Evaluating the changes in economic and social development of Lithuanian counties by multiple criteria methods/Lietuvos regionu (Apskriciu) ekonomines ir socialines raidos pokyciai.

Ginevicius, Romualdas ; Podvezko, Valentinas

1. Introduction

Under the conditions of country economy restructurization (Brauers et al. 2007), the differences between economic and social development of various regions are becoming more prominent. To smooth these differences, a number of scientific and practical problems associated with the concepts of a region, regional policy and its aims, determination of the boundaries of a region and evaluation of its development, etc. should be thoroughly investigated (Snieska, Bruneckien? 2009; Lenz 2008).

Researchers, examining the problems of regional policy, differently approach the concept of a region, suggesting different criteria of their classification and aims of regional development policy. However, all investigators emphasize the need for smoothing the differences between the regions as the main aim of their development (Brock, Urbonavisius 2008; Paulauskas, S., Paulauskas, A. 2008; Kaklauskas et al. 2009; Jakaitis et al. 2009; Grundey 2008a, 2008b; Zavadskas, Kaklauskas 2008; Yetgin, Lepkova 2007).

In practice, economic and social development has many different facets, embracing, apart from economic and social aspects, cultural, ethnographical, ecological and other features (Kavaliauskas 2008; Rutkauskas 2008). This makes it difficult to assess the actual state of economic and social development of a region. For example, if the high level of economic development of a particular region has been achieved on the account of heavy environmental pollution, it is hardly possible to talk about sustainable development. Thus, to assess the state of a region, it should be considered from various, often incompatible, perspectives. This approach to evaluating the development of the regions is only paving its way (Jakimavi?ius, Burinskien? 2007; Lin, Li 2008; Terrados et al. 2007; Wang et al. 2008; Burinskien?, Rudzkien? 2009; Ginevi?ius, Podvezko 2007b; 2008a; Ginevi?ius et al. 2004, 2006a, 2006b; Kosiedowski 2008). One of the reasons is the lack of the appropriate evaluation methods. The economic and social development of the state's regions is comprehensively described in the year-book published by the Statistics Department of the government of Lithuania (Counties of Lithuania ... 2004, 2005, 2006, 2007, 2008). It presents as many as 87 criteria of evaluating social and economic development. However, it is hardly possible to rank the regions based on their economic and social development. This is because of the nature of the provided criteria, which are better for some regions and worse for the others. Therefore, to get a generalizing solution of the considered problems, they should be integrated into a single value. The situation is also complicated due to the fact that the number of the criteria is large and they are of various dimensions. The latter are either maximizing or minimizing, implying that the growth of the value of some criteria means a higher development level, while for other criteria it shows a lower level. Moreover, the criteria have various significances with respect to the phenomenon considered, i.e. social and economic regions' development.

To solve such complicated problems, multicriteria evaluation methods have been recently used (Hwang, Yoon 1981; Figueira et al. 2005; Ginevi?ius 2007; Ginevi?ius, Podvezko 2008b, 2008c; Ginevicius et al. 2007, 2008a, 2008b; Brauers, Zavadskas 2008; Brauers et al. 2008a); this could take into consideration the major aspects of economic and social development of the regions, including the environmental problems, as well as multidimensional character of the criteria, different directions of their changing and significances. The calculations made using the above methods demonstrated the way of evaluating the economic and social development of Lithuanian regions (Ginevi?ius et al. 2006a, 2006b; Ginevicius, Podvezko 2004a, 2004b; Adamiek 2001; Kosiedowski 2001, 2008).

Quantitative evaluation of social and economic region's development allows us to determine the changes, taking place in this development. This, in turn, shows the effectiveness of the EU structural funds, national programmes and other facilities used in conducting the regional policy.

2. Regionalising the territory of the country

The term 'region' is perceived differently , though the research in this area has had a long history. The problems associated with its nature, objectivity as a category, as well as the criteria used to define it, etc. are still discussed. Generally, a region is described as a part of the earth's surface, which may be separated from the surrounding territories by applying to it the procedures based on particular criteria (Adamiek 2001; Kosiedowski 2001). On the other hand, both the criteria and procedures used are subjective, therefore, the regionalisation based on them can hardly be considered objective.

The concept of a region may be defined more precisely by analysing the approaches used in various scientific and political spheres, which consider this problem from various perspectives.

The literature analysis of the problem lets us conclude that the essential approaches and aspects, allowing us to define the regions, include geographical, political, sociological, ethnographical and economic factors (Adamiek 2001; Kosiedowski 2001; Andriusaitien? 2007).

From a geographical perspective, a region is a relatively homogeneous surface area, differing from the surrounding territories by the distinct environmental characteristics, such as the territory formed, type of soil, climate, etc.

From the political perspective, the essential region's characteristics are specific political actions, popularity of the respective political doctrines, self-government in the framework of a federal state, the support of the existing administrative-territorial division, the effectiveness of performance of regional authorities, etc.

From the social perspective, the significant criteria of region's delimitation are the status of belonging to a particular nation, the integrity of the local community, the sense of peculiarity in relations with other territories, emotional links with the so-called 'native land', etc.

Ethnically, the regions differ in linguistic features (e.g. language, intellect, jargon), as well as in traditions and culture (art, garments and traditions of the population), etc.

Economically, a region is primarily an outlined territory with specific economy, which was formed based on the available internal and external economic resources, and factors influencing its development, such as capital, labour force, technologies, information, etc.

It is clear that it is hardly possible under real conditions to define a region based only on regional, political, ethnographical or other characteristics. All these interrelated aspects are integrated in the concept of an economical region. On the other hand, this 'applied' approach to a region can hardly allow us to appropriately fix its boundaries, which is required for planning and management of a region. Therefore, its boundaries are usually associated with territorial-administrative division of a country.

A resolution of the Government of Lithuanian Republic (1998) 'On the guidelines of Lithuanian policy of regional development' stated that administrative-territorial units, counties, would be considered the main divisions for conducting the state regional policy of social-economic development. Now, there are ten counties in Lithuania. Therefore, at present, counties are considered to be the regions in this country. This is also confirmed by A resolution of the Seimas of Lithuanian Republic (1999) 'On the concluding-report of the Seimas Committee for European affairs on the EU regional policy and Lithuania's preparation for its implementation'.

Today, territorial-administrative units of Lithuanian Republic are counties and municipalities (The law on territorial-administrative divisions of Lithuanian Republic 1994). A municipality is an administrative unit, exercising control over self-government institutions elected by the inhabitants. A county is the highest administrative unit subordinate to the government of Lithuanian Republic. It consists of self-governed territories, having common social, economic and ethno-cultural interests.

The situation is changing, and the amalgamation of counties into bigger units is planned. The need for extending the existing administrative-territorial divisions had been already emphasized some years ago. Then, it was believed that regional structures formed by integrating several counties, based on common natural, economic and other conditions, could be established in Lithuania. For this purpose, several regions differing from others by their economic and social development were suggested. They were Western, Central, Northern, South-Western, Eastern and South-Eastern regions (Bura?as 1997). Today, the problem of integrating the existing regions into larger units is included in the programmes of the political parties of Lithuania.

Lithuania as a member-state of the European Union should coordinate its policy of regional development with the EU policy in this area, which is aimed at harmonizing social and economic development. The particular goals of the EU regional development policy are formulated in the EU Agreement. According to the Article 158, the European Union should strive to smooth the differences in the level of development between various regions and diminishing the backwardness of less developed regions. The European funds of regional development are aimed at supporting the development of these regions as well as structural changes and restructuring of industrial regions experiencing economic decline. Regional development policy was worked out specially for diminishing the gap between the richest and the poorest EU member-states or the level of the development of their regions.

3. A system of criteria describing economic and social development of Lithuanian districts

Economic and social development of the state's regions (districts) is reflected in the yearbook of the Statistical Department (Counties of Lithuania 2007). It presents the criteria of social and economic development as a system consisting of separate groups (sets) of criteria describing particular aspects of development (Table 1).

As shown in Table 1, 87 criteria presenting 24 groups are used to describe social and economic development of Lithuanian regions. Their analysis shows that some of them may be deduced from the others and expressed either by absolute or relative values, etc. However, the criteria describing social and economic development of the state, which may be perceived as a system reflecting all aspects of development, should be independent. Therefore, it is possible to reduce their number, not decreasing the accuracy of reflecting the level of the development achieved. By performing these operations we obtained a system of criteria, describing social and economic development of the country (Counties of Lithuania 2004-2008) suitable for further calculations (Table 2).

As shown by the values of the criteria presented in Table 2, it is not possible to rank the regions according to economic and social development level because some of these values are better for some particular regions, while others are better for other regions. This can be more clearly seen if the values are expressed in terms of ranks (Table 3).

One can see that, for example, Vilnius region is ranked first according to some criteria, while being the last according to some others. This means that the ways of integrating all the criteria describing social and economic development into a single magnitude should be developed. By equating these values to each other, it would be possible to rank the regions considered according to the level of their social and economic development. To solve this problem, multicriteria evaluation methods, allowing generalization of the criteria, having various dimensions and changing in various directions, should be used (Ginevi?ius 2008; Podvezko 2008; Ginevi?ius, Podvezko 2008d, e; Turskis et al. 2009; Zavadskas et al. 2008a; Brauers et al. 2008b; Ustinovichius et al. 2007).

4. Multicriteria evaluation of social and economic development of Lithuanian regions

As mentioned above, multicriteria evaluation methods are well suited for evaluating economic and social development of regions.

The basis of quantitative multicriteria methods is the matrix R = [parallel][r.sub.ij][parallel] of the statistical data of the criteria describing the compared regions (Table 2) and their weight values [[omega].sub.i] i = 1, ..., m; j = 1, ..., n where m is the number of criteria (in this case, m = 14) and n is the number of the alternatives (the regions compared) (in this case, n = 10). By applying quantitative multicriteria evaluation methods, the type of each criterion, maximizing or minimizing (max or min in row 3 of Table 2), is determined. The criteria of quantitative multicriteria evaluation methods embrace non-dimensional (normalized) criteria values [[??].sub.ij] and weights cor Most methods rely on a specific normalization or transformation of the initial data of the criteria.

Four methods--SAW, TOPSIS, COPRAS and COPRAS-M are used in this work. The simplest multicriteria evaluation method VS was used for comparison.

The methods used differ in the sophistication level. The most widely known and used method is SAW (Simple Additive Weighing) (Hwang, Yoon 1981). The criterion of the method Sj fully reflects the aim of quantitative multicriteria evaluation methods of integrating the criteria values and weights into a single magnitude.

The sum [S.sub.j] of the weighted normalized criteria values is calculated for each j-th region. It is found according to the formula:

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

where [[omega].sub.i] , is the weight of i-th criterion; [[??].sub.[??]] is normalized i-th criterion value for j-th region ([m.summation over (i=1)][[omega].sub.i] = i).

In this case, normalization of the initial data may be made using the formula (Ginevicius, Podvezko 2007a):

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

where [r.sub.ij] is the value of i-th criterion for j-th region.

The best value of the criterion [S.sub.j] is its largest value.

In using SAW, minimizing criteria should be transformed into maximizing ones prior to normalization by the formula given below (Hwang, Yoon 1981):

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

where the lowest positive criterion values are transformed into a maximizing value equal to one.

The method TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) is based on the principle that the alternative having the shortest distance to the ideal variant (solution) and the longest distance to the worst variants should be chosen (Hwang, Yoon 1981; Opricovic, Tzeng 2004). The method can be applied both to maximized and minimized criteria. TOPSIS relies on vector normalization:

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

where [[??].sub.ij] is normalized value of i-th criterion for j-th object.

The best variant (solution) [V.sup.*] and the worst variant [V.sup.-] are calculated by the formulas:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.]

where [I.sub.1] is a set of maximizing criteria, [I.sub.2] is a set of minimizing criteria, is the weight of the i-th criterion.

Overall distance [D.sup.*.sub.j] of every considered alternative from the best variants and from the worst options, [D.sup.-.sub.j], are calculated by the formulas:

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

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (6)

The criterion [C.sup.*.sub.j] of the method TOPSIS is calculated by the formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (7)

The largest value of the criterion [C.sup.*.sub.j] correlates with the best alternative. The alternatives compared should be ranked in the descending order.

The method COPRAS (Kaklauskas et al. 2007; Zavadskas et al. 2008b; Banaitiene et al. 2008; Vitiekiene, Zavadskas 2007) of complex proportional evaluation and its simplified version (COPRAS- M) can be used if both maximizing and minimizing criteria are available. If only maximizing criteria are used, the results obtained match those of SAW. In fact, the value of the criterion for complex proportional evaluation is calculated from the formula:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (8)

where [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] is the sum of normalized weighted values of all maximizing criteria of the j-th alternative, [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] is same for all minimizing criteria, [S.sub.-min] = [min.sub.j] [S.sub.-j].

The same applies to a simplified method of a complex proportional evaluation suggested by the authors (Ginevi?ius et al. 2004), when the criterion of the method is calculated by the formula:

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

where [S.sub.-max] = [max.sub.j] [S.sub.-j].

The simplest multicriteria method used at the initial stage of evaluation, which was used for comparing the alternatives, is based on the sum of ranks calculated for the alternative, taking into account the values of the criteria describing it (Ginevicius, Podvezko 2007a). This method does not need any transformation of data or positive values as well as the uniformity of units of measurement, being also independent of the particular values of the criteria weights [[omega].sub.i]. The sum of ranks for the j-th alternative is calculated in the following way:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (10)

where [m.sub.ij] is the rank (position) of the j-th alternative for the i-th criterion.

The criteria weights [[omega].sub.i] were obtained by Saaty's method AHP (Saaty 1980, 2005; Podvezko 2007) and are given in Table 4.

Multicriteria evaluation data on social and economic development of Lithuanian regions obtained by using formulas (1)-(9) are given in Table 5 (see 431 p.).

For the sake of comparison, the ranks of the regions were determined for 2007 by the formula (10), using the VS method. The calculation results are given in Table 6.

As shown in Table 6, the ranks of the regions calculated by the VS method differ considerably from those yielded by more precise methods. This confirms the conclusion that the method VS (sum of ranks) may be used only for preliminary evaluation.

The results obtained in the analysis of economic and social development of Lithuanian regions show that only the most highly developed regions (those of Vilnius, Klaipeda and Kaunas) and the least developed regions (those of Taurage, Siauliai and Marijampole) have remained stable in the period considered (see Table 7).

In Table 7, one can see that the situation has greatly improved in TelSiai region, which was ranked third after Vilnius and Klaipeda regions according to its social and economic development in 2007. In general, it may be stated that there have not been any considerable changes in the development of Lithuanian regions, with the leaders and those lagging behind remaining the same. It implies that the regional policy of the country has been in effective.

To assess the rate of economic and social development of the regions and their stability over the considered period, the following indicator is suggested:

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] (11)

where [P.sub.j] is the indicator of j-th region's social and economic development rate and stability; [V.sub.jt] is the rank of j-th region in t-th year (t = 1, 2, ... , T); T is the period evaluated; [MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII.] is the average rank; n is the number of alternatives (regions).

The results of calculations made by formula (11) are presented in Table 8.

As shown in Table 8, the most rapidly developing and stable are the regions of Vilnius, Klaipeda, Kaunas and TelSiai, while the most slowly developing are Taurage, Siauliai and Marijampole.

Conclusions

1. To determine the level of economic and social development of regions, a great number of various and often incompatible criteria should be considered. This makes the solution of this problem a complicated task. On the other hand, striving for sustainable development of the regions, the level achieved should be quantitatively evaluated. However, it has not been made yet because of the lack of the appropriate evaluation methods. The situation has changed when the researchers began to use multicriteria evaluation methods, allowing them to take into account multidimensional character and different directions of the criterion change as well as different significances (weights) of the criteria describing the development of the regions.

2. Considering the economic and social development of regions, the concept of a region should be defined as precisely as possible. The respective documents of the government of Lithuanian Republic state that the main territorial division is a county (region); therefore, regional development is analysed in the present work.

3. The definition of the country's regions and the analysis of their development are required for the developing and pursuing the effective regional policy, perceived both in the European Union and Lithuania as a means of smoothing the differences in social and economic development between regions and promoting uniform and steady development of the whole territory of the country.

4. Eighty seven criteria describe the economic and social development of Lithuanian regions from various perspectives. Some of them may be deduced from the others; therefore, a set of 14 criteria was used in further calculations.

5. Three main methods--SAW, TOPSIS and COPRAS were used in multicriteria evaluation of social and economic development of Lithuanian regions. To determine the ultimate rank of a region, the average estimate of the values obtained in applying all the considered methods was taken.

doi: 10.3846/1392-8619.2009.15.418-436

Received 28 April 2009; accepted 20 August 2009

Reference to this paper should be made as follows: Ginevi?ius, R.; Podvezko, V. 2009. Evaluating the changes in economic and social development of Lithuanian counties by multiple criteria methods, Technological and Economic Development of Economy 15(3): 418-436.

References

A resolution of the Government of Lithuanian Republic on 21 July, 1998 'On the guidelines of Lithuanian policy of regional development'.

A resolution of the Seimas of Lithuanian Republic on 14 January, 1999 'On the concluding report of the Seimas Committee for European affairs on the EU regional policy and Lithuania's preparation for its implementation'.

Adamiek, J. 2001. Territorial self-government and its role in regional and local development, in Zarzadzanie rozwojem regionalnym i lokalnym: problemy teorii i praktyki. Torun: Dom Organizatora, 48-118.

AndriuSaitiene, D. 2007. Extending labour market in depressed regions of the country. PhD thesis. Vilnius Technika.

Banaitiene, N.; Banaitis, A.; Kaklauskas, A.; Zavadskas, E. K. 2008. Evaluating the life cycle of a building: A multivariant and multiple criteria approach, Omega-International Journal of Management Science 36(3): 429-441. doi:10.1016/j.omega.2005.10.010.

Brauers, W. K. M.; Zavadskas, E. K. 2008. Multiobjective optimization in local theory with a simulation for a department store, Transformations in Business & Economics 7(3): 163-183.

Brauers, W. K. M.; Ginevicius, R.; Zavadskas, E. K.; Antucheviciene, J. 2007. The European Union in a transition economy, Transformations in Business & Economics 6(2): 21-37.

Brauers, W. K. M.; Zavadskas, E. K.; Peldschus, F.; Turskis, Z. 2008a. Multi-objective decision-making for road design, Transport 23(3): 183-193. doi:10.3846/1648-4142.2008.23.183-193.

Brauers, W. K. M.; Zavadskas, E. K.; Turskis, Z.; Vilutiene, T. 2008b. Multi-objective contractor's ranking by applying the MOORA method, Journal of Business Economics and Management 9(4): 245-255. doi:10.3846/1611-1699.2008.9.245-255.

Brock, G.; Urbonavicius, S. 2008. Regional FDI growth in LITHUANIA, 1996-2003, Transformations in Business & Economics 7(1): 80-88.

Buracas, A. (Eds.). 1997. Lithuanian Economic Reforms: Practice and Perspectives. Vilnius: Margi rastai.

Burinskiene, M.; Rudzkiene, V. 2009. Future insights, scenarios and expert method application in sustainable territorial planning, Technological and Economic Development of Economy 15(1):10-25. doi: 10.3846/1392-8619.2009.15.10-25.

Counties of Lithuania. Economic and social development 2003. Statistics Lithuania. Vilnius, 2004.

Counties of Lithuania. Economic and social development 2004. Statistics Lithuania. Vilnius, 2005.

Counties of Lithuania. Economic and social development 2005. Statistics Lithuania. Vilnius, 2006.

Counties of Lithuania. Economic and social development 2006. Statistics Lithuania. Vilnius, 2007.

Counties of Lithuania. Economic and social development 2007. Statistics Lithuania. Vilnius, 2008.

Figueira, J.; Greco, S.; Ehrgott, M. Eds. 2005. Multiple Criteria Decision Analysis: State of the Art Survey. Springer.

Ginevicius, R. 2007. Hierarchical structure of processes and phenomena, Verslas: teorija ir praktika [Business: Theory and Practice] 8(1): 14-18 (in Lithuanian).

Ginevicius, R. 2008. Normalization of quantities of various dimensions, Journal of Business Economics and Management 9(1): 79-86. doi:10.3846/1611-1699.2008.9.79-86.

Ginevicius, R.; Podvezko, V. 2004a. Quantitative assessment of regional development, Aplinkos tyrimai, inzinerija ir vadyba 1(27) :10-14.

Ginevicius, R.; Podvezko, V. 2004b. Complex evaluation of the use of information technologies in the Countries of Easters and Central Europe, Journal of Business Economics and Management 5(4): 183-191.

Ginevicius, R.; Podvezko, V. 2007a. Some problems of evaluating multicriteria decision methods, International Journal of Management and Decision Making 8(5/6): 527-539. doi:10.1504/IJMDM.2007.013415.

Ginevicius, R.; Podvezko, V. 2007b. Complex assessment of sustainable development of state regions with emphasis on ecological and dwelling conditions, Ekologija 53(Supplement): 41-48.

Ginevicius, R.; Podvezko, V. 2008a. Housing in the context of economic and social development of Lithuanian regions, Int. J. Environment and Pollution 35(2/3/4): 309-330.

Ginevicius, R.; Podvezko, V. 2008b. A feasibility study of multicriteria methods' application to quantitative evaluation of social phenomena, Verslas: teorija ir praktika [Business: Theory and Practice] 9(2): 81-87 (in Lithuanian).

Ginevicius, R.; Podvezko, V. 2008c. Multicriteria graphical-analytical evaluation of the financial state of construction enterprises, Technological and Economic Development of Economy 14(4): 452-461. doi: 10.3846/1392-8619.2008.14.452-461.

Ginevicius, R.; Podvezko, V. 2008d. The problem of compatibility of various multiple criteria evaluation methods, Verslas: teorija ir praktika [Business: Theory and Practice] 9(1): 73-80 (in Lithuanian).

Ginevicius, R.; Podvezko, V. 2008e. Multicriteria evaluation of Lithuanian banks from the perspective of their reliability for clients, Journal of Business Economics and Management 9(4): 257-267. doi:10.3846/1611-1699.2008.9.257-267.

Ginevicius, R.; Podvezko, V.; Mikelis, D. 2004. Quantitative evaluation of economic and social development of Lithuanian regions, Ekonomika: mokslo darbai 65: 67-81.

Ginevicius, R.; Podvezko, V., Mikelis, D. 2006a. A system for evaluating social-economic development of regions, in Karaszewski, W.; Kunikowski, S. (Eds.). Polityka rozvoju Europy srodkowo-wschodnej. Aspekty makroekonomiczne i regionalne. Wroclawek, 211-224.

Ginevicius, R.; Butkevicius, A.; Podvezko, V. 2006b. Complex Evaluation of Economic Development of the Baltic States and Poland, Ekonomicky Casopis [Journal of Economics] 54(9): 918-930.

Ginevicius, R.; Podvezko, V.; AndruSkevicius, A. 2007. Quantitative evaluation of building technology, International Journal of Technology Management 40(1/2/3): 192-214.

Ginevicius, R.; Podvezko, V.; Bruzge, S. 2008a. Evaluating the Effect of State Aid to Business by Multicriteria Methods, Journal of Business Economics and Management 9(3): 167-180. doi:10.3846/1611-1699.2008.9.167-180.

Ginevicius, R.; Podvezko, V.; Raslanas, S. 2008b. Evaluating the Alternative Solutions of Wall Insulation by Multicriteria Methods, Journal of Civil Engineering and Management 14(4): 217-226. doi: 10.3846/1392-3730.2008.14.14-20.

Grundey, D. 2008a. Applying sustainability principles in the economy, Technological and Economic Development of Economy 14(2): 101-106. doi: 10.3846/1392-8619.2008.14.101-106.

Grundey, D. 2008b. Managing sustainable tourism in Lithuania: dream or reality? Technological and Economic Development of Economy 14(2): 118-129. doi: 10.3846/1392-8619.2008.14.118-129.

Hwang, C. L.; Yoon, K. 1981. Multiple Attribute Decision Making-Methods and Applications, A State of the Art Survey. Springer Verlag, Berlin, Heidelberg, New York.

Jakaitis, J.; Paliulis, N.; Jakaitis, K. 2009. Aspects of the national urban policy management under conditions of integrated planning, Technological and Economic Development of Economy 15(1): 26-38. doi: 10.3846/1392-8619.2009.15.26-38.

Jakimavicius, M.; Burinskiene, M. 2007. Automobile transport system analysis and ranking in Lithuanian administrative regions, Transport 22(3): 214-220.

Kaklauskas, A.; Zavadskas, E. K.; Trinkunas, V. 2007. A multiple criteria decision support on-line system for construction, Engineering Applications of Artificial Intelligence 20 (2): 163-175. doi:10.1016/j.engappai.2006.06.009.

Kaklauskas, A.; Zavadskas, E. K.; Saparauskas, J. 2009. Conceptual modelling of sustainable Vilnius Development, Technological and Economic Development of Economy 15(1): 154-177. doi: 10.3846/1392-8619.2009.15.154-177.

Kavaliauskas, P. 2008. A concept of sustainable development for regional land use planning: Lithuanian experience, Technological and Economic Development of Economy 14(1): 51-63. doi:10.3846/2029-0187.2008.14.51-63.

Kosiedowski, W. 2001. Theoretical problems of regional development, in Zarzadzanie rozwojem regionalnym i lokalnym: problemy teorii i praktyki. Torun: Dom Organizatora, 17-43.

Kosiedowski, W. 2008. The problems of economical cooperation of the Baltic region states in the context of European integration. Torun: Dom organizatora.

Lenz, B. 2008. Information models for assessment and management of development trends, Technological and Economic Development of Economy 14(3): 444-447. doi:10.3846/1392-8619.2008.14.444-447.

Lin, J. J.; Li, C. N. 2008. A grey programming model for regional transit-oriented development planning, Papers in Regional Science 87(1): 119-138. doi:10.1111/j.1435-5957.2007.00146.x.

Opricovic, S.; Tzeng, G.-H. 2004. Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research 156: 445-455. doi:10.1016/S0377-2217(03)00020-1.

Paulauskas, S.; Paulauskas, A. 2008. The virtualics and strategic self-management as tools for sustainable development, Technological and Economic Development of Economy 14(1): 76-88. doi:10.3846/2029-0187.2008.14.76-88.

Podvezko, V. 2007. Determining the level of agreement of expert estimates, International Journal of Management and Decision Making 8(5/6): 586-600. doi:10.1504/IJMDM.2007.013420.

Podvezko, V. 2008. Complex values' evaluation, Verslas: teorija ir praktika [Business: Theory and Practice] 9(3): 160-168.

Rutkauskas, A.V. 2008. On the sustainability of regional competitiveness development considering risk, Technological and Economic Development of Economy 14(1): 89-99. doi:10.3846/2029-0187.2008.14.89-99.

Saaty, T. L. 1980. The Analytic Hierarchy Process. M. Graw-Hill, New York.

Saaty, T. L. 2005. The analytic hierarchy and analytic network processes for the measurement of intangible criteria and for decision-making, in Figueira, J.; Greco, S.; Ehrgott, M. (Eds.). Multiple Criteria Decision Analysis: State of the Art Surveys. Springer, Chapter 9: 345-408.

SnieSka, V.; Bruneckiene, J. 2009. Measurement of Lithuanian Regions by Regional Competitiveness Index, Inzinerine ekonomika-Engineering Economics 1(61): 45-57.

Terrados, J.; Almonacid G.; Hontoria, L. 2007. Regional energy planning through SWOT analysis and strategic planning tools. Impact on renewables development, Renewable and Sustainable Energy Reviews 11(6): 1275-1287. doi:10.1016/j.rser.2005.08.003.

The law on territorial-administrative divisions of Lithuanian Republic and their boundaries adopted on 19 July, 1994.

Turskis, Z.; Zavadskas, E. K.; Peldschus, F. 2009. Multi-criteria optimization system for decision making in construction design and management, Inzinerine ekonomika-Engineering Economics 1(61): 7-17.

Ustinovichius, L.; Zavadskas, E. K.; Podvezko, V. 2007. The application of a quantitative multiple criteria decision making (mcdm-1) approach to the analysis of investments in construction, Control and Cybernetic 36(2): 251-268.

Vitiekiene, M.; Zavadskas, E. K. 2007. Evaluating the sustainability of Vilnius city residential areas, Journal of Civil Engineering and Management 13(2): 149-155.

Wang, Y. M.; Chin, K. S.; Poon, G. K. K. 2008. A data envelopment analysis method with assurance region for weight generation in the analytic hierarchy process, Decision Support Systems 45(4), Sp. Iss. SI: 913-921.

Yetgin, F.; Lepkova, N. 2007. A comparative analysis on housing policies in Turkey and Lithuania, International Journal of Strategic Property Management 11(1): 47-64.

Zavadskas, E. K.; Kaklauskas, A. 2008. The model for Lithuanian construction industry development, Transformations in Business & Economics 7(1): 152-168.

Zavadskas, E. K.; Kaklauskas, A.; Turskis, Z.; TamoSaitiene, J. 2008a. Selection of the effective dwelling house walls by applying attributes values determined at intervals, Journal of Civil Engineering and Management 14(2): 85-93. doi:10.3846/1392-3730.2008.14.3.

Zavadskas, E. K.; Turskis, Z.; TamoSaitiene, J. 2008b. Contractor selection of construction in a competitive environment, Journal of Business Economics and Management 9(3): 181-187. doi:10.3846/1611-1699.2008.9.181-187.

Romualdas GINEVICIUS. Professor, Dr Habil, Head of the Department of Enterprise Economics and Management, construction engineer and economist. The author of more than 350 research papers and over 20 scientific books; editor-in-chief of the 'Journal of Business Economics and Management' (located in ISI database 'Web of Science') and the journal 'Business: Theory and Practice'. Research interests: organization theory, complex quantitative evaluation of social processes and phenomena.

Valentinas PODVEZKO. Doctor, Professor. Dept of Mathematical Statistics. Vilnius Gediminas Technical University. Author and co-author of over 100 publications. Research interests: sampling and forecasting models in economics.

Romualdas Ginevicius (1), Valentinas Podvezko (2)

Vilnius Gediminas Technical University, Saul?tekio al. 11, LT-10223 Vilnius, Lithuania E-mails: (1) [email protected]; (2) [email protected]

Table 1. The criteria of economic and social development of Lithuanian
regions (counties)

No A generic name The criteria of a set
 of criteria

1 Population 1. Population, area and density
 2. Live births, deaths,
 natural increase/decrease
 3. Vital statistics indicators
 4. Marriages and divorces
 5. Mortality by sex and age
 group, 2007
 6. Life expectancy at birth
 7. Mortality by cause of death
 8. Internal and international
 migration
2 Health and 1. Physicians
 social security 2. Physicians by specialty
 3. Odontologists
 4. Nurses
 5. Number of pharmacists
 6. Number of visits to
 outpatient facilities
 7. Number of state social
 insurance old age pensioners
 8. Expenditure on benefits
3 Education and culture 1. Educational attainment of
 the population (aged 25-64)
 2. Preschool education
 3. Number of general schools
 4. Number of vocational schools
 5. Number of colleges
 6. Number of universities
 7. Libraries
 8. Cultural centres
4 Employment and 1. Average annual number of
 unemployment employed persons
 2. Employed persons by economic
 activity and sex
 3. Employed persons and
 employment rate by sex
 4. Unemployed and unemployment
 rate by sex
 5. Labour force and labour force
 activity rate by sex
5 Labour 1. Average number of employees
 by the kind of economic activity
 2. Average gross monthly earnings
 by the kind of economic activity
 3. Average number of employees,
 average gross monthly and
 hourly earnings and indices
6 Household income and 1. Average disposable income, 2007
 expenditure 2. Average consumption
 expenditure, 2007.
7 Dwelling 1. Stock of dwellings
 2. Number of dwellings by
 type of ownership, 2007
 3. Housing provision
8 Crime 1. Registered criminal offences
 2. Investigated criminal offences
9 Gross domestic product 1. Gross domestic product (GDP)
 2. Gross domestic product (GDP)
 per capital
 3. Value added
10 Municipal budgets 1. Municipal budgets revenue, 2007
 2. Municipal budgets expenditure by
 function ofthe Government, 2007
11 Prices 1. Average retail prices for food
 and non-food goods, December
 2. Annual rates of change in prices
 for main consumer goods and
 services by group in major cities
 of the country
12 Foreign trade 1. Exports of goods of
 Lithuanian origin
 2. Exports of goods of Lithuanian
 origin to the European Union
 and to other countries
13 Foreign direct 1. Foreign direct investment
 investment
14 Economic entities 1. Number of economic entities
 in operation
 2. Number of economic entities in
 operation by economic activity, 2008
 3. Number of economic entities in
 operation by personnel, 2008
15 Enterprise statistics 1. Turnover 2. Turnover by the
 kind of economic activity, 2006
16 Investment in tangible 1. Investment in tangible fixed assets
 fixed assets
17 Industry 1. Production of main commodities
18 Construction 1. Construction authorized
 by building permits
 2. Dwellings completed
 3. Construction authorized by
 non-residential buildings permits
 and new non-residential buildings
 completed
 4. Own-account construction work
 carried out within the country
19 Domestic trade 1. Indicators of enterprises of sale,
 maintenance and repair of motor
 vehicles and motorcycles, retail
 sale of automotive fuel
 2. Indicators of enterprises of
 retail trade except sale of motor
 vehicles and motorcycles
 3. Indicators of restaurants, bars
 and other catering enterprises
20 Services 1. Income of service enterprises
21 Tourism 1. Number of accommodation
 establishments
 2. Number of guests in accommodation
 establishments
 3. Overnight stays in accommodation
 establishments
22 Transport and 1. Number of road vehicles, 2007
 communication 2. National freight transport
 by road, 2007
 3. Passengers carried by bus
 4. Main residential telephone lines
 5. Number of private passenger cars
 6. Road traffic accidents
23 Agriculture 1. Gross agriculture production
 2. Utilised agriculture land
 3. Crop area on all farms
 4. Harvest of agricultural crops
 on all farms
 5. Yield of agricultural crops
 on all farms
 6. Number of livestock and poultry
 on all farms, 2008
 7. Animal products and productivity
 per cow on all farms
24 Environment and 1. Water abstraction and consumption
 climate 2. Water consumption by purpose, 2007
 3. Waste water discharge, 2007
 4. Air pollutant emissions
 from stationary sources
 5. Gaseous and liquid emissions
 from stationary sources
 6. Climate
 Total value: 87

Table 2. The statistical data on economical and social development of
Lithuanian regions from 2003 to 2007

No Criterion Criterion Year Regions
 direction Alytus Kaunas

1 Population Max 2003 -4.599 -4.009
 migration (net 2004 -6.060 -5.230
 migration) per 1000 2005 -5.217 -3.611
 inhabitants 2006 -4.182 -1.715
 2007 -4,451 -1,824
2 Municipal budget's Max 2003 1.152 1.038
 revenue (average 2004 1.308 1.199
 amount per capita) 2005 1.397 1.306
 2006 1.640 1.662
 2007 1,774 1,702
3 Municipal budget's Max 2003 150.91 120.38
 expenditure 2004 190.16 158.08
 (average amount, 2005 201.49 171.96
 social security) 2006 225.43 191.44
 2007 144,67 138,84
4 Unemployment Min 2003 13.6 12.1
 rate (%) 2004 16.0 10.3
 2005 8.2 8.9
 2006 5.1 5.9
 2007 3,3 4,2
5 Average gross Max 2003 912 992
 monthly earnings 2004 975 1063
 2005 1072 1192
 2006 1255 1412
 2007 1540 1720
6 Average useful floor Max 2003 25.0 22.5
 space per capita 2004 25.4 22.6
 2005 25.9 22.8
 2006 26.0 23.0
 2007 26,4 23,2
7 Number of Max 2003 102 89
 pre - school 2004 97 86
 establishments 2005 109 88
 (places per 100 2006 112 83
 children) 2007 113 85
8 Number of schools Max 2003 4.08 3.00
 (per 1000 of 2004 3.74 2.55
 students) 2005 2.81 2.46
 2006 2.94 2.47
 2007 3,07 2,55
9 Animal products Max 2003 818 723
 recalculated in 2004 782 756
 terms of milk (100 2005 672 681
 kg per 100 ha of 2006 691 682
 agricultural land) 2007 701 706
10 Indicators of activity Max 2003 3130 4712
 of retail trade 2004 3722 5211
 enterprises (per 2005 4565 6079
 capita) 2006 5095 6983
 2007 6055 8322
11 Investment in Max 2003 1880 2142
 tangible fixed assets 2004 1858 2811
 (per capita) 2005 2508 3781
 2006 3386 4227
 2007 3887 5599
12 Own-account Max 2003 885.0 1146.2
 construction work 2004 904.6 1238.7
 carried out within 2005 1319.6 1512.4
 the country (per 2006 1786.1 2017.2
 capita) 2007 2556,7 2794,4
13 Dwellings Max 2003 0.102 0.122
 completed (per 2004 0.117 0.194
 capita) 2005 0.101 0.218
 2006 0.106 0.189
 2007 0,164 0,214
14 Registered Min 2003 103 144
 criminal offences 2004 165 204
 (misdemeanors per 2005 135 181
 100000 inhabitants) 2006 122 168
 2007 104 168

No Criterion Regions
 Klaipeda Marijampole Panevezys

1 Population -0.237 -1.194 -3.906
 migration (net -1.145 -3.395 -5.143
 migration) per 1000 -1.429 -3.759 -4.583
 inhabitants -0.662 -2.975 -3.746
 0,248 -2,715 -4,282
2 Municipal budget's 1.156 1.126 1.110
 revenue (average 1.337 1.294 1.294
 amount per capita) 1.418 1.350 1.353
 1.683 1.588 1.535
 1,753 1,722 1,688
3 Municipal budget's 129.40 161.56 142.07
 expenditure 187.34 211.54 189.41
 (average amount, 201.37 213.89 207.13
 social security) 228.30 239.30 222.83
 139,93 149,35 160,06
4 Unemployment 12.5 7.5 11.4
 rate (%) 12.7 6.9 12.6
 7.0 3.0 10.8
 6.8 2.6 8.0
 4,1 2,0 6,5
5 Average gross 1060 847 940
 monthly earnings 1125 914 1016
 1256 1001 1094
 1474 1195 1258
 1765 1420 1507
6 Average useful floor 21.0 22.4 25.3
 space per capita 21.3 22.6 25.5
 21.5 22.7 25.8
 21.7 23.0 27.0
 22,0 23,2 27,3
7 Number of 96 83 97
 pre-school 97 84 97
 establishments 102 95 105
 (places per 100 103 97 108
 children) 101 97 110
8 Number of schools 3.06 3.15 3.50
 (per 1000 of 2.49 2.91 2.82
 students) 2.59 3.01 2.97
 2.69 3.18 2.97
 2,76 3,27 3,10
9 Animal products 772 770 680
 recalculated in 812 717 681
 terms of milk (100 727 759 627
 kg per 100 ha of 747 782 637
 agricultural land) 780 827 684
10 Indicators of activity 5044 5990 3783
 of retail trade 5706 6248 4378
 enterprises (per 6490 7024 5076
 capita) 7387 7773 5881
 8720 9144 7000
11 Investment in 2431 1403 1926
 tangible fixed assets 3862 1701 2204
 (per capita) 6442 2007 2362
 6088 3445 3159
 7025 3852 5239
12 Own-account 1416.6 797.8 693.3
 construction work 1711.7 901.7 1047.3
 carried out within 2483.8 958.9 1124.6
 the country (per 3097.3 1725.3 1509.1
 capita) 4197,4 1771,3 2405,3
13 Dwellings 0.090 0.059 0.070
 completed (per 0.138 0.081 0.095
 capita) 0.176 0.079 0.079
 0.207 0.058 0.061
 0,187 0,122 0,082
14 Registered 181 90 213
 criminal offences 336 145 265
 (misdemeanors per 270 116 196
 100000 inhabitants) 200 118 157
 177 114 145

No Criterion Regions
 Siauliai Taurage Telsiai Utena

1 Population -5.303 -2.285 -3.467 -3.806
 migration (net -5.664 -4.279 -4.794 -4.610
 migration) per 1000 -5.688 -5.917 -5.474 -4.604
 inhabitants -4.031 -3.908 -2.832 -3.090
 -6,194 -5,550 -4,003 -4,375
2 Municipal budget's 1.120 1.135 1.098 1.237
 revenue (average 1.278 1.299 1.284 1.418
 amount per capita) 1.351 1.415 1.372 1.526
 1.621 1.684 1.603 1.681
 1,792 1,816 1,731 1,873
3 Municipal budget's 154.58 205.50 178.54 146.71
 expenditure 209.50 234.53 212.59 188.25
 (average amount, 218.50 238.87 221.18 196.59
 social security) 254.42 271.66 260.04 221.83
 173,92 195,97 153,17 156,32
4 Unemployment 16.9 9.5 12.5 15.3
 rate (%) 12.6 8.9 10.3 12.3
 10.1 6.0 7.9 6.0
 5.7 4.2 5.6 5.9
 4,4 3,4 4,3 4,4
5 Average gross 871 807 1059 1111
 monthly earnings 958 859 1162 1145
 1049 936 1248 1231
 1239 1104 1432 1389
 1498 1332 1736 1621
6 Average useful floor 22.4 21.7 22.0 27.9
 space per capita 22.8 22.5 22.3 28.4
 23.1 22.7 22.6 28.7
 23.4 22.9 22.7 29.1
 23,7 23,2 23,0 29,5
7 Number of 95 82 83 108
 pre - school 97 96 84 102
 establishments 89 95 86 104
 (places per 100 98 98 90 103
 children) 97 91 88 104
8 Number of schools 3.80 3.29 3.75 3.75
 (per 1000 of 3.37 3.31 3.47 3.47
 students) 3.14 3.43 3.34 3.41
 3.24 3.49 3.29 3.58
 3,37 3,51 3,35 3,71
9 Animal products 648 741 700 693
 recalculated in 641 741 733 714
 terms of milk (100 616 656 637 639
 kg per 100 ha of 631 740 693 632
 agricultural land) 653 838 709 697
10 Indicators of activity 3854 3099 3614 3833
 of retail trade 4133 3389 3938 4002
 enterprises (per 4866 3798 4334 4533
 capita) 5694 4434 4931 5259
 6783 5700 5733 6169
11 Investment in 1212 1036 2604 1571
 tangible fixed assets 1790 1136 2301 2928
 (per capita) 2094 1268 2783 3378
 3139 1865 4375 2787
 3925 2363 9811 3655
12 Own-account 676.6 758.8 915.5 1060.5
 construction work 814.2 552.7 915.3 1552.5
 carried out within 906.7 795.3 1032.0 1553.8
 the country (per 1556.5 1025.3 1632.5 1647.5
 capita) 1990,5 1620,9 2697,6 1992,9
13 Dwellings 0.074 0.058 0.061 0.060
 completed (per 0.085 0.099 0.076 0.060
 capita) 0.057 0.069 0.078 0.061
 0.091 0.042 0.073 0.063
 0,102 0,058 0,083 0,100
14 Registered 168 168 119 116
 criminal offences 272 276 158 198
 (misdemeanors per 208 252 149 165
 100000 inhabitants) 150 186 125 129
 148 175 107 132

No Criterion Regions
 Vilnius

1 Population 2.996
 migration (net 2.397
 migration) per 1000 2.185
 inhabitants 2.288
 2,984
2 Municipal budget's 1.028
 revenue (average 1.199
 amount per capita) 1.313
 1.552
 1,583
3 Municipal budget's 113.21
 expenditure 183.69
 (average amount, 196.81
 social security) 221.91
 148,86
4 Unemployment 11.7
 rate (%) 11.1
 8.6
 5.0
 4,5
5 Average gross 1249
 monthly earnings 1328
 1487
 1734
 2076
6 Average useful floor 23.0
 space per capita 23.7
 24.3
 24.5
 24,9
7 Number of 98
 pre - school 98
 establishments 96
 (places per 100 96
 children) 94
8 Number of schools 3.06
 (per 1000 of 2.65
 students) 2.72
 2.84
 2,91
9 Animal products 653
 recalculated in 630
 terms of milk (100 583
 kg per 100 ha of 612
 agricultural land) 645
10 Indicators of activity 7563
 of retail trade 8654
 enterprises (per 10458
 capita) 12766
 15002
11 Investment in 3955
 tangible fixed assets 5686
 (per capita) 7179
 7362
 10666
12 Own-account 2026.8
 construction work 2252.1
 carried out within 2620.0
 the country (per 3432.2
 capita) 4821,6
13 Dwellings 0.312
 completed (per 0.446
 capita) 0.382
 0.535
 0,696
14 Registered 237
 criminal offences 370
 (misdemeanors per 332
 100000 inhabitants) 315
 233

Table 3. Te values of the criteria describing economic and social
development of Lithuanian regions for 2007 expressed as ranks

 Regions
Criterion Alytus Kaunas Klaipeda

Population migration (net migration) 8 3 2
per 1000 inhabitants
Municipal budget's revenue (average 4 8 5
amount per capita)
Municipal budget's expenditure 8 10 9
(average amount, social security)
Unemployment rate (% ) 2 5 4
Average gross monthly earnings 6 4 2
Average useful floor space per capita 3 7 10
Number of pre--school establishments 1 10 4
(places per 100 children)
Number of schools (per 1000 of 7 10 9
students)
Animal products recalculated in 6 5 3
terms of milk (100 kg per 100 ha of
agricultural land)
Indicators of activity of retail trade 8 4 3
enterprises (per capita)
Investment in tangible fixed assets 7 4 3
(per capita)
Own-account construction work 5 3 2
carried out within the country (per
capita) 4 2 3
Dwellings completed (per capita )
Registered criminal offences 1 7 9
(misdemeanors per 100000
inhabitants)

 Regions
Criterion Marijampole Panevezys

Population migration (net migration) 4 6
per 1000 inhabitants
Municipal budget's revenue (average 7 9
amount per capita)
Municipal budget's expenditure 6 3
(average amount, social security)
Unemployment rate (% ) 1 10
Average gross monthly earnings 9 7
Average useful floor space per capita 7 2
Number of pre--school establishments 5,5 2
(places per 100 children)
Number of schools (per 1000 of 5 6
students)
Animal products recalculated in 2 8
terms of milk (100 kg per 100 ha of
agricultural land)
Indicators of activity of retail trade 2 5
enterprises (per capita)
Investment in tangible fixed assets 8 5
(per capita)
Own-account construction work 9 6
carried out within the country (per
capita) 5 9
Dwellings completed (per capita )
Registered criminal offences 3 5
(misdemeanors per 100000
inhabitants)

 Regions
Criterion Siauliai Taurage Telsiai

Population migration (net migration) 10 9 5
per 1000 inhabitants
Municipal budget's revenue (average 3 2 6
amount per capita)
Municipal budget's expenditure 2 1 5
(average amount, social security)
Unemployment rate (% ) 7,5 3 6
Average gross monthly earnings 8 10 3
Average useful floor space per capita 5 7 9
Number of pre--school establishments 5,5 8 9
(places per 100 children)
Number of schools (per 1000 of 3 2 4
students)
Animal products recalculated in 9 1 4
terms of milk (100 kg per 100 ha of
agricultural land)
Indicators of activity of retail trade 6 10 9
enterprises (per capita)
Investment in tangible fixed assets 6 10 2
(per capita)
Own-account construction work 8 10 4
carried out within the country (per
capita) 6 10 8
Dwellings completed (per capita )
Registered criminal offences 6 8 2
(misdemeanors per 100000
inhabitants)

 Regions
Criterion Utena Vilnius

Population migration (net migration) 7 1
per 1000 inhabitants
Municipal budget's revenue (average 1 10
amount per capita)
Municipal budget's expenditure 4 7
(average amount, social security)
Unemployment rate (% ) 7,5 9
Average gross monthly earnings 5 1
Average useful floor space per capita 1 4
Number of pre--school establishments 3 7
(places per 100 children)
Number of schools (per 1000 of 1 8
students)
Animal products recalculated in 7 10
terms of milk (100 kg per 100 ha of
agricultural land)
Indicators of activity of retail trade 7 1
enterprises (per capita)
Investment in tangible fixed assets 9 1
(per capita)
Own-account construction work 7 1
carried out within the country (per
capita) 7 1
Dwellings completed (per capita )
Registered criminal offences 4 10
(misdemeanors per 100000
inhabitants)

Table 4. Weights (significances) [[omega].sub.i] of the criteria

No 1 2 3 4 5 6

[[omega].sub.i] 0.0089 0.0744 0.0501 0.0128 0.0163 0.1091

No 7 8 9 10 11 12

[[omega].sub.i] 0.0744 0.0744 0.0501 0.0250 0.2030 0.1867

No 13 14

[[omega].sub.i] 0.1059 0.0089

Table 5. Te results obtained in multicriteria evaluation of social
and economic development of Lithuanian regions in 2003-2007

 Region
Method Criterion Alytus Kaunas Klaipeda Marijampole

2003 m
SAW [S.sub.j] 0.0986 0.1020 0.1088 0.0867
 Rank 5 3 2 8
TOPSIS [C.sub.j.sup.*] 0.237 0.335 0.412 0.115
 Rank 5 3 2 8
COPRAS [Z.sub.j] 0.0985 0.1020 0.1088 0.0863
 Rank 5 3 2 8
2004
SAW [S.sub.j] 0.0894 0.1026 0.1168 0.0843
 Rank 6 4 2 8
TOPSIS [C.sub.j.sup.*] 0.187 0.370 0.517 0.149
 Rank 7 4 2 8
COPRAS [Z.sub.j] 0.892 0.1026 0.1168 0.0844
 Rank 6 4 2 8
2005
SAW [S.sub.j] 0.0914 0.1070 0.1355 0.0840
 Rank 5 3 2 8
TOPSIS [C.sub.j.sup.*] 0.225 0.430 0.703 0.124
 Rank 5 3 2 8
COPRAS [Z.sub.j] 0.0914 0.1070 0.1335 0.0840
 Rank 5 3 2 8
2006
SAW [S.sub.j] 0.0931 0.1016 0.1259 0.0906
 Rank 4 3 2 6
TOPSIS [C.sub.j.sup.*] 0.250 0.375 0.601 0.228
 Rank 5 3 2 6
COPRAS [Z.sub.j] 0.0931 0.1017 0.1260 0.0906
 Rank 4 3 2 6
2007
SAW [S.sub.j] 0.0928 0.0990 0.1149 0.0854
 Rank 5 4 2 8
TOPSIS [C.sub.j.sup.*] 0.217 0.3321 0.482 0.144
 Rank 6 4 2 9
COPRAS [Z.sub.j] 0.0928 0.0991 0.1149 0.0854
 Rank 5 4 2 8

 Regions
Method Criterion Panevezys Siauliai Taurage Telsiai

2003 m
SAW [S.sub.j] 0.0893 0.0810 0.0799 0.0989
 Rank 7 9 10 4
TOPSIS [C.sub.j.sup.*] 0.197 0.078 0.082 0.330
 Rank 7 10 9 4
COPRAS [Z.sub.j] 0.0893 0.0810 0.0799 0.0990
 Rank 7 10 4
2004
SAW [S.sub.j] 0.0901 0.0823 0.0756 0.0861
 Rank 5 9 10 7
TOPSIS [C.sub.j.sup.*] 0.228 0.142 0.081 0.212
 Rank 5 9 10 6
COPRAS [Z.sub.j] 0.0902 0.0824 0.0756 0.0881
 Rank 5 9 10 7
2005
SAW [S.sub.j] 0.0856 0.0770 0.0735 0.0856
 Rank 6-7 10 6-7
TOPSIS [C.sub.j.sup.*] 0.173 0.113 0.071 0.199
 Rank 7 9 10 6
COPRAS [Z.sub.j] 0.0856 0.0771 0.0735 0.0856
 Rank 6-7 9 10 6-7
2006
SAW [S.sub.j] 0.0849 0.0870 0.0732 0.0929
 Rank 9 8 10 5
TOPSIS [C.sub.j.sup.*] 0.186 0.193 0.077 0.292
 Rank 9 7 1
COPRAS [Z.sub.j] 0.0849 0.0871 0.0732 0.0930
 Rank 9 8 10 5
2007
SAW [S.sub.j] 0.0913 0.0834 0.0742 0.1077
 Rank 6 9 10 3
TOPSIS [C.sub.j.sup.*] 0.244 0.187 0.075 0.463
 Rank 5 8 10 3
COPRAS [Z.sub.j] 0.0912 0.0834 0.0742 0.1077
 Rank 6 9 10 3

 Regions
Method Criterion Utena Vilnius

2003 m
SAW [S.sub.j] 0.0955 0.1597
 Rank 6 1
TOPSIS [C.sub.j.sup.*] 0.211 0.895
 Rank 1
COPRAS [Z.sub.j] 0.0955 0.1597
 Rank 6 1
2004
SAW [S.sub.j] 0.1056 0.1651
 Rank 3 1
TOPSIS [C.sub.j.sup.*] 0.382 0.918
 Rank 3 1
COPRAS [Z.sub.j] 0.1056 0.1650
 Rank 3 1
2005
SAW [S.sub.j] 0.0997 0.1606
 Rank 4 1
TOPSIS [C.sub.j.sup.*] 0.322 0.922
 Rank 4 1
COPRAS [Z.sub.j] 0.0998 0.1606
 Rank 4 1
2006
SAW [S.sub.j] 0.0878 0.1628
 Rank 7 1
TOPSIS [C.sub.j.sup.*] 0.189 0.922
 Rank 8 1
COPRAS [Z.sub.j] 0.0878 0.1627
 Rank 7 1
2007
SAW [S.sub.j] 0.0967 0.1646
 Rank 7 1
TOPSIS [C.sub.j.sup.*] 0.155 0.915
 Rank 7 1
COPRAS [Z.sub.j] 0.0868 0.1646
 Rank 7 1

Table 6. The evaluation results obtained for 2007 by using the VS
method

Region 1 2 3 4 5 6 7 8

[V.sub.j] 70 82 68 73,5 83 85 91 76
Rank 2 7 1 5 8 9 10 6

Region 9 10

[V.sub.j] 70,5 71
Rank 3 4

Table 7. The ranks of Lithuanian regions obtained by using all
multicriteria evaluation methods

 Region
Year Alytus Kaunas Klaip?da Marijampole Panevezys

2003 5 3 2 8 7
2004 6 4 2 8 5
2005 5 3 2 8 7
2006 4 3 2 6 9
2007 5 4 2 8 6

 Region
Year Siauliai Taurage Telsiai Utena Vilnius

2003 9 10 4 6 1
2004 9 10 7 3 1
2005 9 10 6 4 1
2006 8 10 5 7 1
2007 9 10 3 7 1

Table 8. The development of Lithuanian regions in 2004-2007 according
to their stability and growth rate

Region Alytus Kaunas Klaipeda Marijampole Panevezys

The value 0.204 0.285 0.500 0.142 0.161
of [P.sub.j]

Rank based 5-6 3 2 8 7
on growth
rate and
stability

Region Siauliai Taurage Telsiai Utena Vilnius

The value 0.114 0.100 0.230 0.200 1.000
of [P.sub.j]

Rank based 9 10 4 5-6 1
on growth
rate and
stability