摘要：
The hydropower plays a key role in electricity system owing to its renewability and largest share of clean electricity generation that promotes sustainable development of national economy. Developing a proper forecasting model for the quarterly hydropower generation is crucial for associated energy sectors, which could assist policymakers in adjusting corresponding schemes for facing with sustained demands. For this purpose, this paper presents a fractional nonlinear grey Bernoulli model (abbreviated as FANGBM(1,1)) coupled seasonal factor and Particular Swarm Optimization (PSO) algorithm, namely PSO algorithm-based FASNGBM(1,1) model. In the proposed method, the moving average method that eliminates the seasonal fluctuations is introduced into FANGBM(1,1), then in which the structure parameters of FASNGBM(1,1) are determined by PSO. Based on hydropower generation of China from the first quarter of 2011 to the final quarter of 2018 (2011Q1-2018Q4), the numerical results show that the proposed model has a better performance than that of other benchmark models. Eventually, the quarterly hydropower generation of China from 2019 to 2020 are forecasted by the proposed model, according to results, the hydropower generation of China will reach 11287.14 x 10(8) Kwh in 2020.
摘要：
The discrete grey model is increasingly used in various real-world forecasting problems, however, in the modeling procedure, neglecting the effect of the time power and requiring the integer-order accumulation impair the prediction performance to some extent. Considering this fact, this paper implements the fractional accumulating generation operator and time power term in the discrete grey polynomial model, and as a consequence, a generalized discrete grey polynomial model, namely GDGMP(1,1,N,α), is proposed. To further improve the prediction accuracy, a metaheuristic algorithm, namely the quantum genetic algorithm (QGA), is applied to determine the emerging coefficients. In the presence of alternate emerging coefficients, the GDGMP(1,1,N,α) model is compatible with other existing grey models. To demonstrate the effectiveness of the newly proposed model, this model is employed to forecast three real cases (i.e., natural gas consumption, electricity consumption, and elderly population) by comparing it with other benchmark models. The experimental results show that among these competitive models, the proposed model achieves the best prediction performance, and its MAPE (often referred to as the core indicator) for natural gas consumption, electricity consumption, and the elderly population achieves values of 6.05%, 3.22%, and 0.66%, respectively, which are all lower than those of the other models, indicating that the proposed model outperforms other benchmarks.
摘要：
The hydroelectricity consumption of China is increasing, and hydropower exerts a crucial influence on sustained economic growth. A new method for estimating the hydroelectricity consumption of China is developed through the grey modeling technique. Taking into account the inherent error occurring in the leap from differential to difference in most existing grey serial models, this study constructs an unbiased NGBM(1,1) model based on the nonlinear grey Bernoulli model (NGBM(1,1)), which outperforms other grey benchmark models by adjusting the nonlinear parameter. The structural parameters of the model are deduced from the differential equation directly and therefore, the inherent error is eliminated. Moreover, the nonlinear parameter for the novel model is determined by Particle Swarm Optimization (PSO). Based on hydroelectricity consumption from 2010 to 2018, the novel model is built to predict its volume in the later one-quarter phase of the 13th Five Year Plan of China (2019-2020). The results show that hydroelectricity consumption maintains a continuous increase, exceeding 270 million tonnes oil equivalent (Mtoe) in 2020, while the growth rate decreases to 0.77%. In accordance with these forecasts, suggestions on associated hydropower are provided for policy-makers. (C) 2020 Elsevier Ltd. All rights reserved.
摘要：
This study aimed to quantify greenhouse gas emissions derived from the production-consumption of rice in Hubei-a major rice-producing province in central China. This research employed primary and secondary data collection methods. Primary data sources included interviews and experimental observations from seven counties in Hubei collected from June 2016 to December 2016. Secondary data sources-including national datasets, inter-governmental reports, and peer-reviewed articles-were used to extract relevant data, such as emission factors, and national and provincial rice output. Life Cycle Assessment was employed to build a comprehensive inventory and map of the rice carbon footprint, including the following five stages: production inputs, farm management, growth period, processing and sale, and consumption. Uncertainty analysis was performed to validate the reliability of carbon footprint estimations. Results showed that the carbon footprint for every 1 ton of polished rice in Hubei ranged between 4.19-6.81t CO(2)e/t and was 5.39t CO(2)e/t on average. Greenhouse gas emissions were primarily produced from rice fields during the growth stage (over 60% of greenhouse gas emissions of the whole life cycle of rice), followed by the consumption stage, and the production and transportation of agricultural inputs. Uncertainty analysis estimations indicated acceptable levels of reliability. This study's results indicate that the production and consumption of rice is a significant contributor to agricultural carbon emissions in Hubei-consistent with national estimates that place China as the largest carbon dioxide emitter globally. This research provides further insight into future policies and targeted initiatives for the efficient use of low-carbon agricultural inputs for rice production and consumption stages in China.
作者机构：
[Wang, Xinxin; Yu, Xing] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Zhang, Weiguo] South China Univ Technol, Sch Business Adm, Guangzhou 510640, Peoples R China.;[Li, Zijin] Univ Jinan, Business Sch, Jinan 250022, Peoples R China.
通讯机构：
[Xing Yu] S;School of Economics and Business Administration, Central China Normal University, Wuhan, China
摘要：
In this paper, we study the hedging effectiveness of crude oil futures on the basis of the lower partial moments (LPMs). An improved kernel density estimation method is proposed to estimate the optimal hedge ratio. We investigate crude oil price hedging by contributing to the literature in the following twofold: First, unlike the existing studies which focus on univariate kernel density method, we use bivariate kernel density to calculate the estimated LPMs, wherein the two bandwidths of the bivariate kernel density are not limited to the same, which is our main innovation point. According to the criterion of minimizing the mean integrated square error, we derive the conditions that the optimal bandwidths satisfy. In the process of derivation, we make a distribution assumption locally in order to simplify calculation, but this type of local distribution assumption is far better than global distribution assumption used in parameter method theoretically and empirically. Second, in order to meet the requirement of bivariate kernel density for independent random variables, we adopt ARCH models to obtain the independent noises with related to the returns of crude oil spot and futures. Genetic algorithm is used to tune the parameters that maximize quasi-likelihood. Empirical results reveal that, at first, the hedging strategy based on the improved kernel density estimation method is of highly efficiency, and then it achieves better performance than the hedging strategy based on the traditional parametric method. We also compare the risk control effectiveness of static hedge ratio vs. time-varying hedge ratio and find that static hedging has a better performance than time-varying hedging.
期刊：
Mathematical Problems in Engineering,2021年2021 ISSN：1024-123X
作者机构：
[Liu, Shuanghua; Feng, Ting] Baise Univ, Sch Math & Stat, Baise 533000, Peoples R China.;[Liu, Chong] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.;[Pang, Haodan] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Dong, Zijie] Hubei Univ, Fac Math & Stat, Wuhan 430062, Peoples R China.
摘要：
The living energy consumption of residents has become an important technical index to promote the economic and social development strategy. The country's medium- and short-term living energy consumption is featured with both a certainty of annual increment and an uncertainty of random variation. Thus, it can be seen as a typical grey system and shall be suitable for the grey prediction model. In order to explore the future development trend of China's per capita living energy consumption, this paper establishes a novel grey model based on the discrete grey model with time power term and the fractional accumulation (FDGM (1, 1, t(alpha)) for short) for forecasting China's per capita living energy consumption, which makes the existing model to adapt to different time series by adjusting fractional order accumulation parameter and power term. In order to verify the feasibility and effectiveness of the novel model, the proposed and eight other existing grey prediction models are applied to the case of China's per capita living energy consumption. The results show that the proposed model is more suitable for predicting China's per capita energy consumption than the other eight grey prediction models. Finally, the proposed model based on metabolism mechanism is used to predict China's per capita living energy consumption from 2018 to 2029, which can provide a reference for energy companies or government decision makers.
作者：
Liu, Chong;Wu, Wen-Ze;Xie, Wanli;Zhang, Tao;Zhang, Jun
期刊：
Energy Reports,2021年7:788-797 ISSN：2352-4847
通讯作者：
Wu, Wen-Ze(wenzew@mails.ccnu.edu.cn)
作者机构：
[Liu, Chong; Zhang, Jun] Inner Mongolia Agr Univ, Sch Sci, Hohhot 010018, Peoples R China.;[Wu, Wen-Ze] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Xie, Wanli] Nanjing Normal Univ, Inst EduInfo Sci & Engn, Nanjing 210097, Peoples R China.;[Zhang, Tao] Guangxi Univ Sci & Technol, Sch Sci, Liuzhou 545006, Peoples R China.
通讯机构：
[Wen-Ze Wu; Tao Zhang] S;School of Economics and Business Administration, Central China Normal University, Wuhan 430079, China<&wdkj&>School of Science, Guangxi University of Science and Technology, Liuzhou 545006, China
关键词：
Natural gas consumption;DFGM(1,1,t(alpha));Quantum Genetic Algorithm (QGA)
摘要：
Natural gas, an important low-carbon and clean energy, is increasingly replacing high-pollution sources such as coal and gasoline. Accurate natural gas consumption forecasts are important to policy makers in making plans, saving costs, and improving efficiency. This study developed a discrete fractional grey model with a time power term (denoted as DFGM(1,1,t(alpha))) with reference to the discretization technique. The new model is simplified, generalized, and overcomes existing model drawbacks. Moreover, the quantum genetic algorithm (QGA) is used to determine the new coefficients, namely, the fractional order and time-power coefficient. Based on observations from 2001 to 2018, the novel model predicted the natural gas consumption in China from 2019 to 2025 better than other benchmarks. Specifically, natural gas consumption was predicted to maintain a steady upward trend, reaching 315.30 billion cubic metres (hereinafter referred to as Bcm) in 2020 and 439.14 Bcm in 2025. Reasonable suggestions are put forward for associated sectors based on the forecasts. (C) 2021 The Author(s). Published by Elsevier Ltd.
摘要：
In China, filial piety, which usually refers to showing respect and obedience to parents, has exerted an important effect in the relationship between work stress and turnover intention. However, the mechanism behind this effect is still unclear. To address this gap in the existing literature, we developed and tested a moderated mediation model of the relationship that work stress shares with job satisfaction and turnover intention. In accordance with the dual filial piety model and the stress-moderation model, our hypothesized model predicted that the mediating effect of job satisfaction on the relationship between work stress and turnover intention would be moderated by reciprocal filial piety (RFP) and authoritarian filial piety (AFP). The analytic results of data that were obtained from 506 employees of manufacturing industries in China supported this model. Specifically, RFP and AFP, as a contextualized personality construct, positively moderated the direct relationship between work stress and turnover intention as well as the corresponding indirect effect through job satisfaction. In particular, RFP and AFP strengthened the positive effect of work stress on turnover intention. Based on these findings, recommendations to help employees fulfill their filial duties and reduce the effect of work stress on turnover intention among employees of Chinese manufacturing industries are delineated.
摘要：
Eco-innovation is the main driver of realizing the coordinated development of resource, environmental and economic systems. This paper measures regional eco-innovation efficiency (EIE) by using the Super-Slack Based Measure (SBM) model with undesirable outputs and distinguishes different agglomeration patterns based on Chinese data of 21 manufacturing sub-industries of 30 provinces. In particular, from the perspective of the dynamic evolution of manufacturing agglomeration, the nonlinear effects of specialized and diversified agglomeration on EIE are investigated based on panel threshold regression models. The results indicate that China's EIE shows a U-shaped changing trend. The impacts of specialized and diversified agglomeration on EIE are nonlinear and have significant three-threshold effects. There exist a U-shaped relationship between specialized agglomeration and EIE, and an S-shaped relationship between diversified agglomeration and EIE. In terms of eco-innovation, the development of diversified agglomeration is superior to that of specialized agglomeration. Overall, there is still much room for more than 70% of provinces in China to increase their EIE by optimizing the layout of manufacturing specialized and diversified agglomeration. To improve the EIE and achieve sustainable economic growth, differentiated agglomeration policies should be formulated in various stages and regions. In addition, the driving mechanism of eco-innovation should be strengthened.
摘要：
In recent years, the grey-based models with fractional accumulation have received extensive attention by scholars and have been widely used in various fields. However, the existing rough construction of the background value in the fractional grey model impairs its predictive performance to some extent. To address this problem, this paper reconstructs a dynamic background value for the fractional grey model by the composite integral median theorem, as a result, a novel fractional grey model-based variable background value (denoted as OFAGM(1,1) for short) is proposed. In particular, the Particle Swarm Optimization algorithm (PSO) is then employed to determine the optimum for the fractional order and the background value coefficients. Based on electricity consumption of two regions of China (i.e. Beijing, Inner Mongolia), the superiority of the proposed model has been verified in comparison with other benchmark models, the electricity consumption of Beijing is predicted to reach 1385.35×108 Kwh in 2022 and that of Inner Mongolia will reach 5063.39×108 Kwh in 2023. This study also takes the relative growth rate and the doubling time into account for these two regions that facilities comparison of the regions’ performance.
摘要：
A vast theoretical and empirical literature has been devoted to exploring the relationship between environmental regulation and total factor productivity (TFP), but no consensus has been reached and the reason may be attributed to the fact that the resource reallocation effect of environmental regulation is ignored. In this paper, we introduce resource misallocation in the process of discussing the impact of environmental regulation on TFP, taking China's provincial industrial panel data from 1997 to 2017 as a sample, and the spatial econometric method is employed to investigate whether environmental regulation has a resource reallocation effect and affects TFP. The results indicate that there is a U-shaped relationship between environmental regulation and industrial TFP and a negative spatial spillover effect of environmental regulation on industrial TFP at the provincial level in China. Both capital misallocation and labor misallocation will lead to the loss of industrial TFP. Capital misallocation has a negative spatial spillover effect on industrial TFP, while labor misallocation is just the opposite. Environmental regulation can produce a positive resource reallocation effect, which in turn promotes the industrial TFP in the range of 28% to 33%, while capital misallocation and labor misallocation are only partial mediator.
作者机构：
[Liu, Bing] Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;[Liu, Bing] Huainan Normal Univ, Sch Econ & Management, Huainan 232038, Peoples R China.
通讯机构：
[Liu, Bing] C;[Liu, Bing] H;Cent China Normal Univ, Sch Econ & Business Adm, Wuhan 430079, Peoples R China.;Huainan Normal Univ, Sch Econ & Management, Huainan 232038, Peoples R China.
期刊：
Mathematical Problems in Engineering,2020年2020 ISSN：1024-123X
通讯作者：
Zheng, Chengli
作者机构：
[Chen, Yan] Cent China Normal Univ, Sch Math & Statisct, Wuhan, Peoples R China.;[Zheng, Chengli; Cai, Ya] Cent China Normal Univ, Sch Econ & Business Adm, Financial Engn Res Ctr, Wuhan, Peoples R China.
通讯机构：
[Zheng, Chengli] C;Cent China Normal Univ, Sch Econ & Business Adm, Financial Engn Res Ctr, Wuhan, Peoples R China.
摘要：
Risk measures based on the trading option prices in the market are forward-looking, such as VIX. We propose a new method combining distorted lognormal distribution with interpolation to price options accurately and then estimate tail risk. Our method can price the option of any strikes between the maximum and the minimum value of strikes in the real market, which reduces the instability and inaccuracy of using the limited option to measure the risk. In addition, our novel method treats the underlying asset price as a stochastic indicator rather than a fixed indicator as described in previous research studies for risk measurement. Moreover, even if the available sample size is very small, we can measure the risk stably and precisely after interpolation. Finally, the empirical test results of SP500 market show that this method has good performance, especially for the option markets with sparse strikes.
关键词：
Remanufacturing;Contrast effect;Assimilation effect;Competition;Third party recycling platform
摘要：
In this paper, we consider a remanufacturing problem in a supply chain structure with two competing original equipment manufacturers (OEMs) and a third party platform collecting used products for the two OEMs to remanufacture. The two OEMs are of different extents of brand equity that consumers prefers one OEM over another. The OEMs provide new products to the same market and decide whether to remanufacture. If one OEM chooses to remanufacture and sells in the remanufactured market, the existence of his remanufactured products may weaken consumers' perceived value for his new products, but enhance that for his competitor's new products, as empirically revealed by Agrawal et al. (2015). We refer to the former as assimilation effect and the latter as contrast effect. We are interested to know, with the existence of assimilation effect and contrast effect, how would the competing OEMs decide their remanufacturing and pricing strategies. Also, when it's the third party recycling platform who collects used materials, how would she allocate used materials among competing OEMs, especially in the case that her operating budget is limited. Our findings show that how the assimilation effect and contrast effect affect the competing OEMs' pricing strategy differ under different remanufacturing scenarios. Interestingly, the platform may save up her energy and would not collect used products for the OEM with a weak brand equity to avoid fierce market competition. (C) 2020 Elsevier Ltd. All rights reserved.
