Environment factors of energy companies and their effect on value: analysis model and applied method/Aplinikos veiksniu poveiko energetikos sektoriaus imoniu vertei nustatymas: analizes modelis ir metodas.

Sliogeriene, Jurate ; Kaklauskas, Arturas ; Zavadskas, Edmundas Kazimieras 等

1. Introduction

Economic infrastructure companies, electricity companies among them, share a feature: they perform an assigned specific function in a specific territory using sophisticated, unique and expensive infrastructure. Real property of such companies makes the biggest share in the corporate capital structure and is created through a long-term operating process. It is difficult, and often inexpedient, to compete with economic infrastructure companies because normally one infrastructure company of a respective branch operates in a certain territory, which may be a city, a district, a region or another administrative division, and satisfies the needs of the economy and residents of such territory. Management of infrastructure companies and of their operating costs must include management of the structure and value of fixed assets. Although economic infrastructure companies are usually a part of the state-controlled public sector, improved practice of their management may make them effective competitors of private companies.

It is difficult to monitor the property value in infrastructure companies. Special-purpose property (e.g. pipelines, electric transmission and distribution lines, transmission substations, pumping stations, etc.) is rarely sold as individual property items and generally is not displayed in market; thus a database of such property sales is not available, though such database would facilitate measurement of preliminary property value. Therefore, a separate property valuation procedure is required in order to learn the value of special-purpose property controlled by a company. Practical valuation of special-purpose property usually depends on: the professional qualities of a specific company or appraiser involved in property valuation; the selected assumptions; and possibilities to learn about and compare practices of such property valuation in various countries. Regular property valuation methods do not account for the trends of changing value, and economic methods based on subjective assumptions of appraisers fail to ensure objective valuation. However, property valuation in infrastructure companies, both based on traditional property valuation methods and on contemporary methods involving mathematical statistics or multiple criteria analysis, must include analysis of the specific features and environment of infrastructure companies, as these factors have significant impact on the activities of such companies.

Such scientists as Bradley, Fulmer, Rosen, Lane, Navickas, who are considered to be the originators of studies in this area, analyse specific features of activities of infrastructure companies. The scientists have defined infrastructure as a set of general conditions, which may facilitate development of private companies within the main economic branches and are designed to satisfy the needs of the entire society. Infrastructure is specified as a set of economic resources, the functioning of which determines the level of active economic practices (Bradley et al. 2004). There are two main branches of infrastructure: economic and social. Economic infrastructure covers all branches which provide for activities within the economic process (Navickas, Cibinskiene 2004). Activities of infrastructure companies are related to "providing" economic branches, product transfer and storage processes, as well as collection, processing and information transfer processes. Activities of infrastructure companies are inseparable from safeguarding of public interests. Jan Eric Lane analyses the principles of operation and management of infrastructure companies, as well as the influence of state control and regulation on infrastructure companies in order to safeguard public interest. The author specified that two parameters determine the efficiency of companies which safeguard public interest: the amount of resources consumed in production of one product item and the degree at which an organisation achieves its goals (Lane 1995). Resource amount management means management of their value as well.

Recently, the impact of infrastructure companies, electricity companies among them, on environment came into spotligh, when the significance of environmental factors shaping the quality of life was assessed. However, usually only the amount of pollution emissions and implementation efficiency of environmental programmes are considered in analysis of the effect on environment of energy sector objects. Various countries take up studies in order to learn about the influence of the location of energy sector objects on the value of neighbouring property. For example, analysis of the impact of the wind park in Great Britain on the price of nearby residential houses has shown that the traditional value criteria, such as the type of ownership and sales timing, are the main factors influencing the price level (Sims et al. 2008). In contrast, such objects as high voltage electricity transfer lines, thermal power plants, sewage management companies or highways make negative impact on the life quality of people in the neighbourhood and the level of property prices (Des Rosiers 2002). When solving a property valuation task, it is equally important to measure both economic parameters and perspectives of company's activities and the environmental aspects, to determine the factors which affect the value, as well as the impact of infrastructure objects themselves on environment (Rosen 2002). In future, solutions of property valuation problems will focus on the importance of assessment of environment factors and the environmental aspect.

The pollution emissions of economic infrastructure objects attributed to electricity, heating, gas supply, utility, communication and transport infrastructure, the influence of electromagnetic field generated by electricity transmission lines, waves of communication objects, transmission of flammable and potentially dangerous substances through main pipelines and other activities affect environment at various degrees. Besides, the location of unattractive and environmentally-aggressive special-purpose objects makes negative impact on activities of nearby residents (e.g. quality of agricultural products), on their accumulated property, on its attractiveness and on price levels (Gwartney et al. 1997). Property which is close to sewage treatment plants, high voltage substations, thermal power plants or waste combustion companies will have lower value compared to the same type of property neighbouring with objects which do not pollute environment and located in a place with well-developed infrastructure of social services. Therefore, proper environment indicators, which have the biggest impact on activities of the analysed object, must be selected and their weights assessed for property valuation in infrastructure companies, energy companies among them. Then valuation methods, which allow to integrate values of the effect of environment factors into the value of the analysed property, can be selected and applied.

Chapter 2 of this paper presents the Analysis Model for Environment Factors, which affect electricity companies, developed by the authors; its main elements are based on the analysis and simulation of macro, meso and microlevel variable factors affecting the efficiency. Also, chapter describes the model's elements characterising the environment of the analysed sector. Chapter 3 dwells on the suggested multiple criteria designing methods: the expert method, the multiple criteria complex proportional evaluation method and the multiple criteria methods for the measurement of the utility degree and market value of real estate. Chapter 4 handles a practical task: the utility degree and market value of the selected electricity companies was measured using the Analysis Model for Environment Factors and multiple criteria analysis methods.

2. Integrated analysis model for environment factors which affect energy companies

Business value is typically multidimensional and indefinite; thus, it is expedient to use several methods in the valuation and to make several interrelated estimates of value aspects. Although scientific and methodological literature suggests various valuation methods, there is a lack of valuation methodology which would regulate valuation of special-purpose property in large economic infrastructure companies and could be used as a basis for integrated assessment of environment factors affecting companies or their property value. Numerous valuation methods currently suggested for practical application can be divided into three main groups: property, market and income valuation methods. However, these methods do not facilitate integrated assessment of macro, meso and microfactors affecting property values, as well as of goals and influence of stakeholder groups. The method for the valuation of corporate property or business must be selected considering:

-- the purpose of valuation;

-- the business field and property group to which belongs the valuated object;

-- which property value is relevant;

-- which value is the best to express property value in open market;

-- which environment factors have the biggest impact on changing value.

In order to find the instruments suitable to measure the factors which affect property value of energy companies and which can best reflect the impact on value and to foresee trends of value changes, we suggest an Analysis Model for Environment Factors in this sector; components of the model integrate the analysis of a company's condition and the value-affecting variable factors of macro, meso and microenvironment. The theoretical Analysis Model for Environment Factors affecting company's value is provided below in Fig. 1.

The analysis of factors affecting a company's value can be divided into four main areas:

1. Analysis of a company's condition within the analysed period including internal processes of the company's financial state, property structure, technical condition, etc.;

2. Comparative analysis of the same type of corporate operating indicators and environment factors;

3. Analysis of macro, meso and microlevel environment factors affecting operating efficiency;

4. Analysis of the impact of groups which affect decisions.

[FIGURE 1 OMITTED]

The above model has already been applied in the development of Lithuanian construction industry (Zavadskas, Kaklauskas 2008), in sustainable development of Vilnius (Zavadskas et al. 2007), in housing credit access (Zavadskas et al. 2004) and in facilities management (Lepkova et al. 2008).

2.1. Analysis of a company's condition within the analysed period First, considering the valuation task, an analysis of a company's financial state, indicators of financial activities and property structure is performed. Corporate operating efficiency is defined by the management of cash flows, the balance of income-to-cost ratio, management of material resources, ability to achieve goals, efficient project management and other types of internal information which may affect corporate value. An important part of this analysis is the analysis of property structure, because property, which consists of special-purpose infrastructure, is the decisive element which is the basis for activities in energy sector. The main features of such property are its complexity and specific nature. Poorly developed infrastructure seriously limits possibilities to offer services and causes system malfunctions, growing demand for production and consumption cause backlogs and a company fails to use the potential granted by the market. In electricity sector, infrastructure and buildings with equipment, which belong to power plants, comprise up to 90% of a company's property; electricity transfer lines and the infrastructure of distributions lines comprise up to 80% of corporate fixed assets. Besides, repair and maintenance of property account for a large lump of operating costs in this sector. Issues related to facility and infrastructure management, investments into infrastructure development, modernisation and upgrade of the available infrastructure using state-of-the-art technology make up the main part of processes of corporate management in energy sector. When electricity companies are being divided and restructured, when separate types of activities undergo the process of privatisation or investments are planned, separate infrastructure items or property items are the objects of valuation, and their value depends on the environment factors which affect the value of the entire property. The analysis of a company's condition within the analysed period, as well as the analysis of its cash flows, property and internal processes, is a basis to come up with preliminary conclusions on the company's value.

2.2. Comparative analysis of the same type of corporate operating indicators and environment factors

To validate preliminary conclusions and to make them more reliable, an analysis of comparative examples is made. The analysis of countries with similar economic levels and companies operating within the same economic sector guarantees more objective results. Historical aspects of the sector's development are also considered. Lithuanian electricity companies or a group of companies can be compared to electricity companies of Eastern Europe (Czech Republic, Poland, Slovakia, Hungary), the Baltic States (Latvia, Estonia) or the Scandinavian Countries (Finland, Sweden). The results of the comparative analysis and the accumulated materials help to determine the development trends of the analysed sector: general economic trends at national or regional level and trends within the same type of sectors in the selected countries are compared, differences with Lithuania are specified.

2.3. Analysis of environment factors affecting corporate operating efficiency Using expert methods, the next phase determines macro, meso and microlevel factors, as well as the systems and subsystems of defining indicators, which provide a thorough description of activities of the sector in which the company operates. The following structural elements of the developed model make the biggest impact on its effectiveness and efficiency:

-- macro, meso and microenvironment;

-- groups taking part in the decision-making process.

Macroenvironment Factors

Macrolevel factors define the level of national or industrial efficiency. Besides, macrolevel factors affect the development level of separate industrial branches. The efficiency of electricity companies significantly depends on the integrated effect of macrolevel variable factors, such as national economic, political and cultural development level, legal acts regulating activities, market, tax system, possibilities and conditions within the loan market, inflation, possibilities to acquire resources, etc. The efficiency level of a branch changes depending on the integrated effect of macrolevel factors: the need for energy resources decreases or increases.

PEST analysis (Political-Legal, Economic, Socio-Cultural and Technological Forces) is the most popular analytic technique in studies of macroenvironment of electricity companies, as well as companies of other industrial branches. This analysis covers four aspects of macroenvironment: political and legal, economic, socio-cultural and technological. PEST analysis applies quantitative (extrapolation, mathematical modelling, etc.) and qualitative (scenarios, Delphi, etc.) forecasting methods to analyse the environment. The analysis of macroenvironment must include a thorough analysis of political-legal environment, because activities of energy companies usually obey strict legal regulation. Their activities are regulated by EU and national legal acts. Recently, EU members started harmonisation of these legal acts and their transfer into national legal bases. This process simplifies the analysis of legal environment.

Expert assessment of macroenvironment criteria revealed that EU regulation of activities, which attempts to create a competitive market of electricity supply and distribution, as well as technological changes and standardisation of environmental requirements are the most significant criteria affecting activities of energy sector. Whereas activities within the energy sector are relevant to all aspects of public life, the impact of public opinion on activities was specified as a significant criterion (see the research results in Chapter 5).

Mesoenvironment Factors

The analysis of mesolevel environment is oriented towards the goals of a specific economic sector, its role in national economy and the branch, features which shape the type of activities, profit, processes within a specific branch, impact of the processes on environment, fulfilment of the sector's social role, documents regulating activities and relations with state institutions. It is an intermediate level between microeconomics and macroeconomics.

In order to make a consistent analysis of mesoenvironment, the relation between the environment of the analysed economic object and economy must be examined. Besides, the specific environment, in which the analysed company operates, must be assessed. The analysis of this environment is based on the analysis of such factors as institutions involved in legislation (legal and normative acts), supervision and control at various levels. There is a direct relation between the decisions of institutions together with their legislative processes (legal acts which regulate corporate activities) and corporate plans and decisions. Vasiliauskas applied Porter's National Diamond to present the specific features of the interaction between companies and the national economy management, thus pointing out the relation between macroenvironment factors and specific environment of institutions (Vasiliauskas 2005). Indicators which assess the ability of a specific analysed object to achieve economic goals when it solves environmental issues and implements resource-saving manufacturing measures and technologies, as well as renewable energy sources, are significant in the analysis of mesolevel factors. Educational background of society, as well as active contribution to the solution of quality issues related to residential and work environment, also makes impact. This expands the limits of macro- and mesoenvironment and the influence of these factors on operating efficiency of energy companies. It is at the mesolevel that the environmental dimension and the external effect (the effect of by-products and pollution on the environment) of activities are analysed in infrastructure companies within the energy sector. The expert study of the influence of mesoenvironment factors of energy companies has shown that respondents from various social groups consider profitability and introduction of environmentfriendly technologies as the most significant mesoenvironment criteria in activities. It is important to note that the criterion of corporate social responsibility is also considered rather significant (see Chapter 5).

Environmental Factors

Making the analysis of activities within the electricity sector, it is worthwhile to make a more thorough assessment of environmental factors. Companies within this sector make a considerable impact on the environment. Organic fuel, which is of limited quantities, is widely used in the process of energy production. Environment is polluted by S[O.sub.2], C[O.sub.2], N[O.sub.x] and other types of particulate matter, which are a by-product of the process of energy production and can affect soil, water, air and biological cycle and generate huge amounts of hard waste (Norvaisa, Galinis 2004). Despite high economic efficiency parameters, nuclear energy includes a complex and expensive burying of radioactive waste accumulated during the energy production cycle. Even electricity transfer through open high voltage lines generates electromagnetic fields, the effect of which is assessed, and legal acts regulate the conditions for operation of such objects. Therefore, cleaner production in the electricity sector is a very effective and economically efficient course of activities.

The Sixth Environment Action Programme of the European Community sets the environmental goals and priorities, which are a part of the EU Sustainable Development Strategy. The programme also foresees measures to achieve these goals. For many years already, EU states apply environmental measures based on market factors, such as environmental taxes, in order to increase the market share of products, processes and services, which are more acceptable in terms of environment protection. Such taxes encourage companies to allocate more funds to research and to invest into technologies less damaging to environment or requiring fewer resources (Staniskis, Stasiskiene 2006).

In Lithuania, the analysis of environment factors yet rarely includes assessment of external environment pollution costs. Although Lithuanian power plants pay taxes for pollution emissions into atmosphere, these taxes are, however, rather small compared to the external costs per one ton of pollution emitted into the atmosphere. Increased pollution taxes would affect the cost structure of energy companies, especially in 2010 and later, when Lithuanians will no longer have the source of cheap and rather clean energy, i.e. Ignalina Nuclear Power Plant. Therefore, the analysis of corporate activities must also consider increasingly strict environmental requirements and the foreseen increase of pollution taxes.

Microlevel Factors

Microenvironment factors are related to a specific firm or company and affect its ability to achieve its goals. These factors embrace all things related to customer value delivery: activities of the company itself, suppliers (from energy sources to various support services), companies within the supply and distribution chain, competitors, consumers and society. These factors depend on macro and mesolevel factors.

Energy sector must continuously keep high levels of infrastructure maintenance, must modernise and develop objects, must implement innovative technologies and management processes. The efficiency of the sector's development and implementation of investment projects is affected by various microlevel factors, such as: land prices; extended procedures of territorial planning and preparation of special and detailed plans; efficiency level of the process related to the supply of technologies, mechanisms and equipment for reconstruction and modernisation; funding conditions of development projects; etc. During the survey, respondents also stressed the importance of the experience of top managers and readiness of personnel to apply innovations.

2.4. Analysis of groups affecting decisions

The analysis of environment factors cannot be thorough until stakeholder groups, which affect activities and decisions, are considered in assessment of the specific environment of energy sector. Such scientists compiled a list of questions which help to identify the main stakeholder groups, the type of their influence, their level, their expectations and requirements, as well as possible outcomes (Arimaviciute 2005). The author suggest distinguishing the following types of stakeholder groups based on the results of the analysis and assessment:

-- potentially problematic;

-- hostile;

-- rather insignificant;

-- supporting.

The analysis and the obtained results help to assess the requirements and expectations of various groups, to evaluate them and to search for the ways to affect hostile groups or to help and strengthen the supporters (Arimaviciute 2005). In the energy sector, the same stakeholder group may represent various interests depending on the type of company's activities. For example, residents usually support companies which use renewable resources but are against construction of wind parks in the neighbourhood of their property. The suppliers of raw materials are interested in the development of the thermal energy sector and challenge the development of nuclear energy.

Interrelations of stakeholder groups are shown in Fig. 2.

The activities within the energy sector are controlled and coordinated by the State and various EU institutions. Various institutional participants--starting with international alliances, association committees and ending with trade unions--have a direct influence on the operation of the sector's companies. The following parties have vested interests in activities of the energy sector: suppliers of resources and raw materials which affect energy prices; manufacturers of devices and equipment; organisations offering designing, construction and other services.

Consumers are also important members of the energy sector. They may be industrial companies and household consumers. Although lately energy consumption was increasing in our country, growing prices of raw materials, as well as electricity production, distribution and supply, make various groups observe the processes within the energy sector and participate in management bodies of energy companies. Natural monopolies, which dominate Lithuanian electricity sector, basically eliminate competitive environment and the consumer's right to choose. Active involvement of stakeholder groups and political organisations affects the process of market liberalisation.

3. Measurement of the utility degree and market value using multiple criteria analysis methods

Multiple criteria decision making methods have been applied to a variety of problems, such as maintenance outsourcing (Almeida 2005), construction and real estate (Kaklauskas et al. 2005, 2007a, b; Zavadskas et al. 2008a), maintenance strategy (Almeida, Bohoris 1996), water supply management (Morais, Almeida 2007), project risk assessment (Zeng et al. 2007), multi-criteria risk analysis (Brito, Almeida 2008), service outsourcing contracts (Almeida 2007) and construction bidding (Seydel, Olson 2001).

[FIGURE 2 OMITTED]

The efficiency must be analysed within the limits determined by micro, meso and macrolevel factors in order to describe the operating efficiency of an energy sector company. These factors constantly change. Changes of these factors also mean changes in the efficiency degree of the analysed branch. Having assessed the impact of macro, meso and microlevel factors and stakeholder groups, it is possible to determine the influence of the factors on corporate operating processes and on the value. The analysis must include formulation of possible variants of organisational or corporate strategy in the analysed sector; these variants must be evaluated on the basis of multiple criteria analysis methods and the most efficient variants must be selected. Organisations or companies cannot adjust or change macro-, meso- or microlevel variables, but can understand their effect, assess them, forecast possible changes and mitigate risks in the implementation of various projects (Kozlinski, Guseva 2006).

In order to process the information about the effect of environment factors and to determine their impact on value, it is expedient to use contemporary multiple criteria analysis methods, that allow to analyse sufficient amount of quantitative and qualitative indicators which define objects, as well as to determine the utility degree and market value of objects. Based on multiple criteria analysis methods, a company or separate property items are appraised considering indicators which describe the analysed object and affect its value; they are market conjuncture, quantitative (number of property items, territorial coverage, length and amount of engineering infrastructure objects), qualitative (condition, modernisation, degree of technological novelty, environment protection, reliability, etc.), political-legal (laws, norms, regulations, limitations, restrictions) and other indicators.

Lithuanian scientists Zavadskas and Kaklauskas suggested the following multiple criteria methods for the comparison of alternative real estate items, for the measurement of the utility degree and for the measurement of the market value (Zavadskas et al. 2008a, b, 2001; Kaklauskas et al. 2006, 2007a, b; Banaitiene et al. 2008):

-- setting of weights of complex indicators considering their qualitative and quantitative characteristics;

-- multiple criteria complex proportional evaluation method;

-- multiple criteria method for the utility degree and market value measurement of real estate items.

The developed Analysis Model for Environment Factors helps to determine the weights of operating indicators and environment effect indicators of the analysed objects. The environment of the analysed electricity sector, as well as energy sector objects, has its peculiar features, is affected by various market conjuncture conditions and is influenced by stakeholder groups with confronting interests. These features impede comparison of objects within the electricity sector. However, using the complex analysis method, it is possible to measure the utility degree of objects and to determine objective market value for separate objects of electricity sector.

The complex analysis method is realised in the following main stages:

1. Measurement and description of qualitative and quantitative criteria which determine activities of a property object/set;

2. Development of an integrated database based on the obtained description of analysed objects;

3. Use of multiple criteria analysis methods in order to measure the utility degree and market value of the obtained alternatives.

Based on the obtained quantitative and conceptual description of objects, an integrated database is developed, which provides comprehensive descriptions of internal and external factors affecting the value of the analysed objects and facilitates their multi-variant designing and multiple criteria analysis.

3.1. Multiple criteria complex proportional evaluation method and method for measurement of the utility degree and market value of objects

This method assumes direct and proportional dependence of the significance and priority of the investigated versions on a system of criteria adequately describing the alternatives and on values and significances of the criteria. The system of criteria is determined and the values and initial significances of criteria are calculated by experts. All this information can be corrected by interested parties (customers, users, etc.) taking into consideration their pursued goals and existing capabilities. Hence, the assessment results of alternatives fully reflect the initial data jointly submitted by experts and interested parties.

The determination of the significance and priority of alternatives is carried out in four stages.

Stage 1. The weighted normalized decision-making matrix D is formed. The purpose of this stage is to receive dimensionless weighted values from the comparative indexes. When the dimensionless values of the indexes are known, all criteria, originally having different dimensions, can be compared. The following formula is used for this purpose:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (1)

where [x.sub.ij] is the value of the i-th criterion in the j-th alternative of a solution; m--the number of criteria; n--the number of the alternatives compared; [q.sub.i]--significance of i-th criterion. The sum of dimensionless weighted index values dij of each criterion [x.sub.i] is always equal to the significance [q.sub.i] of this criterion:

In other words, the value of significance [q.sub.i] of the investigated criterion is proportionally distributed among all alternative versions aj according to their values [x.sub.ij].

Stage 2. The sums of weighted normalized indexes describing the j-th version are calculated. The versions are described by minimizing indexes [S.sub.-j] and maximizing indexes [S.sub.+j].

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (2)

The lower value of minimizing indexes is better. The greater value of maximizing indexes is better. The sums are calculated according to the formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (3)

In this case, the values [S.sub.+j] (the greater is this value (project 'pluses'), the more satisfied the interested parties are) and [S.sub.-j] (the lower is this value (project 'minuses'), the better is the goal attainment by the interested parties) express the degree of goals attained by the interested parties in each alternative project. In any case the sums of 'pluses' [S.sub.+j] and 'minuses' [S.sub.-j] of all alternative projects are always respectively equal to all sums of the significances of maximizing and minimizing criteria:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (4)

In this way, the calculations made may be additionally checked.

Stage 3. The significance (efficiency) of comparative versions is determined on the basis of describing positive projects ('pluses') and negative projects ('minuses') characteristics. Relative significance [Q.sub.j] of each project [a.sub.j] is found according to the formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (5)

Stage 4. Priority determination of projects. The greater is the [Q.sub.j], the higher is the efficiency (priority) of the project.

The analysis of the method presented makes it possible to state that it may be easily applied to evaluating the projects and selecting most efficient of them, being fully aware of a physical meaning of the process. Moreover, it allowed to formulate a reduced criterion [Q.sub.j] which is directly proportional to the relative effect of the compared criteria values [x.sub.ij] and significances [q.sub.i] on the end result. Calculation of the weighted normalized decision matrix are presented in Table 1.

3.2. A method of defining the utility and market value of property

Significance [Q.sub.j] of property [a.sub.j] indicates satisfaction degree of demands and goals pursued by the interested parties--the greater is the [Q.sub.j], the higher is the efficiency of the property. In this case, the significance [Q.sub.max] of the most rational property will always be the highest. The significances of the remaining property are lower as compared to the most rational one. This means that total demands and goals of interested parties will be satisfied to a smaller extent than it would be in the case of the best property.

The degree of property utility is directly associated with quantitative and conceptual information related to it. If one property is characterized by the best comfortability, aesthetics, price indices, while the other shows better maintenance and facilities management characteristics, both having obtained the same significance values as a result of multiple criteria evaluation, this means that their utility degree is also the same. With the increase (decrease) of the significance of the property analyzed, its degree of utility also increases (decreases). The degree of property utility is determined by comparing the property analysed with the most efficient property. In this case, all the utility degree values related to the property analyzed will be ranged from 0% to 100%. This will facilitate visual assessment of property efficiency.

The degrees of utility of the property considered as well as the market value of a property being valuated are determined in seven stages.

Stage 1. The formula used for the calculation of property [a.sub.j] utility degree [N.sub.j] is given below:

[N.sub.j] = ([Q.sub.j] : [Q.sub.max]) * 100% , (6)

here [Q.sub.j] and [Q.sub.max] are the significances of the property obtained from the equation (5).

The degree of utility [N.sub.j] of property [a.sub.j] indicates the level of satisfying the needs of the parties interested in the property. The more goals are achieved and the more important they are, the higher is the degree of the property utility. Since clients are mostly interested in how much more efficient particular property is than the others (which ones can better satisfy their needs), then it is more advisable to use the concept of property utility rather than significance when choosing the most efficient solution.

The degree of property utility reflects the extent to which the goals pursued by the interested parties are attained. Therefore, it may be used as a basis for determining property market value. The more objectives are attained and the more significant they are, the higher will be the property degree of utility and its market value.

Thus, having determined in such a way the ratio of degree of utility and market value of property, one can see what complex effect can be obtained by investing money into the property. There is a complete clarity where it pays better to invest money and what is the efficiency degree of the investment.

Stage 2. The efficiency degree [E.sub.ji] of money invested into property [a.sub.j] is calculated. It shows by how many percent it is better (worse) to invest money into property [a.sub.j] compared with property [a.sub.i]. [E.sub.ji] is obtained by comparing the degrees of utility of the property considered:

[E.sub.ji] = [N.sub.j]--[N.sub.i]. (7)

The received results are presented as a matrix clearly showing utility differences of the property (see Table 2).

Stage 3. The average deviation [k.sub.j] of the utility degree [N.sub.j] of the property [a.sub.j] from the same index of other property (n--1) is being calculated.

[k.sub.j] = [n.summation over (i=1)] [E.sub.ji]: (n - 1). (8)

Stage 4. The development of a grouped decision making matrix for property multiple criteria analysis. The market value of a property being valuated is calculated according to a block-diagram presented in Fig. 3.

At the beginning, a grouped decision making matrix for property multiple criteria analysis is developed (see Table 3), the first criterion of which is based on the actual purchasing/selling prices of the property compared and the value of a property being valuated. The initial value of property being valuated is obtained from the following equation:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (9)

In this matrix, property a1 to be valuated should be assigned the market value ([x.sub.11-R]). Other comparison standard property ([a.sub.2]--[a.sub.n]) were sold, their purchasing/selling prices ([x.sub.12]--[x.sub.1n]) known. All the values and significances of the criteria related to other property are also known (see Table 3).

The problem may be stated as follows: what market value [x11.sub.-R] of valuated property a1 will make it equally competitive on the market with comparison standard property ([a.sub.2]--[a.sub.n])? This may be determined if a complex analysis of the benefits and drawbacks of the property is made.

[FIGURE 3 OMITTED]

Using a grouped decision making matrix (see Table 3) and the equations 1-9 the calculations are made.

Stage 5. The corrected value [x.sub.11-p] of property to be valuated a1 is calculated:

[x.sub.11-p] = x11 * (1 + [k.sub.1] : 100) (10)

Stage 6. It is determined whether the corrected value [x.sub.11-R] of property being valuated a1 had been calculated accurately enough:

[absolute value of [k.sub.1]] < s, (11)

where s is the accuracy, %, to be achieved in calculating the market value [x.sub.11-p] of a property a1. For example, given s = 0,5%, the number of approximations in calculation will be lower than at s = 0,1%.

Stage 7. The market value [x.sub.11-R] of property [a.sub.1] to be valuated is determined. If inequality 2.20 is satisfied the market value of property [a.sub.1] may be found as follows:

[x.sub.11-R] = [x.sub.11-p]. (12)

If inequality 11 is not satisfied, this means that the value of property being valuated had not been calculated accurately enough and the approximation cycle should be repeated. In this case, the corrected value [x.sub.11] = [x.sub.11-p] of property being valuated is substituted into a grouped decision making matrix of property multiple criteria analysis and the calculations according to the formulae 1-9 should be repeated until the inequation 11 is satisfied.

Solving the problem of determining the market value [x.sub.11-R] of a property [a.sub.1] being valuated, which would make it equally competitive on the market compared with the property ([a.sub.2]-[a.sub.n] ) already sold, a particular method of defining the utility degree and market value of property was suggested. This was based on a complex analysis of all the benefits and drawbacks of the property considered.

According to this method the property utility degree and the market value of property being estimated are directly proportional to the system of the criteria adequately describing them and the values as well as significances of these criteria.

The complex proportional valuation method is used in the valuation of economic infrastructure energy companies to determine the priority of objects selected for analysis, as well as their utility degree, which directly depends on the system of criteria defining the selected objects and on the value and weight of these criteria. The system of criteria, which define objects, is based on expert evaluation.

4. Measurement of the utility degree and market value of energy objects using multiple criteria analysis methods

Four objects of energy sector were selected for the practical task of multiple criteria analysis; they represent traditional and alternative types of energy production: Kruonis Pumped-storage Hydroelectric Power Plant, Kaunas Hydroelectric Power Plant, Lithuanian Power Plant and the Experimental Geothermal Power Plant.

Kruonis Pumped-storage Hydroelectric Power Plant (Fig. 4) is an engineering hydrotechnical complex consisting of two water storages (the upper and the lower reservoir), four connecting pipelines, ditches, hydro-aggregates, as well as hydroelectric technical facilities (embankments, dikes, platforms) and equipments. The power plant was launched in full power in 1998. Whereas Kruonis HAE ensures energy balance in the common energy system and only a small part of the produced electricity is sold at the electricity auction, its rated potential is underused.

[FIGURE 4 OMITTED]

Kaunas Hydroelectric Power Plant, which was constructed and launched in 1960, is the biggest power plant that uses renewable resources in Lithuania (Fig. 5). The facilities of the hydroelectric power plant include auxiliary structures of the power plant and hydrotechnical buildings: dam, embankments and dikes. The machinery plant located in the dam contains hydrotechnical equipment, turbines and generators. This object is especially attractive in economic and environmental terms. The power plant produces over 80% of our national energy based on renewable resources. However, the amount of produced electricity depends on the seasonal amounts of water resources.

[FIGURE 5 OMITTED]

[FIGURE 6 OMITTED]

Lithuanian Power Plant is the largest national thermal power plant (Fig. 6). The facilities of the power plant include the main building, which contains the energy equipment, hydrotechnical buildings, as well as auxiliary buildings and structures. The auxiliary buildings host the chemical water treatment plant, the electrolysis plant, the compressor room, laboratories, the physical plant, as well as administrative and household premises. Three chimneys (one of 150 metres and the other two of 250 metres) of the power plant are also important structures. They ensure pull and dissipate emitted gasses. The power plant mainly runs on boiler oil and natural gas. When Ignalina Nuclear Power Plant will be closed in 2010, this power plant will be the main electricity producer and supplier in Lithuania.

[FIGURE 7 OMITTED]

The geothermal Power Plant was constructed in 2004 (Fig. 7) seeking to continue industrial geothermal research, as well as to develop technologies for tapping of underground resources and make integrated use of them in economic activities. Facilities of the company include: the building of Klaipeda geothermal power plant used for activities and the first geothermal bores made in Lithuania, in 1989. Geothermal bores reach geothermal water of a temperature of 40[degrees]C, which is then heated up to 70[degrees]C and supplied to centralised urban networks. Operating efficiency of the power plant depends on the price of natural gas and on fixed prices for procurement of the produced heat. Despite complicated operating conditions, activities of the geothermal power plant are considered very promising and its development is actively promoted.

This research has an aim to measure the utility level and adjusted market value of Lithuanian energy companies, which use traditional and alternative energy resources, applying the Decision Support System for Measurement of Effect of Environment Factors on Value of Energy Companies developed by the authors. It is difficult to appraise objects, which are basically different although operate in the same sector. However, multiple criteria analysis methods are a good choice in order to analyse and assess objects with rather different parameters. Quantitative data of the analysed energy objects are shown in Table 4.

4.1. Creation of the criteria system

The research is based on the results obtained through use of the expert method of criteria assessment. In prepared questionnaires, expert groups assessed the impact of environment factors on activities of the selected energy sector objects. Objective results were ensured by forming expert groups from representatives of different social groups: specialists of energy companies, managers, CEOs; two expert groups included residents who own property close to energy objects. A total of six expert groups took part in the survey. Questionnaires for the expert evaluation were prepared in such way as to achieve maximum assessment of indicators within components of the Analysis Model for Environment Factors. Qualitative criteria which define environment factors of the analysed objects and quantitative criteria which define the actual data were selected for measurement of the utility degree and market value of the objects. The experts used a table to set the values of macro, meso and microenvironment criteria which affect the value of the four specified objects. Weights of the criteria are assessed using conditional measurement units: points between 1 and 10 in this particular case. The experts gave more points to these criteria which they consider to have bigger weight, to be more "influential", and make bigger impact on the end result of valuation. The utility level and market value of the selected objects were measured based on qualitative criteria assessed by the experts and quantitative criteria describing the objects.

First, experts helped to set priorities of all determined criteria, i.e. the criteria were ranked on a scale between 1 and 29. Reliability of the research was verified by calculating the degree of opinion coincidence of expert groups. During the research, each expert group submitted assessments of the four analysed energy objects. The results of expert assessment were processed and summarised in the table of criteria values and weights. The ranking and weights of criteria determined during expert assessment are provided in Table 5.

4.2. Measuring the utility degree and market value

The priority and weight of variants of the analysed objects depend, directly and proportionally, on a criteria system which adequately defines the alternatives, as well as on values and weights of the criteria. The utility level shows the level of goals achieved by stakeholder groups. Considering the utility degrees of analysed real estate alternatives, the value of a specific object/alternative is measured. The utility degree and market value are measured for each object using the calculation sequence presented in subchapter 4.2 and formulas (1) through (12). Although values of criteria which, according to the value, affect the elements specified in the Analysis Model for Environment Factors are assessed by experts, this information, however, can change due to the impact of stakeholder groups who may influence decisions by their goals and ability to achieve them. Therefore, expert groups, which represent certain stakeholders, assessed possible degree of stakeholder influence as well.

The main window of the Decision Support System for Measurement of Effect of Environment Factors on Value of Energy Companies (ESIAPVN-DS) is shown in Fig. 8. ESIAPVN-DS system work on address of internet network http://193.219.145.33/elektra/default.aspx.

[FIGURE 8 OMITTED]

Table 6 presents the calculations for the utility degree and market value of the analysed energy objects, i.e. Kruonis Pumped-storage Hydroelectric Power Plant, Kaunas Hydroelectric Power Plant, Lithuanian Power Plant and Geothermal Power Plant, which were performed using the Decision Support System for Measurement of Effect of Environment Factors on Value of Energy Companies developed in Vilnius Gediminas Technical University.

Having assessed the determined values of indicators, it can be noted that experts attributed the biggest weight to the following indicators: the experience of top managers, staff qualification, EU regulation of activities, cooperation with science establishments and environmental regulations. The social role of energy companies also carries a considerable weight. In future, during the improvement of studies of environment factors, this indicator can be analysed more thoroughly dividing it into more specific components. Using the unique decision support system for the measurement of the utility degree and market value of objects, which was developed in Vilnius Gediminas Technical University, it is possible to measure the ratio of ranks of each selected criterion, that clearly defines each object by showing its differences compared to the best alternative.

It is continued by measurement of indicator weights and making a normalised decisionmaking matrix. Obviously, Kaunas Hydroelectric Power Plant has the highest utility degree and the first priority. This result was determined by the use of renewable sources, high profit margin, environmental aspect (not affected by external pollution costs), favourable public opinion on activities and low production costs. The Geothermal Power Plant comes as the second alternative which has a considerable potential of renewable energy sources independent of seasonal variations, favourable public opinion and opinion of stakeholder institutions about activities, high social responsibility level and innovativeness.

When the best alternative is set, then the adjusted object's market value is calculated using the formulas (10) through (12). The company's replacement cost, which differs from the market value, is taken as the initial value. Energy objects usually have higher replacement cost than the obtained income capitalisation value or possible sales price. Using the intelligent software for the processing of multiple criteria analysis results, we obtained the number of approximations and the adjusted market value of objects. Tables 7-10 show the results of market value measurement of energy objects.

5. Recommendations

The problem is how to define an efficient energy sector enterprises life cycle when a lot of various interested parties are involved, the alternative project versions come to hundreds thousand and the efficiency changes with the alterations in the micro, meso and macro environment conditions and the constituent parts of the process in question. Moreover, the realization of some objectives seems more rational from the economic and ecological perspectives thought from the other perspectives they have various significance. Therefore, it is considered that the efficiency of energy sector enterprises life cycle depends on the rationality of its stages as well as on the ability to satisfy the needs of the interested parties and the rational character of the micro, meso and macro environment conditions.

Formalized presentation of the multiple criteria analysis (see Table 11) shows how changes in the micro, meso and macroenvironment and the extent to which the goals pursued by various interested parties are satisfied cause corresponding changes in the value and utility degree of energy sector enterprises. With this in mind, it is possible to solve the problem of optimisation concerning satisfaction of the needs at reasonable expenditures. This requires the analysis of energy sector enterprises versions allowing to find an optimal combination of different interested parties goals pursued, micro-, meso- and macroenvironment conditions and finances available.

[TABLE 7 OMITTED]

[TABLE 8 OMITTED]

[TABLE 9 OMITTED]

[TABLE 10 OMITTED]

Table 11 provides extensive information about the quantitative effect of environment factors on value of energy companies. Last columns of the matrix provided in Table 11 give information about possibilities to increase the value of energy companies. Let us take production costs (cnt/kwh) of the Lithuanian Power Plant as an example. This cell of the matrix provided in Table 11 shows that:

-- Production cost of Lithuanian Power Plant is 31 cnt/kwh. It is the highest production cost among the compared alternatives (22 cnt/kwh for Kruonis HAE, 9 cnt/kwh for Kaunas HE and 12 cnt/kwh for Geothermal Power Plant).

-- Calculations show that theoretically this production cost may be improved by 70.97%.

-- Improvement of production cost by 70.97% in Lithuanian Power Plant means a 17.24% increase of its market value.

Let us take another example from legal regulation of activities of the Geothermal Power Plant (Table 6):

-- Experts gave 18 points to legal regulation of activities of the Geothermal Power Plant (the lowest result among all analysed power plants).

-- Calculations show that the legal regulation of activities may be improved by about 22%.

-- Improvement of 22% in legal regulation of activities of the Geothermal Power Plant means a 0.18% increase of its market value.

Table 12 provides information about criteria that have the greatest influence on the ranking of energy companies.

6. Conclusions

1. The developed Analysis Model for Environment Factors of electricity companies, which incorporates information and intelligent technology, allows analysing corporate environment and value affecting factors, as well as to assess environment efficiency, the related stakeholder groups which want to achieve their goals, and the entire external macro, meso and microenviroment which that the environment and the stakeholder groups. The authors supplemented the Analysis Model for Environment Factors of electricity companies by the criterion of corporate social responsibility as a promising factor which affects company's value.

2. Assessment of special-purpose property of infrastructure companies must include the analysis of factors which define compliance with environmental requirements and norms, as well as the measurement of weights of such factors and their influence on operating efficiency and, respectively, on the value.

3. When solving tasks related to the valuation of special-purpose property of energy sector, an effective instrument can be a value analysis model which matches corporate economic goals, corporate environmental responsibility from social, ecologic and economic perspective, as well as influence of environment factors on corporate property.

4. Valuation methods which are deemed traditional fail to account for the entire set of value affecting criteria. These methods set value of an energy company as a sum of separate complexes of facilities (using the replacement cost approach) or the transformed value of forecast cash flows based on subjective assumptions (using the income capitalisation or other economic methods). Thorough assessment of environment factors helps to improve objectiveness of assumptions; it also facilitates assessment of the utility level of the analysed objects and, respectively, adjustment of the value.

5. Multiple criteria analysis methods, which incorporate the use of intelligent support systems, enable a broader perspective, through the use of simple instruments, on the market value measurement process of objects operating in various branches; it also facilitates the assessment of a larger variety of value affecting factors and their linking with constantly changing environment factors thus monitoring changes of value. The developed Decision Support System for Measurement of Effect of Environment Factors on Value of Energy Companies (ESIAPVN-DS) facilitates the measurement of the utility level and market value of the analysed objects, as well as the analysis of factors which may affect the value, at the same time searching for solutions to eliminate negative effect of factors or to identify the strengths.

doi: 10.3846/1392-8619.2009.15.490-521

Received 11 May 2009; accepted 20 August 2009

Reference to this paper should be made as follows: Sliogeriene, J.; Kaklauskas, A.; Zavadskas, E. K.; Bivainis, J.; Seniut, M. 2009. Environment factors of energy companies and their effect on value: analysis model and applied method, Technological and Economic Development of Economy 15(3): 490-521.

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Jurate SLIOGERIENE. PhD student at Vilnius Gediminas Technical University, Department of Construction Economics and Property Management. Lecturer at Vilnius Gediminas Technical University. Master degree in business management (2006). Research interests: assessment of special purpose assets in economics infrastructure, electricity companies, environmental and energy economics, promotion of renewable energy sources.

Arturas KAKLAUSKAS. Doctor Habil, Professor, Chair in Construction Economics and Real Estate Management Department and Vice-director of the Institute of Internet and Intelligent Technologies at the Vilnius Gediminas Technical University. Expert member of Lithuanian Academy of Sciences. He participated in 9 Framework 5 and 6 projects and author of 221 research publications and 7 monographs.

Edmundas Kazimieras ZAVADSKAS. Doctor Habil, Professor, Principal vice-rector of Vilnius Gediminas Technical University and head of the Department of Construction Technology and Management at Vilnius Gediminas Technical University, Vilnius, Lithuania. Member of Lithuanian and several foreign Academies of Sciences and Doctor honoris causa at Poznan, Saint-Petersburg, and Kiev Universities. Research interests: building technology and management, decision-making theory, automated design and decision support systems.

Juozas BIVAINIS. Doctor Habil, Professor, Head of Department of Social Economics and Business Management, Vilnius Gediminas Technical University. He is the author of over 200 scientific works. Research interests: intensification of economic development, business management theory, economic legislation.

Mark SENIUT. Researcher. Institute of Internet and Intelligent Technologies. Vilnius Gediminas Technical University. Institute of Internet and Intelligent Technologies. Vilnius Gediminas Technical University. Bachelor degree in informatics, Vilnius University (2004). Master degree in informatics (2006). Research interests: IT, biometric systems, intelligent decisions support systems, project management.

Jurate Sliogeriene (1), Arturas Kaklauskas (2), Edmundas Kazimieras Zavadskas (3), Juozas Bivainis (4), Mark Seniut (5)

(1,2,3,4,5) Vilnius Gediminas Technical University, Sauletekio al. 11, LT-10223 Vilnius, Lithuania, (1,2) Department of Construction Economics and Property Management, (3) Department of Construction Technology and Management, (4) Department of Social Economics and Business Management, (5) Institute of Internet and Intelligent Technologies

E-mail: (1) sliogeriene.j@gmail.com (corresponding author); (2) arturas.kaklauskas@st.vgtu.lt; (3) edmundas.zavadskas@adm.vgtu.lt; (4) vvfsevk@vv.vgtu.lt; (5) mkos@delfi.lt

Table 1. Environment factors multiple criteria analysis results

Quantitative information pertinent to projects

 Criteria
describing macro,
 meso and
microenvironment Measuring
 factors * Significance units

 [X.sub.1] [z.sub.1] [q.sub.1] [m.sub.1]
 [X.sub.2] [z.sub.2] [q.sub.2] [m.sub.2]
 [X.sub.3] [z.sub.3] [q.sub.3] [m.sub.3]
 ... ... ... ...
 [X.sub.i] [z.sub.i] [q.sub.i] [m.sub.i]
 ... ... ... ...
 [X.sub.m] [z.sub.m] [q.sub.m] [m.sub.m]
The sums of weighted normalized maximizing
(projects 'pluses') indices of the project
The sums of weighted normalized minimizing
(projects 'minuses') indices of he project
Significance of the project
Priority of the project
Utility degree of the project (%)

Quantitative information pertinent to projects

 Criteria
describing macro,
 meso and
microenvironment
 factors Compared property

 [a.sub.1] [a.sub.2] ... [a.sub.j] ...
 [X.sub.1] [d.sub.11] [d.sub.12] ... [d.sub.1j] ...
 [X.sub.2] [d.sub.21] [d.sub.22] ... [d.sub.2j] ...
 [X.sub.3] [d.sub.31] [d.sub.32] ... [d.sub.3j] ...
 ... ... ... ... ... ...
 [X.sub.i] [d.sub.i1] [d.sub.i2] ... [d.sub.ij] ...
 ... ... ... ... ... ...
 [X.sub.m] [d.sub.m1] [d.sub.m2] ... [d.sub.mj] ...
The sums of [S.sub.+1] [S.sub.+2] ... [S.sub.+j] ...
weighted
normalized
maximizing
(projects
'pluses')
indices of
the project
The sums of [S.sub.-1] [S.sub.-2] ... [S.sub.-j] ...
weighted
normalized
minimizing
(projects
'minuses')
indices of
he project
Significance [Q.sub.1] [Q.sub.2] ... [Q.sub.j] ...
of the project
Priority of the [P.sub.1] [P.sub.2] ... [P.sub.j] ...
project
Utility degree [N.sub.1] [N.sub.2] ... [N.sub.j] ...
of the project
(%)

Quantitative information pertinent to projects

 Criteria
describing macro,
 meso and
microenvironment Compared
 factors property

 [a.sub.n]
 [X.sub.1] [d.sub.1n]
 [X.sub.2] [d.sub.2n]
 [X.sub.3] [d.sub.3n]
 ...
 [X.sub.i] [d.sub.in]
 ...
 [X.sub.m] [d.sub.mn]
The sums of [S.sub.+n]
weighted
normalized
maximizing
(projects
'pluses')
indices of
the project
The sums of [S.sub.-n]
weighted
normalized
minimizing
(projects
'minuses')
indices of
he project
Significance [Q.sub.n]
of the project
Priority of [P.sub.n]
the project
Utility degree of [N.sub.n]
the project (%)

* - The sign [z.sub.i] (+ (-)) indicates that a greater (less)
criterion value corresponds to a greater significance for a client

Table 2. Calculation of average deviations of the property utility
degrees

 Utility degree deviation of a property
 Property analyzed compared to other property,
considered %

 [a.sub.1] [a.sub.1] [a.sub.3] [a.sub.i]

[a.sub.1] 0 [E.sub.12] [E.sub.13] ...
[a.sub.2] [E.sub.12] 0 [E.sub.23] ...
[a.sub.3] [E.sub.21] [E.sub.32] 0 ...
 ... ... ... ... ...
[a.sub.j] [E.sub.j1] [E.sub.j2] [E.sub.j3] ...
 ... ... ... ... ...
[a.sub.n] [E.sub.n1] [E.sub.n2] [E.sub.n3] ...

 Utility
 degree Average deviation
 deviation [k.sub.j] of utility
 of a prop- degree [N.sub.j]
 perty ana- of property
 lyzed com- [a.sub.j] compared
Property pared to to other (n - 1)
considered other property prpoerty

 [a.sub.n]

[a.sub.1] [E.sub.1n] [k.sub.1]
[a.sub.2] [[E.sub.2n] [k.sub.2]
[a.sub.3] [[E.sub.3n] [k.sub.3]
 ... ... ...
[a.sub.j] [[E.sub.jn] [k.sub.j]
 ... ... ...
[a.sub.n] 0 [k.sub.n]

Table 3. A grouped decision making matrix for property multiple
criteria analysis

Criteria describing the * Significance
compared property

1. Price of a property [a.sub.1]
being valuated and actual
purchasing/selling prices
of comparison standard
property ([a.sub.2]-[a.sub.n] [z.sub.1] [q.sub.1]

 [z.sub.2] [q.sub.2]
 ...
Quantitative criteria [z.sub.i] [q.sub.i]
 ... ...
 [z.sub.t] [q.sub.t]
 [z.sub.t+1] [q.sub.t+1]
Qualitative criteria [z.sub.t+2] [q.sub.t+2]
 ... ...
 [z.sub.i] [q.sub.i]
 ... ...
 [z.sub.m] [q.sub.m]

 Property to be
 valuated and
 comparison
Criteria describing the Measuring standard property
compared property units [a.sub.1]

1. Price of a property [a.sub.1]
being valuated and actual
purchasing/selling prices
of comparison standard
property ([a.sub.2]-[a.sub.n] [m.sub.1] [x.sub.11]

 [m.sub.2] [x.sub.21]
 ... ...
Quantitative criteria [m.sub.3] [x.sub.i1]
 ... ...
 [m.sub.t] [x.sub.t1]
 [m.sub.t+1] [x.sub.t+11]
Qualitative criteria [m.sub.t+2] [x.sub.t+21]
 ... ...
 [m.sub.i] [x.sub.i1]
 ... ...
 [m.sub.m] [x.sub.m1]

 Property to be valuated and
Criteria describing the comparison standard property
compared property [a.sub.2] ... [a.sub.j]

1. Price of a property [a.sub.1]
being valuated and actual
purchasing/selling prices
of comparison standard
property ([a.sub.2]-[a.sub.n] [x.sub.12] ... [x.sub.1j]

 [x.sub.22] ... [x.sub.2j]
 ... ... ...
Quantitative criteria [x.sub.i2] ... [x.sub.ij]
 ... ... ...
 [x.sub.t2] ... [x.sub.tj]
 [x.sub.t+12] ... [x.sub.t+1j]
Qualitative criteria [x.sub.t+22] ... [x.sub.t+2j]
 ... ... ...
 [x.sub.i2] ... [x.sub.ij]
 ... ... ...
 [x.sub.m2] ... [x.sub.mj]

 Property to be
 valuated and
 comparison
Criteria describing the standard property
compared property ... [a.sub.n]

1. Price of a property [a.sub.1]
being valuated and actual
purchasing/selling prices
of comparison standard
property ([a.sub.2]-[a.sub.n] ... [x.sub.1n]

 ... [x.sub.2n]
 ... ...
Quantitative criteria ... [x.sub.in]
 ... ...
 ... [x.sub.tn]
 ... [x.sub.t+1n]
Qualitative criteria ... [x.sub.t+2n]
 ... ...
 ... [x.sub.in]
 ... ...
 ... [x.sub.mn]

* - The sign [z.sub.i] (+ (-)) indicates that a greater (less)
criterion value corresponds to a greater significance for a client

Table 4. Quantitative data of the analysed energy sector objects

Quantitative data of objects Kruonis PPHPP Kaunas HPP

Rated capacity, MW 900 100.8
Production cost 22 9
(energy price) cnt/kw
Company's value (replacement 1,852,000 147,600
cost), thousand LTL

Quantitative data of objects Lithuanian PP Geothermal

Rated capacity, MW 1,800 35
Production cost 31 12
(energy price) cnt/kw
Company's value (replacement 1,495,700 29,950
cost), thousand LTL

Table 5. Measurement of values and weights of qualitative and
quantitative criteria

xi Description Unit Weight of +/-
 criteria
 (1st to 4th
 expert
 groups)

 Qualitative criteria

1 EU regulation of points 0.049 +
 electricity related
 activities

2 Internal (national)
 policy towards "
 this sector 0.023 +

3 Relations with " 0.027 +
 national authorities

4 Trends of economic " 0.028 +
 change

5 Changes of consumption " 0.03 +

6 Investment conditions " 0.047 +

7 Public attitude " 0.047 +
 towards activities

8 Change of industrial " 0.047 +
 technology

9 Development of alternative " 0.034 +
 energy sources

10 Environmental regulations " 0.049 +

11 Legal regulation of " 0.03 +
 activities

12 Municipal influence " 0.027 +

13 Legal basis for " 0.023 +
 infrastr. develop.

14 Profitability degree " 0.055 +

15 Competitive environment " 0.011 -

16 Introduction of " 0.034 +
 environment-friendly
 technologies

17 Dependence on resource " 0.013 -
 provision

18 Integration into " 0.019 +
 internat. structures

19 Degree of corporate social " 0.038 +
 responsibility

20 Degree of external " 0.011 -
 pollution effect costs

21 Taxation base level " 0.042 -

22 Conditions to fund " 0.034 +
 development projects

23 Price of raw materials " 0.014 -
 and energy resources

24 Experience of CEOs " 0.061 +

25 Supply of qualified " 0.053 +
 specialists

26 Price of labour resources " 0.05 -

27 Readiness to select and " 0.052 +
 use innovations

28 Cooperation with sci- " 0.027 +

29 Influence of stakeholder " 0.028 -
 groups

 Total amount of rankings 1,0

1 Production cost cnt/ 0.2 -
 (energy price) kwh

2 Company's value LTL 0.3 +

3 Company's rated MW 0.5 -
 capacity

 Total amount of rankings 1,0

 Ranking average (assessment by 1st
 to 6th expert groups)
xi Description
 Kruonis Kaunas Lithuanian
 PHPP HPP PP

 Qualitative criteria

1 EU regulation of 29 31 29
 electricity related
 activities

2 Internal (national)
 policy towards
 this sector 20 15 17

3 Relations with 17 17 19
 national authorities

4 Trends of economic 24 18 26
 change

5 Changes of consumption 22 19 26

6 Investment conditions 34 30 29

7 Public attitude 22 30 30
 towards activities

8 Change of industrial 29 29 29
 technology

9 Development of alternative 20 22 17
 energy sources

10 Environmental regulations 27 31 19

11 Legal regulation of 20 19 22
 activities

12 Municipal influence 25 17 23

13 Legal basis for 15 15 18
 infrastr. develop.

14 Profitability degree 29 35 16

15 Competitive environment 8 7 11

16 Introduction of 22 22 22
 environment-friendly
 technologies

17 Dependence on resource 13 8 43
 provision

18 Integration into 14 12 19
 internat. structures

19 Degree of corporate social 23 24 24
 responsibility

20 Degree of external 7 7 36
 pollution effect costs

21 Taxation base level 32 27 26

22 Conditions to fund 23 22 21
 development projects

23 Price of raw materials 11 9 37
 and energy resources

24 Experience of CEOs 40 39 40

25 Supply of qualified 33 34 35
 specialists

26 Price of labour resources 32 32 27

27 Readiness to select and 32 33 32
 use innovations

28 Cooperation with sci- 20 17 25

29 Influence of stakeholder 18 18 18
 groups

 Total amount of rankings 661 639 736

1 Production cost 22 9 31
 (energy price)

2 Company's value 1,852,000 147,600 1,495,700

3 Company's rated 900 100.8 1,800
 capacity

 Total amount of rankings

 Ranking average (assessment by 1st
 to 6th expert groups)
xi Description
 Geothermal Sum of
 PP criteria
 ranking

 Qualitative criteria

1 EU regulation of 32 121
 electricity related
 activities

2 Internal (national)
 policy towards
 this sector 14 66

3 Relations with 16 69
 national authorities

4 Trends of economic 17 85
 change

5 Changes of consumption 18 85

6 Investment conditions 20 113

7 Public attitude 29 111
 towards activities

8 Change of industrial 31 118
 technology

9 Development of alternative 25 84
 energy sources

10 Environmental regulations 32 109

11 Legal regulation of 18 79
 activities

12 Municipal influence 15 80

13 Legal basis for 15 63
 infrastr. develop.

14 Profitability degree 29 109

15 Competitive environment 11 37

16 Introduction of 24 90
 environment-friendly
 technologies

17 Dependence on resource 12 76
 provision

18 Integration into 18 63
 internat. structures

19 Degree of corporate social 24 95
 responsibility

20 Degree of external 7 57
 pollution effect costs

21 Taxation base level 26 111

22 Conditions to fund 23 89
 development projects

23 Price of raw materials 13 70
 and energy resources

24 Experience of CEOs 41 160

25 Supply of qualified 36 138
 specialists

26 Price of labour resources 17 108

27 Readiness to select and 33 130
 use innovations

28 Cooperation with sci- 31 93

29 Influence of stakeholder 18 72
 groups

 Total amount of rankings 645 2,681

1 Production cost 12
 (energy price)

2 Company's value 29,950

3 Company's rated 35
 capacity

 Total amount of rankings

Table 6. Initial data and results of multiple criteria evaluation of
the alternatives

 Quantitative and qualitative information pertinent to alternatives

 Compared
Criteria describing the * Measuring Weight alterna-
alternatives tives

 Kruonio
 PHPP

EU regulation of electricity- + points 0.049 0.0117
related activities AVG MIN

Internal (national) policy + points 0.023 0.007
towards this sector AVG MIN

Relations with national + points 0.027 0.0067
authorities AVG MIN

Trends of economic change + points 0.28 0.0079
 AVG MIN

Change of consumption + points 0.03 0.0078
 AVG MIN

Investment conditions + points 0.047 0.0141
 AVG MIN

Public attitude towards + points 0.047 0.0093
activities AVG MIN

Change of industrial + points 0.047 0.0116
technology AVG MIN

Development of alternative + points 0.034 0.0081
energy sources AVG MIN

Environment regulations + points 0.049 0.0121
 AVG MIN

Legal regulation of + points 0.03 0.0076
activities AVG MIN

Municipal influence + points 0.027 0.0084
 AVG MIN

Legal basis for intrastr. + points 0.023 0.0055
develop. AVG MIN

Profitability degree + points 0.055 0.0146
 AVG MIN

Competitive environment - points 0.011 0.0024
 AVG MIN

Introduction of environment- + points 0.034 0.0083
friendly technologies AVG MIN

Dependence on resource - points 0.013 0.0022
provision AVG MIN

integration into internat. + points 0.019 0.0042
structures AVG MIN

Dependence on resource - points 0,013 0.0022
provision AVG MIN

integration Into Intemat. + points 0.019 0.0042
structures AVG MIN

Degree of corporate social + points 0.038 0.0092
responsibility AVG MIN

Degree or external pollution - points 0.011 0.0014
effect costs AVG MIN

Taxation base tevei - points 0.042 0.0121
 AVG MIN

conditions to lund development + points 0 034 0.0088
projects AVG MIN

Price of raw materials and - points 0.014 0.0022
energy resources AVG MIN

Experience of CEOs + points 0.061 0.0152
 AVG MIN

Supply of qualified specialists + points 0.053 0.0127
 AVG MIN

Price of labour resources - points 0.05 0.0148
 AVG MIN

Readiness lo select and use + points 0.052 0.0128
innovations AVG MIN

Cooperation with science + points 0.027 0.0058
establishments AVG MIN

influence of stakeholder groups - points 0.020 0.007
 AVG MIN

company's ncome cap:iahsation - thousand LTL 0.2 0.1051
 value AVG MIN

Company's rated capacity + MW 3.3 0.0952
 AVG MIN

Production cost (energy price) - cnt/kwh 0.5 0.1466
 AVG MIN

The sums of weighted normalized maximizing (projects 0,3046
 'pluses') Indices of Itie alternative

The sums of weighted normalized minimizing (projects 0,2958
 'minuses') indices of the alternative
 Significance of Ihe alternative 0.4708
 Priority of Ihe alternative 4
 Utility degree of the alternative (%) 88,77%

Criteria describing the Compared alternatives
alternatives
 Kauno Lietuvos Geother-
 PP HPP PP mal PP

EU regulation of electricity- 0.0126 0.0117 0.013
related activities AVG MIN AVG MIN AVG MIN

Internal (national) policy 0.0052 0.0059 0.0049
towards this sector AVG MIN AVG MIN AVG MIN

Relations with national 0.0067 0.0074 0.0063
authorities AVG MIN AVG MIN AVG MIN

Trends of economic change 0.0059 0.0086 0.0056
 AVG MIN AVG MIN AVG MIN

Change of consumption 0.0067 0.0092 0.0064
 AVG MIN AVG MIN AVG MIN

Investment conditions 0.0125 0.0121 0.0083
 AVG MIN AVG MIN AVG MIN

Public attitude towards 0.0127 0.0127 0.0123
activities AVG MIN AVG MIN AVG MIN

Change of industrial 0.0116 0.0116 0.0123
technology AVG MIN AVG MIN AVG MIN

Development of alternative 0.0089 0.0069 0.0101
energy sources AVG MIN AVG MIN AVG MIN

Environment regulations 0.0139 0.0085 0.0144
 AVG MIN AVG MIN AVG MIN

Legal regulation of 0.0072 0.0084 0.0068
activities AVG MIN AVG MIN AVG MIN

Municipal influence 0.0057 0.0078 0.0051
 AVG MIN AVG MIN AVG MIN

Legal basis for intrastr. 0.0055 0.0066 0.0055
develop. AVG MIN AVG MIN AVG MIN

Profitability degree 0.0177 0.0081 0.0146
 AVG MIN AVG MIN AVG MIN

Competitive environment 0.0021 0.0033 0.0033
 AVG MIN AVG MIN AVG MIN

Introduction of environment- 0.0083 0.0083 0.0091
friendly technologies AVG MIN AVG MIN AVG MIN

Dependence on resource 0.0014 0.0074 0.0021
provision AVG MIN AVG MIN AVG MIN

integration into internat. 0.0036 0.0057 0.0054
structures AVG MIN AVG MIN AVG MIN

Dependence on resource 0.0014 0.0074 0.0021
provision AVG MIN AVG MIN AVG MIN

integration Into Intemat. 0.0036 0.0057 0.0054
structures AVG MIN AVG MIN AVG MIN

Degree of corporate social 0.0096 0.0096 0.0096
responsibility AVG MIN AVG MIN AVG MIN

Degree or external pollution 0.0014 0.0069 0.0014
effect costs AVG MIN AVG MIN AVG MIN

Taxation base tevei 0.0102 0.0098 0.0098
 AVG MIN AVG MIN AVG MIN

conditions to lund development 0.0084 0.008 0.0088
projects AVG MIN AVG MIN AVG MIN

Price of raw materials and 0.0018 0.0074 0.0026
energy resources AVG MIN AVG MIN AVG MIN

Experience of CEOs 0.0149 0.0152 0.0156
 AVG MIN AVG MIN AVG MIN

Supply of qualified specialists 0.0131 0.0134 0.0138
 AVG MIN AVG MIN AVG MIN

Price of labour resources 0.0148 0.0125 0.0079
 AVG MIN AVG MIN AVG MIN

Readiness lo select and use 0.0132 0.0128 0.0132
innovations AVG MIN AVG MIN AVG MIN

Cooperation with science 0.0049 0.0073 0.009
establishments AVG MIN AVG MIN AVG MIN

influence of stakeholder groups 0.007 0.007 0.007
 AVG MIN AVG MIN AVG MIN

company's ncome cap:iahsation 0.0084 0.0849 0.0017
 value AVG MIN AVG MIN AVG MIN

Company's rated capacity 0.0107 0.1904 0.0037
 AVG MIN AVG MIN AVG MIN

Production cost (energy price) 0.0608 0.2095 0.0811
 AVG MIN AVG MIN AVG MIN

The sums of weighted normalized maximi- 0,2195 0.3962 0,2138
zing (projects 'pluses') Indices of the
 alternatives

 The sums of weighted normalized mini- 0.1079 0.3487 0.1169
 ming (projects 'minuses') indices
 of the alternative
 Significance of the alternative 0.5304 0.5157 0.5227
 Priority of the alternative 1 3 2

 Utility degree of the alternative (&) 100,01% 97.23% 98.55%

Table 11. Recommendations in the ESIAPVN-DS system

Qualitative and quantitative description of the a Item atves

Quantitative and qualitative infofmation pertinent to aternalives

Criteria describing the + Measuring Weight
alternatives units units

EU regulation of electncrty- + points 0,049
related activities
Internal (national) policy + points 0,023
towards this sector
Relations with national + points 0,027
authonbes
Trends of economic change + points 0,028
Changes of consumption points 0,03
Investment renditions + points 0,047
Public attitude towards + points 0,047
activities
Change of industrial technology + points 0,047
Development of alternative points 0,034
energy sources
Environmental regual ons + points 0,049
Legal regulation of activities + points 0,03
Municipal influence + points 0,027
Legal basis tor infrastr. + points 0,023
develop
Profitabifcty degree + points 0,055
Competitive environment - points 0,011
Introduction of environment + points 0,054
friendly terminologies
Dependence on resource provision - points 0,013
Integration into intemat. + points 0,19
structuresluras
Degree of corporate social + points 0,038
responsibility
Degree ot external poiMion - points 0,011
effect costs
Taxation base level - points 0,042
Conditions to fund development + points 0,034
projects
Price of raw materials and - points 0,014
energy resources
Experience of CEOs + points 0,061
Supply of qualified specialists + points 0,053
Price of labour resources - points 0,05
Readiness to select and + points 0,052
use innovations
Cooperation with science + points 0,027
establishments
Influence of stakeholder group - points 0,028
Company's income - thousand 0,9
capitalisation value LTL
Company's rated capacity + MW 0,9
Production cost (energy price) - cnt/Kwh 0,9

Criteria describing the --Compared alternatives
alternatives --Possible improvement of the
 analysed criterion %
 --Possible increase of the market
 value of the alternative in %
 through increased value
 of tne aforementioned criterion

 Kruonio PHPP

EU regulation of electncrty- 29 (10,34%)(0,137%)
related activities
Internal (national) policy 20 (0%)(0%)
towards this sector
Relations with national 17 (11,76%H0,OB6%)
authonbes
Trends of economic change 24 (8,33%)(0,063%)
Changes of consumption 22 (18,10%)(O,147%)
Investment renditions 34 (0%)(0%)
Public attitude towards 22 (36,36%)(0,462%)
activities
Change of industrial technology 29 (6,9%)(0,088%)
Development of alternative 20 (25%)(0,23%)
energy sources
Environmental regual ons 27 (18,52)(0,245%)
Legal regulation of activities 20 (10%)(0,081%)
Municipal influence 25 (0%)(0%)
Legal basis tor infrastr. 15 (20%)(O,124%)
develop
Profitabifcty degree 29 (20,60%)(0,307%)
Competitive environment 8 (12,5%)(0,037%)
Introduction of environment 22 (9,09%)(0,083%)
friendly terminologies
Dependence on resource provision 13 (3s,46%)(0,135%)
Integration into intemat. 14 (35,71%)(0,103%)
structuresluras
Degree of corporate social 23 (4,35%)(0,045%)
responsibility
Degree ot external poiMion 7 (0%)(0%)
effect costs
Taxation base level 32 (18,75%)(0,213%)
Conditions to fund development 23 (0%)(0%)
projects
Price of raw materials and 11 (18,18%)(0,069%)
energy resources
Experience of CEOs 40 (2,5% )(0,041%)
Supply of qualified specialists 33 (9,09%)(0,13%)
Price of labour resources 32 (46,88%)(0,633%)
Readiness to select and 32 (3,12%)(0,044%)
use innovations
Cooperation with science 20 (55%)(0,401%)
establishments
Influence of stakeholder group 18 (0%)(0%)
Company's income 1852000 (98,38%)(23,912%)
capitalisation value
Company's rated capacity 900 (100%)(24,305%)
Production cost (energy price) 22 (59,09%)( 14.362%)

Criteria describing the --Compared alternatives
alternatives --Possible improvement of the
 analysed criterion in %
 --Possible increase of the market
 value of the alternative in %
 through increased value of
 tne aforementioned criterion

 Kauno HPP

EU regulation of electncrty- 31 (3,23%)(0,043%)
related activities
Internal (national) policy 15 (33,33%)(0,207%)
towards this sector
Relations with national 17 (11,76%)(o,08s%)
authonbes
Trends of economic change 18 (44,44% )(0,338%)
Changes of consumption 19 (36,04%)(0,298%)
Investment renditions 30 (13,33%)(0,169%)
Public attitude towards 30 (0%)(0%)
activities
Change of industrial technology 29 (6,9%)(0,088%)
Development of alternative 22 (13,64%)(0,125%)
energy sources
Environmental regual ons 31 (3,23%)(0,O43%)
Legal regulation of activities 19 (15,79%)(O,128%)
Municipal influence 17 (47,06%)(0,343%)
Legal basis tor infrastr. 15 (20%)(0,124%)
develop
Profitabifcty degree 35 (0%)(0%)
Competitive environment 7 (0%)(0%)
Introduction of environment 22 (9,09%)(0,083%)
friendly terminologies
Dependence on resource provision 8 (O%)(0%)
Integration into intemat. 12 (58,33%)(0,299%)
structuresluras
Degree of corporate social 24 (0%)(0%)
responsibility
Degree ot external poiMion 7 (0%)(0%)
effect costs
Taxation base level 27 (3,7%)(0,042%)
Conditions to fund development 22 (4,55%)(0,042%)
projects
Price of raw materials and 9 (0%)(0%)
energy resources
Experience of CEOs 39 (5,13%)(0,084%)
Supply of qualified specialists 34 (5,68%)(0,084%)
Price of labour resources 32 (46,88%)(0,633%)
Readiness to select and 33 (0%)(0%)
use innovations
Cooperation with science 17 (82,35%)(0,6%)
establishments
Influence of stakeholder group 18 (0%)(0%)
Company's income 147600 (79,71%)(19,373%)
capitalisation value
Company's rated capacity 100,8 (1635,71%) (409,706%)
Production cost (energy price) 9 (0%)(0%)

Criteria describing the --Compared alternatives
alternatives --Possible improvement of the
 analysed criterion %
 --Possible increase of the market
 value of the alternative in %
 through increased value
 of tne aforementioned criterion

 Lietuvos PP

EU regulation of electncrty- 29 (10,34%)(0,137%)
related activities
Internal (national) policy 17 (17,65%)(0,11%)
towards this sector
Relations with national 19 (0%)(0%)
authonbes
Trends of economic change 26 (0%)(0%)
Changes of consumption 26 (0%)(0%)
Investment renditions 29 (17,24%)(0,219%)
Public attitude towards 30 (0%)(0%)
activities
Change of industrial technology 29 (6,9%)(0,088%)
Development of alternative 17 (47,06%)(0,432%)
energy sources
Environmental regual ons 19 (68,42%)(0,432%)
Legal regulation of activities 22 (0%)(0%)
Municipal influence 23 (8,7%)(0,063%)
Legal basis tor infrastr. 18 (0%)(0%)
develop
Profitabifcty degree 16 (118,75%)(1,764%)
Competitive environment 11 (36,36%)(0,108%)
Introduction of environment 22 (9,09%)(0,083%)
friendly terminologies
Dependence on resource provision 43 (81,4%)(0,286%)
Integration into intemat. 19 (0%)(0%)
structuresluras
Degree of corporate social 24 (0%)(0%)
responsibility
Degree ot external poiMion 36 (80,56%)(0,239%)
effect costs
Taxation base level 26 (0%)(0%)
Conditions to fund development 21 (9,52%)(0,087%)
projects
Price of raw materials and 37 (75,68%)(0,286%)
energy resources
Experience of CEOs 40 (2,5%)(0,041%)
Supply of qualified specialists 35 (2,86%)(0,041%)
Price of labour resources 27 (37,4%)(0,5%)
Readiness to select and 32 (3,12%)(0,044%)
use innovations
Cooperation with science 25 (24%)(0,175%)
establishments
Influence of stakeholder group 18 (0%)(0%)
Company's income 1495700 (98%)(23,818%)
capitalisation value
Company's rated capacity 1800 (0%)(0%)
Production cost (energy price) 31 (70,97%)(17,248%)

Criteria describing the --Compared alternatives
alternatives --Possible improvement of the
 analysed criterion in %
 --Possible increase of the market
 value of the alternative in %
 through increased value of tne
 aforementioned criterion

 Geothermal PP

EU regulation of electncrty- 32 (0%)(0%)
related activities
Internal (national) policy 14 (42,86%)(0,266%)
towards this sector
Relations with national 16 (18,75%)(0.137%)
authonbes
Trends of economic change 17 (52,94%)(0,4%)
Changes of consumption 18 (44.44%)(0,36%)
Investment renditions 20 (70%)(0,888%)
Public attitude towards 29 (3,45%)(0,044%)
activities
Change of industrial technology 31 (0%)(0%)
Development of alternative 25 (0%)(0%)
energy sources
Environmental regual ons 32 (0%)(0%)
Legal regulation of activities 18 (22,22%)( 18%)
Municipal influence 15 (66,67%)(0,486%)
Legal basis tor infrastr. 15 (20%)(0,124%)
develop
Profitabifcty degree 29 (20,69%)(0,307%)
Competitive environment 11 (36,36%)(0,108%)
Introduction of environment 24 (0%)(0%)
friendly terminologies
Dependence on resource provision 12 (33,33%)(0,117%)
Integration into intemat. 18 (5,56%)(0,029%)
structuresluras
Degree of corporate social 24 (0%)[0%)
responsibility
Degree ot external poiMion 7 (0%)(0%)
effect costs
Taxation base level 26 (0%)(0%)
Conditions to fund development 23 (0%)(0%)
projects
Price of raw materials and 13 (30,77%)( 116%)
energy resources
Experience of CEOs 41 (0%)(0%)
Supply of qualified specialists 36 (0%)(0%)
Price of labour resources 17 (0%)(0%)
Readiness to select and 33 (0%)(0%)
use innovations
Cooperation with science 31 (0%)(0%)
establishments
Influence of stakeholder group 18 (0%)(0%)
Company's income 29950 (0%)(0%)
capitalisation value
Company's rated capacity 35 (5042,36%) (1225,647%)
Production cost (energy price) 12 (25%)(6,076%)

Table 12. TOP 3 object criteria that have the greatest influence on
the ranking

 Possible in-
 crease of the
 alternative in
 Possible % through in-
Kruonio improvement of creased value of
 PHPP Criteria describing the analysed the aforemen-
Position the alternative criterion in % tioned criterion

 1 Company's income 98% 24%
 capitalisation value
 2 Company's rated 100% 24%
 capacity
 3 Production cost 59% 14%
 (energy price)
 Kauno HPP

 1 Company's rated capacity 1686% 410%
 2 Company's income 80% 19%
 capitalisation value
 3 Price of labour 47% 1%
 resources

 Lietuvos PP

 1 Company's income 98% 24%
 capitalisation value
 2 Production cost 71% 17%
 (energy price)
 3 Profitability degree 119% 2%

 Geothermal PP
 1
 Company's rated capacity 5043% 1226%

 2 Production cost 25% 6%
 (energy price)
 3 Investment conditions 70% 1%