Sustainability

Research

274 KiB

Open AccessArticle

Impact of Energy Conservation and Emissions Reduction Policy Means Coordination on Economic Growth: Quantitative Evidence from China

by Guoxing Zhang, Zhenhua Zhang, Xiulin Gao, Lean Yu, Shouyang Wang and Yingluo Wang

Sustainability 2017, 9(5), 686; https://doi.org/10.3390/su9050686 - 26 Apr 2017

Cited by 13 | Viewed by 4454

Abstract

To understand the general relationship between Energy Conservation and Emissions Reduction (ECER) policy means coordination (PMC) and economic growth, this paper quantitatively investigates the impact on economic growth of differing PMCs. ECER policies from 1978 to 2013 in China are quantified across two [...] Read more.

To understand the general relationship between Energy Conservation and Emissions Reduction (ECER) policy means coordination (PMC) and economic growth, this paper quantitatively investigates the impact on economic growth of differing PMCs. ECER policies from 1978 to 2013 in China are quantified across two dimensions of policy power and policy means, and then, PMC degrees are designed as independent variables and incorporated into a modified Cobb−Douglas production model. While determining the cointegration relationships by using a unit root test, a cointegration test and a stability test, cointegration equation is conducted by using quantitative data to explore the economic growth effects of PMC in China. The government’s use of PMC in China is also analyzed and ranked. The empirical results show that there is a long-term cointegration relationship among the variables from 1978 to 2013. Additionally, the effects of the different PMCs on economic growth show significant discrepancies and each PMC usage ranking is also found to be significantly different, thereby implying that the use of different PMCs by the Chinese government needs to be further perfected. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

3043 KiB

Open AccessArticle

A Framework of Sustainable Service Supply Chain Management: A Literature Review and Research Agenda

by Weihua Liu, Enze Bai, Liwei Liu and Wanying Wei

Sustainability 2017, 9(3), 421; https://doi.org/10.3390/su9030421 - 12 Mar 2017

Cited by 90 | Viewed by 29237

Abstract

In recent years, the interdisciplinary research of supply chains and sustainability has received extensive, yet gradual, attention; when compared to the rapid economic growth of the service industry, however, sustainable supply chain management has not been systematically explored yet. It has not only [...] Read more.

In recent years, the interdisciplinary research of supply chains and sustainability has received extensive, yet gradual, attention; when compared to the rapid economic growth of the service industry, however, sustainable supply chain management has not been systematically explored yet. It has not only great theoretical significance, but also positive practical significance to provide a framework for the operation of a sustainable service supply chain from a sustainable development point of view. Based on the triple bottom line (TBL), we have analyzed related sustainable supply chain management research between 2006 and 2015, reviewed papers involving two or three bottom lines as well, and then introduced some classical frameworks for manufacturing supply chain management and service supply chain management. Afterward, by analyzing the differences between the manufacturing and service industries, we propose a framework of sustainable service supply chain management (SSSCM). Based on the impacts of sustainable development TBL on service supply chain participants, we have finally made a framework for sustainable operation facing triads service supply chain and proposed a future research agenda. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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1485 KiB

Open AccessArticle

An Evaluation of the Low-Carbon Effects of Urban Rail Based on Mode Shifts

by Feng Chen, Xiaopeng Shen, Zijia Wang and Yang Yang

Sustainability 2017, 9(3), 401; https://doi.org/10.3390/su9030401 - 8 Mar 2017

Cited by 26 | Viewed by 5279

Abstract

Urban rail is widely considered to be a form of low-carbon green transportation, but there is a lack of specific quantitative research to support this. By comparing the mode, distance, and corresponding energy consumption of residents before and after the opening of rail [...] Read more.

Urban rail is widely considered to be a form of low-carbon green transportation, but there is a lack of specific quantitative research to support this. By comparing the mode, distance, and corresponding energy consumption of residents before and after the opening of rail transit, this paper establishes a carbon reduction method for rail transit. A measurement model takes the passenger carbon emissions before the line is opened as the baseline and compares them with the standard after the opening, determining the carbon emissions reduction. The model requires a combination of a large amount of research data, transit smart card data, and GIS network measurement tools as measured data and parameters. The model is then applied to rail transit lines that have opened in Beijing in recent years. The emissions reductions of four different routes are estimated and the carbon emissions reduction effect of rail transit is evaluated. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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583 KiB

Open AccessArticle

Low Carbon-Oriented Optimal Reliability Design with Interval Product Failure Analysis and Grey Correlation Analysis

by Yixiong Feng, Zhaoxi Hong, Jin Cheng, Likai Jia and Jianrong Tan

Sustainability 2017, 9(3), 369; https://doi.org/10.3390/su9030369 - 4 Mar 2017

Cited by 13 | Viewed by 4468

Abstract

The problem of large amounts of carbon emissions causes wide concern across the world, and it has become a serious threat to the sustainable development of the manufacturing industry. The intensive research into technologies and methodologies for green product design has significant theoretical [...] Read more.

The problem of large amounts of carbon emissions causes wide concern across the world, and it has become a serious threat to the sustainable development of the manufacturing industry. The intensive research into technologies and methodologies for green product design has significant theoretical meaning and practical value in reducing the emissions of the manufacturing industry. Therefore, a low carbon-oriented product reliability optimal design model is proposed in this paper: (1) The related expert evaluation information was prepared in interval numbers; (2) An improved product failure analysis considering the uncertain carbon emissions of the subsystem was performed to obtain the subsystem weight taking the carbon emissions into consideration. The interval grey correlation analysis was conducted to obtain the subsystem weight taking the uncertain correlations inside the product into consideration. Using the above two kinds of subsystem weights and different caution indicators of the decision maker, a series of product reliability design schemes is available; (3) The interval-valued intuitionistic fuzzy sets (IVIFSs) were employed to select the optimal reliability and optimal design scheme based on three attributes, namely, low carbon, correlation and functions, and economic cost. The case study of a vertical CNC lathe proves the superiority and rationality of the proposed method. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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676 KiB

Open AccessArticle

Sustainability Analysis and Buy-Back Coordination in a Fashion Supply Chain with Price Competition and Demand Uncertainty

by Fan Wang, Xiaopo Zhuo and Baozhuang Niu

Sustainability 2017, 9(1), 25; https://doi.org/10.3390/su9010025 - 26 Dec 2016

Cited by 25 | Viewed by 6367

Abstract

Supply chain sustainability has become significantly important in the fashion industry, and more and more fashion brands have invested in developing sustainable supply chains. We note that dual channel system comprising a brand-owned direct channel and retail outsourcing channel is quite common in [...] Read more.

Supply chain sustainability has become significantly important in the fashion industry, and more and more fashion brands have invested in developing sustainable supply chains. We note that dual channel system comprising a brand-owned direct channel and retail outsourcing channel is quite common in the fashion industry, and in the latter, buy-back contract is popular between brands and retailers. Therefore, we build a stylized dual channel model with price competition and demand uncertainty to characterize the main properties of a fashion supply chain. Our foci are the sustainability analysis and the channel coordination mechanism. We first design a buy-back contract with return cost to coordinate the channel. We then study supply chain sustainability and examine the effect of two key influencing factors, i.e., price competition and demand uncertainty. Interestingly, we find that a fiercer price competition will lead to a more sustainable supply chain. From the perspective of supply chain managers, we conclude that (1) if managers care about environmental sustainability, fierce price competition is not a suggested strategy; (2) if managers care about economic sustainability, fierce price competition is an advantageous strategy. We also find that high demand uncertainty results in a less sustainable supply chain, in both an environmental and economic sustainability sense. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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1021 KiB

Open AccessArticle

Natural Gas Consumption of Emerging Economies in the Industrialization Process

by Jian Chai, Ting Liang, Xiaoyang Zhou, Yunxiao Ye, Limin Xing and Kin Keung Lai

Sustainability 2016, 8(11), 1089; https://doi.org/10.3390/su8111089 - 25 Oct 2016

Cited by 9 | Viewed by 5248

Abstract

Natural gas has become more and more important in the world energy market with the change of energy consumption structure and consumption subjects. This paper applies the panel smooth transition regression (PSTR) model to study the nonlinear relationship between natural gas consumption and [...] Read more.

Natural gas has become more and more important in the world energy market with the change of energy consumption structure and consumption subjects. This paper applies the panel smooth transition regression (PSTR) model to study the nonlinear relationship between natural gas consumption and economic variables of emerging economies, and the empirical results show that: (1) There is a non-linear relationship among natural gas consumption, GDP per capita, industrialization and urbanization rate; (2) The optimal PSTR model is a two-regime model by using the lagged industrialization as a transition variable, and the impact of GDP per capita and of industrialization on natural gas consumption shows incomplete symmetry in low and high regime, respectively; (3) The result of time-varying elasticity analysis indicates that natural gas consumption is inelastic to GDP per capita, but elastic to both industrialization and urbanization. The elasticity of GDP per capita generally decrease with fluctuation, the elasticity of industrialization tends to rise, and the elasticity of urbanization is linear at high level; (4) Regional difference shows that there are 10 emerging economies are in first regime (below industrialization of 43.2%), and the remaining 6 are in second regime. This provides reference for countries in different transformation periods to make economic policies adapting to energy saving, energy structure optimization and other sustainable development strategies. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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2287 KiB

Open AccessArticle

The Non-Linear Effect of Chinese Financial Developments on Energy Supply Structures

by Jian Chai, Limin Xing, Quanying Lu, Ting Liang, Kin Keung Lai and Shouyang Wang

Sustainability 2016, 8(10), 1021; https://doi.org/10.3390/su8101021 - 13 Oct 2016

Cited by 3 | Viewed by 4466

Abstract

Currently, oversupply coal and coal-based power in China poses a great challenge to energy structure optimization and emissions reduction. The energy industry, however, is closely linked to the financial sector. In view of this, using a non-linear Panel Smooth Transition Regression (PSTR) model, [...] Read more.

Currently, oversupply coal and coal-based power in China poses a great challenge to energy structure optimization and emissions reduction. The energy industry, however, is closely linked to the financial sector. In view of this, using a non-linear Panel Smooth Transition Regression (PSTR) model, this paper examines the threshold effects of financial developments on energy supply structures for 17 energy supply provinces in China observed over 2000–2014. The main results are: (1) The ratio of coal supply (LCSR) specification is seen to be a four-regime PSTR model with added value in the financial industry/GDP (LFIR) as the threshold variable. The LFIR and LCSR show a positive correlation, and the elastic coefficients change between 0.02 and ~0.085; the impact of financial institutions’ loan balance/GDP (LLAN) on LCSR takes on an inverse U-shaped curve: first positive, then negative, and again positive with the financial crisis in 2008 as the turning point; (2) The ratio of thermal power generation (LTPG) specification is seen to be a two-regime PSTR model with investment in the coal industry/GDP (LCIR) as the threshold variable. Results show that LFIR has a negative effect on LTPG, and the coefficients in the low regime tend to be 0.344%, then gradually decrease to 0.051% in the high regime. The influence of LLAN on the LTPG is positive before and negative after the financial crisis. The influence of the foreign direct investment GDP proportion (LFDI, the degree of financial openness) on the LCSR and LTPG both remain negative. Therefore, in the process of formulating energy conservation policies and adjusting energy-intensive industrial structures, the government should fully consider the effect of financial developments. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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1182 KiB

Open AccessArticle

Low-Carbon Based Multi-Objective Bi-Level Power Dispatching under Uncertainty

by Xiaoyang Zhou, Canhui Zhao, Jian Chai, Benjamin Lev and Kin Keung Lai

Sustainability 2016, 8(6), 533; https://doi.org/10.3390/su8060533 - 4 Jun 2016

Cited by 12 | Viewed by 5375

Abstract

This research examines a low-carbon power dispatch problem under uncertainty. A hybrid uncertain multi-objective bi-level model with one leader and multiple followers is established to support the decision making of power dispatch and generation. The upper level decision maker is the regional power [...] Read more.

This research examines a low-carbon power dispatch problem under uncertainty. A hybrid uncertain multi-objective bi-level model with one leader and multiple followers is established to support the decision making of power dispatch and generation. The upper level decision maker is the regional power grid corporation which allocates power quotas to each follower based on the objectives of reasonable returns, a small power surplus and low carbon emissions. The lower level decision makers are the power generation groups which decide on their respective power generation plans and prices to ensure the highest total revenue under consideration of government subsidies, environmental costs and the carbon trading. Random and fuzzy variables are adopted to describe the uncertain factors and chance constrained and expected value programming are used to handle the hybrid uncertain model. The bi-level models are then transformed into solvable single level models using a satisfaction method. Finally, a detailed case study and comparative analyses are presented to test the proposed models and approaches to validate the effectiveness and illustrate the advantages. Full article

(This article belongs to the Special Issue Low Carbon Development for Emerging Markets)

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