31 10 3494 https://omeka.ibu.edu.ba/files/original/ca864cf69562c308873bf60df189a1ed.pdf 190cbefc1b2bc6797993c990e2dfe798 PDF Text Text 1. International Symposium on Sustainable Development, June 9-10 2009, Sarajevo Analysing Business Competition by Using AHP Weighted TOPSIS Method: An Example of Turkish Domestic Aviation Industry Halil ZAĐM Faculty of Economics and Administrative Sciences, Fatih University, Istanbul, halilzaim@fatih.edu.tr Mehmet ŞANAL Faculty of Economics and Administrative Sciences, Fatih University, Istanbul, msanal@fatih.edu.tr Nuri Gökhan TORLAK Faculty of Economics and Administrative Sciences, Fatih University, Istanbul, gtorlak@fatih.edu.tr Selim ZAĐM Faculty of Economics and Administrative Sciences, Fatih University, Istanbul, szaim@fatih.edu.tr Abstract: The article uses AHP weighted TOPSIS multi-methodological approach in the Turkish domestic aviation industry. It starts by describing exceedingly complex nature of competition in the sector. Then, it deals with the constituent parts of the research methodology and the eclectic approach itself. The implementation of AHP weighted TOPSIS method reveals the ranking of major air carriers in light of key success variables in the sector. Keywords: strategy, AHP weighted TOPSIS, multi-methodology, TOPSIS. 1. Introduction The purpose of this article is to apply AHP weighted TOPSIS approach to the Turkish domestic aviation sector in order to rank air carriers according to their relative closeness coefficient on the basis of criteria that are most critical to success and prosperity in the industry. This analysis provides useful information for airline companies about evaluating their objectives and strategies. To reach this end, in the first section the article initially describes the nature of rising competition in the Turkish domestic aviation industry that became a menace to the survival of firms during the period 2003-2007 as well as provides brief information about the chief characteristics of major domestic air carriers in the sector. The next section, called background information about research methodology, explains AHP weighted TOPSIS method, namely analytic hierarchy process (AHP) method, and the traditional TOPSIS method, and then proposed AHP weighted TOPSIS method. We assume that this multi-methodological AHP weighted TOPSIS approach with its wide-ranging applications meet the requirements of survival volatile environments like aviation industry Then the following section, called the application of the AHP weighted TOPSIS method, undertakes a real industry case from a comparative perspective that provides full and invaluable data for airline companies in the sector so that they should review their goals, strategies, plans, and programmes. Conclusion is provided in the final section. 2. The Nature of Turkish Domestic Aviation Industry Although the Turkish aviation sector has been negatively affected by the political and financial crises, it has continued its progress in the long term with the growth of economy, liberalisation, globalisation, developing international trade, lowering prices, and expanding service net. This sector’s climax was the terrorist attack in 9/11 2001 in the U.S. The aviation sector was globally harmed due to this attack that gave rise to the bankruptcy of some prominent airline companies. While the aviation sector was trying to recover itself, it was damaged again by Gulf War and SARS illness in the Far East Asia in 2003. But, Iraqi War was shorter than expected and SARS was taken under control, so aviation sector got into growing trend in 2004. The high performance of the Turkish economy in recent years, the rising numbers of tourists coming to Turkey, the lower prices of the private airline companies after the tax cut on flight prices in 2004 accelerated the 207 �1. International Symposium on Sustainable Development, June 9-10 2009, Sarajevo Turkish aviation transportation to the sector. Though the domestic passenger number was 8, 7 million in 2002, it rose to nearly 20 million in 2005. This number was 38 percent more than the number in 2004. By 2006, the Turkish aviation sector had 204 passenger planes, 24 cargo planes and capacity of 38 thousand passengers. Although the Turkish Airlines had domestic flights from two airports to 25 scheduled domestic points in 2003, the flights today are from seven airports by five airline companies to 38 points. If we bear in mind the Turkey’s advantageous geographical condition, interregional trade development, and the improvement efforts in tourism, the Turkish aviation sector which has a current growing trend is expected to continue its expansion process. Turkey due to its geographical location acts like a point of passing between Europe, Middle East, and Asia. Improvements in recent years as well as Turkey’s liberal policies and bilateral agreements have turned this hectic geographical area to a special centre for passenger and cargo transportation. However there are still 70 idle airports nationwide that can be opened to air traffic in Turkey. In particular, in the East part of Turkey the number of unused airports is high due to the topographic structure of this region. In a short time, the increasing need for air transportation would bring these airports in use and provide important benefits for Turkey. In terms of competition in the Turkish Domestic Air Transportation after the privatisation of Turkish Airlines in 2003 the number of passengers in Domestic Air Transportation was noticeably increased. This led to new air carriers enter the aviation sector and the competition became severe. The slogan of “Every Turk will try plane at least once” became popular in the Domestic Air Transportation. In relation with the incentive policy to make the domestic flights attractive and to bring activity to regional airports there has been a reduction in DHMI (Government Airport Service) tariffs, and a cut in private communication tax. Furthermore, the Ministry of Transport abolished the education contribution pay in 2003 and gave authorisation of domestic flights to the private airline companies. With this practice a couple of new carriers such as Fly Air, Onur Air, Pegasus Airlines, and Atlas Jet entered the market. As a consequence, a sudden change and a cutthroat competition developed in the sector. This increased the number of domestic passengers (Table 1). Private firms increased domestic flights by taking their licenses. Onur Air, Pegasus Airlines, and Atlas Jet became initial firms that took their licenses. Rank 1 2 3 4 Table 1: Number of Domestic Passenger Carried in 2006 Companies Number of Passenger Turkish Airlines 8.857.000 Onur Air 4.400.267 Atlas Jet 2.982.712 Pegasus 1.818.989 3. Background Information about Research Methodology This section briefly describes the analytic hierarchy process (AHP) technique, and the TOPSIS method, and proposed AHP weighted TOPSIS method. 3.1. The Analytic Hierarchy Process (AHP) Methodology The analytic hierarchy process (AHP) methodology, which was developed by Saaty (1980), is a powerful tool in solving complex decision problems. The AHP helps the analysts to organize the critical aspects of a problem into a hierarchical structure similar to a family tree. By reducing complex decisions to a series of simple comparisons and rankings, then synthesizing the results, the AHP not only helps the analysts to arrive at the best decision, but also provides a clear rationale for the choices made (Chin et al., 1999). In AHP approach, the decision-maker is required to provide his preferences by pairwise comparisons, with respect to the weights and scores (Chu and Lin, 2003). 3.2. The TOPSIS Method TOPSIS method is a technique for order preference by similarity to ideal solution (Hwang and Yoon, 1981). The ideal solution (also called positive ideal solution) is a solution that maximizes the benefit criteria/attributes and minimizes the cost criteria/attributes, whereas the negative ideal solution (also called antiideal solution) maximizes the cost criteria/attributes and minimizes the benefit criteria/attributes. The so-called benefit criteria/attributes are those for maximization, while the cost criteria/attributes are those for minimization (Bellman and Zadeh, 1970). The best alternative is the one, which is closest to the ideal solution and farthest from the negative ideal solution. 208 �1. International Symposium on Sustainable Development, June 9-10 2009, Sarajevo 3.3. The Proposed AHP Weighted TOPSIS Method The basic steps of proposed AHP weighted TOPSIS method can be described as follows: Step 1. In the first step, a panel of decision makers (DMs) who are knowledgeable about airline selection and evaluation process is established. In a group that has K decision-makers (i.e. D1, D2, ..., Dk) are responsible for developing the hierarchical structure of the airline evaluation and selection. Then, using AHP technique, the normalized weights for each evaluation and selection criterion are determined. Step 2. In the second step, DMs evaluate the performance of each airline company with respect to each criterion to obtain a decision matrix.  x11 x X =  21  ...   xm1 x12 x22 ... xm 2 ... x1n  ... x2 n  ... ...   ... xmn  Step 3. After forming the decision matrix, normalized decision matrix is obtained as:  r11 r12 r r R =  21 22  ... ...  rm1 rm 2 ... r1n  ... r2 n  ... ...   ... rmn  Step 4. The weighted normalized decision matrix is computed by multiplying the importance weight of evaluation criteria and the values in the normalized decision matrix. Step 5. Then positive and negative ideal solutions are determined. Step 6. Then the distance of each alternative from positive and negative ideal solutions are calculated. Step 7. Then the closeness coefficient CC is determined. 4. The Application of AHP Weighted TOPSIS Method The application of the proposed algorithm is explained in the following steps. Step 1. In the first stage, a panel of ten DMs from various departments including purchasing, quality, and production and planning who are involved in Strategy process was formed. Based on semi-structured interviews with DMs, a list of nine Strategy Process criteria was generated. These criteria are related to various aspect of strategy ranging from Advertising Product Quality, Price Competitiveness, Customer Loyalty, Market Share, Customer Service, E-commerce, Management Experience, and Branding. The DMs were then asked to specify the relative importance of airline selection criteria using pairwise comparison scale. Then normalized weights for each criterion were obtained. These values are shown in Table 2. Table 2: Normalized Weights for each Evaluation Criteria standart Advertising 0.0417 Product Quality 0.2584 Price Competitiveness 0.1499 Customer Loyalty 0.1555 Market Share 0.0551 Customer Service 0.1396 E-commerce 0.0249 Management Experience 0.0981 Branding 0.0767 Total 1.0000 209 �1. International Symposium on Sustainable Development, June 9-10 2009, Sarajevo Step 2: In this step, we measure the performance of firms with respect to each strategy criterion. Table 3 shows the decision matrix of selection criteria. Table 3: Decision Matrix Advertising Product Quality Price Competitiveness Customer Loyalty Market Share Customer Service Ecommerce Management Experience Branding THY 5 5 3 4 5 5 5 5 5 Onur Air 2 2 4 2 3 1 3 2 1 Pegasus 3 3 5 3 4 3 4 4 3 Atlasjet 3 3 4 2 3 2 3 2 1 Step 3: In this stage, normalized decision matrix is obtained depending on whether the objective of selection criterion is that of minimization or maximization. Table 4 shows the normalized decision matrix. Table 4: Normalized Decision Matrix Turkish Airlines Onur Air Pegasus Atlasjet max max max max max max max max max Advertising Product Quality Price Competitiveness Customer Loyalty Market Share Customer Service Ecommerce Management Experience Branding 0.7293 0.2917 0.4376 0.4376 0.7293 0.2917 0.4376 0.4376 0.3693 0.4924 0.6155 0.4924 0.6963 0.3482 0.5222 0.3482 0.6509 0.3906 0.5208 0.3906 0.8006 0.1601 0.4804 0.3203 0.6509 0.3906 0.5208 0.3906 0.7143 0.2857 0.5714 0.2857 0.8333 0.1667 0.5000 0.1667 Step 4: Then weighted normalized decision matrix is calculated. The weighted normalized decision matrix for each selection criterion is shown in Table 5. Table 5: Weighted Normalized Decision Matrix THY Onur Air Pegasus Atlasjet Advertising Product Quality Price Competitiveness Customer Loyalty Market Share Customer Service Ecommerce Management Experience Branding 0.0304 0.0122 0.0183 0.0183 0.1885 0.0754 0.1131 0.1131 0.0554 0.0738 0.0923 0.0738 0.1083 0.0541 0.0812 0.0541 0.0359 0.0215 0.0287 0.0215 0.1117 0.0223 0.0670 0.0447 0.0162 0.0097 0.0130 0.0097 0.0701 0.0280 0.0561 0.0280 0.0639 0.0128 0.0384 0.0128 Step 5 and Step 6: The positive and negative ideal solutions are determined. Table 6 and 7 show the ideal solutions. Table 6: Positive Ideal Solution and its Distance for Each Alternative THY Onur Air Pegasus Atlasjet Advertising Product Quality Price Competitiveness Customer Loyalty Market Share Customer Service Ecommerce Management Experience Branding 0.0000 -0.0183 -0.0122 -0.0122 0.0000 -0.1131 -0.0754 -0.0754 -0.0369 -0.0185 0.0000 -0.0185 0.0000 -0.0541 -0.0271 -0.0541 0.0000 -0.0144 -0.0072 -0.0144 0.0000 -0.0894 -0.0447 -0.0670 0.0000 -0.0065 -0.0032 -0.0065 0.0000 -0.0421 -0.0140 -0.0421 0.0000 -0.0511 -0.0256 -0.0511 Step 7: The closeness coefficient CC is determined. As initial average weights were used in the TOPSIS calculations, the values of CC in Table 8 are considered as crisp TOPSIS results. Table 7: Negative Ideal Solution and its Distance for Each Alternative THY Onur Air Pegasus Atlasjet 210 Advertising Product Quality Price Competitiveness Customer Loyalty Market Share Customer Service Ecommerce Management Experience Branding 0.0183 0.0000 0.0061 0.0061 0.1131 0.0000 0.0377 0.0377 0.0000 0.0185 0.0369 0.0185 0.0541 0.0000 0.0271 0.0000 0.0144 0.0000 0.0072 0.0000 0.0894 0.0000 0.0447 0.0223 0.0065 0.0000 0.0032 0.0000 0.0421 0.0000 0.0280 0.0000 0.0511 0.0000 0.0256 0.0000 �1. International Symposium on Sustainable Development, June 9-10 2009, Sarajevo Table 8: Computations of AHP Weighted TOPSIS Method (CC) Firm CC THY Onur Air Pegasus Atlasjet 0.8211 0.0977 0.4631 0.2620 5. Conclusion In this study, the AHP weighted TOPSIS methodology has been employed as an alternative to the conventional TOPSIS approach. When AHP weighted TOPSIS approach has been implemented, the Turkish Airlines has been identified as the most suitable company, Pegasus the runner-up, Atlasjet the third, and Onur Air the fourth (Table 8). This research finding indicated that the Turkish Airlines preserved its dominant role even after its privatization and new entrants in the domestic airline industry. It is worthy of noting that Pegasus though newly founded air carrier could intensify the competition in the sector and become a serious rival for the Turkish Airlines in the coming years. References Bellman, B.E., Zadeh, L.A. (1970). Decision-making in a fuzzy environment. Management Science 17 (4), 141–164. Chin, K. S., Chiu, S. , Tummala, V. M. R. (1999). An evaluation of success factors using the AHP to implement ISO 14001- based ESM, International Journal of Quality & Reliability Management, 16, 4, pp. 341-361. Chu, T. C., & Lin, Y. C. (2003). A fuzzy TOPSIS method for robot selection. The International Journal of Advanced Manufacturing Technology, 21, 284–290. Hwang, C.L. and Yoon, K. (1981). Multiple Attribute Decision Making: Methods and Applications. Berlin: Springer Saaty, T.L. (1980). The Analytical Hierarchy Process. Mc. Graw-Hill, New York, NY. 211 � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 193 Title A name given to the resource Analysing Business Competition by Using AHP Weighted TOPSIS Method: An Example of Turkish Domestic Aviation Industry Author Author ZAİM, Halil ŞANAL, Mehmet TORLAK, Nuri Gökhan ZAİM, Selim Abstract A summary of the resource. The article uses AHP weighted TOPSIS multi-methodological approach in the Turkish domestic aviation industry. It starts by describing exceedingly complex nature of competition in the sector. Then, it deals with the constituent parts of the research methodology and the eclectic approach itself. The implementation of AHP weighted TOPSIS method reveals the ranking of major air carriers in light of key success variables in the sector Date A point or period of time associated with an event in the lifecycle of the resource 2009-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 1030 Title A name given to the resource ANALYSIS AND CLASSIFICATION OF GERUNDS (Verbal Adverbs) IN RABIYA Author Author Arnaut , Alica Solak , Edina Abstract A summary of the resource. In this paper, we will try to analyse and classify gerunds. Traditionally, the term gerund in Latin and European grammars is often synonymous with gerundive. In Slavic languages, the distinction is made between gerund (verbal adverb) and gerundive (verbal adjective), which may have an adverbial function as well. Gerunds (verbal adverbs) are verbal forms that have certain features found in verbal nouns and verbs (voice, negation, forms of periphrastic conjugations, modifiers, complements, etc.). In the sentence, they function as adverbials for manner and time. Since the subject in the sentences may be expressed, and since they are semantic equivalents of dependent clauses in European languages, some Turkologists classify them as infinitve predicative (or quasipredicative) forms. One of the issues in contemporary Turkish language studies is gerund classification. Namely, there are other morpho-syntactic forms in Turkish that correspond to gerunds in terms of their function and semantics. They are, therefore, completely or partially classifed as such, without morphological criteria of the classification. These criteria are: they are formed by independent suffixes, they are impersonal and do not accept affixes for case, i.e. they cannot be declined. The examples necessary for the gerund analysis will be taken from Rabiya. Date A point or period of time associated with an event in the lifecycle of the resource 2012-05 Keywords Keywords. Conference or Workshop Item PeerReviewed P Philology. Linguistics Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 3613 Title A name given to the resource Analysis of ACE I/D polymorphism in Gorani population Author Author Buljubašić, Sanida Abstract A summary of the resource. Angiotensin converting enzyme (ACE) gene is 21 kb long gene that is located on chromosome 17q23. Protein coded by this gene, ACE enzyme causes conversion of inactive angiotensin I to active angiotensin II that presents key component of Renin Angiotensin System(RAS) that is known to functions in control of blood pressure and balance of fluids and salts in the body. ACE also increases degradation of bradykinin. It has been shown that ACE gene contains a polymorphism based on the presence (insertion [I]) or absence (deletion [D]) of 287 bp Alu sequence in intron 16. Accordingly, it leads to the generation of three genotypes: deletion homozygotes (DD), insertion homozygotes (II), and heterozygotes (ID). Studies have identified correlation between ACE polymorphism and different diseases as well as correlation between one of three genotypes and sport performance. The main aim of this study was to identify genotype and allele frequencies of ACE gene in Gorani population. Comparison of these results to the results of other population studies on ACE polymorphismswe aimed to understand genotype composition of studied population as well as to see if ACE gene presents suitable genetic marker that could be used in population studies. Genotypes of hundred unrelated individuals were determined by using method initially described by Rigat et al (1992). As overamplification of D allele can cause ID genotype mistyping, DD individuals were subjected to second PCR in which presence or absence of I allele was controlled. Results of the first and second PCR were detected by 2% and 1,5 % gel electrophoresis, respectively. Results of ACE testing revealed that Gorani population is in Hardy Weinberg equilibrium, where the most common genotype is ID(63%), followed by DD (20%) and II (17%) genotypes. When results of present study where compared to other population studies, the highest correlation was observed with Hungarian, Croatian, Serbian and Turkish populations. MDS plot as well as dendrogram revealed grouping of population according to geographical position, being more reliable based on continental distribution. Keywords: ACE gene, ACE polymorphism, Gorani population, Polymerase Chain Reaction, MDS, Dendrogram Date A point or period of time associated with an event in the lifecycle of the resource 2016 Keywords Keywords. Thesis NonPeerReviewed Q Science (General) https://omeka.ibu.edu.ba/files/original/eaf79b7d37d59b6a8bb6653589e9062f.pdf c8abccba35336bd0c4657d66a8693bfe PDF Text Text 2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Analysis of Development Indicators in Balkan Countries Fatih ÇELEBĠOĞLU Dumlupınar University Faculty of Economics and Administrative Sciences Department of Economics, Kutahya, TURKEY fcelebi@dumlupinar.edu.tr Phone: +90 274 265 20 31 (ext.2206) Fax: +90 274 265 21 97 Abstract: Since the collapse of socialism, Balkan countries have been changing as social, economic and politic structure. Some former socialist countries (Bulgaria, Slovenia and Romania) and Greece became full member of EU. Some Balkan countries (Serbia, Montenegro, Croatia, Bosnia-Herzegovina, and Macedonia) lived difficult war years. After the wars, they have started to struggle for economic, social and political reconstruction process. Each country in Balkan Peninsula wants bigger real per capita income, better welfare level, and generally become a developed country. But these countries have some political, economic and social problems in development process. The aim of this paper is to analysis Balkan countries in terms of development indicators such as education, population, national income and income distribution in 2000s. Moreover, new suggestions will be offered to accelerate development process at the end of paper. Key Words: Balkan Countries, Development, Development Indicators Introduction Balkan Peninsula (South Eastern Europe) is an important area because of witness historic and politic experiences and incidents for ages. But it has been living historical alteration in recent decades. Although some Balkan countries (such as Turkey and Greece) were relatively stable in 1990s, there was war in Serbia, Montenegro, Croatia, Bosnia Herzegovina, and Macedonia. Some former socialist countries (Bulgaria, Slovenia and Romania) and Greece became full member of EU. The others have been struggling for this aim. In spite of Kosovo declared of independence in 2008, many countries haven‘t been accepting this situation. Nevertheless Balkan Peninsula is living relatively stable condition nowadays, compare with last ten years. Whole Balkan Countries, especially gain independence in recent decade, wants to become rapidly developed country. But all Balkan countries have some political, economic and social problems in this process. After a long war and unstable political period, Balkans has taken an opportunity about their development process nowadays. This region has been gaining stable structure overtime and this stable period has been supporting development indicators. In this paper, Balkan countries are being analyzed in terms of development indicators such as education, population, national income and income distribution in 2000s. Moreover, new suggestions will be offered to accelerate development process at the end of paper. This paper is organized as follows: the next section explains concept of development. Section 3 investigates indicators of development by using statistic data in this peninsula. Section 4 gives an analysis of development indicators for these countries. Section 5 offers some suggestions to accelerate development process. The last section provides some concluding remarks. Concept of Development34 After World War II, one of the important debating subjects is development. But generally development concept is accepted as a problem of underdeveloped countries. Underdeveloped countries don‘t perform industrial revolution, don‘t experience changing that it‘s bringing, and don‘t fulfill necessities of development process. Development is being used sometimes instead of concepts as improvement, modernization, structural changing, and industrialization. This semantic shift complicates definition of development concept. According to Peet and Hartwick (2009:1), development is better life for most people means, essentially, meeting basic needs: 34 According to Online Etymology Dictionary, Development concept used first time in 1756, "an unfolding, from develop + ment). Of property, with the sense "bringing out the latent possibilities" from 1885. Meaning "state of economic advancement" is from 1902. Meaning "advancement through progressive stages" is 1836. 254 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo sufficient food to maintain good health; a safe, healthy place in which to live; affordable services available to everyone; and being treated with dignity and respect. Other definition about development that is innovative changes resultant in socio-economic structure of a country. It can be understood from these definitions that development is related not only economic paradigm but also social life, health system, educational and vocational structure, democracy, freedoms, human rights etc. For this reason, it is multidimensional and it spreads very long time. Development is also related to economic growth. Stable economic growth process is very important for development. Unstable economic conditions affect negatively this process. In this point, being of stable economic structure is come into question. When being of stable economic structure, economic growth supports development process. This concept is more important for developing countries. For example, Turkey had big problems about unstable economic and political structure in 1970‘s and 1990‘s. Also, almost all Balkans lived unstable political and economic periods in 1990‘s. There are also new approaches to development concept. The most important of these is belonging to Amartya SEN that had Nobel Economy Prize in 1998. Amartya SEN (1993:3) defines development that ―as a process of expanding the real freedoms that people enjoy‖. Again according to SEN, development requires the removal of major sources of unfreedom: poverty as well as tyranny, poor economic opportunities as well as systematic social deprivation, neglect of public facilities as well as intolerance or overactivity of repressive states (Sen, 1993:3). The approach of SEN combines two important concepts: freedoms and development. Besides he recommends developing of freedoms before other indicators. Main Development Indicators For years many indicators have been used by economists in order to explain different level of development among countries. But which indicators are the best explanatories of level of development? We need to investigate indicators that are being used to explain development process by international institutions such as World Bank (especially World Development Indicators-WDI Online Database) and UN (United Nations, especially UNDP-United Nations Development Programme). World Bank uses more than 331 indicators from the World Development Indicators (WDI) covering 209 countries. This indicators take parts inside of 16 topics such as Agriculture & Rural Development, Infrastructure, Aid Effectiveness, Labor & Social Protection, Economic Policy and External Debt, Poverty, Education, Private Sector, Energy & Mining, Public Sector, Environment, Science & Technology, Financial sector, Social Development, Health, and Urban Development (for details look at The World Bank, WDI Online Database). UNDP calculates The Human Development Index (HDI). HDI includes some special data such as life expectancy at birth, adult literacy rates, gross primary-secondary and tertiary enrolment, GDP (gross domestic product) per capita (PPP - purchasing power parity- US$). HDI separates three subgroup as developed (high development), developing (middle development), and underdeveloped (low development) countries. According to Map 1, Africa, Middle East, South Asia and some South American countries have big problems in terms of level of human development. Especially in Africa, the level of human development is lower than other regions of the world. 0.950 and Over 0.900–0.949 0.850–0.899 0.800–0.849 0.750–0.799 0.700–0.749 0.650–0.699 0.600–0.649 0.550–0.599 0.500–0.549 0.450–0.499 0.400–0.449 0.350–0.399 under 0.350 not available Map 1: World map indicating the Human Development Index based on 2007 data, published on October 2009 Look at http://hdr.undp.org/en/, 25.04.2010 Again UNDP (United Nations Development Programme) uses to determine development level of each countries (particularly developing countries) eight topics as eradicate extreme poverty and hunger, achieve 255 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo universal primary education, promote gender equality and empower, reduce child mortality, improve maternal health, combat HIV/AIDS, malaria and other diseases, ensure environmental sustainability, and develop a global partnership for development in scope of Millennium Development Goals (for details look at UN - Millennium Development Goals 2009 Report). Besides each country collect some data on development by using international standards. Hundreds of variables are being used by official statistical institution for this reason. Mainly of these variables are per capita GDP, literacy rate, tertiary education, unemployment rate, urban population, population growth rate, public expenditure on education, number of doctor, electric power consumption, number of computer and internet user, final consumption expenditure, daily newspaper, fertility rate, foreign direct investment, life expectancy at birth etc… Also Human Development Index and Democracy Index35 are used to determine level of development in a country. The next section offers an analysis of development indicators in the Balkan countries by using some of these variables. Analysis of Development Indicators for Balkan Countries In this section, it will be investigated that situation of Balkans countries in terms of some indicators of development. But after the wars and unstable political period in the Balkans, some Balkan countries reached full independence in the different years. For this reason, we have data that has different initial year for each country (especially in 1990s). This problem has been almost solved in 2000s. But Kosovo‘s independence isn‘t being accepted by many countries. This situation complicates comparing all Balkan countries. According to UNDP statistics, all Balkan counties (exclude Slovenia and Greece) are inside of High Human Development classification. Slovenia and Greece are inside of Very High Human Development classification (UN, 2009). According to currently economic development literature, the best indicator of development is value of per capita GDP (Gross Domestic Product) in a country. Mostly Balkan countries have low per capita GDP. For example Albania has $1677 per capita GDP in 2007; Bosnia and Herzegovina has $2044; Bulgaria has $2401; Macedonia has $2061; Montenegro has $2269; Romania has $2595 and Serbia has $1780. Exclusively Greece ($15052), Croatia ($5794), Slovenia ($13333) and Turkey ($5053) have relatively bigger than aforementioned countries‘ per capita GDP (see Table 1). It is possible that global crisis in 2008-2009 and financial crisis in Greece can be changed this figures. GDP per Final consumption Literacy rate, adult Life expectancy at capita, (yearly, expenditure, etc. (% total (% of people ages birth, total (years) dollar) (2007) of GDP) (2007) 15 and above) (2007) (2007) Albania 1677 96.53 99.04 76.5 Bosnia & Herz. 2044 111.89 96.66 75.0 Bulgaria 2401 85.30 98.28 72.7 Croatia 5794 78.67 98.72 75.7 Greece 15052 87.52 97.08 79.7 Macedonia 2061 96.66 96.99 74.1 Montenegro 2269 113.81 .. 74.0 Romania 2596 82.77 97.60 72.6 Serbia 1780 98.95 .. 73.4 Slovenia 13334 69.86 99.68 77.7 Turkey 5053 83.47 88.66 71.8 Table 1: Basic Indicators of Development in Balkan Countries Note: Data comes from WDI Online Database The other important indicator of development is final consumption expenditure (% of GDP). High levels of final consumption expenditure (% of GDP) refer low level intermediate product expenditure, capital goods (% of GDP) in a country. According to table 1, we can say that especially Bosnia & Herzegovina, Montenegro, Serbia and partially Albania have high level final consumption expenditure. These countries have also low level saving rates. For this reason investment amount in these countries is lower than the other Balkan countries. 35 Look at Przeworski et al. (2000). They investigate relations between democracy and development. 256 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Literacy rates are very close to percent 100 (exclude Turkey). Turkey has percent (88.66). This figure shows that Turkey is the worst country in terms of literacy rate in the Balkans (see Table 1). Another important variable is life expectancy in birth. According to Table 1, Greece has the best figures with 79.7 years. Turkey has the lowest number with (71.8 years) (see Table 1). Life expectancy level in the Balkans (averagely) is lower than Euro area (80.4 years) and higher than world average (68.7 years). Population growth rate is very slow in the Balkans. Especially Bosnia & Herzegovina (-0.14), Bulgaria (-0.48), Croatia (-0.04), Romania (-0.16) and Serbia (-0.43) have negative level population growth figures (see Table 2). Others (exclude Turkey and Slovenia) have also figures very close to zero. This situation is dangerous process for next years. Demographic structure will be very old in the next decades. This can bring social security problems similarly Germany and the other West Europe countries. When table 2 is investigated in terms of foreign direct investment (FDI), we can see that Serbia (3.95) and Slovenia (3.34) have the best figures. Macedonia has the lowest number of FDI with (-0.01). The lowest value of per capita electric power consumption is in Albania with 976.1 kWh. The highest value is in Slovenia (7123.5 kWh). Greece has the second best value of per capita electricity power consumption with 5372.1 kWh. Unemployment, as percent of total labor force, is an important indicator of economic development. Macedonia (percent 36.02) and Bosnia & Herzegovina (31.09) have very high unemployment figures in 2006. Third high level unemployment figure is in Serbia with percent (20.84). But global crisis can be changed these figures in Balkan countries as generally world. For example, unemployment figure is percent 14 in Turkey in 2009. Population growth (annual %) (2008) Foreign direct Electric power Unemployment, investment, net consumption (kWh total (% of total outflows (% of per capita) (2006) labor force) (2006) GDP) (2007) 0.35 0.14 976.1 .. Bosnia & Herz. -0.14 0.16 2382.4 31.09 Bulgaria -0.48 0.69 4311.3 8.94 Croatia -0.04 0.42 3635.8 11.13 Greece 0.40 1.68 5372.1 8.75 Macedonia 0.03 -0.01 3495.4 36.02 Montenegro 0.23 .. .. .. Romania -0.16 0.17 2401.6 7.22 Serbia -0.43 3.95 4040.4 20.84 Slovenia 1.05 3.34 7123.5 5.73 Turkey 1.24 0.32 2078.4 9.86 Albania Table 2: Basic Indicators of Development in Balkan Countries (Continued) Note: Data comes from WDI Online Database Income distribution is other considerable variable of development. The highest value of Gini index is in Turkey with (43.2). Macedonia (39.0), Bosnia & Herzegovina (35.8) and Greece (34.3) follow respectively Turkey. Croatia has the lowest value of Gini Index with (29.0). Beside share of poorest 10% of population in GDP is in Turkey with (1.9%). Again Turkey has the highest value in terms of share of richest 10% of population in GDP with (33.2%). The highest share of income in poorest 10% is in Croatia (3.6%) and the lowest share of income in richest 10% is also in Croatia with (23.1%). We can say that Croatia has the best figures in Balkans in terms of income equality (see Table 3). 257 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Share of income or expenditure (%) Greece Slovenia Croatia Bulgaria Romania Montenegro Poorest 10% 2.5 3.4 3.6 3.5 3.3 .. Richest 10% 26.0 24.6 23.1 23.8 25.3 .. Inequality measures Richest 10% to poorest Gini 10% Index 10.2 34.3 7.3 31.2 6.4 29.0 6.9 29.2 7.6 31.5 .. .. Serbia Albania Macedonia Bosnia & Herz. Turkey .. 3.2 2.4 2.8 1.9 .. 25.9 29.5 27.4 33.2 .. 8.0 12.4 9.9 17.4 .. 33.0 39.0 35.8 43.2 Table 3: Share of income or expenditure (%) and inequality measures in Balkan Countries in 2007. Note 1: The Gini index lies between 0 and 100. A value of 0 represents absolute equality and 100 absolute inequalities. Note 2: Data was compiled from UNDP Human Development Index Industrial production index is frequently used an indicator of development. When it is investigated industrial production index values of Balkan countries, Romania (120.6) has the highest value of industrial production index and Greece (101.1) has the lowest value (see Table 4). It is interesting that Serbia loses industrial production capacity, because Serbia has 113.1 index values in 1998, but Serbia has 108.6 score in 2007. Also Greece loses production capacity. Beside we haven‘t got Albania‘s index value. 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Albania 97.0 111.5 124.8 100.0 110.7 86.6 81.9 .. .. .. Bosnia & Herz. 53.7 59.3 64.8 72.8 79.6 83.3 94.4 100.0 107.4 117.3 Bulgaria .. .. 68.6 70.0 73.3 82.9 93.5 100.0 106.0 116.2 Croatia 80.5 79.5 80.7 85.5 89.7 92.7 95.6 100.0 104.1 109.3 Greece 95.1 95.1 100.8 98.7 99.3 99.8 100.8 100.0 100.8 103.4 Montenegro 91.4 84.4 87.6 87.0 87.5 89.6 101.9 100.0 101.0 101.1 Romania 76.3 74.4 97.0 100.8 100.9 100.5 102.9 100.0 109.3 120.6 Serbia 113.1 84.1 93.7 93.8 95.5 92.6 99.2 100.0 104.7 108.6 Slovenia 81.6 81.1 86.2 88.7 90.9 92.1 96.6 100.0 105.7 113.3 Turkey 77.8 74.9 79.4 72.5 79.4 86.3 94.7 100.0 105.8 110.6 Table 4: Industrial Production index (2005=100) in Balkan Countries Note: Data comes from UNECE Statistical Division Database, compiled from national and international (CIS, EUROSTAT, IMF, OECD) official sources. Only economic indicators are necessary, but not sufficient for comparison whole Balkan countries. For this reason we need other pointers. We investigate Human Development Index values and Democracy Index values for Balkan countries. Table 5 shows HDI ranks and values for Balkan countries in 2003 and 2009. The highest value is belonging to Greece with 0.892 and its rank in HDI is 24 in 2003. Again Greece has the highest values of human development index with (0.942) and its rank is 25 in the world in 2009. Turkey (0.806) has the lowest value of HDI in 2009 and its HDI rank is 79. When 2009 ranks are compared with 2003, Greece, Bulgaria, Macedonia, Bosnia & Herzegovina lose former position. But Croatia, Romania, Albania and Turkey obtain better position. 258 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Country Name HDI rank in 2003 Human development index value 2003 HDI rank in 2009 Human development index value 2009 Greece 24 0.892 25 0.942 Slovenia 29 0.881 29 0.929 Croatia Bulgaria 47 57 0.818 0.795 45 61 0.871 0.840 Romania 72 0.773 63 0.837 Montenegro - - 65 0.834 Serbia - - 67 0.826 Albania 95 0.735 70 0.818 Macedonia 60 0.784 72 0.817 Bosnia & Herz. 66 0.777 76 0.812 Turkey 96 0.734 79 0.806 Table 5: Situation of Balkan Countries in Human Development Index Values Note: Data was compiled from UNDP Human Development Report 2009 (calculating with 2007 values) and UNDP Human Development Report 2003 (calculating with 2001 values) Another important thing about development is democracy level in country. We can investigate democracy index to understand this relation. Democracy Index is calculated by The Economist Intelligence Unit based on the answers of 60 questions for 167 countries (EIU, 2008). According to Table 6, Greece is the strongest democracy in Balkans. The weakest democracy in the Balkans is Turkey. While Greece and Slovenia have full democracy; Albania, Bosnia & Herzegovina and Turkey have hybrid regime. This situation is generally parallel to economic development levels. Country Name Rank in the Index Kind of Democracy Score Greece 22 Full Democracy 8.13 Slovenia 30 Romania 50 51 Full Democracy Flawed Democracy 7.96 7.06 Flawed Democracy 7.04 52 Flawed Democracy 7.02 Serbia 63 Flawed Democracy 6.49 Montenegro 65 Flawed Democracy 6.43 Macedonia 72 Flawed Democracy 6.21 Albania 81 Hybrid Regime 5.91 Bosnia & Herz. 86 Hybrid Regime 5.70 Turkey 87 Hybrid Regime 5.69 Croatia Bulgaria Table 6: Democracy Index (2008) Note: Data comes from The Economist, Economist Intelligence Unit When Democracy Index (2008) values are accommodated in the Map 2 for each country, lighter colors show more democratic countries and darker areas represent authoritarian countries. Especially North America and West Europe have lighter colors. Africa, Middle East and Asia countries have mostly darker colors. Balkan countries have averagely values. 259 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Map 2: World Map Indicating the Democracy Index (2008) Look at http://en.wikipedia.org/wiki/Democracy_Index, 01.05.2010 After analysis of indicators that are belonging to Balkan countries, we offer to accelerate development process of Balkan countries some suggestions in the next section. Suggestions for Development Process of Balkan Countries When it is considered special position of Balkans (multi cultural, multi religion and multi ethnical), to offer new suggestions are quite difficult. Even so, we explain some suggestions for Balkan countries below: Stabilization Policy Balkans had important problems it‘s throughout history. Especially after Ottoman Empire, unstable politic and economic life started in all Balkan Peninsula. With together socialism, there was relatively stable politic and economic life. However, after collapse of socialism, again war, blood, tears and unstable politic and economic life came back in Balkans. Nowadays Balkans has been living more stable days. We know that development is closely related to stable politic and economic structure. For this reason, the first and the most important stage strengthen of stabilization process. To strengthen stabilization process; - European Union full membership process should be accelerated for Balkan countries that are not member of EU. By considering ethnic, religion and cultural structure of the region, bilateral goodwill (bona fides) agreements should be signed among countries. - Some countries in the region should play a part in this process as a mediator. For example, Turkey invited presidents of Bosnia & Herzegovina and Serbia to talk problems between two countries in the last April. - All Balkan countries should be invited international institutions. For example Bosnia & Herzegovina was invited to NATO in the last April 2010. Invitation of only Bosnia & Herzegovina is necessary, but it is not enough. For this reason, all Balkan countries that are not member of NATO should be invited. - By protecting cultural, ethnic and religion diversity, an interior peace law should be composed agreeable by different society parts. Trade Policy - EU trade policy should be accepted by all Balkan countries. Free trade should be improved in the Balkans. Tariffs and other arrangements should be reciprocally dropped. Visa applications should be facilitated to improve trade among Balkan counties for especially businessman and scientists. Bilateral trade agreements should be improved. 260 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo - Collective science, education and R&D agreements should be signed. Balkan Common Wealth that is including all Balkan countries should be established in the next time. Substructure of information and communication technologies should be developed. Goods and Service Production - Manufacture and service sectors should be supported by government. Productivity level of industry should be accrued. To support industrial production, it should be allowed to transfer of technology. Barriers in front of foreign direct investment should be decreased. The Others - - Tax system with progressive rates should be performed to decreasing Gini Index and social benefits of poor population should be improved. Banking system should be developed and its trustworthiness level should be boosted. Barriers for touristic travel should be diminished. Especially visa application should be facilitated. Countries that have insufficient capital for investment need foreign direct investment to accelerate of economic development. For this, it should be allowed foreign direct investment for whole sectors. Democratic reforms such as human rights, constitutional state, economic freedoms, freedom of thought should be performed particularly in Turkey, Albania and Bosnia & Herzegovina. The bigger part of budgets should be gone to education and productive investment. Conclusions When compare with developed countries, Balkan countries (exclude some full members of EU such as Greece and Slovenia) has important problems about economic development. Many countries in this region have less level GDP figures. Also human development and democratic level are not sufficient. Nowadays, Balkan Peninsula has some opportunities related to development process after the war and unstable politic and economic life. These opportunities can be realized forthcoming periods. But this is depends on better orientate and management of economic, politic and social processes. Besides protecting and improving of stabilization process will be important in the next decades. It is a reality that war and unstable politic and economic conditions encourage backwardness, poverty and anti-democratic applications of governments. Conversely peace, trade, stable politic and economic life cause better conditions for all nations in the Balkans. References http://data.worldbank.org/indicator, 22.04.2010 http://hdr.undp.org/en/, 25.04.2010 http://hdr.undp.org/en/statistics/, 18.04.2010 Online Etymology Dictionary, http://www.etymonline.com/index.php?search=develop&searchmode=none, 08.04.2010. Peet R. and Hartwick E. (2009) Theories of Development: Contentions, Arguments, Alternatives, 2nd edition, The Guilford Press, New York. Przeworski A. & Alvarez M.E. & Cheibub J.A. & Limongi F. (2000). Democracy and Development: Political Institutions and Well-Being in the World, 1950-1990. CambridgeUniversity Press. Sen A. (1999) Development as Freedom, Oxford University Press, New York. The Economist Intelligence Unit –EIU (2008), Democracy Index, http://graphics.eiu.com/PDF/Democracy%20Index%202008.pdf, 01.05.2010 The World Bank, WDI (World Development Indicators) Online Database 261 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo UN (2009), The Millennium Development Goals Report 2009, New York. UNDP (2003), Human Development Report 2003, Oxford University Press, New York. UNDP (2009), Human Development Report 2009, Palgrave Macmillan, New York. UNECE Statistical Division Database, http://www.unece.org/stats/stats_h.htm, 24.04.2010 262 � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 172 Title A name given to the resource Analysis of Development Indicators in Balkan Countries Author Author ÇELEBİOĞLU, Fatih Abstract A summary of the resource. Since the collapse of socialism, Balkan countries have been changing as social, economic and politic structure. Some former socialist countries (Bulgaria, Slovenia and Romania) and Greece became full member of EU. Some Balkan countries (Serbia, Montenegro, Croatia, Bosnia-Herzegovina, and Macedonia) lived difficult war years. After the wars, they have started to struggle for economic, social and political reconstruction process. Each country in Balkan Peninsula wants bigger real per capita income, better welfare level, and generally become a developed country. But these countries have some political, economic and social problems in development process. The aim of this paper is to analysis Balkan countries in terms of development indicators such as education, population, national income and income distribution in 2000s. Moreover, new suggestions will be offered to accelerate development process at the end of paper. Date A point or period of time associated with an event in the lifecycle of the resource 2010-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory https://omeka.ibu.edu.ba/files/original/f313800370077bf6c93cb34a4c7c1764.pdf 188822bd692fb155b5fd175fcf4cae38 PDF Text Text 3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo İbn Batuta Seyahatnamesi Seçmeler, Çev. İsmet Parmaksızoğlu, MEB Yay, İstanbul, 1993. www.sebilay.org.tr, (25.04.2012). Tuhfat-Al-Vasayâ. Analysis of Factors Affecting the Life Satisfaction of Household Heads Living in Urban Areas: A Case of West Mediterranean Region Ali Riza Aktas1, Burhan Ozkan2, Onur Oku1 1Akdeniz University, Alanya Faculty of Business, Economics and Finance Dept. 2Akdeniz University, Faculty of Agriculture, Agriculture Economics Dept. E-mails: alirizaaktas@akdeniz.edu.tr,bozkan@akdeniz.edu.tr,onuroku@akdeniz.edu.tr Abstract Since the early ages of history, individuals have sought life satisfaction and considered it as a life goal. Because of this fact, the term life satisfaction has kept its importance in time and has been the focus of many studies. Life satisfaction is seen as a positive value gained by an individual’s own evaluation of the quality of life as a whole, therefore may be described as subjective. Nevertheless, studies made about life satisfaction use both subjective and objective indicators. Life satisfaction is partially conceptualized as the result of satisfaction related to various life fields such as work, family, health, etc. and it is assumed that the effects of environmental conditions highly help satisfaction related with life fields. When studies about life satisfaction are taken into consideration, it is notable that the term job satisfaction is generally emphasized. However, studies show that job satisfaction can explain only a few of the changes in life satisfaction. In this study, it is aimed to determine the socioeconomic factors affecting the life satisfaction of household heads by using data from questionnaires and Logit model. “Unclustered Single-Stage Simple Random Probability Sampling Method” was used to apply the questionnaires to 490 household heads living in city centers of Antalya, Isparta and Burdur. In order to determine the probability of whether the household heads were satisfied with their lives or not, explanatory variables oriented to the current perceptions of household heads were included to the model in the study in addition to the demographic variables. Demographic variables were included to the model as the dummy 189 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo variable. Logit model was estimated by Maximum Likelihood Estimation method. According to the results of the analysis, life satisfaction of the household heads decreased with the increase of the size of the city. Similarly, increase in education level also decreased the probability of life satisfaction of the household heads. In addition, household heads with high income levels were happier than the ones with lower income. Similarly, if the spouse of the household head is either healthy, satisfied from job, or is a house wife, satisfied from marriage, then life satisfaction is determined to be higher than the household heads without the aforementioned spouse characteristics. Keywords: Satisfaction, Life Satisfaction, Household Head, Logit Model, West Mediterranean Region. 1. INTRODUCTION Life satisfaction, in its general sense, refers to the satisfaction felt by one with regard to his/her own life (Keser, 2005). In other words, it relates to which extent the person is pleased with the life he/she has (Guler and Emec, 2006). Life satisfaction is the emotional response of the person against the life defined as work, leisure and other non-work time and expresses a general attitude towards life (Dikmen, 1995; Keser, 2005). Life satisfaction is defined as “the positive perception of one’s own life according to the criteria determined by himself/herself” and as the conscious and cognitive perceptions of the person with respect to the quality of his/her own life (Gilman and Huebner, 2000). Life satisfaction is also described as the positive value obtained when the individual evaluates the quality of his/her life as a whole (Ozdevecioğlu and Aktas, 2007). Therefore, it is possible to say that life satisfaction is subjective in essence as it is the product of the evaluation conducted by the individual with regard to his/her own life. However, both subjective and objective indicators are employed in the studies relating to life satisfaction (Cetin et al., 2003). Objective indicators are related to external conditions such as income level, accommodation conditions and quality of such conditions, crime rates and accessibility of health services. Subjective indicators include personal emotions of the individual with regard to his/her life conditions (Gilman and Huebner, 2000). Life satisfaction is partially conceptualized as a result of the satisfaction in various spheres of life such as work, family and health and it is assumed that the impacts of environmental conditions on the life satisfaction substantially contribute to the satisfaction concerning the spheres of life (Rode, 2004). Life satisfaction demonstrates the result obtained from the comparison of the expectations of the individual and the actual situation and generally includes the entire life of the individual as well as the various dimensions of that life; that is, it expresses the satisfaction generally felt for the individual’s whole life rather than a certain situation (Sener, 2009). In the studies 190 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo concerning life satisfaction, it is remarkable that job satisfaction is generally emphasized regarding life satisfaction. Considering the fact that individuals in today’s world spend most of their time in the workplace, it may seem reasonable to accept the assumption that the life satisfaction of the individual is substantially affected by job satisfaction. Nevertheless, studies reveal that job satisfaction may explain approximately 5%-10% of the shifts in life satisfaction (Uyguc et al., 1998). While there are different views on the relation between life satisfaction and job satisfaction and on the direction of such relation, it is notable that no conclusive results could be obtained regarding whether the relation between the two variables is positive or negative or whether there exists a relation between them although many studies were conducted on life satisfaction-job satisfaction. (Uyguc et al., 1998). Considering the definitions regarding life satisfaction, it is possible to say that there exist many factors apart from job satisfaction that determine and affect the life satisfaction of individuals. It was found that life satisfaction is associated with factors such as possessing a meaningful life, enjoying life and having plenty of pursuits in life (Guler and Emec, 2006:131). On the other hand, factors including social connections, sexual activity, success, physical activity, interest in nature, reading or listening to music, nutrition or drink consumption make positive affective contributions to life satisfaction (Dockery, 2003). Some studies in the literature put forth that age, stress, physical health, life style and personality structure are among the basic determinants of life satisfaction (Chow, 2005). A consensus does not exist in the literature regarding the influence of income level on life satisfaction. Some studies emphasize the importance of the quality of social relations and relative insignificance of income on satisfaction. On the other hand, however, some other studies conclude that the income effect is significant for the level of life satisfaction (Dockery, 2003). This research studies the satisfaction level of household heads. City centres of Antalya, Isparta and Burdur were chosen as the research field and it was aimed to determine the socioeconomic factors that affect the satisfaction levels of household heads with the help of Logit model using the data obtained from questionnaire surveys conducted with household heads. 2. MATERIALS AND METHODOLOGY Main material of this study is the cross-sectional data obtained through questionnaire survey method from household heads living in the West Mediterranean Region urban area (AntalyaIsparta-Burdur). Furthermore, national and international studies, publications, statistics and reports prepared by various institutions and organizations concerning the research subject constitute other materials of this study. As to the determination of sample size, the study employed the “Unclustered Single-Stage Simple Random Sampling Method”, which is the most preferred method in consumption studies. Questionnaire surveys were conducted to 490 household heads. Ratios of households 191 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo of each province to the total number of households were taken into account in the distribution of the calculated sample size to the provinces. In this study, social and economic factors affecting the life satisfaction of household heads living in the urban centres of Antalya, Isparta and Burdur were analyzed using the Logit model. Dependent variable in the Logit model is discrete and the estimated probability values vary between 0 and 1. Another method that may be employed for this study is the Probit model. The basic discrepancy between the Logit and Probit models stems from the difference in assumptions regarding the probability distributions of the models. Though, no significant difference exists between the results obtained through these models (Green, 2002). On the other hand, the use of Logit model was preferred in this study as it is accepted that independent variables explain dependent variable better in the Logit model (Amemiya, 1983). The Logit model that is based on cumulative logistic probability function is expressed as follows (Gujarati, 2001): Pi  E (Y  1|X i )     X i Pi  E (Yi  1|X i )  1 1  e  (   X i ) 1  1  e  Zi [1] In the equation, Z i    X i where;  : constant,  : parameters to be estimated for each explanatory variable,  i : ith independent variable. P Equation [1] is named as the logistic distribution function and i denotes the probability of occurrence of the relevant incident. It becomes either zero or one as the result of the binary selection in the form of Yes/No. Z denotes the explanatory variables vector included in the model, whereas  and  denote the model parameters to be estimated. When the equation above is rearranged and natural logarithm of both sides of the equation is taken, the following equation is derived: 192 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo  P  Li  Ln i   Z i    1 X1  2 X 2  .........  n X n    1  Pi  [2] Z  Dependent variable in this regression model i expresses the natural logarithmic value of the ratio of choosing a certain option to choosing none. In other words, coefficients obtained from the Logit model expresses the probability of preferring an incident to not preferring it. “  ” was added to the equation as the error term of the model. As the dependent variable in this study, household heads who are satisfied with their lives as a whole are accepted as 1 and household heads that are included in other options than being satisfied are accepted as 0. In the determination of probabilities of household heads to be and not to be satisfied with their lives, demographic variables as well as explanatory variables regarding the current perception of household heads were included in the model. Demographic variables were included in the model as dummy variables. “I” variable represents the income group the household head belongs to, whereas “PR” and “EL” variables represent the province and educational level of the household head. Moreover, “HWS” variable represent the satisfaction felt by the household head for the housewife status of his spouse and “JS” variable represents the general job satisfaction level of the household head. Similarly, “HS” variable represents the satisfaction of the household head for his health status while “MS” variable represents the satisfaction level of the household head for his marriage. Factors affecting the life satisfaction of household heads living in urban areas are analyzed employing the Logit model. Here, the model in equation 2 is reexpressed according to the said explanatory variables. YM i    1IL1   2 IL2   3 ED1   4 ED2   5G1   6G 2   7 EM  8 SM  9 IM  10 EVM  ei [3] Codes regarding dependent and independent variables used in the Logit analysis are provided in Table 1. Logit model was estimated in Eviews 5.0 software employing the Maximum Likelihood Method. One of the most significant advantages of using this method is that the estimated parameters are consistent and efficient (Pindyck and Rubinfeld, 1991). 193 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Table 1. Variables Used in the Logit Model and Their Definitions Dependent Variable LSi 1 if the household head is generally satisfied with his life, otherwise=0 Independent Variables PR1 1 if the household head resides in the urban centre of Burdur, otherwise=0 PR2 1 if the household head resides in the urban centre of Isparta, otherwise=0 PR3 1 if the household head resides in the urban centre of Antalya, otherwise=0 (reference class) EL1 1 if the household head has an education level of primary education or lower, otherwise=0 EL 2 1 if the household head has an education level of high school or equivalent, otherwise=0 EL3 1 if the household head has an education level of college or higher, otherwise=0 (reference class) I1 1 if the household head has a total income lower than TL1250, otherwise=0 I2 1 if the household head has a total income between TL1250 and TL2500, otherwise=0 I3 1 if the household head has a total income higher than TL2500, otherwise=0 (reference class) HWS 1 if the spouse is housewife, otherwise=0 HS 1 if the household head is generally satisfied with his health status, otherwise=0 JS 1 if the household head is generally satisfied with his job, otherwise=0 MS 1 if the household head is generally satisfied with his marriage, otherwise=0 194 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo 3. DESCRIPTIVE STATISTICS Descriptive statistics regarding the data compiled from 490 household heads used in the analyses are provided. It demonstrates that 16% of household heads reside in Burdur, 18% in Isparta and 66% in Antalya. 39% of the household heads who participated in the research were found to have an educational level of college or higher, whereas 38% have an educational level of high school or equivalent and 23% have an educational level lower than high school or equivalent. 21% of household heads are included in the lowest income group and 53% are included in the highest income group. While the spouses of 47% of the household heads in the research region are housewives, those who stated that their spouses were not housewife were 53%. A great majority (72%) of the household heads stated that they were generally satisfied with their lives, whereas those who stated that they were dissatisfied were found to be 28%. Furthermore, 58% of the household heads in the research region stated that they were generally satisfied with their health status and 42% stated that they were generally dissatisfied with their current jobs. A great majority of the household heads who participated in the research stated that they were satisfied with their marriage (78%), whereas those who stated their dissatisfaction with their marriage were found to be 22%. 4. MODEL ESTIMATION RESULTS The estimated model has 78% accurate estimation of the opinions of household heads living in urban areas. Additionally, the Nagelkerke R Square value, which indicates the explanatory power of the model, was found to be 0.52. The Logit model generally defined in Equation [3] was estimated employing the variables summarized in Table 1 and the estimation results and whether the parameters are statistically significant are presented in Table 2. Table 2: Model Estimation Results Variables Coefficients Z-Value Level of Significance C -0.192 -0.518 0.6042 PR1 -0.733 -2.125 0.0336 PR2 -0.541 -1.659 0.993 EL1 -0.465 -1.350 0.1769 195 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo EL2 -0.617 -2.032 0.0421 I1 -0.938 -2.369 0.0178 I2 -0.552 -1.650 0.0989 HWS 0.482 1.685 0.0920 HS 1.031 4.025 0.0001 JS 0.804 2.818 0.0048 MS 2.319 7.917 0.0000 Nagelkerke R-Square 0.52 Model Accurate Estimation Ratio 0.73 According to the analysis results, all variables included in the model have the anticipated signs. In addition, all of the variables excluding EL1 and ISP were found to be statistically significant at 10% level of significance. According to the model estimation results, the household heads living in a larger city were found to be happier than those living in a relatively smaller city, in other words, it was found that the household heads living in Antalya are more likely to be satisfied with their lives than those living in Isparta and Burdur. According to research results, it is notable that the levels of life satisfaction of household heads decrease as their educational levels increase. The parameter related to the ED1 variable, which includes the household heads possessing the lowest educational level, was calculated as -0.46, which suggests that the household heads with low educational levels are more satisfied with their lives compared to household heads with higher educational levels. However, ED1 variable is not statistically significant. Another variable included in the model is income variable. Similarly, parameters regarding income variables were found to be negative and statistically significant. It was found that the household heads with higher levels of income were more satisfied with their lives compared to those with lower levels of income, in other words, there exists a linear relationship between the income level and life satisfaction of household heads. Parameters regarding housewife (HWS), job satisfaction (JS), health satisfaction (HS) and marriage satisfaction (MS) were found to be positive and statistically significant. In other words, it was found that those who were generally more satisfied with the housewife status of their wives, current job, health status and marriage were more satisfied with their lives. 196 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo 5. CONCLUSION This study analyzes the life satisfaction levels of household heads through the use of questionnaire survey data compiled from household heads living in urban areas. To that end, Logit model is estimated. It was found that life satisfaction decreases as the city in which the household head lives gets larger and similarly, the probability of household heads to be satisfied with their lives decreases as the level of education increases. Moreover, it was found that the household heads with higher levels of income were more satisfied with their lives than those with lower levels of income. Similarly, it was found that the household heads with housewife spouses, health status satisfaction, job satisfaction and marriage satisfaction were likely to be more satisfied with their lives compared to those who do not have such specific satisfactions. REFERENCES Amemiya, T., 1983. Advanced Econometrics. Cambridge, MA Harvard University. Chow, H.P.H., 2005. Life Satisfaction Among Universıty Students in a Canadian Prairie City: a Multivariate Analysis, Social Indicators Research, 70, ss. 139- 150. Cetin, M., Ebrinç, S., Başoğlu, C., Semiz, Ü.B., Çobanoğlu, N., Can, S. & Karaduman, F. 2003. Acemi Erlerin Yaşam Koşullarından Memnuniyetini Belirleyen Faktörlerin İncelenmesi, Türk Psikiyatri Dergisi, 14(2), ss. 125-133. Dikmen, A.A., 1995. İş Doyumu ve Yaşam Doyumu İlişkisi. Ankara Üniversitesi SBF Dergisi, Cilt:50, No:3-4, Haziran-Aralık. Dockery, A.M., 2003. Happiness, Life Satisfaction and the Role of Work: Evidence From two Australian Surveys. Paper Presentend to the 5 th Part to Full Employment Conference on Unemployment, University of Newcastle, 10-12 December. Gilman, R. & Huebner, E. S. 2000. Review of Life Satisfaction Measures for Adolescents, Behaviour Change, Vol. 17, No. 3, ss.178-183. Greene, W., 2002. Econometric Analysis, Macmillan,New York. Gujarati, D., 2001. Temel Ekonometri, Literatür Yayınları, İstanbul Guler K.B. ve Emeç, H. 2006. Yaşam Memnuniyeti Ve Akademik Başarıda İyimserlik Etkisi. D.E.Ü.İ.İ.B.F. Dergisi, Cilt:21 Sayı:2, ss:129-149. Keser, A., 2005. İş Doyumu ve Yaşam Doyumu İlişkisi: Otomotiv Sektöründe Bir Uygulama. Çalışma ve Toplum, 4, ss.77-96. 197 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Özdevecioğlu, M. ve Aktas, A., 2007. Kariyer Bağlılığı, Mesleki Bağlılık ve Örgütsel Bağlılığın Yaşam Tatmini Üzerindeki Etkisi: İş-Aile Çatışmasının Rolü. Erciyes Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Sayı: 28, Ocak-Haziran, ss.1-20. Pindyck, R. S., ve Rubınfeld, D., 1991. Econometric Models and Economic Forecasts. Mc Graw-Hill, Inc, New York. Rode, J., 2004. Job Satisfaction and Life Satisfaction Revisited: A Longitudinal Test of an Integrated Model. Human Relations, Volume 57(9), ss. 1205-1230. ICT Infrastructure for Sustainable Society: A Story of BH Telecom Dzihad Zlatar,Meliha Handzic International Burch University, Sarajevo, 71000, Sarajevo, Bosnia and Herzegovina. E-mails:dzidzmir@gmail.com, mhandzic@ibu.edu.ba Abstract World-class ICT infrastructure is the key to rapid economic and social development ofa country. Past studies show that the growth of ICT, particularly telecommunicationservices has a direct link with the economic growth of the country. However,the access to ICT infrastructure, services and applications and thus the level ofdevelopment varies among the countries. The focus of this study is on the currentsituation in Bosnia and Herzegovina (BiH). The main objective of the study is toexplore the penetration of telecommunication in B&H and the role of BH Telecom inthis process. Keywords:ICT, infrastructure, sustainable society, case study 1. INTRODUCTION The war that has ravaged Bosnia (1992-1995) did not just take its toll in casualties and material damage but has left the communications infrastructure crippled as well. While the other countries in the region introduced beginnings of information technologies, Bosnia had just started an arduous task of rebuilding its communications network. That task fell to the 198 � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 1168 Title A name given to the resource Analysis of Factors Affecting the Life Satisfaction of Household Heads Living in Urban Areas: A Case of West Mediterranean Region Author Author Ali Riza , Aktas Abstract A summary of the resource. Since the early ages of history, individuals have sought life satisfaction and considered it as a life goal. Because of this fact, the term life satisfaction has kept its importance in time and has been the focus of many studies. Life satisfaction is seen as a positive value gained by an individual’s own evaluation of the quality of life as a whole, therefore may be described as subjective. Nevertheless, studies made about life satisfaction use both subjective and objective indicators. Life satisfaction is partially conceptualized as the result of satisfaction related to various life fields such as work, family, health, etc. and it is assumed that the effects of environmental conditions highly help satisfaction related with life fields. When studies about life satisfaction are taken into consideration, it is notable that the term job satisfaction is generally emphasized. However, studies show that job satisfaction can explain only a few of the changes in life satisfaction. In this study, it is aimed to determine the socioeconomic factors affecting the life satisfaction of household heads by using data from questionnaires and Logit model. “Unclustered Single-Stage Simple Random Probability Sampling Method” was used to apply the questionnaires to 490 household heads living in city centers of Antalya, Isparta and Burdur. In order to determine the probability of whether the household heads were satisfied with their lives or not, explanatory variables oriented to the current perceptions of household heads were included to the model in the study in addition to the demographic variables. Demographic variables were included to the model as the dummy variable. Logit model was estimated by Maximum Likelihood Estimation method. According to the results of the analysis, life satisfaction of the household heads decreased with the increase of the size of the city. Similarly, increase in education level also decreased the probability of life satisfaction of the household heads. In addition, household heads with high income levels were happier than the ones with lower income. Similarly, if the spouse of the household head is either healthy, satisfied from job, or is a house wife, satisfied from marriage, then life satisfaction is determined to be higher than the household heads without the aforementioned spouse characteristics. Keywords: Satisfaction, Life Satisfaction, Household Head, Logit Model, West Mediterranean Region. Date A point or period of time associated with an event in the lifecycle of the resource 2012-05-31 Keywords Keywords. Conference or Workshop Item PeerReviewed H Social Sciences (General) https://omeka.ibu.edu.ba/files/original/ade2f568548c50da88671751de1d9811.pdf 6570cefe0cdbb13adcd981ced48fd2a6 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Journal of Natural Sciences and Engineering Identifier An unambiguous reference to the resource within a given context 2637-2835 DOI Digital object identifier 10.14706 Publisher An entity responsible for making the resource available International Burch University Description An account of the resource Journal of Natural Sciences and Engineering (JONSAE) is a peer-reviewed, biannually published international journal focusing on empirical and theoretical research in all branches of Engineering and Natural Sciences. It is published on the behalf of Faculty of Engineering and Natural Sciences of International Burch University and aims to provide the best content regarding by publishing original research papers, review articles, special issues, feature articles, and book reviews. All manuscript submissions are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous referees. All peer review is double-blind and submission is online. The journal welcomes theoretical, applied, interdisciplinary and methodological work, with preference on empirical research, critical approach and problem-solving methods in manuscripts. Language A language of the resource English Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Analysis of High School Graduate Data Using Database Analytics Tools Author Author Ezana Ćeman, Ajdin Salihović, Samed Jukić Abstract A summary of the resource. It can be confidently stated that access to education is one of the most prized possessions available to us today. Although there are underlying factors such as the discrepancies in the education being provided worldwide, it is imperative that data scientists and all those interested take advantage of the data publicly available to draw necessary insights into how to better the education sector in our respective countries. The purpose of this research is to showcase various analytical insights into the 2020 New York State (NYS) high school graduation rate data using various advanced database systems techniques, specifically using SQL. With these analyses, further studies and conclusions can be drawn for local governments to implement into their plans to increase the quality of the schooling system, to aim for equality for all without regard to cultural and ethnic background, and to find discrepancies within the current system.</div> <quillbot-extension-portal></quillbot-extension-portal> Keywords Keywords. Database, data analysis, graduate, high school, New York State, SQL Identifier An unambiguous reference to the resource within a given context ISSN 2637-2835 DOI Digital object identifier 10.14706/JONSAE2021322 Publisher An entity responsible for making the resource available International Burch University Language A language of the resource English language Type The nature or genre of the resource Original research https://omeka.ibu.edu.ba/files/original/bf923b9fd40bcdf388a6e52a68f04f73.pdf 24996345aff8bb328f86c88405bd45cb PDF Text Text 2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Analysis of Human Development in Balkan Countries: A Comparison of West and Middle Europe Countries Hüseyin ALTAY Assist. Prof. Dr., Bilecik University, Faculty of Economics and Administrative Sciences, Department of Economics, Bilecik, TURKEY, Phone: +90 228 212 42 96 (ext.120) huseyin.altay@bilecik.edu.tr Ali ġEN Assist. Prof. Dr., Dumlupinar University, Faculty of Economics and Administrative Sciences, Department of Economics, Kutahya, TURKEY, Phone: +90 274 265 20 31 (ext.2108) Fax: +90 274 265 21 97 alisen@dumlupinar.edu.tr Abstract: Since the beginning of 1990s, Balkan countries have significantly been changing as social, economic and politic structure. However, these countries have important differences in terms of human development indicators. Some countries in Balkans have low GDP levels. However, same countries replace between High Level Development countries in Human Development Index (prepared by UNDP). The aim of this paper is to investigate in terms of human development of Balkan countries that are not being member of EU countries. In scope of this aim, we will compare with three country groups related to human development. These groups are currently EU members countries (exclude Balkan countries), currently Balkan countries that are member of EU and other Balkan countries. As a result, this paper will have determined whether or not suitable for full membership to EU of Balkan countries. Key Words: Balkan Countries, Human Development Index, European Union Countries. Introduction For the first time, ―development‖ concept emerged after nation-states (Balanuye and Halıcı, 2006). It was based on a need for some structural and qualitative improvements in developing countries (ġan, 2005). The same concept as a branch of development economics, for the first time, was used after Great Depression. Especially, development economics took more of an interest in 1940s. Since World War II, development concept has usually been examined economically. In balanced and unbalanced development theories, neo-liberal approaches and dependence theories, development problem was seen as a part of production process. Thus, proposals concerning solution also have focused how production factors could be obtained and how they could be used in production process (Yavilioğlu, 2002). Because development and growth is examined together, in measurement of development is also used indicators related to economic growth. If a country has a positive growth rate in its GDP and its growth rate is stable, it is accepted as a development country. Raising per capita income is other development indicator (Mıhçı, 1996). Gross national product (GNP) or gross domestic product (GDP) were originally created as indicators of total economic output for macroeconomic stabilization policy and were therefore not meant to be indicators of well-being. On the other hand, it is certainly true that policy makers, the media and the public alike seem to equate GNP/GDP with well-being. In international comparison as well, it is thought of the countries with a high GNP/GDP as not only the rich, but also the well-off countries. However, because income is just one of the components of well-being, GNP/GDP have long since been criticized as misleading and deficient indicators of well-being (Neumayer 2004). Not only does development concept describe rising in GDP, but it has important effects on social and economic life, including education, health (Demiral, 2007). However, even if some countries are described as developed economically, they also have very problems. Thus, there is a need for a relationship between economic growth and human development (Demir, 2006). The fact that development is only described as an economic concept means that human factor is highly not considered. Development is based on fact of ―human development‖ (UNDP, 147 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo 2002). Most economics accept that GDP by itself is useful in measuring ―economic development‖ but it is inadequate to understand a nation‘s social and cultural level (Piana, 2001). Therefore, it is defined development as not only a rising in GDP and a diminishing in poverty but also a multidimensional process bringing about an important change in social behaviors and structures and national institutions (Açıkgöz, Kök, Ġspir, 2008). Development states improvement process of life quality of all people. Here, there are three facts in appearance of development that have equal importance. First is an improvement in life quality of people, so that their incomes increase, their education, health conditions improve. Second is an increase in self-confidence and merit of people with developing social, cultural, political and economic structure. Finally, changing in their preference opportunities of people increased their independences, and diversity of goods and services(Günsoy, 2005). What are factors that affect affirmatively human lifetime? How do people live on healthier? How do they prevent more efficient from illness? How do they enrich their thinking world? The kinds of questions are based on human life regarding development (Mıhçı, 1996). The first author is Amartya Sen, who has examined this subject on this base. According to Sen, there is human being in the base of all activities. Thus, development is to be based on their liberties, achievements and capabilities (Anand and Sen, 1994). People will be able to obtain a higher quality lifetime through better education and health system. Higher capacities create more liberty life standard. More liberty people are more productive. In other words, there are subjects regarding people‘s life quality in Sen‘s approach. Therefore, not being monetary issues have more priority than monetary ones do. Having higher growth rate is inadequate to be development for a country. Furthermore, there is a need for being known what development process are. Today, development is not about economic performance alone, but most importantly about people and their wellbeing (Jahan, 2005). Thus, in period that was discussed approaches regarding development, Human Development Report was published by UNDP, focusing Sen‘s capability and functioning approach (Baliamoune and Lutz, 2004). Aim of the reports, which was firstly prepared by Mahbub ul Haq‘s team in 1990, puts human being in national and global policies and attracts attention of international development environments to importance of life quality. Now, governments, non-governmental organizations, academicians and media for the purpose of comparison of countries‘ development levels (Gürses, 2009) use the reports. The concept of human development emphasized that (Jahan, 2005): • Development is about enlarging people‘s choices by enhancing their functionings and capabilities. • Development is of the people, for the people and by the people. The first refers to human capital formation and human resources development through nutrition, health and education. Development for the people stresses that the benefits of economic growth must be translated into lives of people. Development by the people means that people must be able to influence the process, which affects their lives. • Development must be woven around people, and not people around development Measure of Human Development Index The HDI is a summary measure of human development. It measures the average achievements in a country in three basic dimensions of human development (UNDP, 2005): • A long and healthy life, as measured by life expectancy at birth. • Knowledge, as measured by the adult literacy rate (with two-thirds weight) and the combined rimary, secondary and tertiary gross enrolment ratio (with one-third weight). • A decent standard of living, as measured by GDP per capita in purchasing power parity (PPP) terms in US dollars. 148 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo A long and Healthy life DIMENSION Knowledge Adult literacy rate Life expectancy At birth INDICATOR Adult literacy index Gross enrolment ratio (GER) GER index Education index Life expectancy index DIMENSION INDEX A decent standart of living GDP per capita PPP US GDP index HUMAN DEVELOPMENT INDEX (HDI) Figure 1: Formation of Human Development Report. Source: UNDP (2005) Human Development Report Before the HDI itself is calculated, an index needs to be created for each of these dimensions. To calculate these indices—the life expectancy, education and GDP indices—minimum and maximum values (goalposts) are chosen for each underlying indicator. Performance in each dimension is expressed as a value between 0 and 1 by applying the following general formula: Dimension Index= actualvalu e  min value max value  min value The HDI is then calculated as a simple average of the dimension indices. The box at right illustrates the calculation of the HDI for a sample country. Indicator Life expectancy at birth (years) Adult literacy rate (%) Combined gross enrolment ratio (%) GDP percapita (PPP US$) Maximum Minumum Value Value 85 25 100 0 100 0 40.000 100 Table 1: Goalposts for calculating the HDI Source: UNDP (2005) Human Development Report i) Life Expectancy Index: The life expectancy index measures the relative achievement of a country in life expectancy at birth. Life Ecpectancy Index= LE  25 85  25 149 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo ii) Education Index: The education index measures a country‘s relative achievement in both adult literacy and combined primary, secondary and tertiary gross enrolment. First, an index for adult literacy and one for combined gross enrolment are calculated. Then these two indices are combined to create the education index, with two-thirds weight given to adult literacy and one-third weight to combined gross enrolment. Education Index= 2 1 *ALI+ *GEI 3 3 Adult Literacy Index (ALI) = ALR  0 100  0 Gross Enrollment Index (GEI) = CGER  0 100  0 iii) GDP Index: The GDP index is calculated using adjusted GDP per capita (PPP US$). In the HDI income serves as a surrogate for all the dimensions of human development not reflected in a long and healthy life and in knowledge. Income is adjusted because achieving a respectable level of human development does not require unlimited income. Accordingly, the logarithm of income is used. GDP Index= log( GDPpc)  log(100) log( 40.000)  log(100) HDI Index=1/3(Life Expectancy Index) + 1/3 (Education Index) + 1/3 (GDP Index) Human Development Index (HDI) values ranges between 0 and 1. 0 value shows the lowest degree of HDI. 1 value shows the highest degree of HDI. HDI includes in three groups of countries regarding their development levels. If a country‘s HDI value is between 0 and 0.499, it has Low Human Development; if a country‘s HDI value is between 0.500 and 0.799, it has Medium Human Development; if a country‘s HDI value is between 0.800 and 1, it has High Human Development (Ünal, 2008). Human Development in Balkan Countries In the 20th century, Balkan countries had partly different processes of development. Since 1981, Greece has been a member of EU. In addition, it is an insider of Euro zone and Western European Union (WEU). Slovenia joined EU in 2004. Bulgaria and Romania were insiders of EU in 2007. Although Turkey applied for membership of EU, it was able to start membership negotiations in 2005. In 2005, Croatia and Macedonia were members of EU. On the other hand, Bosnia and Herzegovina, Montenegro and Serbia have applied to membership of EU. This paper intends to examine Balkan countries‘ human development levels in process of membership of EU. The countries are three groups that are EU members, Balkan countries in EU and Balkan countries in process of EU membership. Balkan countries will compare with EU (15), and other EU (10) members that were accepted membership in 200431. The paper analyzes sub-indexes in HDI and examines countries‘ HDI as a whole. It is used data from Human Development Reports (2000-2007) by published UNDP. 31 EU (15): Germany (1957), France (1957), Belgium (1957), Italy (1957), Luxemburg (1957), Netherland (1957), Denmark (1973), Ireland (1973), Ġngiltere (1973), Greece (1981), Spain (1986), Portugal (1986), Sweden (1995), Austria (1995), Finland (1995), EU (10): Cyprus, Czech Republic, Estonia, Hungary, Lithuania, Latvia, Malta, Poland, Slovak Republic, Slovenia: (2004) EU (2): Romania, Bulgaria: (2007) Balkan Countries: Greece, Slovenia, Bulgaria, Romania, Albania, Bosnia and Herzegovina, Montenegro, Serbia, Macedonia, Croatia, Turkey 150 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Figure 2: Life Expectancy Index 2000-2007 Greece has the highest Life Expectancy Index. Slovenia, Croatia and Albania follow Slovenia Bulgaria and Romania have rather low LIE values. Within Balkan countries, which are non-member EU, Croatia has the highest value. Turkey is at last rank regarding same value. Figure 3: Education Index 2000-2007 According to Education Index, the highest value belongs to Slovenia, whose value is above of average of EU‘s one. Greece Education Index follows Slovenia‘s one. Turkey has the lowest value of Education Index 151 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Figure 4: GDP Index 2000-2007 According to GDP Index, Greece has the highest value. Slovenia is in second rank. Both counties place above of average of EU (10) countries, whose value is o.844. Within non-member EU countries, Croatia has the highest GDP Index value. Albania has GDP Index value. Figure 5: Human Development Index 2000-2007 Greece has the highest Human Development Index value. Although Greece is above of average of EU‘s (10), it is below of average of EU‘s (15). Slovenia has second high value. Within non-member EU countries, Croatia is a country that has the highest HDI. Montenegro and Serbia follow Slovenia. Moreover, in 2007, levels of these countries‘ HDI were higher than Romania‘s and Bulgaria‘s ones. Turkey has lower value than Macedonia, Bosnia and Herzegovina and Albania do. 152 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Figure 6: Human Development Index 2000-2007, All Countries According to Human Development Index results for all countries, Sweden has the highest value regarding 2000-2007 averages. Respectively, Netherland, Ireland, Belgium, Luxemburg, Finland, France, Austria, Denmark, England, Spain and Germany (EU 15) follow Sweden. Within EU (15) Greece has only better HDI level than Portugal does. Within countries that have been member of EU since 2004, Slovenia has the highest HDI value so that its value is higher than Portugal‘s. Romania and Bulgaria, which have been EU member since 2007, have lower HDI degree than Croatia, Montenegro and Serbia, which have not been EU member yet. Macedonia, Bosnia and Herzegovina, Albania and Turkey are last ranks. Concluding Remarks From 2000 to 2007 in Human Development reports, respectively, Greece, Slovenia, Croatia, Montenegro, Serbia, Bulgaria, Romania and Macedonia have high HDI values. Bosnia and Herzegovina, Albania and Turkey have medium HDI values. Greece is below of EU (15) average HDI. Slovenia has a HDI value that is higher than EU (10) average. Romania and Bulgaria, which have been EU members since 2007, have lower HDI than Croatia, Montenegro and Serbia, which have not been EU members yet. Within non-member EU Balkan countries, Croatia is an outstanding country. Croatia has high values of three sub-indexes of HDI. Although Albania and Bosnia and Herzegovina have high values in Life Expectancy Index, their values of Education Index and GDP Index are rather low. Thus, the countries‘ HDI values are also low. There is a similar situation for Turkey, whose GDP Index value is quite high. However, because of low values of Education Index and Life Expectancy Index, Turkey is in last rank regarding HDI. According HDI values, Balkan countries are two groups: first group includes the countries that are Croatia, Montenegro, Serbia and Macedonia, which have high HDI; second group is Bosnia and Herzegovina, Albania and Turkey that have medium HDI. 153 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo References Açıkgöz, B.& Tarı, R. & Ġspir, S. (2008). Hypothesis Tests Aimed at Globalization Pre-assumption: Experience of Selected Countries on Poverty (1997-2003). Süleyman Demirel Üniversitesi Ġktisadi ve Ġdari Bilimler Fakültesi Dergisi, C:13, S:1, (pp. 351-376). Anand, S.& Sen, A. K. (1994). Human Development Index: Methodology and Measurement. Human development report office occasional papers. 26.04.2010 from Web site: http://hdr.undp.org/en/media/Anand_and_Sen_HDI.pdf . Balanuye, Ç. & Halıcı, E. (2006). Sürdürülebilir GeliĢme Beyin Göçü ve BiliĢim, Felsefi Bir Perspektif. Elektronik Sosyal Bilimler Dergisi. www.e-sosder.com. ISSN: 1304-278, C.5, S.18, (pp. 22-29). Baliamoune, M.L. (2004). On the Measurement of Human Well-being, Fuzzy Set Theory and Sen‘s Capability Approach. United Nation University, World Institute for Development Economic Research (WIDER). Research Paper No: 2004\16. Demir, S. (2006). BirleĢmiĢ Milletler Kalkınma Programı Ġnsani GeliĢme Endeksi ve Türkiye Açısından Değerlendirme. DPT. Ankara. Demiral, M. (2007). Türkiye‘de Sosyal Sermaye Kapsamında Sivil Toplum KuruluĢlarının Sürdürülebilir Sosyo-ekonomik Kalkınma Sürecindeki Rolü. Akademik BakıĢ E-Dergisi. ISSN: 1694-528X, S.13. Günsoy, G. (2005). Ġnsani GeliĢme Kavramı ve Sağlıklı YaĢam Hakkı. Zonguldak Karaelmas Üniversitesi Sosyal Bilimler Dergisi. Cilt 1, Sayı 2, (pp. 35-52). Gürses, D. (2009). Human Development and Turkey. Balıkesir Üniversitesi Sosyal Bilimler Dergisi, Cilt 12, Sayı 21, (pp.339350). Jahan, S. (2005). Measuring Human Development: Evolution of the Human Development Index. http://hdr.undp.org/en/media/Jahan_HDI.pdf. Mıhçı, H. (1996). Kalkınma: Bir Terim Neyi Anlatır? Ekonomik YaklaĢım. Cilt 7, Sayı 23, (pp.65-86). Neumayer, E. (2004). Sustainability and Well-being Indicator. United Nation University World Institute for Development Economic Research (WIDER), Research Paper No: 2004\23. Piana, V. (2001). Gross Domestıc Product Retrieved, 26.04.2010 from Web site: http://www.economicswebinstitute.org/glossary/gdp.htm. Sen, Amartya K. (2004). Özgürlükle Kalkınma. Ayrıntı Yayınları. Ġstanbul. ġan, M. (2005). Kalkınma Planlamasında Bilgi Yönetimi ve Devlet Planlama TeĢkilatı Ġçin Kurumsal Bilgi Politikası Modeli. DPT, 2687, Ankara. UNDP. (2002). Human Development Report. http://hdr.undp.org/en/statistics. UNDP. (2003). Human Development Report, http://hdr.undp.org/en/statistics UNDP. (2004). Human Development Report. http://hdr.undp.org/en/statistics UNDP. (2005). Human Development Report. http://hdr.undp.org/en/statistics UNDP. (2006). Human Development Report. http://hdr.undp.org/en/statistics UNDP. (2007-2008). Human Development Report. http://hdr.undp.org/en/statistics UNDP (2009), Human Development Report, http://hdr.undp.org/en/statistics Ünal, Ç. (2008). Regionall Differencess in Turkey by Human Development Index. Coğrafi Bilimler Dergisi. Cilt 6, Sayı:2, (pp.89-113). Yavilioğlu, C. (2002). The Semantic History of Consept of the Development an its Conceptual Origins. Cumhuriyet Üniversitesi Ġktisadi ve Ġdari Bilimler Dergisi. C.3, S.1, (pp.59-77). 154 � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 201 Title A name given to the resource Analysis of Human Development in Balkan Countries: A Comparison of West and Middle Europe Countries Author Author ALTAY, Hüseyin ŞEN, Ali Abstract A summary of the resource. Since the beginning of 1990s, Balkan countries have significantly been changing as social, economic and politic structure. However, these countries have important differences in terms of human development indicators. Some countries in Balkans have low GDP levels. However, same countries replace between High Level Development countries in Human Development Index (prepared by UNDP). The aim of this paper is to investigate in terms of human development of Balkan countries that are not being member of EU countries. In scope of this aim, we will compare with three country groups related to human development. These groups are currently EU members countries (exclude Balkan countries), currently Balkan countries that are member of EU and other Balkan countries. As a result, this paper will have determined whether or not suitable for full membership to EU of Balkan countries. Date A point or period of time associated with an event in the lifecycle of the resource 2010-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory https://omeka.ibu.edu.ba/files/original/34084530ff1f6f62f05e66d3f96595cc.docx 0a691562a3eaae9aed2b7b7ce77eac60 https://omeka.ibu.edu.ba/files/original/e37f173d77c4bcda8289ae0c3f071bab.pdf a256c4d21df1c158f36b56aa0698ec72 PDF Text Text Analysis of Influence of Italian Language on Slovene Language in Regard of Word Order Nina Lovec University of Primorska / Koper,Slovenia Key words: word order, slovene, italian, influence, language ABSTRACT The Slovene minority that lives in Italy is daily exposed at the influence of Italian language on their mother language. As a consequence of language contact in bilingual speakers it is possible to notice language interference. Interference can occur only if there is open cultural and linguistic communication between the two linguistic communities. Language interference can be divided in four groups relative to phonetics, word formation and morphology and syntax. In my paper I will focus on analysis of syntax interference, more precisely on word order. The Slovene community living in Italy has various printed media. I analyse some articles published in recent issues of the monthly magazine mladika written in Slovene language that is being issued in Trieste since 1957. The articles are written by Slovenes that live in Italy and are bilingual speakers. My analysis concerns only written language because the time lag between thinking and writing should permit the functioning of »defence mechanism«. Slovene and Italian language both have the standard word order called SVO (subject- verb- object), but the role of word order in Slovene differs from Italian language. In Slovene the syntactic role of words is defined by morphology but in contrary, in Italian the syntactic role is defined by sentence word order. The present paper presents the violation of the norms of Slovene standard language. � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 1911 Title A name given to the resource Analysis of Influence of Italian Language on Slovene Language in Regard of Word Order Author Author LOVEC, Nina Abstract A summary of the resource. Key words: word order, slovene, italian, influence, language ABSTRACT The Slovene minority that lives in Italy is daily exposed at the influence of Italian language on their mother language. As a consequence of language contact in bilingual speakers it is possible to notice language interference. Interference can occur only if there is open cultural and linguistic communication between the two linguistic communities. Language interference can be divided in four groups relative to phonetics, word formation and morphology and syntax. In my paper I will focus on analysis of syntax interference, more precisely on word order. The Slovene community living in Italy has various printed media. I analyse some articles published in recent issues of the monthly magazine mladika written in Slovene language that is being issued in Trieste since 1957. The articles are written by Slovenes that live in Italy and are bilingual speakers. My analysis concerns only written language because the time lag between thinking and writing should permit the functioning of »defence mechanism«. Slovene and Italian language both have the standard word order called SVO (subject- verb- object), but the role of word order in Slovene differs from Italian language. In Slovene the syntactic role of words is defined by morphology but in contrary, in Italian the syntactic role is defined by sentence word order. The present paper presents the violation of the norms of Slovene standard language. Publisher An entity responsible for making the resource available IBU Publishing Date A point or period of time associated with an event in the lifecycle of the resource 2013-05-03 Keywords Keywords. Article PeerReviewed https://omeka.ibu.edu.ba/files/original/a18ced04588d7219bf8ab501e19729f7.docx 57cf102ad082bba769fd8f113729d922 https://omeka.ibu.edu.ba/files/original/4036470cdc4a15c6f5308d7f8b5afc40.pdf fe73b20bb3df8327ac0c8e24ca6d4169 PDF Text Text Analysis of Internally Generated Revenue and its Implications on Fiscal Viability of State Governments in Nigeria Asimiyu G. Abiola National Institute for Legislative Studies Nigeria UyiKizitoEhigiamusoe National Institute for Legislative Studies Nigeria ehiuyikizexcel@yahoo.com Abstract: State governments in Nigeria are financed by funds from statutory allocations from the federal government and Internally Generated Revenue (IGR) from each state. But most state governments depend on the federal government due to the poor level of internally generated revenue in their states. Therefore, the paper examines the growth rate of state governments’ internally generated revenue in Nigeria between 1999 and 2011. The main objective of this paper is to examine the relationship between internally generated revenue and state governments’ expenditures. It also seeks to compare the growth rate of internally generated revenue in urban and rural states. The paper adopts analytical and descriptive approaches to examine the relationship between internally generated revenue and government expenditures. The results of the paper revealed a direct relationship between the growth rates of internally generated revenue and capital expenditures. On the overall, the growth rate of state governments IGR was 20.1 per cent, compared to 30.0 per cent and 34.2 per cent for recurrent and total expenditures, respectively. Although, the growth rate of IGR is higher in rural states than in urban states but the growth rates in expenditures are higher than the growth rate of IGR. It was further discovered that the internally generated revenue of urban states financed a greater proportion of their recurrent and total expenditures than the IGR of rural states. The paper therefore recommended that more revenue should be given to rural states to finance capital projects to enable them grow their internally generated revenue, so as to promote economic development. Keywords: Internally Generated Revenue (IGR), Expenditures, Urban states, rural states, Federation Account. 58 � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 2492 Title A name given to the resource Analysis of Internally Generated Revenue and its Implications on Fiscal Viability of State Governments in Nigeria Author Author G. ABIOLA, Asimiyu KIZITO EHIGIAMUSOE, Uyi Abstract A summary of the resource. State governments in Nigeria are financed by funds from statutory allocations from the federal government and Internally Generated Revenue (IGR) from each state. But most state governments depend on the federal government due to the poor level of internally generated revenue in their states. Therefore, the paper examines the growth rate of state governments’ internally generated revenue in Nigeria between 1999 and 2011. The main objective of this paper is to examine the relationship between internally generated revenue and state governments’ expenditures. It also seeks to compare the growth rate of internally generated revenue in urban and rural states. The paper adopts analytical and descriptive approaches to examine the relationship between internally generated revenue and government expenditures. The results of the paper revealed a direct relationship between the growth rates of internally generated revenue and capital expenditures. On the overall, the growth rate of state governments IGR was 20.1 per cent, compared to 30.0 per cent and 34.2 per cent for recurrent and total expenditures, respectively. Although, the growth rate of IGR is higher in rural states than in urban states but the growth rates in expenditures are higher than the growth rate of IGR. It was further discovered that the internally generated revenue of urban states financed a greater proportion of their recurrent and total expenditures than the IGR of rural states. The paper therefore recommended that more revenue should be given to rural states to finance capital projects to enable them grow their internally generated revenue, so as to promote economic development. Keywords: Internally Generated Revenue (IGR), Expenditures, Urban states, rural states, Federation Account. Publisher An entity responsible for making the resource available International Burch University Date A point or period of time associated with an event in the lifecycle of the resource 2014-04-24 Keywords Keywords. Article PeerReviewed Identifier An unambiguous reference to the resource within a given context ISSN 2303-4564 H Social Sciences (General) https://omeka.ibu.edu.ba/files/original/907cbbd3e58985ca628d546b743f6a56.pdf 551d693419df73ca402b797eabfe0349 PDF Text Text PROCEEDINGS th ______ The 5 International Symposium on Sustainable Development_______ ISSD 2014 ANALYSIS OF MAGNETIC FIELD EFFECTS OF UNDERGROUND POWER CABLES ON HUMAN HEALTH Celal Kocatepe, Celal Fadil Kumru, Eyup Taslak Yildiz Technical University, Istanbul, Turkey kocatepe@yildiz.edu.tr, cfkumru@yildiz.edu.tr, etaslak@yildiz.edu.tr ABSTRACT Transmission and distribution lines of electrical energy are generally used to plant far from residential areas. But today, due to the growing population, the cities considerably expanded and electrical network have to lie within the living spaces. Especially, uses of medium voltage underground cables for distribution systems become widespread in such areas. The voltage levels of these cables are not too high and the electric field caused by the voltage is fairly shielded by the cable’s screen. However, by the reason of flowing load current through the cable’s conductor, low frequency magnetic fields occur around the cable. It is known that this magnetic field strength becomes greater with increasing current. Basically, shielding of low frequency magnetic fields is quite harder than shielding the electric fields. In case of being exposed to this kind of magnetic fields by people may lead to crucial health problems. Therefore, some limit values are introduced by the “International Commission On Non‐Ionizing Radiation Protection” (ICNIRP) and “The Institute of Electrical and Electronics Engineers” (IEEE). For this reason, it has importance of measuring magnetic fields caused by high voltage cables (HVC) in urban areas and the required shielding measures should be taken if needed. In this study, magnetic field strengths at different points above a 12/20 kV, 150 mm2 (Al), single core HVC are measured for different current values. According to the results obtained, even at low currents, the magnetic field strength values could exceed the limiting values for certain distances. Keywords: Magnetic Field, Underground Power Cable, Human Health 137 | P a g e �th ISSD 2014 The 5 International Symposium on Sustainable Development_______ PROCEEDINGS 1. INTRODUCTION Electrical energy is one of the most important sources in our age. The need for electrical energy is rapidly growing with developing technology and increasing population. Generated energy is supplied for the end users through transmission and distribution lines to meet this energy demand. Resulting from expanding of residential areas and increasing energy demand, especially distribution lines penetrate in living spaces [1]. While energy is distributed with overhead lines in the beginning, today underground power cables are being used especially for human safety and clear visual pollution. These cables are widely used for supplying distribution transformers in thickly populated places [2,3]. Underground power cables used in distribution systems cause electric field because of being operated at medium voltage. All underground power cables, which operate at medium voltage, consist a screen layer made of copper or lead [4]. This screen is grounded in practice and can shield almost all electric field arise from conductor. However, this screen layer cannot totally shield low frequency magnetic fields arise from load current. Current carrying capacity of underground power cables, which generally used in residential areas, is quite high. Therefore, magnetic field exposure risk occurs for humans. In literature, there several studies about the effects of magnetic field exposure on human health [5-8]. Thus, analysis of magnetic fields arise from underground power cables has an importance. Limiting magnetic field values for different frequencies are introduced by ICNIRP [9]. In this study, magnetic field measurements of an underground power cable are carried out for different currents at certain distances. The results obtained are analyzed by using ICNIRP standard. In the following section, for magnetic field calculation for, fundamental formulas of a current carrying conductor are given and limit values by ICNIRP are presented. In the third section, measurement setup and results are presented. Consideration of results and suggestions are given in the last section. 2. BASIC THEORY In power systems, magnetic fields occur around the conductors which carry currents. When the current increases, the magnetic field is also strengthen proportionally. Magnetic field induced a voltage in conductors and dielectric materials placed within the field [10]. This induced voltage cause to flow current in object which harms the livings. Limiting values are defined to keep human health in safe. It is important to consider these values while designing a system which consist current carrying conductors. At a specified distance, magnetic field value of a current carrying conductor can be calculated by Bio-Savart equation given in Eq. (1). H I 2   r [A/m] where, H = Magnetic Field Strength [A/m] I = Current [A] r = Distance [m] 138 | P a g e (1) �th PROCEEDINGS ______ The 5 International Symposium on Sustainable Development_______ ISSD 2014 As it is known that magnetic field strength (H) is a vectorial magnitude. So, a current carrying conductor at point K causes to occur both horizontal and vertical magnetic field component. With vectorial sum of these components, resultant magnetic field (H) at point P is acquired as shown in Fig. 1 [10]. Figure 1 Magnetic field strength of a conductor (K) at point P According to the Figure 1, horizontal and vertical components of magnetic field strength (H) at point P can be calculated with formulas given in Eq. (2) and (3) respectively. Hx  y j  yi I  2  r2 (2) Hy  x j  xi I  2  r2 (3) Here, xi and yi are the coordinates of point K and xj and yj are the coordinates of point P. r is the distance from the current source defined as, r x  xi    y j  y i  2 j 2 (4) To calculate resultant magnetic field strength, horizontal and vertical components are vectorially added. If there are n conductors in a system, resultant magnetic field strength can be calculated with the Eq. (5). 2  n   n  H    H xi     H yi   i 1   i 1  2 (5) Magnetic flux density (MFD) can be calculated by multiplying the magnetic field strength (H) and magnetic permeability of vacuum or air (  0  4    10 7 [H/m] ) as given in Eq. (6). B  0  H (6) In Eq. (6), B is the magnetic flux density or magnetic induction in Wb/m2 or Tesla. Several studies have been published about the effects of magnetic field on human health. Magnetic field exposure levels depend on many factors such as distance from the magnetic field source, exposure duration, strength and frequency of the magnetic field. Therefore, limit 139 | P a g e �ISSD 2014 th The 5 International Symposium on Sustainable Development_______ PROCEEDINGS values for magnetic fields at different frequencies are specified by the ICNIRP [9]. These values are given in Table 1 for occupational and general public exposure. Table 1 Reference levels for occupational exposure to time varying magnetic fields (unperturbed rms values). Exposure Occupational General Public Frequency Range 1 Hz – 8 Hz 8 Hz – 25 Hz 25 Hz – 300 Hz 300 Hz – 3 kHz 3 kHz – 10 Mhz 1 Hz – 8 Hz 8 Hz – 25 Hz 25 Hz – 50 Hz 50 Hz – 400 Hz 400 Hz – 3 kHz 3 kHz – 10 MHz Magnetic Field Strength H (A/m) 1.63 x 105/f2 2 x 104/f 8 x 102 2.4 x 105/f 80 3.2 x 104/f2 4 x 103/f 1.6 x 102 1.6 x 102 6.4 x 104/f 21 Magnetic Flux Density B (T) 0.2/f2 2.5 x 10-2/f 1 x 10-3 0.3/f 1 x 10-4 4 x 10-2/f2 5 x 10-3/f 2 x 10-4 2 x 10-4 8 x 10-2/f 2.7 x 10-5 In this study, 50 Hz power system frequency is considered. Measured MFD values at this frequency should be under 1 mT for general public exposure and 0.2 mT for occupational exposure. 3. EXPERIMENTAL SETUP AND RESULTS In the measurement, 12/20 kV, 150 mm2, single core high voltage underground cable is used. The technical specifications of the cable sample are given in Table 2 [11]. Table 2 Technical specifications of the cable sample Parameter VDE Code Nominal voltage (kV) Nominal cross-section (Al/Cu Tape) (mm2) Value NA2XSY 12 / 20 1x150/16 Conductor DC resistance (at 20°C) (ohm/km) 0.198 Operating inductance (mH/km) Operating capacitance (µF/km) Current carrying capacity (in air) (A) Cable length (m) Overall diameter (mm) 0.63 0.25 425 12 33.5 The cross-sectional area of the sample cable is given in Fig. 2. The underground power cable consists of a few layers. The conductor is the main part which transfers energy. The main insulation material of the cable is cross linked polyethylene (XLPE). There are semiconductor layers around the copper conductor and insulation. Semi-conductor layer is used for smoothing the field distortion caused by stranded structure of conductor and roughness of the sheath. The role of the screen is shielding of electric and magnetic fields. For this reason, lead is generally used as screen material for cables which have high current carrying capacity. The outer sheath is made of PVC and it protects cable from environmental effects. 140 | P a g e �PROCEEDINGS th ______ The 5 International Symposium on Sustainable Development_______ ISSD 2014 Figure 2 Cross-sectional area of underground power cable The measurement setup given in Fig. 3 is arranged for flowing current through the cable conductor. The conductor of the cable is connected to the secondary windings of a 220V/5V and 5 kVA high current transformer. This transformer is supplied with a 220V/0-220V, 5 kVA variac. So the desired current value is obtained by varying the secondary winding voltage of the variac. A 1000 A clamp meter with ±1.5% sensitivity is used to measure the cable current. Additionally, the screen of the cable is grounded as in practice. Figure 3 The experimental setup In the measurement, a magnetic field measurement device Spectran NF-5035 is used. The measurements are realized for certain distances (5, 10, 20, 40, 60, 80 and 100 cm) above the upper side of cable. The minimum load current for measurement is specified as 50 A. The measurements are carried out up to 450 A with 50 A steps. The results obtained are given in Table 3. Table 3 Measured magnetic flux density values Distance From Upper Side (cm) 5 10 20 40 60 80 100 Magnetic Flux Density [µT] 50 A 135.5 70.27 39.65 18.98 16.54 14.79 12.04 100 A 150 A 200 A 250 A 300 A 350 A 400 A 450 A 262.5 142.5 75.05 40.81 23.45 19.55 19.05 371.3 210.9 113.8 60.37 40.6 27.31 21.1 471.6 267 149.8 78.37 50.51 36.59 27.81 559.1 333.6 182 97 65.9 46.97 33.5 693.7 384.4 215.4 113.9 75.08 54.67 42 794.2 449.9 247.7 131.2 87.94 63.56 50.72 914 504.2 283 151.2 102 75.46 56.27 1010 567.2 312.9 170.3 112.8 83.29 63.89 141 | P a g e �th ISSD 2014 The 5 International Symposium on Sustainable Development_______ PROCEEDINGS As seen in Table 1, MFD is increasing with the increased current. Also, it reaches the highest values for all current levels when it gets closer to the cable surface. The highest MFD is obtained as 1010 µT for 450A current and 5 cm distance. The weakest MFD value is acquired as 12.04 µT for 50 A current and 100 cm distance. Additionally in Table 1, some values, which exceed the limit values in ICNIRP for general public exposure, are given in bold. Especially for the currents from 300 A up to 450 A and 20–30 cm distance, it is clearly seen that the measured MFD values are unsafe for general public. 1100 Magnetic flux density (µT) 1000 900 occupational exposure 800 700 600 100A 200A 300A 400A 450A 500 public exposure 400 300 200 100 0 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100 Distance (cm) Figure 4 The relation between distance and magnetic flux density The relation between the distance and MFD for all current levels is given in Fig. 4. It seen from the Fig. 4 that, MFD is exponentially increasing with decreasing distance from the source for all current levels. Additionally, the difference between MFDs obtained for certain current levels show difference according to the distances. When it gets closer to the cable such as 5 cm distance, the difference is quite high for different current levels. In contrast with this change, the difference is quite small when it goes far from the cable. 4. CONCLUSION In this study, magnetic field measurements of a 12/20 kV, 1x150/16 mm2 underground power cable is realized for particular current and measurement distances. The results showed that magnetic field is increasing with the increased current and decreased distance. Especially for 450 A current, the MFD value exceed the limit value for general public at 35 cm distance. In addition, underground power cables are commonly installed 80 cm below the ground surface. So approximate distance value, that the people can be exposed to magnetic field, is over 80 cm distances from the cable. Therefore, the MFD values obtained in this study seem safe for human health. However in practice, there are at least three cables in the cable route for three phase systems. In this situation, each magnetic field strength value is vectorially added together as in Eq. (5). Thus, the magnitude of MFD can be reach to considerable high values which can be unsafe for human health. Additionally, there underground cables whose sectional area and so the current carrying capacity is higher from the one in this study. So, the cables which have high current carrying capacities are bigger threads for human health. 142 | P a g e �PROCEEDINGS th ______ The 5 International Symposium on Sustainable Development_______ ISSD 2014 Consequently, magnetic field strength caused by an underground power cable can be at dangerous levels for human health. To get over this problem, magnetic field measurements around the underground power cables should be done carefully. In the case of existing high magnetic field values, the whole cable system could be shielded by a ferromagnetic material or the cable route could be further from the ground. Thus, generated magnetic field can be decreased down to required limit values. 5. REFERENCES [1] Kalenderli, O., Kocatepe, C., Arikan, O., (2011). High Voltage Technique with Solved Problems, Vol.1, Birsen Press, Istanbul, Turkey. [2] Gobba, F., Bargellini, A., Scaringi, M., Bravo, G., & Borella, P., (2008), Extremely Low FrequencyMagnetic Fields (ELF-EMF) occupational exposure and natural killer activity in peripheral blood lymphocytes, Science of The Total Environment, 407(3), 1218–1223. [3] Ali, E., Memari, A.R., (2010). Effects of Magnetic Field of Power Lines and Household Appliances on Human and Animals and its Mitigation, IEEE Middle East Conference on Antennas and Propagation (MECAP),Cairo, Egypt, 1-7. [4] Gudmundsdottir, U. S., De Silva, J., Bak, C. L., Wiechowski, W., (2010). Double Layered Sheath in Accurate HV XLPE Cable Modeling, IEEE Power and Energy Society General Meeting, 1-7. [5] A. S. Safigianni, A. I. Spyridopoulos and V. L. Kanas, (2011), Electric and magnetic field measurements in a high voltage center, 10th International Conference on Environment and Electrical Engineering (EEEIC), 1-4. [6] Takebe, H., Shiga, T., Kato, M., Masada, E., (2001). Biological and Health Effects from Exposure to Power Line Frequency Electromagnetic Fields – Confirmation of Absence of Any Effects at Environmental Field Strength, IOS Press, ISBN 158 603 1058. [7] M. Maslanyj et al., Investigation of the sources of residential power frequency magnetic field exposure in the UK Childhood Cancer Study, (2007). Journal of Radiological Protection Vol. 27, 41–58. [8] World Health Organization (WHO), (2007). Extremely Low Frequency Fields Environmental Health Criteria Monograph No. 238, Chapter. 2, p. 48. [9] ICNIRP Publication (2010). ICNIRP Guidelines, For limiting exposure to time varying electric and magnetic fields (1 Hz – 100 kHz), Health Physics 99(6), 818-834. [10] Guclu, G., Kaypmaz, A., Kalenderli, O., (2011). Calculation of Magnetic Field Around 34,5 kV Power Lines, Electromagnetic Fields and Effects Symposium, 270-273. [11] Demirer Cable, Low, Medium and High Voltage Cables Catalogue, (2012). 143 | P a g e � Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Extent The size or duration of the resource. 2501 Title A name given to the resource ANALYSIS OF MAGNETIC FIELD EFFECTS OF UNDERGROUND POWER CABLES ON HUMAN HEALTH Author Author KOCATEPE, Celal KUMRU, Celal F. TASLAK, Eyup Abstract A summary of the resource. Transmission and distribution lines of electrical energy are generally used to plant far from residential areas. But today, due to the growing population, the cities considerably expanded and electrical network have to lie within the living spaces. Especially, uses of medium voltage underground cables for distribution systems become widespread in such areas. The voltage levels of these cables are not too high and the electric field caused by the voltage is fairly shielded by the cable’s screen. However, by the reason of flowing load current through the cable’s conductor, low frequency magnetic fields occur around the cable. It is known that this magnetic field strength becomes greater with increasing current. Basically, shielding of low frequency magnetic fields is quite harder than shielding the electric fields. In case of being exposed to this kind of magnetic fields by people may lead to crucial health problems. Therefore, some limit values are introduced by the “International Commission On Non‐Ionizing Radiation Protection” (ICNIRP) and “The Institute of Electrical and Electronics Engineers” (IEEE). For this reason, it has importance of measuring magnetic fields caused by high voltage cables (HVC) in urban areas and the required shielding measures should be taken if needed. In this study, magnetic field strengths at different points above a 12/20 kV, 150 mm2 (Al), single core HVC are measured for different current values. According to the results obtained, even at low currents, the magnetic field strength values could exceed the limiting values for certain distances. Keywords: Magnetic Field, Underground Power Cable, Human Health Publisher An entity responsible for making the resource available International Burch University Date A point or period of time associated with an event in the lifecycle of the resource 2014-05-15 Keywords Keywords. Article PeerReviewed Identifier An unambiguous reference to the resource within a given context ISSN 978-9958-834-36-3 Q Science (General),QH301 Biology,QH426 Genetics