1 JOURNAL OF ECONOMICS AND BUSINESS … OF ECONOMICS AND BUSINESS RESEARCH Year XVI, No. 2/2010 ... Ph.D Professor Ilie Rotariu , ... G. Cristescu, L. Jitaru,

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JOURNAL OF ECONOMICS AND BUSINESS RESEARCH

Year XVI, No. 2/2010

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JOURNAL OF ECONOMICS AND BUSINESS RESEARCH

Year XVI, No. 2/2010

ISSN 2068 - 3537

Edited by “AUREL VLAICU” University Arad, 2010

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Editorial Board: Editor in chief: Ph.D Associate Professor Luiela Magdalena Csorba, "Aurel Vlaicu" University of Arad, Romania Associate Editor in chief: Ph.D Associate Professor Cristina Nicolaescu, "Aurel Vlaicu" University of Arad, Romania Associate executive editors 1. Ph.D Professor Tania Matos Gomes Marques, Instituto Politecnico de Leiria, School of Technology and Management, Portugal 2. Ph.D Professor Elek Sandor, Corvinus University, Budapest, Hungary 3. Ph.D Professor Fabian Attila, University of Sopron, Hungary 4. Ph.D Professor Rodica Hîncu, Economic Studies Academy, Chişinău, Moldova Republic 5. Ph.D Associate Professor Ana Suhovici, Economic Studies Academy, Chişinău, Moldova Republic 6. Ph.D Professor Mirjana Radovic-Markovic, Institute of Economic Sciences, Belgrad, Serbia 7. Ph.D Professor Ricardo Bruno Ferreira, Instituto Politecnico de Portalegre, Portugal 8. Ph.D Associate Professor Dragoş Şimandan, Brock University, Canada 9. Ph.D Professor Beata Farkas, University of Szeged, Hungary Associate editors 1. Ph.D Professor Victor Manole, Economic Studies Academy, Bucharest, Romania 2. Ph.D Professor Ilie Rotariu, University „Lucian Blaga”, Sibiu, Romania 3. Ph.D Professor Gheorghe Ciobanu, University „Babes Bolyai”, Cluj-Napoca, Romania 4. Ph.D Professor Emilia Ungureanu, Faculty of Economis, University of Piteşti, Romania Editorial Secretariate 1. Ph.D Associate Professor Mihaela Iacob, "Aurel Vlaicu" University of Arad, Romania 2. Ph.D Lecturer Radu Cureteanu, "Aurel Vlaicu" University of Arad, Romania 3. Ph.D Candidate Assistant Bogdan Gomoi, "Aurel Vlaicu" University of Arad, Romania

Address University “Aurel Vlaicu” of Arad

Romania, 77 RevoluŃiei Avenue, Arad Tel/fax: 0040-257-280679

E-mail: [email protected]

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CONTENTS

Decision making based on assessing the welfare gained …………7 By G. Cristescu, L. Jitaru, , L. NeamŃiu, S.G. Szentesi Environmental monetary valuation - an important step to estimate the economic-ecologic balance ………………………………….….26 By S.G. Szentesi, G. Cristescu Designing a management model for achieving economic-environmental balance in investment projects…………….………40 By S. G. Szentesi, M. FranŃescu, S.Crişan Evaluation model for the economical-ecological balance……………………………………………………….………49 By S. Szenteşi The environmental impact of electro-thermal plant (CET) Arad ……………………………………………………………………..…61 By S. G. Szentesi, M. FranŃescu Etude sur la relation entre la performance financière et performance sociale de l'entreprise…...…...…...…...…...…....…....…....…....…....….......…70 By C. Nicolaescu, M. Vizental Develop economic-ecological balance of investment objectives with the model confirmation/infirmation ………………………………………………………………….……76 By G. Szentesi, M. FranŃescu Modern approaches in modeling the economic-environmental balance modeling for investment projects affecting the environment…………………………………………………………84 By S.G. Szentesi

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Achieving the economic-environmental balance for investment projects based on modified utility model………………………………………………………………100 By S.G. Szentesi, M. Viezental Electre Method in Multicriterial Projects Evaluation Form Economic and Ecologic Point of View………………………………………………………………112 By M.Viezental, S. G. Szentesi, G. MoŃ

Journal of Economics and Business Research, ISSN: 2068 - 3537, Year XVI, No. 2, 2010, pp. 7-25

Decision making based on assessing the welfare gained The paper is supported by the Romanian Education and Research

Ministry, within the Research Project ID-1239/2007

G. Cristescu, L. Jitaru, L. NeamŃiu, S.G. Szentesi Gabriela Cristescu, LaurenŃiu Jitaru, Silviu Gabriel Szentesi ”Aurel Vlaicu” University of Arad, Romania Luciana NeamŃiu ”I. ChiricuŃă” Oncology Institute of Cluj-Napoca – România

Abstract We propose a decision aid model based on assessing the welfare gained of an investment project. The mathematical model consists in a multiple criteria binary programming problem. The solution of this model leads the decision maker to using a welfare gained measure, which arises from finding a Pareto point of the multiple criteria programming problem. The possibility of gambling with the relative importance of criteria provides the decision maker with extended information on the consequences of the investment project on the environment and humans involved in the project. Few examples, taken out of our own practical experience, are included. Keywords: environment, mathematical model, investment project

1. Introduction Ethical issues often appear in the process of selecting an

investment policy taking into account both economic and environmental and human criteria. The need of protecting both the environment in which the project is going to develop and the employees involved in it comes often into conflict with the need of keeping the work productivity at high level, also trying to minimize the costs.

The necessity of studying the economic-ecologic efficiency of an investment policy of a company is often mentioned both in technical and in scientific literature. The relationship between industry,

G. Cristescu, L. Jitaru, L. NeamŃiu, S.G. Szentesi 8

environment and society should receive considerable attention from two points of view: within the organization and between the organization and the society and nature. The economic-ecologic efficiency is a concept related to that of welfare in nowadays literature. Assessing this kind of efficiency is a part of assessing the contribution of an investment project to the welfare of the community.

A general method of assessing this kind of efficiency is never described. There are many domains that use efficiency indexes to assess various types of activities and economic processes from other points of view then the financial one. For example, in the energy domain there are more efficiency indexes; both in terms of costs and in terms of effects, depending on the aim of the researcher (see [1], [7], [11]). The relationship between trade and environmental conditions is very important whenever countries are in the process of negotiating trade agreements. So, an environmental efficiency index for a sample of high income and low and middle income countries was developed (see \cite{9}) allowing to examine the role of trade on the changes in environmental efficiency. The idea of an efficiency of a legislation system was recently published (see [10]). An efficiency index to assess the economic efficiency of a vaccine was derived in farmaco-economics (see [6]).

Each investment project has impact on more directions. The classical theory of decision making in investment domain takes into account the financial aspect. But this is only one side of the project impact. It has impact on the environment, on the employees’ lives, on the society, on the environment. We propose a model, which may be used in decision aid, taking into account all these aspects.

The framework of our study consists in the basic hypothesis that pathology in a direction consists in increasing the value of some characteristic parameter so that it exceeds normality. So, the best project is that which does not create pathology. If the pathology already exists, then the best project contributes to diminishing the damage. Therefore, the immediate idea is to find a possibility of comparing the "before" of the project with the "after" the project from all the above mentioned points of view in order to assess the contribution of the project to the general welfare. In the second section of this paper we elaborate a mathematical model, based on multiple criteria binary programming, to provide the decision maker with the possibility of optimizing the choice. The solution of this model leads the decision maker to using a welfare

Decision making based on assessing the welfare gained

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gained measure, which arises from finding a Pareto point of the multiple criteria programming problem.

In the third section we present an example of decision making using the previously described method in the fields of farmaco-economics. The fourth section describes an example of using this method to the problem of ecological modernization of the railway transport system, as it appears in small local railway companies in our country. The examples from the last section contain real problems, with real data, collected by authors as members of the research team of the project ID-1239/2007. 2. Decision aid by means of the welfare gained 2.1 Basic results

First, let us recall few basic concepts that are used in this

section. Let X be a nonempty set and let f = (f1, f2, ... , fn): X → Rⁿ.

Definition 2.1. A point a ∈ X is called a min-efficient point of f on X if there is no x∈ X such that fi(x) ≤ fi(a), i ∈ {1, 2, ... , n}, and ( ) ( )∑∑ == < n

1j jn1j j afxf .

In order to solve problem (PE), we use the weight method, obtaining a unique synthesis function. The main result of Galperin [3] is used: Theorem 2.2. If λ1>0, λ2>0, ..., λn>0 are n given real numbers, then every minimum point of the function F: X → R, defined by

( ) ( )∑ == n1j jj xfxF λ

for every x ∈ X, is a min-efficient point of the vectorial function f on X. The methods of finding the min-efficient points depend on the particular properties of the function f and are largely described in the literature (see, for example, [2] and [6]).

2.2. Problem Formulation The consequences of an investment policy are assessed by

means of n criteria, referring to the environment, security of personnel, energy consumption, etc. The benefit may come as a second level of assessment, leading to a bi-level programming problem, if needed. Let us consider known sNk, the normal score of criterion k, k ∈ {1, 2, …, n}. If no investment project is chosen then sk is the score of criterion k, k


∈ {1, 2, …, n}. If an investment project (P) is chosen then sPk is the score of criterion k, k ∈ {1, 2, …, n} after a known period of time. The following costs are known:

• cp = the total cost of applying the investment project (P); • cPk = the total cost of treating the damage, negative reactions or side effects produced by the investment project (P) in the domain of criterion k, k ∈ {1, 2, …, n}; • ck = the total cost of treating the damage, negative reactions or side effects in the domain of criterion k, k ∈ {1, 2, …, n}, if no investment project is chosen.

The main purpose is to elaborate a method of choosing, among more investment projects possible, those that brings the score of each criterion as close to its normal level as possible. A mathematical model is attached for this purpose, in terms of a multiple criteria programming problem in variables 0 and 1. These values are meant to express the preference for a type of action, meaning that two binary variables x1 and x2 are introduced, having the following significance:

• x1 = 1 means that project (P) is chosen; • x1 = 0 means that project (P) is not chosen; • x2 = 1 means that no project of investment is preferred; • x2 = 0 means that there is a project of investment that is preferred.

Of course, x1 + x2 = 1, since an investment project can be only accepted or rejected. We suppose that if a project is preferred then it is chosen, assumption which is consistent within the binary logic. If another kind of logic is taken into account, then the model should be rewritten to be consistent. Let us define the numbers pk and pPk as it follows:

• pk = 100(sk – sNk) / sNk, if sNk ̸≠ 0 and sk > sNk; • pk = 0, if sNk ̸= 0 and sk ≤ sNk; • sk, if sNk = 0; • pPk = 100(sPk − sNk) / sNk, if sNk ̸= 0 and sPk > sNk; • pPk = 0, if sNk ̸= 0 and sPk ≤ sNk; • pPk = sPk, if sNk = 0. The number pk is called the actual variation of criterion k, k ∈

{1, 2, …, n}, with respect to its normal score. The number pPk is called the variation induced by project (P) of criterion k, k ∈ {1, 2, …, n}, with respect to its normal score.

The objective functions are


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fk : {0; 1} × {0; 1} → R, k ∈ {1, 2, …, n} and fn+1 : {0; 1} × {0; 1} → R,

for every (x1; x2) ∈ {0; 1} × {0; 1} by: fk(x1, x2) = (pNk − pPk)x1 + (pNk − pk)x2 , k ∈ {1, 2, …, n}

fn+1(x1, x2) = x1 + 2xPαα

,

where the numbers α and αP are defined in terms of costs as it follows:

∑=

=n

kkc

1

α ,

∑=

+=n

kPkPP cc

1

α .

Suppose that the pathology at the level of each criterion consists in increasing its value. The solution comes from finding the min-efficient points of the following vectorial programming problem, denoted by (PE):

((pN1 − pP1)x1 + (pN1 − p1)x2, …, (pNn − pPn)x1 + (pNn − pn)x2, x1

+ 2xPαα

) → v − min

submit to x1 + x2 = 1 for (x1, x2) ∈ {0; 1} × {0; 1}.

2.3. Solution to problem (PE) In order to solve problem (PE), we introduce the synthesis function F: {0, 1} × {0, 1} → R using the pounds λ1>0, λ2>0 and λ3>0, getting

F(x1,x2)=λ1f1(x1,x2)+λ2f2(x1,x2) +…+ λn+1fn+1(x1,x2). With this function, problem (PE) turns into the following problem (P):

F(x1,x2) =

( ) ( )[ ]

++−+− +

=∑ 211

121 xxxppxpp

P

n

n

kkNkPkNkk α

αλλ →

min,

when x1 + x2 = 1, (x1, x2) ∈ {0,1} × {0,1}. The point (0; 1) from the domain of F describes the situation when project (P) is not chosen,


while (1,0) represents the case when (P) is put in practice. By elementary calculus one gets

( ) ( )P

n

n

kkNkk ppF

αα

λλ 11

1,0 +=

+−=∑ ,

( ) ( ) 11

0,1 +=

+−=∑ n

n

kPkNkk ppF λλ

and, as consequence,

( ) ( ) ( )

−+−=− +

=∑

P

n

n

kPkkk ppFF

αα

λλ 11,00,1 11

.

This is the stage of decision making. If F(1, 0) − F(0, 1) ≥ 0 then one can decide that the investment project (P) is acceptable since it is supposed to bring the set of all the scores of criteria closer to normal than the actual values. Remark 2.3. An investment project (P1) is better than another one, (P2) if

(F(1, 0) − F(0, 1))(P1) > (F(1, 0) − F(0, 1))(P2), meaning that (P1) brings the parameters closer to normality than (P2).

This is the reason of using the difference F(1, 0) − F(0, 1) as a method of decision making, when a choice of an investment policy is under debate.

3. Assessing the welfare gained by an investment project Due to the previous remark we decided to introduce the

following tool to characterize an investment project. Definition 3.1. The welfare gained by an investment project (P) is the number

( ) ( )

−+−= +

=∑

P

n

n

kPkkkg ppPW

αα

λλ 111

Remark 3.2. As one can see, Wg(P) = (F(1, 0) − F(0, 1))(P). It is now necessary to study the monotony properties of Wg(P), in order to understand the manner in which it characterizes the effect of the investment project in the directions represented by the set of criteria. Definition 3.3. An investment project (B) is said to be strongly dominated by an investment project (A) if


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sNk < sAk < sBk for any k ∈ {1, 2,…, n} and if

BA αα

αα

−<− 11 .

Definition 3.4. An investment project (B) is said to be dominated with respect to the set of criteria by an investment project(A) if

sNk < sAk < sBk for any k ∈ {1, 2,…, n}. The following remarks, which contain properties of the welfare

gained, are easy to prove. Remark 3.5. Wg(P) > 0 when sPk < sk for any k ∈ {1, 2,…, n} and λn+1 = 0. Remark 3.6. If project B is strongly dominated by project A then Wg(B) < Wg(A). Remark 3.7. If project B is dominated with respect to the set of criteria by project A and λn+1 = 0 then Wg(B) < Wg(A).

All the above mentioned monotony properties of the welfare gained Wg by an investment project show us that it is able to characterize the project. This is an inner characterization of the project, being able to take into account its effect on all the directions described by the set of criteria. It is possible to replace the function fn+1 by other criteria arising from the cost/utility analysis, combining them with the environmental ones such as the above described reasoning stands. A new formula of the same class of efficiency indexes may result.

If the pathology consists in decreasing some values under the normal level, then the model still stands, but the condition of negativity of Wg should be taken into account. This may happen in problems arising from farmaco-economics, for example. Also, the condition of negativity replaces the selection condition from this section in case of the condition of vectorial maximum in (PV). The next section contains such an example.

4. Example: Multiple criteria optimization to approach the ethical issues expressing the conflict between the medico-economic management and the medical professional group

The insufficient funding is one of the major issues of all the

medical units, all over the world. The budget is often exceeded by the


total cost of the applications for various treatments and surgical interventions. As consequence, the very difficult decision problem of choosing those applications that are going to be funded and those to reject or put on hold arises. It is difficult not only from mathematical point of view but also from the point of view of ethics. This was the main topic approached within one the working session of the 2nd International Forum on Oncology and Health Economics CECOG, Wien, April 20-21, 2002.The possibility of using the cost-utility analysis in solving it was discussed, given a practical example. Since we consider that the cost-utility analysis does not use all the available information and the solution provided by this method does not accord to the common sense, we gave another solution to this problem, based on multiple criteria optimization.

4.1. The formulation of the medico - economic problem A medical unit has 7000 money units (m.u.) for solving the following applications:

� Case 1: Mr. Harper, 68 years old, retired, having two adult sons, has prostate cancer and his doctor recommended a surgical intervention. Taking into account his present condition, if this operation is not performed, he would be able to live at most 10 more years, having health state 0.9. If the operation is performed, he would live at most 13 more years, but with 0.6 health state (due to the incontinence and impotence following the surgical intervention). The cost of this operation is 3200 m.u.;

� Case 2: Mrs. Patel, 58 years old, needs a hip prosthesis. She takes care on her 2 years old grand-daughter, while her unique daughter works and takes care on her husband and two sons living with her. Her actual condition indicates the chance of living 20 more years, either with or without hip prosthesis. The hip prosthesis would increase her health state with 0.2 for the next 20 years. The cost of this operation is 4100 m.u.;

� Case 3: Mrs. Hargreaves, 69 years old, no-smoking, no children, has a heart disease which condemns her to death if a surgical intervention is not performed. If the operation is done, she has the chance of living 10 more years, with 0.7 health state. The cost of this operation is 6900 m.u.;


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� Case 4: Marta, a 25 years old young girl, has a tattoo on her neck, representing a flower, the name “Dean” being written in the middle. This is the name of a former friend that abused her, causing her relocation from the town she lived and worked before. She complains that the tattoo is psychologically harming her, diminishing her health state at 0.8, which affects her employment possibility. The psychiatrist estimates her health state will increase at 1 if the tattoo is removed. She is estimated to live until 79 years old. The cost of this operation is 3100 u.m.;

� Case 5: Javinder, a 7 years old little boy, has cystic fibrosis. He could live 6 more months without operation, with 0.3 health state. After a heart and lung transplant he can leave until 10 years old, his health state being 0.7. The cost of this operation is 7000 m.u.;

� Case 6: Patrick, physician anaesthetist, 35 years old, did a vasectomy 8 years ago because his first wife did not want to have children. He remarried a 37 years old woman and his present wife wishes very much to have children. The doctor considers that his wife risks a psychological depression in case she is not able to have children. Patrick’s health is perfect, with or without operation, and he is estimated to live until 75 years old. The cost of the reverse operation to vasectomy is 900 m.u.;

� Case 7: Mr. Moss, worker, 48 years old, smoked about 40 cigarettes by day during the last 28 years. He has a 10 years old boy at home and pays for the college education of another one. He suffers a severe heart infarct and needs a bypass of the coronary artery (CABG). He is not able to live with no surgical intervention. An extension of his life with 10 more years is estimated in case the operation is done, with 0.8 health state. The cost of this operation is 5300 u.m.

The board of the hospital must decide which application to accept, since the total amount of 7000 m.u. cannot be exceeded.

4.2. The solution by cost-utility analysis

The solution given by the above mentioned Forum is based on the cost-utility analysis, taking into account the quality of life of the patient after the surgical intervention (see [6]). The principle of this method consists in the following steps:


– Compute, for each application, QALYs gained and the ratio between the cost of the operation and QALYs gained;

– Decreasingly order the applications with respect to the value of QALYs gained and, for equal values, decreasingly order with respect to the ratios values;

– Analyse each application, taking them into account the order obtained before; if the cost of the intervention does not exceed the difference between the initial amount of money and the sum of costs of the interventions already approved, the application is accepted. Otherwise, it is rejected.

The QALYs gained is computed by the formula

QALYs gained = QALYo – QALYw,

where, if hso means the health state after the operation is performed, hsw means the health state if the operation is not performed, then

QALYo = hso × years lived after operation,

QALYw = hsw × years lived without operation.

The following table contains the data obtained studying the above formulated problem.

Name of the applicant

No. QALYs

gained

Cost of intervention

Cost / QALYs gained

Harper 7 -1.2 3200 m.u. -2666 m.u./QALY

Patrick 6 0 900 m.u. -

Marta 1 15.8 3100 m.u. 196

Moss 2 8 5300 m.u. 662

Hargreaves 3 7 6900 m.u. 986

Javinder 4 6.85 7000 m.u. 1022

Patel 5 4 4100 m.u. 1025

The aim of the cost-utility analysis is to maximize the value of QALYs gained and to minimize the ratio cost / QALYs gained. The table


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shows that Mr. Harper has a negative QALYs gained and this is zero in case of Patrick. The maximum value of QALYs gained appears to Marta and equals to 15.8, and the corresponding ratio, equal to 196, represents the minimum expense per unit of quality of life gained. The greatest ratio cost / QALYs gained is reached in case of Mrs. Patel, her hip prosthesis leading to the greatest cost per unit of life quality earned. Therefore, the decision reached using the cost-utility analysis is to accept Marta’s application and to reject all the other. One can remark that this decision would allow to direct money either to Mr. Harper’s operation or to Patrick’s operation. But both cases do not lead to increasing of QALYs gained, while the ratio between the total sum of costs of operations performed and the total sum of QALYs gained would increase.

4.3. Critical remarks on the cost-utility analysis solution The solution of the cost-utility analysis is not ethically acceptable. It let three people die (Mrs. Hargreaves, little Javinder and Mr. Patel) and accepts the funding of a plastic operation for a person that, willingly did tattoo the neck. This happens because the cost-benefit analysis does not take into account other aspects of patient’s life, as:

– their role in supporting the family, – the influence of their health status on the other members of the

family, – their contribution to rendering sick, – the operation is vital.

This solution puts the quality of life above life itself, creating an ethical conflict within the medical staff, consisting from members that already took the Oath of Hippocrates. Protecting life above all is one of the mankind ethical values not depending on the stage of the history,

type of society, political regime, a.s.o.

Therefore, the choice should be restricted not only by medical and financial criteria but also by criteria of ethical nature. We intend to show, in what follows, how it is possible to solve such a problem by means of the multiple criteria optimization. A more general formulation of the problem is given, together with a mathematical model, solving it by the pounds method. This method allows us, by specifying the relative importance of criteria, to operate with the above discussed ethical issues.


4.4. Generalisation of the problem – mathematical model The amount of S m.u. is destined to funding some surgical treatments. There are n applications from the part of patients P1, P2, …, Pn. The problem is to choose the patients such that the budget is not exceeded. For each patient, the following data are known:

– the age ti; – the cost of the treatment ci; – qi = QALYs gained; – if the treatment is vital then let vi = 1; otherwise vi = 0; – if the patient has other persons, having no other support, in ones

care and the number of these persons; – if the patient supports (helps) persons from the family and the

number of these persons; – if the previous behaviour of the patient is responsible on the

disease; – if the surgical treatment changes the health state of persons

belonging to the patient’s family and the number of these persons.

Based on these data, we are able to define three quality variables, similar to the quality of life:

– the social variable, s; – the guilt variable, g; – the responsibility for other person variable, r.

The guilt g and the responsibility r are binary variables, taking the values 0 and 1. The social variable has two dimensions, and its one dimension components are: variable care taken and variable supporter. The values of these variables depend on two coefficients, called the care taken coefficient and the supporter coefficient that may have values between 0 and 10 and express the degree of dependence on the care of the patient:

– 0 means that the supported (care taken) person has another possibility of support, respectively, is able to maintain oneself;

– 1 means that the supported (care taken) person has no income, respectively is not able to take care on oneself.

If a patient Pi supports mi persons having the degrees of maintenance equal to

iim21 z,...,z,z , and takes care of ni persons having the degree of

help iin21 a,...,a,a , then


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∑∑==

+=ii n

1hih

m

1kiki azs .

In order to formulate the mathematical model, let us consider the binary variables xi, i ∈ {1, 2, …, n}:

• xi := 1 if the application of patient Pi is approved; • xi := 0 otherwise.

Let us define the functions fi: {0, 1} → R, i ∈ {1, 2, 3, 4, 5, 6}, as it follows: if x = (x1, x2,…, xn) ∈ {0, 1}n, then

( ) ∑=

=n

1iii1 xqxf describes the total QALYs gained ,

( ) ∑=

=n

1iii2 xsxf describes the social contribution of all the patients,

( ) ∑=

=n

1iii3 xvxf expresses the value of the operation for the patients’

lives,

( ) ∑=

=n

1iii4 xrxf expresses the contribution of the operation to the health

state of other family members of the patients,

( ) ∑=

=n

1ii5 xxf represents the good will of satisfying as most

applications as possible,

( ) ∑=

=n

1iii6 xgxf expresses the degree of guilt of patients for the illness.

The problem, formulated at the beginning of this paragraph, is mathematically modelled and solved by the following multiple criteria optimization problem:


( )

{ } { }

∈∈

≤

→

→

→

→

→

→

∑∑∑∑∑∑∑

=

=

=

=

=

=

=

.n,...,2,1ifor,1,0x

Sxc

maxx

minxg

maxxr

maxxv

maxxs

maxxq

PV

i

n1i ii

n1i i

n1i ii

n1i ii

n1i ii

n1i ii

n1i ii

Let us solve this problem using the weighting method. Let us introduce the pounds λ1, λ2, λ3, λ4, λ5, λ6 satisfying the condition

161i i =∑ = λ . Every solution of the problem

( ) ( )

∈

→

,Xg

maxxgQ

( ) { }{ },Sxc1,0x,...,x,xxX n1i ii

nn21 ≤∈== ∑ =

function g: {0, 1}n → R, being defined by

( ) ( ) ( )xfxfxg 66

5

1jjj λλ −= ∑

=, for x ∈ {0, 1}n,

is a Pareto point of the multiple criteria optimization (PV). 4.5. Solution to the medico - economic problem

Let us come back to the initial problem by means of the method presented in subsection 2.4. The data are in the following table:

i ci vi qi gi ri si 1 3200 0 -1.2 0 0 0

2 4100 0 4 0 0 5

3 6900 1 7 0 0 0

4 3100 0 15.8 1 0 0

5 7000 1 6.85 0 0 0

6 900 0 0 1 0.2 0

7 5300 1 7 1 0 15


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Taking equal weights, λ, = λ2 = λ3 = λ4 = λ5 = λ6 = 5

1,

function g is given by

( ) ( )7654321n21 x23x2.0x35.7x8.15x5.7x5.9x7.05

1x,...,x,xg ++++++−=

.

The optimum solution of problem (Q) is

( )1,1,0,0,0,0,0x = ,

meaning that Mrs. Moss and Patrick are selected for operation.

According to our opinion, this solution is more correct than that given by the cost-utility analysis, since it saves one of the three lives that should be saved and it solves one more application. We remark that the budget allows saving only one life. On the other hand, it is not in conflict with the medical Oath of Hippocrates, supposing first to protect the life itself and second to improve it. As we can remark, the ethical choice puts life itself before the quality of life all along the mankind history.

5. Example: the ecological modernization of the railway transport system

In this section we intend to study, using the welfare gained Wg index, more projects to ecologically modernize the railway transport system on the technological level. We intend to compare all the possibilities of ecologically improving the carriages from technical point of view. Three projects are possible:

Project P1) Ecological modernization of the box of the railway vehicle in order to improve the travelers’ comfort, basically on high speed (V > 160km/h); Project P2) Optimization, from constructive point of view, of the Lifting structure of the railway vehicle, especially of the bogie frame and tread apparatus, for avoiding shocks and transversal or longitudinal vibrations, which are source of major travelers’ discomfort; Project P3) Modernization of braking systems of railway vehicles, in order to produce as soft as possible breaking, with


deceleration allowed by the human body (af < 0; 8m=s2), in established braking way. One of the most important goals of the International Union of

Railways (UIC) is to enable the railway companies to measure the impact of their activity on the environment (see [11]). Environment indicators in the domain of railway transport are defined under UIC and the project RAVEL, funded by the European Union (RAVEL Sustainable Mobility Railway in the future Projects, see[12]). The Working Group UIC on environment presented the Guide to establish the indicators of environment for the railways, [12], that is updated each year and is included in the technical portfolio of the Committee C6 - UIC, dealing with economy, finance and environment protection. Four criteria are taken into account, according to this guide, in assessing the impact of the railway transport on the environment.

The data are presented according to the measurements made by the railway station of Arad and its depot. The costs are established by the Timişoara central unit of Romanian Railways, CFR. Criterion 1) Concentration of CO2 in air:

Normal: 0,03% from the atmosphere; Actual: 1,68 g/km; Estimated after improvement: 1 g/km;

Criterion 2) Level of noise: Normal: 50 dB(A) (STAS 10009-88 and STAS 6161/1-

79); Actual: 125-130 dB(A) (Noise produced by wagons); Estimated after improvement: 60-70 dB(A).

Criterion 3) Energy consumption: Normal: 4,5 t/day over 1 million tones / km; Actual: 4,05 t/day over 1 million tones / km; Estimated after improvement: 3,85 t/day over 1 million

tones / km. Criterion 4) Annual number of accidents:

Normal: 0 Actual: 2900 dead/year; Estimated after improvement: max. 1500 dead/year

Project (P1) is estimated to reduce the annual number of accidents by 3%, project (P2) by 2% and project (P3) by 35%. The following table contains the differences

jPkj pp − between the actual


23

variations and the variations induced by project (Pk) on criterion j, for k ∈ {1, 2, 3} and j ∈ {1, 2, 3, 4}. The costs, expressed in Romanian currency, are after the last evaluations.

Project CO2 Noise Energy Accidents Cost

1 0 0 7.5% 87 1.5 mill. lei / wagon

2 0 40% 17% 58 500 000 lei / boghiu

3 44% 30% 3% 1015 250 000 lei / br. sys

Since the costs of treating the damages are not supported by

CFR directly ([11]), this company paying only occasionally to each County’s Authority for Environment various amounts of money for damages, we take λ5 = 0. As consequence, the symbol < is used to describe the order of preference according to the four criteria only. In [6] the authors discuss about the significance of handling the effects of reinforced preference and counter-veto in credibility of outranking. Various experiments of decision aid are described in the following table. The first column contains the values given to pounds, presented as a vector λ = (¸λ1, λ2, λ3, λ4).

Weights Wg Project 1

Wg Project 2

Wg Project 3

Hierarchy Best

λλλλ1= λλλλ2=10


λλλλ5=0

94.5

475

1758

P1<P2<P3

P3


λλλλ3=1, λλλλ4=10

λλλλ5=0

877.5

815

10523

P2<P1<P3

P3


λλλλ3=10, λλλλ4=2

λλλλ5=0

259

790

2134

P1<P2<P3

P3

λλλλ1= λλλλ3=λλλλ4=1

λλλλ2=100,

λλλλ5=0

94.5

4075

4062

P1<P3<P2

P2


The weights are used to emphasize either the environment point of view or the humanitarian point of view or the energy consumption direction. In the first case we find that if the environment criteria (CO2 emission and noise) are of great importance, then project P3 seems to be the most suitable. The same result is obtained if the number of accidents is considered of greater importance than some other criteria. But project P2 seems to be the most preferred from the point of view of energy consumption. It is easy to see how such a gambling with weights procedure is able to provide the decision maker with a great amount of information on the consequences of each decision.

As consequence, the welfare gained index gives enough information to the decision group as to become conscious on the consequences of ones decision. Also, the method used to deduce this kind of tools is able to provide models to a wide range of decision problems, as the two examples presented in this paper show.

References [1] Baker, T., Ekins, P., Strachan, N., Energy-Economy-Engineering-Environment: An E4 Representation of the UK Energy System, UK Energy Research Centre, on line [http://www.ukerc.ac.uk]. [2] Brans, J-B. Mareschal, B., PROMETH´ EE-GAIA. Une méthode d’aide á la décision en présence de critères multiples, Édition de l’Université de Bruxelles, Édition Ellipses, 2002. [3] Galperin, E.A., Nonscalarized Multiobjective Global Optimization, J. O. T..A. 75(1992), 1, 69-85. [4] NeamŃiu, L., Applications of the Numerical Analysis, Optimisation and Informatics in Medecine (in Romanian), Ph.D. Thesis, ”Babeş-Bolyai” University of Cluj-Napoca, Faculty of Mathematics and Computer Sciences, Cluj-Napoca, 2007. [5] Phillips, C., Thompson, G., What is a QALY?, Hayward Medical Communications, 1, 6, on line [www.evidence-based-medicine.co.uk]. [6] Roy, B., Slowinski, R., Handling effects of reinforced preference and counterveto in credibility of outranking, European Journal of Operational Research 188:1 (2008), 185-190. [7] Siderius, H-P., Harrison, R., An Energy Efficiency Index for TVs, In Energy Efficiency in Household Appliences and Lighting (editors Bertoldi, Ricci, de Almeida), Springer Verlag, Berlin, 2001, 267-277.


25

[8] Taskin, F., Zaim, O., The role of international trade on environmental efficiency: a DEA approach, Economic Modelling, 18(2001), 1, 1-17. [9] Varsavsky, M., Legislation Efficiency Index, (2005) on line [http://english.martinvarsavski.net/general/legislationefficiency-index.html], posted May 29 2006. [10] Energy Efficiency Index, NUS Centre for Total Building Performance, on line [http://www.bdg.nus.edu.sg/buildingenergy/e energy/audit results.html]. [11] C.F.R., CFR şi protecŃia mediului, on line [http://www.cfr.ro]. [12] U.I.C., Guide to establish the indicators of environment for the railways, on line [http://www.uic.asso.fr/environment].


Environmental monetary valuation - an important step to estimate the economic-ecologic balance

Research conducted in the Project CNCSIS IDEI 1239/ 2007

S.G. Szentesi, G. Cristescu

Silviu Gabriel Szentesi, Gabriela Cristescu ”Aurel Vlaicu” University of Arad, Romania

Abstract

The economic sustainable development is a mainly concern of our day decision takers. We need to improve continuously our living standard that is the social command, especially thru economic development, but in the same time to maintain or to grow the welfare recording to the natural resources and environmental abusive utilization. A rational balance between economic development and natural resources and environmental exploitation is the task for assuring the welfare. Looking for a solution in that way the most reasonable is to start up the building this balance with every economic project with impact on environment and to calculate the balance between economic and ecologic aspects. The balance is relevantly a question of welfare. In the future the economists and decision takers have to consider this requirement in their decision. One of the first steps in this process is to evaluate the cost of environmental damage. Keywords: enviroment evaluation, model, balance,net present value

The term of “balance” comes from Latin, where “aequs” means

equal and “libra” means scale or equality. In nowadays’ language, “balance” refers to a quantity or quality stability of phenomena, objects, situations, without altering the state of the phenomenon regarded, at least not on a short term.

Environmental Monetary Valuation an important step to …

27

1. Contingent valuation methods

Contingent valuation methods (CVM) are techniques used to

analyze the value people attach to Environment changes, not by using actual or surrogate markets, but hypothetical markets. The main source of data of the CVM is the survey which employ questionnaires asking preferences of respondents representing the population who are potentially going to be affected by an assumed Environment change. The name "contingent valuation" implies that the choices people reveal in the survey assuming a hypothetical market are contingent on the actual occurrence of said market .

The bidding game is a CVM technique which directly asks respondents their willingness-to-pay (WTP) for a specific environment improvement or their willingness-to-accept (WTA) compensation for natural resources (NRE) or environment. There are basically two bidding game systems, the single-bid system and converging-bid system.

The procedure in the bidding game approach is as follows. First, the interviewer describes accurately to the respondent the specific features of the environment improvement or damage in question, including its quantity, quality, location, and the respondent's access rights. Next, the respondent is asked about his WTP or WTA associated to the improvement or damage by using a single-bid or converging-bid system. In the single-bid system, the respondent is asked only once about the amount he is willing to pay or accept in relation to the improvement or damage. In the converging-bid system, the respondent is given a starting bid which he is asked to accept or reject. Once a starting bid is accepted, higher or lower bids are given until the maximum WTP or the minimum WTA of the respondent for the improvement or damage is ascertained.Once the WTP or the WTA of all the respondents are known from the survey, individual WTPs or WTAs are then summed up vertically to come up with an aggregate bid curve for the environment improvement or damage. This bid curve serves as proxy of the income compensated demand curve in analyzing the total value attached by the affected population to the project which causes an improvement or damage.

The tradeoff game is a CVM approach which gives the respondent a choice between having a lower or higher level of an

S.G. Szentesi, G. Cristescu 28

environment good at no expense made or compensation received (base option) or a higher or lower level of the good but with some level of expenses made or compensation received (alternative option).In its simplest form, the tradeoff game gives the respondent a base option and a particular alternative option (which has a stated amount of money the respondent has to spend or receive) to choose from. If he chooses the alternative, higher or lower amounts of money the respondent has to spend or receive is set until he is indifferent between the base option and the alternative option. The final amount of money in the alternative option acceptable to the respondent is then taken as an approximation of his maximum WTP or minimum WTA for the difference in the levels of the environment good between the base and alternative options. As in the bidding game, the individual WTP or WTA are added vertically to come up with the aggregate bid curve for the good.

The costless choice is a CVM technique which provides the respondent an option to decide between quantities of goods which are desirable to him and at the same time provided free of charge (thus, costless). In the two-alternative case, the respondent is usually given a choice between an NRE good and an economic good. If the environmental good is chosen, the value of the economic good is taken as a measure of the minimum value the respondent attaches to the NRE good because by choosing the NRE, the respondent must have valued it at least as much as the economic good. If, on the other hand, the economic good is chosen, its quantity will be reduced until the respondent will choose the NRE good over it. Once this happens, the value of the final quantity of the economic good again serves as the minimum approximation of the value of the NRE good. The vertical sum of these minimum values across respondents serves as an estimate of the aggregate demand curve for the NRE good.The main difference of the costless choice approach from the other CVM approaches is that in making choices, the respondent will have his choice free of charge, that is, he will not have to pay anything for the NRE good if he chooses it or he will not have to lose any existing NRE good if he chooses the economic good instead.

The priority evaluator technique is similar to the costless choice technique in that respondents are also made to choose between goods, among which is an NRE good. The technique, however, is unique for three reasons. First, the technique allows adjustment of prices of the goods from their initially set levels, to encourage convergence to a set


29

of equilibrium values. Second, the technique considers only goods which meet conditions that simulate a perfectly competitive market, that is, the goods must be independent in production, they must be continuously variable in production and consumption and their consumption utilities must be independent of any other consumption. Third, the technique allows respondents to make choices between goods given constrained income.The specific steps followed in the application of the priority evaluator technique are relatively more complicated and lengthy than those of the other CVM techniques.

Delphi techniques are different from other CVM methods in that instead of interviewing representatives of the affected population, they generate opinion of experts on the NRE good in question. The Delphi technique usually involves experts residing in different areas. These experts who are independently asked through written communication about their valuation of an environment good. The initial values gathered from the experts are tabulated and sent back to them for further examination. Continuous re-evaluation by the experts is conducted until the valuation organizers believe a satisfactory average value of the environment good has been derived. The Delphi technique is highly useful for checking results of valuation studies using the other CVM techniques. No empirical literature using the Delphi Technique, however, is available for this review. 2. Benefit-cost analysis valuation methods

The benefit-cost (B/C) criterion is a well-applied technique for

judging the acceptability of a certain development project. In the context of B/C analysis, the acceptance of a proposed project whose implementation has negative and significant impacts on the environment is based on the following criterion:

Be / (Ce + Cn) > 1 (1) , where Be is the discounted total economic benefits to be derived

from the project, Ce is the discounted total economic costs and Cn is the discounted total environment costs. Cn is measured either as the value of environment benefits which is preserved if the proposed project is discontinued or, symmetrically, the value of environment costs if it is pursued.


For an environment -friendly development project, the equivalent B/C criterion is

(Be + Bn) / Ce > 1 (2) where Bn is the discounted environment benefits which is

measured as the value of lost environment gain if the project is not pursued, or symmetrically, the value of the environment benefit if the project is implemented.

The measurement of the environment cost, Cn, and the environment benefit, Bn, is usually done using microeconomic valuation methods. Actually, however, most B/C analysis excludes natural resources and environment costs and benefit valuation. A reason for this is that almost all natural resources and environment goods are underpriced, if not freely provided. This makes their "true" values difficult to measure.Several microeconomic valuation methods are employed in natural resources and environment analysis. As stated earlier, the rationale for reviewing these methods is that they are potentially useful for the project management, especially for investments in fix assets with high impact on environment and natural resources. Is necessary taken consideration on damage produced for evaluating the welfare effects of the natural resources and environment change induced by policies, once the change has been measured.

Evaluation reveals that the percentage of projects justified by cost-benefit analysis has been declining for several decades, due to both a decline in adherence to policy and difficulty in applying cost-benefit analysis. This study highlights that the society needs to revisit the policy for cost-benefit analysis to account for difficulties in quantifying benefits yet preserve a high degree of rigor in justifying projects. The study recommends that the our days society implement reforms to ensure quality, rigor, and objectivity in its cost-benefit analysis, and use the results to influence decisions and improve develpment assistance. 3. Microeconomic valuation methods

Microeconomic valuation methods can be classified into market-

oriented and survey-oriented methods. Market-oriented methods are further disaggregated into methods using actual markets and those employing surrogate markets.


31

3.1. Methods using actual markets 3.1.1. Productivity change method

The productivity change method measures the NRE impacts of a

project by looking into its on-site and off-site effects on the on the productivity of man-made or natural production systems. Theoretically, the method assumes that NRE quality is another input in the production process. Therefore, the production function can be reformulated as

X = f (L, N, K, E) (3) where X is the output, L, N and K are the usual inputs land,

labor and capital and E stands for NRE quality. In this revised production function, it is posited that a change in E will change production costs which, in turn, either change the quantity and price of the output or the returns to the other inputs or both.

The general steps followed in quantifying productivity gains or losses from NRE changes using the productivity change method are:

a. measurement of the production response to the NRE quality change and then quantification of the gains or losses of producers in terms of increases or decreases in profits;

b. measurement of the consumption response to production changes and then quantification of the gains or losses of consumers in terms of changes in consumer surplus;

c. measurement of the gains or losses of owners of factor of production in terms of increases or decreases in factor returns; and

d. measurement of the total benefits or losses from quality changes by aggregation of the different values attained in the previous computations.

Where efficient markets exist, the valuation of productivity gains or losses from NRE quality changes in each of the above steps is based on actual market prices. On the other hand, when markets are distorted, adjustment will be made so prices used in valuation to reflect true prices.

The productivity change method is often used in valuing the productivity effects of projects affecting the land, such as projects which cause soil erosion, improve quality of irrigation water or abate water pollution caused by industries.


3.1.2. Human capital method The human capital method is used to assess the impacts of NRE

changes on people. It is founded on the generally accepted notion that NRE damage can have negative and significant costs on human health.

The human capital method measures the human costs of NRE damage by valuing the foregone opportunities of people resulting from NRE-induced health problems. In the case of premature illness or death of an individual, the following general formula of Mishan (1972) can be used as the measure of the value of the life:

( ) ( )Tt

t

Tt

t rYL−−

∞

=

+=∑ 1P tT1

(4) , where L1 is the discounted value of the labor of individual 1; Yt

is his expected gross earnings, or value added, in the t-th year outside of returns from non-human resources he owns; PtT is the current (year T) likelihood that he will be alive in year t; and rt is the social discount rate in year t. The sum of the cost of death of the individual is L1 plus the medical costs. However, these costs can be expanded further to include the money value of the disutility related to the suffering of the family and friends of the individual. This method is used to estimate the value of morbidity and mortality associated to air and water pollution. The value of the health effects of air pollution is significantly more than the value of the health impacts of water pollution although both types of pollution affects health substantially. 3.1.3. Opportunity cost method

The opportunity cost method is based on the opportunity cost

concept, which, for a given resource, is defined as the value of the benefit that accrues from the best alternative use of the resource. In NRE valuation, there are basically two kinds of opportunity costs: the opportunity cost of development, which is measured as the present value of the benefits from preservation, and the opportunity cost of preservation, which is estimated as the present value of the benefits from development.

Empirically, the opportunity cost method is more often used to measure the opportunity cost of preservation only. This is because the benefits from development, or the opportunity cost of preservation, can


33

be easily quantified from existing markets. The method is seldom used to measure the opportunity cost of development, which is the value of preservation benefits, because many of the goods produced by preservation are not traded and are difficult to estimate.

An opportunity cost technique often used for assessing the cost of preservation is the computation of the net present value of value (NPV) from a project. The general form of the net present value formula

is

( )( )

∑= +

−=

n

tn

tt

t

CBNPV

00

1 (5) where NPV0 is the net present value in year 0, Bt and Ct are the values of the total benefits and total costs in year t, r is the discount rate and n is the number of years of project life. If the NPV of the project is small relative to some estimated value of preservation, the project is rejected. 3.1.4. Cost-effectiveness method

The cost-effectiveness (C-E) method is a criterion useful for comparing projects that has comparable outputs. The method selects among projects the one which either minimizes costs given a fixed output or maximizes output with a fixed cost. In the case of the NRE sector, the output of concern may be some kind of NRE quality level, such as a certain pollution standard for instance.

With the nature of its objective, the empirical application of the C-E method can be done by employing mathematical optimization and programming models which generate optimal solutions that leads to the selection of the optimal project. The method, however, may use also the traditional approach of simply comparing financial estimates between competing projects.

In practice are studies using optimization and programming models for C-E analysis. An application of the method is in the search for the best alternative for controlling a specific disease.

3.1.5. Preventive expenditures method

The preventive expenditures method is a valuation approach which measures the value people attach to NRE quality through the expenditures people incur to prevent quality decline.

The preventive expenditures method assumes that when faced by a decline in NRE quality, e.g. neighborhood air pollution, the individual


affected has the choice of ignoring the problem, moving to another area or spending on measures which mitigate the problem. The amount spent by the individual to prevent the quality decline is taken as his personal valuation of the NRE quality before the deterioration occurred. The total of the expenses of all affected individuals for preventive measures is then used as the substitute demand curve for NRE quality. The preventive expenditures method has been fairly applied internationally.

3.1.6. Replacement cost method

Similar to the preventive expenditures method, the replacement cost method provides a value of environment quality. In contrast, however, the method takes as proxy measure the cost of replacing productive assets destroyed or rendered unproductive by the deterioration in environment quality.The cost of replacement is usually counted in terms of market values of physical replacements (e.g. cost of fertilizer to solve soil fertility loss). Therefore, the replacement cost method is a relatively straight-forward one to implement, assuming that it is technically feasible to replace damaged systems. 3.1.7. Shadow project method

The shadow project method is a special type of the replacement

cost method which uses the cost of putting up a hypothetical shadow project which provide an alternative source of the environment goods lost to development as the substitute estimate of the value of the natural resources and environmental goods. Assuming technical feasibility of a shadow project, the method is straightforward to apply although understatement of costs will likely occur since the total value of the lost environmental good may always significantly outweigh the cost of the shadow project. 3.1.8. Relocation cost method

The relocation cost method is similar to the preventive

expenditures method but instead of estimating expenditures on prevention, it uses the cost of relocation from the area where there is an environment problem to an area where environment amenity is better as a proxy measure for environment quality. The amount the individual is


35

willing to spend for the relocation is taken as his valuation of the benefits of an improved environment quality in the new area or the cost of disamenity in the old location. 3.2. Methods using surrogate markets

In contrast to valuation methods directly using actual markets

reviewed above, the methods reviewed below indirectly use actual markets only. These methods are called surrogative methods because they estimate the value of unmarketed environment goods by using the values of other marketed goods. These methods are also known as hedonic price methods and have their beginnings in the work of Rosen (1974).

3.2.1. Marketed goods as environment goods surrogates method

This method is useful for measuring the benefits of environment improvement in situations where a privately marketed good is a perfect substitute for an environment good. In such a case, the value of costs or benefits from the fall or rise in the supply of the non-marketed environment good is approximated by the value of the increase or decrease in the demand of the marketed private good.The marketed goods as environment goods surrogates method is easy to apply since the demand for the substitute goods that are marketed are usually easily known and, thus, measured. A constraint of the method is that isolating the change in the demand for the marketed substitute good specifically induced by the change in the supply of the unmarketed environment good can prove difficult.

3.2.2.. Property value method

The property value method estimates the value people attach to

an environment improvement, such as a decline in air pollution in a certain locality, by studying the actual market for real properties, such as housing, that are affected by the improvement.Taking the housing and air pollution example, the property value method is applied by first assuming that the area analyzed is a single, well-functioning and competitive market for housing. Under these assumptions, the following relationship can be defined


Ri = f ( Pi, Ai, Ni, Ei) (6)

where: Ri = price of housing (usually measured as rent per unit of time); Pi = physical characteristics of housing such as house size, lot

size, number of rooms, age of house, type of construction materials, etc.;

Ai = accessibility characteristics such as distance to market, school, church, place of employment, etc.;

Ni = neighborhood characteristics such as average income of neighborhood residents and crime rate of neighborhood, etc.; and

Ei = air quality or pollution level in the housing location. Computationally, the method proceeds by assuming a functional

form for the relationship in equation (6). Assuming a linear function, the estimated equation is

Ri = a0 + a1 C1i + a2 C2i + ...+ an Cn + ae Ei + ei (7)

where a0 is the intercept, the ais are the coefficients, Cis are the housing characteristics, ae is the coefficient for the air quality variable Ei and ei is the error term.With a linear equation, the marginal willingness-to-pay (WTP) for an additional unit of improvement in air quality is measured by the coefficient ae. The total incremental benefits of an air pollution reduction program that improves air quality is estimated by

( )121

QQaVs

i

ni −=∑= (8) ,

where V is the total incremental benefits, Q2-Q1 is the improvement in air quality, and s is the number of housing in the study site.

3.2.3. Wage differential approach

The wage differential method is similar to the property value method except that here, instead of the market for real property, the market for labor is used as the surrogate market for environment quality.The wage differential method starts by assuming a competitive


37

labor market situation where the main motivation of workers for accepting jobs associated with greater exposure to environment hazard is higher remuneration. Then, it assumes a wage equation of the form

Wi = f ( Ji, Li) (9), where: Wi = wage level i; Ji = non-environment related job attributes such as distance

from residence, etc.; and Li = environment-related job attributes such as exposure to air

pollution, etc. Equation (9) is estimated assuming a specific functional form. If

the functional form is linear and the environment-related factor considered is air pollution at the job site, then the estimated equation is

Wi = b0 + b1 D1i + b2 D2i + ...+ bn Dn + be Ai + ui (10) where b0 is the intercept, the bis are the coefficients, the Dis are the job characteristics, ae is the coefficient for the air quality at the site variable Ai and ui is the error term. The marginal willingness-to-accept (WTA) a higher or lower wage for a unit of additional unit of decrease or increase in air quality at the site is given by the coefficient be. The total amount workers are willing to accept for a reduction in air pollution at the job site is estimated by

( )∑=

−=s

i

ni WWbV1

12

(11) ,where V is the total change in wage and W2-W1 is the change in air quality. 3.2.4. Travel cost method

The travel cost method is an approach used for measuring the

value of public recreational services such as parks, amusement centers and similar amenities. The method was developed because directly estimating the value attached to these places by users based on subsidized admission fees will grossly underestimate true values.For the analysis of a specific recreation site, application of the travel cost method employs the following steps:

a) zoning of surrounding areas of the recreation site (where


visitors come from) based on distance from the site; b) surveying the site users to get information on zones of

origin, visitation rates, travel costs and socioeconomic characteristics; c) estimating the following visitation rate function of each zone:

Vi = f (TC, X1, ..., Xn) (12) where: Vi = visitation rate computed as the number of visitors from the

zone i divided by population of the zone (This is can be varied by subdividing further the zone into specific areas, e.g. districts); and

TC = is the travel cost (time and resources costs) of each visitor from the residence to the site; and

X1...Xn = socioeconomic variables associated to each visitor. d) using the information from step c) to create a demand curve for

each zone relating travel cost to total visitation; e) computing the consumer surplus from each zone assuming an

actual user admission fee; and f) summing the consumer surpluses for all zones to arrive at total consumer surplus.

This total surplus estimates the gains by all users from the use of the site. Bibliography

Accounting: Insights for Philippine Policy-Making, Paper Presented at the International Workshop on the Contribution of Policy of Environmental and Natural Resource Accounting held in Tagaytay City, Philippines on 16-21 January 1994. Angeles, M., Philippine Environmental and Natural Resources

Accounting Phase II: Empirical Findings and Insights for Policy-

Making, Paper No. 1, Environmental and Natural Resources Accounting Project Phase II Final Workshop, INNOTECH, Commonwealth Avenue, Quezon City, March 16, 1994; Australia Biological Diversity Advisory Committee, Making economic valuation work for biodiversity conservation,.Publisher: Canberra, Land and Water Australia, 2005; Cabrido, C., Jr. and E. Samar, Economic Framework for Land Use Decision Making Cost Benefit Analysis of Various Land Uses, Paper


39

No. 9-1, Environmental and Natural Resources Accounting Project Phase II Final Workshop, INNOTECH, Commonwealth Avenue, Quezon City, March 16, 1994; Danilo C. Israel, Review of Macroeconomic Models and Microeconomic Valuation Methods Applied in the Natural Resources and Environment

Sector 1994 Ebarvia, M. C, Valuation of Environmental Damages, Workshop Paper No. 3, Environmental and Natural Resources Accounting Project Phase II Final Workshop, INNOTECH, Commonwealth Avenue, Quezon City, March 16, 1994. H. Peskin and M. C. Bennagen. Environmental and Natural Resource, (1994); J.Asafu-Adjaye. Environmental economics for non-economists

techniques and policies for sustainable development , Publisher World Scientific Singapore 2005; Tisdell, CA Economics of environmental conservation,.Publisher Cheltenham, UK, Northampton


Designing a management model for achieving economic-environmental balance in investment

projects Research conducted in the Project CNCSIS IDEI 1239/ 2007

S. G. Szentesi, M. FranŃescu, S.Crişan

Szentesi Silviu Gabriel, Crişan Simona “Aurel Vlaicu” University of Arad FranŃescu Marius National Meteorological Administration

Abstract This paper describes a method for achieving the economic-environmental balance based on the assessment of environmental and/or pollutant factors in connection to community option on the evaluation of investment projects having a major impact on environment. This assessment is based on the concept of welfare, the distinction between satisfaction and dissatisfaction and implies a practical approach including the scientific aspects of environment pollution degree and the community position on developing an investment project, by assuming responsibility for negative and positive aspects of such a project, respectively for satisfaction and dissatisfaction, in order to fulfill the supreme goal of preserving the environment and ensuring human welfare. Keywords: Pareto optimum, satisfaction/dissatisfaction, model, economic-environmental balance

Designing a management model for achieving …

41

1. Definition of welfare and the historical evolution of the welfare concept

Social welfare indicates the satisfaction or utility degree gained by each participant, but is not equal to the sum of individual welfare.1

Pareto concept of welfare represents a milestone in economics history. Until then it was considered that the welfare is the sum of communities’ quantifiable cardinal utilities, the optimal resource allocation maximizing the welfare.

As noted before, Pareto optimum is defined as the point that allows the improvement of a certain individual welfare, meaning his movement to a preferred position by adjusting goods or services through production or exchange without affecting someone else’s welfare. In order to remove the need for interpersonal utilities’ comparison, Pareto has refused to assess any other changes of welfare. Therefore, his definition drops the concept of unique social optimum, providing instead an infinite number of unmatched optimums.2 The comparability area can be extended by introducing the concept of compensatory payment. This concept was mentioned first by Enrico Barone in his famous article called “The Ministry of Production in the Collectivist State” (1908). Barone suggested that all individual welfare changes can be expressed using the real equivalent income an individual agreed to receive or pay in order to regain his original welfare.

A change that favors certain individuals in the detriment of others can still generate an improvement of global welfare, if those who earn can compensate the losers, so they voluntary accept this change, after compensatory payment is made, and the winners are better off, but also the losers are not in a worse situation. In order to better understand this statement, we consider the example of coexistence of an airport and its surrounding areas. The airlines company and its passengers are the winners, while the neighbors are the ones that lose because of sonic pollution. The inhabitants have nothing to lose if they are compensated for their loss, finally obtaining an increased community welfare.

1 Gilbert Abraham-Frois -Political Economy, Editura Humanitas Bucureşti, 1994, pag. 312. 2 X* vector is the optimum solution if from the equations: fi(x) ≥ fi (x*) (i=1,2..., m) we have fi(X) = fi (X*) (i=1,2..., m). When fi(X) are concave, and the admissible set of solutions x is closed and convex, then for each Pareto optimum x* we have weighting coefficients that maximize the amount at x*. This point provides the best available welfare.

S. G. Szentesi, M. FranŃescu, S.Crişan 42

The Pigovian economy of welfare implies a Pigou analysis of the divergence between private marginal profit and social marginal profit. It is the problem of real external economies or diseconomies in relation with income marginal benefits. Pigou describes in his work „The Economics of Welfare” social losses such as: industrial accidents, professional diseases, child and women employment, air and water pollution, technological unemployment. The measuring of such diseconomies is a difficult task because of their pretty difficult “internalization” as they are considered outside the price system by definition.

A reward of Pigovian economics of welfare when the society goal is to maximize the difference between global benefits and global costs, shows that in a market where the price equals the marginal social cost of a product, the Pareto optimum condition is met. This can be better explained in the case of an economic activity generating external effects (diseconomies).

2. Practical considerations on designing an economic-environmental balance model for investment projects

The investment projects for fixed assets having a major impact on environment must be assessed and classified according to models that lead to their approval or rejection. Tha major pollutant investment projects are thermal plants, electric plants, power stations, nuclear plants, etc., but also investments in the chemical, petrochemical, steel and rubber fields. The development of a model implies, besides scientific and theoretic issues such as the acceptable pollution level, eco, green and clean technologies, also a responsible involvement of all parties involved in the positive and negative outcomes of an investment project development. These parties can be the beneficiary of the investment, the environmental agency, the developer, local administration, population, farmers from the affected area, other individuals or legal entities affected by the investment project development. Therefore, in taking the approval or rejection decision, the parties involved must assume a point of view based on a scale derived from the one suggested by the theoretic model, that can be a Stapel scale, as follows:


43

Stapel scale

Maximum pollution Null pollution ____________________________________________

-5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5

In addition to assessing the pollution level on the main environment components – air, water, soil, etc. – we need to quantify the importance of each type of pollution and/or pollutant, using a weighting or importance scale (similar to the one included in the theoretical model). Through this practical approach we can determine the degree of satisfaction and/or dissatisfaction for each issue of the analyzed investment project. For example: noise level, level of suspended particles in the air, radioactivity level, thermal pollution, chemical substances soil pollution, water pollution, etc. Such an approach facilitates the classification of suggested project alternatives, the decision-taking process regarding mutually exclusive projects and the collectivity involvement in assuming both benefits (satisfactions) and pollution (dissatisfactions) generated by such an objective.

Its practical implementation implies an active collaboration with the Environment Agency, environment experts and professionals in investment projects’ design, in order to develop a model for pollutants that allows the measurement of the perceived satisfaction or dissatisfaction level, and finally to achieve a global level of satisfaction or dissatisfaction regarding the development of an investment project, based on weighting these elements with the importance assigned to each pollutant.

The main equation is:

i

k

i

ij pABB ⋅=∑=1

where: Bj- is the j party score for a project or project alternative, which indirectly expresses a certain level of welfare as a result of project development; ABi- is the welfare level influence degree generated by the influence factor or pollutant i pi- is the weight of the influence factor or pollutant i


i=1,.., k is the number of pollutants

n

B

B

n

j

j∑== 1

where: B- is the global score of a project or a project alternative, which indirectly expresses a certain level of welfare as a result of project development; j=1,..,n is the number of parties involved in assessment.

For each investment project, the Environment Agency identifies the parties involved in preserving the environment and the parties affected by the project development, on the basis of an impact study. The Environment Agency provides the assessment applications to the beneficiary and the parties involved, and requires their response before the final notice of the project. The assessment application can also be provided to a representative sample of the affected population; in the case of major investment projects having complex implications on the economic-environmental balance, a full research can be done. 3. Case Study: Recycling plant and aluminum casting

Recycling plant and aluminum casting is a model for both investors and good practices regarding the collection and selection of waste. Pioneer aluminum recycling begins with the discovery potential of the area, with good cooperation and support from local authorities.

The raw material used is composed of 90% of aluminum waste. They are sorted, analyzed and stored according to quality and chemical composition. Waste is then recast in a mix containing other alloying metals metallurgy obtaining required customer specification. To obtain an aluminum alloy from recycled waste requires low power consumption of only 5% compared with conventional aluminum production by electrolysis process, which contributes to reducing the consumption of natural resources. The merit of such a plant is established both on industry and commerce and in terms of employment. A more analytical way of evaluation of an investment project using the model presented in this paper can be formed on the basis of


45

scoring sites (-10 → 10) given by the authorities, specialists and the local population directly affected by the operation unit in question. Table 1. Scoring software provided by the relevant institutions/experts/public environmental factors assessed, with reference to a recycling plant and aluminum castings (-10 → +10)

F1 F2 F3 F4 F5 F6 Factors evaluated

Institutions/ populations

Air quality (air

pollution)

Surface water quality

(hydrological pollution)

Groundwater quality

(hydrogeological pollution)

Soil quality (pedological pollution)

Flora (vegetation)

Noise

1 Local administration

-1 0 0 0 1 +8

2 Local environmental protection agency

-3 -3 -2 -2 0 +6

3 Local Public Health Department

-2 -2 -1 -1 0 +7

4 Local Department Romanian Waters

1 -2 -1 0 1 +7

5 Local Direction land reclamation

1 -2 -1 -1 1 +8

6 Local farmers Association

-1 0 -1 -2 0 +6

7 Operators in tourism sector

1 0 2 1 2 +8

8 The population surrounding areas (200 households)

-2 -2 -1 -1 1 +8


Table 2. Scoring average obtained for each environmental factor evaluated (-10 → +10)

Total dissatisfaction Indifference Total Satisfaction

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5 +6 +7 +8 +9 +10 F1 * F2 * F3 * F4 *

F5 * F6 *

To obtain values of type Stapel scale, positioned tabulated

below, were taken into account air pollution, surface water and groundwater (especially groundwater) with: HCl, SO2, NO2, dioxins, particulate matter, particulate sedimentation, and noise pollution.

Table 3. Positioning aluminum recycling factory type Stapel Scale (-5 → 5) in terms of environmental Institution → Indicators

↓

Share

Local environmental protection agency

Local Public Health

Department

Population (community) in

the area

Air pollution 0,50 -3 -2 -2 Water pollution 0,30 -3 -2 -2 Pedological pollution

0,15 -2 -1 -1

Noise 0,05 +6 +7 +8 Total 1,00 -2 +2 +3

-0,50 +0,50 +0,75 Average +0,25

Stapel Scale

Maximum pollution Null Pollution ________________________↓_______________________ -5 -4 -3 -2 -1 0 +1 +2 +3 +4 +5 The results are relatively good, but special attention must be

paid, however, particularly air pollution, and water and soil, the results


47

presented above and in the opinion of specialists. Regarding the first four factors evaluated (air quality, surface water, groundwater and soil) to produce a scoring -1, value that is not a very serious situation as regards the environment. The influence of vegetation around the recycling plant and aluminum castings, achieve a better scoring positive, 1. Of all the factors taken into consideration, get the best noise scoring 7, which shows that the recycling plant and aluminum casting does not cause discomfort in terms of noise. Regarding other discomforts created dissatisfaction and a recycling plant and aluminum casting, is highlighted human health in general and respiratory diseases including, but not yet alarming.

With the results obtained and presented to it can be concluded that the functioning of an economic unit (industrial) type of recycling plant and aluminum casting can bring rewards and benefits to the community, provided they meet the standards of labor protection, employees and rules preventing and combating environmental pollution.

Bibliography

BOOKS: Silviu Szentesi, Fundamentals of Statistics, Ed. Institutul Biblic “Emanuel”, Oradea, 2000; Silviu Szentesi, Investment decision process, Ed. U.A.V., Arad, 1999; Silviu Szentesi, Economy and Environment, Ed. Servo-Sat, Arad, 1998; David W. Pearce and R. K. Turner, Economics of Natural Resources Environment,. Harvester Wheatsheaf, London, 1990; Silviu Szentesi, Management of investment projects, Ed. UniversităŃii “Aurel Vlaicu” , Arad, 1998; Szentesi Silviu and Cureteanu Radu, Management and analysis of investment projects, Editura Mirton Timişoara 2004; Silviu Szentesi, Management and efficiency of investment projects, Editura Expert , Bucureşti 2002; Coordonatori. C. Florescu, P Mâlcomete, N Al. Pop Marketing. Glossary., Editura Economică 2003, coautor. Silviu Szentesi, Sergiu Rusu, Radu Cureteanu, Economic activity statistics,. Editura Mirton Timişoara 2005; Silviu Szentesi, Economic statistics, Ed. Institutul Biblic “Emanuel”, Oradea, 2000; Silviu Szentesi, Statistics for Business Management - applications, Ed.


Institutul Biblic “Emanuel”, Oradea, 2000; S.Szentesi,E. Ionescu, R.Lile, L. Balan, S. Rusu, Statistics, Editura Concordia, Arad, 2007; S.Szentesi,E. Ionescu, R.Lile, R. Cureteanu, S. Rusu, Statistics, Editura Concordia, Arad, 2006; Silviu Szentesi, Statistics, Editura CARD Bucureşti 2003; Silviu Szentesi, Trade and International Affairs, Tipografia “Universum Trade”,Arad 2001; Mark Blaug, Economic Theory in Retrospect, Editura Didactică şi Pedagogică,. Bucureşti, 1992; Cretì, Anna The Economics of Natural Gas Storage, A European Perspective (Ed.) 2009, XII, 116 p. 20 illus., Hardcover, ISBN: 978-3-540-79406-6; David Anderson, Environmental Economics and Natural Resource Management (Hardcover) United States, New York Regulations:

Law No 265/2006 (OJ 586, 06.07.2006) for the approval and amendment of EGO No 195/2005 (OJ 1196, 30.12.2005) on the environmental protection Council Directive 96/61/EC of 24 September 1996 concerning integrated pollution prevention and control, OJ L 257, 10.10.1996, p. 26-40 Order 152/2005, concerning integrated pollution prevention and control, published in the Official Gazette of Romania. Issue 2078/30.11.2005; Treaty establishing the European Community (in particular Article 174). Decision 1600/2002/EC of the European Parliament and of the Council laying down the Sixth Community Environment Action Programme, OJ L 242, 10.9.2002, Directive 92/43/EEC regarding the conservation of natural habitats and of wild fauna and flora, amended by de Directives 97/62/EC, 2006/105/EC and Regulation (EC) No 1882/2003 http://www.mmediu.ro (is hosted by the Ministry of ENVIRONMENT of Romania) http://www.cleaner-production.de (is hosted by the Federal Environmental Agency of Germany and provides comprehensive, in-depth information on the performance of German environmental technologies and services)


Evaluation model for the economical-ecological balance Research conducted in the Project CNCSIS IDEI 1239/ 2007

S. G. Szenteşi

Silviu Gabriel Szenteşi Faculty of Economics ”Aurel Vlaicu” University of Arad, Romania

Abstract Evolving of models for realizing an economical-ecological balance for accepting or rejecting investment projects should be increasingly from practical viewpoint, implying a more elaborate theoretical approach and scientific fundamented. Even if we have pertain to an economical approach and aim a level of updated real net income fairly high for each accepted project, the model also includes ecological component monetary tackled, but fundamented from welfare viewpoint. Proposed model proves practical utility and has the ability to generate individual and social welfare. Keywords: investment projects, cost of pollution, total net present value, enviromental criteria

1. Investment projects and pollution

Investments represent an important factor of economic and social development. There are many situations when investments and investment projects with major environmental impact especially, such as those from energetic field, chemical industry, mining or ferrous metallurgy, besides bringing about benefits they lead to appearance of externalities pollution likeness or significant deterioration of environment, even if it is not felt directly and actively as a high pollution. How much deterioration of environment is, for investment projects represents a problem which neither theory, nor economical practice or policy-makers can neglect anymore. Lasting development

S.G. Szentesi 50

involves efficient and responsible decisions, in order to achieve a dynamic economical-ecological equilibrium.

When taking decisions on an investment object is important to compare the investment (project cost), net profit (gain) and total economic value which is lost because of the project.

Figure 1 The evolution of investment process and pollution

where the following symbols were used:

C - Cost of production during objective operation; Q - Output value during objective operation; D - Objective economic lifetime; Df - Objective physical lifetime; T - Duration of investment recovering; S1 - Total investment value; S2 - Value of benefit for investment recovery (S2 = S1); S3 - Amount of net profit (gain) obtained by objective operation during economic lifetime Based on presented relations can be established: 1. If S3-Bc > 0 investment project is realized or modernized 2. If S3-Bc < 0 investment project is not realized or modernized where: Bc - Benefit obtained as a result of environment preservation and therefore of investment project unfulfilment or area development

Evaluation model for the economical-ecological balance

51

Total economic value represents actually measurement unit for preservation benefit Bc, meaning of total amount for asset remained as natural environment.

Benefits and costs of the project can be measured relatively easily because they are presented as data based on market prices. This is not the case for total economic value and so it is necessary to investigate ways for measuring the components of total economic value.

Such an assessment represents a practical and theoretical particularly complex problem which has not been fully clarified till present. Importance of techniques’ elucidation for establishing the total economic value is that decisions for investment or function maintenance of various economical objectives are based on it.

Total economic value of natural environment is the main element also for both benefit measurement of environment improvements and measurement of environment damages.

If consider one development project whose total economic value lost due to this project or gained because of its unfulfilment must be calculated (Fig. 1), it can be concluded that losses and benefits are opposite sides of the same concept.

2. Environmental perspective

Nature and living creatures (including humans), considered from their interdependece perspective, are driven by distinct laws ensuring a natural dynamic balance between different ecosystems.

Along with the development of economic activities, the natural balance of different ecosystems was affected.

We can affirm that nature regenerates itself or has the ability to create a new balance between ecosystems and economic activities, but this ability is constrained, and economic activities determine a constantly growing accumulation of polluting factors in the environment, making impossible their annihilation. Finally, the environmental balance is affected, with undetermined extraeconomic and economic effects, influencing even the human race existence. Starting from this statements, Dansereau formulated in 1957 a series of rules for interaction between man and environment. Reversion law – the environment tends to regain the lost positions right after the ceising of humn economic activities. The cultivated land, abandoned from various reasons, is spontaneously reintegrated in the nature; Irreverisibility law

S.G. Szentesi 52

– certain renewable natural resources becomes unrenewable when humans, through irrational economic measures, interrupt them or the conditions in which the cycle takes place; Reversed action law – Any environmental change as a result of human economic activities has consequential effects on economy, social life and even health. Massively cutting forests in ancient Italy had fatal consequences on agriculture.

Summarizing, the human action on the environment results are: disturbance of bio-geo-chemical cycles – through removing materials from the cycle and transforming cyclical processes in acycylical ones; change of environment’s chemical composition – through discharging waste on rivers; replacement of natural interaction systems – with human social-economic activity determined interaction systems; replacement of environment’s natural components with artificial ones (for example: earth crust completely human controlled).

Regarding the interaction between humans and nature, Vemadski and Teilhard de Chardin introduced the concept of noosphere (deriving from the greek noos = brain, intelligence, intellect). Noosphere means human rational, conscious control of the environment, based on ecological principles. This is a necessity for ensuring the existence of future generations. One of the basic conditions to be met is to control and maintain the environment pollution in acceptable limits in order to ensure the conditions for sustainable functioning and development of the society.

These concerns regarding the human rational, conscious control of the environment (ambient) materialized in the 80s and 90s in a new interdisciplinary science, environmental economics, that intends to identify the relationship and the methods for rational environmental management, condiered an economic resource, on the basis of the hedonistic principle of achieving maximum social satisfaction with a minimum of insatisfactions.

Returning to ecology, we can say that pollution has a totaly different meaning than the economic one, in any ecosystem pollution being a shock that detonates a growing imbalance as the polluters quantity increases. The balance is decisively broken when the polluters quantity exceeds the environment’s capacity of absorption.


53

In figure 2 the horizontal line AA' is the environment’s absorption capacity; the line OP is the pollution level. The balance is broken when pollution exceeds E.

Figure 2 – Pollution and environment’s absorption capacity

Pollution A E A’

O QE* Production level We can say that QE* is the „optimal” level of activity from an ecological point of view, of course if the absorption capacity is not exceeded but for an activity level above QE*. In reality we canot speak of an optimal QE* representing the maximum flow of activity accepted by the receiving environment during a certian period of time. We notice that curve AA is just an approximate representation; it is not easy to precisely determine the extreme environment capacity, we can identify an undetermination area (the drawing area).

We cannot state that pollution is present only from a starting point. It is obvious that as soon as it becomes positive, it generates imbalances in ecosystems, and when it reaches the maximum tolerable ecological level (E), it becomes harmful and implies a social cost from the economic point of view. The point E in figure 2 is an ecological ceiling, and an economic doorstep.

3. Comparative analysis of economic and ecologic criteria

The comparative analysis of economic and ecologic criteria

allows us to state that ecology and economics are two different and antinomic fields. The analysis purpose is not to determine which of these two fields must prevail, but to identify guidelines for solving the

S.G. Szentesi 54

economic-ecologic balance. As the society will have a certain protection of the environment as a goal, it must accept that only the economic criteria are not sufficient for adopting decisions.

Finally, the problem regards the environment’s absorption capacity, including the capacity to recycle the waste, the crowding limits, the ecological processes and space covering.

We cannot conclude that economic activity must be ceised or limited, it would be a nonsense, but if the society decides that environmental protection is important, it must limit certain activities to a level that does not exceed the environment’s absorption capacity. The cost-benefit analysis itself cannot identify such a purpose. Usually, a „good” analysis must involve a proper cooperation between the involved factors: public administration (government), companies and community members. This means to get over the fact that economic analysis is not capable of measuring everythin in monetary units, and accepting the fact the cost-benefit analysis is unable to evaluate ecological phenomena and the risks associated. This perception deficiency makes the existing generation to undertake risks for the future generations, and from this must come at least the carefulness, if not the thoughtfulness. More than ever, the environmental issues remind us that economics cannot manage everything and that J. St. Mille’s statement - „he is a poor economist who is just an economist” is more actual than ever.

All this approches depend on the power of natur, the natural environment and the asimilation power and on the evolution of tehnologies.

Figure 3 – Pollution and environment’s assimilation power related to tehnologies Pollution P A E A’

0 QE* Production level with new tehnologie


55

4. Prezent total net value – criteria for decision maker

For accomplishing economical-ecological equilibrium for an investment project it can be used a model based on estimation of updated total net income. This model requires a comparison of incomes total amount in their updated form and costs and damages produced by investment objective during conception, operation and sometimes after its closing. Main income categories on the one hand and losses, damages on the other hand are:

A. REVENUES 1. Updated net incomes obtained as a result of investment objective operation - VNA 2. Updated net wage incomes - VSNA; 3. Updated state incomes - taxes, social insurances, etc. - VASTA; 4. Incomes involved by investment objective existence and operation - VAA; 5. Incomes resulted from residual sale - VRA. B. LOSSES, DAMAGES, COSTS 1. Environmental damages produced by objective accomplishing - DMA; 2. Pollution produced during lifetime - PDVA; 3. Pollution generated by manufactured and sold products, performed services; updated - CHDPA (updated remediation costs); 4. Updated costs for natural environment restoration after economical activity - CRMA. One first model which can cause updated total real net income

without taking into account the social component and state incomes would be possible starting with all previous indicators. Updating can be done when making an investment decision or at the time of objective commissioning.

r

d

h

ah

T

h

ah

T

h

ahrta VnDnPnVnVn +−−= ∑∑∑=== 111

1

where: T = lifetime of investment objective;

S.G. Szentesi 56

Pnah = updated net losses since "h" year produced by environment deterioration because of objective operation, which can be determined by impact studies; Vnah = updated net income since "h" year obtained through objective operation; Dnah = updated losses produced by environment deteriorations during "h" year due to environment damages during objective construction; Vnr = residual net income obtained by removing the use of objective; Vr = residual income obtained from the goal out of service; Vnrta = total real net income, which represents the total real benefit of the community obtained as result of objective operation.

The second model involves an extension of the calculation and financial analysis to an economic analysis, according to a model similar to World Bank where in addition to issues strictly related to company’s cost-benefit analysis there are quantified also private social benefits and state incomes. Such a model also based on updated total actual net income is:

Vnrta=VNA+VSNA+VASTA+VAA+VRA– –DMA–PDVA–CHDPA–CRMA Where,

( )hDd

h

ha

VnVNA+

⋅= ∑+

= 1

1

1 , VNA is total of discounted cashflows generated by the investment

project

( )hDd

h

ha

VSNVSNA+

⋅= ∑+

= 1

1

1 , VSNA is the value of total net present average salary

( )hDd

h

ha

VSTVSTA+

⋅= ∑+

= 1

1

1 ,


57

VSTA is the total net present government income (taxes and turn over contributions)

( )hDd

h

ha

VAVAA+

⋅= ∑+

= 1

1

1 , VAA is a total induced additional incomes (asurance, incomes of

other companies)

( )DaVRVRA

+⋅=

1

1

, VRA is the present final value of fix assets

=DMA ( )hd

h

ha

DM+

⋅∑= 1

1

1 ,

DMA is the total present environmental damages produced by objective accomplishing

( )hD

h

ha

PDVPDVA+

⋅=∑= 1

1

1 ,

PDVA is net present total pollution produced during lifetime

=CHDPA ( )hD

h

ha

CHDP+

⋅∑= 1

1

1 ,

CHDPA is pollution generated by manufactured and sold products, performed services; updated - (updated remediation costs)

CRMCRMA = ( )Da+⋅

1

1

CRMA is updated costs for natural environment restoration after

economical activity

S.G. Szentesi 58

Measurement and monetary assessment of pollution and damages caused to natural environment come under the concept of total economic value, of finding a market value for environment resources and measurement of losses due pollution generated by investment objective or investment project variant, respectively. It represents a permanent research field, but also the reason of many controversies among economists and ecologists. From economical viewpoint, one project is realizable if updated total real net income is positive and large enough and minimum benefit principle is applied. In this case, minimum benefit represents an opportunity cost.

5.Case study

The case study is about an aluminium plant wich produce more than 6 thousend tone aluminium bars per month and pollute the aer, soil, and water and phonic pollution .The economic date are brought in the following table.

Benefits Alternativs Profit Wage Governmental

tax contribution

Local tax

contibutions

Other benfits

Project value 3,2 0,05 1,44 0,69 0 Avarage value 3,89 0,05 1,75 0,85 0,01

Normal standard value

2,98 0,24 2,04 0,69 0,30

Expected value

4 0,12 1,01 0,29 0,10

For an economic life of 15 years with 10% interest rate with the

values between 3,2 mil euro and 1 mil. NPV is 22,57 mil euro. VSNA is the value of total net present average salary 0,38 mil.euro, and if the salary is growing normal 0,568 mil.euro. VSTA is the total net present government income (taxes and turn over contributions) and in this case 10,95 mil euro for governmental tax and 5,25 mil.euro for local tax. Other benefits zero. VRA is the present final value of fix assets and his value is 5 mil.euro. Total benefits are 44,15 mil euro net present benefits. This amount most be compared with the damaged evaluated. The damage evaluation need a further environmental evaluation


59

methods development. The total net present benefits are compared with the total present damages. 6. Conclusions

The economic-ecologic balance is a major concern of our days for a sustainable development. The issue of this challenge can start from the investments projects and the decisions makers how can except or reject a harmful project or less useful for the society or community. To put together economic criteria with economic criteria is not an easy task from many points of view. According to this objective a theoretical and practical proposal is to be use for decision the indicator named real net present value. This indicator aggregates in general and practical way the economic and ecologic criteria the benefit on a project end the losses for the environment caused by the realization of the investment project. This method is also acceptable from accounting and banking perspective and generated if is necessary a hierarchy of the project and their alternatives. Bibliography

C. Florescu, P. Mâlcomete, N al. Pop Szentesi Silviu Marketing co. Explanatory Dictionary, Economic Publishing House, 2003; M. Blaug, Economic Theory in Retrospect, Didactic and Pedagogic Publishing House, Bucharest, 1992; Polasky S, Nelson E, Pennington D, Johnson KA (this issue) The impact of land-use change on ecosystem services biodiversity and returns to

landowners: a case study in the State of Minnesota. Environ Resource Ricketts TH, Daily GC, Ehrlich PR, Michener CD, Economic value of tropical forest to coffee production, Proc Nat Acad Sci USA 101:12579–12582, (2004); Sanchirico JN, Springborn M, How to get there from here: ecological and economic dynamics of ecosystem service provision. Environ Resour Econ Smith R, Muir R,WalpoleM, Balmford A, Leader-WilliamsN Governance and the loss of biodiversity, Nature 426:67–70, (2003); Sodhi NS, Posa MRC, Lee TM, Bickford D, Koh LP, Brook BW The state and conservation of Southeast Asian biodiversity. Biodiver Conserv 19:317–328,(2010);

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Solan M, Cardinale BJ, Downing AL, Engelhardt KAM, Ruesink JL, Srivastava DS Extinction and ecosystem function in the marine benthos. Science 306:1177–1180, (2004); S. Szentesi, Investment decisions in the process, UAV Publishing House, Arad, 1999; S. Szentesi, Economy and the environment, Servo-Sat Publishing House, Arad, 1998; . Szentesi, R. Cureteanu, Management and analysis of investment projects, Mirton Publishing House, Timisoara, 2004; S. Szentesi, S. Rusu, R. Cureteanu, Statistics economic activity, Mirton Publishing House, Timisoara, 2005; R. D. Simpson, M. A. Toman, R. U. Ayres, Natural Resources and the Environment in the New Millennium, Lamson Library and Learning Commons, 2005; www.mmediu.ro (is hosted by the Ministry of ENVIRONMENT of Romania); Stern N, The economics of climate change: the stern review. Cambridge University Press, Cambridge, (2007); Sterner T, Persson UM An even sterner review: introducing relative prices into the discounting debate, (2008); A, Vance-Borland K, Watkinson AR One hundred questions of importance to the conservation of global biological diversity, Conserv Biol 23:557–567, (2009); Tilman D, Polasky S, Lehman C Diversity productivity and temporal stability in the economies of humans and nature. J Environ Econ Manag 49(3):405–426, (2005); Tilman D, Reich PB, Knops JMH Biodiversity and ecosystem stability in a decade-long grassland experiment, Nature 441:629–632, (2006); Tilman D, Wedin D, Knops J Productivity and sustainability influenced by biodiversity in grassland ecosystems. Nature 379:718–720, (1996); Wardle DA,Walker LR, Bardgett RD Ecosystem properties and forest decline in contrasting long-term chronosequences. Science 305:509–513, (2004); Weitzman ML Areviewof the stern reviewon the economics of climate change. J Econ Liter 45(3):703–724, (2007); Zabel A, Pittel K, Bostedt G, Engel S, Comparing conventional and new policy approaches for carnivore conservation—theoretical results and application to tiger conservation, (2005)


The environmental impact of electro-thermal plant (CET) Arad


S. G. Szentesi, M. FranŃescu

Szentesi Silviu Gabriel “Aurel Vlaicu” University of Arad, Romania FranŃescu Marius National Meteorological Administration

Abstract This paper describes a method for achieving the economic-environmental balance based on the assessment of environmental and/or pollutant factors Keywords: pollution, technology, investment, development, strategy

1. Electro-Power Plant(CET) Arad

1.1. Field activity Company “Arad District Heating Power Plant (CET)” is a joint

stock company established in April 2002 under the authority of Municipal Council Arad, who manages the assets of the former concession Electrocentrale Arad Branches removed from SC Thermoelectric S.A. Bucharest based H.G. 105/2002.

S.C. CET Arad S.A. produce electricity and thermal power and is composed as follows: - CET Lignite Arad; - CET Hydrocarbons Arad.

Operational coordination in terms of producing electricity is provided by the National Power Dispatcher (DEN). In terms of thermal energy production needed by consumers in the city of Arad, the two central interconnected functions resulting in increased security and continuity of heat supply to consumers. S.C. CET Arad S.A. is a

S. G. Szentesi, M. FranŃescu 62

member of COGEN - Association of Electricity Producers and heat in cogeneration in Romania. Field activity is:

- Generation, transmission, distribution and supply of heat; - Electricity generation and supply.

There are operating permit for: - Lignite CET located in the northern city of Arad; - Hydrocarbons CET located near the center of Arad; - Transmission and distribution of heat in the city of Arad.

There is ANRE license for: - Electricity production; - Heat production; - The supply of heat; - Electricity supply; - Distribution of heat.

Services provided: - Producing and supplying electricity to which the market trades through OPCOM (Electricity Market Operator in Romania), based on regulated agreements and day-ahead energy market (DAM) - Provides an important part of the electricity needs of the county of Arad; - Producing, transporting and supplying heat for the city of Arad; - Provide the necessary heat to Arad by 163 km primary transport network and 376 km secondary pipeline distribution networks; - Heating fuel 42 points and 37 compact substations, for the population; - 53 points fueling stations;

Fuels used are: - Coal; - Methane gas; - Oil.

Staff: -933 employees, of which most people working in shifts to

ensure continuous power supply to the city. Prices provided for heating are valid from 01.08.2008:

- 188.86 lei / Gcal (VAT included) - the local price of heat transmission;


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- 278.04 lei / Gcal (VAT included) - price of local heat distribution networks;

the population. Strengths: - Balanced production structure Freight half financial results are derived from electricity and heat production half; - Local heat stable market; - Flexibility for all types of fuel; - Increased adaptability to different operating regimes; - Qualified and stable staff; - Sizing balanced energy capacity, allowing almost full production in cogeneration of heat; - Sizing sufficient transportation networks to support new customers; - Technology of electricity and heat in cogeneration is a solution to a cheap energy with low environmental impact. She provides prerequisites for modernization and streamlining of central heating systems and provide conditions for the use of alternative fuels, taking into account the continuous increase of gas price-qualified and stable; - It is the cleanest and safest form of thermal energy for urban heating network. Rehabilitation of district heating network solution by introducing modules in each block, brings the primary heat loss less to the consumer, giving advantage to the possibility of adopting the desired thermal regime, but without the disadvantages them, for it produces an explosion in housing, do not cause intoxication or carbon monoxide gas and does not require the consumer to undertake mandatory periodic inspections. 1.2. Investment strategies

S.C. CET Arad S.A. has a perspective of development and modernization through the commissioning of boiler no. 2 420 t / h and turboaggregate no. 2 of 50 MW. There are also programs for rehabilitation and upgrading environmental line running by 2011. - Modernization of the electrostatic precipitator for dust reduction; - Gas desulphurization to reduce SO2; - Use low NOx burners; - Recovery of dry ash and use it to reduce pollution by fly ash; - Achieving the flue slag and ash in dense sludge.

Upgrades are also provided for hot water boilers, the secondary heat networks by mounting the modules directly to customers and


computerized system for dispatching CET - Central Heating. It proposes bringing heat from primary to consumers by installing modules (M) near the ladder block. These modules will be automated and powered by direct heating of thermal primary and secondary network will have a closed circuit filled with softened water, heating (thus avoiding deposits in radiators) and a circuit powered directly from the water mains to provide water heating. Points can be converted into thermal distribution nodes will be able to refurbish primary and secondary thermal network (between points and blocks heat) by passing the system with four pipes (2 each for heating and hot water) and moving to the second system Pre-insulated pipes (with very small losses, 2%). Thus the heat consumers will pay only the parameters taken from CET on who will define themselves, the losses will decrease dramatically, and the losses of hot water secondary network will be completely eliminated.

2.Environmental pollution sources in energy

Of all the factors of influence, the air is of greatest importance for the city of Arad, because changing the radiative balance made it entails profound changes in the urban thermal economy and other regime elements and weather phenomena. 2.1. Energy complexes

Energy complexes involved in urban air pollution in Arad with a share of 10%, the quantities of polluting substances almost as large as those emitted by industry, mainly by sulfur oxides (SO), nitrogen oxides (NO), carbon , ash, hot steam and hydrocarbons (HC). This is because electricity consumption is achieved mainly by burning coal (lignite), gas and fuel oil.

Electro-Thermal (CET) Arad. is one of the largest sources of air pollution in the northern city of Arad: Since sulfur (S2) is an ingredient that fuels the economic unit (coal, gas and oil), it is understood that the electro-thermal plant is a major source of pollutant sulfur dioxide (SO2). Coal used in the production process is of lower quality (brown), having a low calorific value and generating more ash (tens of tons daily in winter). In these circumstances, in the vicinity of the plant, develops warehouse ash and slag, a major source of pollution of soil, water and atmosphere. Derived from lignite ash composition preserves the chemical elements found in coal, including heavy metals or radioactive scandium (Sc), cobalt (Co), Strontium (Sr), yttrium (Y), Zirconium (Zr)


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cesium (Cs), Thorium (Th), uranium (U), etc.. When dry the dumps, especially in summer, high wind and ash is transported to varying distances into surrounding neighborhoods: Gai, Poltura, Aurel Vlaicu, 6 Vinatori and Gradiste. In some favorable weather conditions, smoke, soot and ashes of the plant is carried even to the city center, often visible from great distances in Plains Mures. 2.2. Space heating

Space heating caused by Electro-Thermal (CET) Arad, although it contributes with smaller quantities of polluting substances, 5%, are still among the major sources of atmospheric pollution of Arad. Sulphur oxides (SO) and oxides of carbon (CO) are released, usually by burning fuel containing sulfur (S2), such as coal, natural gas, fuel oil or wood. This source of air pollution include isolated or clustered homes, apartment buildings, stations, bus stations, hospitals, clinics, schools, kindergartens, libraries, philharmonic halls, theaters and cinemas, clubs, restaurants, shops, hotels etc.

3. The main types of pollutants 3.1. Sulfur oxide Sulfur oxide (SO) is the result of combustion processes, the sulfur content in coal, oil, wood and other fuels reaching many of Arad atmosphere as sulfur dioxide (SO2), hydrogen sulfide (H2S), sulfuric acid ( H2SO3) and sulfuric acid (H2SO4). As the main source of sulfur oxides remark energy complexes, motor vehicles (fuel used in transport), industry, space heating and domestic activities. 3.2. Carbon oxide Carbon monoxide (CO), the main pollutant of urban air Arad, is a colorless, odorless and extremely harmful. Result of incomplete combustion, it has the largest share in the exhaust gas of motor vehicles in all industrial smoke emissions, space heating and help her share of this chemical element. 3.3. Nitrogen oxide Nitrogen oxide (NO) may be the main pollutant, pollution resulting from primary motor or secondary pollutant, resulting in its oxidation: nitrogen dioxide (NO2).


3.4. Hydrocarbons Hydrocarbons (HC) are air pollutants come from burning oil (fuel oil), natural gas, coal, wood and other fuels. As sources of hydrocarbons is noted traffic (motor vehicles), industry, space heating and energy complexes. 3.5. Sediment and suspended particles Sediment and suspended particles are solid and liquid particles, with a wide range of sizes, ranging from less than 0.1 mm to 100 mm. These include: smoke and fly ash from energy complexes of Electro-Thermal Plant CET Arad, smoke and fly ash from industry (the 8 major industrial areas of the city of Arad), dust raised by the earth's surface (as wind action, earthquakes and traffic Arad), aerosols and organic compounds. 4. Factors affecting air pollution 4.1. Factors influencing the stagnation of pollutants

Spread issued impurities are closely related to topography of the region and weather conditions in areas where pollution sources are located.

A particular synoptic situation that fosters stagnation ground pollutants caused by atmospheric stability is the persistence of an anticyclone regime. Under these conditions, the soil near the weak wind blowing and the air descending from a height causes a decrease in cloud. This phenomenon causes the formation of temperature inversion layer and atmospheric turbulence reduced or absent. Simultaneously, the soil is low wind or calm atmospheric signals (0-1 m / s), which prevents dispersion of pollutants. Multiannual frequency atmospheric calm is 29% during the years 1954 to 2009, as the statistic of County Meteorological Station (SMJ) Arad. If the frequency of calm is over 15%, such as Arad, the atmospheric conditions are conducive to the development process for air pollution, promoting the maintenance of low levels of impurities in the atmosphere, up to 100 m.

With increased atmospheric stability, the installation of air layer above the earth's surface in temperature favors the stagnation of the pollutants in soil. Thermal inversions, marked by increasing air temperature with altitude, the lower layers of the atmosphere keep the temperature low. This becomes particularly important when considering practical issues of Arad pollution because it favors the emergence and


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persistence of mists in the air pollutants in the immediate vicinity of the surface underlying assets. Lowering the thermal inversion layer increases the concentration of pollutants in the earth's surface. Thermal inversions occur mainly in cold months of the year, especially in areas of low meadow Mures.

During the night, because of cooling air near the earth's surface is increasing atmospheric stability, turbulence layer decreases, and the concentration of pollutants increases. 4.2. Factors encouraging the dispersion of pollutants

Under conditions of atmospheric instability, convective currents favors vertical dispersion of pollutants. The phenomenon is accentuated in the sunny days of summer thanks to strong warming the earth's surface vertically grown layer becomes turbulent.

Winds, depending on configuration and local relief, quickly spread pollutants vertically and horizontally at varying distances. Knowing the frequency of the dominant wind directions helps to establish meaning that it is possible to provide transport of large amounts of impurities, so the sectors most exposed to pollution based on emission sources. Distribution of dominant winds affecting air quality of Arad, due to the fact that pollutants are emitted from the units involved present platforms and industrial parks NV, V, S, E, etc.

Rainfall is an important factor in the treatment of polluted air. This parameter determines Weather eliminating 80-90% of the total amount of impurities emitted into the atmosphere. Above the industrial district (NW Industrial Park, Industrial Park E, S Industrial Park, etc..) Higher amounts of precipitation fall, encouraged by the maximum concentration of condensation nuclei. Condensation nuclei formation increases water vapor in the atmosphere even at low values of relative humidity (70%). This leads to an increase in rainfall, which indirectly causes air purification. 5. The consequences of air pollution

The consequences of atmospheric contamination of Arad is

divided into two categories. First, the nature of climate change relates to the quality and quantity of solar radiation, resulting in a series of changes of meteorological elements. A second category of consequences of biological order, health, refers to urban air pollution by


exceeding the maximum permissible concentration (MPC) for different types of impurities.

When air pollution is combined with urban, site specific weather conditions, visibility is low, forming smog. The phenomenon is a mixture of water and ice particles with solid particles of different sizes and different gas pollution. Much of the condensation nuclei are very active due to their high hygroscopicity and a high capacity transmission, especially soot particles. Phenomenon, yellowish or reddish, have different characteristics from one season to another is called: type smog hivernal summer winter and summer-type smog.

Air pollution, destroy green space in the city of Arad, but also on forest located in the surroundings, causing phenomena of drying and defoliation, which, in dry years occurring since July. The city's central park (Mihai Eminescu, Children, forest, etc..) Are affected mostly brown and Arad E, Cladovei Valley were especially affected species: Quercus cerris, Quercus petraea and Pinus sylvestris. Vegetation is also favored the road pollution and specific microclimate, air-fluid system is worse, with negative consequences for the trees. High temperature and air pollution system generates less developed foliage. Particles driven by currents of air in fine fraction, and accumulation of pollutants emanate by plants in high concentrations of metals such as Molybdenum (Mo) and arsenic (As) causes degradation of vegetation. Partial drying of leaves and early conclusion of vegetation, determine the level of Arad consuming less carbon dioxide (CO2) and generate a small amount of oxygen (O2).

6. Preventing and combating pollution

In order to protect the environment, the law prohibits the

discharge of harmful substances into the atmosphere as a gas vapor, aerosols, solids and other beyond the limits set by regulations. It also prohibits, commissioning of new units or expansion of existing units, which, by their activity, can be sources of air pollution without restraint and installations and neutralize pollutants in running the appropriate times without any works or measures to ensure compliance with air quality protection requirements set by professional bodies.

The industrial units present in the area of Arad costly endeavor to meet European Union standards and norms (EU) on the conditions of air quality protection.


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The Electro-Thermal (CET) Arad took a series of direct and indirect measures for environmental protection, employment norms plant requirements of the European Union (EU) and the GD 541/2003: - Supply of fuel oil with low sulfur content (S) below 0.5% respectively; - Purchase of equipment for automated analysis of the air inside the plant; - Execution of a heap spraying plant ash and slag; - To obtain cinders and ash and use it dry. - Improve the wetting ash and slag dump by mounting holes in the levees intermediate discharge; - Change oil from CET Arad burners with low NOx burners; - Upgrading of electrostatic precipitators which have reached an efficiency of dust retention in the flue gas of 99.6%; - Lignite CET Arad gas desulphurization; - Continuous monitoring of emissions; - Hydrocarbons CET linking household sewage from domestic sewage of the city of Arad; - Planting of trees, both in the plant perimeter and the perimeter dykes of the mound of slag and ash; - Installation of silencers.

Bibliography Ciulache S., The influence of weather and climate on air pollution, University of Bucurest Publishing House, 2004; S. Szentesi, Investment decisions in the process, UAV Publishing House, Arad, 1999. S. Szentesi, R. Cureteanu, Management and analysis of investment projects, Mirton Publishing House, Timisoara, 2004. Szentesi S., FranŃescu M., Cristescu G., MoŃ G., Crişan S., Vizental M., Dănoiu D., Modeling economic-environmental balance for investment projects, UAV Publishing House, Arad din Arad, 2009; FranŃescu M., Historical developments - demographic and economic of Arad, UAV Publishing House, Arad, 2007; www.cet.arad.ro: public data. .


Etude sur la relation entre la performance financière et performance sociale de l'entreprise

C. Nicolaescu, M. Vizental

Cristina Nicolaescu, Mihaela Vizental Université „Aurel Vlaicu” d'Arad

Resumé Nous assistons actuellement à la transition vers une nouvelle phase de développement du concept de responsabilité social qui se présentent et conduire à une amélioration de l'environnement, ce qui implique l'émergence d'un nouveau concept: la réactivité de la société. La mesure de la comptabilité de la performance économique a beaucoup de techniques et outils que nous ne pouvons pas dire la même chose pour les deux autres objectifs, environnementaux et sociaux. Dans l'hypothèse de maximisation des avantages, la question se pose de savoir si les entreprises sociales atteindre des niveaux de performance similaires à celles de la performance financière ne sont pas aussi intéressés par les aspects de la responsabilité sociale Mots-clés: responsabilité social, entreprise, coûts sociaux, comptabilité, performance sociale, performance financière, environnement.

Le concept de responsabilité sociale des entreprises (Corporate

Social Responsibility) a eu lieu aux États-Unis dans les années 1980. Pour la première fois le concept a été utilisé et défini en 1953 dans "Responsabilité sociale de l'homme d'affaires" par Howard Bowen. Il définit la responsabilité sociale comme «une série d'obligations que conduire à des décisions politiques et lignes directrices de conduite compatibles avec les objectifs et les valeurs de la société.

En Europe, le concept a conclu que bien plus tard, puis une connaissance plus approfondie et un développement continu. Donc, si

Etude sur la relation entre la performance financière …

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au début, il ne couvre que les responsabilités sur la base répondant aux fonctions essentielles de l'entreprise par rapport à la production, l'emploi et la croissance au fil du temps est venu d'adhérer à ce concept et en tenant compte des questions environnementales, le développement de la société et des relations sociales.

Contrairement à la vision américaine de la responsabilité sociétale, la philanthropie est limitée aux activités économiques étrangères de la société, l'approche européenne a tendance à croire que de telles actions ne sont pas effectuées dans le cadre de la responsabilité sociale et qu'ils soient évalués dans les conditions habituelles de l'entreprise. Cette approche est la définition cohérente de la Commission européenne sur la responsabilité sociale des entreprises, qui comprend dans sa sphère d'intégration volontaire des préoccupations sociales et environnementales à ses activités. Plus précisément, la prospérité économique de l'entreprise (objectif économique) est prise en conjonction avec le respect de l'environnement (objectif écologique) et de renforcer la cohésion sociale (objectif social).

Si la mesure de la comptabilité de la performance économique a beaucoup de techniques et outils que nous ne pouvons pas dire la même chose pour les deux autres objectifs, environnementaux et sociaux. Dans l'hypothèse de maximisation des avantages, la question se pose de savoir si les entreprises sociales atteindre des niveaux de performance similaires à celles de la performance financière ne sont pas aussi intéressés par les aspects de la responsabilité sociale.

Pour analyser la relation entre les deux peut démarrer à des locaux qui en général mettent en question la performance financière des entreprises compte seŃine la fois la valeur de ses actions et la performance mesurée sur la comptabilité des différents indicateurs: le bénéfice par action, le bénéfice etc. Un outil utile pour mesurer les problèmes de performances liés à l'entreprise sociale pourrait être un tableau de bord extrafinanciară genre. Cette image peut être développée dans plusieurs domaines tels que: les partenaires commerciaux (clients et fournisseurs), les employés, actionnaires, etc.

En termes de performance sociale d'une société commerciale peut être évaluée en termes de qualité et de sa relation avec les fournisseurs et les clients, leur éthique et leur responsabilité sociale et environnementale. Un autre aspect serait la qualité des produits offerts par les clients d'entreprise dans la matière organique (leur biodégradabilité, de la recyclabilité, impact sur l'environnement, etc.).

C. Nicolaescu, M. Vizental 72

Responsabilité sociale des entreprises implique sa préoccupation pour le bien-être de ses employés: leurs droits, la création de bonnes conditions de travail, assurer la sécurité et l'hygiène au travail, des salaires décents, etc. comportement des actionnaires et des décisions qu'ils prennent et qu'ils reflètent l'engagement social de l'entreprise, car elle aide à protéger l'environnement et accroître le bien-être social, non seulement ses employés, mais aussi d'autres personnes (par opération de mécénat, le parrainage, soutenir le travail des ONG, etc.)

Ce qui est clair est que toute cette participation et actions entraînent des coûts pour les entreprises. Mais gue serait l'avantaje de l'entreprise de ces préoccupations? Il ya cet avantage, et si oui, peut-elle être mesurée?

Un moyen serait de corréler la performance économique de la responsabilité sociales des entreprises d'activités commerciales à condition que l'efficacité économique nécessite, entre autres choses, la meilleure utilisation des ressources, à la fois d'impact significatif sur l'environnement et l'homme objectif social d'entreprise.

En d'autres termes, ont révélé la façon dont les externalités environnementales et sociales ont influencé le rendement économique de l'entreprise.

Les coûts sociaux sont la principale préoccupation du plan stratégique de la responsabilité sociale d'une entreprise. L'expérience a montré que les coûts sont plus faibles si elles sont faites pour éviter tout dommage pour eux que la différence entre le coût des dommages-intérêts compensa.Ca conséquence la diference entre le cout de damage et des coûts de les études d'impact et des mesures de protection sociale et environnementale peut être considéré comme une avantaje.

Dans la même catégorie des coûts sociaux et ceux relatifs à des investisseurs, les créanciers, les fournisseurs, les clients des organismes gouvernementaux et les ONG dans le domaine. Promouvoir de bonnes relations avec eux permettra à l'entreprise d'éviter les conflits sociaux et environnementales. D'autre part la construction d'une image de «green business» contribue à préférant la compagnie en tant que partenaire dans les activités économiques génératrices de revenus.

Nous ne pouvons négliger pas l'impact fiscal. Cette technologies polluantes va générer des dépense fiscale (par exemple les coûts pour les émissions de dioxyde de carbone taxes d'émission), tandis que pour l'utilisation des technologies de l'environnement, sont accordé des incitations fiscales. La même reconnaissance d'avantages fiscaux


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bénéficier les coûts sociaux en misant sur la fiscalité întreprinderii.L'etat, par levier fiscale, encourager les entreprises à exercer une activité bénéfique pour l'environnement à la fois écologiquement et socialement. Connaissance et application de ces mesures par l'entreprise peut augmenter ses performances en réduisant les dépenses fiscales de l'entreprise.

Gestion d'entreprise et d'autres tiers à qui il a une certaine responsabilité sociale, utiliser la comptabilité d'obtenir des informations sur les conséquences sur les possibilités de croissance economique et les coûts environnementaux.

Idéalement, tous (ou même une majorité) d'impacts de l'entreprise sur la société et l'environnement etre mis en évidence par le système comptable de l'entreprise.

En cette idée OMFP 3055/2009 se refere la obligation de reconnaissance porte des provisions pour "les coût de l'élimination des effets négatifs, produit a l'environnement, punissable par la loi, qui degaje une sortie de ressources et incorpore d'avantages économiques, indépendamment des actions futures de l'entité. De même, une entité comptabilise une provision pour coûts de fermeture d'installations pétrolières, à condition que cette entité pour corriger le dommage a déjà eu lieu. " Même loi dispose également que "contrairement à ce cas, une entité peut intention ou peut avoir besoin, en raison des pressions commerciales ou juridiques d'effectuer une dépense d'agir d'une certaine façon (par exemple par installation des filtres à fumée dans un certain type d'usine). Depuis l'entité peut éviter des coûts futurs à travers diverses actions, par exemple, en modifiant le processus de fabrication, elle n'a pas une obligation actuelle liées à des dépenses futures, et donc ne reconnaîtra aucune provision. " Dans ce dernier cas, les coûts seront enregistrés dans un compte distinct: 652 "Dépenses de protection de l'environnement" groupe des comptes 65 "Autres charges d'exploitation".

Avec ce compte sont enregistrés les coûts environnementaux, de la période curente, qui les taxes environnementales payés (5121), les certificats d'emision de gaz à effet de serre achetés, le coût de la protection de l'environnement à l'avance pour l'année en cours, etc .

En intégrant ces coûts à la suite de l'exercice est mis en évidence l'impact économique sur les résultats.

Les dispositions prises pour les dépenses de protection de l'environnement, pour: protection de l'air, gestion des eaux usées, la

C. Nicolaescu, M. Vizental 74

gestion des déchets, la protection des sols, eaux souterraines et de surface, la protection de la biodiversité et des paysages et autres activités de protection de l'environnement sera présenté le bilan sous la rubrique «Autres provisions».

Un autre document de raport financière qui comprend des renseignements sur le rôle environnemental et social de l'entreprise est «La Rapport de gestion". Ce, dans la mesure c'est nécessaire pour comprendre le développement de l'entité, sa performance financière ou la position, comprend des indicateurs financiers et, le cas échéant, non financière clés de performance, liés aux questions environnementales et les employés de l'entreprise ..

OMFP 3055/2009 ne précise pas l'obligation d'utiliser d'autres comptes de mettre en évidence l'impact environnemental et social d'entreprise sur l'environnement, mais chaque entreprise en fonction des besoins d'information et de l'application du principe de l'importance de créer leur propre comptabilité analytique pour mettre en évidence toutes les entrées et les sorties liées aux activités de responsabilité sociale. Dans la pratique, actuellement en Roumanie, seule une petite partie de ces opérations sont mises en évidence soit volontairement ou par la contrainte de certains réglementation directe ou indirecte. Mais sans les informations relatives l'impact des transactions commerciales sur l'environnement, le système de décision des entreprises ne peut pas appuyer la réalisation des actions cohérents pour atteindre les objectifs environnementaux et sociaux.

Une raison à cela est le système comptable actuel est un système d'information construit pour mesurer les performances économiques passées et actuelles, sans assure une prévision de résultats futurs

En conclusion, l'existance d'une stratégie rigoureuse de mettre en évidence des les effets de l'impact environnemental et social de l'entreprise, conduit à l'obtention d'informations qui permet les meilleures mesures pour améliorer la performance de l'entreprise tant a niveau économiquement et environnementalement et socialement. À court terme la reconnaissance des coûts environnementaux influence directement le résultat des dépenses courantes (économique, sociale ou environnementale) en déterminant le coût actuel des nouvelles, comptabilisés en charges de la période, et les engagements futurs, comptabilisées comme des provisions. À long terme ces dépenses ont souvent l'effet d'augmenté des futurs bénéfices de l'entreprise et sa sustenabilite économique, sociale et environnementale.


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Parce que la comptabilité financière ne fournit pas beaucoup de techniques pour mettre en évidence la performance sociale de l'entreprise, la comptabilité de gestion environnementale pourrait être un outil utile pour ca. Avec l'aide qu'ils peuvent fournir l'identification des structures d'être considérés comme des externalités revenu courant, grâce à l'internalisation ou de liaison sur les résultats futurs en rendant leurs engagements futurs au moyen de provisions.

Un autre outil utile serait une analyse coûts-avantages afin de déterminer les indicateurs spécifiques de performance sociale et environnementale, d'autant plus qu'ils sont de plus en plus demander tant des partenaires financiers d'entreprise afin de la société civile. Bibliographie: Bebbington J., Larrinaga-Gonzales Carlos, „Carbon Trading: Accounting and Reporting Issues, European Accounting Review, vol 17, No. 4, 2008, pg. 697 – 717; Bouquin H., “ La notion de performance ”, journée d’étude I.A.E. de Tours, 15/1/2004 OMFP 3055/2009 privind reglementările contabile româneşti conform cu Directiva a IV-a a ComunităŃilor Economice Europene


Develop economic-ecological balance of investment objectives with the model confirmation / infirmation



Szentesi Silviu Gabriel “Aurel Vlaicu” University of Arad, Romania FranŃescu Marius National Meteorological Administration, Romania

Abstract Fixed assets investment projects that have a major impact on the environment must be evaluated and ranked using models that lead to acceptance or rejection. It is considered that the best alternative for conducting socio-economic activities which achieve maximum satisfaction for a unique investment projects with a major pollution in the boundary conditions at a time. Keywords: model, pollution, confirmation, denial.

1. Practical considerations on developing a model of economic-environmental balance for investment projects

Fixed assets investment projects that have a major impact on the

environment must be evaluated and ranked using models that lead to acceptance or rejection. Major investment projects are polluting boilers, electrical, thermal power, nuclear, etc., and other investments in the chemical, petrochemical, rubber, steel, etc. Developing a model requires the addition of scientific or theoretical aspects such as allowable level of pollution or technology eco, green, clean and responsible involvement of players who suffer the consequences of positive and negative aspects of achieving an investment project. This paper aims at assessing satisfaction versus dissatisfaction as a beneficiary population of both the services provided by CET Arad and the receiver in the form of pollution

Develop economic-ecological balance of investment objectives…

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externalities. Assessment of satisfaction and dissatisfaction are made based on the model confirmation / denial of people's expectations of the beneficiary households affected by pollution.

2. Evaluation of the concept of satisfaction and dissatisfaction

Satisfaction and dissatisfaction helps us to optimize decisions

and improve economic and social activities conducted. Optimum can not be treated as a single economic optimal for projects with externalities, polluting major objectives it must be tackled as a global optimum that includes optimum economic, technical and technological superstructure, organic. True global optimum must prevail optimum economic, technical and ecological superstructure. It is considered that the best alternative for conducting socio-economic activities which achieve maximum satisfaction for an investment project with major pollution boundary conditions at a time. Global optimum mathematical formula is given by:

( ) MAXISSufMm

k

k

n

i

i →−== ∑∑== 11

where Si is the satisfaction and performed by members of society,

measured in units of social utility

ISk is the dissatisfaction k felt by members of society , social disutility measured in units of (mathematics, endowed with a negative sign).

3. The confirmation / denial on the basis of satisfactions and dissatisfactions

To systematize the theories and concepts that are related to the formulation of public satisfaction (the beneficiaries, those who feel the positive effects of both the existence and operation of investment objective and the negative effects of operating and investment objective

( )ni ÷∈ 1

( )mk +∈ 1


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existence that made pollution . Model (paradigm) Confirmation / denial (C / I). has grown in consumer satisfaction research.

Summary of the C / I is to establish satisfaction of population (beneficiaries), by comparing the actual experience gained from using a product or service, implemented in the subjective perception of quality / performance of a product or service with a particular reference standard of customer expectations on product quality or performance. If there is a coincidence, an overlap between standards and performance expectations for product performance actually experienced the product when there is confirmation of consumer expectations. There is a confirmation for this model the level of satisfaction when there is overlap between them.

Satisfaction depends on perceived performance compared to the standard. The same model can be applied to the satisfaction of the beneficiaries of industrial services that directly affected people, businesses, institutions involved and affected Analysis of satisfaction of beneficiaries

To rationalize the theories and concepts that are related to the development of relevant beneficiaries' satisfaction, we rely on C/D paradigm (Confirmation/denial of expectations). Paradigm C/I implies comparison beneficiary satisfaction (actual performance) from a comparison of actual experience in using a service with a particular reference standard of the recipient (performance targets). If perceived performance and customer expectations in comparison with the standard is an overlap then we have a confirmation of beneficiary satisfaction. If expectations exceed performance standards of the beneficiaries when there is a positive denial. If beneficiaries are below expectations then we expected a negative denial that beneficiaries perceived actual performance is below expectations in comparison with the standard. It should be noted that the standard is not entirely determined objectively, it has components and goals (standards) and subjective (ideals) or perception of reality. This model C/I, we compare the basic paradigm is illustrated in Figure nr.1.


79

3. CET Arad Case Study

Company "Arad District Heating Power Plant, under the authority of the Municipal Council Arad (CMA), the concession given by the former Heritage SC gleaned from Arad Electrocentrale Branches Thermoelectric S.A. Bucharest based H.G. 105/2002. S.C. CET Arad S.A. produce electricity and thermal power plants in the second heat which is composed as follows: CET Arad Lignite and CET Arad Hydrocarbons. In terms of thermal energy production needed by consumers in the city of Arad, the two central interconnected functions resulting in increased security and continuity of heat supply to consumers. Taking into account local weather conditions, but especially

Current performance level ( )

Compared to standard

( )

Comparison Satisfaction

Confirmation ( = )

above expectations

as expected

below expectations

Positive confirmation

( > )

Negative confirmation

( < )


80

the frequency of wind directions, it is considered inappropriate sites Electro-Heat Center (TEC) in downtown Arad Hydrocarbons and Electro-Heat Center (TEC) in the northern city of Arad Lignite.

To obtain values of Likert-type scale as positioned tabulated below, were taken into account air pollution, water pollution and soil pollution (including ground water, especially groundwater) with carbon monoxide (CO), Oxide Sulfur (SO), nitrogen oxide (NO), Lead and lead compounds (Pb), Hydrocarbons (HC), particulate matter settled and noise. The results are not the best, special attention should be paid to air pollution (value -3) and soil (value -2) in particular, where data for the Environmental Protection Agency (EPA) Arad.

Regarding other discomforts created dissatisfaction and Electro-Thermal (CET) Arad, it highlights human health in general and particularly respiratory diseases, according to data from the Public Health Directorate (PHD).

For practical evaluation applied a questionnaire to 200 beneficiary households affected while experiencing the benefits that the existence of the boiler and pollution (externalities) made by it.

total dissatisfaction Confirm Satisfaction total dissatisfaction satisfaction

_______________________________________________________ -2 -1 0 +1 +2

�� ☺☺☺☺ Feature index of confirmation IK will be calculated using the

formula:

Index of confirmation feature "i" ∑∑=

=z

i k

kk

in

nciIC

1

and Index of

confirmation IC ∑=

=z

i

k

z

I

1

where:

zi ,1= - number of features evaluated (two in our case and benefits and pollution) cik - confirmation level value "k" for feature "i" nk - number of people with level value of C / I "k" for feature “i”


81

n = 200 households If we take into account both the characteristics 1.POLLUTION

and 2. BENEFITS we obtain: For Pollution [(- 2)x46+(-1)x84+(0)x40+(+1)x 26+ (+2)x4] : 200 = [-92-84+0+26+8]:200= - 0,71 For Benefits [(- 2)x12+(-1)x13+(0)x92+(+1)x67+ (+2)x16] : 200 = [-24-13+0+67+32]:200= 0,31 ICtotal= (-0,71+0,31): 2 = - 0,20 Conclusions

The denial/confirm model shows the degree of satisfaction of beneficiaries to provide CET Arad what matters positive that want the benefits and negative aspects that unwanted pollution and the degree to which it is felt by beneficiaries.

In our case the result actually reflects a level between the expected (confirmed by reality) and which shows a light dissatisfaction of the population towards this objective expectations of industrial operation. The level of – 0,20 is between confirmation of expectation and a dissatisfaction generated by a slow disappointment.

Un important thing is the potential of the model to evaluate more detailed aspects about benefits and pollution. A further development is needed and a serial evaluation of confirmation in different seasons in winter time, summer, spring or autumn can give a better assessment.

Perceptions about POLLUTION and BENEFITS in winter can be very different from people perceptions in summer time. The further developments of this model can be using the human capital method is used to assess the impacts of natural resource changes on people. It is founded on the generally accepted notion that natural resources damage can have negative and significant costs on human health. In fact the human capital method measures the human costs of environmental damage by valuing the foregone opportunities of people resulting from natural resources-induced health problems. In the case of


82

premature illness or death of an individual, the following general formula of Mishan (1972) can be used as the measure of the value of the life:

( ) ( )Tt

t

Tt

t rYL−−

∞

=

+=∑ 1P tT1 (4) ,

where L1 is the discounted value of the labor of individual 1; Yt is his expected gross earnings, or value added, in the t-th year outside of returns from non-human resources he owns; PtT is the current (year T) likelihood that he will be alive in year t; and rt is the social discount rate in year t. The sum of the cost of death of the individual is L1 plus the medical costs. However, these costs can be expanded further to include the money value of the disutility related to the suffering of the family and friends of the individual. This method is used to estimate the value of morbidity and mortality associated to air and water pollution. The value of the health effects of air pollution is significantly more than the value of the health impacts of water pollution although both types of pollution affects health substantially. Bibliography Szentesi Silviu, Bazele statisticii, Ed. Institutul Biblic “Emanuel”, Oradea, 2000 Szentesi Silviu Decizii în procesul de investiŃii, Ed. U.A.V., Arad, 1999 Szentesi Silviu Economia şi mediul, Ed. Servo-Sat, Arad, 1998 David W. Pearce and R. K. Turner. Economics of Natural Resources Environment, Harvester Wheatsheaf, London, 1990 Szentesi Silviu, Managementul proiectelor de investiŃii, Ed. UniversităŃii “Aurel Vlaicu” , Arad, 1998 Szentesi Silviu şi Cureteanu Radu, Managementul şi analiza proiectelor de investiŃii, Editura Mirton Timişoara 2004 Szentesi Silviu, Managementul şi eficienŃa proiectelor de investiŃii, Editura Expert , Bucureşti 2002 Szentesi S., Ionescu E., Lile R., Balan L., Rusu S., Statistica, Editura Concordia , Arad , 2007 Mark Blaug, Economic Theory in Retrospect, Editura Didactică şi Pedagogică,. Bucureşti, 1992.


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Cretì, Anna The Economics of Natural Gas Storage, A European Perspective, (Ed.) 2009, XII, 116 p. 20 illus., Hardcover, ISBN: 978-3-

540-79406-6

Hans Christian Weis, Verkaufsmanagement, Kiehl, 2005, Hans Christian Weis, Peter Steinmetz , Verkaufsgesprachsfuhrung, Kiehl,2005, Jurgen Bruns, Internationales Marketing, Kiehl, 2006, Jurgen Bruns, Direktmarketing, Kiehl,2005, Peter Godefroid, Business-to-business-marketing, Kiehl,2005, Harald Vergossen, Marketing- Kommunikation, Kiehl, 2005 Harald Ehrmann, Marketing Controlling, Kiehl, 2006, Ingo Bieberstein, Dienstleistungsmarketing, Harald Ehrmann, 2005, Sabine Haller, Handels Marketing, Harald Ehrmann, 2006, Christian Homburg< Kundenzufiedenheit, editia 6, Editura Gabler Wiesbaden,2006 Law No 265/2006 (OJ 586, 06.07.2006) for the approval and amendment of EGO No 195/2005 (OJ 1196, 30.12.2005) on the environmental protection Council Directive 96/61/EC of 24 September 1996 concerning integrated pollution prevention and control, OJ L 257, 10.10.1996, p. 26-40 Order 152/2005, concerning integrated pollution prevention and control, published in the Official Gazette of Romania. Issue 2078/30.11.2005; Treaty establishing the European Community (in particular Article 174). Decision 1600/2002/EC of the European Parliament and of the Council laying down the Sixth Community Environment Action Programme, OJ L 242, 10.9.2002, Directive 92/43/EEC regarding the conservation of natural habitats and of wild fauna and flora, amended by de Directives 97/62/EC, 2006/105/EC and Regulation (EC) No 1882/2003 http://www.mmediu.ro (is hosted by the Ministry of ENVIRONMENT of Romania) http://www.cleaner-production.de (is hosted by the Federal Environmental Agency of Germany and provides comprehensive, in-depth information on the performance of German environmental technologies and services)


Modern approaches in modeling the economic-environmental balance modeling for investment projects

affecting the environment Research conducted under the Research Project Ideas 1239 PN II

S.G. Szentesi, M. Viezental

Silviu Gabriel Szentesi, Mihaela Viezental “Aurel Vlaicu” University of Arad, Romania

Abstract Modeling the economic-environmental balance for new investment projects having a major impact on the environment implies the critical analysis of the partiality bias existing in these models and the natural tendency to develop models in accordance with economic-social realities and the human judgement, and not the use of exact mathematically formulas often providing practically irrelevant solutions starting from subjective premises. The analysis for investment projects comprises the decision-making process from a multicriteria point of view. These criteria are often presented in a subjective manner. The permanent connection between objective and subjective during the decision-making process is also examined in this paper. Rational-deductive philosophy tries to sustain objectivity. There are many critics of rational-deductive opinion. It is presented the potential of subjectivity integration in the multicriteria decision-making process. There are two approaches – image theory and verbal decision analysis – used as instruments for supporting a subjective perspective on multicriteria decision implementation in modeling the economic-environmental balance. Keywords: modeling, economic-environmental balance, partiality, multicriteria analysis, image theory, verbal decision analysis

Modern approaches in modeling the economic-environmental …

85

Introduction

Multicriteria decision analysis for modeling the economic-

environmental balance evolved from economic theory (simple cost/benefit analysis), using mathematical modeling in the attempt to support the offset decision-making process, such as the analysis of economy-environment relationship. Multicriteria decision analysis is succesfull, but faces one major problem. Modeling works optimally with objective parameters. But human preferences are difficult to be measured objectivelly. Analyzing the offsets occuring in the decision-making process is difficult, especially in the circumstances of uncertainity regarding the environment issues.

Henig and Buchanan (1996) require additional efforts for achieving a greater objectivity in multicriteria analysis. There is a natural preference for objectivity in this area of research. Kersten and Noronha (1996) suggest the modeling adjustment to the human decision-making process rather than adjusting human to the modeling process, like in many situations.

Strating from this issue we discuss the rational objectivity in multicriteria analysis. We present some critics of the rational philosophy, arguing for for subjective perspective support, followed by a discussion regarding the objective/subjective complex. We study the implications of various degrees of objectivity/subjectivity on the multicriteri decision-making process, and we discuss the subjectivity implementation methods in multicriteria modeling. Some modeling approaches, such as AHP (analytic hierarchy process) and MAHP, include subjective elements. Methods like ELECTRE (Roy and Slowinski, 2008) and PROMETHEE (Beynon and Wells, 2008) use weights subjectively selected. Approaches like software system methodology become integrated in recent multicriteria methods in order to support the development of the subjective modeling process. The usefulness of economic-environemntal balance modeling can be demonstrated using a simple multicriteria problem.

S.G.Szentesi, M.Vizental 86

Theoretical foundations CRITICISM OF NORMATIVE RATIONAL PERSPECTIVE IN THE SETTLEMENT OF ENVIRONMENTAL ISSUES

There is a lot of criticism regarding normative rational

perspective. Georgescu- Roegen (1954) talks about decident actions in order to settle the unsolved problems of normative utility theory. Georgescu-Roegen states that cardinal utility is based on two unwarranted premises: undiminished wishes and perfect knowledge. Wildavsky (1997) observed the high uncertainity degree of the decision-making process. We are not sure even of our own preferences, since they depend on complete knowledge of our actions implications. Without complete knowledge, there is no optimization. We use our knowledge, including estimated reactions from others to our actions. Wildavsky suggests marginalismul (Lindblom, 1959; Lindblom and Braybrook, 1963) as a proper approach of high uncertainity environments. In the economy, Morgenstern (1972) identifies thirteen problems unsolved properly by the normative economic theory. Marginal changes can be better than system optimization, because in trying to identify the rational, normative optimum we make too many assumptions, leading to dangerous changes.

Simon (1979) observed a satisfying behaviour from many decidents in the business area. Although he agrees with it, Simon suggests that normative, rational optimization is not the best approach in certain business conditions. Kahneman, et al. (1982) ascertains that decidendts often rely on eheuristics, violating the rational utility procedure when they face offset situations. MacCrimmon and Wehrung (1968;1988) published a detailed study regarding the techniques adopted by managers in their attempt to settle difficult offsets problems. Managers have different degrees of risk aversion, being concerned about the potential amount of gains or losses. They adjust the risk level by collecting data, negotiating, portponing and delegation.

Zey (1992, 1998) analyzed the controversy about rational choice in a systematic manner. She identified ten assumptions, analyzing each impact. (1) Our welfare depends on the welfare of our beloved ones. (2) Altruism represents a value for most ipeople. (3) A general definition is tautological and irrefutable, ie an immaginative analyst can project a value maximization alternative for any given action. Individuals react


87

differently to risk when they face a potential gain situation than a potential loss situation. (4) Value is subjective, different from one person to another. Relations of trust are difficult if the parties involved are completely selfish. (5) Objective obervation is often too complex for human undertanding capacity. (6) Utility is subjective. (7) Myrdal (1979) underlines that rational choice models must use subjective values for efficiency, productivity and growth. (8) The importance of group decisions increases, making hardly sustainable the free will concept. (9) What is rational for one group is irational for another group. (10) Market economies are not uniform systems, but a group of subsystems consisting of numerous interacting groups.

The implications of this overview on the organisational decision-making process are important for decision and decision groups support. Management and research focus on models, ideally optimal models, in the organisational decision-making process. However, by their very nature, models do not take into account all existing issues. The model tries to mathematically express the nature of the problem. The difficulty derives from the fact that, in most cases, it is more convenient to ignore the complicated side of reality, or the system elements that are difficult to be measured accurately. The focus on decision-making process can provide means to include information that can only be expressed subjectively.

If an element of the system is complicated or difficult to be measured, it doesn’t mean it is unimportant. The issues regarding the production for an energy producer are accurately measured. Pollution issues are extremely important, but very complex and difficult to be measured.

In solving economic-environmental balance problems, the group preference is an issue. Because each individual has its own beliefs, and beacuse there is only one truth, group consensus does not mean truth. Global interest clearly differs from individual interest. The only way to act inside a group is to acceot compromise, as Nozick (1993) stated.

Alternatives Of Economic-Environmental Balance Modeling

1.CLASSICAL APPROACH 1.1. Welfare, essential criterium in determining economic-environmental balance and the pollution level


We cannot talk about social welfare without considering the economic aspects of human activities. These are extremely complex and decisively affect the welfare of a society, often disconsidering the real social cost of these activities and, consequently, the general pollution cost of the economic activity. This problem occurs also because environment is a natural resource and a „social” good contributing to welfare.

The interaction between economy and environment is complex, and its optimization implies firstly welfare maximization.

Welfare maximization implies that the difference between the sum of satisfactions and insatisfactions of a society to be maximized:

( ) MAXISSUfBm

k

k

n

i

i ⇒−== ∑∑== 11

where: B = society welfare; si = society satisfactions; (i ÷ n) = number of society satisfactions; ISk = society insatisfactions; (k ÷ m) – number of society insatisfactions. Obviously, such an approach on pollution cost is complex and

implies a series of issues. First, welfare is a comprehensive concept including not only economic and environmental elements, but in our case it must comprise only ecobomic and environmental aspects:

MAXISSBm

k

k

n

i

i ⇒−= ∑∑== 11

''

where: B' – welfare depending on economic and environmental aspects. Another problem consists in the lag between satisfactions and

insatisfactions. Massive cutting down of forests in Romania could provide a source for cheap furniture, translating in an increase of society’s satisfaction. But in time, it represents an environmental deterioration, because of oxygen production decrease and soil erosion, with difficult to predict effects. An example is the danger of flooding and landslides that threaten more and more areas of Romania as a result of massive cuts in recent years. We have:


89

( ) ( )tm

t

ktt

n

t

Itaa

ISa

ISB+

⋅−+

⋅= ∑∑== 1

1

1

1

11

'

where:

'aB - updated welfare

Extending the analysis, we notice that 'aB represents the global

welfare, being a premise for economic-environmental balance at global level and not an additional individual welfare.

It should be notedthat certain economic satisfactions are gained as a result of environmental insatisfactions.

The major problem is the way the welfare, the satisfactions and insatisfactions are expressed. One solution is to express them in monetary terms, but they can be presented as utilities and disutilities. In monetary terms, we have:

ecoeecoe CCBBB −−+='

where:

eB - economic benefits;

ecoB - environmental benefits, relatively difficult to express monetary, but it can be done by determining total economic value VET;

eC - economic costs;

ecoC - environmental costs or pollution cost. From this welfare equation, we need to determine environmental

damages and translate them in monetary terms, directly or indirectly. The direct approach implies an impact study for all economic

goals; combining results, environmental functions and natural resources analysis; loss estimates by market price identification for environmental functions and resources.

The indirect approach implies determining the optimal welfare level first (B), which will be achieved in the future, and from this calculating the polution cost:

Pollution cost = '*BCBB eecoe −−+

or


'*

11

.. BCBPCm

k

k

n

i

i −−= ∑∑==

where:

∑=

n

i

iB1 - the sum of benefits gained from the economic activity

and as a result of environment use and utility.

∑=

m

k

kC1 - sum of total economic costs. It is interesting that

society makes efforts such as investments, representing current insatisfactions, with the intention of future satisfactions and are included in Ck

'*B - welfare expressed monetary for a given level of pollution;

The cost is similar to a loss of welfare. Returning to the previous

equation:B *'

* ..PCCBB ki −−= ∑∑ We can develop pollution regulating techniques and we can

establish an acceptable pollution level *..PC at global level.

Esentially, the pollution cost for a society is equal to the welfare loss generated by pollution..

tBBCP −= 0 where

0B - welfare level without pollution

tB - welfare level with a given level of pollution Welfare can be measured in monetary units or in utilities gained

by a colectivity:

( )∑=

=n

i

iXYB1

But the problem becomes simple as we consider only the economic and environmental issues..

X – satisfactors generating vital (environmental) and economic utilities for individuals and societies.

i = 1...n – number of satisfactors.


91

In consequence, we can state that a society’s welfare depends on pollution, especially the cost of pollution. In case of monetary evaluation, pollution level can be determined starting from a given level of welfare. This theory is supported by the social-economic practice, an increase in welfare being linked to a reduced pollution.

In addition, the essential decision criterium is the comparison between VED, determinable economic value, (to a certain moment in time, based on evaluations and perceptions) and VET, total economic value of the environment. 1.2.MULTI-ATTRIBUTE UTILITY THEORY (MAUT) and ANALYTIC HIERARCHY PROCESS (AHP)

In multicriteria decision analysis, the MAUT ideal represents

total objectivity. This approach integrates offsets expressed in abstract terms, so that the subjects cannot predict accurately the selection impact (so that they cannot adjust their preferences to their beliefs). We can use subjective scales, but MAUT supporters avoid them even if the analysis becomes more difficult.

Multi –atribute utility (MAU) models are mathematical tools for evaluating and comparing alternatives to assist in decision making about complex alternatives, especially when groups are involved. They are designed to answer the question, "What's the best choice?" The models allow you to assign scores to alternative choices in a decision situation where the alternatives can be identified and analyzed. They also allow you to explore the consequences of different ways of evaluating the choices. The models are based on the assumption that the apparent desirability of a particular alternative depends on how its attributes are viewed. For example, if you're shopping for a new car, you will prefer one over another based on what you think is important, such as price, reliability, safety ratings, fuel economy, and style, are open for all to see, it's possible to make any number of changes and review the results. For example, if it appears that some attribute is too important in determining the results, the weights can be adjusted to produce different results.

To the other extreme, AHP is designed to quantify the subjective – fproviding a subjective measurement scale such as “equal, little more, much more”. Analytic Hierarchy Process (AHP) is one of Multi Criteria decision making method that was originally developed by Prof. Thomas


L. Saaty. In short, it is a method to derive ratio scales from paired comparisons. The input can be obtained from actual measurement such as price, weight etc., or from subjective opinion such as satisfaction feelings and preference. AHP allow some small inconsistency in judgment because human is not always consistent. The ratio scales are derived from the principal Eigen vectors and the consistency index is derived from the principal Eigen value. AHP is a structured technique for dealing with complex decisions. Rather than prescribing a "correct" decision, the AHP helps the decision makers find the one that best suits their needs and their understanding of the problem.

Users of the AHP first decompose their decision problem into a hierarchy of more easily comprehended sub-problems, each of which can be analyzed independently. The elements of the hierarchy can relate to any aspect of the decision problem—tangible or intangible, carefully measured or roughly estimated, well- or poorly-understood—anything at all that applies to the decision at hand.

Once the hierarchy is built, the decision makers systematically evaluate its various elements by comparing them to one another two at a time. In making the comparisons, the decision makers can use concrete data about the elements, or they can use their judgments about the elements' relative meaning and importance. It is the essence of the AHP that human judgments, and not just the underlying information, can be used in performing the evaluations

Bilevel decision models are useful in identifying the optimal decision regarding an investment project that implies major pollution; their efficiency depends on the two selection levels and the criteria considered for each decision level. 2.ALTERNATIVE MULTICRITERIA METHODS

Besides the modeling tools presented above, based on subjective aspects, there can be developed practical methods of multicriteria evaluation. These approaches are described using an investment project scenario for a heating plant generating major pollution. The criteria considered are death rate and health of population, agricultural pollution and decreasing production (loss expressed in million RON), pollution risk. The social benefits are as follows:


93

Global Death rate Agricultural loss Risk Social benefits and health death rate and health are calculated as net adjusted values, expressed in million RON. Agricultural loss is determined as net adjusted value, expressed in million RON. The risk is determined as major pollution probability, such as earthquakes, explosions, landslides, flooding, etc. Social benefits and thermal comfort increase are calculated objectively as households whose thermal comfort has improved from the original level. The alternatives are presented below:

Project alternatives

Death rate

Agricultural loss

Pollution risk

Social benefits

Project 1 50 1200 0,1 312 Project 2 23 1430 0,2 70 Project 3 56 410 0,25 40 Project 4 89 390 0,30 20 Project 5 75 860 0,20 58

The solution can be identified using weights.

Project alternatives

Death rate

Agricultural loss

Risk Benefit loss

Weight 1- weight

Project 1 0,1706 0,2797 0,1 0,37

Project 2 0,0784 0.333 0,2 0,86 Project 3 0,1911 0,0955 0,25 0,92 Project 4 0,3037 0,0909 0,30 0,96 Project 5 0,2559 0,2004 0,20 0,884

The results are then used in alternatives ordering.


Project 1 0,001777 Project 2 0,0044 Project 3 0,0041 Project 4 0,0079 Project 5 0,0090

The model provides cardinal values that can be used in precise

ordering of each alternative. Image theory

Image theory (Pesta et al., 2005) uses decision classification to enable rapid taking of the optimal decision in the case of numerous decisions that must be taken into account or when the timeframe is limited. Image theory provides an overview of the decision-making process. Morrell (2004) states that while rational choice theory is consitent with the utilitarian ethics, it is not consistent to kantian ethics or virtue-based ethics, but the image theory is in consensus with all these perspectives.

Image theory is probably the useful in the multicriteria analysis structuring phase. For example, analysis can be structured on four interest groups:

Interest group Criteria Government death rate and sickness, pollution risk, political benefits Energy profit, heat demand Local Council solving the household heating problem, political benefits, jobs Households thermal comfort, wages, cheap heat Farmers reducing crops, reducing selling price, sickness risk

Image theory will increase analysis complexity, requesting more opinions. Measurements (objective or subjective) are needed for all important criteria, reflected in a more severe analysis. Also, the attention of one group is likely to focus on a different issue than another group. This makes the decision-making process more difficult that in the case of a central decision authority.

Another aspect of image theory regards the support gaining political process. Even the fiercest supporters of objectivity must sell their ideas. The way the outputs are presented clearly influences the final result. While analysits try an objective presentation, politicians are


95

experts in subjective presentations. Mitroff şi Linstone (1993) suggest that decision problems must be

considered from three perspectives: technical, organisational and individual. Offsets support the decision-making process from the technical perspective, while beliefs and creativity govern the individual perspective. Uncertainity tends to be considered unmanageable, or is replaced by estimated probabilities. The „what if” practice develops the ability to cope with surprises, like hedging or crisis management. From the organisational perspective, the reaction to problems starts with stonewalling. From the individual point of view, there is a tendency to ignore complex feedback loops, to update and to ignore threats. The possible system performance improvement actions include the division of technical problems, adjustments of organisational issues and the use of all perspectives in the first phases of individual planning.

Image theory does not affect the numerical methodology used. Churchman (1971) considers it as sinergic, providing a means of problem identification that allows the projection of improved alternatives. Verbal decision analysis

Verbal decision analysis (Larichev and Moshkovich, 1997) uses qualtitative data for highly uncertain decisional environments. This approach compares controlled pairs of offsets using conflictual criteria, in order to identify the decident’s preffered solution. This method uses information less intensively than multicharacteric utility theory, based on subjective evaluation of the decident at strategic level.

Verbal decision analysis simplifies the decisional problem, focusing on what is important. The unessential, but accurate measurements are rejected. For example, inaccurate estimates of 58.930 million RON and 60.156 million RON cand be considered equivalent. Death rate,

health

Agricultural losses

Major pollution – risk

Social benefits

Project 1 Moderate Low Very high Low Project 2 Very high Very high Very low Very high Project 3 High Very low Low High Project 4 High Very low Average Average Project 5 High High Low Very high


Selection can be used to remove additional alternatives, remaining only two possible alternatives. For example, health loss and estimated death rate must not be too elevated, and the major pollution risk must be low. These conditions remove Projects 1 and 2, being left only three options. Removing further certain unsignificant advantages, Project 3 is better than Project 4. Thus, the analysis will focus on Projet 3 and Project 5

Death rate,

health

Agricultural losses

Major pollution – risk

Social benefits

Project 3 High Very low Low High Project 5 High High Low Very high

Project 3 presents relative advantages considering the death rate

and estimated losses in agriculture. Project 5 has the relative advantage of social benefits. Decidents will face the following offset problem: relative advantages of Projectu 3 with those of Project 5. Conclusions

In achieving the economic-environmental balance and modeling this balance for investment projects, the analysis of multiple characteristics can be done using various subjectivity degrees. Most researchers argument in favour of objectivity; according to them, the real decision-making process requests scientific elements as much as possible. Although, partiality exists and must be accepted. We cannot provide the best answer to complex social decision problems, but we can try to understand better the system. The subjective reasoning is useful in adopting better decisions. It is needed a sustainable balance between subjective and objective so that the subjects involved in a complex decision to achieve the highest level of satisfaction with the lowest insatisfaction. This approach is the most feasible approach from the economic-environmental balance point of view, without neglecting the assimilation capacity of the environment and the maximum acceptable pollution levels considering human, plants, anaimals, soil and air sanity.

Adopting mathematical assumptions makes possible the development of theorems regarding human behaviour in solving the economic-environmental balance problem. Reason is a concept often


97

used to justify mathematical convenient assumptions. Such assumptions include the concepts of Pareto optimality, minimization of the distance to the ideal point and the unsatisfied demand for a product. First, Pareto optimality (based on the continuous preference for more than less of a certain product) is valid in many cases, but is doubtful in dynamic problems, if used for alternatives discharge. In the previous example, one alternative was rejected according the Pareto rule. This rule must be carefully used. Second, minimizing the distance to an ideal point is used in the case of total lack of information on preferences. Finally, the unsatisfied demand for a certain product is empirically observed, even in the case of individual acting rationally. As Nozick stated (1993), economists start from the premise of welfare maximization, considered an essential issue in modeling the economic-environmental balance.

Reason is the core of human decision-making process. Hegel (1873) considered that reasoning is a subjective process. For a decision to be taken impartially, the decident must adopt the alternative with the highest calculated useful value. Even in the multicriteria decision analysis area, human decidents are responsible for the final decision, using the “sustainable decision” method. This will be probably the right decision for a wrong reason. The verbal decision analysis simplifies the decision-making process because it focuses on significant differences. By focusing on the final versions comparison, verbal decision analysis can be considered hegelian, according to Churchman (1971).

Models are imperfect. They don’t include all existing factors. Even the most careful attempt to objectively measure will involve imprecisions. Bibliography Danilo C. Israel, Review of Macroeconomic Models and Microeconomic Valuation Methods Applied in the Natural Resources and Environment

Sector 1994 Paper Presented During the Technical Workshop of MIMAP Project Phase III held on February 17-18, 1994 in Ternate, Cavite, Philippines. Special issue on Optimization models in environment and sustainable development Istvan Maros Æ Garyfallos Arabatzis Æ Angelo Sifaleras, August 2009 / Published online: 29 August 2009 _ Springer-Verlag 2009


� Aadland D, Caplan A (2006) Curbside recycling: waste resource or waste of resources?. J Policy Anal Manag

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ShumanH(1993) Report of theNOAApanel on contingent � valuation. Available at:

www.darp.noaa.gov/library/pdf/cvblue.pdf � American Association for Public Opinion, Mason � Bateman I, Mawby J (2004) First impressions count: a study

of the interaction of interviewer appearance and � information effects in contingent valuation studies. Ecol

Econ 49(1):47–55 � Benney M, Riesman D, Star SA (1956) Age and sex in the

interview. Am J Sociol 62(2):143–152 � Blaine T, Lichtkoppler F, Jones K, Zondag R (2005) An

assessment of household willingness to pay for curbside � Brookshire D, Thayer M, Schulze W, d’Arge R (1982)

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Conference of the American Association for � Public Opinion Research [CD-ROM]. American Statistical

Association, Alexandria, VA, pp 3815–3821 � Clarke P, Sproston K, Thomas R (2003) An investigation

into expectation-led interviewer effects in health surveys. Soc Sci Med 56:2221–2228

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Hersch J, Viscusin (2006) The generational divide in support for environmental policies: European evidence. Clim Change 77:121–136 Kahneman D, Sugden R (2005) Experienced utility as a standard of policy evaluation. Environ Resour Econ 32:161–181 Brendan Fisher Stephen Polasky Thomas Sterner, Conservation and HumanWelfare: Economic Analysis of Ecosystem Services Accepted: 19 September 2010 © Springer Science+Business Media B.V. 2010


Achieving the economic-environmental balance for investment projects based on modified utility model Research conducted under Research Project Ideas 1239/2007

S. G. Szentesi Silviu Gabriel Szentesi “Aurel Vlaicu” University of Arad, Romania

Abstract The work is the fruit of scientific research on ecological economic equilibrium modeling for investment projects. The proposed model is verified in this work and a case study of an investment project consisting of an aluminum recycling plant, the proposed model is based on determining the utility of the project in terms of environmental criteria and comparing it with accepted standard utility for the such a project on pollution norms derived from the assimilative capacity of the natural environment of polluting factors. Keywords: balance, modeling, investment projects, utility, polluting factors

1. Concepts of modeling ecological economic equilibrium of the investment projects.

Striking a balance is a goal of ecological economy of contemporary economic science. A general balance between human activity and particularly the economic and natural environment is difficult in practical terms or in terms of costs is made unbearable by the current generation. The challenge to achieve sustainable development sometimes seems lackluster economy and achieving environmental balance and actually also implies a balance between the interests of our generation and future generations interests. One of the core ideas of the research team realized our was based on the generation of such a balance by making new investments, new projects in the economic, social and environmental impact analysis based on models and / or criteria to meet the requirements such a balance.

Achieving the economic-environmental balance for investment …

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In our modeling we started exploring some directions for achieving this balance and different action:

1. A first direction of solving the ecological economic equilibrium is the classical economic theory known as the cost / benefit analysis. Even from the classical analysis of the ecological economic equilibrium approach there different versions and even different models, but all share a social issue and Inspection criticized quite pertinent criticism of environmentalists about the monetary aspects of the environment and economic cost of pollution generated by economic activity resulting from pollution and environmental damage caused in monetary terms.

2. A second direction of solving the problem is related to ecological economic equilibrium of the natural functions and environmental capacity to assimilate pollutants factors) residues, particulates, toxic gases, waste, etc..) But also by technological progress and other technical aspects of waste recycling pressure reducing pollution and environmental polluting factors. This direction, or technical guidance is important and its effectiveness depends on accurate determination of the assimilation capacity of the natural environment and the development of new clean or less polluting technologies and the organization of recycling and reusing waste, residues or gases, or industrial plant household.

3. A third way of achieving environmental and economic equilibrium modeling and mathematical modeling in that it is appropriate to develop a series of mathematical models based on input parameters such as the hazards of pollution, economic indicators, and determine the level of output ( output) based on mathematical expressions.

4. A fourth category of models is one based on utility maximization and wealth. Determining the utility can be achieved using different techniques and practical models can be developed using the absolute scale by comparison, using the confirmation-denial of expectations, etc..

5. A fifth approach involves ranking of variants of an investment project based on environmental criteria and economic criteria and social environment in which the criteria can get different weights in most cases a higher specific weight in the model. Multicriterial ranking of investment projects that

S. G. Szentesi 102

involve choosing the best one that surpasses all variants analyzed. Some of the methods used for these models are: electric methods, process analysis method hierarchical AHP, MAUT method, Multi-attribute utility theory, method PROMETHEE.

6. A sixth direction of model development involves a combination of other models listed above. One of the models involving a combination of models is usability analysis.

2. Research method

This paper proposes the use of utility analysis method in modeling ecological economic equilibrium and determination of this equilibrium case study of an aluminum plant recycling. The model developed involves a combination of utility theory and methods for determining the utility of the method technique that requires a knowledge of the level of pollution allowable emission standards of waste assimilation capacity of the natural environment.

Considerations on usability analysis:

Usability analysis involves the partial utility for different levels of decision criteria to prioritize investment projects or to compare an investment project with a standard situation acceptably utilitarian based standard. Utility analysis method methodology involves the following steps:

1. determination of objective criteria 2. objective criteria for determining the specific weight. 3. determination the partial utilities 4. dermination calculation of total utility, 5. evaluating alternatives and variations setting better. The first step in usability analysis is to determine objective

criteria. In their determination to be taken into account several aspects such as objective criteria must be formulated in operational mode that means that each criterion can be measured using a scale (which can be an ordinal scale, nominal or cardinal). Also it is important to avoid multiple registration of the characteristics of the project. Lack of records and many utilities are essential premises of Independence in utility analysis. Utility independence exists when an objective criterion to achieve this accomplishment is possible without replacing lead to another criterion. If utility analysis is recommended to give up monetary


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criteria. The reason for this recommendation is that the revenues or the ins and outs typically affect an investment project in several ways. Monetary criteria to be included in other criteria. Determination of objective criteria requires a structured analysis and system objectives. If an object size complex decision problems can be divided in several hierarchical levels of objectives, this includes a mix and operationality concreteness objectives with setting the levels of hierarchy

The second step in the usability analysis is to establish objective criteria specific weight. Share or the specific weight of different criteria is different for each situation and allows removal out or emphasize important relevant criteria. To determine the weighting of the criteria we use several methods such as direct or Upgrading comparison and various direct and indirect scaling methods. Scaling involves ordering direct target of value criteria on a scale of intervals, the distance between values is reflected on the differences in preferences of decision makers. On a scale of intervals is done primarily indirect sequencing of objective criteria for ranking. Depending on their position in the ordered list according to importance of each criterion is given a figure that looks rank. Having agreed this figure it is converted into weights using an interval scale. Generally this percentage has ranged from 0 to -1 or 0-100. where there is a different hierarchy level of objective criteria to determine the specific gravity for each level of objective criteria.

The third step is determining the partial utilities of each alternative and each criterion icepand the lower hierarchical levels. This third step involves doaua most important processes: First, it is important to know the variation of objective criteria for each alternative, to this end are used nominal scales, ordinal or cardinal. Finally, measured values of the criteria are transformed into partial utilities. They will be measured using a scale that is usually partial utility cardinal and must be unified for all criteria. Verification of transformation value targets in partial utility values and requires a subjective assessment by improving traceability of transformation functions. It can distinguish three different types of processing functions.

1) The International Teams discrete processing specific categories of targets are arranged each on certain partial utilities. They establish only one measurement of ordinal or nominal data transfer measured in an ordinal scale.

2) a piecewise constant function processing all values of a given range will be converted into specific partial utilities.

S. G. Szentesi 104

3) It is also available using a transformation function that, for it is characteristic that a small difference between the values set as an objective in each case to arrive at different partial utility.

In the fourth step, usability analysis is the calculation of total utility. This means the next thing, objective criteria were measured and were determined on the same scale partial cardinal utilities and the utilities are independent of each other

In this case the notation is useful uik partial version of the project and for criterion k. Partial utility for each criterion is weighted k with the mean specific weight wik. Ui total utility of an alternative product and is given by the sum of partial utilities and share of each relationship features k as:

k

k

k

iki wuU ×=∑=1

To develop further the model is necessary to transform the polution in in utility functions. This functions can be determened in a statistical way or in with a mathematical cost function of losst utility.The diferent approches can be further explored.Un exemple for an ilustration can be callculation of noise pollution. Example noise pollution

In terms of contemporary civilization, people are undergoing continuous aggression due to a diverse range of sounds as a result of using, industrial machinery, appliances. Like air pollution, noise nuisance affects human communities that man is adapted to a certain level of noise and vibration, sound intensity maximum threshold is 80dB over the messy overlap 111g69b sound becomes harmful. The limit of human endurance is 60db. Sound is a vibration of air which propagates in the form of elastic waves with 340 m / s and the noise at level 111g69b overlapping of different sounds messy. The physical characteristics of sound:

- Sound frequency (Hz): the number of complete oscillations per unit of time. The human ear perceives sounds in the range 16 (infra)-20000Hz (ultrasound).

- Sound pressure (db): pressure difference between the minimum and a maximum oscillation occurs due to compression and expansion of the environment in which sound waves propagate. 1db =


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lowest pressure variation informer acoustic (hearing) by man. To characterize the frequency dependence of sound introduced a scale to measure the foni appreciate the sensitivity with which the human ear to different sounds (size-related subjective way the human ear perceives sound intensity). This perception is determined using fonomeasuring diveices. Examples of acoustic pressure: Pollution Utility - 0dB sensitivity threshold 0% 100% - Whisper, whisper, hum library 10dB 0% 100%+ - 50dB normal conversation 30,77% 69,23% - 70dB urban traffic 46,16% 53,84% - 80dB 53,85% 46,15% - 110dB rock band 76,93% 23,07 - Higher threshold 130dB 92,30% 7,70% - Sonic threshold = 140dB deafness. 100,00% 0%

The propagation of sound waves is influenced by environmental conditions and distance from sources. Pollution y

0

20

40

60

80

100

120

0 50 100 150

Series1

The evolution is a linear one and can be transformed in a mathematical function like y=0,0077*x – 0,08 where y represent de pollution and x the dB noise level.

S. G. Szentesi 106

3. Case Study Basic data are next case study; An aluminum recycling plant, built

punched in an investment project worth 50 million euros. Aluminum processing factory has an initial capacity of 80,000 tonnes per year, which will be extended in the coming years, the investor estimating an annual turnover of 75 million working euro. Capacity which is currently 205 tonnes of cast aluminum per day. The factory has about 120 employees. Emissions

The treatment and melting furnaces are no potential emissions of dust, metal components, chlorine, hydrochloric acid and products of incomplete combustion such as dioxins and other organic compounds. It may be possible formation of dioxins in the combustion zone and the cooling of the exhaust gas treatment system. Emissions may escape from the process either as emissions or as fugitive emissions basket depending on plant age and wear technology. Flue they are usually emissions continuously or periodically monitored and reported by staff on site or by outside consultants by the competent authorities. Ammonia and other gases may be emitted as a result of storage, improper handling and transport of crustal dust also will be formed as a result of sludge handling and treatment. There are potential water leakage in suspended solids, metals and oil production and storage as a result of improper discharge of materials. Emissions to air

Potential emissions to air are: - - Dust and smoke - Metal components - Organic matter (dioxins and VOCs) and SO. - Nitrogen oxides (NOx) - Sulfur dioxide - Chlorides, HCl and HF. A significant amount of emissions of these substances is produced

by fuel use and supply of material impurities. Some quantities of dust can be produced by gas and by waste powder salt


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Dust and metals They are linked together and are produced from burning gas or slag

and flows used. Certain metals, which contaminants are present that will be thrown out during the melt and form dust. Smoke production and organic carbon due to the presence of chloride can lead to the formation of dioxins, which in turn will be associated with particles Organic materials (VOCs, dioxins) and CO

Incomplete combustion or organic content of food material can lead to emissions of organic materials. Effective supply of furnace burners and controls are used to optimize combustion. High firing rates of the organic materials included should be considered if they are placed in the furnace. It was agreed that waste prewash removes much of organic matter and improves melting blend for degassing and removal of magnesium chloride, and the use of chloride (salt flux) will provide a source of chlorine for dioxin formation potential.

Sulfur dioxide and nitrogen oxides

Both components are produced as a result of combustion systems used kiln emissions are generally insignificant. To minimize NOX emissions can be used for burning fuel poor or low in sulfur. Using oxy-fuel burners can reduce thermal NOX formation, but there is a possibility that the increase in oxygen lead to opposite effects due to higher operating temperatures, higher concentrations are however associated with lower gas volumes and regular amounts. HF, HCl and Chlorides

Chlorine can be used to treat molten aluminum to remove hydrogen before and magnesium (magnesium removal). A rotary furnace use is to extract without the use of magnesium chloride. If chlorine is used in excess, can be eliminated as aluminum chloride hydrolysis is in contact with air produces hydrochloric acid. In some places using wet scrubbers and other dry or semi-used, scrubbers to remove these compounds.

Their formation can be minimized with good control by using mixtures of chlorine and inert gases. Using the flow of salt in a foundry can generate emission fumes containing fine metal chloride. Use to remove magnesium fluoride or a stream may result in release fluoride and hydrofluoric acid in small quantities.

S. G. Szentesi 108

Emissions to water

The production of secondary aluminum raw material is primarily a wet process.

Release of wastewater is usually limited to cold water is often reinstated and rain water flow close to surfaces and roofs. Rain water can be contaminated by close open store raw materials such as solid pieces and greasy stored. Values typical for these contaminants are <0.03 kg / ton for particulate matter. In addition, considerable amounts of wastewater can be discharged when wet systems are used to control air pollution.

He plant analyzed, the raw material (waste) is stored indoors and rain concrete. Waters are passed through an oil and sand separator before being discharged into the channel CC2 area. Water used in the cooling system casting is recirculated, so this water contamination risk. Process residues and wastes

Scaling is the process of mixing and treatment from 15 to 20 kg / ton of aluminum produced. This material contains significant amounts of Al and pre-treatment for example by pressing the crust into the atmosphere and cooling the inert gas reduces oxidation. During storage, crusts can react with moisture (from air) to produce ammonia and other gases.

Scaling is the process of mixing and treatment from 15 to 20 kg / ton of aluminum produced. This material contains significant amounts of Al and pre-treatment for example by pressing the crust into the atmosphere and cooling the inert gas reduces oxidation. During storage, crusts can react with moisture (from air) to produce ammonia and other gases. 4. Calculation of total utility investment objective and useful comparison with the standard. Level I Project investment in equilibrium with the environment Level II Water Pollution (0.3) Soil Pollution (0.2) Air pollution (0,5) Level III PF Pollution (0.5), Waste (0.50; Particles in air (0.4);


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The Water Pollution (0.5) Acid Rain (0.5) Toxic gases (0.6)

To determine the ecological economic equilibrium for acetate type of investment projects have proposed a method to combine the utility of this technical approach based on assimilative capacity of environmental pollutants, expressed by rules or standards of permissible pollution. In the table for each pollutant found weights determined by direct ranking method. To transform the partial utilities pollution was used to convert the table.

Water Pollution

%

Partial utilities

Soil Pollution

%

Partial utilities

Air pollution

%

Partial utilities

5% 0,90 5% 0,90 5% 0,80 10% 0,80 10% 0,80 10% 0,70 12% 0,78 12% 0,78 12% 0,65 15% 0,75 15% 0,75 15% 0,60 20% 0,70 20% 0,70 20% 0,50 25% 0,30 25% 0,30 25% 0,37 30% 0,10 30% 0,10 30% 0,30 40% 0 40% 0 40% 0,05 50% 0 50% 0 50% 0

1. A. Water Pollution 12% → 0.78 partial utility

B. Pollution standard partial utility allowance 15% → 0.75 2. A. Soil Pollution 10% → 0.8 partial utility→ 15%

B. Standard Pollution 0.75 partial utility 3 A. Air Pollution 25% → 0,37 partial utility

B. Standard allowed pollution 30%→ 0,30

A. a. 0,78 x 0,3 = 0,224 b. 0,8 x 0,2 = 0,16 c. 0,37 x 0,5 = 0,185 ____________________ project under consideration 0,569

S. G. Szentesi 110

B. a. 0,75 x 0,3 = 0,225 b. 0,75 x 0,2 = 0,15 c. 0,30 x 0,5 = 0,15 ____________________ standard project 0,525 5. Conclusions

Based on case study results can be concluded that the project represents investment in recycling aluminum manufacturing plant meets the requirements of ecological economic equilibrium, the total utility of 0.569 calculated for this purpose is more useful than the standard required for a situation that is a situation for admissible limit pollution norms.

Analysis method combined utility and completed pollution standards can be used in practical terms by policy makers and environmental agencies to determine the correct balance for each project the green economy (objective) investment. This method has theoretical and practical potential to be further developed and this paper presents a case in point. Bibliography Florescu C. , Mâlcomete P, Pop A.N. Szentesi S Marketing co. Explanatory Dictionary, Economic Publishing House, 2003. Endres A., Umweltokonomie, Kohlhammer, Stuttgard 2007 Erichson, Plinke,Weiber Backhaus, Multivariate Analysenmethoden, Springer, ed XII, 2008 http://www.mmediu.ro (is hosted by the Ministry of Environment of Romania M. Blaug, Economic Theory in Retrospect, Didactic and Pedagogic Publishing House, Bucharest, 1992. Simpson R.D. , Toman M.A., Ayres R., Natural Resources and the Environment in the New Millennium, Lamson Library and Learning Commons, 2005. Szentesi S., Economy and the environment, Servo-Sat Publishing House, Arad, 1998.


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Szentesi S., Investment decisions in the process, UAV Publishing House, Arad, 1999. Szentesi S., Cureteanu R., Management and analysis of investment projects, Mirton Publishing House, Timisoara, 2004. Szentesi S., Rusu S., Cureteanu R., Statistics economic activity, Mirton Publishing House, Timisoara, 2005. Gotze. U, Deryl Northcott, Peter Schuster, Investment Appraisal: Methods and Models, Spriger 2007 Gotze. U, Investitionsrechnung, Springer, 2008 .


Electre method in multicriterial projects evaluation form economic and ecologic point of view


M.Viezental, S. G. Szentesi, G. MoŃ

Viezental Mihaela, Szentesi Silviu Gabriel, MoŃ Ghiocel “Aurel Vlaicu” University of Arad, Romania

Abstract Ranking and selecting projects considering ecological criteria( pollution) and economic criteria in the same decision making is not relatively common, and often difficult task. It is complicated because there is unusually to analyze simultaneously the economic and ecologic dimension for measuring the impact of each project and more than one decision maker. The ELECTRE method has several unique features not found in other solution methods; these are the concepts of outranking and indifference and preference thresholds. The ELECTRE method is explained and applied to the project selection problem using a Visual Basic application within Microsoft Excel. Results show that ELECTRE was well received by the decision makers and, importantly, provided sensible and straightforward rankings. ELECTRE method is useful for realizing for each investment project a balance between economic criteria and pollution. Keywords: multiatribut decision making, ELECTRE, projects evaluation, multicriterial evaluation.

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1. Decision Making Process

Decision making is the study of identifying and choosing alternatives based on the values and preferences of the decision maker. Making a decision implies that there are alternative choices to be considered, and in such a case we want not only to identify as many of these alternatives as possible but to choose the one that best fits with our goals, objectives, desires, values, and so on. (Harris (1980)

According to Baker et al. (2001), decision making should start with the identification of the decision maker(s) and stakeholder(s) in the decision, reducing the possible disagreement about problem definition, requirements, goals and criteria. Then, a general decision making process can be divided into the following steps:

Step 1. Define the problem

This process must, as a minimum, identify root causes, limiting assumptions, system and organizational boundaries and interfaces, and any stakeholder issues. The goal is to express the issue in a clear, one-sentence problem statement that describes both the initial conditions and the desired conditions.. Of course, the one-sentence limit is often exceeded in the practice in case of complex decision problems. The problem statement must however be a concise and unambiguous written material agreed by all decision makers and stakeholders. Even if it can be sometimes a long iterative process to come to such an agreement, it is a crucial and necessary point before proceeding to the next step.

Step 2. Determine requirements

Requirements are conditions that any acceptable solution to the problem must meet. Requirements spell out what the solution to the problem must do.. In mathematical form, these requirements are the constraints describing the set of the feasible (admissible) solutions of the decision problem. It is very important that even if subjective or judgmental evaluations may occur in the following steps, the requirements must be stated in exact quantitative form, i.e. for any possible solution it has to be decided unambiguously whether it meets the requirements or not. We can prevent the ensuing debates by putting down the requirements and how to check them in a written material.


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Step 3. Establish goals

Goals are broad statements of intent and desirable programmatic values.... Goals go beyond the minimum essential must have.s (i.e. requirements) to wants and desires.. In mathematical form, the goals are objectives contrary to the requirements that are constraints. The goals may be conflicting but this is a natural concomitant of practical decision situations.

Step 4. Identify alternatives

Alternatives offer different approaches for changing the initial condition into the desired condition.. Be it an existing one or only constructed in mind, any alternative must meet the requirements. If the number of the possible alternatives is finite, we can check one by one if it meets the requirements. The infeasible ones must be deleted (screened out) from the further consideration, and we obtain the explicit list of the alternatives. If the number of the possible alternatives is infinite, the set of alternatives is considered as the set of the solutions fulfilling the constraints in the mathematical form of the requirements.

Step 5. Define criteria

Decision criteria, which will discriminate among alternatives, must be based on the goals. It is necessary to define discriminating criteria as objective measures of the goals to measure how well each alternative achieves the goals. Since the goals will be represented in the form of criteria, every goal must generate at least one criterion but complex goals may be represented only by several criteria. It can be helpful to group together criteria into a series of sets that relate to separate and distinguishable components of the overall objective for the decision. This is particularly helpful if the emerging decision structure contains a relatively large number of criteria. Grouping criteria can help the process of checking whether the set of criteria selected is appropriate to the problem, can ease the process of calculating criteria weights in some methods, and can facilitate the emergence of higher level views of the issues. It is a usual way to arrange the groups of criteria, subcriteria, and sub-subcriteria in a tree-structure (UK DTLR (2001)).

According to Baker et al. (2001), criteria should be:


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� able to discriminate among the alternatives and to support the comparison of the performance of the alternatives,

� complete to include all goals, � operational and meaningful, � non-redundant, � few in number.

In some methods, see Keeney and Raiffa (1976), non-redundancy is required in the form of independency.

We mention that some authors use the word attribute instead of criterion. Attribute is also sometimes used to refer to a measurable criterion.

Step 6. Select a decision making tool There are several tools for solving a decision problem. Some of them will be briefly described here, and references of further readings will also be proposed. The selection of an appropriate tool is not an easy task and depends on the concrete decision problem, as well as on the objectives of the decision makers. Sometimes .the simpler the method, the better. but complex decision problems may require complex methods, as well.

Step 7. Evaluate alternatives against criteria Every correct method for decision making needs, as input data,

the evaluation of the alternatives against the criteria. Depending on the criterion, the assessment may be objective (factual), with respect to some commonly shared and understood scale of measurement (e.g. money) or can be subjective (judgmental), reflecting the subjective assessment of the evaluator. After the evaluations the selected decision making tool can be applied to rank the alternatives or to choose a subset of the most promising alternatives.

Step 8. Validate solutions against problem statement

The alternatives selected by the applied decision making tools have always to be validated against the requirements and goals of the decision problem. It may happen that the decision making tool was misapplied. In complex problems the selected alternatives may also call the attention of the decision makers and stakeholders that further goals or requirements should be added to the decision model.


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Step 9. Validate solutions against problem statement

The alternatives selected by the applied decision making tools have always to be validated against the requirements and goals of the decision problem. It may happen that the decision making tool was misapplied. In complex problems the selected alternatives may also call the attention of the decision makers and stakeholders that further goals or requirements should be added to the decision model. 2. Single criterion vs. multiple criteria, finite number of alternatives vs. infinite number of alternatives

It is very important to make distinction between the cases whether we have a single or multiple criteria. A decision problem may have a single criterion or a single aggregate measure like cost.

Then the decision can be made implicitly by determining the alternative with the best value of the single criterion or aggregate measure. We have then the classic form of an optimization problem: the objective function is the single criterion; the constraints are the requirements on the alternatives.

Depending on the form and functional description of the optimization problem, different optimization techniques can be used for the solution, linear programming, nonlinear programming, discrete optimization, etc. (Nemhauser et al. (1989)).

The case when we have a finite number of criteria but the number of the feasible alternatives (the ones meeting the requirements) is infinite belongs to the field of multiple criteria optimization.

Also, techniques of multiple criteria optimization can be used when the number of feasible alternatives is finite but they are given only in implicit form (Steuer, R. E. (1986)).

This brief survey focuses on decision making problems when the number of the criteria and alternatives is finite, and the alternatives are given explicitly. Problems of this type are called multiattribute decision making problems.

3. Multi-attribute decision making methods

Consider a multi-attribute decision making problem with m criteria and n alternatives. Let C1,…, Cm and A1 ,.., An denote the criteria and alternatives, respectively. A standard feature of multi-


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attribute decision making methodology is the decision table. In the table each row belongs to a criterion and each column describes the performance of an alternative. The score aij describes the performance of alternative Aj against criterion Ci. For the sake of simplicity we assume that a higher score value means a better performance since any goal of minimization can be easily transformed into a goal of maximization.

As shown in decision table, weights w1,...,wm are assigned to the criteria. Weight wi reflects the relative importance of criteria Ci to the decision, and is assumed to be positive. The weights of the criteria are usually determined on subjective basis. They represent the opinion of a single decision maker or synthesize the opinions of a group of experts using a group decision technique, as well. The values x1,...,xn associated with the alternatives in the decision table are used in the MAUT methods and are the final ranking values of the alternatives. Usually, higher ranking value means a better performance of the alternative, so the alternative with the highest ranking value is the best of the alternatives.

Multi-attribute decision making techniques can partially or completely rank the alternatives: a single most preferred alternative can be identified or a short list of a limited number of alternatives can be selected for subsequent detailed appraisal.

Besides some monetary based and elementary methods, the two main families in the multi-attribute decision making methods are those based on the Multi-attribute Utility Theory (MAUT) and Outranking methods.

The family of MAUT methods consists of aggregating the different criteria into a function, which has to be maximized. Thereby the mathematical conditions of aggregations are examined. This theory allows complete compensation between criteria, i.e. the gain on one criterion can compensate the lost on another (Keeney and Raiffa (1976)).

The concept of outranking was proposed by Roy (1968). The basic idea is as follows. Alternative Ai outranks Aj if on a great part of the criteria Ai performs at least as good as Aj (concordance condition), while it’s worse performance is still acceptable on the other criteria (non-discordance condition). After having determined for each pair of alternatives whether one alternative outranks another, these pair wise outranking assessments can be combined into a partial or complete


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ranking. Contrary to the MAUT methods, where the alternative with the best value of the aggregated function can be obtained and considered as the best one, a partial ranking of an outranking method may not render the best alternative directly. A subset of alternatives can be determined such that any alternative not in the subset be outranked by at least one member of the subset. The aim is to make this subset as small as possible. This subset of alternatives can be considered as a shortlist, within which a good compromise alternative should be found by further considerations or methods. 3.1 Cost-benefit analysis

Cost-benefit analysis (CBA) is a worldwide used technique in decision making. CBA evaluates the costs and benefits of the alternatives on monetary basis. Recently, attempts have been made to incorporate the environmental impacts within CBA to improve the quality of environmental decision making. Although advances have been made, problems persist in applying CBA to environmental issues, including the monetary valuation of environmental impacts (UK DTLR (2001)).

On the other hand, CBA has great attractions as a tool for guiding public policy:

� it considers the gains and losses to all members of the society on whose behalf the CBA is being undertaken;

� it values impacts in terms of a single, familiar measurement scale - money - and can therefore in principle show that implementing an alternative is worthwhile relative to doing nothing;

� the money values used to weight the relative importance of the different impacts are based on people’s preferences generally using established methods of measurement..

Despite its limitations, CBA can be efficiently integrated into complex methods of environmental decision making. See Munda (1996) how CBA can be integrated into environmental assessment and US EPA (2000) for guidelines on economic analysis including cost and benefit analysis.

3.2 Elementary methods

These elementary approaches are simple and no computational support is needed to perform the analysis These methods are best suited for


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problems with a single decision maker, few alternatives and criteria that is rarely characteristic in environmental decision making (Linkov et al. (2004)).

3.2.1 Pros and cons analysis

Pros and cons analysis is a qualitative comparison method in which good things (pros) and bad things (cons) are identified about each alternative. Lists of the pros and cons are compared one to another for each alternative. The alternative with the strongest pros and weakest cons is preferred. It requires no mathematical skill and is easy to implement. (Baker et al. (2001)).

3.2.2 Maximin and maximax methods

The maximin method is based upon a strategy that tries to avoid the worst possible performance, maximizing the minimal performing criterion. The alternative for which the score of its weakest criterion is the highest is preferred. The maximin method can be used only when all criteria are comparable so that they can be measured on a common scale, which is a limitation (Linkov et al. (2004)).

3.2.3 Conjunctive and disjunctive methods

These methods require satisfactory rather than best performance in each criterion. The conjunctive method requires that an alternative must meet a minimal performance threshold for all criteria. The disjunctive method requires that the alternative should exceed the given threshold for at least one criterion. Any alternative that does not meet the conjunctive or disjunctive rules is deleted from the further consideration. These screening rules can be used to select a subset of alternatives for analysis by other, more complex decision making tools (Linkov et al. (2004)). Screening by conjunctive and disjunctive rules can also be applied in Step 2 (Determine requirements) of the decision making process.

3.2.4 Lexicographic method

In the lexicographic method criteria are ranked in the order of their importance. The alternative with the best performance score on the most important criterion is chosen. If there are ties with respect to this criterion,


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the performance of the tied alternatives on the next most important criterion will be compared, and so on, till a unique alternative is found (Linkov et al. (2004)).

3.3 MAUT methods

In most of the approaches based on the Multi-attribute Utility Theory (MAUT), the weights associated with the criteria can properly reflect the relative importance of the criteria only if the scores aij are from a common, dimensionless scale. The basis of MAUT is the use of utility functions. Utility functions can be applied to transform the raw performance values of the alternatives against diverse criteria, both factual (objective, quantitative) and judgmental (subjective, qualitative), to a common, dimensionless scale. In the practice, the intervals [0,1] or [0,100] are used for this purpose. Utility functions play another very important role: they convert the raw performance values so that a more preferred performance obtains a higher utility value. A good example is a criterion reflecting the goal of cost minimization. The associated utility function must result in higher utility values for lower cost values.

It is common that some normalization is performed on a nonnegative row in the matrix of the aij entries. The entries in a row can be divided by the sum of the entries in the row, by the maximal element in the row, or by a desired value greater than any entry in the row. These normalizations can be also formalized as applying utility functions.

3.3.1 Simple multiattribute rating technique (SMART)

SMART is the simplest form of the MAUT methods. The ranking value xj of alternative Aj is obtained simply as the weighted algebraic mean of the utility values associated with it.

Besides the above simple additive model, Edwards (1977) also proposed a simple method to assess weights for each of the criteria to reflect its relative importance to the decision. First, the criteria are ranked in order of importance and 10 points are assigned to the least important criterion. Then, the next-least-important criterion is chosen, more points are assigned to it, and so on, to reflect their relative importance. The final weights are obtained by normalizing the sum of the points to one.

However, as Edwards and Barron (1994) pointed out, the comparison of the importance of attributes is meaningless if it does not reflect the range of the utility values of the alternatives as well. They


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proposed a variant named SMARTS (SMART using Swings) that in the course of the comparison of the importance of the criteria also considers the amplitude of the utility values, i.e. the changes from the worst utility value level to the best level among the alternatives. See also Barron and Barrett (1996) for further techniques. 3.3.2 Generalized means

In a decision problem the vector x=(x1,...,xn) plays a role of aggregation taking the performance scores for every criterion with the given weight into account. This means that the vector x should fit into the rows of the decision matrix as well as possible. Mészáros and Rapcsák (1996) introducedan entropy optimization problem to find the vector x of best fit. They pointed out that the optimal solution is a positive multiple of the vector of the weighted geometric means of the columns, consequently.

3.3.3 The Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) was proposed by Saaty (1980). The basic idea of the approach is to convert subjective assessments of relative importance to a set of overall scores or weights. AHP is one of the more widely applied multiattribute decision making methods. We follow here the summary of UK DTRL (2000) on the AHP.

The methodology of AHP is based on pairwise comparisons of the following type ’How important is criterion Ci relative to criterion Cj. Questions of this type are used to establish the weights for criteria and similar questions are to be answered to assess the performance scores for alternatives on the subjective (judgmental) criteria.

Consider how to derive the weights of the criteria. Assume first that the m criteria are not arranged in a tree-structure. For each pair of criteria, the decision maker is required to respond to a pairwise comparison question asking the relative importance of the two. The responses can use the following nine-point scale expressing the intensity of the preference for one criterion versus another 1 = Equal importance or preference. 3 = Moderate importance or preference of one over another. 5 = Strong or essential importance or preference. 7 = Very strong or demonstrated importance or preference.


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9 = Extreme importance or preference. If the judgement is that criterion Cj is more important than

criterion Ci, then the reciprocal of the relevant index value is assigned. Let cij denote the value obtained by comparing criterion Ci relative to criterion Cj. Because the decision maker is assumed to be consistent in making judgements about any one pair of criteria and since all criteria will always rank equally when compared to themselves, we have cij=1/cij and cii=1.

This means that it is only necessary to make 1/2m(m - 1) comparisons to establish the full set of pairwise judgements for m criteria. The entries cij, i,j=1,.,m can be arranged in a pairwise comparison matrix C of size mxm.

The next step is to estimate the set of weights that are most consistent with the relativities expressed in the comparison matrix. Note that while there is complete consistency in the (reciprocal) judgements made about any one pair, consistency of judgments between pairs. Several of techniques were proposed for this purpose.

Saaty’s original method to compute the weights is based on matrix algebra and determines them as the elements in the eigenvector associated with the maximum eigenvalue of the matrix. The eigenvalue method has been criticized both from prioritization and consistency points of view and several other techniques have been developed. A number of other methods are based on the minimization of the distance between matrices C and W. Some of these approaches give the vector w directly or by simple computations, some other ones require the solution of numerically difficult optimization problems. One of these approaches, the logarithmic least squares method, results in a straightforward way of computing vector w: calculate the geometric mean of each row in the matrix C, calculate the sum of the geometric means, and normalize each of the geometric means by dividing by the sum just computed (Saaty and Vargas (1984)). See Gass and Rapcsák (2004) for further references on distance-minimizing methods and a new approach based on singular value decomposition.

In the practice the criteria are often arranged in a tree-structure. Then, AHP performs a series of pairwise comparisons within smaller segments of tree and then between sections at a higher level in the tree-structure.

Similarly to calculation of the weights for the criteria, AHP also uses the technique based on pairwise comparisons to determine the


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relative performance scores of the decision table for each of the alternatives on each subjective (judgemental) criterion. Now, the pairwise questions to be answered ask about the relative importance of the performances of pairs of alternatives relating the considered criterion. Responses use the same set of nine index assessments as before, and the same techniques can be used as at computing the weights of criteria.

With the weights and performance scores determined by the pairwise comparison technique above, and after further possible normalization, alternatives are evaluated using any of the decision table aggregation techniques of the MAUT methods. The so-called additive AHP uses the same weighted algebraic means as SMART, and the multiplicative AHP is essentially based on the computation of the weighted geometric means.

A number of specialists have voiced a number of concerns about the AHP, including the potential internal inconsistency and the questionable theoretical foundation of the rigid 1-9 scale, as well as the phenomenon of rank reversal possibly arising when a new alternative is introduced. On the same time, there have also been attempts to derive similar methods that retain the strengths of AHP while avoiding some of the criticisms. See Triantaphyllou, E. (2000) and Figueira et al. (2004) for state-of-art surveys and further references.

3.4 Outranking methods

The principal outranking methods assume data availability broadly similar to that required for the MAUT methods. That is, they require alternatives and criteria to be specified, and use the same data of the decision table, namely the aij.s and wi.s.

Vincke (1992) provides an introduction to the best known outranking methods; see also Figueira et al. (2004) for state-of-art surveys. Here, the two most popular families of the outranking methods, the ELECTRE and the PROMETHEE methods will be briefly outlined.

3.4.1 The ELECTRE methods

The simplest method of the ELECTRE family is ELECTRE I. The ELECTRE methodology is based on the concordance and discordance indices defined as follows. We start from the data of the


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decision matrix, and assume here that the sum of the weights of all criteria equals to 1. For an ordered pair of alternatives (Aj,Ak), the concordance index cjk is the sum of all the weights for those criteria where the performance score of Aj is least as high as that of Ak.

Clearly, the concordance index lies between 0 and 1. The computation of the discordance index djk is a bit more complicated: djk = 0 if aij>aik, i = 1,...,m, i.e. the discordance index is zero if Aj performs better than Ak on all criteria. For each criterion where Ak outperforms Aj, the ratio is calculated between the difference in performance level between Ak and Aj and the maximum difference in score on the criterion concerned between any pair of alternatives. The maximum of these ratios (which must lie between 0 and 1) is the discordance index.

A concordance threshold c* and discordance threshold d* are then defined such that 0<d*<c*<1. Then, Aj outranks Ak if the cjk>c* and djk<d*, i.e. the concordance index is above and the discordance index is below its threshold, respectively.

This outranking defines a partial ranking on the set of alternatives. Consider the set of all alternatives that outrank at least one other alternative and are themselves not outranked. This set contains the promising alternatives for this decision problem. Interactively changing the level thresholds, we also can change the size of this set.

The ELECTRE I method is used to construct a partial ranking and choose a set of promising alternatives. ELECTRE II is used for ranking the alternatives. In ELECTRE III an outranking degree is established, representing an outranking creditability between two alternatives which makes this method more sophisticated (and, of course, more complicated and difficult to interpret). See Figueira et al (2004) for more details and further members of the ELECTRE family. 3.4.2 The PROMETHEE methods

The decision table is the starting point of the PROMETHEE methodology introduced by Brans and Vincke (1985) and Brans et al. (1986). The scores aij need not necessarily be normalized or transformed into a common dimensionless scale. We only assume that, for the sake of simplicity, a higher score value means a better performance. It is also assumed that the weights wi of the criteria have been determined by an appropriate method (this is not a part of the PROMETHEE methods).

In order to take the deviations and the scales of the criteria into account, a preference function is associated to each criterion. For this


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purpose, a preference function Pi(Aj,Ak) is defined, representing the degree of the preference of alternative Aj over Ak for criterion Ci. We consider a degree in normalized form, so that 0 ≤Pi(Aj,Ak) ≤ 1 and Pi(Aj,Ak) =0 means no preference or indifference, Pi(Aj,Ak) ≈ 0 means weak preference, Pi(Aj,Ak) ≈ 1 means strong preference, and Pi(Aj,Ak) =1 means strict preference.

In most practical cases Pi(Aj,Ak) is function of the deviation ij ik d = a − a , i.e. Pi(Aj,Ak)= ( ) i ij ik p a − a , where pi is a nondecreasing function,

pi(d)=0 for d ≤ 0 , and 0 ≤ p (d ) ≤ 1 I for d > 0 . A set of six typical

preference functions was proposed by Brans and Vincke (1985) and Brans et al. (1986). The simplicity is the main advantage of these preferences functions: no more than two parameters in each case, each having a clear economical significance.

The positive outranking flow expresses how much each alternative is outranking all the others. The higher φ + (Aj), the better the alternative. φ + (Aj) represents the power of Aj, its outranking character.

The negative outranking flow expresses how much each alternative is outranked by all the others. The smaller φ − (Aj), the better the alternative. φ − (Aj) represents the weakness of Aj, its outranked character. The PROMETHEE I partial ranking

Aj is preferred to Ak when φ + (Aj) ≥φ + (Ak), φ − (Aj) ≤ φ − (Ak), and at least one of the inequalities holds as a strict inequality. Aj and Ak are indifferent when φ + (Aj)=φ + (Ak) and φ − (Aj)=φ − (Ak). Aj and Ak are incomparable otherwise.

In this partial ranking some couples of alternatives are comparable, some others are not. This information can be useful in concrete applications for decision making.

The PROMETHEE II complete partial ranking If a complete ranking of the alternatives is requested by the decision maker, avoiding any incomparabilities, the net outranking flow can be considered: φ (Aj) =φ + (Aj) -φ − (Aj). The PROMETHEE II complete ranking is then defined: Aj is preferred to Ak when φ (Aj)>φ (Ak), and Aj and Ak are indifferent when φ (Aj)=φ (Ak).


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All alternatives are now comparable, the alternative with the highest φ (Aj) can be considered as best one. Of course, a considerable part of information gets lost by taking the difference of the positive and negative outranking flows.

PROMETHEE V: Optimization under constraints

Optimization under constraints is a typical problem of operations research. The problem of finding an optimal selection of several alternatives, given a set of constraints, belongs to this field. PROMETHEE V extends PROMEHEE II to this selection problem. The objective is to maximize the total net outranking flow value of the selected alternatives meanwhile they are feasible to the constraints. Binary variables are introduced to represent whether an alternative is selected or not, and integer programming techniques are applied to solve the optimization problem.

The GAIA visual modelling method The set of alternatives can be represented by n points in the m-

dimensional space, where m is the number of criteria. As the number of criteria is usually greater than two, it is impossible to have a clear vision of these points. GAIA offers a visualization technique by projecting the points on a two-dimensional plane, where the plane is defined so that as few information as possible gets lost by the projection. The GAIA plane provides the decision maker with a powerful tool for the analysis of the differentiation power of the criteria and their conflicting aspects. Clusters of similar alternatives as well as incomparability between two alternatives are clearly represented. The projection of the vector of the weights of criteria suggests the direction, where the most promising alternatives can be found on the plane.

The methodology applied in GAIA appeared earlier in statistics as a visualization tool under the name of principal components analysis. See Rapcsák (2004) for the mathematical background of the methodology. Strengthening PROMETHEE with ideas of AHP

Some ideas of AHP can also be applied in the PROMEETHE methodology. Recently, Macharis et al. (2004) proposed to use the pairwise comparison technique of AHP to determine the weights of the criteria. Similarly, the use of the tree-structure to decompose the decision problem into smaller parts can also be beneficial.


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4. Introduction History

How far back in history should we go to discover the origins of ELECTRE methods? Some years ago B. Roy and D. Vanderpooten published an article (“The European School of MCDA: Emergence, Basic Features and Current Works”, Journal of Multi-Criteria Decision Analysis) on this very topic. This introduction is largely based on their paper, but additional material has been included to define the origins more precisely and to look more deeply into the history of ELECTRE methods. We have also benefited from an old, but nonetheless excellent, bibliography containing a lot of references collated by Y. Siskos, G. Wascher and H. Winkels . The latter only covers the period 1966-1982, but contains many valuable references.

The origins of ELECTRE methods go back to 1965 at the European consultancy company SEMA, which is still active today. At that time, a research team from SEMA worked on a concrete, multiple criteria, real-world problem regarding decisions dealing with the development of new activities in firms. For “solving” this problem a general multiple criteria method, MARSAN (Méthode d’Analyse, de Recherche, et de Sélection d’Activités Nouvelles) was built.

The analysts used a weighted-sum based technique included in the MARSAN method for the selection of the new activities. When using the method the engineers from SEMA noticed serious drawbacks in the application of such a technique. B. Roy was thus consulted and soon tried to find a new method to vercome the limitations of MARSAN. The ELECTRE method for choosing the best action(s) from a given set of actions was thus devised in 1965, and was later referred to as ELECTRE I (electre one). In that same year (July, 1965) the new multiple criteria outranking method was presented for the first time at a conference (les journées d’études sur les méthodes de calcul dans les sciences de l’homme), in Rome (Italy). Nevertheless, the original ideas of ELECTRE methods were first merely published as a research report in 1966, the notorious Note de Travail 49 de la SEMA.. Shortly after its appearance, ELECTRE I was found to be successful when applied to a vast range of fields [18], but the method did not become widely known until 1968 when it was published in RIRO, la Revue d’Informatique et de Recherche Opérationnelle [89]. This article presents a comprehensive description of ELECTRE and the foundations of the outranking approach; the reader may also consult the graph theory book


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by B. Roy [90]. The method has since evolved and given rise to an “unofficial” version, ELECTRE Iv (electre one vee). This version took into account the notion of a veto threshold. A further version known as ELECTRE IS (electre one esse) appeared subsequently (see [117]) and was used for modelling situations in which the data was imperfect (see below). This is the current version of ELECTRE methods for choice problematic.

The acronym ELECTRE stands for: ELimination Et Choix Traduisant la REalité (ELimination and Choice Expressing the REality), and was cited for commercial reasons. At the time it seemed adequate and served well to promote the new tool. Nevertheless, the developments in ELECTRE methods over the last three decades, the way in which we consider the tool today and the methodological foundations of multiple criteria decision aiding have made the meaning of the acronym unsatisfactory.

1. A short evaluation of the ELECTRE Electre method is able to classify the different alternatives of a

problem or project the best alternative to worst, based on criteria. Electre method has two main procedures: building relationships one or more senior, followed by an operating procedure.

The context in which ELECTRE method are relevant is modeling with an outranking relation, their structure, the role of criteria, and how to account for imperfect knowledge.

ELECTRE methods are relevant when facing decision situations with the following characteristics:3

1. The decision-maker (DM) wants to include in the model at least three criteria. However, aggregation procedures are more adapted in situations when decision models include more than five criteria (up to twelve or thirteen).

And, at least one of the following situations must be verified.

2. Actions are evaluated (for at least one criterion) on an ordinal scale 4 or on a weakly interval scale5. These

3 B. Roy and D. Bouyssou, Aide Multicritère á la Décision: Méthodes et Cas. Economica, Paris, 1993. 4 F. Roberts, Measurement Theory, with Applications to Decision Making, Utility and the Social Sciences, Addison-Wesley, New York, 1979. 5 J. Martel and B. Roy, Analyse de la signifiance de diverses procédures d’agrégation multicritère. Annales du LAMSADE 1, Université Paris-Dauphine, 2002.


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scales are not suitable for the comparison of differences. Hence, it is difficult and/or artificial to define a coding that makes sense in terms of preference differences of the

)()(

)()(

dgcg

bgag

jj

jj

−

− where )(xg j is the evaluation of the

action x on criterion y. 3. A strong heterogeneity related with the nature of

evaluations exists among criteria (e.g., duration, noise, distance, security, cultural sites, monuments). This makes it difficult to aggregate all the criteria in a unique and common scale.

4. Compensation of the loss on a given criterion by a gain on another one may not be acceptable for the DM. Therefore, such situations require the use of noncompensatory aggregation procedures

5. For at least one criterion the following holds true: small differences of evaluations are not significant in terms of preferences, while the accumulation of several small differences may become significant. This requires the introduction of discrimination thresholds (indifference and preference) which leads to a preference structure with a comprehensive intransitive indifference binary relation.

Preferences in ELECTRE methods are modelled by using binary

outranking relations, S, whose meaning is "at least as good as". Considering two actions a and b, four situations may occur:

• a S b and not b S a, i.e. a P b (a is strictly preferred to b).

• b S a and not a S b, i.e. b P a (b is strictly preferred to a).

• a S b and b S a, i.e. a T b (a is indifferent to b). • Not a S b and not b S a, i.e. a R b (a is incomparable to

b).

ELECTRE methods comprise two main procedures: construction of one or several outranking relation(s) followed by an exploitation procedure.


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The construction of one or several outranking relation(s) aims at comparing in a comprehensive way each pair of actions. The exploitation procedure is used to elaborate recommendations from the results obtained in the first phase. The nature of the recommendations depends on the problematic (choosing, ranking or sorting). Hence, each method is characterized by its construction and its exploitation procedures.

The relative role attached to criteria in ELECTRE methods is defined by two distinct sets of parameters: the importance coefficients and the veto thresholds. The importance coefficients in ELECTRE methods refer to intrinsic "weights". Forgiven criterion the weight, jw ,

reflects its voting power when it contributes to the majority which is in favor of an outranking. The weights do not depend neither on the ranges nor the encoding of the scales. Let us point out that these parameters can not be interpreted as substitution rates as in compensatory aggregation procedures AHP6, MACBETH7 and MAUT8

Veto thresholds express the power attributed to a given criterion to be against the assertion "a outranks b", when the difference of the evaluation between g(b) and g(a) is greater than this threshold. These thresholds can be constant along a scale or it can also vary.

The method is very simple and it should be applied only when all the criteria have been coded in numerical scales with identical ranges. In such a situation we can assert that an action "a outranks b" (that is, "a is at least as good as b") denoted by aSb, only when two conditions hold.

On the one hand, the strength of the concordant coalition must be powerful enough to support the above assertion. By strength of the concordant coalition, we mean the sum of the weights associated to the criteria forming that coalition. It can be defined by the following concordance index (assuming, for the sake of formulae simplicity, that

∑ ℑ∈ =j jw 1 where T J is the set of the indices of the criteria):

6 T. Saaty, The Analytical Hierarchy Process, McGrow Hill, New York, 1980. 7 C. Bana, E. Costa, J. Vansnick, MACBETH – An interactive path towards the construction of cardinal value functions, International Tranzactions in Operational Research, 1: 489-500, 1994. 8 R. Keeney and H. Raiffa, Decision with Multiple Objectives: Preferences and Value Tradeoffs, John Wiley & Sons, New York, 1976.


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∑≥

=)}()(:{

)(bjgajgjjwaSbc

(where )}()(:{ bjgajgj ≥ is the set of indices for all the criteria

belonging to the concordant coalition with the outranking relation a S b).

In other words, the value of the concordance index must be greater than or equal to a given concordance level, s , whose value generally falls within the range ]min1;5,0[ jj wℑ∈− , i. e. saSbc ≥)( .

On the other hand, no discordance against the assertion "a is at least as good as b" may occur. The discordance is measured by a discordance level defined as follows:

)}()({max)()}()(:{

agbgaSbd jjbjgajgj

−=≥

This level measures in some way the power of the discordant coalition, meaning that if its value surpasses a given level, v, the assertion is no longer valid. Discordant coalition exerts no power whenever vaSbd ≤)( .

Both concordance and discordance indices have to be computed for every pair of actions ),( ba in the set A, where ba ≠ .

It is easy to observe that such a computing procedure leads to a binary relation in comprehensive terms (taking into account the whole set of criteria) on the set A. Hence for each pair of actions ),( ba , only one of the following situations may occur:

• a S b and not b S a, i. e. a P b (a is strictly preferred to b).

• b S a and not a S b, i. e. b P a (b is strictly preferred to a).

• a S b and b S a, i.e. a T b (a is indifferent to b). • Not a S b and not b S a¸ i.e. a R b (a is incomparable to

b).

This preference-indifference framework with the possibility to resort to in-comparability, says nothing about how to select the best compromise action, or a subset of actions the DM will focus his attention on.


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Case 1. Sum of importance coefficients given to criteria „Pollution” and „Benefits” is 0,5

Table 1 Decision matrix POLLUTION Air

Pollution*

Ground Pollution* Powders deposits mg/Nm

Pollution of surface water *

Chlorides mg/l

Noise Pollution (sound) dB(A)

Initial Value 2 10 0,8 280 80 Existing Value

4 20 0,5 250 70

Standard Value

0,5 5 0,1 200 60

Expected Value

0,8 6 0,3 210 65

Measured Values

6 21 0,8 220 75

Kj 0,08 0,08 0,14 0,10 0,10

BENEFITS

Pro

fit

Sal

arie

s

Contribu-tions in the form of taxes,

state budget

Contributions in the form of taxes, local budget

Other benefits (meal vouchers, etc.)

0 0 0 0 0 6,355

41950 1,016 0 4600

5 70000 1,5 50000 10000 7 100000 2,05 1000000 50000 6 40000 1,1 45000 9000

0,18 0,12 0,10 0,05 0,05

Table 2 Utilities Matrix

(State of nature 1)

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10

min min min min min max max max max max A1 0,7272 0,6875 0 0 0 0 0 0 0 0 A2 0,363636 0,0625 0,428571 0,375 0,5 0,907857 0,4195 0,49561 0 0,092

A3 1 1 1 1 1 0,714286 0,7 0,731707 0,05 0,2

A4 0,945455 0,9375 0,714286 0,875 0,75 1 1 1 1 1

A5 0 0 0 0,75 0,25 0,857143 0,4 0,536585 0,045 0,18


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Table 3 Concordance Matrix (State of nature 1)

A1 A2 A3 A4 A5

A1 1 0,21 0 0 0,3

A2 0,84 1 0,18 0 0,7

A3 1 0,82 1 0,5 0,82

A4 1 1 0,5 1 1

A5 0,84 0,3 0,18 0 1

Table 4 Discordance Matrix

(State of nature 1)

A1 A2 A3 A4 A5

A1 0 0,907857 1 1 0,857143

A2 0,625 0 0,9375 1 0,375

A3 0 0,193571 0 0,95 0,142857

A4 0 0 0,285714 0 0

A5 0,727273 0,428571 1 0,955 0

Table 5 Differences Matrix

(State of nature 1)

A1 A2 A3 A4 A5

A1 1 -0,69786 -1 -1 -0,55714

A2 0,215 1 -0,7575 -1 0,325

A3 1 0,626429 1 -0,45 0,677143

A4 1 1 0,214286 1 1

A5 0,112727 -0,12857 -0,82 -0,955 1

Table 6 Preferences Matrix

(State of nature 1)

A1 A2 A3 A4 A5 Suma

A1 0 0 0 0 0 0

A2 1 0 0 0 1 2

A3 1 1 0 0 1 3

A4 1 1 1 0 1 4

A5 1 0 0 0 0 1


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Top of Preferences

4A P { }5321 ;;; AAAA

3A P { }521 ;; AAA

2A P };{ 51 AA

5A P { }1A

1A P φ (P = preference) Case 2. Sum of importance coefficients given to criteria “Pollution” =

0,7 and “Benefits” = 0,3

Table 7 Decision matrix POLLUTION

Air Pollution*

Ground Pollution*

powdersdeposits mg/Nm

Pollution of surface water

* Chlorides mg/l


Initial Value 2 10 0,8 280 80 Existing Value 4 20 0,5 250 70 Standard Value 0,5 5 0,1 200 60 Expected Value 0,8 6 0,3 210 65 Measured Values 6 21 0,8 220 75 Kj 0,26 0,24 0,05 0,06 0,09

BENEFITS

Pro

fit

Sal

arie

s

Contribu-tions in the form of taxes,

state budget

Contribu-tions in the form of taxes, local

budget


0 0 0 0 0 6,355

41950 1,016 0 4600

5 70000 1,5 50000 10000 7 100000 2,05 1000000 50000 6 40000 1,1 45000 9000

0,11 0,12 0,01 0,04 0,02


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Table 8 Utilities Matrix (State of nature 2)

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 min min min min min max max max max max

A1 0,7272 0,6875 0 0 0 0 0 0 0 0 A2 0,363636 0,0625 0,428571 0,375 0,5 0,907857 0,4195 0,49561 0 0,092 A3 1 1 1 1 1 0,714286 0,7 0,731707 0,05 0,2 A4 0,945455 0,9375 0,714286 0,875 0,75 1 1 1 1 1 A5 0 0 0 0,75 0,25 0,857143 0,4 0,536585 0,045 0,18

Table 9 Concordance Matrix (State of nature 2)

A1 A2 A3 A4 A5

A1 1 0,54 0 0 0,55

A2 0,5 1 0,11 0 0,87

A3 1 0,89 1 0,7 0,89

A4 1 1 0,3 1 1

A5 0,5 0,13 0,11 0 1

Table 10 Discordance Matrix (State of nature 2)

A1 A2 A3 A4 A5

A1 0 0,907857 1 1 0,857143

A2 0,625 0 0,9375 1 0,375

A3 0 0,193571 0 0,95 0,142857

A4 0 0 0,285714 0 0

A5 0,727273 0,428571 1 0,955 0

Table \11 Differences Matrix (State of nature 2)

A1 A2 A3 A4 A5

A1 1 -0,36786 -1 -1 -0,30714

A2 -0,125 1 -0,8275 -1 0,495

A3 1 0,696429 1 -0,25 0,747143

A4 1 1 0,014286 1 1

A5 -0,22727 -0,29857 -0,89 -0,955 1


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Table 12 Preferences Matrix (State of nature 2)

A1 A2 A3 A4 A5 Sum

A1 0 0 0 0 0 0

A2 1 0 0 0 1 2

A3 1 1 0 0 1 3

A4 1 1 1 0 1 4

A5 1 0 0 0 0 1

Top of Preferences

4A P { }5321 ;;; AAAA

3A P { }521 ;; AAA

2A P };{ 51 AA

5A P { }1A

1A P φ

Case 3. Sum of importance coefficients given to criteria „Pollution” = 0,3 and „Benefits” = 0,7

Table 13 Decision matrix

POLLUTION Air Pollution*

Ground Pollution*

powdersdeposits

mg/Nm

Pollution of surface water

* Chlorides

mg/l


Initial Value

2 10 0,8 280 80

Existing Value

4 20 0,5 250 70

Standard Value

0,5 5 0,1 200 60

Expected Value

0,8 6 0,3 210 65

Measured Values

6 21 0,8 220 75

Kj 0,11 0,12 0,01 0,04 0,02


137

BENEFITS

Pro

fit

Sal

arie

s Contribu-tions

in the form of taxes, state

budget

Contributions in the form of taxes,

local budget


0 0 0 0 0 6,355 41950 1,016 0 4600

5 70000 1,5 50000 10000 7 100000 2,05 1000000 50000 6 40000 1,1 45000 9000

0,26 0,24 0,05 0,06 0,09

Table 14 Utilities matrix

(State of nature 3)

C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 min min min min min max max max max max

A1 0,7272 0,6875 0 0 0 0 0 0 0 0 A2 0,363636 0,0625 0,428571 0,375 0,5 0,907857 0,4195 0,49561 0 0,092 A3 1 1 1 1 1 0,714286 0,7 0,731707 0,05 0,2 A4 0,945455 0,9375 0,714286 0,875 0,75 1 1 1 1 1 A5 0 0 0 0,75 0,25 0,857143 0,4 0,536585 0,045 0,18

Table 15 Concordance Matrix

(State of nature 3)

A1 A2 A3 A4 A5

A1 1 0,29 0 0 0,24

A2 0,77 1 0,26 0 0,76

A3 1 0,74 1 0,3 0,74

A4 1 1 0,7 1 1

A5 0,77 0,24 0,26 0 1


138

Table 16 Discordance Matrix

(State of nature 3)

A1 A2 A3 A4 A5

A1 0 0,907857 1 1 0,857143

A2 0,625 0 0,9375 1 0,375

A3 0 0,193571 0 0,95 0,142857

A4 0 0 0,285714 0 0

A5 0,727273 0,428571 1 0,955 0

Table 17 Differences Matrix

(State of nature 3)

A1 A2 A3 A4 A5

A1 1 -0,61786 -1 -1 -0,61714

A2 0,145 1 -0,6775 -1 0,385

A3 1 0,546429 1 -0,65 0,597143

A4 1 1 0,414286 1 1

A5 0,042727 -0,18857 -0,74 -0,955 1

Table 18 Preferences Matrix (State of nature 3)

A1 A2 A3 A4 A5 Sum

A1 0 0 0 0 0 0

A2 1 0 0 0 1 2

A3 1 1 0 0 1 3

A4 1 1 1 0 1 4

A5 1 0 0 0 0 1

Top of Preferences

4A P { }5321 ;;; AAAA

3A P { }521 ;; AAA

2A P };{ 51 AA

5A P { }1A

1A P φ


139

Results and Discussion

Although, several decades past since the birth of the first ELECTRE method, research on ELECTRE family method stills active today. Some of the recent developments are shortly described in this Section. When dealing with real-world decision problems, DMs and analysts are often facing with several sources of imperfect knowledge regarding the available data. This leads to the assignment of arbitrary values to certain “variables”. In addition, modelling activity frequently requires to choose between some technical options, introducing thus an additional source of arbitrariness to the problem.

For these reasons, analysts hesitate when assigning values to the preference parameters (weights, thresholds, categories lower and upper limits, ...), and the technical parameters (discordance and concordance indices, level, ...) of ELECTRE methods. In practice, it is frequent to define a reference system built from the assignment of central values to these two types of parameters. Then, an exploitation procedure should be applied in order to obtain outputs which are used to elaborate recommendations. But, what about the meaningfulness of such recommendations? They strongly depend on the set of central values attributed to the parameters. Should the analyst analyze the influence of a variation of each?

Parameter, considered separately, on the results? And, then enumerate those parameters which provoke a strong impact on the results when their values vary from the central positions. This is a frequent way to proceed in classical operations research methods and it is called sensitivity analysis. But, this kind of analyzes has rather a theoretical interest than a practical one.

Analysts are most often interested in building recommendations which remain acceptable for a large range of the parameters values. Such recommendations should be elaborated from what we call the robust conclusions Rather than purchase or develop an application to implement the ELECTRE method, we decided to take advantage of the flexibility of Excel and prototype a project ranking tool.

The rationale for this was that we considered that the inputs and creation of the performance matrix was very much an iterative process and could change significantly as the project developed. Also, the complete system could be thoroughly tested and proven prior to


140

committing any significant expenditure to application development. A meeting of project social actors and stakeholders was called and the ranked list was proposed as a starting point to identify the cut-off line. Each project was then quickly reviewed to ensure that it had been properly represented. Projects “below” the line were more thoroughly reviewed to ensure that an essential project was not being dropped in place of another project with more quantifiable benefits. The inputs to different projects proposals were updated and a revised ranking obtained.

As can be seen, top of preferences obtained in three cases is the same, even if the allocation of importance coefficients is different in those three states of nature. This is due to quite significant differences between the consequences of the five alternatives. In the case of the two ranked alternatives, the difference between them is made by the consequences of the economical criteria, because the differences between consequences of pollution criteria are not significant in the case of alternative “Expected Value” to “Standard Value” alternative.

References Aleskerov F. and Monjardet B., Utility Maximization, Choice and Preference, Springer Verlag, Heidelberg, 2002. Anderson David R., Sweeney Dennis J., Quantitative Methods for Business, West Publishing Company, New York, Los Angeles, 1992. Bana C., Costa E. and Vansnick J.-C., „MACBETH - An interactive path towards the construction of cardinal value functions”, International Transactions in Operational Research, 1:489-500, 1994. Bana e Costa C. A., „The use of multi-criteria decision analysis to support the search for less conflicting policy options in a multi-actor context: Case study”, Journal of Multi-Criteria Decision Analysis, 10(2): 111-125, 2001. Bardon A.F., Candeal J. C., Herden G., Induráin E., and Mehta G. B., „The non-existence of a utility function and the structure of non-representatble preference relations”. Journal of Mathematical

Economics, 37:17-38, 2002. Belton V. and Stewart T., Multiple Criteria Decision Analysis: An Integrated Approach, Kluwer Academic Publishers, Dordrecht, 2001.


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Benayoun R., Roy B., and Sussmann B., ELECTRE: Une méthode pour guider le choix en présence de points de vue multiples. Note de travail 49, SEMA-METRA International, Direction Scientifique, 1966. Buffet P., Grémy J, Marc M. and Sussmann B., „Peut-on choisir en tentant compte de critères multiples? Une méthode ELECTRE et trois applications”, Revue METRA, VI : 283-316, 1967. Dias L. and Climaco J., „On computing ELECTRE’s credibility indicesunder partial informations”, Journal of Multi-Criteria Decision Analysis, 8(2): 74-92, 1999. Dias L. and Mousseau V., „Infering ELECTRE’s credibility indices under partial information”, European Journal of Operational Research, 2004. Ionescu, Gh. Gh., Teza de doctorat „Modelarea cercetării şi dezvoltării noilor produse industriale”, GalaŃi iunie 1997. Modelul MARSAN. Modelul ELECTRE modificat. Modelul PROPLAN. Ionescu, Gh. Gh., „Regarding some consideration and improvements of the ELECTRE Method” in Business Research Yearbook. Global Business Perspectives, Volume II 1995, Ed. Abbass F. Alkhafaji. Publication of the Academy of Business Disciplines. Ionescu, Gh. Gh., Cazan, E., Negruşa, A.L., Modelarea şi optimizarea deciziilor manageriale; Ed. Dacia Cluj-Napoca 1999. Maystre L., Pictet J. and Simos J., Les Méthodes Multicritères ELECTRE, Presses Polytrchniques et Universitaires Romandes, Lausanne, 1994. Mousseau V. and R. Slowinski, „Inffering an ELECTRE TRI model from assignment examples”, Journal of Global Optimization, 12(2): 157-174, 1998. Mousseau V., Fgueira J. and J. Naux, „Using assignment examples to infer weights for ELECTRE TRI method: Some experimental results”, European Journal of Operational Research, 130(2): 263-275, 2001. Mousseau V. and Dias L., „Valued outranking relation in ELECTRE providing manageable disaggregation procedures”, European Journal of Operational Research, in press, 2004. Roy B., „Classement et choix en présence de points de vue multiples (la méthode ELECTRE)”, RIRO, 8 : 57-75, 1968. Roy B. and Skalka J., ELECTRE IS: Aspects méthodologiques et guide d’utilisation, Document du LAMSADE 30, Université Paris Dauphine, 1984.


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Vizental M., „A comparative overview of the ELECTRE Methods”, Sesiunea de comunicări doctorale în management „Managementul organizaŃiilor din România” – Prima ediŃie, Timişoara 02-03 iulie 2010, SecŃiunea Management şi Leadership.

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