Assessing the environmental management efficiency of manufacturing sectors: evidence from emerging economies

Accepted Manuscript Assessing the Environmental Management Efficiency of Manufacturing Sectors: Evidence from Emerging Economies X.M. Xie, Dr. Z.P. Zang, G.Y. Qi PII:

S0959-6526(15)01095-1

DOI:

10.1016/j.jclepro.2015.08.006

Reference:

JCLP 5972

To appear in:

Journal of Cleaner Production

Received Date: 18 July 2013 Revised Date:

13 February 2015

Accepted Date: 3 August 2015

Please cite this article as: Xie XM, Zang ZP, Qi GY, Assessing the Environmental Management Efficiency of Manufacturing Sectors: Evidence from Emerging Economies, Journal of Cleaner Production (2015), doi: 10.1016/j.jclepro.2015.08.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

0

ACCEPTED MANUSCRIPT

Title: Assessing the Environmental Management Efficiency of Manufacturing Sectors: Evidence from Emerging Economies

RI PT

Authors: X. M. Xie a, Z. P. Zang b *, G. Y. Qi c School of Management, Shanghai University, Shanghai 200444, China

b

Humanities School, East China University of Political Science and Law, Shanghai 200042, China

c

School of Business, East China University of Science and Technology, Shanghai 200237, China

* Corresponding Author:

Dr. Z. P. Zang 10-202, 188 Jufengyuan Road

TE D

Shanghai, 2000444

M AN U

SC

a

P.R. CHINA

EP

Phone numbers: 86+136 6163 3946 Fax: 86+021 66133851

AC C

E-mail: [email protected]

1

ACCEPTED MANUSCRIPT

Assessing the Environmental Management Efficiency of Manufacturing Sectors: Evidence from Emerging Economies

RI PT

ABSTRACT: Environmental management in the Chinese manufacturing industry has attracted global attention. Using environmental indicator data from 2001-2010 for this industry, we empirically examine its environmental management efficiency using Data Envelopment Analysis

SC

(DEA) and Hierarchical Clustering methods. Our findings reveal that the environmental

M AN U

management of the Chinese manufacturing industry has more DEA inefficiency than efficiency. Environmental management efficiency showed a significant decline before 2004, but rapid growth since 2007. Our findings also indicate that there is input redundancy and output insufficiency in the manufacturing industry’s environmental management from 2002 to 2004. In

TE D

addition, we found that most manufacturing sectors in China had consistently inefficient environmental management over the 10 years under study. Overall, our findings reveal that

EP

efficiency remains low. Thus, the manufacturing industry’s environmental management needs to improve from the perspective of enterprises and government. We hope that our study paves the

AC C

way for future research into improving the manufacturing industry’s environmental management in emerging countries.

Keywords: Environmental Management; Manufacturing Sectors; Data Envelopment Analysis (DEA)

2

ACCEPTED MANUSCRIPT

1. Introduction We face increasingly serious global environmental crises, and countries are taking measures to address them. Over the past 10 years, there has been a significant growth in environmental

RI PT

management reporting, evaluation of contamination levels and their effects on the environment being one of the most pressing problems this century (Burger et al., 2007; Crowley and Ahearne, 2002; Qu et al., 2013; Zhu et al., 2007a). China, as a developing country, has also increased its

SC

emphasis on economic development while seeking to maintain a balance with environmental

M AN U

protection (Zhu et al., 2007b). However, a combination of serious environmental pollution and ineffective governance makes it difficult to move effective environmental management forward. Therefore, environmental management requires not only baseline information, and temporal and spatial patterns to evaluate the status of environmental health and well-being (Baird, 2005), but

TE D

also compliance with regulations and active participation by businesses. Evaluating, improving, and managing the environment are long-standing concerns are now

EP

attracting a broader audience (Burger, 2008). One goal of environmental evaluation is to assess environmental management efficiency in order to enhance environmental sustainability.

AC C

Generally, environmental management is a political ecology or environmental policy concept related to defining the elements needed to achieve sustainability, including not only government, but also business and civil society, and emphasizes whole system management (Brandes and Brooks, 2005). Management efficiency is one of the crucial indicators that can reflect the performance of environmental management in manufacturing. What is more, the quality of environmental management determines the potential for sustainable development in manufacturing and can provide environmental safeguards while enhancing management

3

ACCEPTED MANUSCRIPT efficiency.

Since 1979, China has maintained a high economic growth rate by adopting economic reform policies, increasing international trade, and transitioning to a market economy (Zhang et al.,

RI PT

2008). Because the manufacturing industry is the driving force behind China’s economic growth, the manufacturing industry has experienced rapid growth over many years of market-oriented reform (Zeng et al., 2010). However, China’s scale-driven economic development has led to

SC

inefficient natural resource and energy use in the production process, and high pollution levels

M AN U

(Zhang et al., 2008). The Chinese manufacturing industry had experienced increasing ecological pressures from a variety of institutional players, including the market, the government, and competitive sources (Zhu and Sarkis, 2007). To be sure, environmental pollution in China is becoming increasingly serious. Industrial pollution has been the greatest obstacle to China’s

TE D

sustainable development (Liu and Ma, 2010). For example, according to statistical data in China,① in 2006, manufacturing wastewater reached 16.67 billion tons, wasted gas 21.7626 trillion standard cubic meters, and solid waste 580 million tons. Even more serious is the fact that

EP

China’s sulphur dioxide emissions are the highest in the world. Moreover, less than 20% of urban

AC C

garbage was taken to landfills, and only 32% of industrial hazardous waste disposal. These numbers highlight the environmental management inefficiencies of the Chinese manufacturing industry. Although many Chinese manufacturers have implemented organizational approaches, such as cleaner production and environmental management systems to improve their environmental performance (Zhu and Sarkis, 2007), and successive Chinese governments have established and enforced additional laws and regulations to control pollution (Zhu et al., 2007b),

①

News.xinhuanet. China Environmental Data [EB/OL] http://news.xinhuanet.com/banyt//content_2713384.htm.

4

ACCEPTED MANUSCRIPT

China’s environmental management has not improved substantially in the past 20 years. What is the major reason for this? On one hand, as Hussey and Eagan (2007) have revealed, the low environmental management efficiency in business derived from the fact that businesses did not

RI PT

comply with the regulations. On the other, insufficient resources were allocated to the Environmental Management Unit (Rodriguez et al., 2011). Evaluating the manufacturing industry’s environmental management efficiency for China is therefore important.

SC

We undertook our study in this context. First, we evaluated the manufacturing industry’s

M AN U

overall environmental management efficiency. Second, because environmental management efficiency varies between manufacturing sectors, we designed this study to examine the environmental management efficiency of sub-sectors. Third, we attempted to locate the manufacturing industry’s environmental management efficiency input redundancy and output

TE D

insufficiency, in order to effectively reduce the input and improve the output of environmental management. We hope that our findings pave the way to improving the environmental

EP

management efficiency of the manufacturing industry in emerging countries.

2. Literature review

AC C

In recent years, evaluating environmental management efficiency as a means of sustainable development has attracted a broader audience and dominated much debate (Burger, 2008). The United States’ National Research Council (NRC) and Environmental Protection Agency (EPA) have paid close attention to the quantitative measures and evaluation methods for environmental management efficiency. For instance, the EPA issued a “Framework of Environmental Risk Evaluation” in 1992 and “Guidelines of Environmental Risk Evaluation” in 1998. In the late 1990s, the Organization for Economic Co-operation and Development (OECD) issued a

5

ACCEPTED MANUSCRIPT

“Pressure-State-Response” model. The model describes clearly the close interaction between human activities and environment, which lays a solid foundation for environmental evaluation. Recent studies have explored environmental evaluations for a variety of ecosystems, including

RI PT

forests, rivers, and lakes (Amores et al., 2013; Burger, 2008; Lee et al., 2007; Rodriguez et al., 2011; Vrscaj et al., 2008). Costanza (1992) proposed a way to measure ecosystem health and ecological security that promoted the development of environmental evaluation. Schulze and

SC

Frosch (1999) conducted ecosystem analyses using ecological indicators such as water pH, air

M AN U

temperature, solid element, and the number of biological species. Rees (1992) proposed an ecological footprint (EF) method that compared human resource consumption to environmental carrying capacities in order to evaluate the environmental security. Vrscaj et al. (2008) developed an evaluation method for measuring the urban soil quality for different land uses within one

TE D

particular system and applied it to two areas: urban soil quality control and soil evaluation for urban planning. Overall, the EF method has become the main means by which a large number of organizations and research scholars evaluate sustainable development capacity.

EP

Indicators imprint quantifiable trends in observable phenomena and can be characterized as

AC C

signs or signals that relay a complex message from potentially numerous sources in a simple and useful manner (Kurtz et al., 2001; Peris-Mora et al., 2005). Environmental indicators are expected to provide an early warning to help prevent environmental, social, and economic damage (Huang et al., 2009). The changing and complex global environment requires the integration of diverse environmental management disciplines and techniques (Burger, 2008). Thus, in recent years, many scholars have begun using multi-indicator methodologies to evaluate the environment. Vencheh et al. (2005) developed a DEA-based model for efficiency evaluation simultaneously

6

ACCEPTED MANUSCRIPT

incorporating undesirable inputs and outputs. Hermann et al. (2007) presented a new analytical tool called COMPLIMENT, which provides detailed information on a business’s overall environmental sustainability and can integrate tools such as life cycle assessment, multi-criteria

RI PT

analysis, and environmental performance indicators. He et al. (2007) carried out a multi-indicator assessment on government auditing of water protection programmes to evaluate the performance of national environmental protection programmes and provide technical support for

SC

environmental auditors. Similarly, Fang et al. (2011) provided a risk management methodology

M AN U

aimed at process control for land settlement in China. Liu et al. (2010) proposed an evaluation criterion that incorporated a technological index of whether businesses utilized obsolete technologies. These safety controls, incorporated into designing these standards and the measures taken in their construction, can serve as a practical reference for other similar studies or projects.

TE D

Previous studies have explored environmental evaluation and developed a few indicators for urban and regional sustainability, e.g. for cities in China (Li et al., 2009; Yuan et al., 2003) and in developed western countries (Scipioni et al., 2009; Tanguay et al., 2010). The use of urban

EP

sustainability indicators constitutes an important international tool for assessing urban status

AC C

(economic, social, and environmental) and monitoring the progress achieved towards sustainable development (Graymore et al., 2009; Valentin and Spangenberg, 2000). Moussiopoulos et al. (2010) studied the development and utilization of a system of indicators as a dynamic tool for the management of environmental, social, and economic information in order to evaluate sustainability in urban areas. Huang et al. (2010) developed a two-layered DSS for rural sustainable development (DRSD) for comprehensive planning of socioeconomic development and environmental protection in Yongxin County, Jiangxi Province, China. They analysed the

7

ACCEPTED MANUSCRIPT

relationships between rapid economic development, ecological destruction, and environmental deterioration within the region. Overall, urban indicators can provide crucial guidance for environmental management decision-making (Moussiopoulos et al., 2010).

RI PT

Some studies have also explored the relationship between environmental management and performance (Klang et al., 2003; Peiro-Signes et al., 2013). Hughey et al. (2005) found that while each system appeared to have its own strengths, no one environmental management system was

SC

better than another. Zeng et al. (2011) suggested that small and medium-sized enterprises (SMEs)

M AN U

with different pollution levels present significant differences in the relationship between driving forces and performance. Liu et al. (2010) suggested that enterprises that often arranged internal environmental training were more likely to adopt proactive environmental activities and address more concerns from the public and mass media in order to enhance normative power to improve

TE D

the environmental management level in China in the future. Montabon et al. (2007) used a more comprehensive set of practices than prior studies to test the relationships between environmental management practices and firm performance. Their results supported previously posited

EP

relationships based on traditional data and indicated that environmental management practices are

AC C

associated with firm performance. Hussey and Eagan (2007) evaluated the development of an environmental performance model for SMEs, and concluded that it was critical to better define environmental results and that SMEs should be educated on the benefits of improved environmental performance. Thus, environmental evaluations form the basis for all methods of environmental management, including conducting environmental impact assessments, managing the environment, and assessing the efficacy of long-term stewardship (Burger, 2003). Overall, previous work has explored environmental evaluations, environmental indicators, and

8

ACCEPTED MANUSCRIPT the relationship

between

environmental

management

and

performance,

providing a

comprehensive review of environmental management efficiency. However, previous work has explored environmental evaluation from the point of view of the country, region, city, or

RI PT

ecosystem, ignoring that of the manufacturing industry. In addition, although there have been some studies on environmental indicators, they have not taken account of the perspective of environmental management efficiency and the input redundancy and output insufficiency of the

SC

manufacturing industry. Therefore, it is necessary and valuable to carry out this research to

M AN U

evaluate environmental management efficiency from the manufacturing industry’s viewpoint. First, this study aims to assess the environmental management efficiency of the manufacturing industry in order to examine its causes and internal mechanism. Second, as the environmental management efficiency of various manufacturing sectors is quite different, this paper examines

3. Methodology

EP

3.1. Method

TE D

various manufacturing sectors.

AC C

Data Envelopment Analysis (DEA), first proposed by Charnes, Cooper, and Rhodes in 1978 (Charnes et al., 1978), is commonly used to evaluate the efficiency of a number of “units”, such as a group of producers or hospitals, characterized by multiple inputs and outputs (Zhang et al., 2008). Today, researchers recognize DEA as a decision aid in multi-criteria analyses of discrete alternatives (Srdjevic et al., 2005). Given that DEA is the most widely used method in multi-indicator analysis, we used it to evaluate the environmental management efficiency of the manufacturing industry. At present, however, most top managers of manufacturing enterprises

9

ACCEPTED MANUSCRIPT

view the input of pollution control as a cost of consumption. They are therefore bound to reduce environmental management input as much as possible in operating management, and its returns to scale are changing constantly. Thus, we chose the input-oriented BCC model of DEA to evaluate

software.

m

s

i =1

r =1

Minh j = θ − ε (∑ sij− + ∑ srj+ )

SC

The formula of the BCC model is expressed in equation (1).

RI PT

the environmental management efficiency of the manufacturing industry, using DEAP2.1

 − ∑ λ j xij −θ xij + sij = 0  i =1  s + ∑ λ j yrj − srj = yrj s.t.  r =1  n ∑ λ j = 1  j =1 λ , s − , s + ≥ 0; i = 1, 2, L , m; r = 1, 2, L , s; j = 1, 2, L , n  j ij rj

M AN U

m

(1)

TE D

where sij− and srj+ are the slack variables, n is the number of decision-making units (DMU),

m and s are the input and output of DMU respectively, xij depicts the input i of the DMUj,

EP

yrj depicts the output r of the DMUj, θ is the objective function value, and ε is a very small

AC C

positive number (generally set as 10−6 ). 3.2. Measures

Environmental management efficiency refers to the management performance resulting from environmental management and recycling. The environmental management efficiency level actually reflects the manufacturing industry’s capacity for environmental management under the same input conditions. One important process of environmental evaluation is the selection of indicators (Burger, 2008). Most environmental evaluations involve two-level indicators of input

10

ACCEPTED MANUSCRIPT

and output (e.g., Mickwitz et al., 2006; Zhang et al., 2008). As the efficiency of environmental management examines the management performance level based on certain inputs, it needs to select indicators from both the input of environmental management and the output of

require three inputs: capital, personnel, and facilities.

RI PT

management performance. Usually, to carry out environmental management activities, enterprises

We regarded annual expenditure of facilities for treatment (including annual expenditure for

SC

facilities for treatment of waste gas, wastewater, and solid wastes) as an indicator of capital input.

M AN U

Given the difference of the scale and input, we used the indicator ‘Expenditure of facilities for treatment per unit of output’ to measure the capital input for environmental governance. For environmental personal input, we used the indicator ‘Ratio of environmental personal’. We used the indicator ‘Quantity of facilities for treatment per unit of output’ for facilities input.

TE D

In selecting indicators for the output of management performance, and because our research focuses on the environmental management of the manufacturing industry, we used three indicators: ‘Ratio of industrial wastewater utilized’, ‘Ratio of industrial waste gas utilized’, and

EP

‘Ratio of industrial solid wastes utilized’. In addition, the output value of products made from

AC C

waste gas, wastewater, and solid wastes indicator can reflect more comprehensively the utilization capacity of major environmental pollutants in manufacturing industry, and is thus an important indicator of management performance. In order to eliminate the impact of industry, we divided the indicator above by the output value of manufacturing sectors, thus obtaining the output value of products made from the three wastes.

We can see from the indicators above that

our evaluation of environmental management efficiency involves the multi-index evaluation of three input indicators and four output indicators. We list those indicators in Table 1.

ACCEPTED MANUSCRIPT 11

Table 1-Evaluation indicators of the environmental management efficiency of manufacturing sectors Indicator Output volume of wastewater

Ratio of industrial wastewater utilized

Measurement Volume of industrial wastewater utilized for each manufacturing sector / Volume of industrial wastewater discharged for each manufacturing sector Volume of sulphur dioxide, smoke, and dust utilized for each manufacturing sector / Volume of sulphur dioxide, smoke, and dust discharged for each manufacturing sector

Ratio of industrial waste gas utilized

Output volume of solid wastes

Ratio of industrial solid wastes utilized

Output value of three wastes

Output value of products made from the three wastes

The value of products made from waste gas, wastewater, and solid wastes per unit of output

Capital input

Expenditure of facilities for treatment per unit of output

Annual expenditure of facilities for treatment of waste gas, wastewater, and solid wastes

Personnel input

Ratio of environmental personnel

The proportion of environmental personnel accounted for by the total employees for each manufacturing sector

Quantity of environmental personnel for each manufacturing sector / Quantity of annual average employees of each manufacturing sector

Facilities input

Quantity of facilities for treatment per unit of output

Quantity of facilities for treatment of waste gas, wastewater, and solid wastes per unit of output for each manufacturing sector

Quantity of facilities for treatment of waste gas, wastewater, and solid wastes for each manufacturing sector / Output value of each manufacturing sector

AC C

EP

TE D

M AN U

SC

Output volume of waste gas Output

Input

Explanation The proportion of the volume of industrial wastewater utilized accounted for the discharged volume of industrial wastewater for each manufacturing sector The proportion of the volume of sulphur dioxide, smoke, and dust utilized accounted for the discharged volume of sulphur dioxide, smoke, and dust for each manufacturing sector The proportion of the volume of industrial solid wastes utilized accounted for the volume of industrial solid wastes generated for each manufacturing sector

RI PT

Item

Note: CESY = China Environmental Statistical Yearbook; CSY = China Statistical Yearbook.

Volume of industrial solid wastes utilized for each manufacturing sector / Volume of industrial solid wastes generated for each manufacturing sector

Output value of products made from waste gas, wastewater, and solid wastes for each manufacturing sector / Output value of each manufacturing sector Annual expenditure of facilities for treatment of waste gas, wastewater, and solid wastes for each manufacturing sector / Output value of each manufacturing sector

Data source CESY (2002-2011)

CESY (2002-2011)

CESY (2002-2011) CESY (2002-2011); CSY (2002-2011) CESY (2002-2011); CSY (2002-2011) CESY (2002-2011); CSY (2002-2011). CESY (2002-2011); CSY (2002-2011)

12

ACCEPTED MANUSCRIPT 3.3. Data

The data were drawn from the China Environmental Statistical Yearbook (2002-2011) and the China Statistical Yearbook (2002-2011) (retrieval dates Jan. 2013 to Mar. 2013). The China

RI PT

Statistical Yearbook is published by the National Bureau of Statistics of China, while the China Environmental Statistical Yearbook is jointly published by the National Bureau of Statistics of

SC

China and the Ministry of Environmental Protection of China. The Statistical Yearbook for each year reports the industry-level environmental data of the previous year. In accordance with

M AN U

China’s Manufacturing Classified Standards, the sample consists of 29 manufacturing sectors (data from one industry, ‘Recycling and Disposal of Waste’, are partially missing, and so the sector is excluded from the study) and data were collected for the period 2001-2010.

TE D

4. Results

4.1. Analysis for the whole manufacturing industry

EP

Analysing the data using the DEAP 2.1 software, we obtained the environmental management efficiency of China’s whole manufacturing industry from 2001 to 2010, shown in Table 2 and

AC C

Figure 1.

Table 2-Environmental management efficiency of the whole manufacturing industry for 2001-2010 Year

TE a

PTE b

SE c

RTS d

2001 2002 2003 2004 2005 2006 2007 2008 2009

0.872 0.792 0.794 0.821 0.971 0.882 1.000 1.000 1.000

1.000 1.000 0.913 0.930 1.000 1.000 1.000 1.000 1.000

0.872 0.792 0.870 0.882 0.971 0.882 1.000 1.000 1.000

drs e drs drs drs drs drs --- f -----

13

ACCEPTED MANUSCRIPT 2010 Mean

1.000 0.913

1.000 0.984

1.000 0.927

-----

a

TE = Technical Efficiency; b PTE = Pure Technology Efficiency; c SE = Scale Sufficiency;

d

RTS = Returns to Scale; drs = Diminishing Returns to Scale; --- = Constant Returns to Scale.

e

f

2002

2003

2004

2005

2006

2007

2008

2009

2010

M AN U

2001

TE

SC

RI PT

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

Fig. 1-Environmental management efficiency (TE) of the whole manufacturing industry for 2001-2010

TE D

The results in Table 2 reveal that the manufacturing industry’s environmental management efficiency for this 10-year period is largely low. They show that only four years (2007-2010) were DEA efficient. Five years rate below the average DEA efficiency level. Additionally,

EP

environmental management efficiency decreased significantly from 2001 to 2004, far below the

AC C

average value of the decade under study, particularly the value of TE (technical efficiency), which was 0.792 in 2001. The main reason for such low numbers may be the lack of environmental awareness on the part of manufacturing management in China. It is also the case that many manufacturing enterprises did not comply with the environmental regulations (Hussey and Eagan, 2007), and that the government does not enforce manufacturing industry pollution controls, resulting in inefficient environmental management. Our results also indicate that the environmental management efficiency of the manufacturing

14

ACCEPTED MANUSCRIPT

industry improved rapidly from 2007, with a 0.118 increase over 2006, to reach the DEA efficient 1.0 mark. Table 3 shows the input and output results from our DEAP 2.1 data analysis for the 10-year

RI PT

period 2001-2010. Table 3-Input and output of the environmental management efficiency of the manufacturing industry for 2001-2010

Input Redundancy

Ratio of

Ratio of

Output Level

industrial

Industrial

Industrial

of Utilization

wastewater

Waste Gas

Solid Wastes

of the Three

utilized

Utilized

Utilized

2001

0.000

0.000

0.000

2002

0.000

0.000

0.000

2003

0.026

0.000

0.034

2004

0.009

0.000

0.009

2005

0.000

0.000

0.000

2006

0.000

0.000

0.000

2007

0.000

0.000

2008

0.000

0.000

2009

0.000

0.000

2010

0.000

0.000

Mean

0.003

0.000

Wastes

Quantity of

of Facilities

Ratio of

Facilities for

for Treatment

Environmenta

Treatment Per

Per Unit of

l personal

Unit of

Output

Output

0.000

0.000

0.000

0.000

0.036

0.000

0.000

0.026

0.018

0.000

0.000

0.009

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

TE D

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.000

0.004

0.003

0.005

0.000

0.000

EP

Year

Expenditure

M AN U

Ratio of

SC

Output Insufficiency

The results in Table 3 reveal input redundancy. For example, we found an input redundancy in

AC C

the facilities’ expenditure on treatment per unit of output of 360 Yuan and 180 Yuan respectively for manufacturing output per billion Yuan in 2002 and 2003. We also found output insufficiency. For example, for 2003-2004 we identified output insufficiency reductions in the ratio of industrial wastewater meeting discharge standards, from 2.6% (2003) to 0.9% (2004), and in the ratio of industrial solid wastes utilized, from 3.4% (2003) to 0.9% (2004). Moreover, we noted output insufficiency in the output level of utilization of the three wastes, from 260 Yuan RMB to 90 Yuan RMB for manufacturing output per billion Yuan RMB in 2003-2004. These results show

15

ACCEPTED MANUSCRIPT

that, although it is improving, the environmental management efficiency of the Chinese manufacturing industry still needs to improve.

4.2. Analysis for manufacturing sectors

RI PT

Using the DEA multi-stage analysis and DEAP 2.1 software, we obtained the environmental management efficiency for 29 manufacturing sectors, as well as the input and output of

SC

environmental management efficiency for 29 manufacturing sectors, as shown in Table 4 and

AC C

EP

TE D

M AN U

Table 5.

ACCEPTED MANUSCRIPT 16

Table 4-Environmental management efficiency (TE) of 29 manufacturing sectors for 2001-2010 2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

MTE a

Food Processing Food Manufacturing Beverage Manufacturing Tobacco Manufacturing Textile Manufacturing Garments and Other Fibre Products Leather, Furs, Down, and Related Products Timber Processing, Bamboo and Straw Products Furniture Manufacturing Papermaking and Paper Products Printing and Record Medium Reproduction Cultural, Educational, and Sports Goods Petroleum Processing and Coking Chemical Materials and Chemical Products Medical and Pharmaceutical Products Chemical Fibre Rubber Products Plastic Products Nonmetal Mineral Products Smelting and Pressing of Ferrous Metals Smelting and Pressing of Nonferrous Metals Metal Products Ordinary Machinery Special Equipment Transport Equipment Electrical Equipment and Machinery Electronic and Telecommunications Equipment Instruments, Meters, Cultural, and Office Machinery Crafts and Other Industries Mean

0.606 0.321 0.430 0.790 0.319 1.000 0.575 0.485 0.679 0.212 1.000 1.000 0.766 0.481 0.329 1.000 0.749 0.689 0.581 1.000 0.655 0.359 0.857 1.000 1.000 1.000 0.923

0.484 0.379 0.490 1.000 0.275 1.000 0.500 0.537 0.656 0.315 1.000 1.000 1.000 0.410 0.406 1.000 0.833 0.733 0.446 1.000 0.674 0.331 0.383 0.796 0.887 1.000 1.000

1.000 0.506 0.933 1.000 0.241 1.000 0.583 0.900 0.741 0.491 1.000 1.000 1.000 0.733 0.514 0.877 0.780 1.000 1.000 1.000 0.792 0.329 1.000 0.652 1.000 1.000 1.000

0.967 0.571 1.000 1.000 0.240 1.000 0.748 1.000 0.775 0.390 0.924 1.000 1.000 0.686 0.502 1.000 0.610 1.000 1.000 1.000 0.975 0.284 0.803 0.969 0.859 1.000 1.000

0.600 0.416 0.469 1.000 0.247 1.000 1.000 1.000 0.935 0.277 0.653 1.000 1.000 0.442 0.356 0.833 0.768 1.000 0.792 1.000 0.856 1.000 1.000 0.995 1.000 1.000 1.000

0.872 0.542 0.689 1.000 0.216 0.782 0.284 0.607 0.507 1.000 1.000 1.000 1.000 0.606 0.409 0.820 0.692 1.000 1.000 1.000 0.858 0.253 1.000 1.000 0.734 1.000 1.000

0.572 0.404 0.340 0.569 0.299 1.000 0.297 0.678 0.681 1.000 0.894 1.000 1.000 0.372 0.225 0.777 0.415 1.000 1.000 1.000 1.000 0.198 0.656 0.727 1.000 1.000 1.000

1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000

0.574 0.418 0.697 0.618 0.249 1.000 0.347 0.966 0.684 1.000 1.000 1.000 1.000 1.000 0.271 0.568 0.547 1.000 1.000 0.800 0.802 0.255 1.000 0.843 1.000 1.000 1.000

0.424 0.262 0.347 0.645 0.201 1.000 0.332 0.477 1.000 1.000 1.000 1.000 1.000 0.267 0.231 0.531 0.320 0.703 0.590 0.738 0.664 0.215 0.699 0.828 0.677 1.000 0.983

0.710 0.482 0.640 0.862 0.329 0.978 0.567 0.765 0.766 0.669 0.947 1.000 0.977 0.600 0.424 0.841 0.671 0.913 0.841 0.954 0.828 0.422 0.840 0.881 0.916 1.000 0.991

1.000

0.879

0.503

0.676

1.000

0.974

0.631

1.000

0.668

0.761

0.809

1.000 0.717

0.697 0.693

0.824 0.807

0.983 0.826

1.000 0.815

0.612 0.774

0.792 0.708

1.000 1.000

0.709 0.759

1.000 0.652

0.862 0.775

MTE = Mean of Technical Efficiency.

SC

M AN U

TE D

EP

AC C

a

RI PT

Manufacturing Sectors

ACCEPTED MANUSCRIPT 17

Table 5-Input and output of environmental management efficiency of 29 manufacturing sectors for 2001-2010

0.835 0.872 0.876 0.892 0.942 0.961 0.891 0.854 0.950 0.923 0.937 0.895 0.966 0.920 0.931 0.933 0.973 0.909 0.921 0.958 0.883 0.942 0.937 0.937 0.954 0.945 0.965

Output Level of Utilization of the Three Wastes

0.948 0.915 0.970 0.777 0.925 0.876 0.795 0.963 0.894 0.874 0.828 0.864 0.793 0.694 0.910 0.919 0.963 0.918 0.972 0.774 0.394 1.003 0.847 0.790 0.846 0.854 0.798

0.005 0.004 0.005 0.001 0.001 0.001 0.004 0.006 0.002 0.017 0.003 0.001 0.004 0.007 0.002 0.006 0.002 0.002 0.028 0.010 0.009 0.003 0.001 0.001 0.001 0.002 0.001

EP

AC C

SC

Food Processing Food Manufacturing Beverage Manufacturing Tobacco Manufacturing Textile Manufacturing Garments and Other Fibre Products Leather, Furs, Down, and Related Products Timber Processing, Bamboo and Straw Products Furniture Manufacturing Papermaking and Paper Products Printing and Record Medium Reproduction Cultural, Educational, and Sports Goods Petroleum Processing and Coking Chemical Materials and Chemical Products Medical and Pharmaceutical Products Chemical Fibre Rubber Products Plastic Products Nonmetal Mineral Products Smelting and Pressing of Ferrous Metals Smelting and Pressing of Nonferrous Metals Metal Products Ordinary Machinery Special Equipment Transport Equipment Electrical Equipment and Machinery Electronic and Telecommunications Equipment Instruments, Meters, Cultural, and Office Machinery Crafts and Other Industries Mean

Ratio of Industrial Solid Wastes Utilized

M AN U

Ratio of industrial wastewater utilized

Input Redundancy Expenditure of Facilities for Treatment Per Unit of Output 0.003 0.004 0.004 0.000 0.007 0.002 0.003 0.002 0.002 0.013 0.001 0.001 0.004 0.006 0.003 0.006 0.001 0.001 0.008 0.007 0.007 0.004 0.001 0.001 0.001 0.001 0.001

TE D

Manufacturing Sectors

Ratio of Industrial Waste Gas Utilized 0.771 0.792 0.711 0.811 0.804 0.821 0.736 0.752 0.858 0.831 0.773 0.801 0.782 0.843 0.813 0.905 0.856 0.771 0.786 0.898 0.888 0.740 0.743 0.809 0.865 0.786 0.849

RI PT

Output Insufficiency

0.005 0.005 0.007 0.002 0.006 0.001 0.002 0.003 0.001 0.019 0.001 0.001 0.008 0.008 0.005 0.008 0.002 0.001 0.009 0.004 0.006 0.007 0.002 0.001 0.001 0.001 0.001

Quantity of Facilities for Treatment Per Unit of Output 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000

Ratio of Environmental personal

0.957

0.758

0.782

0.001

0.001

0.002

0.000

0.946 0.924

0.699 0.802

0.923 0.855

0.001 0.005

0.001 0.003

0.001 0.004

0.000 0.000

18

ACCEPTED MANUSCRIPT

The results in Table 4 report two important and interesting findings: the mean technical efficiency (MTE) for each manufacturing sector for the 10-year study period and the mean TE for all manufacturing sectors for each year. The former can reveal the average environmental

RI PT

management efficiency of each manufacturing sector for each year between 2001 and 2010, while the latter can reveal the environmental management efficiency of all manufacturing sectors. The MTE values shown in Table 4 reveal that the environmental management of most

SC

manufacturing sectors for the 10-year period under study was largely inefficient. However, the

M AN U

environmental management efficiency for some high-energy consumption and high-pollution sectors was relatively high. For example, the environmental management of the electrical equipment and machinery and cultural, educational, and sporting goods sectors maintained DEA efficiency for the duration of the study period. Manufacturing sectors such as garments and other

TE D

fibre products and petroleum processing and coking maintained DEA efficiency for nine years out of 10. The smelting and pressing of ferrous metals and the electronic and telecommunications equipment sectors maintained DEA efficiency for eight years. In addition, environmental

EP

management efficiency was also high in printing and record medium reproduction (MTE = 0.947),

AC C

transport equipment (MTE = 0.916), and plastic products (MTE = 0.913). However, some high-pollution manufacturing sectors had low environmental management efficiency. The medical and pharmaceutical products, textile manufacturing, food manufacturing, and beverage manufacturing sectors failed to achieve DEA efficiency in nine of 10 years. Chemical materials and products and leather, furs, down, and related products failed to achieve DEA efficiency in eight years. The MTE value of nine manufacturing sectors (textile manufacturing; metal products; medical and pharmaceutical products; food; leather, furs, down,

19

ACCEPTED MANUSCRIPT

and related products; chemical materials and products; beverages; papermaking and paper products; and rubber products) was lower than the average MTE for the whole manufacturing sector over the 10-year period.

RI PT

The mean results shown in Table 4 reveal the environmental management efficiency of the whole manufacturing sector for the years under study. These show that the environmental management of all manufacturing sectors maintained DEA efficiency for the year 2008.

SC

Environmental management efficiency was also high in 2003, 2004, and 2005. Overall, however,

M AN U

the findings reveal that the environmental management of all manufacturing sectors for most years between 2001 and 2010 was largely inefficient.

Our results also indicate that the environmental management efficiency of most sectors was in a state of oscillation during the study period (see Fig. 2). The oscillation amplitude for food

TE D

manufacturing, metal products and textile manufacturing is relatively large. The food processing, food manufacturing, beverages, leather, furs, down, and related products, timber processing, bamboo and straw products, chemical materials and products, rubber products, and metal

EP

products sectors show downward trends in the last two years. As the environmental management

AC C

efficiency of all 29 manufacturing sectors in 2008 was 1.000, revealing that all manufacturing sectors maintained DEA efficiency, the figure is in a steady state. The results also show that the environmental management efficiency in the year 2010 was trending down (mean = 0.652). The possible reason for this is as follows. Affected by the global financial crisis in 2008, the development speed of the Chinese manufacturing industry slowed down. In 2009 in particular, the output value of the manufacturing industry fell rapidly. As a result, many firms reduced the input for environmental management in order to survive, which resulted in the lower

20

ACCEPTED MANUSCRIPT environmental management efficiency for 2010. 1.0 0.9 0.8 0.7

RI PT

0.6 0.5 0.4 0.3

0.1 0.0 2002

2003

2004

Food Processing

2005

2006

2007

2008

2009

2010

Food Manufacturing

Beverage Manufacturing Textile Manufacturing

M AN U

2001

SC

0.2

Tobacco Manufacturing Garments and Other Fiber Products

Leather, Furs, Down and Related Products

Timber Processing, Bamboo and Straw Products

Furniture Manufacturing

Papermaking and Paper Products

Printing and Record Medium Reproduction

Cultural, Educational and Sports Goods

Petroleum Processing and Coking

Chemical Materials and Chemical Products

Medical and Pharmaceutical Products Rubber Products

Chemical Fiber

Plastic Products

TE D

Nonmetal Mineral Products

Smelting and Pressing of Ferrous Metals

Smelting and Pressing of Nonferrous Metals

Metal Products

Ordinary Machinery

Special Equipment

Transport Equipment

Electric Equipment and Machinery

Electronic and Telecommunications Equipment

Instruments, Meters, Cultural and Office Machinery

EP

Crafts and other industries

Fig. 2-Environmental management efficiency for 29 manufacturing sectors for 2001-2010

AC C

The results in Table 5 report two important findings: the mean of four indicators of output insufficiency and the mean of three indicators of input redundancy for all manufacturing sectors. The output insufficiency in the ratio of industrial wastewater utilized, the ratio of industrial waste gas utilized, and the ratio of industrial solid wastes utilized in the 29 manufacturing sectors is alarming and fell by an average of 92.4%, 80.2%, and 85.5% respectively. The results reveal input redundancy and output insufficiency in all 29 manufacturing sectors over the 10-year study period. In addition, Table 5 shows similarly disturbing results for the output insufficiency in the

21

ACCEPTED MANUSCRIPT

ratio of industrial wastewater utilized for textile manufacturing, petroleum processing and coking, and electronic and telecommunications equipment, and the output insufficiency in the ratio of industrial waste gas utilized for smelting and pressing of both ferrous and nonferrous metals. In

RI PT

addition, the output insufficiency in the ratio of industrial solid wastes utilized for metal products, rubber products, timber processing, bamboo and straw products is also a concern.

Moreover, all 29 manufacturing sectors exhibit input redundancy in facilities’ expenditure on

SC

treatment per unit of output, 30 Yuan for manufacturing output per billion Yuan. Additionally,

M AN U

they all have input redundancy in the ratio of 40 environmental personnel per million employees. No input redundancy exists for the quantity of facilities for treatment per unit of output. This suggests that the current ratio of facilities for treatment of environmental management for these 29 sectors is relatively reasonable.

TE D

To examine the specific environmental management efficiency categories of the 29 manufacturing sectors more closely, the Hierarchical Clustering method is used. The results are shown in Figure 3. The 29 manufacturing sectors are divided into four categories, each containing

EP

a relatively uniform number of sectors. The sectors are divided according to their average

AC C

environmental management efficiency for the period 2001-2010.

22

TE D

M AN U

SC

RI PT

ACCEPTED MANUSCRIPT

Fig.3-Dendrogram of hierarchical clustering for the environmental management efficiency of manufacturing sectors

EP

The results indicate that the environmental management efficiency of nine manufacturing

AC C

sectors – garments and other fibre products (MTE = 0.978), printing and record medium reproduction (MTE = 0.947), cultural, educational, and sporting goods (MTE = 1.000), petroleum processing and coking (MTE = 0.977), transport equipment (MTE = 0.916), electrical equipment and machinery (MTE = 1.000), electronic and telecommunications equipment (MTE = 0.991), plastic products (MTE = 0.913), and smelting and pressing of ferrous metals (MTE = 0.954) – is very high. Moreover, the environmental management efficiency is relatively high in tobacco

23

ACCEPTED MANUSCRIPT

manufacturing (MTE = 0.862), timber processing, bamboo and straw products (MTE = 0.765), furniture manufacturing (MTE = 0.766), ordinary machinery (MTE = 0.840), special equipment (MTE = 0.881), instruments, meters, cultural, and office machinery (MTE = 0.809), crafts and

RI PT

other industries (MTE = 0.862), chemical fibre (MTE = 0.841), nonmetal mineral products (MTE = 0.841), and smelting and pressing of nonferrous metals (MTE = 0.828).

However, the environmental management efficiency of six manufacturing sectors is relatively

SC

low: food processing (MTE = 0.710), beverages (MTE = 0.640), leather, furs, down, and related

M AN U

products (MTE = 0.567), papermaking and paper products (MTE = 0.669), chemical materials and products (MTE = 0.600), and rubber products (MTE = 0.671).

For four manufacturing sectors, food manufacturing (MTE = 0.482), textile manufacturing (MTE = 0.329), medical and pharmaceutical products (MTE = 0.424), and metal products (MTE

TE D

= 0.422), the environmental management efficiency is very low.

The results of these categories for environmental management efficiency reveal that each category has a different level of environmental management efficiency. Thus, distinguishing

EP

policies are required for different categories to assist with improvement to environmental

AC C

management efficiency and sustainable development. Some manufacturing sectors have more advanced technology, higher management levels, and higher quality human resources, which undoubtedly use resources more efficiently and discharge fewer pollutants. Thus, the central government should provide more technical and financial resources and assistance to the manufacturing sectors with inefficient environmental management.

5. Discussions and conclusions Environmental management has attracted global attention in recent years. Environmental

24

ACCEPTED MANUSCRIPT

management of the Chinese manufacturing industry is becoming more and more urgent. Using real Chinese manufacturing industry data from the period 2001-2010, our study has explored the environmental management efficiency of Chinese manufacturing sectors by taking various

RI PT

outputs and inputs into account to develop a DEA-based model. We found that the environmental management of Chinese manufacturing sectors exhibits more DEA inefficiency than efficiency. Environmental management efficiency showed a significant decline before 2004, but rapid

SC

growth from 2007. There was also input redundancy and output insufficiency in the period

M AN U

2002-2004. The results for 29 manufacturing sectors show that the environmental management of most manufacturing sectors was largely inefficient over the 10-year period under study. However, there are some counterintuitive findings which indicate that the environmental management efficiency of some high-energy consumption and high-pollution manufacturing sectors is

TE D

relatively high. The reason may be that these high-energy consumption and high-pollution manufacturing sectors are usually the key industries monitored by the Ministry of Environmental Protection of the People’s Republic of China (usually involving 24-hour environmental

EP

monitoring by the National Monitoring Centre of Environment), so the environmental

AC C

management efficiency of these industries is usually high. Conversely, the environmental management efficiency of the food manufacturing, textile manufacturing, medical and pharmaceutical products, and metal products sectors is very low. This suggests that reducing raw material inputs and pollution emissions is the most urgent task facing China in its efforts to promote environmental management (Zhang et al., 2008). Overall, we found that the environmental management efficiency of the Chinese manufacturing industry is low. Manufacturing enterprises are the main targets of environmental management in

25

ACCEPTED MANUSCRIPT

China. Generally, manufacturing enterprises have two ways to participate in environmental management: active and passive. Passive participation means that they solve environmental problems to comply with government regulations and avoid fines or other repercussions, such as

RI PT

repeated media exposure. This is the most common approach taken by Chinese manufacturing firms, especially SMEs. As Hussey and Eagan (2007) indicated, the main reason for the low environmental management efficiency of global SMEs is noncompliance with environment

M AN U

aimed at sustainability (Moussiopoulos et al., 2010).

SC

regulations. Environmental protection and restoration also require all mitigation efforts to be

5.1. Contributions and managerial implications

This study explored the environmental management efficiency of the Chinese manufacturing industry from the perspective of the inputs and outputs of environmental management and offers

TE D

three theoretical insights. First, compared with similar studies in developed countries, which mainly analyse the relationships between environmental pollution and economic performance (Hughey et al., 2005; Montabon et al., 2007), this study contributes to the environmental

EP

management literature by evaluating the environmental management efficiency of the

AC C

manufacturing industry and providing empirical data. Second, this study shows how a focus on environmental indicators of input and output might significantly advance our understanding of how to improve the environmental management efficiency of the manufacturing industry. The study extends knowledge by identifying input redundancy and output insufficiency, contributing to the literature by providing deeper insights into the causes and the input and output allocation mechanism of environmental management efficiency, which could inform policy-making for environmental management in China. Third, some previous work focused on environmental

26

ACCEPTED MANUSCRIPT

management from the point of view of country, region, or city (Moussiopoulos et al., 2010; Huang et al., 2010). This study extends previous studies by taking the perspective of the manufacturing industry. Fourth, some previous work focused on environmental management in

RI PT

developed countries (Hughey et al., 2005; Montabon et al., 2007; Rodriguez et al., 2011). This study explored the environmental management efficiency of manufacturing based on Chinese data, and thus provides some new findings for emerging economies.

SC

This study also highlights important implications and makes recommendations for

M AN U

policy-makers and practitioners concerned about environmental management. First, the government needs to strengthen its role in the environmental management of the manufacturing industry. On one hand, the government should increase environmental protection and management awareness. On the other, as policy proves to be conducive to sustainable

TE D

development within the industry (Liu et al., 2010), the government could introduce policies that encourage capital investment in low-carbon environmental industries. In addition, an independent monitoring information system could be set up to monitor key industries closely and provide

EP

early warning of potential problems (Burger, 2008; Leitao and Ahern, 2002). Second,

AC C

manufacturing enterprises need to enhance their environmental management by taking the initiative to develop environmental security technology and environmentally friendly products. Third, industry associations could provide environmental management leadership by guiding and regulating enterprise behaviour, and coordinating relationships between government and enterprises. The Chinese industry associations differ from those in western countries in that they are set up under government intervention. This means that the functional position of Chinese industry associations is quite different from that of western equivalents. Therefore, it is necessary

27

ACCEPTED MANUSCRIPT

to give industry associations the freedom to support manufacturing enterprises with environmental management. Thus, industry associations should coordinate actively with government departments, news media, and the public to provide appropriate guidance and help to

RI PT

enterprises. For instance, training activities on environmental security can be coordinated to increase the acceptance of environmental management. At the same time, industry associations also need to assist government in monitoring and inspecting the environmental security of

SC

enterprises.

M AN U

Theoretical implications and managerial implications are listed in Table 6. Table 6-Theoretical and managerial implications Theoretical Implications

Managerial Implications

Implications

Explored environmental management efficiency

● Evaluated the environmental management efficiency of the manufacturing industry ● Provided empirical validation for the environmental management efficiency of the manufacturing industry

Implications

Government

● Increase environmental protection and management awareness ● Introduce policies that encourage capital investment in low-carbon industries ● Set up an independent monitoring information system to monitor key industries closely

● Identified input redundancy and output insufficiency ● Gained deeper insights into the causes and mechanism of environmental management efficiency ● Extended previous studies with the perspective of the manufacturing industry

Industry associations

● Guide enterprise behaviour, and coordinate relationships between government and enterprises ● Provide training activities on environmental security ● Assist government in monitoring and inspecting the environmental security of enterprises

● Provided new findings for emerging economies

Manufacturing enterprises

● Develop environmental security technology and environmentally friendly products

EP

AC C

Identified the causes and mechanism

Perspectives

TE D

Perspectives

Perspective of manufacturing industry Data from emerging economies

28

ACCEPTED MANUSCRIPT 5.2. Limitations and future research

There are several limitations to this study that may inspire future research. Most notably, our findings are derived from data for Chinese manufacturing sectors, making them industry-specific.

RI PT

Future studies may use data from other industries and explore their impact on the Chinese economy with more demographic information to test and extend the generalizations we have found. Next, due to a lack of available data from the China Environmental Statistics Yearbook, we

SC

utilized only seven indicators to evaluate the environmental management efficiency of China’s

M AN U

manufacturing industry. As a result, we ignored some environmental management factors. Third, future research should explore some interesting issues, such as exploring the relationship between environmental management and economic output of the manufacturing industry, or using the

AC C

EP

TE D

environmental DEA technology to explore environmental management more accurately.

29

ACCEPTED MANUSCRIPT

ACKNOWLEDGEMENTS This research was supported by the National Natural Science Foundation of China (Grant number: 71002053, 71472118), the Shanghai Planning Fund of Philosophy and Social Sciences (Grant

RI PT

number: 2014BGL011), and “Shu Guang” project of Shanghai Municipal Education Commission

AC C

EP

TE D

M AN U

SC

and Shanghai Education Development Foundation (Grant number: 13SG41).

30

ACCEPTED MANUSCRIPT REFERENCES

Amores, M. J., Meneses, M., Pasqualino, J., Antón, A., Castells, F., 2013. Environmental assessment of urban water cycle on Mediterranean conditions by LCA approach. Journal of Cleaner Production 43, 84-92. Baird, R.C., 2005. On sustainability, estuaries, and ecosystem restoration: the art of the practical. Restoration

RI PT

Ecology 13(1), 154-158. Brandes, O.M., Brooks, D. B., 2005. The Soft Path in a Nutshell. University of Victoria, Victoria, BC. Page 8. Burger, J., 2008. Environmental management: integrating ecological evaluation, remediation, restoration, natural resource damage assessment and long-term stewardship on contaminated lands. Science of the Total

SC

Environment 400(1), 6-19.

Burger, J., Gochfeld, M., Powers, C.W., 2007. Integrating long-term stewardship goals into the remediation

M AN U

process: natural resource damages and the Department of Energy. Journal of Environmental Management 82(2), 189-99.

Burger, J., Leschine, T.M., Greenberg, M., Karr, J., Gochfeld, M., Powers, C.W., 2003. Shifting priorities at the department of energy’s bomb factories: protecting human and ecological health. Environmental Management 31(2), 157-167.

TE D

Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring efficiency of decision making units. European Journal of Operational Research 2, 429-444.

Costanza, R., 1992. Toward an operational definition of health. In: Costanza R, eds. Ecosystem Health: New

EP

Goals for Environmental Management. Washington DC: Island Press, 239-256. Crowley, K.D., Ahearne, J.F., 2002. Managing the environmental legacy of U.S. nuclear-weapons production.

AC C

American Scientist 90(6), 514-523.

Fang, Q., Zhang, D.L., Wong, L. N. Y., 2011. Environmental risk management for a cross interchange subway station construction in China. Tunnelling and Underground Space Technology 34(3), 1-14. Graymore, M., Wallis, A., Richards, A., 2009. An index of regional sustainability: a GIS-based multiple criteria analysis decision support system for progressing sustainability. Ecological Complexity 6(4), 453-462. He, G.Z., Lu, Y.L., Ma, H., Wang, X.L., 2007. Multi-indicator assessment of water environment in government environmental auditing. Journal of Environmental Sciences 19, 494-501. Hermann, B.G., Kroeze, C., Jawjit, W., 2007. Assessing environmental performance by combining life cycle assessment, multi-criteria analysis and environmental performance indicators. Journal of Cleaner Production

31

ACCEPTED MANUSCRIPT 15(18), 1787-1796.

Huang, G.H., Sun, W., Nie, X.H., Qin, X.S., Zhang, X.D., 2010. Development of a decision-support system for rural eco-environmental management in Yongxin County, Jiangxi Province, China. Environmental Modelling and Software 25(1), 24-42.

RI PT

Hughey, K.F.D., Tait, S.V., Connell, M.J. O., 2005. Qualitative evaluation of three ‘environmental management systems’ in the New Zealand wine industry. Journal of Cleaner Production 13(12), 1175-1187. Hussey, D. M., Eagan, P.D., 2007. Using structural equation modeling to test environmental performance in small and medium-sized manufacturers: can SEM help SMEs? Journal of Cleaner Production 15(4),

SC

303-312.

Klang, A., Vikmana, P.A., Brattebø, H., 2003. Sustainable management of demolition waste—an integrated

M AN U

model for the evaluation of environmental, economic and social aspects. Resources, Conservation and Recycling 38, 317-334.

Kurtz, J., Jackson, L., Fisher, W., 2001. Strategies for evaluating indicators based on guidelines from the Environmental Protection Agency’s Office of Research and Development. Ecological Indicators 1(1), 49-60. Lee, S.-H., Choi, K. I., Osako, M., Dong, J. I., 2007. Evaluation of environmental burdens caused by changes

TE D

of food waste management systems in Seoul, Korea. Science of the Total Environment 387(1), 42-53. Leitao, A.B., Ahern, J., 2002. Applying landscape ecological concepts and metrics in sustainable landscape planning. Landscape Urban Plan 59(2), 65-93.

Li, F., Liu, X., Hu, D., Wang, R., Yang, W., Li, D., Zhao, D., 2009. Measurement indicators and an evaluation

EP

approach for assessing urban sustainable development: a case study for China’s Jining City. Landscape Urban Plan 90(3-4), 134-142.

AC C

Liu, L., Ma, X.M., 2010. Technology-based industrial environmental management: a case study of electroplating in Shenzhen, China. Journal of Cleaner Production 17(18), 1731-1739. Liu, X.B., Liu, B.B., Shishime, T., Yu, Q.Q., Bi, J., Fujitsuka, T., 2010. An empirical study on the driving mechanism of proactive corporate environmental management in China. Journal of Environmental Management 91(8), 1707-1717. Mickwitz, P., Melanen, M., Rosenström, U., Seppälä, J., 2006. Regional eco-efficiency indicators: a participatory approach. Journal of Cleaner Production 14, 1603-1611. Montabon, F., Sroufe, R., Narasimhan, R., 2007. An examination of corporate reporting, environmental management practices and firm performance. Journal of Operations Management 25(5), 998-1014.

32

ACCEPTED MANUSCRIPT

Moussiopoulos, N., Achillas, C., Vlachokostas, C., Spyridi, D., Nikolaou, K., 2010. Environmental, social and economic information management for the evaluation of sustainability in urban areas: a system of indicators for Thessaloniki, Greece. Cities 27(5), 377-384. Peiro-Signes, A., Segarra-Ona, M., Mondejar-Jimenez, J. et al., 2013. Influence of the environmental, social

RI PT

and corporate governance ratings on the economic performance of companies: an overview. International Journal of Environmental Research 7(1), 105-112.

Peris-Mora, E., Diez Orejas, J.M., Subirats, A., Ibáñez, S., Alvarez, P., 2005. Development of a system of indicators for sustainable port management. Marine Pollution Bulletin 50(12), 1649-1660.

Dalian, China. Journal of Cleaner Production 52, 176-184.

SC

Qu, Y., Zhu, Q., Sarkis, J., Geng, Y., Zhong, Y., 2013. A review of developing an e-wastes collection system in

M AN U

Rees, W. E., 1992. Ecological Footprints and appropriated carrying capacity: what urban economics leaves

out. Environment and Urbanization 4(2), 121-130.

Rodriguez, G., Alegre, F.J., Martinez, G., 2011. Evaluation of environmental management resources (ISO 14001) at civil engineering construction worksites: a case study of the community of Madrid. Journal of Environmental Management 92(7), 1858-1866.

TE D

Schulze, P. C., Frosch, R.A., 1999. Overview: Measures of Environmental Performance and Ecosystem Condition. Washington, DC: National Academy Press. Scipioni, A., Mazzi, A., Mason, M., Manzardo, A., 2009. The dashboard of sustainability to measure the local urban sustainable development: the case study of Padua Municipality. Ecological Indicators 9(2), 364-380.

EP

Srdjevic, B., Medeiros, Y.D.P., Porto, R.L.L., 2005. Data envelopment analysis of reservoir system performance. Computers & Operations Research 32, 3209-3266.

AC C

Tanguay, G., Rajaonson, J., Lefebvre, J-F., Lanoie, P., 2010. Measuring the sustainability of cities: an analysis of the use of local indicators. Ecological Indicators 10(2), 407-418. Valentin, A., Spangenberg, J., 2000. A guide to community sustainability indicators. Environmental Impact Assessment Review 20(3), 381-392. Vencheh, A.H., Matin, R.K., Kajani, M.T., 2005. Undesirable factors in efficiency measurement. Applied Mathematics and Computation 163, 547-552. Vrscaj, B., Poggio, L., Marsan, F. A., 2008. A method for soil environmental quality evaluation for management and planning in urban areas. Landscape and Urban Planning 88(4), 81-94. Yuan, W., James, P., Hodgson, K., Hutchinson, S.M., Shi, C., 2003. Development of sustainability indicators

33

ACCEPTED MANUSCRIPT

by communities in China: a case study of Chongming County, Shanghai. Journal of Environmental Management 68(3), 253-261. Zeng, S.X., Meng, X.H., Zeng, R.C., Tam, C.M., Tam, V.W.Y., Jin, T., 2011. How environmental management driving forces affect environmental and economic performance of SMEs: a study in the Northern China

RI PT

district. Journal of Cleaner Production 19(13), 1426-1437. Zeng, S.X., Xie, X.M., Tam, C.M., 2010. Relationship between cooperation networks and innovation performance of SMEs. Technovation 30(3), 181-194.

Zhang, B., Bi, J., Fan, Z.Y., Yuan, Z.W., Ge, J.J., 2008. Eco-efficiency analysis of industrial system in China: a

SC

data envelopment analysis approach. Ecological Economics 68, 306-316.

Zhu, Q., Sarkis, J., 2007. The moderating effects of institutional pressures on emergent green supply chain

M AN U

practices and performance. International Journal of Production Research 45(18-19), 4333-4355. Zhu, Q., Sarkis, J., Lai, K.H., 2007a. Initiatives and outcomes of green supply chain management implementation by Chinese manufacturers. Journal of Environmental Management 85, 179-189. Zhu, Q., Sarkis, J., Lai, K.H., 2007b. Green supply chain management: pressures, practices and performance

AC C

EP

TE D

within the Chinese automobile industry. Journal of Cleaner Production 15(11-12), 1041-1052.