An ISM Approach for the Risk Analysis of Energy Service Company (ESCO) in China

Management Science and Research November 2015, Volume 4, Issue 3, PP.41-45

An ISM Approach for the Risk Analysis of Energy Service Company (ESCO) in China Herui Cui, Fangxin Liu† North China Electric Power University, 650500, China †

Email: 296308072@qq.com

Abstract Energy Performance Contracting (EPC) is an environmental protection mechanism which our country is vigorously promoting. It is a market-oriented mechanism for promoting energy efficiency. But its carrier----Energy Service Company (ESCO) is influenced by many factors in the development process in China. This article analyzed these risk factors by using ISM approach, got the ISM based model for the risks of ESCO and gave detailed explanation to this model, hoping to contribute to ESCO development in China.

Keywords: Energy Service Company (ESCO); Interpretive Structural Modeling(ISM); Risk Factors

1 INTRODUCTION Energy is the essential material basis for human survival and development. China is the second energy consumption country who is next to America in the world. With increasing growth of energy consumption, the voice for energy-saving is becoming higher and higher. China's 12th five-year plan clearly illustrated the energy conservation and environmental protection task during the "twelfth five-year" period, put forward “per unit of GDP energy consumption reduced by 16%, carbon dioxide emission reduced by 17%”, also pointed “create a green environment, promote the grand development of service industry”. Therefore, energy conservation and emission reduction is no longer an environmental problem, which is an important career to promote China’s economy and society to take a sustainable development, low carbon development road. [1] Scholars at home and abroad have done a lot of researches about EPC and ESCO risk factors. Mills etc. identified the risks associated with energy-efficiency projects, classifying them into five aspects, i.e. economic, contextual, technology, operation, measurement and verification (M&V) risks and putting forward Monte Carlo simulation model and the coefficient of variation the two risk analysis technology as tools for quantificating and managing energy projects risks [2]. Esin Okay etc. analyzed the EPC present situation and problems in Turkey by literature review and offered related suggestion [3]. Wang Ting, Hu Bo believed that energy management contract project risks include: external environment risk, energy-saving technology risk, market risk, financing risk, organization and management risk, customers risk, and established the gray analytic hierarchy evaluation model to evaluate the risks of the energy-saving project using Analytic Hierarchy Process (AHP) and gray system theory [4]. Shang Tiancheng, Pan Zhenni systematically analyzed the existing policy risk, market risk, financing risk, operation risk and benefit risk based on the implementation status of EPC in China, evaluated the risks by the theory of fuzzy comprehensive evaluation and proposed a risk-control optimization model [5].

There are no lacks of studies on investigating risk factors of the ESCO. However, most researches about EPC and ESCO risks in China isolated analyzed the effect of every risk factor on the project, rather than analyzing the mutual restrictive or influence relationship between every risk factor in a systematic and dynamical view point.

This paper aims to fill this gab by employing ISM approach to analyze the risk factors and finally obtain the results and conclusions.

- 41 www.ivypub.org/msr

2 METHODOLOGY In this paper, the objective of the work is achieved by the methodology of Interpretive Structural Modeling (ISM).

ISM is a conceptual model which was developed to analyze the complex social and economic system structure and so on by J.N.Warfield professor in America in 1973. Its basic idea is: through a variety of creative technology extracting the component elements of the problem, using directed graph, matrix and computer technology to deal with the element and other mutual relationship, finally construct a multilevel structural model. It decomposes the complex system into several subsystems (elements) with people’s actual experience, eventually establish the system as a multilevel hierarchical structure model, explicit the level and the overall structure of the problem. [7] ISM is a kind of analysis widely used in the system engineering method and can simplify and model the complex problems in social and economic system. Zhang Xiaoqing etc. through constructing the index system of low carbon buildings and analyzing these indexes by ISM, finally got senior and basic indexes, which promoted the development of low carbon building [8]. Yang Bin etc. explained the mechanism of the offshore oil field development project’s risk using ISM, and got the hierarchical relationship between each risk factor through the model [9].

3 APPLICATION OF ISM To analyze the risk factors for the ESCO in China, ten factors are considered based on the related literature. These factors are: policy risk, technology risk, management risk, financial risk, income risk, market risk, credit risk, customer risk, cognizance risk, credit risk. And variables S1 , S2 , S3 ...S10 refer to them. From the literature ten risk factors are taken and after discussion with experts. These experts are managers, executives of ESCO and professors in university and some other people in society.

3.1 Adjacent Matrix A Adjacent matrix is square which shows system telling basic binary relation or direct contract,

A = {aij }n*n . In this matrix, aij means the direct relationship between risk factor Si and S j , namely:  1,Si RS j ; aij =   0,Si R S j ; .

Based on the literature review and experts’ advice, the adjacent matrix is given in Fig.1.

S1 S2 S1 S2 S3 S4 A = S5 S6 S7 S8 S9 S10

0 0  0  0 0  0 0  0 1  0

S3 S 4

S5

S6

S7

S8

S9

S10

0 1 1 1 1 0 0 1 0 0 1 1 1 0 0 0 0 0  0 0 1 0 0 0 0 0 0  1 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0  0 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0  0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0  0 1 0 1 0 0 0 0 0 

FIG. 1 ADJACENT MATRIX A

3.2 Reachability Matrix M The reachability matrix M is used to represent that what extent different nodes in a directed graph can reach to(i.e. the indirect influence) each other through some certain channels. The reachability matrix M is calculated from the adjacent matrix A, using the Boolean algebra operation, we get: - 42 www.ivypub.org/msr

( A + I ) ≠ (A + I) 2 ≠ (A + I)3 = (A + I) 4 So, reachability matrix M is (A + I) 3 , which is shown in Fig.2.

S1 S2 S1 S2 S3 S4 M = S5 S6 S7 S8 S9 S10

1 0  0  0 0  0 0  0 1  0

S3 S 4

S5 S 6

S7

S8 S 9

S10

1 1 1 1 1 0 0 1 0 1 1 1 1 0 0 0 0 0  1 1 1 1 0 0 0 0 0  1 1 1 1 0 0 0 0 0 0 0 0 1 0 0 0 0 0  1 1 1 1 1 0 0 0 0 0 0 0 1 0 1 0 0 0  0 0 0 0 0 0 1 0 0 1 1 1 1 1 0 0 1 0  1 1 1 1 0 0 0 0 1 

FIG.2 REACHABILITY MATRIX M

3.3 Level Partitions The reachability set and antecedent set for each factor is obtained from the reachability matrix. The reachability set for a particular variable consists of the variable itself and the other variables which it may help achieve. The antecedent set consists of the variable itself and the other variables which may help in achieving them. Namely, the reachability set is:

R (Si ) = {S j S j ∈ S , aij = 1, j = 1, 2, , n}i = 1, 2, n

;

the antecedent set is:

A(Si ) = {S j S j ∈ S , a ji = 1, j = 1, 2, , n}i = 1, 2, n

.

The variable for which the reachability and the intersection sets are the same is given the top-level variable in the ISM hierarchy which would not help achieve any other variable above their own level. After the identification of the top-level element, it is discarded from the other remaining variables. In this study, the ten risk factors, along with their reachability set, antecedent set, intersection set and levels are presented in Table 2. From Table 2, it can be seen that fear of failure factor is found at levelⅠ. Thus it would be positioned at the top of the ISM model. This interaction is continued till the levels of each variable are obtained. The identified levels aid in building the digraph and final model of ISM. TABLE 1 LEVEL PARTITIONS FOR FACTORS: ITERATIONⅠ-ITERATION Ⅳ Risk factors

Reachability set R (Si )

Antecedent set A(Si )

Intersection set R (S ) ∩ A(S ) i i

Iteration No.&level

S5

5

1,2,5,6,7,9,10

5

Ⅰ

S8

8

8

8

Ⅰ

S2 S3

2

1,2,6,9,10

2

Ⅱ

2

1,2,6,9,10

2

Ⅱ

S5

2

1,2,6,9,10

2

Ⅱ

S7

7

7

7

Ⅱ

S6

6

1,6,9

6

Ⅲ

S10

10

10

10

Ⅲ

S1

1,9

1,9

1,9

Ⅳ

S9

9

9

9

Ⅳ

- 43 www.ivypub.org/msr

3.4 Formation of ISM Based Model Based on the partition above, the ESCO interpretive structural model is generated and given in Fig.3. The relationship between the risk factors i and j is shown by an arrow pointing from i to j.

Level Ⅰ

Level Ⅱ Level Ⅲ Level Ⅳ

Income risk

Technology risk

Management risk

Customer risk

Financial risk

Market risk

Credit risk

Other risk

Policy risk

Cognizance risk

FIG.3. THE ESCO INTERPRETIVE STRUCTURAL MODEL

4 RESULTS We have gotten the ESCO structural model by ISM. The mechanism of the ESCO risk could be saw clearly. From this model, we find this system is a four-lever hierarchical structure model.

Level Ⅰ: Income risk and Customer risk. Getting the most benefit is the most fundamental purpose of each company.

Income risk is avoidless, while it can be mitigated though enhancing and improving technical equipment and management level. Energy-consumption customer is closet partner with ESCO, which directly affects the whole process of energy-saving project operation and its importance is self-evident. Customer is cooperated with ESCO, so it will not bring too many risks. In a word, these two risk factors are ESCO internal risk factors and the surface risk factors.

Level Ⅱ: Technology risk, Manage risk, Financing risk and Credit risk. These four risks have influence on each other. The lack of technology, the insufficient of capital, the low level of customer’s credit inevitably would affect the management of ESCO; In turn, the poor management also would affect the speed technology upgrading, customer’s credit level and the ability to obtain bank loans. In a word, these four risk factors are ESCO internal risk factors and the middle-level risk factors, which are most direct risk factors restrict ESCO to realize its value.

Level Ⅲ: Market risk and Other risk. Market is an indispensable and important factor for ESCO development and growth. Whether the external market is well or not directly affect the procurement of equipment and the update of technology, then affect the profit. Other risk here mainly means the bad weather or natural disasters bring unnecessary loss to ESCO, which also has influence on a company’s management and has risks on profit. In a word, these two risk factors are ESCO external risk factors and the middle-level risk factors.

Level Ⅳ: Policy risk and Cognizance risk. Policy risk may affect the changes of the laws and regulations of the buyer’s and seller’s market, the improvement of the financing policy, the contract that ESCO signs with energyconsumption customer. Cognizance risk emphasizes the subjective effect of the public. As an ESCO, what it can do is just looking forward the national policy will be more and more perfect and the cognitive ability and acceptance level of the public is more and more increased. In a word, these two risk factors are ESCO external risk factors and also the fundamental risk factors.

In conclusion, from the ESCO structural model, we can find that the fundamental factors(risk factors in level Ⅳ), the direct factors(risk factors in level Ⅱ), the internal factors(risk factors in level Ⅰ and Ⅱ) and the external factors (risk factors in level Ⅲ and Ⅳ)of the energy-saving benefit sharing model ESCO risk generation .

5 CONCLUSION EPC is a new energy-saving mechanism and business model with good wide development prospect. In terms of years - 44 www.ivypub.org/msr

of development abroad, it is a mature technology with huge development potential and market, whose smooth implementation can make every participants including: ESCO, energy-consumption customer, investment organization, the government, the third party(energy-saving research institutions, Energy-saving monitoring and evaluation center), the social public obtain considerable benefits. Nowadays, ESCO in China really faces many risks which not only hinder itself development, but also isn’t conducive to the development of the country's energy-saving.

This article is from the point of view of system engineering, uses ISM approach to analyze the risk factors of ESCO, offers a new perspective for ESCO risk management. Though building multilevel hierarchical structure model, the hierarchy relations between various risk factors can be clearly found. It is convenient for company manager to find the surface and the fundamental factors which affect profit quickly. Looking forward to contribute to EPC and energy conservation and emissions reduction in the future in China.

REFERENCES [1]

Xie ZH, Ding XY. The management practice and risk prevention of EPC. Shanghai Press, 2011:11-15

[2]

Evan Mills. Risk transfer via energy-savings insurance. Energy Policy 2003, 31(3):273-281

[3]

Esin Okay, Nesrin Okay, Alp Er S.Konukman, Ugur Akman. Views on Turkey’s impending ESCO market: Is it promising?

Energy Policy, 2008, 36:1821-1825

[4]

Wang T, Hu B. The risk evaluation of EPC management item. Power demand side management, 2007, 9(5):24-26

[5]

Shang TC, Pan ZN. The risk research of modern enterprise EPC management item. Journal of Tianjin university, 2007, 9(3): 214-

[6]

Zhang XD. System Engineering, 2010, 7

[7]

Zhang XQ, Zhu YL, Chen HX, Wang X. The index system analysis of low carbon building based on ISM. Modern times, 2011,

217

12:119-121 [8]

Yang B, Yu B, Sun Q. The research of offshore oil and gas development project risk based on ISM. Journal of Harbin engineering university, 2010,31(9):1259-1264

- 45 www.ivypub.org/msr