Intuitionistic fuzzy measures of enterprise Eco-efficiency and its influencing factors

Abstract

As the theme of sustainable development in the 21st century, environmental management creates value through the combination of ecological and economic elements and forms the enterprise Eco-efficiency. Enterprise Eco-efficiency can not only measure the performance of the company’s environmental management, but also guide the implementation of enterprise environmental management strategy and the realization of business objectives. There is a mutual causal relationship between environmental management and enterprise Eco-efficiency. Based on the analysis of the forming mechanism of enterprise Eco-efficiency within the environmental management system, it is found that whether the place influencing factors or vicissitude influencing factors, their impacts on the enterprise Eco-efficiency measurement value may be uncertain and ambiguous. In this paper, the similarity model of intuitionistic fuzzy set is established to conduct the intuitionistic fuzzy identification of the enterprise Eco-efficiency influencing factors, and a large-scale oil refining and chemical company is used as an example for application testing to determine measurement effectiveness.

Keywords

Enterprise Eco-efficiency environmental management place influencing factor vicissitude influencing factor intuitionistic fuzzy identification

1. Introduction

The concept of Eco-efficiency was first proposed in academia by Schaltegger and Sturm in 1990, which demonstrates the ratio of increased value to increased environmental impact [1]. The World Business Council for Sustainability Development (WBCSD) has made the concept of Eco-efficiency widely disseminated and universally accepted. The core idea of Eco-efficiency “Minimizing environmental impact, maximizing economic value” has exerted great influence in the industry and academia [2]. But how can the Eco-efficiency be improved by minimizing the environmental impact and maximizing the economic value? Which factors could affect the Eco-efficiency numerator and denominator and thus to determine the level of Eco-Efficiency? This is a question that is of practical significance to study.

2. Enterprises Eco-efficiency and its formation mechanism based on environmental management

2.1. The concept of enterprises Eco-efficiency based on environmental management

The object of Eco-efficiency measurement was divided into three different levels by academia: regional level, industry level and enterprise level. WBCSD presented the definition and expression of Eco-efficiency in an industrial sense [3]. Different Eco-efficiency objects determine the different descriptive indicators of “economic value” and “environmental impact” for the numerator and denominator in the Eco-efficiency expression, the different corresponding measurement methods, and the different specific Eco-efficiency affecting factors [4]. Therefore, the canonical expression of Eco-Efficiency’s numerator and denominator should be determined on the premise of a certain Eco-efficiency measurement object.

With the development of ecological economy, environmental management has been integrated into the theme of sustainable development in the 21st century. The new concept of “environmental management” and the new business model are increasingly being put into practice in many countries [5]. The environmental management model is a new business model that adapts to the ecological economy, which considers environmental factors from a strategic perspective and pursues reduction of the environmental load during the entire production and management process [6]. It provides a strategy to solute the environmental issues in business operations by a holistic, strategic, and preventive approach. The essence of environmental management is to organically integrate the environment and economy in the business activities and create values through the combination of ecological environmental factors and economic factors [7]. This is reflected in the business objectives and business behaviors that reduce environmental costs and increase resource utilization value [8]. Therefore, on the attitude of the ecological environment and the business objectives, principles and ideas, enterprise environmental business model and Eco-efficiency have a complete compatibility. Only when the enterprise adopts an environmental management model can it form a high level of Eco-efficiency. The Eco-efficiency measurement value can not only measure the performance of the company’s environmental management, but also encourage and induce the implementation of the business strategy that is conducive to the realization of the environmental management goals. Eco-efficiency has a causal relationship with environmental management [9].

This paper proposes the concept of Enterprise’s Eco-efficiency (EE2) based on environmental management, that is, the ratio of the ecological economic results obtained by the company’s environmental management to the resulting ecological environmental impact, that also is, the ecological economic benefits generated by the unit ecological pressure and the intensity of resources. The definition of ecological environmental impact involves both the consumption of ecological and environmental resources and the pollution of the ecological environment. Taking the ecological environment as a resource is a much profound and comprehensive understanding of the concept of resources, and it can better reflect the concept and essence of resources. The purpose of using the ecological environment as a resource is to urge the company to cherish the ecological environment as much as it cherishes the economic resources, to meticulously protect the ecological environment, and to economically use the ecological resource, thereby to effectively implement the environmental management model.

2.2. Theoretical expressions of enterprise’s Eco-efficiency

The object of EE2 measurement is the resource allocation efficiency of the environmental management system. It represents the extent to which the system resources are effectively used, and the ecological environment is effectively protected, and describes the information of the input, output, flow, and inventory of various resources of the system. In order to fulfill the requirements of measuring the resource allocation efficiency on enterprise environmental management systems, to meet the needs of information for environmental management decision-making, control, and evaluation, and to depicts the ecological economic results achieved by the company’s environmental management and the resulting ecological environmental impacts, this paper proposed the concept of EE2 based on environmental management, which could be further described as “the ratio of ecological economic benefit to ecological environmental load” of environmental management, and could be further expressed by the following formula:

$\begin{matrix} EE 2 = Ecological Economic Benefit / (Positive \\ Ecological Resource + Negative Ecological \\ Resource) \end{matrix}$ (1)

The essence of EE2 represented by formula (1) is the resource allocation efficiency of the enterprise environmental management system. The positive eco-resource of the denominator formula (1) is expressed by its input (physical quantity or amount), and the negative eco-resource is expressed by its output (physical quantity or amount). They correspond to the “utilization of resources and energy and its environmental pressure” in the denominator of the Eco-efficiency theoretical definition. According to relevant literature, ecological environment resources can be divided into positive and negative categories from the perspective of corporate environmental management [10]. Positive eco-environmental resources (abbreviated as positive eco-resources) are defined in this paper as eco-environmental resources that are beneficial to the conduction of corporate production and business activities, and the creation of corporate value; negative eco-environmental resources (abbreviated as negative eco-resources) are defined as the pressure on the ecological environment caused by the business production and operation. The input on positive ecological resources and the output of negative ecological resources in this paper are corresponding to Eco-efficiency’s denominator “resource and energy use and its environmental pressure” [11]. The value of the products and services of Eco-efficiency’s molecules, formula (1) is expressed in terms of eco-economic returns, which is an objective and specific representation of the value of products and services in the context of the enterprise’s environmental management. Thus, formula (1) is well matches the WBCSD theoretical definition of the Eco-efficiency.

2.3. Enterprise’s Eco-efficiency formation mechanism

EE2, as the resource allocation efficiency of the enterprise environmental management system, its measurement is related to the variation of the ecological environment resources and economic resources of the enterprise environmental management system, and the level of its measurement is determined by the stock and variation of the enterprise environmental management system resources. The econ is used to indicate the system’s economic resource stock (the net stock of economic resources produced by the system after deducting economic resources input over a period of time), and ecol⁺ indicates the positive eco-environment resource stock of the system (the net stock of the positive result of the system deducting positive eco-resources consumed over a period of time), ecol^- indicates the system’s negative eco-environment resource stock (the total amount of negative eco-system resources accumulated by the system over a period of time).

From the period of t₀ to t₁, econ₀ is the initial stock of economic resources, econ₁ is the stock of changed economic resources, ${ecol}_{0}^{+}$ is the initial positive eco-environment resource stock, and ${ecol}_{1}^{+}$ is the positive stock of environmental resources after the change, ${ecssocol}_{0}^{-}$ is the initial negative eco-environment resource stock, ${ecol}_{1}^{-}$ is the stock of negative eco-environment resources after the change, and Δ indicates the difference beforeand after the change of various resources. Then: $\begin{matrix} Δ econ = {econ}_{1} - {econ}_{0}, Δ {ecol}^{+} = {ecol}_{1}^{+} \\ - {ecol}_{0}^{+}, Δ {ecol}^{-} = {ecol}_{1}^{-} - {ecol}_{0}^{-} \end{matrix}$

The EE2 represents the measure of the company’s eco-economic efficiency, and the ΔEE2 represents the difference before and after the EE2 measure change.

The elements of the enterprise environmental management system are divided into two categories. One is the set of various elements that consist the system which collectively referred to as the Place(P), and P ={ P₁, P₂, …, P_m }. Another is the mechanisms that represents the variance of system elements which collectively referred to as Transitions(T), T ={ T₁, T₂, …, T_n }; and F is defined as a ordered pair collection consisting of a P-type element and a T-type element, F = {(P_i, T_j) or (T_j, P_i) |P_i ∈ P , T_j ∈ T}, then F ⊆ (P × T) ∪ (T × P), F is called flow, then the corporate environmental management system is represented by the triple network N ={ P, T, F }. P is a finite set of entities and T is a set of finite transitions (mechanisms). Dom(F) ⊆ (P × T) is the input set, and cod(F) ⊆ (T × P) is the output set. The network figure represents the Place by a circle, the Transition is indicated by a box, and the relationship between the two types of elements such as association, dependence, and influence is represented by arrows [12]. The enterprise environmental management system Place P has various resources such as economic resources, positive, negative ecological environment resources and information resources. Define M(P) as the stock of resources for Place P. W(P, T) indicates the amount of change in Place P resources caused by the Transition T. T may increase certain types or categories of resources in Place P, and may also decrease certain types or categories of resources and in Place P. EE2, as the guiding mechanism of the system, belongs to the Transition set T, and has the function of guiding the change of the Place P, and it changes along withthe state change of the Place P caused by the Transition, and the changes are caused and jointly determined by various resources of the Place P. This reflects the opinion of this paper that EE2 and environmental management are mutually causal.

Fig.1

Enterprise’s eco-efficiency mechanism analysis.

In the figure above: $\begin{matrix} M (P_{i}) & = & {{econ}_{0}, {ecol}_{0}^{+}, {ecol}_{0}^{-}} \\ M (P_{i}^{*}) & = & {{econ}_{1}, {ecol}_{1}^{+}, {ecol}_{1}^{-}} \\ (P_{i}^{*} is P_{i} after change) \\ W (P_{i}, T_{k}) & = & {Δ econ, Δ {ecol}^{+}, Δ {ecol}^{-}} \end{matrix}$

According to the theoretical expression of EE2, the numerator and denominator of its measurement inevitability affected by the changes in the economic resources, the positive and negative ecological environment resources of the enterprise’s environmental management system, and ultimately affect the level of the enterprise’s Eco-efficiency measurement. The variety of transit machines act on variety of Places, resulting the changes of Place state which are the variation of resources stock, thus changing the configuration of environmental management system resources, and affecting the efficiency of environmental management system resource allocation. The transmission path of this influence is complex, and the impact relationship formed is non-linear, and the degree of influence and even the influence direction are not completely determined [13, 14].

3. Influencing factors classification of enterprise’s Eco-efficiency based on environmental management

From the EE2 mechanism analysis, it can be found that the status of the elements in the environmental management system and the degree to which the system mechanisms exert its functions are both uncertain, thus causing the uncertainty in the EE2 measurement.

The constituent elements and operating mechanisms of the environmental management system are collectively referred to as the environmental management elements. They directly or indirectly determine the operational efficiency of the system and determine the level of EE2 measurement. The factors of the Place directly affect the EE2 measurement, while the Transition factors affect the EE2 measurement indirectly by influencing the state of Place. Further discussion is needed on the main factors affecting the Place features and the factors that affect the Transition. What are the main factors and whether the influence of these influencing factors is determined or ambiguous.

3.1. Place influencing factors

Related literatures directly or indirectly provide the results of the research on the influencing factors of the Place influencing factors [15, 16]. Since the number of literatures is relatively small, the literatures on the implementation of EE2 is also included in this paper. Through the collation and classification of relevant literatures, the Place factors related to EE2, to positive and negative eco-environment resources of the enterprise environmental management system and the system’s economic resource stock are summarized and shown in Table 1:

Table 1
Place influencing factors of EE2

Place Influencing Factors	Notation	Positive Ecological Environment Resource Stock	Negative Ecological Environment Resource Stock	Economic Resources Stock
Green Purchase	P₁	Influential	Influential	Influential
Life Cycle Assessment	P₂	Influential	Influential	Uncertain
Material and Energy Intensity	P₃	Influential	No impact	Influential
Recycling and Utilization of Resources and Energy	P₄	Influential	Influential	Influential
Waste Recycling	P₅	Influential	Influential	Influential
Industrial “Three Wastes” Emission	P₆	Influential	Influential	Influential

3.2. Transition Influencing Factors

The Place factors influence the level of EE2 measurement by causing the increase or decrease of various resource stocks in the environmental management system. The Transition factors make indirect changes in the resource flow and stock of the environmental management system through the influence of Place factors. Because there are relatively few literatures on EE2 influencing factors, and for EE2 is closely related to energy efficiency, environmental regulatory efficiency, total factor productivity (TFP), and energy conservation and emission reduction efficiency. Among them, energy efficiency, energy conservation, and emission reduction efficiency have direct influences on the measures of corporate eco-economic efficiency. TFP encompasses the role of ecological and environmental factors, and environmental regulation could become an important component of the enterprise’s environmental management system. For this reason, this paper uses some of these factors influencing the efficiency, through the refinement of the core content of the relevant literature and the main research results, conclude to the Transition factors Table 2 [17 –19]:

Table 2
Transition factors of EE2

Transition Influencing Factors	Letter	Positive Ecological Environment Resource Stock	Negative Ecological Environment Resource Stock	Economic Resources Stock
Environmental Regulation Stringency	T₁	Influential	Influential	Uncertain
Government Incentives and Subsidies	T₂	Influential	Influential	Influential
Technical Innovation	T₃	Influential	Influential	Influential
Environmental Investment	T₄	Influential	Influential	Influential
Market Conditions	T₅	Influential	Influential	Influential
Market Performance	T₆	Uncertain	Uncertain	Influential
Environmental Management System	T₇	Influential	Influential	Uncertain
The Stage of Enterprise Scale Development	T₈	Influential	Influential	Influential
Industry and Region	T₉	Influential	Influential	Uncertain

4. Identification of EE2 uncertain influence factors based on intuitionistic fuzzy set theory

4.1. Similarity method for intuitionistic fuzzy measures of uncertain factors

From the analysis of the previous literatures and the analysis of the Place and Transition factors, it can be known that the impact of some factors on the resource stock of the enterprise’s environmental management system and the further impact on the EE2 measurement are ambiguous and uncertain, and it is difficult to make a clear assertion of whether it is “influential” or “no impact". In this paper, the intuitionistic fuzzy set theory is used to design the method of identifying the influencing factors of EE2 measurement uncertainty. The basic principle of method design is to establish an intuitionistic fuzzy set that may affect the inventory of enterprise environmental management system resources, and an intuitionistic fuzzy set of uncertain influencing factors. Through the fuzzy estimation of the similarity between sets, it will make fuzzy measurement and judgment of influencing degree of uncertain factors.

According to the intuitionistic fuzzy set theory, the intimate level of the object relations represented by the two intuitionistic fuzzy sets can be measured by the degree of similarity of the two sets [20].

Definition 1. Similarity between Intuitionistic Fuzzy Sets: let A and B be intuitionistic fuzzy subsets on a given domain U, and T is the map, T : IFS (U) × IFS (U) → [0, 1], if T (A, B) satisfies the following properties, T (A, B) is called the similarity degree between intuitionistic fuzzy sets A and B.

o ⩽ T (A, B) ⩽1;

T (A, B) =0, if and only if A = B;

T (A, B) = T (B, A);

If A, B, C ∈ U, A ⊆ B ⊆ C, then T (A, C) ⩾ T (B, A) T (A, C) ⩾ T (B, C)

The distance and the similar relationship between two intuitionistic fuzzy sets can be given by the following theorem:

Theorem 1.Ifd (A, B) is the distance between intuitionistic fuzzy setsAandB, thenT (A, B) =1 - d (A, B) is the similarity between intuitionistic fuzzy setsAandB.

Table 3
Set of possible influencing Factors on Resource Stock of Enterprise Environment Management System

Uncertain Factors Uncertain Factors Impact on System Resources Stocks Economic Resources Positive Ecological Environment Resources Negative Ecology Environmental resources

Letter B₁ B₂ B₃

Life Cycle Assessment A₁ ={ P₁ } fuzzy – –

Environmental Regulation Intensity A₂ ={ T₁ } fuzzy – –

Market Performance A₃ ={ T6 } – fuzzy fuzzy

Environmental Management System A₄ ={ T7 } fuzzy – –

Industry and Region A₅ ={ T9 } – – fuzzy

Uncertain Factors Uncertain Factors	Impact on System Resources Stocks	Economic Resources	Positive Ecological Environment Resources	Negative Ecology Environmental resources
	Letter	B₁	B₂	B₃
Life Cycle Assessment	A₁ ={ P₁ }	fuzzy	–	–
Environmental Regulation Intensity	A₂ ={ T₁ }	fuzzy	–	–
Market Performance	A₃ ={ T6 }	–	fuzzy	fuzzy
Environmental Management System	A₄ ={ T7 }	fuzzy	–	–
Industry and Region	A₅ ={ T9 }	–	–	fuzzy

In this paper, the distance between two intuitionistic fuzzy sets in discrete space is measured by the standardized Hamming distance.

Set the domain U = {x₁, …, x_n}, A, B ∈ IFS (U), then the distance between the two intuitionistic fuzzy sets A and B is:

$\begin{matrix} l_{m} (A, B) = \frac{1}{2 n} \sum_{i = 1}^{n} (| μ_{A} (x_{i}) - μ_{B} (x_{i}) | \\ + | γ_{A} (x_{i}) - γ_{B} (x_{i}) | + ρ \times | π_{A} (x_{i}) - π_{B} (x_{i}) |) \end{matrix}$ (2)

Take ρ1/2 in the above formula. According to Theorem 1, the similarity between two intuitionistic fuzzy sets A and B in discrete space U based on the standardized Hamming distance can be measured by the following formula:

$\begin{matrix} S (A, B) = 1 - l_{m} (A, B) = 1 - \frac{1}{2 n} \sum_{i = 1}^{n} \\ (| μ_{A} (x_{i}) - μ_{B} (x_{i}) | + | γ_{A} (x_{i}) - γ_{B} (x_{i}) | \\ + ρ \times | π_{A} (x_{i}) - π_{B} (x_{i}) |) \end{matrix}$ (3)

4.2. Identification of uncertain factors

Suppose domain U is a collection of factors that may have an impact on the enterprise’s environmental management system’s resource stocks,and B₁ indicates that the factors have an impact on the system’s economic resources [21, 22], and B₂ indicates that the factors have an impact on the system’s positive eco-environmental resource stock, B₃ indicates that the factors have an impact on the system’s negative ecological environment resource inventory, then B₁, B₂, B₃ ∈ Ifs (U) [14].

From the above table, U = {P₂, T₁, T₆, T₇T₉}, A₁ = {P₂}, A₂ = {T₁}, A₃ = {T₆}, A₄ = {T₇}, A₅ = {T₉}, then the eigenfunction of A_i (i = 1, 2, 3, 4, 5) is: $ψ_{Ai} (x) = {\begin{matrix} 1 & x \in A_{i} \\ 0 & x \notin A_{i} \end{matrix}$

With the eigenfunction A_i (i = 1, 2, 3, 4, 5) as its membership function, then $μ_{Aj} (x) = 1 or 0, γ_{Ai} (x) 1 or 0, π_{A_{j}} (x) \equiv 0,$

This paper combines the actual conditions of the influencing factors on the environmental management system resource stocks, and based on the improved Hamming distance, designs a similarity model that is applicable to the two sets, in the uncertain influencing factors domain U = {P₂, T₁, T₆, T₇, T₉, } = {x₁, x₂, x₃, x₄, x₅}

$\begin{matrix} S (Ai, Bj) = 1 - \frac{1}{15} \sum_{i = 1}^{5} (| μ_{Ai} (x_{i}) - μ_{Bj} (x_{i}) | \\ + | γ_{Ai} (x_{i}) - γ_{Bj} (x_{i}) | + ρ \times | π_{Ai} (x_{i}) - π_{Bj} (x_{i}) |) \end{matrix}$ (4)

Table 4

Fuzzy Influence Extent of Uncertain Factors on System Resources Stock

Related collection A_i and B_j	SimilarityS (A_i, B_j) = S_ij	Related collection A_i B_i	SimilarityS (A_i, B_j) = S_ij
A₁ and B₁	S₁₁	A ₃ andB ₃	S₃₃
A₂ and B₁	S₁₂	A ₄ andB ₁	S₁₄
A₃ and B₂	S₂₃	A ₅ andB ₃	S₃₅

A_i (i = 1, 2, 3, 4, 5,) is the set of uncertain influencing factors, the similarity of each intuitionistic fuzzy set B₁, B₂, B₃ that has influence on the inventory of the enterprise’s environmental management system resources depends on the membership function and non-membership function in the similarity model (4). This paper will apply the fuzzy statistics method combined with contrast compositor method based on the condition and quality of the survey data, to determine the function values of the membership function and the non-membership function, substituting numerical values into the model (4), and calculate the similarity of the relevant intuitionistic fuzzy set, thus to realize the fuzzy identification of the influence of various factors on the enterprise’s environmental management system resources stocks in U ={ P₂, T₁, T₆, T₇, T₉ }, and then get the degree of fuzzy influence on the stock of system resources for each uncertain influence factor(S_ij) [23].

5. Application examples of intuitionistic fuzzy identification method of EE2 influencing factors

The application of EE2 influencing factors to intuitionistic fuzzy identification method selected a large-scale oil refining and chemical company. In order to obtain survey data, this paper conducted a field survey on the status of environmental operations in this company and conducted interviews with the two vice general managers in charge of production and finance at the senior management level, as well as the leaders and main staff of the company’s offices, and a meeting for technical staff in seven workshops and team leaders. 57 questionnaires were distributed and collected. According to the field survey data, the method of combining the fuzzy statistics with the comparative ranking method was used to process the relevant data and get the result that three intuitionistic fuzzy sets B₁, B₂, and B₃ which contains various uncertain factors of the company’s environmental management resources [24]. The correlation matrix of the impact degree is as follows: $B_{1} - h_{ij} = [\begin{matrix} 1 & 0.53 & 0.55 & 0.56 & 0.60 \\ 1 & 1 & 0.88 & 0.87 & 0.90 \\ 1 & 1 & 1 & 1 & 1 \\ 1 & 1 & 0.95 & 1 & 0.95 \\ 1 & 1 & 1 & 1 & 1 \end{matrix}]$ $B_{2} - h_{ij} = [\begin{matrix} 1 & 1 & 1 & 1 & 1 \\ 1 & 1 & 1 & 1 & 1 \\ 0.90 & 0.90 & 0.90 & 0.90 & 0.90 \\ 1 & 1 & 1 & 1 & 1 \\ 1 & 1 & 1 & 1 & 1 \end{matrix}]$ $B_{3} - h_{ij} = [\begin{matrix} 1 & 1 & 1 & 1 & 1 \\ 1 & 1 & 1 & 1 & 1 \\ 0.45 & 0.55 & 1 & 0.50 & 0.55 \\ 1 & 1 & 1 & 1 & 1 \\ 0.90 & 0.95 & 1 & 1 & 1 \end{matrix}]$

The membership degree and non-subordination degree functions of the three intuitionistic fuzzy sets that affect the company’s environmental management system resource inventory are shown in Table 5.

Table 5
Fuzzy Relation between Uncertain Factors and Environmental Management

Uncertain Factors		Life Cycle Assessment		Environmental Regulation Intensity		Market Performance		Environmental Management System		Industry and Area
Uncertain Factors	Letter	P ₁		T ₁		T ₆		T ₇		T ₉
Impact on System Resources Stocks		μ	γ	μ	γ	μ	γ	μ	γ	μ	γ
Economic Resources	B ₁	0.53	0.35	0.87	0.10	–	–	0.95	0.00	–	–
Positive Ecological Environment Resources	B ₂	–	–	–	–	0.89	0.05	–	–	–	–
Negative Ecology Environmental resources	B ₃	–	–	–	–	0.45	0.52	–	–	0.90	0.05

Then, using the data in Table 5, to calculate in an intuitionistic fuzzy identification model (4) of uncertain influence factors, and get the result in Table 6.

Table 6

Fuzzy Influence Degree of Uncertain Factors on System Resources Stock

Related Collection	P₂ and B₁	T₁ and B₁	T₇ and B₁	T₆ and B₂	T₇ and B₃	T₉ and B₃
Similarity	0.424	0.503	0.614	0.444	0.403	0.519

If λ = 0.5 is selected as the cut-off parameter, it can be determined that the environmental regulatory intensity, environmental management system, industry and region and the company’s environmental management resources, these factors will have an impact on EE2, which should be taken into account in the process of measuring the eco-economic efficiency of the company.

6. Conclusion

The analysis of the definition and formation mechanism of EE2 in this paper shows that the state and change of enterprise environmental management system elements determine the measurement level of EE2, and the influence of related factors on the environmental management system elements of enterprises indirectly affects the measurement level of EE2. For the influencing factors of uncertainty, regardless of whether it is a Place or Transition factor, an Intuitionistic Fuzzy Measures method can be used in combination with the actual operation of the company’s environmental management to make an objective estimation and judgment of the extent of its influence.

References

Diebold Jr. , Changing course: A global business perspective on development and the environment[J], Thrombosis & Haemostasis111(4) (1992), 575–582.

Ribeiro , European environment agency. Reporting on environmental measures: Are we being effective?[M], European Environment Agency (2001).

Dahlstrom and

Ekins , Eco-efficiency trends in the UK steel and aluminum industries: Differences between resource efficiency and resource productivity[J], Journal of Industrial Ecology9(4) (2005), 171–188.

Oggioni ,

Riccardi and

Toninelli , The cement industry: Eco-efficiency country comparison using data envelopment analysis[J], Journal of Statistics & Management Systems14(6) (2011), 1067–1102.

Welford , Corporate environmental management: Systems and strategies [J], Corporate Environmental Strategy5(4) (1998), 90–92.

Michelsen ,

Annik and

Dahlsrud , Eco-efficiency in extended supply chains: A case study of furniture production[J], Journal of Environmental Management79(3) (2006), 290–297.

Cheng , The environmental management concept and practice of japanese enterprises [J], Modern Japanese Economy2010(1), 40–45.

Ge , Environmental management in japan based on sustainable development perspective [J], Japanese Journal2010(5), 87–100.

Jinuangdafu , Environmental Business Analysis [M], China University of Political Science and Law University Press, 2011.

10.

J.A.

Aragón-Correa and

Sharma , A contingent resource-based view of proactive corporate environmental strategy[J], The Academy of Management Review28(1) (2003), 71–88.

11.

L.D.

Desimone and

Popoff , Eco-Efficiency: The Business Link to Sustainable Development [J], The MIT Press, 2000.

12.

J.H.

Holland ( Xiaomei

Zhou

etc translation), Hidden Order: How Adaptation Builds Complexity[M]. Shanghai Science and Technology Education Press, 2011.

13.

Liu , etc. Enterprise Environmental Management Strategy based on E2-Efficiency Concept[C], International Conference on Management Science and Engineering, Helsinki, Finland,2014, pp. 496–500.

14.

Liu , etc. The E2-efficiency and its intuitionistic fuzzy measurement in petrochemical enterprise[J], Chemical Engineering Transactions62 (2017), 1519–1524.

15.

Chu ,

Wu ,

Zhu , et al., Analysis of China's regional eco-efficiency: A DEA two-stage network approach with equitable efficiency decomposition[J], Computational Economics (2016), 1–23.

16.

Liu , etc. Enterprise Environmental Management Strategy based on E2-Efficiency Concept[C], International Conference on Management Science and Engineering, Helsinki, Finland,2014, pp. 496–500.

17.

Wu , etc. Analysis of ecological efficiency measurement in China and its influencing factors [J], Technological Economy35(3) (2016), 75–80.

18.

Dai , ect., Ecological efficiency analysis of iron and steel enterprises[J], Journal of Northeastern University(Natural Science Edition)26(12) (2005), 1168–1173.

19.

Charmondusit ,

Phatarachaisakul and

Prasertpong , The quantitative eco-efficiency measurement for small and medium enterprise: A case study of wooden toy industry[J], Clean Technologies & Environmental Policy16(5) (2014), 935–945.

20.

Lei , etc. Intuitive Fuzzy Set Theory and Its Application.[M], Science Press, 2014.

21.

Zhao ,

Bai ,

Peng and

Xu , Efficient key management scheme for health blockchain, CAAI Transac-tions on Intelligence Technology3(2) (2018), 114–118.

22.

Huang and

Chen , Guest Editorial: Internet of things and intelligent devices and services, CAAI Transactions on Intelligence Technology3(2) (2018), 73–74.

23.

Rajendra Achary ,

Hagiwara ,

S.N.

Deshpande ,

Suren ,

J.E.W.

Koh ,

S.L.

Oh ,

Arunkumar ,

E.-W.J.

Ciaccio and

C.M.

Lim , Characterization of focal EEG signals: A review, Future Generation Computer Systems91 (2019), 290–299.

24.

S.L.

Oh ,

Hagiwara ,

Raghavendra ,

R.-A.

Yuvaraj ,