart mobile devices, the location based social media (LBSM) data are increasingly being used as a proxy for real-time human activities. However, little work was carried out to explore the potential of LBSM data in estimating economic development at different scales in China. This study filled this gap by evaluating the effectiveness of Tencent user density (TUD) data, a typical type of LBSM data in China, in Gross Domestic Product (GDP) modeling at the provincial, municipal, and county scales. In this study, we employed holiday and non-holiday TUD sample data to simulate the annual TUD data, and compared it with the new generation NTL data, NPP/VIIRS images. The results showed that although the simulated annual TUD data does not perform better than NPP/VIIRS-NTL data in provincial and municipal GDP estimation, it outperforms NPP/VIIRS-NTL data at the county scale. More importantly, the simulated annual TUD data are much more powerful and reliable than NPP/VIIRS-NTL data in underdeveloped areas with complex terrain, such as the Northwest and Southwest China, as well as in more developed areas with separation of work and housing, such as the North China and South China. This is mainly because TUD data can reduce the impact of natural factors such as terrain on data collection as well as reflect both daytime and nighttime human activities. This study confirmed that the LBSM-TUD data is a potential and promising data source for economic modeling in small scale areas of China, which will help to support China's regional economic evaluation.

Analysis of regional economic evaluation based on machine learning

The regional economic evaluation and analysis has guiding significance for the subsequent economic strategy formulation. Due to the influence of various factors, the volatility of some current economic evaluation models is relatively large. According to the needs of regional economic evaluation, this study uses computer technology combined with regional economic development to build an economic development evaluation model to evaluate and analyze the regional economy. Through comparative analysis, this study selects the entropy weight-TOPSIS model as the comprehensive evaluation model of regional economy, uses the entropy weight method to determine the weight of each index, and then uses the TOPSIS method to conduct comprehensive evaluation. In addition, this study designs a control experiment to analyze the performance of this study model. Moreover, this study uses the model proposed in this study to conduct regional economic evaluation in recent years, and compares it with real data, and observes the test results with statistical charts and table data. The research results show that this research model has a certain effect, which can provide analytical tools for the follow-up economic strategy research and analysis.

Regional Economic Evaluation Based on a Novel Fuzzy Clustering Method in Big Data

Cloud computing, Internet of things, social networks and other new services make human society's data type and size increase at unprecedented rates. In order to analyze and make use of the huge data resources, the effective data analysis technique needed to be used. Thus, an optimized fuzzy clustering method GAPSO-FCM is proposed in this paper. The GA and PSO algorithm is adopted in order to overcome FCM be sensitive to initial value and noise problems and easy to fall into local minimum value. The combination of PSO and GA algorithm can partly solve the problem that is easy to appear premature phenomenon to PSO algorithm. It improves the global search ability by combining GAPSO algorithm and FCM algorithm. At last, the algorithm is used to analyze the comprehensive economic strength of cities in the Yangtze River Delta.

Regional Economic Evaluation on Soft Energy Path and Location of High Technology Industries

A new and widespread crisis resulting from the reduction in oil supply has made its impact not only upon regional energy demand but also on regional economic development. Hokkaido region of Japan has a heavy foreign and interregional trade deficit but an abundant potential of energy and also good prospects for regional development. We have estimated the foreign and interregional trade deficit by using Model Reference Adaptive Control Model, and the reduction of the foreign and interregional trade deficit of Hokkaido by the substitution of oil energy with soft energy utilization and by the location of high technology industries. As for the analytical results, the reductions in the foreign and interregional trade deficit of Hokkaido by the substitution oil energy with soft energy utilization and by the location of high technology industries have demonstrated a high level of success. Besides this, the economically direct and indirect impacts of alternative investments in the soft energy industrie have been estimated to be at high level in Hokkaido.