Special Issue "Decision Models in Green Growth and Sustainable Development"

A special issue of International Journal of Environmental Research and Public Health (ISSN 1660-4601). This special issue belongs to the section "Environmental Science and Engineering".

Deadline for manuscript submissions: closed (31 January 2018).

Special Issue Editors

Prof. Dr. Zaiwu Gong
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Guest Editor
Institute of management science and technology, College of economics and management, Nanjing University of Information Science and Technology, Nanjing 210044, China
Special Issues and Collections in MDPI journals
Prof. Dr. Kevin W. Li
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Guest Editor
Odette School of Business, University of Windsor, Windsor, ON N9B 3P4, Canada
Interests: logistics and supply chain management; conflict resolution; multicriteria decision analysis
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

The 2017 G20 Summit Leaders Declaration identifies “strong, sustainable, balanced, and inclusive growth” as the highest priority in the world. Consistent with what has been reached at previous summits, especially the 2016 Hangzhou Summit, the G20 leaders specify that taking actions to improve sustainability is one of the three key aims. It is clear from these summits that sustainable development has arisen as one of the most urging and critical challenges around the globe. It has been well recognized that broad public participation in the decision process plays a crucial role in achieving sustainable development. This Special Issue aims to address these concerns from a decision modeling perspective. We welcome theoretical and practical contributions to the understanding of decision making in green growth and sustainable development from a wide variety of angles. Specific topics include, but are not limited to, the following: Ecological, carbon, and water footprint, water rights, water security, marine economic security, integrated flooding control and risk management, disaster prevention and mitigation, environmental impact assessment and ecological compensation, green product design and remanufacturing, sustainable development and employment, assessment of sustainable development, sustainable operations and green supply chain management.

Prof. Dr. Kedong Yin
Prof. Dr. Zaiwu Gong
Prof. Dr. Yuhong Wang
Prof. Dr. Kevin W. Li
Guest Editor

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Environmental Research and Public Health is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Sustainable development
  • Decision models
  • Water footprint
  • Water rights
  • Water security
  • Marine economic security
  • Disaster prevention and mitigation
  • Green product design
  • Sustainable operations
  • Supply chain management

Published Papers (55 papers)

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Editorial

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Open AccessEditorial
Special Issue “Decision Models in Green Growth and Sustainable Development”
Int. J. Environ. Res. Public Health 2018, 15(6), 1093; https://doi.org/10.3390/ijerph15061093 - 28 May 2018
Cited by 2
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)

Research

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Open AccessArticle
Decision-Making and Environmental Implications under Cap-and-Trade and Take-Back Regulations
Int. J. Environ. Res. Public Health 2018, 15(4), 678; https://doi.org/10.3390/ijerph15040678 - 04 Apr 2018
Cited by 7
Abstract
To reduce carbon emissions during production and realize the recycling of resources, the government has promulgated carbon cap-and-trade regulation and take-back regulation separately. This paper firstly analyses the manufacturing, remanufacturing and collection decisions of a monopoly manufacturer under cap-and-trade regulation and take-back regulation [...] Read more.
To reduce carbon emissions during production and realize the recycling of resources, the government has promulgated carbon cap-and-trade regulation and take-back regulation separately. This paper firstly analyses the manufacturing, remanufacturing and collection decisions of a monopoly manufacturer under cap-and-trade regulation and take-back regulation conditions, and then explores the environmental impact (i.e., carbon emissions) of both carbon regulation and more stringent take-back regulation. Finally, numerical examples are provided to illustrate the theoretical results. The results indicate that it will do good for the environment once the cap-and-trade regulation is carried out. We also conclude that government’s supervision of carbon trading price plays an important role in reducing the environmental impact. Furthermore, unexpectedly, we prove that if emissions intensity of a remanufactured (vis-á-vis new) product is sufficiently high, the improvement of collection and remanufacturing targets might lead to the deterioration of environment. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Hesitant Fuzzy Linguistic Preference Utility Set and Its Application in Selection of Fire Rescue Plans
Int. J. Environ. Res. Public Health 2018, 15(4), 664; https://doi.org/10.3390/ijerph15040664 - 03 Apr 2018
Cited by 16
Abstract
Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities [...] Read more.
Hesitant fuzzy linguistic term set provides an effective tool to represent uncertain decision information. However, the semantics corresponding to the linguistic terms in it cannot accurately reflect the decision-makers’ subjective cognition. In general, different decision-makers’ sensitivities towards the semantics are different. Such sensitivities can be represented by the cumulative prospect theory value function. Inspired by this, we propose a linguistic scale function to transform the semantics corresponding to linguistic terms into the linguistic preference values. Furthermore, we propose the hesitant fuzzy linguistic preference utility set, based on which, the decision-makers can flexibly express their distinct semantics and obtain the decision results that are consistent with their cognition. For calculations and comparisons over the hesitant fuzzy linguistic preference utility sets, we introduce some distance measures and comparison laws. Afterwards, to apply the hesitant fuzzy linguistic preference utility sets in emergency management, we develop a method to obtain objective weights of attributes and then propose a hesitant fuzzy linguistic preference utility-TOPSIS method to select the best fire rescue plan. Finally, the validity of the proposed method is verified by some comparisons of the method with other two representative methods including the hesitant fuzzy linguistic-TOPSIS method and the hesitant fuzzy linguistic-VIKOR method. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Robust Economic Control Decision Method of Uncertain System on Urban Domestic Water Supply
Int. J. Environ. Res. Public Health 2018, 15(4), 649; https://doi.org/10.3390/ijerph15040649 - 31 Mar 2018
Cited by 3
Abstract
As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle [...] Read more.
As China quickly urbanizes, urban domestic water generally presents the circumstances of both rising tendency and seasonal cycle fluctuation. A robust economic control decision method for dynamic uncertain systems is proposed in this paper. It is developed based on the internal model principle and pole allocation method, and it is applied to an urban domestic water supply system with rising tendency and seasonal cycle fluctuation. To achieve this goal, first a multiplicative model is used to describe the urban domestic water demand. Then, a capital stock and a labor stock are selected as the state vector, and the investment and labor are designed as the control vector. Next, the compensator subsystem is devised in light of the internal model principle. Finally, by using the state feedback control strategy and pole allocation method, the multivariable robust economic control decision method is implemented. The implementation with this model can accomplish the urban domestic water supply control goal, with the robustness for the variation of parameters. The methodology presented in this study may be applied to the water management system in other parts of the world, provided all data used in this study are available. The robust control decision method in this paper is also applicable to deal with tracking control problems as well as stabilization control problems of other general dynamic uncertain systems. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Open AccessArticle
Evaluation of an Agricultural Meteorological Disaster Based on Multiple Criterion Decision Making and Evolutionary Algorithm
Int. J. Environ. Res. Public Health 2018, 15(4), 612; https://doi.org/10.3390/ijerph15040612 - 28 Mar 2018
Cited by 12
Abstract
The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete [...] Read more.
The evaluation of a meteorological disaster can be regarded as a multiple-criteria decision making problem because it involves many indexes. Firstly, a comprehensive indexing system for an agricultural meteorological disaster is proposed, which includes the disaster rate, the inundated rate, and the complete loss rate. Following this, the relative weights of the three criteria are acquired using a novel proposed evolutionary algorithm. The proposed algorithm consists of a differential evolution algorithm and an evolution strategy. Finally, a novel evaluation model, based on the proposed algorithm and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), is presented to estimate the agricultural meteorological disaster of 2008 in China. The geographic information system (GIS) technique is employed to depict the disaster. The experimental results demonstrated that the agricultural meteorological disaster of 2008 was very serious, especially in Hunan and Hubei provinces. Some useful suggestions are provided to relieve agriculture meteorological disasters. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Evaluation of Loss Due to Storm Surge Disasters in China Based on Econometric Model Groups
Int. J. Environ. Res. Public Health 2018, 15(4), 604; https://doi.org/10.3390/ijerph15040604 - 27 Mar 2018
Cited by 2
Abstract
Storm surge has become an important factor restricting the economic and social development of China’s coastal regions. In order to improve the scientific judgment of future storm surge damage, a method of model groups is proposed to refine the evaluation of the loss [...] Read more.
Storm surge has become an important factor restricting the economic and social development of China’s coastal regions. In order to improve the scientific judgment of future storm surge damage, a method of model groups is proposed to refine the evaluation of the loss due to storm surges. Due to the relative dispersion and poor regularity of the natural property data (login center air pressure, maximum wind speed, maximum storm water, super warning water level, etc.), storm surge disaster is divided based on eight kinds of storm surge disaster grade division methods combined with storm surge water, hypervigilance tide level, and disaster loss. The storm surge disaster loss measurement model groups consist of eight equations, and six major modules are constructed: storm surge disaster in agricultural loss, fishery loss, human resource loss, engineering facility loss, living facility loss, and direct economic loss. Finally, the support vector machine (SVM) model is used to evaluate the loss and the intra-sample prediction. It is indicated that the equations of the model groups can reflect in detail the relationship between the damage of storm surges and other related variables. Based on a comparison of the original value and the predicted value error, the model groups pass the test, providing scientific support and a decision basis for the early layout of disaster prevention and mitigation. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Modelling a Compensation Standard for a Regional Forest Ecosystem: A Case Study in Yanqing District, Beijing, China
Int. J. Environ. Res. Public Health 2018, 15(4), 565; https://doi.org/10.3390/ijerph15040565 - 21 Mar 2018
Cited by 8
Abstract
The assessment of forest ecosystem services can quantify the impact of these services on human life and is the main basis for formulating a standard of compensation for these services. Moreover, the calculation of the indirect value of forest ecosystem services should not [...] Read more.
The assessment of forest ecosystem services can quantify the impact of these services on human life and is the main basis for formulating a standard of compensation for these services. Moreover, the calculation of the indirect value of forest ecosystem services should not be ignored, as has been the case in some previous publications. A low compensation standard and the lack of a dynamic coordination mechanism are the main problems existing in compensation implementation. Using comparison and analysis, this paper employed accounting for both the costs and benefits of various alternatives. The analytic hierarchy process (AHP) method and the Pearl growth-curve method were used to adjust the results. This research analyzed the contribution of each service value from the aspects of forest produce services, ecology services, and society services. We also conducted separate accounting for cost and benefit, made a comparison of accounting and evaluation methods, and estimated the implementation period of the compensation standard. The main conclusions of this research include the fact that any compensation standard should be determined from the points of view of both benefit and cost in a region. The results presented here allow the range between the benefit and cost compensation to be laid out more reasonably. The practical implications of this research include the proposal that regional decision-makers should consider a dynamic compensation method to meet with the local economic level by using diversified ways to raise the compensation standard, and that compensation channels should offer a mixed mode involving both the market and government. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Prediction and Analysis of CO2 Emission in Chongqing for the Protection of Environment and Public Health
Int. J. Environ. Res. Public Health 2018, 15(3), 530; https://doi.org/10.3390/ijerph15030530 - 16 Mar 2018
Cited by 3
Abstract
Based on the consumption of fossil energy, the CO2 emissions of Chongqing are calculated and analyzed from 1997 to 2015 in this paper. Based on the calculation results, the consumption of fossil fuels and the corresponding CO2 emissions of Chongqing in [...] Read more.
Based on the consumption of fossil energy, the CO2 emissions of Chongqing are calculated and analyzed from 1997 to 2015 in this paper. Based on the calculation results, the consumption of fossil fuels and the corresponding CO2 emissions of Chongqing in 2020 are predicted, and the supporting data and corresponding policies are provided for the government of Chongqing to reach its goal as the economic unit of low-carbon emission in the ‘13th Five-Year Plan’. The results of the analysis show that there is a rapid decreasing trend of CO2 emissions in Chongqing during the ‘12th Five-Year Plan’, which are caused by the adjustment policy of the energy structure in Chongqing. Therefore, the analysis and prediction are primarily based on the adjustment of Chongqing’s coal energy consumption in this paper. At the initial stage, support vector regression (SVR) method is applied to predict the other fossil energy consumption and the corresponding CO2 emissions of Chongqing in 2020. Then, with the energy intensity of 2015 and the official target of CO2 intensity in 2020, the total fossil energy consumption and CO2 emissions of Chongqing in 2020 are predicted respectively. By the above results of calculation, the coal consumption and its corresponding CO2 emissions of Chongqing in 2020 are determined. To achieve the goal of CO2 emissions of Chongqing in 2020, the coal consumption level and energy intensity of Chongqing are calculated, and the adjustment strategies for energy consumption structure in Chongqing are proposed. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
The NLS-Based Nonlinear Grey Multivariate Model for Forecasting Pollutant Emissions in China
Int. J. Environ. Res. Public Health 2018, 15(3), 471; https://doi.org/10.3390/ijerph15030471 - 08 Mar 2018
Cited by 4
Abstract
The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) [...] Read more.
The relationship between pollutant discharge and economic growth has been a major research focus in environmental economics. To accurately estimate the nonlinear change law of China’s pollutant discharge with economic growth, this study establishes a transformed nonlinear grey multivariable (TNGM (1, N)) model based on the nonlinear least square (NLS) method. The Gauss–Seidel iterative algorithm was used to solve the parameters of the TNGM (1, N) model based on the NLS basic principle. This algorithm improves the precision of the model by continuous iteration and constantly approximating the optimal regression coefficient of the nonlinear model. In our empirical analysis, the traditional grey multivariate model GM (1, N) and the NLS-based TNGM (1, N) models were respectively adopted to forecast and analyze the relationship among wastewater discharge per capita (WDPC), and per capita emissions of SO2 and dust, alongside GDP per capita in China during the period 1996–2015. Results indicated that the NLS algorithm is able to effectively help the grey multivariable model identify the nonlinear relationship between pollutant discharge and economic growth. The results show that the NLS-based TNGM (1, N) model presents greater precision when forecasting WDPC, SO2 emissions and dust emissions per capita, compared to the traditional GM (1, N) model; WDPC indicates a growing tendency aligned with the growth of GDP, while the per capita emissions of SO2 and dust reduce accordingly. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection
Int. J. Environ. Res. Public Health 2018, 15(3), 446; https://doi.org/10.3390/ijerph15030446 - 03 Mar 2018
Cited by 6
Abstract
In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source [...] Read more.
In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Grey Language Hesitant Fuzzy Group Decision Making Method Based on Kernel and Grey Scale
Int. J. Environ. Res. Public Health 2018, 15(3), 436; https://doi.org/10.3390/ijerph15030436 - 02 Mar 2018
Cited by 2
Abstract
Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method [...] Read more.
Based on grey language multi-attribute group decision making, a kernel and grey scale scoring function is put forward according to the definition of grey language and the meaning of the kernel and grey scale. The function introduces grey scale into the decision-making method to avoid information distortion. This method is applied to the grey language hesitant fuzzy group decision making, and the grey correlation degree is used to sort the schemes. The effectiveness and practicability of the decision-making method are further verified by the industry chain sustainable development ability evaluation example of a circular economy. Moreover, its simplicity and feasibility are verified by comparing it with the traditional grey language decision-making method and the grey language hesitant fuzzy weighted arithmetic averaging ( G L H W A A ) operator integration method after determining the index weight based on the grey correlation. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Open AccessArticle
Investigation of a Brownfield Conflict Considering the Strength of Preferences
Int. J. Environ. Res. Public Health 2018, 15(2), 393; https://doi.org/10.3390/ijerph15020393 - 24 Feb 2018
Cited by 4
Abstract
By employing the Graph Model for Conflict Resolution methodology, this paper models and analyzes a brownfield conflict that occurred at the Changzhou Foreign Language School in Jiangsu, China, in 2016. This conflict made national headlines when news reports revealed that a large number [...] Read more.
By employing the Graph Model for Conflict Resolution methodology, this paper models and analyzes a brownfield conflict that occurred at the Changzhou Foreign Language School in Jiangsu, China, in 2016. This conflict made national headlines when news reports revealed that a large number of students and staff suffered from health issues after the school moved to a new site that is built on recently restored land adjacent to the original “Chang Long Chemical” block. Since stakeholders in the conflict hold different strengths of preference, a new option prioritization technique is employed to elicit both crisp preferences and the strength of preferences for the decision-makers (DMs) in the conflict. The conflict analysis result is consistent with the actual trajectory of the conflict and provides strategic insights into the conflict. More specifically, equilibrium results suggest that the firm should have been required to thoroughly clean the site, the local government should not have relocated the school, and the environmental agency and other stakeholders should have closely monitored the firm’s activities. In short, strategic insights garnered from this case study indicate that positive interactions should be fostered among the local government, the enterprise, and the public to ensure sustainable brownfield land redevelopment in the future. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
The Impacts of Regulations and Financial Development on the Operations of Supply Chains with Greenhouse Gas Emissions
Int. J. Environ. Res. Public Health 2018, 15(2), 378; https://doi.org/10.3390/ijerph15020378 - 22 Feb 2018
Cited by 3
Abstract
To establish a micro foundation to understand the impacts of greenhouse gas (GHG) emission regulations and financial development levels on firms’ GHG emissions, we build a two-stage dynamic game model to incorporate GHG emission regulations (in terms of an emission tax) and financial [...] Read more.
To establish a micro foundation to understand the impacts of greenhouse gas (GHG) emission regulations and financial development levels on firms’ GHG emissions, we build a two-stage dynamic game model to incorporate GHG emission regulations (in terms of an emission tax) and financial development (represented by the corresponding financing cost) into a two-echelon supply chain. With the subgame perfect equilibrium, we identify the conditions to determine whether an emission regulatory policy and/or financial development can affect GHG emissions in the supply chain. We also reveal the impacts of the strictness of GHG emission regulation, the financial development level, and the unit GHG emission rate on the operations of the supply chain and the corresponding profitability implications. Managerial insights are also discussed. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
The Impact of Sustainable Development Technology on a Small Economy—The Case of Energy-Saving Technology
Int. J. Environ. Res. Public Health 2018, 15(2), 295; https://doi.org/10.3390/ijerph15020295 - 08 Feb 2018
Cited by 2
Abstract
We investigated the impact of a sustainable development technology on the macroeconomic variables in a small economy utilizing a case study with a stochastically improving energy saving technology and a stochastically increasing energy price. The results show the technological displacement effects of energy [...] Read more.
We investigated the impact of a sustainable development technology on the macroeconomic variables in a small economy utilizing a case study with a stochastically improving energy saving technology and a stochastically increasing energy price. The results show the technological displacement effects of energy saving technology are stronger, but there are more ambiguous instantaneous returns to physical capital. However, the energy saving technology’s displacement effects might not affect the conditions under which the Harberger-Laursen-Metzler (HLM) effect holds. The effects of rising energy prices on bonds are stronger, and there are more ambiguous instantaneous returns, but the conditions under which the HLM effect holds are different. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Influential Effects of Intrinsic-Extrinsic Incentive Factors on Management Performance in New Energy Enterprises
Int. J. Environ. Res. Public Health 2018, 15(2), 292; https://doi.org/10.3390/ijerph15020292 - 08 Feb 2018
Cited by 4
Abstract
Background: New energy has become a key trend for global energy industry development. Talent plays a very critical role in the enhancement of new energy enterprise competitiveness. As a key component of talent, managers have been attracting more and more attention. The [...] Read more.
Background: New energy has become a key trend for global energy industry development. Talent plays a very critical role in the enhancement of new energy enterprise competitiveness. As a key component of talent, managers have been attracting more and more attention. The increase in job performance relies on, to a certain extent, incentive mechanism. Based on the Two-factor Theory, differences in influences and effects of different incentives on management performance have been checked in this paper from an empirical perspective. Methods: This paper selects the middle and low level managers in new energy enterprises as research samples and classifies the managers’ performance into task performance, contextual performance and innovation performance. It uses manager performance questionnaires and intrinsic-extrinsic incentive factor questionnaires to investigate and study the effects and then uses Amos software to analyze the inner link between the intrinsic-extrinsic incentives and job performance. Results: Extrinsic incentives affect task performance and innovation performance positively. Intrinsic incentives impose active significant effects on task performance, contextual performance, and innovation performance. The intrinsic incentive plays a more important role than the extrinsic incentive. Conclusions: Both the intrinsic-extrinsic incentives affect manager performance positively and the intrinsic incentive plays a more important role than the extrinsic incentive. Several suggestions to management should be given based on these results. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Stakeholders Opinions on Multi-Use Deep Water Offshore Platform in Hsiao-Liu-Chiu, Taiwan
Int. J. Environ. Res. Public Health 2018, 15(2), 281; https://doi.org/10.3390/ijerph15020281 - 06 Feb 2018
Cited by 2
Abstract
This paper describes a group model building activity designed to elicit the potential effects a projected multi-use deep water offshore platform may have on its local environment, including ecological and socio-economic issues. As such a platform is proposed for construction around the island [...] Read more.
This paper describes a group model building activity designed to elicit the potential effects a projected multi-use deep water offshore platform may have on its local environment, including ecological and socio-economic issues. As such a platform is proposed for construction around the island of Hsiao-Liu-Chiu, Taiwan, we organized several meetings with the local stakeholders and structured the debates using group modeling methods to promote consensus. During the process, the participants iteratively built and revised a causal-loop diagram that summarizes their opinions. Overall, local stakeholders concluded that a multi-use deep water offshore marine platform might have beneficial effects for Hsiao-Liu-Chiu because more tourists and fish could be attracted by the structure, but they also raised some potential problems regarding the law in Taiwan and the design of the offshore platform, especially its resistance to extreme weather. We report the method used and the main results and insights gained during the process. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Empirical Study on the Sustainability of China’s Grain Quality Improvement: The Role of Transportation, Labor, and Agricultural Machinery
Int. J. Environ. Res. Public Health 2018, 15(2), 271; https://doi.org/10.3390/ijerph15020271 - 05 Feb 2018
Cited by 3
Abstract
As a major part of farming sustainability, the issues of grain production and its quality improvement have been important in many countries. This paper aims to address these issues in China. Based on the data from the main production provinces and by applying [...] Read more.
As a major part of farming sustainability, the issues of grain production and its quality improvement have been important in many countries. This paper aims to address these issues in China. Based on the data from the main production provinces and by applying the stochastic frontier analysis methodology, we find that the improvement of transportation and the use of agricultural machinery have become the main driving forces for grain quality improvement in China. After further studying different provinces’ potentials of grain quality improvement, we show that grain quality has increased steadily. Therefore, we can conclude China’s grain quality improvement is indeed sustainable. Furthermore, different grains like rice, wheat, and corn share similar characteristics in terms of quality improvement, but the improvement rate for rice is relatively low, while those of corn and wheat are relatively high. Moreover, the overall change of efficiency gain of grain quality improvement is not significant for different provinces. The efficiency gains of the quality improvements for rice and wheat even decrease slightly. In addition, we find that only expanding grain quality improvement potential can simultaneously achieve the dual objectives of improving grain quality and increasing yield. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
The External Performance Appraisal of China Energy Regulation: An Empirical Study Using a TOPSIS Method Based on Entropy Weight and Mahalanobis Distance
Int. J. Environ. Res. Public Health 2018, 15(2), 236; https://doi.org/10.3390/ijerph15020236 - 30 Jan 2018
Cited by 8
Abstract
In China’s industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved [...] Read more.
In China’s industrialization process, the effective regulation of energy and environment can promote the positive externality of energy consumption while reducing negative externality, which is an important means for realizing the sustainable development of an economic society. The study puts forward an improved technique for order preference by similarity to an ideal solution based on entropy weight and Mahalanobis distance (briefly referred as E-M-TOPSIS). The performance of the approach was verified to be satisfactory. By separately using traditional and improved TOPSIS methods, the study carried out the empirical appraisals on the external performance of China’s energy regulation during 1999~2015. The results show that the correlation between the performance indexes causes the significant difference between the appraisal results of E-M-TOPSIS and traditional TOPSIS. The E-M-TOPSIS takes the correlation between indexes into account and generally softens the closeness degree compared with traditional TOPSIS. Moreover, it makes the relative closeness degree fluctuate within a small-amplitude. The results conform to the practical condition of China’s energy regulation and therefore the E-M-TOPSIS is favorably applicable for the external performance appraisal of energy regulation. Additionally, the external economic performance and social responsibility performance (including environmental and energy safety performances) based on the E-M-TOPSIS exhibit significantly different fluctuation trends. The external economic performance dramatically fluctuates with a larger fluctuation amplitude, while the social responsibility performance exhibits a relatively stable interval fluctuation. This indicates that compared to the social responsibility performance, the fluctuation of external economic performance is more sensitive to energy regulation. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Environmental Regulation, Foreign Direct Investment and Green Technological Progress—Evidence from Chinese Manufacturing Industries
Int. J. Environ. Res. Public Health 2018, 15(2), 221; https://doi.org/10.3390/ijerph15020221 - 29 Jan 2018
Cited by 10
Abstract
This study examines the spillover effects of foreign direct investment (FDI) on green technology progress rate (as measured by the green total factor productivity). The analysis utilizes two measures of FDI, labor-based FDI and capital-based FDI, and separately investigates four sets of industry [...] Read more.
This study examines the spillover effects of foreign direct investment (FDI) on green technology progress rate (as measured by the green total factor productivity). The analysis utilizes two measures of FDI, labor-based FDI and capital-based FDI, and separately investigates four sets of industry classifications—high/low discharge regulation and high/low emission standard regulation. The results indicate that in the low discharge regulation and low emission standard regulation industry, labor-based FDI has a significant negative spillover effect, and capital-based FDI has a significant positive spillover effect. However, in the high-intensity environmental regulation industry, the negative influence of labor-based FDI is completely restrained, and capital-based FDI continues to play a significant positive green technological spillover effects. These findings have clear policy implications: the government should be gradually reducing the labor-based FDI inflow or increasing stringency of environmental regulation in order to reduce or eliminate the negative spillover effect of the labor-based FDI. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Multiple Attribute Group Decision-Making Methods Based on Trapezoidal Fuzzy Two-Dimensional Linguistic Partitioned Bonferroni Mean Aggregation Operators
Int. J. Environ. Res. Public Health 2018, 15(2), 194; https://doi.org/10.3390/ijerph15020194 - 24 Jan 2018
Cited by 7
Abstract
In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic [...] Read more.
In this paper, we investigate multiple attribute group decision making (MAGDM) problems where decision makers represent their evaluation of alternatives by trapezoidal fuzzy two-dimensional uncertain linguistic variable. To begin with, we introduce the definition, properties, expectation, operational laws of trapezoidal fuzzy two-dimensional linguistic information. Then, to improve the accuracy of decision making in some case where there are a sort of interrelationship among the attributes, we analyze partition Bonferroni mean (PBM) operator in trapezoidal fuzzy two-dimensional variable environment and develop two operators: trapezoidal fuzzy two-dimensional linguistic partitioned Bonferroni mean (TF2DLPBM) aggregation operator and trapezoidal fuzzy two-dimensional linguistic weighted partitioned Bonferroni mean (TF2DLWPBM) aggregation operator. Furthermore, we develop a novel method to solve MAGDM problems based on TF2DLWPBM aggregation operator. Finally, a practical example is presented to illustrate the effectiveness of this method and analyses the impact of different parameters on the results of decision-making. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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The Sustainable Development Assessment of Reservoir Resettlement Based on a BP Neural Network
Int. J. Environ. Res. Public Health 2018, 15(1), 146; https://doi.org/10.3390/ijerph15010146 - 18 Jan 2018
Cited by 12
Abstract
Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir [...] Read more.
Resettlement affects not only the resettlers’ production activities and life but also, directly or indirectly, the normal operation of power stations, the sustainable development of the resettlers, and regional social stability. Therefore, a scientific evaluation index system for the sustainable development of reservoir resettlement must be established that fits Chinese national conditions and not only promotes reservoir resettlement research but also improves resettlement practice. This essay builds an evaluation index system for resettlers’ sustainable development based on a back-propagation (BP) neural network, which can be adopted in China, taking the resettlement necessitated by step hydropower stations along the Wujiang River cascade as an example. The assessment results show that the resettlement caused by step power stations along the Wujiang River is sustainable, and this evaluation supports the conclusion that national policies and regulations, which are undergoing constant improvement, and resettlement has increasingly improved. The results provide a reference for hydropower reservoir resettlement in developing countries. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Optimization of Location–Routing Problem for Cold Chain Logistics Considering Carbon Footprint
Int. J. Environ. Res. Public Health 2018, 15(1), 86; https://doi.org/10.3390/ijerph15010086 - 06 Jan 2018
Cited by 22
Abstract
In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics [...] Read more.
In order to solve the optimization problem of logistics distribution system for fresh food, this paper provides a low-carbon and environmental protection point of view, based on the characteristics of perishable products, and combines with the overall optimization idea of cold chain logistics distribution network, where the green and low-carbon location–routing problem (LRP) model in cold chain logistics is developed with the minimum total costs as the objective function, which includes carbon emission costs. A hybrid genetic algorithm with heuristic rules is designed to solve the model, and an example is used to verify the effectiveness of the algorithm. Furthermore, the simulation results obtained by a practical numerical example show the applicability of the model while provide green and environmentally friendly location-distribution schemes for the cold chain logistics enterprise. Finally, carbon tax policies are introduced to analyze the impact of carbon tax on the total costs and carbon emissions, which proves that carbon tax policy can effectively reduce carbon dioxide emissions in cold chain logistics network. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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On the Simulation-Based Reliability of Complex Emergency Logistics Networks in Post-Accident Rescues
Int. J. Environ. Res. Public Health 2018, 15(1), 79; https://doi.org/10.3390/ijerph15010079 - 06 Jan 2018
Cited by 7
Abstract
This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks’ statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics [...] Read more.
This paper investigates the reliability of complex emergency logistics networks, as reliability is crucial to reducing environmental and public health losses in post-accident emergency rescues. Such networks’ statistical characteristics are analyzed first. After the connected reliability and evaluation indices for complex emergency logistics networks are effectively defined, simulation analyses of network reliability are conducted under two different attack modes using a particular emergency logistics network as an example. The simulation analyses obtain the varying trends in emergency supply times and the ratio of effective nodes and validates the effects of network characteristics and different types of attacks on network reliability. The results demonstrate that this emergency logistics network is both a small-world and a scale-free network. When facing random attacks, the emergency logistics network steadily changes, whereas it is very fragile when facing selective attacks. Therefore, special attention should be paid to the protection of supply nodes and nodes with high connectivity. The simulation method provides a new tool for studying emergency logistics networks and a reference for similar studies. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Dynamic Impact of Online Word-of-Mouth and Advertising on Supply Chain Performance
Int. J. Environ. Res. Public Health 2018, 15(1), 69; https://doi.org/10.3390/ijerph15010069 - 04 Jan 2018
Cited by 6
Abstract
Cooperative (co-op) advertising investments benefit brand goodwill and further improve supply chain performance. Meanwhile, online word-of-mouth (OWOM) can also play an important role in supply chain performance. On the basis of co-op advertising, this paper considers a single supply chain structure led by [...] Read more.
Cooperative (co-op) advertising investments benefit brand goodwill and further improve supply chain performance. Meanwhile, online word-of-mouth (OWOM) can also play an important role in supply chain performance. On the basis of co-op advertising, this paper considers a single supply chain structure led by a manufacturer and examines a fundamental issue concerning the impact of OWOM on supply chain performance. Firstly, by the method of differential game, this paper analyzes the dynamic impact of OWOM and advertising on supply chain performance (i.e., brand goodwill, sales, and profits) under three different supply chain decisions (i.e., only advertising, and manufacturers with and without sharing cost of OWOM with retailers). We compare and analyze the optimal strategies of advertising and OWOM under the above different supply chain decisions. Secondly, the system dynamics model is established to reflect the dynamic impact of OWOM and advertising on supply chain performance. Finally, three supply chain decisions under two scenarios, strong brand and weak brand, are analyzed through the system dynamics simulation. The results show that the input of OWOM can enhance brand goodwill and improve earnings. It further promotes the OWOM reputation and improves the supply chain performance if manufacturers share the cost of OWOM with retailers. Then, in order to eliminate the retailers from word-of-mouth fraud and establish a fair competition mechanism, the third parties (i.e., regulators or e-commerce platforms) should take appropriate punitive measures against retailers. Furthermore, the effect of OWOM on supply chain performance under a strong brand differed from those under a weak brand. Last but not least, if OWOM is improved, there would be more remarkable performance for the weak brand than that for the strong brand in the supply chain. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Forecasting the Amount of Waste-Sewage Water Discharged into the Yangtze River Basin Based on the Optimal Fractional Order Grey Model
Int. J. Environ. Res. Public Health 2018, 15(1), 20; https://doi.org/10.3390/ijerph15010020 - 23 Dec 2017
Cited by 6
Abstract
With the rapid development of the Yangtze River economic belt, the amount of waste-sewage water discharged into the Yangtze River basin increases sharply year by year, which has impeded the sustainable development of the Yangtze River basin. The water security along the Yangtze [...] Read more.
With the rapid development of the Yangtze River economic belt, the amount of waste-sewage water discharged into the Yangtze River basin increases sharply year by year, which has impeded the sustainable development of the Yangtze River basin. The water security along the Yangtze River basin is very important for China, It is something aboutwater security of roughly one-third of China’s population and the sustainable development of the 19 provinces, municipalities and autonomous regions among the Yangtze River basin. Therefore, a scientific prediction of the amount of waste-sewage water discharged into Yangtze River basin has a positive significance on sustainable development of industry belt along with Yangtze River basin. This paper builds the fractional DWSGM(1,1)(DWSGM(1,1) model is short for Discharge amount of Waste Sewage Grey Model for one order equation and one variable) model based on the fractional accumulating generation operator and fractional reducing operator, and calculates the optimal order of “r” by using particle swarm optimization(PSO)algorithm for solving the minimum average relative simulation error. Meanwhile, the simulation performance of DWSGM(1,1)model with the optimal fractional order is tested by comparing the simulation results of grey prediction models with different orders. Finally, the optimal fractional order DWSGM(1,1)grey model is applied to predict the amount of waste-sewage water discharged into the Yangtze River basin, and corresponding countermeasures and suggestions are put forward through analyzing and comparing the prediction results. This paper has positive significance on enriching the fractional order modeling method of the grey system. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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The Effect of Environmental Regulation on Employment in Resource-Based Areas of China—An Empirical Research Based on the Mediating Effect Model
Int. J. Environ. Res. Public Health 2017, 14(12), 1598; https://doi.org/10.3390/ijerph14121598 - 19 Dec 2017
Cited by 7
Abstract
While environmental pollution is becoming more and more serious, many countries are adopting policies to control pollution. At the same time, the environmental regulation will inevitably affect economic and social development, especially employment growth. The environmental regulation will not only affect the scale [...] Read more.
While environmental pollution is becoming more and more serious, many countries are adopting policies to control pollution. At the same time, the environmental regulation will inevitably affect economic and social development, especially employment growth. The environmental regulation will not only affect the scale of employment directly, but it will also have indirect effects by stimulating upgrades in the industrial structure and in technological innovation. This paper examines the impact of environmental regulation on employment, using a mediating model based on the data from five typical resource-based provinces in China from 2000 to 2015. The estimation is performed based on the system GMM (Generalized Method of Moments) estimator. The results show that the implementation of environmental regulation in resource-based areas has both a direct effect and a mediating effect on employment. These findings provide policy implications for these resource-based areas to promote the coordinating development between the environment and employment. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Recycling Pricing and Coordination of WEEE Dual-Channel Closed-Loop Supply Chain Considering Consumers’ Bargaining
Int. J. Environ. Res. Public Health 2017, 14(12), 1578; https://doi.org/10.3390/ijerph14121578 - 15 Dec 2017
Cited by 14
Abstract
Environmentally friendly handling and efficient recycling of waste electrical on Waste Electrical and Electronic Equipment (WEEE) have grown to be a global social problem. As holders of WEEE, consumers have a significant effect on the recycling process. A consideration of and attention to [...] Read more.
Environmentally friendly handling and efficient recycling of waste electrical on Waste Electrical and Electronic Equipment (WEEE) have grown to be a global social problem. As holders of WEEE, consumers have a significant effect on the recycling process. A consideration of and attention to the influence of consumer behavior in the recycling process can help achieve more effective recycling of WEEE. In this paper, we built a dual-channel closed-loop supply chain model composed of manufacturers, retailers, and network recycling platforms. Based on the influence of customer bargaining behavior, we studied several different scenarios of centralized decision-making, decentralized decision-making, and contract coordination, using the Stackelberg game theory. The results show that retailers and network recycling platforms will reduce the direct recovery prices to maintain their own profit when considering the impact of consumer bargaining behavior, while remanufacturers will improve the transfer payment price for surrendering part of the profit under revenue and the expense sharing contract. Using this contract, we can achieve supply chain coordination and eliminate the effect of consumer bargaining behavior on supply chain performance. It can be viewed from the parameter sensitivity analysis that when we select the appropriate sharing coefficient, the closed-loop supply chain can achieve the same system performance under a centralized decision. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Environmental Concerns, Environmental Policy and Green Investment
Int. J. Environ. Res. Public Health 2017, 14(12), 1570; https://doi.org/10.3390/ijerph14121570 - 13 Dec 2017
Cited by 5
Abstract
Environmental regulators often use environmental policy to induce green investment by firms. However, if an environmental policy fails to exert a long-run effect on regulating the economic agents’ behavior, it may be more reasonable to think of the firm as the leader in [...] Read more.
Environmental regulators often use environmental policy to induce green investment by firms. However, if an environmental policy fails to exert a long-run effect on regulating the economic agents’ behavior, it may be more reasonable to think of the firm as the leader in the game, since the investment in green technology is usually a strategic decision. In this paper, we consider a three-stage Stackelberg game to address the interaction between a profit-maximizing firm (Stackelberg leader) facing emission-dependent demand, and the environmental regulator (Stackelberg follower). The firm decides on the green technology level in the first stage of the game based on its understanding of the regulator’s profits function, especially an environmental concern that is introduced as an exogenous variable. In the current research, we show that high levels of the regulator’s environmental concerns do not necessarily lead to the choice of green technology by the firm, and green investment level depends on the combined effects of the market and operational factors for a given level of the regulator’s environmental concerns. The result also shows that increasing environmental awareness amongst the consumers is an effective way to drive the firm’s green investment. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Non-Linear Relationship between Economic Growth and CO2 Emissions in China: An Empirical Study Based on Panel Smooth Transition Regression Models
Int. J. Environ. Res. Public Health 2017, 14(12), 1568; https://doi.org/10.3390/ijerph14121568 - 13 Dec 2017
Cited by 10
Abstract
The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) [...] Read more.
The non-linear relationship between provincial economic growth and carbon emissions is investigated by using panel smooth transition regression (PSTR) models. The research indicates that, on the condition of separately taking Gross Domestic Product per capita (GDPpc), energy structure (Es), and urbanisation level (Ul) as transition variables, three models all reject the null hypothesis of a linear relationship, i.e., a non-linear relationship exists. The results show that the three models all contain only one transition function but different numbers of location parameters. The model taking GDPpc as the transition variable has two location parameters, while the other two models separately considering Es and Ul as the transition variables both contain one location parameter. The three models applied in the study all favourably describe the non-linear relationship between economic growth and CO2 emissions in China. It also can be seen that the conversion rate of the influence of Ul on per capita CO2 emissions is significantly higher than those of GDPpc and Es on per capita CO2 emissions. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Open AccessArticle
The Multi-Attribute Group Decision-Making Method Based on Interval Grey Trapezoid Fuzzy Linguistic Variables
Int. J. Environ. Res. Public Health 2017, 14(12), 1561; https://doi.org/10.3390/ijerph14121561 - 13 Dec 2017
Cited by 6
Abstract
With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of [...] Read more.
With respect to multi-attribute group decision-making (MAGDM) problems, where attribute values take the form of interval grey trapezoid fuzzy linguistic variables (IGTFLVs) and the weights (including expert and attribute weight) are unknown, improved grey relational MAGDM methods are proposed. First, the concept of IGTFLV, the operational rules, the distance between IGTFLVs, and the projection formula between the two IGTFLV vectors are defined. Second, the expert weights are determined by using the maximum proximity method based on the projection values between the IGTFLV vectors. The attribute weights are determined by the maximum deviation method and the priorities of alternatives are determined by improved grey relational analysis. Finally, an example is given to prove the effectiveness of the proposed method and the flexibility of IGTFLV. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Open AccessArticle
Using Grey Relational Analysis to Evaluate Energy Consumption, CO2 Emissions and Growth Patterns in China’s Provincial Transportation Sectors
Int. J. Environ. Res. Public Health 2017, 14(12), 1536; https://doi.org/10.3390/ijerph14121536 - 08 Dec 2017
Cited by 8
Abstract
The transportation sector is a complex system. Collecting transportation activity and the associated emissions data is extremely expensive and time-consuming. Grey Relational Analysis provides a viable alternative to overcome data insufficiency and gives insights for decision makers into such a complex system. In [...] Read more.
The transportation sector is a complex system. Collecting transportation activity and the associated emissions data is extremely expensive and time-consuming. Grey Relational Analysis provides a viable alternative to overcome data insufficiency and gives insights for decision makers into such a complex system. In this paper, we achieved three major goals: (i) we explored the inter-relationships among transportation development, energy consumption and CO2 emissions for 30 provincial units in China; (ii) we identified the transportation development mode for each individual province; and (iii) we revealed policy implications regarding the sustainable transportation development at the provincial level. We can classify the 30 provinces into eight development modes according to the calculated Grey Relational Grades. Results also indicated that energy consumption has the largest influence on CO2 emission changes. Lastly, sustainable transportation policies were discussed at the province level according to the level of economy, urbanization and transportation energy structure. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Study on Spatial Spillover Effects of Logistics Industry Development for Economic Growth in the Yangtze River Delta City Cluster Based on Spatial Durbin Model
Int. J. Environ. Res. Public Health 2017, 14(12), 1508; https://doi.org/10.3390/ijerph14121508 - 04 Dec 2017
Cited by 5
Abstract
The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of [...] Read more.
The overall entropy method is used to evaluate the development level of the logistics industry in the city based on a mechanism analysis of the spillover effect of the development of the logistics industry on economic growth, according to the panel data of 26 cities in the Yangtze River delta. On this basis, the paper uses the spatial durbin model to study the direct impact of the development of the logistics industry on economic growth and the spatial spillover effect. The results show that the direct impact coefficient of the development of the logistics industry in the Yangtze River Delta urban agglomeration on local economic growth is 0.092, and the significant spatial spillover effect on the economic growth in the surrounding area is 0.197. Compared with the labor force input, capital investment and the degree of opening to the world, and government functions, the logistics industry’s direct impact coefficient is the largest, other than capital investment; the coefficient of the spillover effect is higher than other control variables, making it a “strong engine” of the Yangtze River Delta urban agglomeration economic growth. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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The Impact of Technological Progress in the Energy Sector on Carbon Emissions: An Empirical Analysis from China
Int. J. Environ. Res. Public Health 2017, 14(12), 1505; https://doi.org/10.3390/ijerph14121505 - 04 Dec 2017
Cited by 10
Abstract
This paper investigates the relationship between technological progress in the energy sector and carbon emissions based on the Environment Kuznets Curve (EKC) and data from China during the period of 1995–2012. Our study confirms that the situation in China conforms to the EKC [...] Read more.
This paper investigates the relationship between technological progress in the energy sector and carbon emissions based on the Environment Kuznets Curve (EKC) and data from China during the period of 1995–2012. Our study confirms that the situation in China conforms to the EKC hypothesis and presents the inverted U-curve relationship between per capita income and carbon emissions. Furthermore, the inflection point will be reached in at least five years. Then, we use research and development (R & D) investment in the energy industry as the quantitative indicator of its technological progress to test its impact on carbon emissions. Our results show that technological progress in the energy sector contributes to a reduction in carbon emissions with hysteresis. Furthermore, our results show that energy efficiency improvements are also helpful in reducing carbon emissions. However, climate policy and change in industrial structure increase carbon emissions to some extent. Our conclusion demonstrates that currently, China is not achieving economic growth and pollution reduction simultaneously. To further achieve the goal of carbon reduction, the government should increase investment in the energy industry research and improve energy efficiency. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Research and Development of a DNDC Online Model for Farmland Carbon Sequestration and GHG Emissions Mitigation in China
Int. J. Environ. Res. Public Health 2017, 14(12), 1493; https://doi.org/10.3390/ijerph14121493 - 01 Dec 2017
Cited by 3
Abstract
Appropriate agricultural practices for carbon sequestration and emission mitigation have a significant influence on global climate change. However, various agricultural practices on farmland carbon sequestration usually have a major impact on greenhouse gas (GHG) emissions. It is very important to accurately quantify the [...] Read more.
Appropriate agricultural practices for carbon sequestration and emission mitigation have a significant influence on global climate change. However, various agricultural practices on farmland carbon sequestration usually have a major impact on greenhouse gas (GHG) emissions. It is very important to accurately quantify the effect of agricultural practices. This study developed a platform—the Denitrification Decomposition (DNDC) online model—for simulating and evaluating the agricultural carbon sequestration and emission mitigation based on the scientific process of the DNDC model, which is widely used in the simulation of soil carbon and nitrogen dynamics. After testing the adaptability of the platform on two sampling fields, it turned out that the simulated values matched the measured values well for crop yields and GHG emissions. We used the platform to estimate the effect of three carbon sequestration practices in a sampling field: nitrogen fertilization reduction, straw residue and midseason drainage. The results indicated the following: (1) moderate decrement of the nitrogen fertilization in the sampling field was able to decrease the N2O emission while maintaining the paddy rice yield; (2) ground straw residue had almost no influence on paddy rice yield, but the CH4 emission and the surface SOC concentration increased along with the quantity of the straw residue; (3) compared to continuous flooding, midseason drainage would not decrease the paddy rice yield and could lead to a drop in CH4 emission. Thus, this study established the DNDC online model, which is able to serve as a reference and support for the study and evaluation of the effects of agricultural practices on agricultural carbon sequestration and GHG emissions mitigation in China. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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The Role of China in the UK Relative Imports from Three Selected Trading Regions: The Case of Textile Raw Material Industry
Int. J. Environ. Res. Public Health 2017, 14(12), 1481; https://doi.org/10.3390/ijerph14121481 - 30 Nov 2017
Cited by 3
Abstract
The UK textile industry was very prosperous in the past but in the 1970s Britain started to import textile materials from abroad. Since 1990, half of its textile materials have been imported from the EEA (European Economic Area), ASEAN (Association of Southeast Asian [...] Read more.
The UK textile industry was very prosperous in the past but in the 1970s Britain started to import textile materials from abroad. Since 1990, half of its textile materials have been imported from the EEA (European Economic Area), ASEAN (Association of Southeast Asian Nations) and North America countries. Meanwhile, UK imports from China have increased dramatically. Through comparisons, this paper calculates the trade competitiveness index and relative competitive advantages of regions and investigates the impact of Chinese textiles on UK imports from three key free trade regions across the textile sectors in the period 1990–2016 on the basis of United Nation Comtrade Rev. 3. We find that China’s textile prices, product techniques, political trade barriers and even tax system have made a varied impact on the UK’s imports across related sectors in the context of green trade and the strengthening of barriers, which helps us recognize China’s competitiveness in international trading and also provides advice on China’s sustainable development of textile exports. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Joint Decision-Making and the Coordination of a Sustainable Supply Chain in the Context of Carbon Tax Regulation and Fairness Concerns
Int. J. Environ. Res. Public Health 2017, 14(12), 1464; https://doi.org/10.3390/ijerph14121464 - 27 Nov 2017
Cited by 19
Abstract
Carbon tax regulation and consumers’ low-carbon preference act as incentives for firms to abate emissions. Manufacturers can improve product sustainability and retailers can strengthen the promotion of low-carbon products as part of such abatement. Current incomplete rationality also affects product sustainability and low-carbon [...] Read more.
Carbon tax regulation and consumers’ low-carbon preference act as incentives for firms to abate emissions. Manufacturers can improve product sustainability and retailers can strengthen the promotion of low-carbon products as part of such abatement. Current incomplete rationality also affects product sustainability and low-carbon promotion level. In this context, we consider a supply chain with a manufacturer and a retailer and investigate the impacts of the manufacturer’s and the retailer’s fairness concerns on their production sustainability level, low-carbon promotion level and profitability. We also explore the coordination contract. The results show that the manufacturer’s and the retailer’s fairness concerns decrease their product sustainability and low-carbon promotion level, together with the profits of the system and the manufacturer. With regard to the retailer’s fairness concern, the product sustainability level and the manufacturer’s profit are lower; moreover, the low-carbon promotion level and the profits of the supply chain and the retailer are higher. A revenue-sharing contract can coordinate the supply chain perfectly; however, members’ fairness concerns increase the difficulty of coordination. Finally, the numerical results reveal that carbon tax regulation can encourage the manufacturer to enhance the product sustainability level. Further, the impacts on the low-carbon promotion level and firms’ profitability are related to the cost coefficients of product sustainability. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Intuitionistic Linguistic Multiple Attribute Decision-Making with Induced Aggregation Operator and Its Application to Low Carbon Supplier Selection
Int. J. Environ. Res. Public Health 2017, 14(12), 1451; https://doi.org/10.3390/ijerph14121451 - 24 Nov 2017
Cited by 8
Abstract
The main focus of this paper is to investigate the multiple attribute decision making (MADM) method under intuitionistic linguistic (IL) environment, based on induced aggregation operators and analyze possibilities for its application in low carbon supplier selection. More specifically, a new aggregation operator, [...] Read more.
The main focus of this paper is to investigate the multiple attribute decision making (MADM) method under intuitionistic linguistic (IL) environment, based on induced aggregation operators and analyze possibilities for its application in low carbon supplier selection. More specifically, a new aggregation operator, called intuitionistic linguistic weighted induced ordered weighted averaging (ILWIOWA), is introduced to facilitate the IL information. Some of its desired properties are explored. A further generalization of the ILWIOWA, called intuitionistic linguistic generalized weighted induced ordered weighted averaging (ILGWIOWA), operator is developed. Furthermore, by employing the proposed operators, a MADM approach based on intuitionistic linguistic information is presented. Finally, an illustrative example concerning low carbon supplier selection and comparative analyses are conducted to demonstrate the effectiveness and practicality of the proposed approach. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
Open AccessArticle
Greenhouse Gas Emissions, Energy Consumption and Economic Growth: A Panel Cointegration Analysis for 16 Asian Countries
Int. J. Environ. Res. Public Health 2017, 14(11), 1436; https://doi.org/10.3390/ijerph14111436 - 22 Nov 2017
Cited by 17
Abstract
This research investigates the co-movement and causality relationships between greenhouse gas emissions, energy consumption and economic growth for 16 Asian countries over the period 1990–2012. The empirical findings suggest that in the long run, bidirectional Granger causality between energy consumption, GDP and greenhouse [...] Read more.
This research investigates the co-movement and causality relationships between greenhouse gas emissions, energy consumption and economic growth for 16 Asian countries over the period 1990–2012. The empirical findings suggest that in the long run, bidirectional Granger causality between energy consumption, GDP and greenhouse gas emissions and between GDP, greenhouse gas emissions and energy consumption is established. A non-linear, quadratic relationship is revealed between greenhouse gas emissions, energy consumption and economic growth, consistent with the environmental Kuznets curve for these 16 Asian countries and a subsample of the Asian new industrial economy. Short-run relationships are regionally specific across the Asian continent. From the viewpoint of energy policy in Asia, various governments support low-carbon or renewable energy use and are reducing fossil fuel combustion to sustain economic growth, but in some countries, evidence suggests that energy conservation might only be marginal. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Towards More Nuanced Classification of NGOs and Their Services to Improve Integrated Planning across Disaster Phases
Int. J. Environ. Res. Public Health 2017, 14(11), 1423; https://doi.org/10.3390/ijerph14111423 - 21 Nov 2017
Cited by 1
Abstract
Nongovernmental organizations (NGOs) are being integrated into U.S. strategies to expand the services that are available during health security threats like disasters. Identifying better ways to classify NGOs and their services could optimize disaster planning. We surveyed NGOs about the types of services [...] Read more.
Nongovernmental organizations (NGOs) are being integrated into U.S. strategies to expand the services that are available during health security threats like disasters. Identifying better ways to classify NGOs and their services could optimize disaster planning. We surveyed NGOs about the types of services they provided during different disaster phases. Survey responses were used to categorize NGO services as core—critical to fulfilling their organizational mission—or adaptive—services implemented during a disaster based on community need. We also classified NGOs as being core or adaptive types of organizations by calculating the percentage of each NGO’s services classified as core. Service types classified as core were mainly social services, while adaptive service types were those typically relied upon during disasters (e.g., warehousing, food services, etc.). In total, 120 NGOs were classified as core organizations, meaning they mainly provided the same services across disaster phases, while 100 NGOs were adaptive organizations, meaning their services changed. Adaptive NGOs were eight times more likely to report routinely participating in disaster planning as compared to core NGOs. One reason for this association may be that adaptive NGOs are more aware of the changing needs in their communities across disaster phases because of their involvement in disaster planning. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Dual Competing Photovoltaic Supply Chains: A Social Welfare Maximization Perspective
Int. J. Environ. Res. Public Health 2017, 14(11), 1416; https://doi.org/10.3390/ijerph14111416 - 20 Nov 2017
Cited by 4
Abstract
In the past decades, the inappropriate subsidy policies in many nations have caused problems such as serious oversupply, fierce competition and subpar social welfare in the photovoltaic (PV) industry in many nations. There is a clear shortage in the PV industry literature regarding [...] Read more.
In the past decades, the inappropriate subsidy policies in many nations have caused problems such as serious oversupply, fierce competition and subpar social welfare in the photovoltaic (PV) industry in many nations. There is a clear shortage in the PV industry literature regarding how dual supply chains compete and the key decision issues regarding the competition between dual PV supply chains. It is critical to develop effective subsidy policies for the competing PV supply chains to achieve social welfare maximization. This study has explored the dual PV supply chain competition under the Bertrand competition assumption by three game-theoretical modeling scenarios (or supply chain strategies) considering either the public subsidy or no subsidy from a social welfare maximization perspective. A numerical analysis complemented by two sensitivity analyses provides a better understanding of the pricing and quantity decision dynamics in the dual supply chains under three different supply chain strategies and the corresponding outcomes regarding the total supply chain profits, the social welfare and the required total subsidies. The key findings disclose that if there are public subsidies, the dual PV supply chains have the strongest intention to pursue the decentralized strategy to achieve their maximal returns rather than the centralized strategy that would achieve the maximal social welfare; however, the government would need to pay for the maximal subsidy budget. Thus, the best option for the government would be to encourage the dual PV supply chains to adopt a centralized strategy since this will not only maximize the social welfare but also, at the same time, minimize the public subsidy. With a smart subsidy policy, the PV industry can make the best use of the subsidy budget and grow in a sustainable way to support the highly demanded solar power generation in many countries trying very hard to increase the proportion of their clean energy to combat the global warming effect. Several subsidy policies such as shared solar energy arrangements and performance-based incentive (PBI) are proposed to integrate the market users and the PV supply chains. This study serves as a pioneering study into the dual PV supply chain research which is very limited in the PV management and policy study literature. The findings and several untended issues provide a foundation for the future PV supply chain studies. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Forecasting the Water Demand in Chongqing, China Using a Grey Prediction Model and Recommendations for the Sustainable Development of Urban Water Consumption
Int. J. Environ. Res. Public Health 2017, 14(11), 1386; https://doi.org/10.3390/ijerph14111386 - 15 Nov 2017
Cited by 5
Abstract
High accuracy in water demand predictions is an important basis for the rational allocation of city water resources and forms the basis for sustainable urban development. The shortage of water resources in Chongqing, the youngest central municipality in Southwest China, has significantly increased [...] Read more.
High accuracy in water demand predictions is an important basis for the rational allocation of city water resources and forms the basis for sustainable urban development. The shortage of water resources in Chongqing, the youngest central municipality in Southwest China, has significantly increased with the population growth and rapid economic development. In this paper, a new grey water-forecasting model (GWFM) was built based on the data characteristics of water consumption. The parameter estimation and error checking methods of the GWFM model were investigated. Then, the GWFM model was employed to simulate the water demands of Chongqing from 2009 to 2015 and forecast it in 2016. The simulation and prediction errors of the GWFM model was checked, and the results show the GWFM model exhibits better simulation and prediction precisions than those of the classical Grey Model with one variable and single order equation GM(1,1) for short and the frequently-used Discrete Grey Model with one variable and single order equation, DGM(1,1) for short. Finally, the water demand in Chongqing from 2017 to 2022 was forecasted, and some corresponding control measures and recommendations were provided based on the prediction results to ensure a viable water supply and promote the sustainable development of the Chongqing economy. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Pricing, Carbon Emission Reduction, Low-Carbon Promotion and Returning Decision in a Closed-Loop Supply Chain under Vertical and Horizontal Cooperation
Int. J. Environ. Res. Public Health 2017, 14(11), 1332; https://doi.org/10.3390/ijerph14111332 - 01 Nov 2017
Cited by 16
Abstract
In this paper, we examine the influences of vertical and horizontal cooperation models on the optimal decisions and performance of a low-carbon closed-loop supply chain (CLSC) with a manufacturer and two retailers, and study optimal operation in the competitive pricing, competitive the low-carbon [...] Read more.
In this paper, we examine the influences of vertical and horizontal cooperation models on the optimal decisions and performance of a low-carbon closed-loop supply chain (CLSC) with a manufacturer and two retailers, and study optimal operation in the competitive pricing, competitive the low-carbon promotion, the carbon emission reduction, the used-products collection and the profits. We consider the completely decentralized model, M-R vertical cooperation model, R-R horizontal cooperation model, M-R-R vertical and horizontal cooperation model and completely centralized model, and also identify the optimal decision results and profits. It can be observed from a systematic comparison and numerical analysis that the completely centralized model is best in all optimal decision results among all models. In semi-cooperation, the M-R vertical cooperation model is positive, the R-R horizontal cooperation model is passive, and the positivity of the M-R-R vertical and horizontal cooperation model decreases with competitive intensity increasing in the used-products returning, carbon emissions reduction level, low-carbon promotion effort and the profits of the manufacturer and the entire supply chain. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Research on Storm-Tide Disaster Losses in China Using a New Grey Relational Analysis Model with the Dispersion of Panel Data
Int. J. Environ. Res. Public Health 2017, 14(11), 1330; https://doi.org/10.3390/ijerph14111330 - 01 Nov 2017
Cited by 12
Abstract
Owing to the difference of the sequences’ orders and the surface structure in the current panel grey relational models, research results will not be unique. In addition, individual measurement of indicators and objects and the subjectivity of combined weight would significantly weaken the [...] Read more.
Owing to the difference of the sequences’ orders and the surface structure in the current panel grey relational models, research results will not be unique. In addition, individual measurement of indicators and objects and the subjectivity of combined weight would significantly weaken the effective information of panel data and reduce the reliability and accuracy of research results. Therefore, we propose the concept and calculation method of dispersion of panel data, establish the grey relational model based on dispersion of panel data (DPGRA), and prove that DPGRA exhibits the effective properties of uniqueness, symmetry, and normality. To demonstrate its applicability, the proposed DPGRA model is used to research on storm-tide disaster losses in China’s coastal areas. Comparing research results of three models, which are DPGRA, Euclidean distance grey relational model, and grey grid relational model, it was shown that DPGRA is more effective, feasible, and stable. It is indicated that DPGRA can entirely utilize the effective information of panel data; what’s more, it can not only handle the non-uniqueness of the grey relational model’s results but also improve the reliability and accuracy of research results. The research results are of great significance for coastal areas to focus on monitoring storm–tide disasters hazards, strengthen the protection measures of natural disasters, and improve the ability of disaster prevention and reduction. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
An Improved Graph Model for Conflict Resolution Based on Option Prioritization and Its Application
Int. J. Environ. Res. Public Health 2017, 14(11), 1311; https://doi.org/10.3390/ijerph14111311 - 27 Oct 2017
Cited by 5
Abstract
In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a [...] Read more.
In order to quantitatively depict differences regarding the preferences of decision makers for different states, a score function is proposed. As a foundation, coalition motivation and real-coalition analysis are discussed when external circumstance or opportunity costs are considering. On the basis of a confidence-level function, we establish the score function using a “preference tree”. We not only measure the preference for each state, but we also build a collation improvement function to measure coalition motivation and to construct a coordinate system in which to analyze real-coalition stability. All of these developments enhance the applicability of the graph model for conflict resolution (GMCR). Finally, an improved GMCR is applied in the “Changzhou Conflict” to demonstrate how it can be conveniently utilized in practice. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Water Pollution Prediction in the Three Gorges Reservoir Area and Countermeasures for Sustainable Development of the Water Environment
Int. J. Environ. Res. Public Health 2017, 14(11), 1307; https://doi.org/10.3390/ijerph14111307 - 27 Oct 2017
Cited by 2
Abstract
The Three Gorges Project was implemented in 1994 to promote sustainable water resource use and development of the water environment in the Three Gorges Reservoir Area (hereafter “Reservoir Area”). However, massive discharge of wastewater along the river threatens these goals; therefore, this study [...] Read more.
The Three Gorges Project was implemented in 1994 to promote sustainable water resource use and development of the water environment in the Three Gorges Reservoir Area (hereafter “Reservoir Area”). However, massive discharge of wastewater along the river threatens these goals; therefore, this study employs a grey prediction model (GM) to predict the annual emissions of primary pollution sources, including industrial wastewater, domestic wastewater, and oily and domestic wastewater from ships, that influence the Three Gorges Reservoir Area water environment. First, we optimize the initial values of a traditional GM (1,1) model, and build a new GM (1,1) model that minimizes the sum of squares of the relative simulation errors. Second, we use the new GM (1,1) model to simulate historical annual emissions data for the four pollution sources and thereby test the effectiveness of the model. Third, we predict the annual emissions of the four pollution sources in the Three Gorges Reservoir Area for a future period. The prediction results reveal the annual emission trends for the major wastewater types, and indicate the primary sources of water pollution in the Three Gorges Reservoir Area. Based on our predictions, we suggest several countermeasures against water pollution and towards the sustainable development of the water environment in the Three Gorges Reservoir Area. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Assessment of SIP Buildings for Sustainable Development in Rural China Using AHP-Grey Correlation Analysis
Int. J. Environ. Res. Public Health 2017, 14(11), 1292; https://doi.org/10.3390/ijerph14111292 - 25 Oct 2017
Cited by 5
Abstract
Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in [...] Read more.
Traditional rural residential construction has the problems of high energy consumption and severe pollution. In general, with sustainable development in the construction industry, rural residential construction should be aimed towards low energy consumption and low carbon emissions. To help achieve this objective, in this paper, we evaluated four different possible building structures using AHP-Grey Correlation Analysis, which consists of the Analytic Hierarchy Process (AHP) and the Grey Correlation Analysis. The four structures included the traditional and currently widely used brick and concrete structure, as well as structure insulated panels (SIPs). Comparing the performances of economic benefit and carbon emission, the conclusion that SIPs have the best overall performance can be obtained, providing a reference to help builders choose the most appropriate building structure in rural China. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
A Study of The Effect of Demand Uncertainty for Low-Carbon Products Using a Newsvendor Model
Int. J. Environ. Res. Public Health 2017, 14(11), 1276; https://doi.org/10.3390/ijerph14111276 - 25 Oct 2017
Cited by 3
Abstract
This paper studies the effect of uncertain demand on a low-carbon product by using a newsvendor model. With two different kinds of market scales, we examine a game whereby a manufacturer produces and delivers a single new low-carbon product to a single retailer. [...] Read more.
This paper studies the effect of uncertain demand on a low-carbon product by using a newsvendor model. With two different kinds of market scales, we examine a game whereby a manufacturer produces and delivers a single new low-carbon product to a single retailer. The retailer observes the demand information and gives an order before the selling season. We find in the game that if the retailer shares truthful (or in contrast unreal or even does not share) forecast information with the manufacturer, the manufacturer will give a low (high) wholesale price through the sequence of events. In addition, as a policy-maker, the government posts a subsidy by selling the low-carbon product per unit. The manufacturer creates a new contract with a rebate for the retailer. We also take the consumer aversion coefficient and truth coefficient as qualitative variables into our model to study the order, pricing, and expected profit for the members of supply chain. The research shows that uncertain demand causes a the major effect on the new low-carbon product. Thereby, we suggest the retailer should share more truthful information with the manufacturer. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China
Int. J. Environ. Res. Public Health 2017, 14(10), 1253; https://doi.org/10.3390/ijerph14101253 - 19 Oct 2017
Cited by 7
Abstract
Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are [...] Read more.
Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
To Facilitate or Curb? The Role of Financial Development in China’s Carbon Emissions Reduction Process: A Novel Approach
Int. J. Environ. Res. Public Health 2017, 14(10), 1222; https://doi.org/10.3390/ijerph14101222 - 13 Oct 2017
Cited by 11
Abstract
With the Paris Agreement coming into effect, China, as the largest CO2 emitter in the world, will be facing greater pressure to reduce its carbon emissions. This paper discusses how to solve this issue from the perspective of financial development in China. [...] Read more.
With the Paris Agreement coming into effect, China, as the largest CO2 emitter in the world, will be facing greater pressure to reduce its carbon emissions. This paper discusses how to solve this issue from the perspective of financial development in China. Although many studies have analyzed its impact on carbon emissions, the conclusions are contradictory. A major criticism of the existing studies is the reasonability of the selection of appropriate indicators and panel estimation techniques. Almost all studies use only one or limited indicators to represent the financial development and ignore the cross-sectional dependence. To fulfil the gaps mentioned above, a financial development index system is built, and with the framework of the STIRPAT (Stochastic impacts by regression on population, affluence, and technology) model, this paper applies an ARDL approach to investigating the long-run relationship between financial development and carbon emissions and a dynamic panel error-corrected model to capture the short-run impact. The empirical results show that financial development can improve carbon emissions, and such impact not only shows a regional difference but also reflects the features of stage differences. Additionally, based on the discussion on seven specific aspects of financial development, our findings can be helpful for policy makers to enact corresponding policies to realize the goal of reducing carbon emissions in China. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Regional Sustainable Development Analysis Based on Information Entropy—Sichuan Province as an Example
Int. J. Environ. Res. Public Health 2017, 14(10), 1219; https://doi.org/10.3390/ijerph14101219 - 13 Oct 2017
Cited by 6
Abstract
According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure [...] Read more.
According to the implementation of a scientific development perspective, sustainable development needs to consider regional development, economic and social development, and the harmonious development of society and nature, but regional sustainable development is often difficult to quantify. Through an analysis of the structure and functions of a regional system, this paper establishes an evaluation index system, which includes an economic subsystem, an ecological environmental subsystem and a social subsystem, to study regional sustainable development capacity. A sustainable development capacity measure model for Sichuan Province was established by applying the information entropy calculation principle and the Brusselator principle. Each subsystem and entropy change in a calendar year in Sichuan Province were analyzed to evaluate Sichuan Province’s sustainable development capacity. It was found that the established model could effectively show actual changes in sustainable development levels through the entropy change reaction system, at the same time this model could clearly demonstrate how those forty-six indicators from the three subsystems impact on the regional sustainable development, which could make up for the lack of sustainable development research. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Priority of a Hesitant Fuzzy Linguistic Preference Relation with a Normal Distribution in Meteorological Disaster Risk Assessment
Int. J. Environ. Res. Public Health 2017, 14(10), 1203; https://doi.org/10.3390/ijerph14101203 - 10 Oct 2017
Cited by 13
Abstract
As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In [...] Read more.
As meteorological disaster systems are large complex systems, disaster reduction programs must be based on risk analysis. Consequently, judgment by an expert based on his or her experience (also known as qualitative evaluation) is an important link in meteorological disaster risk assessment. In some complex and non-procedural meteorological disaster risk assessments, a hesitant fuzzy linguistic preference relation (HFLPR) is often used to deal with a situation in which experts may be hesitant while providing preference information of a pairwise comparison of alternatives, that is, the degree of preference of one alternative over another. This study explores hesitation from the perspective of statistical distributions, and obtains an optimal ranking of an HFLPR based on chance-restricted programming, which provides a new approach for hesitant fuzzy optimisation of decision-making in meteorological disaster risk assessments. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Modelling the Ozone-Based Treatments for Inactivation of Microorganisms
Int. J. Environ. Res. Public Health 2017, 14(10), 1196; https://doi.org/10.3390/ijerph14101196 - 09 Oct 2017
Cited by 7
Abstract
The paper presents the development of a model for ozone treatment in a dynamic bed of different microorganisms (Bacillus subtilis, B. cereus, B. pumilus, Escherichia coli, Pseudomonas fluorescens, Aspergillus niger, Eupenicillium cinnamopurpureum) on a heterogeneous [...] Read more.
The paper presents the development of a model for ozone treatment in a dynamic bed of different microorganisms (Bacillus subtilis, B. cereus, B. pumilus, Escherichia coli, Pseudomonas fluorescens, Aspergillus niger, Eupenicillium cinnamopurpureum) on a heterogeneous matrix (juniper berries, cardamom seeds) initially treated with numerous ozone doses during various contact times was studied. Taking into account various microorganism susceptibility to ozone, it was of great importance to develop a sufficiently effective ozone dose to preserve food products using different strains based on the microbial model. For this purpose, we have chosen the Weibull model to describe the survival curves of different microorganisms. Based on the results of microorganism survival modelling after ozone treatment and considering the least susceptible strains to ozone, we selected the critical ones. Among tested strains, those from genus Bacillus were recognized as the most critical strains. In particular, B. subtilis and B. pumilus possessed the highest resistance to ozone treatment because the time needed to achieve the lowest level of its survival was the longest (up to 17.04 min and 16.89 min for B. pumilus reduction on juniper berry and cardamom seed matrix, respectively). Ozone treatment allow inactivate microorganisms to achieving lower survival rates by ozone dose (20.0 g O3/m3 O2, with a flow rate of 0.4 L/min) and contact time (up to 20 min). The results demonstrated that a linear correlation between parameters p and k in Weibull distribution, providing an opportunity to calculate a fitted equation of the process. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Tackling Complex Emergency Response Solutions Evaluation Problems in Sustainable Development by Fuzzy Group Decision Making Approaches with Considering Decision Hesitancy and Prioritization among Assessing Criteria
Int. J. Environ. Res. Public Health 2017, 14(10), 1165; https://doi.org/10.3390/ijerph14101165 - 02 Oct 2017
Cited by 5
Abstract
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE [...] Read more.
In order to be prepared against potential balance-breaking risks affecting economic development, more and more countries have recognized emergency response solutions evaluation (ERSE) as an indispensable activity in their governance of sustainable development. Traditional multiple criteria group decision making (MCGDM) approaches to ERSE have been facing simultaneous challenging characteristics of decision hesitancy and prioritization relations among assessing criteria, due to the complexity in practical ERSE problems. Therefore, aiming at the special type of ERSE problems that hold the two characteristics, we investigate effective MCGDM approaches by hiring interval-valued dual hesitant fuzzy set (IVDHFS) to comprehensively depict decision hesitancy. To exploit decision information embedded in prioritization relations among criteria, we firstly define an fuzzy entropy measure for IVDHFS so that its derivative decision models can avoid potential information distortion in models based on classic IVDHFS distance measures with subjective supplementing mechanism; further, based on defined entropy measure, we develop two fundamental prioritized operators for IVDHFS by extending Yager’s prioritized operators. Furthermore, on the strength of above methods, we construct two hesitant fuzzy MCGDM approaches to tackle complex scenarios with or without known weights for decision makers, respectively. Finally, case studies have been conducted to show effectiveness and practicality of our proposed approaches. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessArticle
Linguistic Multi-Attribute Group Decision Making with Risk Preferences and Its Use in Low-Carbon Tourism Destination Selection
Int. J. Environ. Res. Public Health 2017, 14(9), 1078; https://doi.org/10.3390/ijerph14091078 - 17 Sep 2017
Cited by 9
Abstract
Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute [...] Read more.
Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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Open AccessFeature PaperArticle
On Consistency Test Method of Expert Opinion in Ecological Security Assessment
Int. J. Environ. Res. Public Health 2017, 14(9), 1012; https://doi.org/10.3390/ijerph14091012 - 04 Sep 2017
Cited by 2
Abstract
To reflect the initiative design and initiative of human security management and safety warning, ecological safety assessment is of great value. In the comprehensive evaluation of regional ecological security with the participation of experts, the expert’s individual judgment level, ability and the consistency [...] Read more.
To reflect the initiative design and initiative of human security management and safety warning, ecological safety assessment is of great value. In the comprehensive evaluation of regional ecological security with the participation of experts, the expert’s individual judgment level, ability and the consistency of the expert’s overall opinion will have a very important influence on the evaluation result. This paper studies the consistency measure and consensus measure based on the multiplicative and additive consistency property of fuzzy preference relation (FPR). We firstly propose the optimization methods to obtain the optimal multiplicative consistent and additively consistent FPRs of individual and group judgments, respectively. Then, we put forward a consistency measure by computing the distance between the original individual judgment and the optimal individual estimation, along with a consensus measure by computing the distance between the original collective judgment and the optimal collective estimation. In the end, we make a case study on ecological security for five cities. Result shows that the optimal FPRs are helpful in measuring the consistency degree of individual judgment and the consensus degree of collective judgment. Full article
(This article belongs to the Special Issue Decision Models in Green Growth and Sustainable Development)
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