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Special Issue "Transition from China-Made to China-Innovation "

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: 1 December 2018

Special Issue Editors

Guest Editor
Dr. Jeffrey Yi-Lin Forrest

School of Business, Pennsylvania State System of Higher Education (Slippery Rock campus), USA
E-Mail
Interests: industrial revolution; investment; market dynamics; systems research; uncertainty
Guest Editor
Dr. Zaiwu Gong

Institute of management science and technology, College of economics and management, Nanjing University of Information Science and Technology, Nanjing, Jiangsu 210044, China
E-Mail

Special Issue Information

Dear Colleagues,

China has been the largest manufacturing nation in the world, but not the strongest nation. Currently, China faces internal pressures such as economic downturn, insufficient scientific and technological innovation, low energy efficiency, serious environmental pollution, rising labor costs, and others. At the same time, the strategy of re-industrializing traditional manufacturing power, as well as external competition squeeze such as much lower costs of various production factors of the emerging manufacturing nations, also greatly affects Chinese manufacturing. Facing the time of opportunity of the Internet+ intelligent manufacturing, this Special Issue will include research papers that comprehensively analyze

  • The paths and countermeasures of the strategic upgrade from China-made to China innovation, and

  • The tactics and strategies for Chinese manufacturing sector to meet international challenges,

in the following four dimensions: Economy, science and technology, energy, and environment, by employing statistics, optimization, strategic analysis, and other methods. More specifically, this Special Issue will include papers that

  • Comprehensively evaluate the current state of China’s manufacturing industry, forecast the industry’s overall development trend, analyze the connotation of “new manufacturing industry”, develop the system of evaluation criteria, and explore the deep-rooted problems existing in the development of China’s manufacturing industry; or

  • Carefully analyze the economic, scientific/technological, energy, environmental, political, and other critical factors that affect China’s manufacturing industry, and pinpoint out the macroeconomic factors that shake the future development of this industry; or

  • Investigate comparatively the development trajectories of the manufacturing powers, such as the United States, Germany, Japan, etc., analyze the advantages and disadvantages of emerging manufacturing countries, such as India and South Korea, in order to establish cooperative paths by learning from the international experiences and drawing lessons from the past developments; or

  • Study the effect of such strategies as informatization, intelligentization, Internet+ , etc., on the transition from China-made to China-innovation.

All papers selected for this Special Issue will be subject to a rigorous peer review procedure with the aim of rapid and wide dissemination of research results, developments, and applications.

Keywords:

  • Manufacturing nation

  • Internet+ intelligent manufacturing

  • Strategic upgrade

  • New manufacturing industry

  • Development trajectories of the manufacturing powers

  • Emerging manufacturing country


Dr. Jeffrey Yi-Lin  Forrest
Dr. Zaiwu  Gong
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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. Sustainability is an international peer-reviewed open access monthly 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 1400 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

  • Manufacturing nation

  • Internet+ intelligent manufacturing

  • Strategic upgrade

  • New manufacturing industry

  • Development trajectories of the manufacturing powers

  • Emerging manufacturing country

Published Papers (15 papers)

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Research

Open AccessArticle Can China’s Carbon Emissions Trading Rights Mechanism Transform its Manufacturing Industry? Based on the Perspective of Enterprise Behavior
Sustainability 2018, 10(7), 2421; https://doi.org/10.3390/su10072421
Received: 1 June 2018 / Revised: 4 July 2018 / Accepted: 5 July 2018 / Published: 11 July 2018
PDF Full-text (558 KB) | HTML Full-text | XML Full-text
Abstract
The pilot policy of carbon emissions trading rights covers six heavy pollution industries in the manufacturing industry and has achieved considerable emission reductions. Based on enterprise behavior, this study analyzes the impact of the carbon emissions trading rights pilot policy on the productivity
[...] Read more.
The pilot policy of carbon emissions trading rights covers six heavy pollution industries in the manufacturing industry and has achieved considerable emission reductions. Based on enterprise behavior, this study analyzes the impact of the carbon emissions trading rights pilot policy on the productivity of manufacturing enterprises. In addition, we examine whether the pilot policy can aid in the transformation and upgrading of China’s manufacturing industry. Furthermore, we examine the influence of carbon emissions trading rights on manufacturing enterprises of different sizes and with different property rights. The results show that the trading rights have not produced a “Porter effect” on the productivity of manufacturing enterprises in China or in subsamples based on the nature of enterprise ownership. The impact of the carbon trading rights on the productivity of state-owned manufacturing enterprises in the pilot provinces is based on the compliance cost hypothesis. Therefore, the pilot policy has yet to achieve coordinated economic, social, and environmental development. Lastly, we put forward several policy suggestions on the coordinated development of a carbon trading policy and manufacturing enterprises from the perspective of the government, enterprises, and society. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Tendency of Embodied Carbon Change in the Export Trade of Chinese Manufacturing Industry from 2000 to 2015 and Its Driving Factors
Sustainability 2018, 10(6), 1839; https://doi.org/10.3390/su10061839
Received: 11 May 2018 / Revised: 27 May 2018 / Accepted: 31 May 2018 / Published: 1 June 2018
PDF Full-text (1095 KB) | HTML Full-text | XML Full-text
Abstract
The manufacturing industry is an important part of the national industrial system, and is usually an industry with high carbon content. However, few studies have been carried out on the total amount, structure and the trend of the embodied carbon emission in the
[...] Read more.
The manufacturing industry is an important part of the national industrial system, and is usually an industry with high carbon content. However, few studies have been carried out on the total amount, structure and the trend of the embodied carbon emission in the international trade of the Chinese manufacturing industry. Based on the input–output method, the thesis proposes the coefficient of direct carbon emission and complete carbon emission and a method for calculating the embodied carbon of the export trade. It also calculates the coefficient of direct carbon emission and complete carbon emission for the Chinese manufacturing sector from 2000 to 2015 and breaks down the embodied carbon change of export trade in the manufacturing industry to a technological effect, structural effect and scale effect by using the method of structural decomposition. Several inspiring conclusions could be drawn from the thesis. For example: (1) the coefficient of both the direct carbon emission and the complete carbon emission has been decreasing significantly, indicating the achievements of the energy saving and emission reduction of the Chinese manufacturing industry. (2) The embodied carbon emission from the manufacturing exports remains high and presents a rising tendency. The main sectors that export the embodied carbon includes “S10 mechanical equipment and instruments”, “S9 metal products”, “S6 chemical industry”, etc., which should be the key sectors on reducing embodied carbon in exports. (3) The driving force of the embodied carbon exports lies in the scale effect of the manufacturing industry, on which the technical effect of the industry has a significant negative effect. The structural effect should have a positive influence that takes on a rising tendency; generally, this effect is only two-thirds of the scale effect. Finally, the corresponding policy suggestions have been made. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle The Effectiveness of Government Subsidies on Manufacturing Innovation: Evidence from the New Energy Vehicle Industry in China
Sustainability 2018, 10(6), 1692; https://doi.org/10.3390/su10061692
Received: 27 April 2018 / Revised: 18 May 2018 / Accepted: 20 May 2018 / Published: 23 May 2018
Cited by 2 | PDF Full-text (509 KB) | HTML Full-text | XML Full-text
Abstract
Manufacturing innovation is of strategic importance to China in its effort to reshape future technology. This study explores the impact of government subsidies on the research and development (R&D) intensity of China’s new energy vehicle (NEV) enterprises. The dynamic relationship between government subsidies
[...] Read more.
Manufacturing innovation is of strategic importance to China in its effort to reshape future technology. This study explores the impact of government subsidies on the research and development (R&D) intensity of China’s new energy vehicle (NEV) enterprises. The dynamic relationship between government subsidies and R&D intensity is tested with a panel regression model and a threshold regression model. We find that government subsidies have a significantly positive impact on R&D intensity when considering the sample group as a whole, but market profit does not contribute to R&D intensity. As for the sub-sample, government subsidies have a significantly positive impact on R&D intensity in assembly enterprises but are insignificant in supporting enterprises. Two threshold values are also identified with the logarithm of government subsidy. We find that government subsidies have a significant crowding in effect on the R&D intensity of NEV enterprises. With the increasing of government subsidy, the crowding in effect weakens gradually. The policy implication is that the structure of government subsidies should be optimized. More demand-oriented policy instruments should be adopted to cultivate the market. The government subsidies should be reduced gradually until full withdrawal. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Evaluating Water Consumption Based on Water Hierarchy Structure for Sustainable Development Using Grey Relational Analysis: Case Study in Chongqing, China
Sustainability 2018, 10(5), 1538; https://doi.org/10.3390/su10051538
Received: 20 March 2018 / Revised: 17 April 2018 / Accepted: 26 April 2018 / Published: 12 May 2018
PDF Full-text (1080 KB) | HTML Full-text | XML Full-text
Abstract
With the economic development, the demand for water resources has been increasing dramatically during the last several decades. The sustainable development of water resources has become a major challenge in our society. As the largest economic center in west China, Chongqing was chosen
[...] Read more.
With the economic development, the demand for water resources has been increasing dramatically during the last several decades. The sustainable development of water resources has become a major challenge in our society. As the largest economic center in west China, Chongqing was chosen as a typical unit to investigate this issue by using statistical data of fifteen years. In this study, the complexity of the water resource system was simplified through hierarchical structure analysis. Then, grey relational analysis was used to measure hierarchical correlation degree. The correlation between the levels of water consumption was analyzed, especially between water consumption and socio-economic indicators. Based on the result of hierarchical grey evaluation, three conclusions were drawn: (1) from the water consumption-oriented aspect, the correlation rankings, from high to low, are production water use, domestic water use, and eco-environmental water use respectively; (2) from industrial structure aspect, the secondary industry has the highest grey relational degree, which is followed by the primary industry (agriculture); and (3) from the economic and social indicators aspect, many significant factors are highly related to water consumption, such as precipitation, urbanization rate, total population, GDP, the proportion of output value of the three industries and residential water price. In this paper, to achieve the goal of the strictest system of water resource management during the 13th Five-Year Period, the corresponding policy suggestions are proposed for the municipal government of Chongqing. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle A Supply Chain Coordination Mechanism with Cost Sharing of Corporate Social Responsibility
Sustainability 2018, 10(4), 1227; https://doi.org/10.3390/su10041227
Received: 11 February 2018 / Revised: 28 March 2018 / Accepted: 11 April 2018 / Published: 17 April 2018
PDF Full-text (2110 KB) | HTML Full-text | XML Full-text
Abstract
The competition of modern enterprises has shifted from brand competition among enterprises of the past to that of supply chains; and considering corporate social responsibility (CSR) within supply chain management has become an inevitable requirement for improving the competitiveness of enterprises and conforms
[...] Read more.
The competition of modern enterprises has shifted from brand competition among enterprises of the past to that of supply chains; and considering corporate social responsibility (CSR) within supply chain management has become an inevitable requirement for improving the competitiveness of enterprises and conforms to the trend of standardization of social responsibility guidelines. This paper deals with channel coordination and decision-making in a CSR supply chain that is comprised of a dominant retailer and n homogeneous suppliers. The Stackelberg game is employed to analyze the optimal decision-making of this supply chain under either decentralized or centralized decision-making processes. After that, the thought and method of super conflict equilibrium are used to design the coordination decision-making mechanism of this supply chain based on the cost sharing of CSR to solve channel conflict and to optimize the decision. The results show that the proposed mechanism based on the cost sharing of CSR is better than those with only either the retailer or the suppliers being CSR; and it can well describe the relationship between the retailer and the suppliers, and increase the eagerness of the retailer and suppliers to carry out their CSR under various circumstances without having the profits adversely affected. As a matter of fact, this mechanism maximizes the profits of the entire supply chain system and also enhances the competitiveness of the chain. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Manufacturing Decisions and Government Subsidies for Electric Vehicles in China: A Maximal Social Welfare Perspective
Sustainability 2018, 10(3), 672; https://doi.org/10.3390/su10030672
Received: 16 January 2018 / Revised: 16 February 2018 / Accepted: 26 February 2018 / Published: 1 March 2018
Cited by 1 | PDF Full-text (1442 KB) | HTML Full-text | XML Full-text
Abstract
In order to address challenges in the sustainable development of transportation, economy, and environment, governments of China and conventional automobile manufacturers are extremely concerned about the development of the electric vehicle (EV) manufacturing industry and market. However, owing to the limitations of EVs
[...] Read more.
In order to address challenges in the sustainable development of transportation, economy, and environment, governments of China and conventional automobile manufacturers are extremely concerned about the development of the electric vehicle (EV) manufacturing industry and market. However, owing to the limitations of EVs and the government economic policies on decreasing subsidies in China, many manufacturers are worried about entering the EV market. Given the low consumer preference for EVs, using a leader-follower Stackelberg game model, we investigate the impact of government a subsidy on the optimal production and pricing decisions of an auto manufacturer who could produce both EVs and conventional vehicles. We characterize whether/under what conditions the manufacturer’s decision to offer EV products under government subsidy, whilst increasing its profits (a win-win situation). On the policy side, we delineate how government a subsidy can be set to realize the inherent economic, environmental, and social benefits of EV production (the triple win of EV production). We further investigate the impact of EV manufacturing- and society-related factors on the balance among manufacturer profits, environmental impact and social welfare. This study also finds that the adoption of EVs is not bound to be beneficial for the environment. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Can Environmental Regulations Promote Corporate Environmental Responsibility? Evidence from the Moderated Mediating Effect Model and an Empirical Study in China
Sustainability 2018, 10(3), 641; https://doi.org/10.3390/su10030641
Received: 8 January 2018 / Revised: 20 February 2018 / Accepted: 23 February 2018 / Published: 28 February 2018
PDF Full-text (718 KB) | HTML Full-text | XML Full-text
Abstract
Based on the Stakeholder theory, a moderated mediating effect model is developed to reach the study objective, revealing an important connection that suggests environmental regulations (ERs) influence corporate environmental responsibility (CER) (Porter Hypothesis). In building the model, the validity of the questionnaire data
[...] Read more.
Based on the Stakeholder theory, a moderated mediating effect model is developed to reach the study objective, revealing an important connection that suggests environmental regulations (ERs) influence corporate environmental responsibility (CER) (Porter Hypothesis). In building the model, the validity of the questionnaire data was analyzed with factor analysis. By employing a two-step approach, a regression analysis is utilized to discuss the mediating effect of altruistic motivation and moderating effect of green innovation, and a structural equation model is used to explore the interactive mechanism of different variables. It is found that altruistic motivation plays a medium role in the relationship between ERs and CER, and green innovation engages a positive coordination in the relationship. The empirical study identifies factors affecting enterprises’ willingness to undertake environmental responsibility, including environment policies, corporate culture, and personal characters among others. It is also revealed that altruistic motivation is conducive to forming a community interests among enterprises and enhancing their resistance to market risks, which explains and corroborates the Stakeholder theory; and the higher the level of green innovation, the more willing enterprises are to implement environmentally friendly operations. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Economic and Emission Dispatch Using Ensemble Multi-Objective Differential Evolution Algorithm
Sustainability 2018, 10(2), 418; https://doi.org/10.3390/su10020418
Received: 16 January 2018 / Revised: 26 January 2018 / Accepted: 1 February 2018 / Published: 6 February 2018
Cited by 1 | PDF Full-text (1117 KB) | HTML Full-text | XML Full-text
Abstract
In the past two decades, China’s manufacturing industry has achieved great success. However, pollution and environmental impacts have become more serious while this industry has grown. The economic and emission dispatch (EED) problem is a typical multi-objective optimization problem with conflicting fuel costs
[...] Read more.
In the past two decades, China’s manufacturing industry has achieved great success. However, pollution and environmental impacts have become more serious while this industry has grown. The economic and emission dispatch (EED) problem is a typical multi-objective optimization problem with conflicting fuel costs and pollution emission objectives. An ensemble multi-objective differential evolution (EMODE) is proposed to tackle the EED problem. First, the equality constraints of the problem have been transformed into inequality constraints. Next, two mutation strategies DE/rand/1 and DE/current-to-rand/1 have been implemented to improve the conventional DE. The performance of the proposed algorithm is evaluated on six test functions and the numerical results have indicated that the proposed algorithm is effective. The proposed algorithm EMODE is used to solve a series of six generators and eleven generators in the EED problem. The experimental results obtained are compared with those reported using single optimization algorithms and multi-objective evolutionary algorithms (MOEAs). The results have revealed that the proposed algorithm EMODE either matches or outperforms those algorithms. The proposed algorithm is an effective candidate to optimize the manufacturing industry of China. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Independent R and D, Technology Introduction, and Green Growth in China’s Manufacturing
Sustainability 2018, 10(2), 311; https://doi.org/10.3390/su10020311
Received: 25 December 2017 / Revised: 24 January 2018 / Accepted: 25 January 2018 / Published: 25 January 2018
Cited by 1 | PDF Full-text (252 KB) | HTML Full-text | XML Full-text
Abstract
An analysis of not only the effects of independent research and development (R and D), but also of the effects of the introduction of domestic and foreign technology on the growth of green manufacturing, can help China achieve the green transformation of manufacturing.
[...] Read more.
An analysis of not only the effects of independent research and development (R and D), but also of the effects of the introduction of domestic and foreign technology on the growth of green manufacturing, can help China achieve the green transformation of manufacturing. In this paper we first use a non-directional distance function (NDDF) and meta-frontier methods to calculate a green growth index. Then, using 2003 to 2015 manufacturing panel data, we empirically test the effects of three different types of R and D investment on the green growth of China’s manufacturing. The regression results show that there is significant industrial heterogeneity in the effects of independent R and D, in the introduction of domestic technology and in the introduction of foreign technology on the green growth of China’s manufacturing. Independent R and D is conducive to the green growth of the three types of technological industries, but the contribution of independent R and D to green growth has gradually weakened with improvements in industrial technology. Domestic technology introduction is conducive to green growth in low and middle-technology industries, but its effect on high-technology industries is not significant. On the other hand, foreign technology introduction is conducive to the green growth of middle and high-technology industries, but its effect on low-technology industries is not significant. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
Open AccessArticle Environmental Regulation, Green Innovation, and Industrial Green Development: An Empirical Analysis Based on the Spatial Durbin Model
Sustainability 2018, 10(1), 223; https://doi.org/10.3390/su10010223
Received: 7 December 2017 / Revised: 14 January 2018 / Accepted: 15 January 2018 / Published: 16 January 2018
Cited by 5 | PDF Full-text (580 KB) | HTML Full-text | XML Full-text
Abstract
Environmental regulation and green innovation are two main fulcrums in the realization of green transition of industrial growth. However, few studies have done an empirical analysis of the impact of environmental regulation and green innovation on green development. Based on the theory of
[...] Read more.
Environmental regulation and green innovation are two main fulcrums in the realization of green transition of industrial growth. However, few studies have done an empirical analysis of the impact of environmental regulation and green innovation on green development. Based on the theory of systematic interduality, regional industrial green development is regarded as a dynamic system composed of two subsystems: the state and the process subsystem. Using provincial industrial panel data from 2007–2015 and the spatial Durbin model under the unified analysis framework, this paper examines the role and mechanism of environmental regulation (divided into administrative environmental regulation, market-based environmental regulation, and public participation environmental regulation) in the impact of green innovation (divided into green product innovation and green craft innovation) on industrial green development. The results indicate a sharp fluctuating trend in China’s overall industrial green development performance, and that China’s 30 provinces can be divided into four categories, based on the development levels of two subsystems of industrial green development. There is a clear positive spatial correlation between the industrial green development performance in different provinces. Considering the impact of environmental regulation on industrial green development performance, different types of environmental regulation have different regional influences. Considering the impact of green innovation on industrial green development performance, in the absence of environmental regulation constraints, green product innovation shows a certain promotional role, and green craft innovation has a significant inhibitory effect. However, under environmental regulation constraints, market-based environmental regulation through the encouragement of green craft innovation rather than green product innovation achieves a positive impact on industrial green development. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Manufacturing Quality Prediction Using Intelligent Learning Approaches: A Comparative Study
Sustainability 2018, 10(1), 85; https://doi.org/10.3390/su10010085
Received: 26 November 2017 / Revised: 26 December 2017 / Accepted: 27 December 2017 / Published: 30 December 2017
PDF Full-text (4263 KB) | HTML Full-text | XML Full-text
Abstract
Under the international background of the transformation and promotion of manufacturing, the Chinese government proposed the “Made in China 2025” strategy, which focused on the improvement of a quality-based innovation ability. Moreover, predicting manufacturing quality is one of the crucial measures for quality
[...] Read more.
Under the international background of the transformation and promotion of manufacturing, the Chinese government proposed the “Made in China 2025” strategy, which focused on the improvement of a quality-based innovation ability. Moreover, predicting manufacturing quality is one of the crucial measures for quality management. Accurate prediction is closely related to the feature learning of manufacturing processes. Therefore, two categories of intelligent learning approaches, i.e., shallow learning and deep learning, are investigated and compared for manufacturing quality prediction in this paper. Specifically, the feed forward neural network (FFNN) with one hidden layer and the least squares support vector machine (LSSVM) with no hidden layers are selected as the representatives for shallow learning, and the deep restricted Boltzmann machine (DRBM) and the stack autoencoder (SAE) are chosen as the representatives for deep learning. The manufacturing data is collected from a competition about manufacturing quality control in the Tianchi Data Lab of China. The experiments show that the deep framework overwhelms the shallow architecture in terms of mean absolute percentage error, root-mean-square error, and threshold statistics. In addition, the prediction results also indicate that the performances depend on the length of the training data. That is, the bigger the sample size is, the better the performance is. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle A Novel Grey Wave Method for Predicting Total Chinese Trade Volume
Sustainability 2017, 9(12), 2367; https://doi.org/10.3390/su9122367
Received: 7 November 2017 / Revised: 13 December 2017 / Accepted: 15 December 2017 / Published: 18 December 2017
PDF Full-text (4576 KB) | HTML Full-text | XML Full-text
Abstract
The total trade volume of a country is an important way of appraising its international trade situation. A prediction based on trade volume will help enterprises arrange production efficiently and promote the sustainability of the international trade. Because the total Chinese trade volume
[...] Read more.
The total trade volume of a country is an important way of appraising its international trade situation. A prediction based on trade volume will help enterprises arrange production efficiently and promote the sustainability of the international trade. Because the total Chinese trade volume fluctuates over time, this paper proposes a Grey wave forecasting model with a Hodrick–Prescott filter (HP filter) to forecast it. This novel model first parses time series into long-term trend and short-term cycle. Second, the model uses a general GM (1,1) to predict the trend term and the Grey wave forecasting model to predict the cycle term. Empirical analysis shows that the improved Grey wave prediction method provides a much more accurate forecast than the basic Grey wave prediction method, achieving better prediction results than autoregressive moving average model (ARMA). Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Analysis of Interval Data Envelopment Efficiency Model Considering Different Distribution Characteristics—Based on Environmental Performance Evaluation of the Manufacturing Industry
Sustainability 2017, 9(12), 2080; https://doi.org/10.3390/su9122080
Received: 7 October 2017 / Revised: 31 October 2017 / Accepted: 6 November 2017 / Published: 27 November 2017
Cited by 2 | PDF Full-text (960 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
This study utilizes the Data Envelopment Efficiency (DEA) model to assess input–output efficiency from two perspectives. First, not considering the distribution of interval data, we introduce an adjusted parameter to transform interval data to determination data. Second, by contrast, we take into account
[...] Read more.
This study utilizes the Data Envelopment Efficiency (DEA) model to assess input–output efficiency from two perspectives. First, not considering the distribution of interval data, we introduce an adjusted parameter to transform interval data to determination data. Second, by contrast, we take into account the distribution characteristics of interval data and test the DEA model with interval data based on linear uniform distribution and normal distribution with uncertainty. Based on the normal distribution DEA evaluation model, this paper aims to evaluate the input–output performance of the manufacturing industry with the constraint of environmental pollution in the Yangtze River Delta (YRD) region, China. Research has shown that the optimal solution of the normal distribution model is better than that of linear distribution. Therefore, it is imperative to adopt an appropriate method to evaluate the energy and environmental efficiency of this region. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Going Public and Industrial Upgrading of Traditional Clusters in Developing Countries: Rethinking the Dynamics of the ‘Jinjiang Model’ in China
Sustainability 2017, 9(11), 2133; https://doi.org/10.3390/su9112133
Received: 24 September 2017 / Revised: 24 September 2017 / Accepted: 24 September 2017 / Published: 19 November 2017
PDF Full-text (982 KB) | HTML Full-text | XML Full-text
Abstract
Extant literature concerns about industrial upgrading in developing countries, and stresses the importance of joining global production networks (GPN). Taking the perspective of the updating approach of GPN theory, this paper selects the case of China to combine local industrial upgrading with financial
[...] Read more.
Extant literature concerns about industrial upgrading in developing countries, and stresses the importance of joining global production networks (GPN). Taking the perspective of the updating approach of GPN theory, this paper selects the case of China to combine local industrial upgrading with financial activities, and explores how going public triggers industrial upgrading in developing countries. In 2015, semi-structured interviews were conducted with 36 listed firms and their related partners in Jinjiang, a county-level city in China. The findings indicate that local lead firms in developing countries have been increasingly involved in the global financial market by going public, which in turn provides these countries with opportunities of industrial upgrading. However, it does not necessarily guarantee industrial upgrading. Whether or not going public can bring about industrial upgrading depends mainly on intrafirm coordination, reconfiguration of interfirm relationships, and extrafirm bargaining with local governments. This case study suggests that finance be integrated into GPN theory as some scholars suggest, and the impacts of local lead firms in developing countries on the dynamics or reconfiguration of GPN be taken consideration, especially in some specific sectors. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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Open AccessArticle Forecasting the Energy Consumption of China’s Manufacturing Using a Homologous Grey Prediction Model
Sustainability 2017, 9(11), 1975; https://doi.org/10.3390/su9111975
Received: 13 September 2017 / Revised: 24 October 2017 / Accepted: 27 October 2017 / Published: 31 October 2017
Cited by 3 | PDF Full-text (1247 KB) | HTML Full-text | XML Full-text
Abstract
With the rapid development of China’s manufacturing, energy consumption has increased rapidly, and this has become a major bottleneck affecting the sustainable development of China’s economy. This paper deduces and constructs a homologous grey prediction model with one variable and one first order
[...] Read more.
With the rapid development of China’s manufacturing, energy consumption has increased rapidly, and this has become a major bottleneck affecting the sustainable development of China’s economy. This paper deduces and constructs a homologous grey prediction model with one variable and one first order equation (HGEM(1,1)) for forecasting the total energy consumption of China’s manufacturing based on the Grey system theory. Both parameter estimation (PE) and the deduction of the final restored expression (FRE) of the HGEM(1,1) model are all from the time response expression of the whitenization differential equation, which solves the ‘non-homologous’ defects of PE and FRE with traditional grey prediction models. HGEM(1,1) has good performance and can unbiasedly simulate a homogeneous/non-homogeneous exponential function sequence and a linear function sequence. Then, the HGEM(1,1)model is used to simulate and forecast the total energy consumption of China’s energy manufacturing, and the results show that the comprehensive performance of this model is much better than that of the classic 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, we forecast the total energy consumption of China’s manufacturing industry during the years 2018–2024. The results show that the total energy consumption in China’s manufacturing is slowing down but is still too large. For this, some measures, such as optimizing the manufacturing structure and speeding up the development and promotion of energy saving and emission reduction technologies, to ensure the effective supply of energy in China’s manufacturing industry are suggested. Full article
(This article belongs to the Special Issue Transition from China-Made to China-Innovation )
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