Participation in global value chain and green technology progress: evidence from big data of Chinese enterprises

Environmental quality assessment and spatial spillover effects of three urban agglomerations in China: A Meta-EBM approach

The new development form of urban agglomeration has greatly promoted economic and social progress in recent years, but it is also facing severe environmental pollution problems. Understanding the status quo of environmental efficiency in urban agglomerations and its leading driving forces is an important prerequisite for formulating energy conservation and emission reduction policies. This research uses the Meta Epsilon Based Measure (Meta-EBM) model to measure the environmental emission efficiency of the Beijing-Tianjin-Hebei（BTH）, Yangtze River Delta (YRD) and Pearl River Delta (PRD) urban agglomerations in China from 2014 to 2018 so as to improve on the inability of traditional Data Envelopment Analysis (DEA) to combine linear and non-linear characteristics, and employs Moran's I index and spatial econometric methods to analyze their spatial dependence and main driving factors. The results demonstrate that the overall environmental efficiency of the three major urban agglomerations in the five years from 2014 to 2018 presents a wave-like development and then tends to be flat. The itemized efficiency of economic outputs has maintained a relatively high level with the environmental output index exhibiting the best efficiency for industrial wastewater, followed by industrial sulfur dioxide (SO2). The scores of the two indicators for inhalable fine particle emissions (PM2.5) and industrial smoke and dust in each urban agglomeration are not ideal, and there are obvious differences between regions. Among them, YRD and PRD are relatively inferior. From the perspective of spatial spillover effects, various indicators show diverse characteristics at different development stages of the regions. Population and Normalized Difference Vegetation Index (NDVI) have a positive effect on environmental efficiency, while both Gross Domestic Product (GDP) per capita and transportation tend to show greater negative effects on regional environmental optimization. This study proposes countermeasures as follows. Each urban agglomeration should set up measures suitable to local conditions and give full play to their location advantages. They can also use space radiation to promote sector economic development and optimize urban environmental benefits.

Can Global Value Chains Embedment Reduce Carbon Emissions Embodied in Exports?-Empirical Test Based on the Manufacturing Industries

Active participation in the global value chains (GVC) has been recognized as an important factor in curbing the growth of carbon emissions. However, how GVC embedment affects carbon emissions in economies and what are the pathways of its impact need to be further studied. This paper analyzes the mechanism of GVC embedment affecting carbon emissions embodied in exports (CEEE) and selects 17 manufacturing industries in 36 economies around the world for empirical testing. It is found that GVC embedment significantly reduces the CEEE. Specifically, GVC embedment has a suppressive effect on the CEEE of both developed and developing countries, and the former has a greater suppressive effect than the latter; the effect on the CEEE of low-tech industries is significantly negative but not conducive to carbon emissions reduction in high-tech industries; complex and forward embedment have higher emissions reduction effects compared with simple and backward embedment. More importantly, GVC embedment reduces the CEEE through energy conservation effect, structure effect and transfer effect, and all of them show significant inverted U-shaped mediation effect. The findings of this paper have important implications for the sustainable economic development around the world under the GVC division of labor system.

Coordination mechanisms for digital and sustainable textile supply chain

Purpose

Supply chain network is complicated to manage due to the involvement of a number of agents. Formation of virtual organization using Industry 4.0 (I4.0) is an approach to improve the efficiency and effectiveness and to overcome the complexities of the channel. However, the task of managing the channel further becomes complicated after incorporating sustainability into the supply chain. To fill this gap, this paper focuses on designing of mechanism and demonstration of I4.0-based virtual organization to coordinate sustainable supply chain.

Design/methodology/approach

In this paper, we model and compare I4.0-based virtual organization models using four other traditional contracts with centralized supply chain. The non-cooperative game theoretic approach has been used for the analysis of models.

Findings

Our game-theoretic analysis shows that investment in I4.0 and sustainable innovation are beneficial for the overall supply chain. Our results show that linear two-part tariff contract and I4.0-based virtual organization model can perfectly coordinated with the supply chain.

Research limitations/implications

This study consider deterministic model settings with full information game. Therefore researchers are encouraged to study I4.0-based coordination models under information asymmetry and uncertain situations.

Practical implications

The paper includes implications for the development of I4.0-based coordination model to tackle the problems of channel coordination.

Originality/value

This study proposes I4.0-based game-theoretic model for the sustainable supply chain coordination.

Structural characteristics and evolution of the "international trade-carbon emissions" network in equipment manufacturing industry: international evidence in the perspective of global value chains

The objective of this paper is to analyze structural characteristics and the evolution of "international trade-carbon emissions" network in the equipment manufacturing industry. To do so, we construct four kinds of networks, namely export trade network (E network), export implied carbon emission network (EC network), foreign value-added network (FVA network), and foreign value-added implied carbon emission network (FVAC network) for the said industry. The data obtained from world-input-output table and social network analysis method was used for empirical analysis. The results indicate that (1) the four types of networks show a trend of denseness, which also has the characteristics of trade clustering effect and small-world network. As the equipment manufacturing industry in various countries is increasingly embedded in the global value chain, the value chain is extended globally, which leads to the complexity of the international carbon transfer network. (2) The four types of networks' pattern are basically stable. Germany plays an important intermediary role. Whereas China is deeply involved in the division of global value chain and has achieved the shift from the edge to the core in all four types of networks, but there is still a big gap compared with Germany. (3) The E network and EC network have the obvious core-edge feature, and the two kinds of networks can be divided into developed countries block represented by Germany, Japan, the USA; developing countries block represented by China and India; and European Union block represented by Spain and France. The developing world receives carbon emission transfer from the developed world. Finally, (4) the division of FVA network and FVAC network segment shows that the global value chain under the current international division of labor is characterized by multi-regionalization. Therefore, actively embedding in the regional value chain has become an important way for China's equipment manufacturing industry to upgrade to low carbon.

Evaluating the sustainability of big data centers using the analytic network process and fuzzy TOPSIS

The big data revolution has created data center sustainability problems, whose solutions require the consideration of environmental factors. The purpose of this study is to establish a big data center sustainability evaluation index and provide guidance for sustainable data center construction. This research formulated a big data center sustainability evaluation model that integrates multiple-criteria decision-making methods based on the analytic network process and fuzzy technique for order preference by similarity to an ideal solution (TOPSIS). Furthermore, a case study was used to examine the proposed model. The refrigeration system, layout and ventilation, data center location, data volume, and server power consumption are the five most crucial factors in determining the sustainability level of a big data center. The areas that require further development are the balancing of tasks on different IT equipment, renewable energy use, and waste heat utilization. This research provides a method or guide that can be used by managers when they build new big data centers or upgrade and optimize existing big data centers to make them more sustainable. This study is the first to assess the sustainability of a big data center according to multiple criteria decision-making methods, in which fuzzy theory is applied to evaluate the imprecise and subjective judgments of decision-makers. This study provides a systematic evaluation framework that is based on qualitative and quantitative criteria and comprises the four factors of big data level, equipment level, room level, and data center level. Big data is new oil, but it is not clean oil. It is both a vital driver of economic growth and a source of environmental damage. We need to ensure that big data centers are run in a sustainable way.

Global value chains, technological progress, and environmental pollution: Inequality towards developing countries

The production and trade activities of global value chains (GVC) increasingly contribute to the gross domestic product (GDP) of developing countries. However, while the development of domestic economies brings about technological progress, it also may have negative consequences such as environmental pollution. Technological progress can be conducive to reducing pollution emissions. Our motive is to realize the dual effects of technological progress and energy saving and emission reduction in developing countries' participation in the global value chain through research on GVC, technological progress and environmental pollution. Improving environmental quality through technological advances and reducing the adverse effects of inequality in trade status, enabling developing countries to obtain dividends from participating in the value chain as much as possible, and mitigating the adverse effects of environmental pollution during development. And lay the policy foundation for developing countries to go green. However, most of the current researches focus on the relationship between GVC and technological progress or GVC and environmental pollution, and the research on the relationship between the three is scarce. We use the WIOD database to try to find the relationship between developing country global value chain participation, technological progress and environmental pollution. Wang's method for GVC embedding is adopted for empirical research on input and output, energy utilization, high-skilled labor ratio, and pollution emissions in five typical developing countries, namely, Brazil, Russia, India, China, and Mexico. The relationships among the degree of participation in GVC, technological progress, and environmental pollution is studied from the perspective of industries in each country. The outcomes indicate that there is a value chain threshold in developing countries. When the degree of participation in a value chain is lower than the threshold, technological progress can result in an increase in pollution; otherwise, technological progress can reduce emissions. These results provide a theoretical basis and practical suggestions for developing countries to realize their own energy conservation, emission reductions, and green development while participating in globalized value chains. However, because the data related to the WIOD database is limited to 1995-2009, there are a few flaws in data integrity, which is also a challenge we face.

Modeling drivers for successful adoption of green business: an interpretive structural modeling approach

Like most other developing countries, Bangladesh is facing tremendous pressure to mitigate climate change effects and prior environmental degradation, further creating a vulnerable condition in mitigating its environmental, social, and economic circumstances. Green business approaches could be one of the better weapons for these severe conditions as they quantify the incorporation of environmental and social concerns without compromising economic development. They have gained considerable attention from governments, industries, and researchers over the past few years. The main aim of this paper is designed to build up a structured model (interpretive structural modeling) of drivers for adopting green business (GB) in the context of emerging economies. The interpretive structural modeling (ISM) will allow the assessors in the regulatory, market, and other sectors to promote the smooth utilization of green business strategies by defining and recognizing the linkages among the drivers associated with the green business. The driver's intimate relationship enables a hierarchy by compiling their dependence and driving power. For demonstrating the structural modeling for the identified drivers, we used combined "Matriced' Impacts Croisés Multiplication Appliquée á un Classement" (MICMAC) analysis and ISM model for characterizing the drivers as indicated by their driving and dependence power. Throughout, the evaluation of the available literature followed by a discussion with experts (both industrial and academic) was done for the identification of the drivers for green business adoption. A structured model (ISM) and MICMAC (as fuzzy analytical tools) analysis are required to give a boon set of knowledge to the assessors of the legislature and business industry, which further lead them for resource maximization in a sustainable way to embrace green strategies into their core business process.

Application of industry 4.0 technologies in SMEs for ethical and sustainable operations: Analysis of challenges

In the era of Industry 4.0 and circular economy, small and medium enterprises (SMEs) are under huge pressure to make their manufacturing operations ethical and sustainable. Business with ethical and sustainable operations has become the need of the day in the present environment of Industry 4.0 and circular economy. It has been observed that the application of Industry 4.0 technologies may help in achieving the goal of ethical and sustainable operations. Although a lot of research has been done in context to larger enterprises, limited research is available on the application of Industry 4.0 technologies in SMEs for ethical and sustainable operations. The espousal of Industry 4.0 technologies is a challenging task for SMEs due to various operational and financial constraints. The problem is more acute, specifically in context to developing countries like India. Keeping in mind the role of technologies in ethical business and circular economy, we have identified fifteen challenges, impacting the application of Industry 4.0 technologies in SMEs. A questionnaire was designed for collecting the response from industry and academic experts. On the collected data, the DEMATEL approach has been applied to check the degree of influence and interrelationship among challenges. It has also helped in the categorization of factors as cause and effect. Sensitivity analysis is also performed to validate the results obtained from the DEMATEL approach. Authors have observed that lack of motivation from partners and customers on the application of I4.0 technologies is the leading challenge. Fear of failure of I4.0 technologies is the main effect group challenge. The findings of the study will help SMEs in formulating strategies for implementing Industry 4.0 technologies for ethical and sustainable business processes.

Analysis of resource allocation and environmental performance in China's three major urban agglomerations

This study focuses on the analysis of optimal energy allocation and environmental performance of China's three major urban agglomerations. Specifically, this paper first uses a fixed-input DEA model to obtain the optimal allocation of energy input. Then, an evaluation model based on the optimal allocation of energy input is proposed to evaluate environmental performance. Finally, these models are applied to the empirical analysis of the three major urban agglomerations in China. This article mainly draws the following conclusions. First, energy is wasted in most cities in the Beijing-Tianjin-Hebei region. Second, from 2012 to 2016, the environmental performance of each urban agglomeration showed a downward trend and then an upward trend. Third, the overall environmental performance of the three major urban agglomerations is not high. Some specific regions, such as Handan, Anyang, Xingtai, and Baoding, behave not well in protecting the environment.

The Causality between Participation in GVCs, Renewable Energy Consumption and CO2 Emissions

Using the panel vector autoregressive (PVAR) model accompanied by the system-generalized method of moment (System-GMM) approach, this paper investigates the dynamic causality between participation in global value chains (GVCs), renewable energy consumption and carbon dioxide (CO2) emissions throughout 1990–2015 for 172 countries. The results show that participation in GVCs negatively causes renewable energy consumption except for the Middle East and North America (MENA) and sub-Saharan Africa. Second, except for the Asia–Pacific region and globally, participation in GVCs has no causal impact on CO2 emissions, and participation in GVCs has a positive effect on CO2 emissions in the Asia–Pacific region and globally. Third, except for globally and sub-Saharan Africa, CO2 emissions have no causal impact on participation in GVCs; however, CO2 emissions hurt participation in GVCs globally and in the sub-Saharan African region. Forth, renewable energy consumption positively causes participation in GVCs in MENA, while renewable energy consumption does not cause participation in GVCs globally and in other regions. Fifth, there is no causality between CO2 emissions and renewable energy consumption both at the global and regional levels. Several policy implications are proposed and discussed for promoting participation in GVCs and improving the environment.

Realization of green transition based on the anti-driving mechanism: An analysis of environmental regulation from the perspective of resource dependence in China

Environmental regulations and ecological efficiency are the driving force and objective function of China's economic growth, respectively. Whether they can achieve a win-win effect is key to the green transformation and high-quality development of resource-based cities. Based on the normative explanation of the implications of the resource curse, this paper uses panel data to calculate the ecological efficiency level and comprehensive index of environmental regulation by respectively using the global reference of undesirable output super-efficiency SBM model and the entropy method. The spatial panel Durbin model is used to test the Porter and resource curse hypotheses, and whether resource dependence can become the mediating variable of environmental regulation affecting ecological efficiency is further verified by using the mediating effect model. The results show that environmental regulation has a significant U-shaped curve relationship with ecological efficiency and a significant inverted U-shaped curve relationship with resource dependence. The relationship between resource dependence and ecological efficiency is different between resource-based and non-resource-based cities. Resource dependence can be used as a mediating variable of environmental regulation that affects ecological efficiency. Environmental regulation can directly affect the level of ecological efficiency through the mechanisms of "cost of compliance" and "cost-saving innovation," and indirectly the level of ecological efficiency through that of resource dependence. Therefore, there exists an effective "anti-driving mechanism" in China's environmental regulation policy, which can not only promote urban ecological efficiency, but also solve the resource curse of cities.

Tracing Air Pollutant Emissions in China: Structural Decomposition and GVC Accounting

The depth and breadth of China’s participation in global value chains have an important impact on the emissions of air pollutants from the production side, consumption side, and trade implications in China’s industries. Based on the global value chain accounting framework, this paper examines the path of China’s major air pollutant emissions in production and consumption during 1995–2009 and structurally decomposes the factors affecting air pollutant emissions. The results show that, firstly, both the air pollutant emissions on the production side and the air pollution emissions on the consumption side have increased significantly, and the production-side emissions have been higher than the consumption-side emissions. Secondly, the export of intermediate products shows a trend of “high pollution”, and this trend was more obvious after China’s accession to the world trade organization (WTO). Thirdly, the expansion of economic growth was the most important factor in the rapid emission of air pollutants in China and the reduction of pollution efficiency in Chinese industries depends on the increase in service inputs.

Does financial development promote the win-win balance between environmental protection and economic growth?

Existing studies have analyzed the effects of financial development on economic growth and environmental pollution respectively, but few studies have analyzed the effects of financial development on economic growth and environmental protection from a unified framework. This paper reports on a study which took the 28 provinces of China, for the years 2002-2014, as its research object. It used green efficiency to measure the win-win balance between economic growth and environmental protection. It divided green efficiency into economic efficiency and environmental efficiency and then studied the effects of financial development on economic growth and environmental protection within a unified framework. The primary findings indicate that (1) overall, financial development is conducive to obtaining the win-win balance in China's economy, with its positive effects on economic growth being more significant than on environmental protection; (2) capital market development promotes both economic growth and environmental protection, while also playing a significant role in the win-win balance of China's economy.