57 10 3494 https://omeka.ibu.edu.ba/files/original/3faa780a9a68b5a6a507234fd850401e.pdf 457bc2d5dd62929a487ddd023ac6e05e PDF Text Text 1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo Climatic Hazards Phenomena of the Warm Semester of the Year in the South-West Development Region. Romania Carmen-Sofia Dragotă Institute of Geography, Romanian Academy, Physical Geography Department, Bucharest dragotacarmen @yahoo.co.uk Ines Grigorescu Institute of Geography, Romanian Academy, Physical Geography Department, Bucharest inesgrigorescu@yahoo.com M onica Dumitraşcu Institute of Geography, Romanian Academy, Physical Geography Department, Bucharest stefania_dumitrascu@yahoo.com Costin Dumitraşcu Faculty of Geography, Spiru Haret University, Bucharest costin_dumitrascu@yahoo.com Abstract. The South-West Development Region is exposed to several climatic hazards with major impact upon the environment. The paper emphasizes the occurrence and the amplitude of the hazard phenomena characteristic of the warm semester of the year within the study area based on processed annual, monthly and daily extreme climatic values (temperature, precipitations, wind, dangerous atmospheric phenomena) from all the meteorological stations involved (1961-2007) in order to establish the main vulnerability classes (mixed, very high, high, medium and low). On the basis of this survey a climatic hazard map was realized in order to emphases the main threats of these hazardous phenomena (heat waves and positive thermal singularities, dryness and drought, heavy rainfall, thunderstorms, hail storms, strong winds, acid deposits and fog) to the environment. Thus, certain areas have been identified with different vulnerability classes: mixed, high and very high, medium and low to the above mentioned climatic hazards. 1. Introduction The South-West Development Region is situated in the south-western part of Romania covering 12.3 % (29,010 km2) of the national territory and 10.7% of its population (2,301,833 inh.) [Figure 1 A]. The region expands from the heights of Southern Carpathians and Banat Mountains in the north and north-westto the hilly, plain areas and Danube floodplaininthe centre and south.The genesis of specific climatictypes (mountain, hilltableland and plain) is mainly determined by the amphitheatre-like distribution of the relief units. The climatic influences (submediterraneean in the south-western extremity, oceanic in the north and transitionalto arid in the east), filling the temperate-continental climate of the South-West Development Region (Romania. The Environment and the ElectricTransportation Network. Geographical Atlas). These major climatic traits are completed by the multitude of factors related to the local geographical environment (orographic barrier of the mountains situated in the north, exposure, massiveness and fragmentation, vegetation, soil and water bodies as well as the man-made changes) determining a wide range of local climatic features and exposing it to several climatic hazards with major impact upon the environment (Figure 1). 2. Methodology Natural risk assessment studies have often been elaborated based one criterion determining a one-sided approach of the involved phenomena. In 1991, E. Bryant developed one of the most complex classifications based on multiple criteria, which inspired Croitoru and Moldovan (2005) in approaching the hazardous meteorological phenomena specific to Romania’s territory. They identified for the southern part of the country droughts, heat waves, cold waves, strong winds, blizzards, frontal and convective rainfall, hail, 248 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo thunderstorms, glazing, fog and dust/sand transportation as dangerous phenomena (Bryant, 1991, Croitoru, Moldovan, 2005). Starting from these complex classifications and yet adapted to the particularities and to the scale of the study-area, a regionalization of the main climatic hazards could be done, based on the annual occurrence and the amplitude of the main thermal, pluvial and mixed phenomena. Figure 1: The position of meteorological stations according to relief unitsinthe South-West Development Region and itslocation within the Romanian territory (A) Thus, these could be grouped into two main categories: climatic hazards within the cold semester of the year (October - March) and climatic hazards within the warm semester ofthe year (April-September),revealing with accuracy the two periods in the year where the emergence and development of the extreme climatic phenomena have the greatest impact on the environment. Due to the representatively of the dangerous meteorological phenomena of the warm semester of the year by means of intensity, effects and the covering surface,the present paper analyses in detailthe environmental vulnerabilityto climatic hazards occurring during thistime span. Thus, the above mentioned climatic hazards were analysed in a GIS format, based on the processed annual, monthly and daily extreme climatic values for the period 1961-2007 (temperature, precipitations, wind, and dangerous climatic phenomena) from all the meteorological stations involved and on the climatic hazard elementsidentified within the study-area (Figure 1). In a first stage, main meteorological elements’ distribution maps (temperature, rainfall, wind) which fit into the area ofinterest have been analyzed by drawing the variabilitylines ofthe climatic parameters. Later on, the main meteorological phenomena specific to the warm semester of the year with different degrees of vulnerability have been analyzed and establish the main vulnerability classes (mixed, very high, high, medium and low). The identified vulnerability categories were underlined by the mean and maximum frequency, duration and intensity of hazardous meteorological phenomena, as well as by the periods in the year affected by these phenomena. Each climatic hazard was represented by a layer in GIS format comprising of the spatial distribution of the environmental vulnerability to the main climatic hazards which are affecting the studied area in order to emphasize the main threats of these hazardous phenomena to the environment. Following the layers’ superposition and correlation, a complex climatic hazard map for the warm semester of the year for the studyregion has resulted. The significance ofthe chosen dangerous climatic phenomena characteristic forthe warm semester of the year within the studied area was also emphasized through the analyses of the most significant extreme climatic sequences, considered as case-studies. 249 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo 3. Results Based on the methodology described above, the regionalization of the main hazardous meteorological phenomena that take theirtoll on the South-West Development Region between April and September could be performed in orderto make the climatic hazards map forthe warm semester ofthe year. Climatic hazards occurring during the warm semester of the year are caused by the exceeding of the multi-annual mean values in correlation with the general circulation of the atmosphere combined with solar radiation and with the nature of the subjacent surface or by the frequency and intensity of extreme climatic phenomena related to the global warming. Within the South-West Development Region, the meteorological phenomena with greatimpact on the environment during this period of the year are related to the action of heat waves and positivethermal singularities, dryness and drought, heavy rainfall,thunderstorms, hailstorms, strong winds, acid deposits and fog (Figure 3). Heat waves and positive thermic singularities are generated by the tropical air advections and the criteria according to which they are classified are as follow (Bogdan, Niculescu, 1999): - mean monthly temperatures of the hottest months (July, August) ≥ 250 C; - maximum daily temperatures that exceed 350 C (extremely hot days); - minimum nightly temperatures ≥ 200 C (tropical nights). Heat waves and positive thermic singularities are enabled by the complex interaction of different genetic factors such as: the intensity of the heating process, the relief’s characteristics (orographic barrier of the surrounding hills/mountains, exposure, massiveness and fragmentation), the vegetation cover, the physical and chemical characteristics of soillayer,the man-made related changes etc. The penetration of tropical heat waves in favourable synoptic situations has lead to excess values in the South-West Development Region which have reached the state of climaticrecord. Due to the persistence of anticyclonal baric formations for several days in a row, local heat-strike phenomena intensify which leads to en increase in the degree of aridity and drought, emphasizing the value ofthe positive thermic singularities. It ought to be noticed the presence of an extended area in south-east Oltenia, between Jiu River, the Danube and the Oltenia hills where massive heating processes are worthy of comparison with those in Bărăgan Plain, very well known in Romania for its increases aridisation process. The absolute maximum value in this area is only one degree lower than that ofthe entire country, and,in addition,the massive heating processes can be seen here earlier (35.5 0 C in Bechet on 04.10.1985) and later (43.50 C in Strehaia on 08.20.1946 and on 09.08.1946),than inthe rest ofthe country. Thus, Olteniaisthe firstarea ofthe country struck by heat waves the earliest(in spring), but also the latest(the first decade of September). This area could be considered the second epicentre of extreme heatin Romania (Marinică, 2006). Due to heat waves, as well as positive thermic singularities, the Oltenia Plain is affected by drought, a phenomenon which can be seen allthe more often and which has repercussions on the environment by the severe reduction in phreatic waters, changes in the structure and texture of the soil, phenological changes in vegetation etc. In the past decades, the southern part of the South-West Development Region has been struck by extreme heat. Such alterations have occurred during the heat waves of July 1916 and 1936, August 1946 and 1951, JuneJuly 1994 etc. A special situation isthe massive heating in the summer of 2000 when the intensity ofthe heat coincided with the year of maximum solar activity of a seculartype,resembling the one in 1946, only much more intense. Figure 2: Baric configuration in Europe on July 5th 2000 (ww w.wetterzentrale.de) The weather heating process began on July 2nd, 2000 when the Icelandic depression west of Great Britain up to the northern seas interacted with the Greenland Anticyclone above the Atlantic Ocean towards Northern 250 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo Africa.In this synoptic context the rapid advection of warm air over south-western area of Romania favoured a south-western circulation of airinthe whole ofthe inferiortroposphere (Figure 2). The final stage of the extreme heat reached its peak in the interval of July 4th-5th of 2000 when it affected the southern half of the country and the temperature-humidity index (ITU) exceeded the threshold of 80 units, which lead to an extremely high thermic hazard. In the South-West Development Region the hottest summer day in 2000 was the 4th of July, which also holds the record in the past 84 years forthe hottest day of any July (Table 1). Subsequently, within the same synoptic context, the tropical heat waves have hit repeatedly and in addition with the scarce quantities of rainfall, completed the massive heating aspect characteristic for the summer of 2000 in the South-West Development Region. As to theimpact maximum dailytemperatures have on the environment,exceeding the 350 C threshold has a negative impact on the environment. Taking into consideration the fact that temperatures are measured in meteorological shelter, its equivalent at soil level has 10-150 C more, which amplifies the thermic discomfort. Positive thermic singularities in the warm semester of the year have higher values that the criticalthreshold of 350 C in the southern part of the area under discussion, even exceeding 410 C in Oltenia Plain along the Jiu Valley, up to Filiaşitown. These thermic singularities are upheld by the frequency of days when characteristic maximum temperatures are registered of ≥300 C (tropical days), ≥350 C (extreme heat) and when minimal temperatures of ≥200 C (tropical nights) are also taken into account (Table 1). Meteorological Station Absolute maximu m temperature ≥300 C ≥350 C Relief unit (selection) (0 C)/date Obârşia Lotrului 29.0/5. July 0 0 Southern Carpathians Voineasa 36.7/4. July 11 2 Tg. Jiu 40.6/4. July 18 6 Getic Subcarpathians Polovragi 39.2/4. July 15 4 R m. Vâlcea 40.6/4. July 17 5 Apa Neagră (Padeş) 41.8/4. July 17 6 Getic Piedmont Tg. Logreşti 40.0/4. July 14 5 Drăgăşani 40.7/4. July 18 7 Vânju Mare 42.4/4. July 17 9 Oltenia Plain Băileşti 43.1/4. July 19 11 Caracal 42.3/4. July 19 10 Calafat 43.2/4. July 18 12 Danube Floodplain Bechet 42.0/4. July 16 12 Source: National Meteorological Agency Database Table 1. Absolute extreme temperatures and the frequency of days when characteristic maximum temperatures are registered in July 2000,in the South-West Development Region Heat waves have a special impact on vegetation by underlying physiological and phenological changes and on humans by increasing the risk associated diseases or even death. Thus, following the heat wave in the summer of 2000, the Romanian Government issued the Government Ordinance 99/2000, regarding protection measures taken by the population in the case of extreme climatic phenomena. In the South-West Development Area the degree of vulnerability to heat waves and positive thermic singularitiesincreases from northto south,revealing an area of very high vulnerabilityin Oltenia Plain,along Jiu Valley, up to north of Filiaşi. Within this space, an area of a very high degree of vulnerability to aridity and drought can be found. This degree increases as we approach the Danube Floodplain. The Southern and Eastern slopes of Almăjului Mountains, the southern part of MehedinŃi Tableland, MehedinŃi Piedmont, BălăciŃei and Motrului Piedmont, central and southern part of OlteŃ and Cotmeana Piedmont, as well as the Olt valley up to the Râmnicu-Vâlcea – OcniŃa Depression displays a high degree of vulnerabilitytothese climatic hazards. Areas with a medium degree of vulnerability are in the north of MehedinŃi Tableland, the Getic Subcarpathians (except Târgu-Jiu and Râmnicu-Vâlcea – OcniŃa Depressions) expanding towards the Olt Valley inthe mountain sector,to the northern part of OlteŃ and Cotmeana Piedmonts. This area also displays a medium degree of vulnerabilityto aridity and drought phenomena. The mountain area subscribed to the South-West Development Region is not affected by these thermic hazards and is,thus, characterized by a low degree of vulnerability. By way of their characteristic parameters (intensity, duration, quantity), heavy rainfall are dependant on altitude, relief, solar radiation, and on the role as a orographic barrier the Carpathian Mountains play to the 251 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo humid air advections. The highly active dynamics of the humid tropical air or of the polar-maritime air over Romania’s territory, as well as the unequal heating of the terrestrial surface generates heavy rainfall during summer unleashing flood-waves. W hen taking into consideration the South-West Development Region,the evolution ofthe meteorological factors,aside from topographic particularities of riverbeds and fundamentalfeatures ofthe water system, plays a decisive role in the occurrence of floods most often brought about by heavy rainfall. From the point of view of the synoptic situations, heavy rainfalls within the area belong to certain types (Milea et. al.,1976): � Type 1 – heavy rainfall determined by the Mediterranean cyclones; � Type 2 – heavy rainfall determined by the cyclones centred inthe Pannonia Plain; � Type 3 – heavy rainfall inside the depression corridor formed by an Icelandic anti-cyclone and a cyclone from the eastern area ofthe Mediterranean Sea; � Type 4 – heavy rainfall brought about atthe limits of an anti-cyclonic field; � Type 5 – heavy rainfall of athermo-convective nature. As a moment when heavy rainfall occur after being generated by such weather situations, a greater frequency during spring and sum mer comes forwards when talking about the South-West Development Region, due tothe more frequent surging of warm and humid oceanic or Mediterranean air above the Romanian territory. During summer,the thermo-convective type 5 is prevalent. Within the analyzed area,floods are determined by a certain quantity of water coming from precipitations (Milea et. al., 1976): � in plain areas: − inthe case of dry soil,a quantity of water of 50 l/m2 or more isrequired in a 24 hour period; − inthe case of humid or soaked soil,a quantity of water of 15 – 30 l/m2 or more isrequired in a 24 hour period; � in hill or mountain areas: − inthe case of dry soil,a quantity of water of 30 l/m2 or more isrequired in a 24 hour period; − inthe case of humid or soaked soil,a quantity of water of 10 – 20 l/m2 or more isrequired in a 24 hour period. In the South-West development Region, the maximum monthly precipitation amounts of a year is registered inthe months of June – July. One sector where heavy rainfallareregistered isthat ofthe sand dunes at Ciuperceni – Calafat, where the underlying sand surface is rapidly heated and the frequency of unstable moist and tropical air is very high. Another sector greatly affected by heavy rainfall is that of the Subcarpathian Depressions of Oltenia, where the orographic barrier of the relief plays a major role in the increase in value of rainintensity, on the background of Mediterranean cyclones evolving on the classicalsouth-west north-east axis. In such situations,in plain, hill and tableland areas, rainfall of a torrential character have mean intensities of 4 m m/min or even higher. The greatest pluvialintensities determined during torrentialrain have been registered at: Meteorological station Ciupercenii Vechi Târgu Jiu Tismana After Marinică, 2006 Date of occurrence 28.06.1945 30.07.1941 27.06.1934 Mean intensity (m m/min) 6.15 5.60 0.50 Duration (minutes) 2 6 240 Total quantity of water (m m) 12.3 33.6 120.0 Table 2. Maximum quantity of heavy rainfallin Oltenia As the altitude increases,the intensity of torrentialrains drops under 3 mm/min due to the increase in air humidity which quells airtemperature values thus preventing thermo convection. The destructive aspects oftorrentialrainfall depend on the intensity, duration and on the water quantities, as well as on the numerous characteristics ofthe active area:lithology,the presence/absence ofthe vegetallayer, the declivity rate,the moment when they occur during the year (afterlong drought periods, when the soilis very dry and its cohesion isreduced and the rain’s force of erosion is higher, but also after a period of heavy rainfall, or after snow meltdowns when the soil is oversoaked). In such conditions, heavy rainfalls trigger geomorphological processes, affects crops, economic infrastructure (roads, bridges, railroads, networks of electrical energy transportation sewage systems and water/gas pipelines) and houses determining a negative impact on the environment. The environmental vulnerability to this climatic hazard takes into consideration especially the pluvial intensity, which,inthe south and the centre ofthe area under discussion becomes one ofthe highest.Itis worthy of mentioning the special role of meteorological phenomena associated with heavy rainfall (strong winds, hailstorms, floods etc.), which usually complete the aspects that make up the climatic hazard in the warm 252 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo semester ofthe year. One has to mention the impact ofthe precipitation registered during short periods oftime,of which those cumulated in 24 hours play a very importantrole. These amounts ofrainfallthatfallduring the warm semester of the year, genetically juxtaposed to thermo convective and frontal processes subscribe themselves to the Azores circulation of air which prevails, and reach the highest values in the whole year. The months during which the most abundant day precipitations are registered, are June, July and August,followed by the autumn months, and then by spring months (especially May). From the perspective of quantity, they exceed the mean values and quantities of the entire month, and in some cases they grow near to the annual mean. In the South-West Development Region, among the most representative such amounts are the following: Meteorological station M aximu m amount of precipitations/24 h (m m) Date of occurrence Bîcleş 110.1 31.07.1980 Calafat 194.0 4.06.1940 Dragotă, 2006 Table 3 Absolute maximum quantities of precipitations registered in 24 hours One ofthe most significant examples of precipitation fallen in short periods oftime and in large areasthat generate floods in the South-West Development Region isrepresented by the 1st-3rdof July heavy rainfall. The year 2005 stands outthrough thelong list of meteorological observations conducted since 1874, as an exceptional year in terms of the quantity of monthly rainfall, but especially during the warm semester. In Romania, this has generated, from April until November, seven flood waves with catastrophic results, since material damage of over one billion Euros, and 62 human casualties were registered (Dragotă, 2006). The synoptic contextfavourabletothe unfolding ofthe climatic hazard in July 2005 started off on the 30th of June 2005, due to vast depression areas north of Romania, in Ukraine and Poland that merged with the Icelandic depression above our country. The Azores Anticyclone had extended over the western and central areas of Europe and led to the contact of cold, polar air with the humid masses of air coming from the Mediterranean, thus generating an intense cyclic genesis best displayed by the synoptic situation on the 2nd of July 2005 (Figure 3). Figure 3: Baric configuration in Europe on July 2nd 2005 (ww w.wetterzentrale.de) The evolution ofthe synoptic context has led to the development of a strong associated cloud system, and inthe southern part ofthe country,especiallyin Oltenia,rainfall has been signalled associated with strong winds. The rainfall ofthree days equalled, and even exceeded,the multi-annual monthly mean withinthe interval 19012007 (Table 4),flooding wide areas in the South-West Development Region. A similar synoptic context stands out forthe 11th - 13th of July 2005 when heavy rainfallseriously damaged Jiu and Olt rivers catchments. Thus, due to the damage inflicted (11 human causalities and 839,415 mil. Ron), the month of July 2005 has been deemed to have been the month with the most serious floods in the past 50 years for the area under analysis (Dumitraşcu, Dumitraşcu, 2001, Dumitraşcu, 2006). The largest part of the South-West Development Region displays a medium vulnerability to climatic hazards generated by torrential rain overlapping with the central and northern part ofthe Oltenia Plain and with the entire piedmont area. 253 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo Precipitation amounts (m m) Relief unit Registration date 1.07.2005 2.07.2005 3.07.2005 Total(1-3.07 2005) Runcu 30.8 87.5 1.8 120.1 Getic Subcarpathians Balta 49.7 92.7 0.9 143.3 MehedinŃi Plateau Rovinari 66.2 93.1 2.8 162.1 Getic Piedmont Potcoava 191.5 2.9 194.4 Scorniceşti 137.0 2.0 139.0 Slatina 18.6 109.4 30.0 158.0 Breasta 55.0 75.0 26.0 156.0 Oltenia Plain MărunŃei 27.3 143.0 21.5 191.8 Corbu Buzeşti 3.0 164.0 167.0 Văleni 1.0 168.0 4.9 173.9 After Marinică, 2006 Table 4. Rainfall amounts registered between the 1st and the 3rd of July 2005 Meteorological station (selection) To the South, in the Danube Defilee, BlahniŃa Plain, DesnăŃui Plain and in the southern part of RomanaŃi Plain, as well as in the insular area that covers MehedinŃi Plateau and the depressions in the Oltenia Subcarpathians,the degree of vulnerabilitytothis climatic hazard is high.Inthe mountain area,the vulnerability totorrentialrain islow (Figure 4). Hailis a dangerous meteorological phenomenon which occurs during the warm semester of the year and has major consequences on the environment. Usually, hailis associated with heavy rainfalland lightning and its character of a climatic hazard is provided by the size oftheice hailstones,the duration,the amount of water,the intensity ofthe hailstorm and the wind speed thatleads to the storm before hail. The South-West Development Region generally displays the same degree of vulnerability to these meteorological phenomena as those determined by heavy rainfall, which is why on the map for dangerous meteorological hazards distribution concerning the warm semesterthey are represented by the same symbol. In the case of a high vulnerabilitythe mean annual frequency is 2-6 days of hail and the absolute annual mean is o 5-10 days. The areas described by this vulnerability step are:the Danube Defilee, DesnăŃui Plain and the south of RomanaŃi Plain, as well as the insular area covering MehedinŃi Plateau and the Oltenia Subcarpathians’ depressions.The medium vulnerability,specificforthe centre and north of Oltenia Plain and the entire piedmont areais determined by an average number of 1-2 days and a maximum number of 4-5 days of hail (Bogdan, Marinică, 2007). Areas which show low vulnerability register less than one case of hail in a mean regime and lessthan 4 cases per year of maximum frequency in multi-annualregime, being representative forthe entire mountain area. The damage caused by this climatic hazard is of a mechanic nature through their destructive effect the hailstones have on crops, as well asthrough the wind intensifications that accompany or anticipate hail. Thunderstorms are part of the electro-meteor category and consist of sudden atmospheric electrical discharge which manifestthemselves as a short-lived and intense light(lightning) and smothered sounds or loud thuds (thunder). Thunderstorms are associated with convection clouds (Cumulonimbus) and usually come accompanied by rainfalls. In the South-West Development Region, an average number of thunderstorm days on an annual basis, oscillates from south to north: - between 30-35 cases/year in the south of BălăciŃa Piedmont and in Oltenia Plain and display a low vulnerability; - 40-50 cases per year in the rest of the piedmont area and in the Oltenia Subcarpathians east of Târgu Jiu, leading to an medium vulnerability; - in MehedinŃi Plateau,the eastern part of the Getic Subcarpathians, as well as in the entire area overlapping the South-West Development Area have, alltogether, a number exceeding 45 cases of thunderstorms, thus determining a high vulnerability. Allthe year round,the maximum number of days/month of thunderstorms is reached in June, when, on a multi-annual regime,the maximu m amount of precipitations isregistered. Strong winds (with a frequency and speed of >15 m/s) are generated by the thermo-baric contrasts between the differentregions characterised by the high values of horizontal gradients,asthey can occur any time of the year.If during the cold semester of the year winds are associated with the snow layer and with snowfall, forthe warm semesterthey are seen as climatic hazards when associated especially with extreme heat or with the 254 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo begging of heavy rainfall. The main role in the dispersion of pollutantsin the terrestrial atmosphere isthat of masses’ circulation as well as the relief’s configuration. Atmospheric calm associated with the lack of precipitations favours the stagnation ofthese elements of pollution forlong periods of time, usually atlower altitudes and inthe same areas where they were generated. The factthat atmospheric precipitations along with strong winds are the most active pair of meteorological elements which influence the geographical environment is very well known. The annual mean ofthe dominant wind frequency is predominantly west-wards and in the direction ofits components. The aspects of a climatic hazard developed by the wind meteorological factor results in the strong intensification and are characterised by the sudden changes in direction and intensity, resulting in values of 16 m/s. These can be regarded as strong winds and convective thunderstorms associated with the passing of cold fronts of air. The aspect of a climatic hazard induced by strong winds and thunderstorms can produce significant damage, especially in the case of those that hit frontally (due to the large expansion area): the dislodging and destruction of roof-tops, suspended cables and especially electric energy transportation network, knocking down treesin hilly an mountain areas (especially ifthe front of air comes right after a period of heavy rainfall and the soilisintensely humid), affecting crops etc. In the South-West Development Region, the average number of days/year with strong winds varry between north (mountain area) where 50-100 cases have been registered,towards south (the Danube Valley and the south of Oltenia Plain) where theirfrequency drops to 10 cases, exceeding 10 days (Clima României, 2008), and the maximum number of cases possible during the warm semester can go beyond 40.In the north of Oltenia Plain and in the south of the Getic Plateau, due to local orographic factors and to the southern exposure, the number of days with strong windsis 10-25 cases. Withinthe analysed area, maximum winds speeds registered at the meteorological stations display a variety in value different,in the sense that the lowest value is specific to BlahniŃa Plain and to the south of DesnăŃui Plain (20-30 m/s) while the Oltenia Subcarpathians east of Tismana River registerthe lowest maximu m speeds (under 20 m/s). In the rest of the plain and piedmont areas on the southern slope of Vulcan-Parâng-CăpăŃânii Mountains and in MehedinŃi Mountains and Mehedinti Plateau, maximu m speeds range between 30 and 40 m/s. In the mountain area maximum wind speeds of over 40 m/s are registered, providing an elevated frequency of this climatic hazard. Combining the climatic parametersrepresented by the maximu m speed and frequency of days with strong winds (>15 m/s) that have an impact on the South-West Development Regions’s environment; areas displaying vulnerability to strong winds can be individualized. The north area of the analysed region is the most exposed partto this climatic hazard, and overlaps the high-altitude mountain space,thus describing a region with a very high vulnerability. The south-west part of Almăj Mountains,the high-altitude mountain area,the Danube Gorge, MehedinŃi Mountains,the south ofthe Getic Plateau and the north of Oltenia Plain display a high vulnerabilityto this climatic hazard. A medium vulnerability is characteristic for the southern slopes of the Carpathian Mountains, as they merge with the Oltenia Subcarpathians, Olt Valley (mountain sector),the north of the Getic Piedmont, Danube Valley, BlahniŃa Plain, DesnăŃui Plain, south of RomanaŃi Plain. Areas with a low vulnerability generally overlap the east of MehedinŃi Plateau and the Oltenia Subcarpathians. Within this area, atthe lowest altitudes of Târgu Jiu – Câmpu Mare Depression, an insular area stands out within which the degree of vulnerabilityto thistype of meteorological phenomenon is very low. Acid deposits and fog are a very important source of pollution of the atmosphere, due to the mechanic (fog) and chemical (acid deposits) effectsthat have a negative impact on the environment. Fog is basically atmospheric suspension in the form of microscopic drops that reduce visibility to less than 1 kilometre. The presence of fog,in no matter what shape, has a negative impact on transport means (road transport, watertransport, airtransport,sewage transport) and on population’s health. The highest monthly frequency of fog within a year can be registered during winter (December-January), and the lowest during summ er (June-August). The physical and geographical allotment of this hydro-meteor highlightsthe highest number of foggy days (40-50)inthe subcarpathian depressions and down the valleys of Jiu River (Motru – Rovinari coalfield) and Olt River (from the mountain region to the plain region). Isolated, in Târgu Jiu – Câmpu Mare and Râmnicu Vâlcea – OcniŃa depressions up to 60 cases in annual mean regime are registered.In the rest ofthe analysed territory the number offoggy days decreases,rarely exceeding 40 cases as an average value per year (e.g.:the Danube Valley). W hen associated with various polluting substances its effect on the environment increases in direct ratio with their concentration rate, and the intensity and duration of parameters characteristic for this meteorological phenomenon amplify or diminish the content of polluting substances existentinthat micro-climatic area. Precipitations associated with polluting substances enhance the negative impact fog has on the environment.In a polluted area, asinthe case of some regions inthe analysed area, 5% of the polluting elements present in the free atmosphere can be engulfed in the precipitations that fall on the soil (wash-out).In the case where precipitations come from a dirty cloud that has a high concentration of polluting substances (rain-out), 255 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo these substances reach the earth’s surface atthe same time the precipitations do and at great distances from the emission source. The mostimportantindustrialsources for atmosphere pollution are concentrated in the urban ecosystems of: Râmnicu Vâlcea (Oltchim S.A.), Craiova (S.C. Dolj Chim, CET 1 IşalniŃa, CET 2 Şimnic), Slatina (Slatina Industrial Platform), Târgu Jiu (Romcin), Drobeta Turnu Severin (Power Plant), Turceni (Energetic Complex), Rovinari(CET Rovinari) etc.These sources also determine the pollution caused by the dusts conditioned during constant exploitation in the Motru-Rovinari coal exploitation, as well as by the toxic substances and polluting emissions in the atmosphere that come from the fuel burns coming out oftechnological processes,from thermic plantsthat produce heat and running water, and,last but notleast,from road traffic. These lead to the identification, within the South-West Development Area, of regions that display different degrees of vulnerability associated with sources previously mentioned that manifestthemselves even 45 km around the affected cities. The direction and the average speed in a multi-annual wind system, imprintthe differentiated dispersion also favoured by the local configuration of the relief as well as by the degree of sheltering conveyed by the frequency ofthe atmospheric calm. Figure 4: Climatic hazards in the warm semester ofthe year within South-West Development Region Acid precipitations or acid rainfall that have a pH value lower that 5.6 refer to the process of dry or humid deposit ofthe acid materialsin the atmosphere on the earth’s surface.In the absence of rain or any other sort of precipitations, atmospheric polluting substances shift from the atmosphere by gravitational fall and by direct contact with the soil, vegetation and buildings. The rate for the dry deposit of these polluting substances varies between 0.1 and 1.0 cm/s. Dry deposits can have a great contribution to the increase in acidity, and both types of deposits (dry and humid) bear the name of acid deposits (Fărcaş, Croitoru, 2003) which manifest themselves associated with the risk of fog formation and in the topo-climatic conditions ofthe heatisland of the urban ecosystems affected (Râmnicu Vâlcea, Craiova, Slatina, Târgu Jiu, Drobeta Turnu Severin, Turceni, Rovinari) and increasesin directratio with these cities’territorial expansion. Due to the factthatroad traffic has increased, sources of mobile pollution have also multiplied and, associated with dangerous meteorological phenomena (mist,fog, acid deposits etc.)lead to a majorimpact on the environment and on the state of health of the population. Thus, by analyzing the main dangerous meteorological phenomena having different degrees of climatic vulnerability characteristicforthe warm semester ofthe yearinthe South-West Development Region a complex hazard map with the identified vulnerability areas have resulted (Figure 4). 256 �1st International Syposium on Sustainable Development, June 9-10 2009, Sarajevo 4. Conclusions The joint effect of hazardous climatic phenomena can be felt gradually depending on how their parameters manifestthemselves: according to the altitude (from the plains’levelto he mountain areas), but also from East to West. During the warm semester of the year, the central, southern area of the Getic Piedmont, as well as the southern slopes of the Southern Carpathians reveal an area of mean vulnerability to the climatic hazards characteristic for this time of the year. Towards the south,in the Oltenia Plain, an area affected by heat waves accompanied by positive thermal singularities, drought and dryness, heavy rainfall and winds of a regional and local character, the degree of vulnerability is high. In the Subcarpathian depressions and in the northern area of the Getic Piedmont, an area with mean towards low vulnerability stands out, especially regarding heavy rainfall and thunderstorms, which, when confronted with atmospheric polluting sources,favour the existence of insular areas with acid deposits. The mountain sectors exhibitlow vulnerability to heat waves, but a high degree of vulnerabilityto humidity, winds, and thunderstorms. The importance of making the hazard maps consists in assessing and monitoring the environment vulnerabilityto different disturbing factorsin orderto avoid or even diminish their negative impact. Hereby,the maps dictate the delimitation of areas with different vulnerability scales to the analyzed hazards, having a practicalimportance forthe human communities atregional and locallevel. References Bălteanu, D., Şerban, Mihaela (2004), Natural and technological hazards in Romania, Environmental Change and Sustainable Development, Proceedings of the second Romanian–Turkish Workshop of Geography, Bucharest, Romania/June 15-22, 2003, Editura Universitară, Bucharest Bogdan, Octavia, Marinică, I., (2007), Hazarde meteo-climatice din zona temperată. Factori genetici şi vulnerabilitate cu aplicaŃii la România, Editura Lucian Blaga, Sibiu Bryant E. A., (1991), Natural Hazards, Cambrige University Press Croitoru Adina, Moldovan F., (2005), Vulnerability of Romanian territory to climatic hazards, Analele UniversităŃii de Vest din Timişoara, Seria Geografia, XV/2005 Dragotă, Carmen-Sofia., (2006), PrecipitaŃiile excedentare din România, Editura Academiei Române, Bucureşti Dumitraşcu, Monica, Dumitraşcu, C. (2001), Vulnerabilitatea ecosistemelor urbane la riscuri naturale, Comunicări de Geografie, IV, Universitatea din Bucureşti Dumitraşcu, Monica, Dumitraşcu, C., Douguedroit, Annick (2002), ConsideraŃii asupra tendinŃei de evoluŃie a temperaturii aerului în Oltenia, Rev. Geografică, VIII, p. 18-24. Dumitraşcu, Monica, (2006), Modificări ale peisajului în Câmpia Olteniei, Edit. Academiei Române, Bucureşti Marinică, I., (2006), Fenomene climatice de risc în Oltenia, Editura Autograf MJM, Craiova Milea Elena et. al., (1976), Studiul meteorologic al apelor mari din 4-12 octombrie 1972 în sudul Ńării, Culegere de lucrări a INH ***, (2002), Romania. The Environment and the Electric Transportation Network. Geographical Atlas, Editura Academiei Romane, Bucuresti ***, (2008), Clima României, Editura Academiei Române, Bucureşti 257 � 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. 473 Title A name given to the resource Climatic Hazards Phenomena of the Warm Semester of the Year in the South-West Development Region. Romania Author Author Dragotă, Carmen-Sofia Grigorescu, Ines Dumitrascu, Monica Dumitrascu, Costin Abstract A summary of the resource. The South-West Development Region is exposed to several climatic hazards with major impact upon the environment. The paper emphasizes the occurrence and the amplitude of the hazard phenomena characteristic of the warm semester of the year within the study area based on processed annual, monthly and daily extreme climatic values (temperature, precipitations, wind, dangerous atmospheric phenomena) from all the meteorological stations involved (1961-2007) in order to establish the main vulnerability classes (mixed, very high, high, medium and low). On the basis of this survey a climatic hazard map was realized in order to emphases the main threats of these hazardous phenomena (heat waves and positive thermal singularities, dryness and drought, heavy rainfall, thunderstorms, hail storms, strong winds, acid deposits and fog) to the environment. Thus, certain areas have been identified with different vulnerability classes: mixed, high and very high, medium and low to the above mentioned climatic hazards. 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 Q Science (General) https://omeka.ibu.edu.ba/files/original/b26595efc28ad1061041d54c95c6f372.pdf 194b2e51a734a9a514c96b5039f69e48 PDF Text Text 3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Kazim Develioglu1, Kemal Kantarci2 1Akdeniz University, Alanya Faculty of Business,Department of Human Resource Management 2Akdeniz University, Alanya Faculty of Business Department of Tourism Management E-mails: kdevelioglu@akdeniz.edu.tr, kantarci@akdeniz.edu.tr Abstract Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitivenes Index” to analyse the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out that Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. Keywords: Cluster, Competitiveness, Strategic Management, Balkan Countries 1.Literature review In an era of great competition among nations and firms, it is vital for firms’ strategy makers to develop strategies to adapt to environmental changes and speed their processes. Vietor (2006) indicates that, in national level, as a result of globalizaton, countries compete each other in terms of markets, technology, skills, and investment to grow and raise their standards of living. Although, macroeconomic competitiveness creates the potential for high productivity, it is not sufficient. Productivity ultimately depends on improving the micro economic capability of the economy and sophistication of local competition (Porter, 2009). Economic Forum (2011) defines competitiveness as the set of institutions, policies, and factors that determine the level of productivity of a country. The level of productivity, in turn, sets the level of prosperity that can be earned by an economy. The productivity level also determines the rates of return obtained by investments in an economy, which in turn are the 199 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo fundamental drivers of its growth rates. In other words, a more competitive economy is one that is likely to grow faster over time. “Competitive strategy is the search for a favorable competitive position in an industry, the fundamental arena in which competition occurs. Competitive strategy aims to establish a profitable and sustainable position against the forces that determine industry competition” (Porter, 2004: 1). To be competitive, nations are struggling to remain competitive by having regional specializations in terms of hihger value added – non manufacturing industries and Research & Development intensive manufacturing niches (OECD, 2007). Similarly, Porter (2009) indicates that competitiveness depends on the productivity with which a nation uses its human, capital, and natural resources. Economic coordination among neighboring countries can significantly enhance competitiveness. By the similar vein, as developing countries, economic collaboration among Balkan countries is expected to enhance sustainable competition. At this point, it has to be noted that competition policies of advanced countries might not be appropriate for the stage of development of most developing countries (Singh, 1999). Singh (1999) indicates that “It is important for developing countries to have a competition policy which is designed to take appropriate account of their level of development and the long term objective of sustained economic growth. This is in part due to the potential effects of the international merger movement and also because of privatization, deregulation and liberalization which have occurred in the domestic economies of most developing countries” (pp. 1). As a developing region, the Balkan peninsula is becoming recovered and develop after postsocialist and instable period because of the war among some of states. “The Balkan Peninsula is an important area, having witnessed important historical and political experiences and incidents for ages” (Çelebioğlu 2011: 112). Having a population of, nearly, 140 million citizens, the Balkan region provides a promising market for firms from international arena and especially Balkan countries. As it is indicated in WEF’s (2011-2012) Global Competitiveness Report, “national competitiveness, we note that despite much work in the area of sustainability, there is not yet a well-established body of literature on the link between productivity (which is at the heart of competitiveness) and sustainability. However, at the World Economic Forum we believe that the relationship between competitiveness and sustainability is crucial (pp. 52). Developing economically sound strategies, especially for international firms and firms from the region, it is crucial to examine competitiveness indicators of Balkan countries. This will help firms to develop a sustainable competitive edge by investing and selling in the region. Taking this neccessity into account, this study aims to fill the gap for lack of comparative studies for Balkan countries. More specifially, we analyse Balkan countries’ competitiveness factors by, first, clustering them and, second, compare the clusters to grasp which cluster perform in which competitive factor well. 200 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo In this study, we used the data of The World Economic Forum’s (WEF) classification of “Global Competitiveness Index” factors to examine indicators that are expected to influence sustainable competition in the region. for the years between 2008-2011. WEF’s classification consists of three subindexes and 12 factors that measure these subindexes, which are reported below:     Basic requirements (Institutions, Infrastructure, Macroeconomic environment, and Health and primary education) Efficiency enhancers (Higher education and training, Goods market efficiency, Labor market efficiency, Financial market development, Technological readiness, and Market size) Innovation and sophistication factors (Business sophistication and Innovation) 2.Methodology As it is mentioned above, in this study, we used the data of The World Economic Forum’s (WEF) “Global Competitiveness Index” for the years between 2008-2011. By using the secondary data, we aimed, first, to cluster the Balkan countries in terms of above mentioned “Global competitiveness index factor”s and second to compare these clusters to reveal which of them are more competitive in subindexes and factors. 3.Findings In order to cluster the Balkan countries in terms of Global competitiveness factors, we employed a k-means cluster analysis and derived two clusters, which is reported in Table 1 below. One of these clusters (Cluster 1) includes countries: Bulgaria, Croatia, Greece, Romania, Serbia, and Turkey. The second cluster (Cluster 2) countries are Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia. Scores in Table 1 betray that only in market size competitiveness factor, Cluster 1 countries have a competitive advantage compared with Cluster 2 countries. Table 1: Cluster Analysis Results Cluster Global Competitiveness Factor 1 2 F p Institutions 3,63 4,35 1,784 0,214 Infrastructure 4,00 3,38 0,401 0,542 Macroeconomic environment 4,70 4,93 1,827 0,209 Health and primary education 5,45 5,90 0,033 0,860 Higher education and training 3,95 4,38 0,022 0,885 201 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Goods market efficiency 4,33 4,35 0,396 0,545 Labor market efficiency 3,60 4,58 3,599 0,090 Financial market development 4,18 4,83 0,021 0,889 Technological readiness 3,78 4,05 0,105 0,754 Market size 5,20 2,05 15,499 0,003 Business sophistication 4,20 3,80 0,018 0,897 Innovation 3,13 3,30 0,120 0,737 Table 2: t-test Results for Cluster Membership and Global Competitiveness Subindexes Std. Deviation Variable Basic requirements Efficiency enhancers Innovation and sophistication factors Cluster Mean 1 4,38 0,246 2 4,47 0,449 1 4,06 0,161 2 3,87 0,326 1 3,39 0,214 2 3,34 0,473 t p -0,858 0,396 2,547 0,015 0,479 0,634 In order to compare Cluster 1 and Cluster 2 countries, we used t-test analysis and obtained the results, which are reported in Table 2 and Table 3. In table 2, we compared two clusters in terms of Global Competitiveness subindexes. Results in Table 2 portray that Cluster 1 (Mean= 4,06) and Cluster (Mean= 3,87) countries both had medium-level but statistically significant difference (t= 2,547; P= 0,015) in efficiency enhancers subindex. For the other two subindexes, namely basic requirements (t= 0,858; P= 0,396) and innovation and sophistication factors (t= 0,479; P= 0,634), both of the clusters showed no statistically significant results. It has to be noted that in both, basic requirements and innovation and sophistication factors, Cluster 1 and Cluster 2 countries had medium level competitiveness scores. Table 3: t-test Results for Cluster Membership and Global Competitiveness Factors Variable 202 Cluster Mean Std. t p �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Deviation Institutions Infrastructure Macroeconomic environment Health and primary education Higher education and training Goods market efficiency Labor market efficiency Financial market development Technological readiness Market size Business sophistication Innovation 1 3,53 0,233 2 3,84 0,515 1 3,70 0,691 2 3,43 0,851 1 4,55 0,482 2 4,89 0,435 1 5,73 0,228 2 5,76 0,319 1 4,21 0,254 2 4,17 0,625 1 4,00 0,239 2 4,12 0,376 1 4,04 0,325 2 4,34 0,208 1 4,04 0,224 2 4,07 0,504 1 3,82 0,286 2 3,74 0,616 1 4,20 0,579 2 2,83 0,479 1 3,75 0,313 2 3,72 0,427 1 3,45 0,131 2 2,97 0,507 -2,657 0,011 1,158 0,254 -2,406 0,021 -0,332 0,741 0,305 0,762 -1,194 0,239 -3,592 0,001 -0,255 0,800 0,597 0,554 8,427 0,000 0,268 0,790 0,705 0,485 Examination of Table 3 revealed mixed results for Cluster 1 and Cluster 2 countries. In Table 3, the results betray that Cluster 2 countries scored better in three of twelve Global Competitiveness factors than Cluster 1 countries. Only for market size competitiveness factor, Cluster 1 countries had statistically significant difference scores (t= 8,427; P= 0,000). 203 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo 4.Discussion Analysis results at the findings section pointed out that competitiveness scores of Balkan countries, whether it belongs Cluster 1 or Cluster 2, are relatively low or medium and need to be developed. Specifically, Cluster 2 countries (Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia) should have a national strategic plan to improve their competitive position in infrastructure (quality of roads, railroads, ports, and airtransport infrastructure), higher education and training (secondary education enrollment, tertiary education enrollment, quality of the educational system, math &science education, management schools, internet access in schools, availability of research and services), goods market efficiency (intensity of local competition, extent of market dominance, effectiveness of anti-monopoly policy, extent and effect of taxation, total tax rate, number of procedures to start a business, agricultural policy cost, buyer sophistication), labor market efficiency (cooperation in labor-employer relations, flexibility of wage determination, hirin and firing practices, women in labor force), financial market development (availability of financial services, effordability of financial services, ease of access to loans, ventur capital availability), technological readiness (availability of latest technologies, firm-level technology absorption, FDI and technology transfer, internet related factors), business sophistication (local supplier quantity and quality, state of cluster development, nature of competitive advantage, control of international distribution, extent of amrketing, willingness to delegate authority), and innovation (capacity for innovation, quality of scientific research institutions, company spending on R&D, utility patents granted). Similarly, Cluster 1 countries should emphasize on development of institutions, infrastructure, financial market, and technological environment and better conditions in macroeconomic environment, higher education and training, goods market efficiency, business sophistication, and innovation. It seems from analysis results that the major advantage for these cluster is their population and market size. This picture warns us that firms plan to invest in the Balkan region should be aware of disadvantageous competitive factors in both cluster countries. It seems that eventhough both clusters have disadvantages for investors they also offer certain advantages for them. We believe that for strategy makers in national governments and firms, these findings provide useful insights to develop their strategic plans. REFERENCES Çelebioğlu, F. (2011). Investigation of Development Indicators in the Balkan Countries for the Post-Socialist Period, Journal of Economic and Social Studies, Volume 1, Number 1, 111-122. Porter, M. E. (2004). Competitive Advantage, Free Press, New York. 204 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Porter, M. E. (2009). The Competitive Advantage of Nations, States, and Regions, Harvard Business School, Advanced Management Program. OECD, (2007). Competitive Regional Clusters: National Policy Approaches, (http://www.oecd.org/document/2/0,3746,en_2649_33735_38174082_1_1_1_1,00.html), (22.04.2012). Singh, A., (1999). Competition Policy, development and developing Countries, Indian Council for research on international economic relations, New Delhi. Vietor, R.H.K. (2006). Strategy, Structure, and Government in the Global Economy, Harvard Business School Press ,Boston, Massachusetts. World Economic Forum, The Global Competitiveness Report, (2008-2009). World Economic Forum, The Global Competitiveness Report, (2009-2010). World Economic Forum, The Global Competitiveness Report, (2010-2011). World Economic Forum, The Global Competitiveness Report, (2011-2012). Implementation Of Critical Path Method And Project Evaluation And Review Technique Ali Göksu, Selma Ćatović International Burch University,Faculty of economics Management and information technologies Sarajevo, Bosnia and Herzegovina Abstract Because of the growing effects of the globalization in various business environments, the manufacturing industry is expected to be effective and yet efficient. According to this, in 205 � 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. 1113 Title A name given to the resource Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Author Author Kazim, Develioglu Abstract A summary of the resource. Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitivenes Index” to analyse the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out that Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. Keywords: Cluster, Competitiveness, Strategic Management, Balkan Countries 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/b7bc98d09981b7daf894effbf5781231.pdf b40a53b0771d61acf2bad3e7fa9bf8d4 PDF Text Text 3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Kazim Develioglu1 ,Kemal KantarcI2 1Akdeniz University, Alanya Faculty of Business,Department of Human Resource Management Alanya-Antalya / TURKEY 2Akdeniz University, Alanya Faculty of Business,Department of Tourism Management Alanya-Antalya / TURKEY E-mails: kdevelioglu@akdeniz.edu.tr ,kantarci@akdeniz.edu.tr Abstract Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitivenes Index” to analyse the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out that Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. Keywords: Cluster, Competitiveness, Strategic Management, Balkan Countries 1.Literature review In an era of great competition among nations and firms, it is vital for firms’ strategy makers to develop strategies to adapt to environmental changes and speed their processes. Vietor (2006) indicates that, in national level, as a result of globalizaton, countries compete each other in terms of markets, technology, skills, and investment to grow and raise their standards of living. Although, macroeconomic competitiveness creates the potential for high productivity, it is not sufficient. Productivity ultimately depends on improving the micro economic capability of the economy and sophistication of local competition (Porter, 2009). Economic Forum (2011) defines competitiveness as the set of institutions, policies, and factors that determine the level of productivity of a country. The level of productivity, in turn, sets the level of prosperity that can be earned by an economy. The productivity level also determines the rates of return obtained by investments in an economy, which in turn are the fundamental drivers of its growth rates. In other words, a more competitive economy is one that is likely to grow faster over time. 125 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo “Competitive strategy is the search for a favorable competitive position in an industry, the fundamental arena in which competition occurs. Competitive strategy aims to establish a profitable and sustainable position against the forces that determine industry competition” (Porter, 2004: 1). To be competitive, nations are struggling to remain competitive by having regional specializations in terms of hihger value added – non manufacturing industries and Research & Development intensive manufacturing niches (OECD, 2007). Similarly, Porter (2009) indicates that competitiveness depends on the productivity with which a nation uses its human, capital, and natural resources. Economic coordination among neighboring countries can significantly enhance competitiveness. By the similar vein, as developing countries, economic collaboration among Balkan countries is expected to enhance sustainable competition. At this point, it has to be noted that competition policies of advanced countries might not be appropriate for the stage of development of most developing countries (Singh, 1999). Singh (1999) indicates that “It is important for developing countries to have a competition policy which is designed to take appropriate account of their level of development and the long term objective of sustained economic growth. This is in part due to the potential effects of the international merger movement and also because of privatization, deregulation and liberalization which have occurred in the domestic economies of most developing countries” (pp. 1). As a developing region, the Balkan peninsula is becoming recovered and develop after postsocialist and instable period because of the war among some of states. “The Balkan Peninsula is an important area, having witnessed important historical and political experiences and incidents for ages” (Çelebioğlu 2011: 112). Having a population of, nearly, 140 million citizens, the Balkan region provides a promising market for firms from international arena and especially Balkan countries. As it is indicated in WEF’s (2011-2012) Global Competitiveness Report, “national competitiveness, we note that despite much work in the area of sustainability, there is not yet a well-established body of literature on the link between productivity (which is at the heart of competitiveness) and sustainability. However, at the World Economic Forum we believe that the relationship between competitiveness and sustainability is crucial (pp. 52). Developing economically sound strategies, especially for international firms and firms from the region, it is crucial to examine competitiveness indicators of Balkan countries. This will help firms to develop a sustainable competitive edge by investing and selling in the region. Taking this neccessity into account, this study aims to fill the gap for lack of comparative studies for Balkan countries. More specifially, we analyse Balkan countries’ competitiveness factors by, first, clustering them and, second, compare the clusters to grasp which cluster perform in which competitive factor well. In this study, we used the data of The World Economic Forum’s (WEF) classification of “Global Competitiveness Index” factors to examine indicators that are expected to influence sustainable competition in the region. for the years between 2008-2011. WEF’s classification consists of three subindexes and 12 factors that measure these subindexes, which are reported below: 126 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo    Basic requirements (Institutions, Infrastructure, Macroeconomic environment, and Health and primary education) Efficiency enhancers (Higher education and training, Goods market efficiency, Labor market efficiency, Financial market development, Technological readiness, and Market size) Innovation and sophistication factors (Business sophistication and Innovation) 2.Methodology As it is mentioned above, in this study, we used the data of The World Economic Forum’s (WEF) “Global Competitiveness Index” for the years between 2008-2011. By using the secondary data, we aimed, first, to cluster the Balkan countries in terms of above mentioned “Global competitiveness index factor”s and second to compare these clusters to reveal which of them are more competitive in subindexes and factors. 3.Findings In order to cluster the Balkan countries in terms of Global competitiveness factors, we employed a k-means cluster analysis and derived two clusters, which is reported in Table 1 below. One of these clusters (Cluster 1) includes countries: Bulgaria, Croatia, Greece, Romania, Serbia, and Turkey. The second cluster (Cluster 2) countries are Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia. Scores in Table 1 betray that only in market size competitiveness factor, Cluster 1 countries have a competitive advantage compared with Cluster 2 countries. Table 1: Cluster Analysis Results Cluster Global Competitiveness Factor 1 2 F p Institutions 3,63 4,35 1,784 0,214 Infrastructure 4,00 3,38 0,401 0,542 Macroeconomic environment 4,70 4,93 1,827 0,209 Health and primary education 5,45 5,90 0,033 0,860 Higher education and training 3,95 4,38 0,022 0,885 127 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Goods market efficiency 4,33 4,35 0,396 0,545 Labor market efficiency 3,60 4,58 3,599 0,090 Financial market development 4,18 4,83 0,021 0,889 Technological readiness 3,78 4,05 0,105 0,754 Market size 5,20 2,05 15,499 0,003 Business sophistication 4,20 3,80 0,018 0,897 Innovation 3,13 3,30 0,120 0,737 Table 2: t-test Results for Cluster Membership and Global Competitiveness Subindexes Variable Basic requirements Efficiency enhancers Innovation and sophistication factors Std. Deviation Cluster Mean 1 4,38 0,246 2 4,47 0,449 1 4,06 0,161 2 3,87 0,326 1 3,39 0,214 2 3,34 0,473 t p -0,858 0,396 2,547 0,015 0,479 0,634 In order to compare Cluster 1 and Cluster 2 countries, we used t-test analysis and obtained the results, which are reported in Table 2 and Table 3. In table 2, we compared two clusters in terms of Global Competitiveness subindexes. Results in Table 2 portray that Cluster 1 (Mean= 4,06) and Cluster (Mean= 3,87) countries both had medium-level but statistically significant difference (t= 2,547; P= 0,015) in efficiency enhancers subindex. For the other two subindexes, namely basic requirements (t= 0,858; P= 0,396) and innovation and sophistication factors (t= 0,479; P= 0,634), both of the clusters showed no statistically significant results. It has to be noted that in both, basic requirements and innovation and sophistication factors, Cluster 1 and Cluster 2 countries had medium level competitiveness scores. 128 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Table 3: t-test Results for Cluster Membership and Global Competitiveness Factors Mean Std. Deviation 1 3,53 0,233 2 3,84 0,515 1 3,70 0,691 2 3,43 0,851 Macroeconomic environment 1 4,55 0,482 2 4,89 0,435 Health and primary education 1 5,73 0,228 2 5,76 0,319 Higher education and training 1 4,21 0,254 2 4,17 0,625 Goods market efficiency 1 4,00 0,239 2 4,12 0,376 1 4,04 0,325 2 4,34 0,208 Financial market development 1 4,04 0,224 2 4,07 0,504 Technological readiness 1 3,82 0,286 2 3,74 0,616 1 4,20 0,579 Variable Institutions Infrastructure Labor market efficiency Market size 129 Cluster t p -2,657 0,011 1,158 0,254 -2,406 0,021 -0,332 0,741 0,305 0,762 -1,194 0,239 -3,592 0,001 -0,255 0,800 0,597 0,554 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo Business sophistication Innovation 2 2,83 0,479 1 3,75 0,313 2 3,72 0,427 1 3,45 0,131 2 2,97 0,507 8,427 0,000 0,268 0,790 0,705 0,485 Examination of Table 3 revealed mixed results for Cluster 1 and Cluster 2 countries. In Table 3, the results betray that Cluster 2 countries scored better in three of twelve Global Competitiveness factors than Cluster 1 countries. Only for market size competitiveness factor, Cluster 1 countries had statistically significant difference scores (t= 8,427; P= 0,000). 4.Discussion Analysis results at the findings section pointed out that competitiveness scores of Balkan countries, whether it belongs Cluster 1 or Cluster 2, are relatively low or medium and need to be developed. Specifically, Cluster 2 countries (Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia) should have a national strategic plan to improve their competitive position in infrastructure (quality of roads, railroads, ports, and airtransport infrastructure), higher education and training (secondary education enrollment, tertiary education enrollment, quality of the educational system, math &science education, management schools, internet access in schools, availability of research and services), goods market efficiency (intensity of local competition, extent of market dominance, effectiveness of anti-monopoly policy, extent and effect of taxation, total tax rate, number of procedures to start a business, agricultural policy cost, buyer sophistication), labor market efficiency (cooperation in labor-employer relations, flexibility of wage determination, hirin and firing practices, women in labor force), financial market development (availability of financial services, effordability of financial services, ease of access to loans, ventur capital availability), technological readiness (availability of latest technologies, firm-level technology absorption, FDI and technology transfer, internet related factors), business sophistication (local supplier quantity and quality, state of cluster development, nature of competitive advantage, control of international distribution, extent of amrketing, willingness to delegate authority), and innovation (capacity for innovation, quality of scientific research institutions, company spending on R&D, utility patents granted). Similarly, Cluster 1 countries should emphasize on development of institutions, infrastructure, financial market, and technological environment and better conditions in macroeconomic environment, higher education and training, goods market efficiency, business sophistication, and innovation. It seems from analysis results that the major advantage for these cluster is their population and market size. This picture warns us that firms plan to invest in the Balkan region should be aware of disadvantageous competitive factors in both cluster countries. It seems that eventhough both clusters have disadvantages for investors they also offer certain advantages for 130 �3rd International Symposium on Sustainable Development, May 31 - June 01 2012, Sarajevo them. We believe that for strategy makers in national governments and firms, these findings provide useful insights to develop their strategic plans. REFERENCES Çelebioğlu, F. (2011). Investigation of Development Indicators in the Balkan Countries for the Post-Socialist Period, Journal of Economic and Social Studies, Volume 1, Number 1, 111-122. Porter, M. E. (2004). Competitive Advantage, Free Press, New York. Porter, M. E. (2009). The Competitive Advantage of Nations, States, and Regions, Harvard Business School, Advanced Management Program. OECD, (2007). Competitive Regional Clusters: National Policy Approaches, (http://www.oecd.org/document/2/0,3746,en_2649_33735_38174082_1_1_1_1,00.html), (22.04.2012). Singh, A., (1999). Competition Policy, development and developing Countries, Indian Council for research on international economic relations, New Delhi. Vietor, R.H.K. (2006). Strategy, Structure, and Government in the Global Economy, Harvard Business School Press ,Boston, Massachusetts. World Economic Forum, The Global Competitiveness Report, (2008-2009). World Economic Forum, The Global Competitiveness Report, (2009-2010). World Economic Forum, The Global Competitiveness Report, (2010-2011). World Economic Forum, The Global Competitiveness Report, (2011-2012). 131 � 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. 1372 Title A name given to the resource Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Author Author Kazim , Develioglu Abstract A summary of the resource. Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitivenes Index” to analyse the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out that Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. Keywords: Cluster, Competitiveness, Strategic Management, Balkan Countries 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/d398261f7baecb6b92b01fa04e7bf616.pdf 93e12514df6a427e73370dfe12a3a5ae PDF Text Text Journal of Economic and Social Studies Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Kazım DEVELİOĞLU Akdeniz University, Alanya Business Faculty Alanya, Turkey kdevelioglu@akdeniz.edu.tr Kemal KANTARCI Akdeniz University, Alanya Business Faculty Alanya, Turkey kantarci@akdeniz.edu.tr Abstract: Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitiveness Index” to analyze the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out those Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. KEYWORDS: Cluster, Competitiveness, Strategic Management, Balkan Countries ARTICLE HISTORY Submitted: 20 March 2012 Resubmitted: 15 July 2012 Resubmitted: 18 December 2012 Accepted: 24 December 2012 JEL code: M20 237 �Kazım DEVELİOĞLU & Kemal KANTARCI Literature review In an era of great competition among nations and firms, it is vital for firms’ strategy makers to develop strategies to adapt to environmental changes and speed their processes. Vietor (2006) indicates that, in national level, as a result of globalizaton, countries compete each other in terms of markets, technology, skills, and investment to grow and raise their standards of living. Although, macroeconomic competitiveness creates the potential for high productivity, it is not sufficient. Productivity ultimately depends on improving the micro economic capability of the economy and sophistication of local competition (Porter, 2009). Economic Forum (2011) defines competitivenessas the set of institutions, policies, and factors that determine the level of productivity of a country. The level of productivity, in turn, sets the level of prosperity that can be earned by an economy. The productivity level also determines the rates of return obtained by investments in an economy, which in turn are the fundamental drivers of its growth rates. In other words, a more competitive economy is one that is likely to grow faster over time. “Competitive strategy is the search for a favorable competitive position in an industry, the fundamental arena in which competition occurs. Competitive strategy aims to establish a profitable and sustainable position against the forces that determine industry competition” (Porter, 2004, p1). According to Porter (2003) competitive success cannot solely depend on managerial and company attributes when many successful firms in a given field are concentrated in just a few locations (pp. 254). Therefore, we need to see location and cluster membership as integral part of a company’s success. A cluster is “a geographically proximate group of interconnected companies, suppliers, service providers and associated institutions in a particular field, linked by externalities of various types” (Porter, 2003b, p562). Becoming in a cluster offers a firm certain advantages such as knowledge, skills, inputs, components, services, etc. A cluster, geographically, “can range from a single city or state to a country or even a group of neighboring countries” (Enright, 1993; in Porter, 2003a, pp. 254). Regional cooperative formations (e.g., NAFTA, APEC) aimed to develop trade and investment in as particular region. It is expected that cooperation among neighbors can significantly have an impact on productivity of national business environment (Porter, 1998). 238 Journal of Economic and Social Studies �Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective To be competitive, nations are struggling to remain competitive by having regional specializations in terms of hihger value added – non manufacturing industries and Research & Development intensive manufacturing niches (OECD, 2007). Similarly, Porter (2009) indicates that competitiveness depends on the productivity with which a nation uses its human, capital, and natural resources. Economic coordination among neighboring countries can significantly enhance competitiveness. By the similar vein, as developing countries, economic collaboration among Balkan countries is expected to enhance sustainable competition. At this point, it has to be noted that competition policies of advanced countries might not be appropriate for the stage of development of most developing countries (Singh, 1999). Singh (1999) also indicates that “It is important for developing countries to have a competition policy which is designed to take appropriate account of their level of development and the long term objective of sustained economic growth. This is in part due to the potential effects of the international merger movement and also because of privatization, deregulation and liberalization which have occurred in the domestic economies of most developing countries” (p1). As a developing region, the Balkan peninsula is becoming recovered and develop after post-socialist and instable period because of the war among some of states. “The Balkan Peninsula is an important area, having witnessed important historical and political experiences and incidents for ages” (Çelebioğlu 2011, p.112). Having a population of, nearly, 140 million citizens, the Balkan region provides a promising market for firms from international arena and especially Balkan countries. As it is indicated in WEF’s (2011-2012) Global Competitiveness Report, “national competitiveness, we note that despite much work in the area of sustainability, there is not yet a well-established body of literature on the link between productivity (which is at the heart of competitiveness) and sustainability. However, at the World Economic Forum we believe that the relationship between competitiveness and sustainability is crucial (pp. 52). Developing economically sound strategies, especially for international firms and firms from the region, it is crucial to examine competitiveness indicators of Balkan countries. This will help firms to develop a sustainable competitive edge by investing and selling in the region. Taking this necessity into account, this study aims to fill the gap for lack of comparative studies for Balkan countries. More specifically, we analyze Balkan countries’ competitiveness factors by, first, clustering them and, second, compare the clusters to grasp which cluster perform in which competitive factor well. 239 �Kazım DEVELİOĞLU & Kemal KANTARCI In this study, we used the data of The World Economic Forum’s (WEF) classification of “Global Competitiveness Index” factors to examine indicators that are expected to influence sustainable competition in the region. for the years between 2008-2011. WEF’s classification consists of three sub-indexes and 12 factors that measure these sub-indexes, which are reported below: • Basic requirements (Institutions, Infrastructure, Macroeconomic environment, and Health and primary education) • Efficiency enhancers (Higher education and training, Goods market efficiency, Labor market efficiency, financial market development, Technological readiness, and Market size) • Innovation and sophistication factors (Business sophistication and Innovation) Methodology As it is mentioned above, in this study, we used the data of The World Economic Forum’s (WEF) “Global Competitiveness Index” for the years between 2008-2011. By using the secondary data, we aimed, first, to cluster the Balkan countries in terms of above mentioned “Global Competitiveness Index” factors and second to compare these clusters to reveal which of them are more competitive in subindexes and factors. To classify Balkan Countries, we employed a k-means cluster analysis to see “how objects should be assigned to groups so that there will be as much similarity within and difference among groups as possible” (Churchill, 1998, pp. 860). In comparing Balkan countries based on competitiveness index actors, ttest analysis was used aiming that whether the means of two clustered countries were statistically different from each other. 240 Journal of Economic and Social Studies �Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Findings In order to cluster the Balkan countries in terms of Global competitiveness factors, we employed a k-means cluster analysis and derived two clusters, which is reported in Table 1 below. One of these clusters (Cluster 1) includes countries: Bulgaria, Croatia, Greece, Romania, Serbia, and Turkey. The second cluster (Cluster 2) countries are Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia. Scores in Table 1 betray that only in market size competitiveness factor, Cluster 1 countries have a competitive advantage compared with Cluster 2 countries. Table 1. Cluster Analysis Results Cluster Global Competitiveness Factor Institutions Infrastructure Macroeconomic environment Health and primary education Higher education and training Goods market efficiency Labor market efficiency Financial market development Technological readiness Market size Business sophistication Innovation 1 3,63 4,00 4,70 5,45 3,95 4,33 3,60 4,18 3,78 5,20 4,20 3,13 2 4,35 3,38 4,93 5,90 4,38 4,35 4,58 4,83 4,05 2,05 3,80 3,30 F 1,784 0,401 1,827 0,033 0,022 0,396 3,599 0,021 0,105 15,499 0,018 0,120 p 0,214 0,542 0,209 0,860 0,885 0,545 0,090 0,889 0,754 0,003 0,897 0,737 In order to compare Cluster 1 and Cluster 2 countries, we used t-test analysis and obtained the results, which are reported in Table 2 and Table 3. In table 2, we compared two clusters in terms of Global Competitiveness sub-indexes. Table 2. T-test Results for Cluster Membership and Global Competitiveness Subindexes Variable Basic requirements Efficiency enhancers Innovation and sophistication factors Cluster 1 2 1 2 1 2 Mean 4,38 4,47 4,06 3,87 3,39 3,34 Std. Deviation 0,246 0,449 0,161 0,326 0,214 0,473 t p -0,858 0,396 2,547 0,015 0,479 0,634 241 �Kazım DEVELİOĞLU & Kemal KANTARCI Results in Table 2 portray that Cluster 1 (Mean= 4,06) and Cluster (Mean= 3,87) countries both had medium-level but statistically significant difference (t= 2,547; P= 0,015) in efficiency enhancers sub-index. For the other two sub-indexes, namely basic requirements (t= 0,858; P= 0,396) and innovation and sophistication factors (t= 0,479; P= 0,634), both of the clusters showed no statistically significant results. It has to be noted that in both, basic requirements and innovation and sophistication factors, Cluster 1 and Cluster 2 countries had medium level competitiveness scores. Table 3. T-test Results for Cluster Membership and Global Competitiveness Factors Variable Institutions Infrastructure Macroeconomic environment Health and primary education Higher education and training Goods market efficiency Labor market efficiency Financial market development Technological readiness Market size Business sophistication Innovation Cluster 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 1 2 Mean 3,53 3,84 3,70 3,43 4,55 4,89 5,73 5,76 4,21 4,17 4,00 4,12 4,04 4,34 4,04 4,07 3,82 3,74 4,20 2,83 3,75 3,72 3,45 2,97 Std. Deviation 0,233 0,515 0,691 0,851 0,482 0,435 0,228 0,319 0,254 0,625 0,239 0,376 0,325 0,208 0,224 0,504 0,286 0,616 0,579 0,479 0,313 0,427 0,131 0,507 t p -2,657 0,011 1,158 0,254 -2,406 0,021 -0,332 0,741 0,305 0,762 -1,194 0,239 -3,592 0,001 -0,255 0,800 0,597 0,554 8,427 0,000 0,268 0,790 0,705 0,485 Examination of Table 3 revealed mixed results for Cluster 1 and Cluster 2 countries. In Table 3, the results betray that Cluster 2 countries scored better in three of twelve Global Competitiveness factors than Cluster 1 countries. Only for market size competitiveness factor, Cluster 1 countries had statistically significant difference scores (t= 8,427; P= 0,000). 242 Journal of Economic and Social Studies �Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective Discussion Analysis results at the findings section pointed out those competitiveness scores of Balkan countries, whether it belong Cluster 1 or Cluster 2, are relatively low or medium and need to be developed. Specifically, Cluster 2 countries (Albania, Bosnia and Herzegovina, Macedonia, Montenegro, and Slovenia) should have a national strategic plan to improve their competitive position in infrastructure (quality of roads, railroads, ports, and air transport infrastructure), higher education and training (secondary education enrollment, tertiary education enrollment, quality of the educational system, math &science education, management schools, internet access in schools, availability of research and services), goods market efficiency (intensity of local competition, extent of market dominance, effectiveness of antimonopoly policy, extent and effect of taxation, total tax rate, number of procedures to start a business, agricultural policy cost, buyer sophistication), labor market efficiency (cooperation in labor-employer relations, flexibility of wage determination, hiring and firing practices, women in labor force), financial market development (availability of financial services, affordability of financial services, ease of access to loans, venture capital availability), technological readiness (availability of latest technologies, firm-level technology absorption, FDI and technology transfer, internet related factors), business sophistication (local supplier quantity and quality, state of cluster development, nature of competitive advantage, control of international distribution, extent of marketing, willingness to delegate authority), and innovation (capacity for innovation, quality of scientific research institutions, company spending on R&D, utility patents granted). Similarly, Cluster 1 countries should emphasize on development of institutions, infrastructure, financial market, and technological environment and better conditions in macroeconomic environment, higher education and training, goods market efficiency, business sophistication, and innovation. It seems from analysis results that the major advantage for these clusters is their population and market size. This picture warns us that firms plan to invest in the Balkan region should be aware of disadvantageous competitive factors in both cluster countries. It seems that even though both clusters have disadvantages for investors they also offer certain advantages for them. We believe that for strategy makers in national governments and firms, these findings provide useful insights to develop their strategic plans. 243 �Kazım DEVELİOĞLU & Kemal KANTARCI References Churchill, Gilbert A. (1998). Marketing Research. Dryden Press. Çelebioğlu, F. (2011). Investigation of Development Indicators in the Balkan Countries for the Post-Socialist Period. Journal of Economic and Social Studies, Volume: 1, Number: 1, 111-122. Enright, M. J. (1993), "The Geographic Scope of Competitive Advantage," in E. Dirven, J. Groenewegen, and S. van Hoof (eds), Stuck in the Region?: Changing Scales of Regional Identity. (Utrecht: Netherlands Geographical Studies 155), 87-102. Porter, M. E. (1998). The Competitive Advantage of Nations. The Free Press. Porter, M. E. (2003a). Locations, Clusters, and Company Strategy (in The Oxford Handbook of Economic Geography, Gordon L. Clark, Maryann P. Feldman, and Meric S. Gertler (eds), Chapter 13, pp. 253-274), Oxford University Press. Porter, M. E. (2003b). The Economic Performance of Regions. Regional Studies, Vol. 37, 67, 549-578. Porter, M. E. (2004). Competitive Advantage, The Free Press. Porter, M. E. (2009). The Competitive Advantage of Nations, States, and Regions, Harvard Business School, Advanced Management Program. OECD. (2007). Competitive Regional Clusters: National Policy Approaches, (http://www.oecd.org/document/2/0,3746,en_2649_33735_38174082_1_1_1_1,00.html), (22.04.2012). Singh, A.. (1999). Competition Policy, development and developing Countries. Indian Council for Research on International Economic Relations, New Delhi. Vietor, R. H. K.. (2006). Strategy, Structure, and Government in the Global Economy. Harvard Business School Press, Boston, Massachusetts. World Economic Forum, The Global Competitiveness Report, (2008-2009). World Economic Forum, The Global Competitiveness Report, (2009-2010). World Economic Forum, The Global Competitiveness Report, (2010-2011). World Economic Forum, The Global Competitiveness Report, (2011-2012). 244 Journal of Economic and Social Studies � 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. 1396 Title A name given to the resource Clustering Balkan Countries Based on Competitiveness Factors: A Strategic Perspective2 Author Author Kazim, Develioglu Kemal, KANTARCI Abstract A summary of the resource. Prior to directing their investments, strategy makers at national and firm level need to know competitive advantages and disadvantages in a country or region. By bearing this need in mind, this study aims to examine competitive factors in Balkan countries to develop a road map for investors. To do this, we used World Economic Forum’s “Global Competitiveness Index” to analyze the case of Balkan countries as a region to cluster and compare them based on Global competitiveness factors. Analysis results pointed out those Balkan countries were clustered in two groups and scored lower or medium level on almost all competitive factors as the region. Based on these findings, authors suggested various strategic recommendations at micro and macro level. 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 2012 Keywords Keywords. Article PeerReviewed H Social Sciences (General),HB Economic Theory,HG Finance https://omeka.ibu.edu.ba/files/original/dafb0c76d794b81eb4600ca9a2c93d06.pdf 26139e02a5bf1cd6c192223f69a1fe55 PDF Text Text Clustering Marketing Datasets with Data Mining Techniques Özgür Örnek International Burch University, Sarajevo oornek@ibu.edu.ba Abdülhamit Subaşı International Burch University, Sarajevo asubasi@ibu.edu.ba Abstract: Customer analysis is crucial phase for companies in order to create new campaign for their existing customers. If a company can understand customer features and make efforts to fulfill their wants and provide friendly service then the customer will be more supportive to the enterprise. The aim of this study was to develop a methodology to identify the characteristics of customers. It involved identification of the demographic characteristics of customers based on the analysis of categorical data using data mining clustering methods. The extracted knowledge can help companies identify valuable customers, and enable companies to make efficient knowledge-driven decisions. Keywords: Data mining, Clustering, Marketing Segmentation, K-means, E-M Algorithm 1. Introduction Customer analysis is crucial phase for companies in order to create new campaign for their existing customers. Companies are able to group or cluster certain customers which have similar features. This may assist companies to make better marketing strategies over certain customer groups. Companies recognize that their existing customer database is their most important asset (Athanassopoulos, 2000). It is also important that how to effectively process and use customer data. Thus, this new techniques to assist analyze, comprehend or even visualize the massive amounts of stored data obtained from business and scientific applications (Liao et al, 2004). Data mining is the process of discovering and extracting considerable customer knowledge, such as rules, patterns, associations, clusters, and significant structures from large amounts of data stored in databases (Liao et al., 2008; Coussement et al., 2010). According to a research conducted by Reinartz et al., it is more beneficial to keep and satisfy existing customers than to constantly attract new customers who are characterized by a high attrition rate (Reinartz et al., 2003). Thus, if a company can understand customer features and make efforts to fulfill their wants and provide friendly service then the customer will be more supportive to the enterprise. For instance, specific measures and motivation may be proposed to the most risky customer groups, i.e. the most disposed to leave the company, they may remain constant (Burez et al., 2007). The aim of this study was to develop a methodology to identify the characteristics of customers. It involved identification of the demographic characteristics of customers based on the analysis of categorical data using data mining clustering methods. The extracted knowledge can help companies identify valuable customers, and enable companies to make efficient knowledge-driven decisions. 2. Materials and Methods In last decades, data mining techniques have been employed to forecast customer behavior (Giudici et al., 2002). Data mining is an application that involves specific algorithms for pattern extraction (Mitra et al., 2001). Data mining implements association algorithm according to decision attributes in order to analyze customer features so that the marketing managers can develop strategies for target customers. 408 �2.1. Data mining Data mining, also known as knowledge discovery in database, is prompted by the need of new techniques to help analyze, understand or even visualize the large amounts of stored data gathered from business and scientific applications. It is the process of investigating knowledge, such as patterns, associations, changes, anomalies or significant structures from large amounts of data stored in database, data warehouse, or other information repositories (Hui et al., 2000). Nowadays, some data mining methods and applications have been developed to analyze the practices and planning methods of sales and marketing management between customers and vendors in the market (Bloemer et al., 2003; Liao et al., 2004) Another study conducted by Hsieh (Hsieh, 2004) offered a method that integrated data mining and behavioral scoring models for the management of banking customers. He categorized customers into three groups according to their shared behaviors, characteristics, and effectiveness. Marketing managers conclude the profiles of each group of customers and propose management appropriate policies to the characteristics of each group. Customer behavioral variables, demographic variables, and transaction databases are employed to create a method of mining changes in customer behavior in the retail market (Chen et al., 2005). In their study, customer behavior patterns are first recognized using association rule mining. After the association rules for customer behavior are realized, changes in customer behavior are identified by comparing two sets of association rules produced from two datasets from different periods. The changes in patterns can then be investigated and evaluated to provide a basis for creating marketing strategies. Customer behavior analysis in Internet marketing has already been investigated by many researchers (Jenamani et al., 2003). In most of similar researches, data mining technologies are applied to produce a categorized customer profile of the Internet shopper and to further investigate the Web usage pattern of the online consumer. The knowledge obtained through data mining helps to promote informed Internet marketing decision-making and provides for the improvement of Web content and infrastructure to raise Internet marketing (Kwan et al., 2005; Liou et al. 2010). This paper proposes the clustering analysis for data mining to extract market knowledge of customers’ database. In this work we analyzed customer demographic knowledge using clustering techniques, and then relevant knowledge was extracted to explore useful information/knowledge of patterns for marketing and customer relationship management. Knowledge extracted from this analysis can serve as useful input for upper management and analysts of planning and operation and marketing departments. 2.2. Clustering Clustering is a task of grouping objects into classes of similar objects (Jain et al., 1999). It is an unsupervised classification or partitioning of patterns into groups or clusters based on their locality and connectivity within an n-dimensional space. In this study, clustering has been used for finding clusters of customers with similar characteristics. 2.3. Marketing Data In this study, we used marketing dataset gathered from shopping mall customers in the San Francisco Bay area (Impact Resources, 1987). The dataset income data is an extract from this survey. It consists of 14 demographic attributes. This survey’s aim was to predict the annual income of household from the other 13 demographics attributes. 8993 instances have been used for this survey. The attributes that are used in this survey summarized as follows: • • • • • • • • • • • • Annual income of household (personal income if single) Sex Marital status Age Education Occupation How long have you lived in the san fran./oakland/san jose area? Dual incomes (if married) Persons in your household Persons in household under 18 Householder status Type of home 409 �• • Ethnic classification What language is spoken most often in your home? 3. Results and Discussion In this paper, we used Weka software which has some useful advantageous. It is free software system, and it uses the same dataset external representation format. So, it can easily be downloaded from Internet, used without data format problems and, if required, changed using the same programming language (Romero et al., 2007). Weka (Witten & Frank, 2005) is open source software which contains a collection of machine learning and data mining algorithms for data pre-processing, classification, regression, clustering, association rules, and visualization. We clustered 3 similar groups from marketing datasets. We used simple K-means and E-M clustering algorithm in Weka system. The K-means algorithm is one of the simplest and most popular clustering algorithms. It is an algorithm that clusters objects based on attributes in k partitions. The Expectation–Maximization (EM) algorithm is developed for incomplete data (Dempster & Laird, 1977). It can be used to run maximum likelihood parameter prediction for mixture models. It applies the principle of maximum likelihood to find the model parameters. The E-M algorithm repeats the Expectation (E) and Maximization (M) steps iteratively after randomly initializing the mixture model parameters. The E and M steps are iterated until an intended convergence is acquired (Witten & Frank, 2000). We have performed the K-means over the marketing dataset with 3 number of clusters. Weka K-means algorithm results summarized in Table 1 that shows information about the each cluster, the number and percentage of instances in each cluster. Attribute Full Data Cluster0 Cluster1 Cluster2 Sex MaritalStatus Age Education Occupation YearsInSf DualIncome HouseholdMembers Under18 HouseholdStatus TypeOfHome EthnicClass Language Income Clustered Instances 1.5469 3.031 3.4152 3.8351 3.788 4.1983 1.5448 2.8518 0.6669 1.8367 1.8557 5.9559 1.1275 4.895 8993 2 4.2449 2.884 3.4709 4.2206 4.207 1.0285 2.8443 0.7052 2.1938 2.0139 5.843 1.1292 3.4094 2775 ( 31%) 1.5974 1.1208 4.2922 4.2199 3.3105 4.3348 2.3122 3.0091 0.7602 1.3345 1.5519 6.1424 1.103 6.6379 3587 ( 40%) 1 4.3551 2.7799 3.6946 3.9825 4.003 1.0429 2.6453 0.499 2.1448 2.103 5.8206 1.1591 4.0859 2631 ( 29%) Table 1. Weka K-means clustering algorithm results Second, We have executed the EM over the marketing dataset with number of 3 clusters. Weka E-M algorihtm results have been summarized in Table 2. Attribute Cluster0 Cluster1 Cluster2 Sex MaritalStatus Age Education Occupation YearsInSf 1.0544 4.4007 2.8438 3.9473 3.5763 3.8344 1.8043 4.2871 2.8991 3.4354 4.3277 4.2998 1.5821 1.1166 4.2066 4.1412 3.4079 4.306 410 �DualIncome HouseholdMembers Under18 HouseholdStatus TypeOfHome EthnicClass Language Income Clustered Instances 1 2.341 0.2379 2.0581 2.2464 5.824 1.2424 4.4533 2174 ( 24%) 1 2.9506 0.8005 2.2001 1.9015 5.8889 1.0714 3.5124 3324 ( 37%) 2.3478 3.0433 0.781 1.3796 1.5975 6.0904 1.1157 6.4129 3495 ( 39%) Table 2. Weka EM clustering algorithm results We can see in Table 1 and Table 2 that there are 3 clusters of customers. According to Table 1, Cluster 0 is characterized by customers with lower or few features. Cluster 1 is characterized by customers with more values than Cluster 0. Finally, Cluster 2 is characterized by customers with values somewhat smaller than cluster 1 but greater than cluster 0. We can also see in the figure that the students are grouped into 3 clusters with regular numbers of customers 2775, 3587 and 2681 respectively. According to Table 2 results, Cluster 2 has higher values than other clusters, while Cluster 1 has lower values. This information can be used in order to group customers into three types of customers: high valuable customers (cluster 1), lower valuable customers (cluster 2) and non-valuable students (0). Starting from this information, for example, the marketing managers can group customers for making marketing strategies. The marketing managers can also group new customers into these clusters depending on their features. 4. Conclusion In this study we have conducted data mining clustering techniques over a marketing dataset in order to obtain interesting information in a more efficient and faster way. Marketing managers can use this extracted knowledge to perform relevant strategies over certain customer groups. This paper proposes K-means and E-M algorithm as a methodology of clustering analysis for data mining, which is implemented for mining customer knowledge from the marketing dataset. Knowledge extraction from data mining results is illustrated as knowledge patterns, rules, and knowledge maps in order to propose suggestions and solutions to the case firm for determining marketing strategies. Three clusters were obtained from the K-means and E-M analysis. Both clustering algorithm results show some characteristic features of customers. These characteristic may briefly explained as follows: customer age range is 35-44, education level is 1 to 3 year college, marital status is married, number of household members is greater than 3, and householder status is own. Briefly, clustering analysis results show that companies can promote a new strategy by considering customers features including age, education, marital status, and dual income. In these regards, the marketing managers can figure out how to maintain its reputation. References Athanassopoulos, A. D. (2000) Customer satisfaction cues to support market segmentation and explain switching behaviour, Journal of Business Research, 47(3). Bloemer, J. M. M., Brijs, T., Vanhoof, K., & Swinnwn, G. (2003) Comparing complete and partial classification for identifying customers at risk, International Journal of Research in Marketing, 20, 117–131. Burez, J., & Van den Poel, D. (2007) CRM at Canal + Belgique: Reducing customer attrition through targeted marketing, Expert Systems with Applications, 32(2), 277–288. Chen, M.C., Chiu A.L., Chang H.W. (2005) Mining changes in customer behavior in retail marketing, Expert Systems with Applications 28, 773–781. Coussement, K., Benoit D.F., De Poel, D.V. (2010) Improved marketing decision making in a customer churn prediction context using generalized additive models 411 �Dempster, A. K., & Laird, N. M. (1977) Maximum likelihood from incomplete data via the EM algorithm, Journal of the Royal Statistical Society, Series B, 39, 1–38. Giudici, P., Passerone, G. (2002) Data mining of association structures to model customer behavior, Computational Statistics and Data Analysis 38, 533-541. Hsieh, N.C., (2004) An integrated data mining and behavioral scoring model for analyzing bank customers, Expert Systems with Applications, 27 623-633. Hui, S. C., & Jha, G. (2000) Data mining for customer service support, Information and Management, 38, 1–13. Impact Resources, (1987). http://www-stat.stanford.edu/ElemStatLearn. Jain, A. K., Murty, M. N., Flynn, P. J. (1999) Data clustering: A review, ACM Computing Surveys, 31(3), 264–323. Jenamani, M., Mohapatra, P., Ghose, S. (2003) A stochastic model of e-customer behavior, Electronic Commerce Research and Applications 2, 81–94. Kwan, I., Fong, J., Wong H.K. (2005) An e-customer behavior model with online analytical mining for internet marketing planning, Decision Support Systems 41, 189–204. Liao, S. H., Chen, C. M., & Wu, C. H. (2008) Mining customer knowledge for product line and brand extension in retailing, Expert Systems with Applications, 35(3), 1763–1776. Liao, S. H., Chern, Y. W., & Liao, W. B. (2004) Information technology and relationship management: a case study of Taiwan’s small manufacturing firm, Technovation, 24, 97–108. Liao, S. H., Chen, Y. J. (2004) Mining customer knowledge for electronic catalog marketing, Expert Systems with Applications 27, 521–532 Liau, J.H.J., Tzeng, G. (2010) A Dominance-based Rough Set Approach to customer behavior in the airline market, Information Sciences 180, 2230–2238. Mitra, S., Mitra, P., Pal, S.K. (2001) Evolutionary modular design of rough knowledge-based network using fuzzy attributes, Neurocomputing 36, 45–66. Reinartz, W. J., & Kumar, V. (2003). The impact of customer relationship characteristics on profitable lifetime duration. Journal of Marketing, 67(1). Romero, C., Ventura, S., Garcia, E. (2007) Data mining in course management systems: Moodle case study and tutorial, Computers & Education 51, 368–384. Witten, I. H., & Frank, E. (2000) Data mining: Practical machine learning tools and techniques with java implementations. San Francisco, CA: Morgan Kaufmann. Witten, I. H., & Frank, E. (2005). Data mining: Practical machine learning tools and techniques. Morgan Kaufman. 412 � 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. 536 Title A name given to the resource Clustering Marketing Datasets with Data Mining Techniques Author Author Örnek, Özgür Subasi, Abdulhamit Abstract A summary of the resource. Customer analysis is crucial phase for companies in order to create new campaign for their existing customers. If a company can understand customer features and make efforts to fulfill their wants and provide friendly service then the customer will be more supportive to the enterprise. The aim of this study was to develop a methodology to identify the characteristics of customers. It involved identification of the demographic characteristics of customers based on the analysis of categorical data using data mining clustering methods. The extracted knowledge can help companies identify valuable customers, and enable companies to make efficient knowledge-driven decisions. 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 Q Science (General) https://omeka.ibu.edu.ba/files/original/9188a153e2816289591640f79369c77a.pdf 1a30622686998c21c99e6e8c0bd1826f PDF Text Text Journal of Economic and Social Studies Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period Cumhur Şahin University of Bilecik Seyh Edebali Turkey cumhur.sahin@bilecik.edu.tr Abstract: The purpose of this study is to investigate whether there is a co-integration amongst (3) three Balkan countries; Bosnia Herzegovina, Macedonia and Turkey in relation to the German stock market (important for the Europe scale). For this purpose, the relevant stock market’s weekly closing values (in the time series) were analyzed between the periods of September 2010 and August 2015. The long-term co-integrated relationship is analyzed by the Johansen Juselius Co-integration Test. The empirical results show that these three Balkan countries have a meaningful, but moderate relationship in reference to the stock markets. In addition, the German stock market has a more powerful effect on the Turkish stock exchange in comparison to the Bosnia Herzegovinian and Macedonian stock exchanges. This paper suggests that international investors can diversify their portfolios in these (3) three Balkan stock markets. Volume 6 Number 1 Spring 2015 Keywords: The Balkans, Emerging Stock Markets, Indexes, Market Linkages, Co-Integration Analysis JEL Classification: G15, O16 Article History Submitted: 7 May 2015 Resubmitted: 21 September 2015 Resubmitted: 19 October 2015 Accepted: 26 October 2015 http://dx.doi.org/10.14706/JECO SS155210 105 �Cumhur Şahin Introduction The Balkans, located in the southeast portion of the European continent, is a region that has its own unique structure. Though being an important part of Europe, and having an important international place both historically and culturally, unfortunately, we cannot say the same from an economic point of view. Most especially, in financial terms, when compared to other parts of Europe, it has a quite small share. However, important developments have been observed in terms of the financial markets in the Balkan nations since 1980’s. Along with the liberalization process that occurred in these countries, the first and most important stocks and bonds exchange was established in Turkey in 1986 under the name of IMKB. Since 2013, it has continued its activities as the Borsa Istanbul. Another important stock exchange is the Athens Stock Exchange in Greece. Along with liberalization policies, it has experienced significant progress since the 1990’s. Also one of the major stock exchanges in the Balkans is Romania's Bucharest Stock Exchange that experienced an important leap with the destruction of communism. These three countries both in terms of exchange trading volume and stocks traded are the most important stock markets in the Balkans. The historical, cultural and humanistic ties with the Balkans are as important as its geographical, political and economic ones. Geographically, the Balkans forms the extension of Turkey to Europe. This has not only influenced the shaping the Turkish nation historically, but has also influenced its position as being a target for European Union membership. The common sharing of this aspect with all the regional countries is of vital importance for Turkey, thus raising its potential progression. There are historically strong ties between Turkey and Balkan countries. Minor, cognate, coreligionist and relative members of society live in the Balkan countries and people originating from the Balkan countries are living in Turkey. There also are many important Turkish economic investments in the Balkan countries with respect to either quantitative aspects or volume. The previously mentioned Balkan countries have the characteristics of what can be called the “Hinterland of Turkey”. In this study, we will investigate whether there is financial co-integration between Turkey with the Balkan hinterland countries and Germany or not. Bosnia Herzegovina and Macedonia have been chosen for this reason. In fact, the aim of this study was to investigate Albania and Kosovo, but due to the lack of transparency in their financial 106 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period markets, it was not possible to include them. In addition to these countries, Germany’s financial market has also been added to this study due to its economic size and political standing as well as its historical interests in the Balkan countries. Literature Review From a literary perspective, there have been many studies documented regarding the securities exchange in the Balkan countries. Some of them are mentioned below: In the study by Birau, the co-integration relationship was investigated between the Romanian Stock Exchange and the Greek Stock Exchange. The daily stock exchange index closing data for the period of January 2003 and December 2012 was investigated by the Granger Causation Method. Causation could not be determined for the first periods of January 2003 and December 2007, even though it was determined that there was a single direction effect between the Greek stock exchange and the Romanian stock exchange during the second periods of December 2007 and December 2012. (Birau, 2013). In the studies of Birau and Trivedi, co-integration relationships were investigated between the Bucharest Stock Exchange and the Athens, Paris and Frankfurt Stock Exchanges. The daily stock exchange index closing data for the periods of January 2003 and December 2012 were investigated by the Granger Causation Method. Relationship and co-integration could not be found for the first periods of January 2003 and December 2007 between the Bucharest Stock Exchange and the Athens, Paris and Frankfurt Exchanges, even though it was determined that there was a single direction effect and co-integration between the Athens Stock Exchange and the Bucharest Stock Exchange for the second periods of January 2007 and December 2012. Co-integration between the Bucharest Stock Exchange and the Athens, Paris and Frankfurt Stock Exchanges were observed. (Birau and Trivedi, 2013). In the study of co-integration between Croatia, Slovenia, Hungary, the Czech Republic, Poland, Germany and the middle and eastern European countries of Vizek and Dadic, it was determined that there is no co-integration between Croatia and the middle and eastern European country markets when determined by the Johansen Method for daily index data investigation during the periods of 1997 and 2005. (Vizek and Dadic, 2006). In the study made by Papavassilou, co-integration between Montenegro, the European Union, and the USA plus 11 country markets were investigated by Volume 6 Number 1 Spring 2016 107 �Cumhur Şahin Granger Causation Tests on data during the periods of March 2003 and September 2008. The existence of long-term balance was proven between the markets of Montenegro, the European countries and the USA. (Papavassilou, 2014). In Tudor’s study, the relationship between the stock markets of Central and Eastern European countries, (consisting of Russia, Poland, the Czech Republic, Hungary, Romania and Bulgaria) and the US markets were investigated during two periods including the periods before and after the global crisis. In this study, daily data from January 2006-March 2009 was analzed by Granger Causality. After the analyses, it was concluded that there was co-integration between the US market and the markets of the six Eastern European countries during the crisis, and that this relationship was stronger in comparison to the periods before and after the crisis. It was also concluded that co-integration ran in a sole direction from the US to these six countries. (Tudor, 2011). Syriopoulos and Roumpis had revealed the relationship between the financial markets of the Balkan countries, but their correlation with developed countries was even higher. (Syropoulos and Roumpis, 2009). In the study by Syriopoulos, the early European Monetary Union was examined. It was proven that mutual interaction increased between the stock exchanges of the Balkan countries and the eastern European countries especially after the establishment of the Monetary Union. The high levels of affiliation between the stock exchanges were affected by developed countries, the foremost of which was the USA stock exchange. (Syropoulos, 2007). Stoica and Diaconașu’s study included the investigation of the interaction between the Balkan country stock exchanges (such as Bosnia Herzegovina, Bulgaria, Croatia, Macedonia, Romania, Serbia and Slovenia) with Austria’s stock exchange. It was observed that there is a long-term and mutually positive interactive relationship between the stock exchanges of the above-mentioned countries; however, they are more sensitive to Austria’s Stock exchange. (Stoica and Diaconașu, 622). In the study by Progonaru and Apostol, it was observed that in the relationship between the Romanian Stock Exchange and the other middle and eastern European stock exchanges, that the correlation of the Romanian Stock Exchange to the middle and eastern European stock exchanges is lower than the higher correlation with the stock exchanges of developed countries. (Progonaru and Apostol,2000). 108 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period In the study by Drakos and Kutan, the Turkish and Greek Stock Exchanges are mutually dependent on one other in short and long-terms and their sensitivity to the stock markets of developed counties was observed as high (Drakos and Kutan, 2001). Samitas and Kenourgios’s study, in which the exchanges between the Balkan countries themselves and the integration with the stock markets in the United States, Britain and Germany for the period including the years 2000/2006 were examined concluding that the exchanges of the Balkan countries among themselves and those of three developed countries were long-term based and strong (Samitas and Kenourgios, 2011). Syllignakis and Kouretas used Johansen’s Co-integration Tests where mostly Balkan countries were involved along with the central and eastern European countries. The relationship between the financial markets and the international markets, were found to especially increase with the European Union's enlargement process (Syllignakis and Kouretas, 2010). In the study by Horvath and Petrovski, the common transactions of country markets between the developed countries and central European countries including the Czech Republic, Hungary, Poland and also the western Balkan countries such as Serbia and Macedonia were examined. By using the multi-variate GARCH models as analyzing the data exchanges, it was observed that the integration degree of the stock markets of the central European countries was much higher than the Balkan countries. On the other hand, the integration degree and correlation of the Serbian and Macedonian stock exchanges with the developed countries were at almost a zero level, while, the Croatian Exchange integration and correlation level with the developed countries markets was much higher than the Macedonian and Serbian stock markets. (Horvath and Petrovski, February 2012). Onay’s study of the European Union candidate countries regarding the long-term financial integration of the U.S. stock market were examined using the Johansen Cointegration Tests. It was determined that Bulgaria and Romania had the highest integration between the European Union and the U.S. stock markets when compared with Turkey and Croatia's integration into the European Union and the U.S. stock markets (Onay, 2006). Volume 6 Number 1 Spring 2016 109 �Cumhur Şahin Guidi and Uğur examined the integration of the stock exchanges of the southeastern European countries with the developed ones evaluating the static and dynamic analysis of co-integration between the Romanian, Bulgarian, Slovenian, and Croatian markets with the German, British and U.S. stock market for the period of 2000–2013. It was identified that the new European Union member states tended to co-integrate with the stock markets of Germany and the U.K. whereas the same trend was not identified with the U.S. stock market (Guidi and Uğur, 2014). In the study by Gradojević and Dobardžic, the regional stock market causalities and stock markets relationships of Serbian, Croatian, Slovena, Hungarian, and Germany were also examined and daily closing data was used for the related relevant stock exchange between October 4, 2005 and August 18, 2009. When the data was analyzed, it was identified that the Serbian exchange had a partial impact on the Hungarian and Croatian exchanges whereas the Serbian and Slovenian markets had mutual two-way causation (Gradojević andDobardžić, 2013). In the study by Dobardžic and others, the financial markets and joint economic movements of emerging and developed countries were examined. The Serbian Exchange together with the German, Hungarian, Croatian and Slovenian markets were also discussed for the periods of 2005 – 2009. Granger Causality Tests were used in this study and it was concluded that there was a significant relationship between the Slovenian and Croatian exchanges similar to the Serbian and German stock markets, with the Serbian and German Stock Exchanges proving to have the highest correlation (Dobardžic, Dobardžic and Brničanin, 2012). Patev and Kanaryan’s study examined the behavior of stock exchanges and their characteristics. The daily values of Greek, Turkish and Romanian stock markets were also observed for the period between September 22, 1997 and May 31, 2002. As the data was analyzed in this VAR model study, it was understood that there was neither a significant relationship nor a proper integration between the stock markets of these three Balkan nations. A further result indicated that the Turkish stock market had the highest market risk, while the Greek stock market’s volatility risk was very high and the Romanian stock exchange indicated the least open-tendency stock market regarding external influences. It can be assumed that the Turkish and Greek have the least stock market integration in contrast to the Romanian stock exchange that is entirely non-integrated, meaning that they are completely closed off from external influences. This is an interesting situation. (Patev and Kanaryan, 2002). 110 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period In the studies by Samitas and others, the integration of the Balkan countries’ rising stock markets and the behavioral properties were analyzed along with the relationship amongst themselves and with advanced markets. In this study, daily closing data of the Romanian, Bulgarian, Serbian, Macedonian, Turkish, Croatian and Albanian, Greek, U.S., German and U.K. markets were analyzed. Johansen Cointegration Tests were used. The result of the analysis indicated that there was a meaningful and positive direction towards a strong relationship between the GreekRomanian, Bulgarian and Serbian-Macedonian exchanges, whereas there was a strong and positive relationship observed between the German stock exchange and the Croatian-Turkish stock exchange with Albania (Samitas, Kenourgios and Paltalidis, 2008). In the study by Karagöz and Ergun, the integration of the stock markets between the Balkan countries are discussed for both the Bulgarian, Greek, Turkish, Croatian and Romanian markets and also for the markets of the developed countries such as the U.S., Britain and Japan. Daily closing values were observed between the dates of January 2, 2006 and March 31, 2009 and once again, Johansen Co-integration Tests were used. When the data was analyzed, it was concluded that there is a two-way relationship between the stock markets of the Balkan countries. The Turkish stock exchange had the lowest interaction and the British stock exchange being the most developed, had the highest effect on these stock exchanges markets (Karagöz and Ergun, 2010). Data, Methodology and Scope of Research In this study, the aim was to determine whether there exists financial co-integration between Turkey and the Balkan hinterland countries and Germany or not. Bosnia Herzegovina and Macedonia were specifically chosen for this reason. In fact, Albania and Kosovo were intended to be investigated, however, for reasons of the lack of transparency in their financial markets, unfortunately, it was not possible to include them. In addition to these countries, Germany’s financial market has been added due to its economic size, its political standing and its important historic interests with the Balkan countries. In this context, the indexes used are: for Bosnia Herzegovina the SASE 10 stock exchange 10 index, for Macedonia the MIB 10 index, for Turkey the BİST 100 index and for Germany the DAX index of the period between September 2010 and August 2015. Weekly closing data was investigated. The idea of selecting the 2010Volume 6 Number 1 Spring 2016 111 �Cumhur Şahin 2015 period came about because this period reflected the actual current status of last five years. The data was obtained from Bloomberg and was analyzed with Eviews 7.1 packaged software. In the analysis, serial graphics, a correlation analysis, an ADF unit root test and Johansen Co-integration Tests were used. Mentioned time series values were taken. The first issue to be considered for the time series analysis was the subject of the static variables. Because of economic and financial variables, time series often consist of trends or seasonality, and this could lead to the violation of the principles for being stable of series, (Yurdakul, 2003). Stability can be defined as the independence of the undertaken time series average and the variances from the time. In the absence of a stable of time series, estimated econometric models can provide misleading results. For this reason, in the time-series econometric analysis, a unit root test (test of stillness) was applied mostly to the time series. Therefore, in this study, by using the Augmented Dickey-Fuller (ADF) Test (Eviews, with the help of the program), we determined whether the time series included unit root (stillness) or not. Table 1: Descriptive Statistics for Indexes Bosnia Macedonia Turkey Germany Mini mum Maxim um Mean Std. Deviati on Statistic Variance Skewness Kurtosis Statist ic Statisti c Statistic Std. Error Statistic Statis tic Std . Err or Statis tic Std . Err or 636.4 0 1556. 96 5018 2.53 1118. 12 2771. 38 9192 4.84 793.25 91 1931.2 657 71011. 7848 7.217 60 18.70 629 617.4 1741 116.60 392 302.20 932 9974.6 8354 13596.4 74 91330.4 73 994943 11.784 1.30 5 1.16 2 .032 .15 1 .15 1 .15 1 .641 .30 0 .30 0 .30 0 5189. 93 1287 4.73 8206.0 667 106.3 3193 1717.8 4483 295099 0.873 .505 .15 1 .333 1.00 6 .631 .30 0 Source: Authors’ own work 112 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period Table 2: Correlation between Germany, Bosnia and Herzegovina, Macedonia and Turkey Stock Market Indexes Bosnia Macedonia Turkey Germany r p r p r p r p Bosnia 1 0,911 0,000 -0,448 0,000 -0,534 0,000 Macedonia 0,911 0,000 1 -0,531 0,000 -0,576 0,000 Turkey -0,448 0,000 -0,531 0,000 1 0,749 0,000 Germany -0,534 0,000 -0,576 0,000 0,749 0,000 1 Source: Authors’ own work As seen in the correlation table, there is a positive and strong correlation between Bosnia Herzegovinian and the Macedonian stock markets (r = 0,911). There is a negative correlation between the Bosnia Herzegovinian and the Macedonian markets with the German and Turkish markets. While the degree of correlation between the German and Bosnia Herzegovinian market closing prices was medium and negative (r=-0,5345), the correlation between the German and Macedonian market closing price has a medium level degree (r=-0,576) As for the correlation between the German and Turkish market closing prices, the correlation is positive and has a high degree (0,749) All three coefficients of correlation are statistically significant. (p< 0,01) Figure 1: Graphics of DAX Index Volume 6 Number 1 Spring 2016 113 �Cumhur Şahin Figure 2: Graphics of the MIB 10 Index Figure 3: Graphics of the BIST–100 Index 114 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period Figure 4: Graphics of the Sarajevo 30 Index When the graphics above were analyzed, it can be said that the German and Turkish stock exchange values had similar courses. Macedonian and Bosnian markets can be said to have similar courses as well. When the graphics were generally evaluated, suspicion that the series may not have been stationary was aroused. Stationarity of the series were then analyzed with the Dickey-Fuller Method and the test results are given below. In time series analyses, the time series used in model must first be tested. A time series is stationary if it does not change over time and has mutual variance between the two terms depending only on the distance between the two periods, not on the period in which this mutual variance is calculated. Augmented Dickey–Fuller (ADF) Unit Root Test Dickey-Fuller is a test used to determine whether unit root exists (whether the series is stationary or not) or not in an observed series. There are three equation types Dickey-Fuller has propounded; Dickey–Fuller equation without constant or trend:ΔYt =γY(t-1) +ut (1) Volume 6 Number 1 Spring 2016 115 �Cumhur Şahin Dickey–Fuller equation without constant or trend:ΔYt =a+γY(t-1) +ut (2) Dickey–Fuller equation without constant or trend: ΔYt =a+bt+γY(t-1) +ut (3) There are two hypotheses used to test the existence of unit root. These are; H1: γ<0 (p<1) (there is no unit root in the series.) (The series is stationary.) H0 : γ=0 (p=1) (there is a unit root in the series.) (The series is not stationary.) Empirical Results and Discussion Table 3: ADF Unit Root Test Results C ADF-t Statistic -1.07 (1) %5 Mac Kinnon -2.87 -0.96 (1) Macedonia Turkey Bosnia Herz. Germany C+T 0.72 ADF-t Statistic -1.82 (1) %5 Mac Kinnon -3.42 -2.87 0.76 -2.30 (1) -3.42 0.43 -1.37 (1) -2.87 0.59 -1.93 (1) -3.42 0.63 -1.95 (0) -2.87 0.30 -2.49 (0) -3.42 0.32 Possibility Possibility 0.69 1. Difference C ADF-t Statistic -13.90 (0) %5 Mac Kinnon -2.87 -19.13 (0) Macedonia Turkey Bosnia Herz. Germany C+T 0.00 ADF-t Statistic -13.87 (0) %5 Mac Kinnon -3.42 -2.87 0.00 -19.10 (0) -3.42 0.00 -14.06 (0) -2.87 0.00 -14.03 (0) -3.42 0.00 -15.88 (0) -2.87 0.00 -15.85 (0) -3.42 0.00 Possibility Possibility 0.00 * Values inside the parentheses state lagged values determined in accordance with Schwarz criterion 116 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period It can be seen that all variables are not stationary in table values because ADF-t statistic values are smaller than MacKinnon critical values with a 5 % significance level in terms of absolute value. According to a new unit root test conducted by first differenced variables, it has been detected that all series are stationary in the first difference. The fact that all series are stationary in the first difference indicates the possibility of a co-integration relationship between the series. Graphics of Stationary Series Figure 5: Stationary Series of DAX Index Volume 6 Number 1 Spring 2016 117 �Cumhur Şahin Figure 6: Stationary Series of Sarajevo 30 Index Figure 7: Stationary Series of MIB 10 Index 118 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period Figure 8: Stationary Series of BIST–100 Index The relationship of co-integration was initiated by Engle and Granger (1987) then developed by Johansen (1988) and Johansen and Juselius (1990). Engle–Granger and Johansen’s co-integration methods were applied for investigation of the longterm relations between time serials. Engle and Granger propose that serials should be integrated on the same level in order to obtain co-integration between the serials. If a serial is stable without taking the first gap, it is called stable within a serial level. In other words the integration level of serial is zero. If it is taken as d gap, that serial is integrated on d level. In this context, if the X and Y two time serials are stable on the same level, it means there is co-integrative relation. In this environment, the stability of serials has been investigated by ADF Root Tests as the first phase of Johansen Cointegration Method of this study. After the necessary pre-tests for co-integration, VAR analysis was conducted to determine the optimum lagged value, and its results are given below. Optimum lagged values have been determined within the framework of the Schwarz and Akanke information criteria. Volume 6 Number 1 Spring 2016 119 �Cumhur Şahin Table 4: Optimum Lagged Values AIC SC TURKEY-BOSNIA AND HERZEGOVINA 0 0 TURKEY- MACEDONIA 1 1 TURKEY-GERMANY 0 0 As seen in the table, optimum lagged values in accordance with both information criteria. Table 5: Johansen-Juselius Co-integration Test Results H0 Hypothesis Maximum Eigenvalue TURKEY-BOSNIA AND HERZEGOVINA r=0 r≤1 Trace Statistic 184.26 (0,00) TURKEY- MACEDONIA r=0 r≤1 190.08 (0,00) 103.30 (0,00) TURKEY-GERMANY r=0 r≤1 213.89 (0,00) 117.86 (0,00) 100.18 (0,00) Dual co-integration relationships between Turkey and Bosnia, between Macedonia and Germany can be seen in the table. The H0 hypothesis that there is no co-integration relationship amongst Turkey and Bosnia Herzegovina, Macedonia and Germany is rejected. (p< 0,01) In this regard, it is concluded that there is a co-integration relationship amongst Turkey and Bosnia Herzegovina, Macedonia and Germany closing prices. Conclusion In this study, the relationships of Balkan countries such as Turkey, Bosnia and Herzegovina and Macedonia were investigated in terms of stock exchanges and their interaction with each other. Being one of the most important in terms of the European Union, Germany’s stock exchange DAX index effects on these three 120 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period countries was investigated. For this purpose, time series of the Sarajevo 10 index, the MIB 10 index and the BIST–100 index data were used and thought to representative of the stock exchanges of these countries. The review period of the data was the weekly closing values between September January 2010 and August 2015. The Johansen Method was used for co-integration analyzes. Upon analysis of the data, there is a statistically significant and strong (p < 0.01) relationship of % 91,1 between the Macedonian and the Bosnia Herzegovinian stock exchange, if one increases, the other one also increases. There is a statistically significant (p < 0.01) relationship of % 44,8 between the Turkish stock exchange and the Bosnia Herzegovinian exchanges. If one increases, the other one decreases. There is a statistically significant (p < 0.01) relationship of % 53,4 between the German stock exchange and the Bosnia Herzegovinian exchange. If one increases, the other one decreases. There is a statistically significant (p < 0.01) relationship of % 53,1 between the Turkish stock exchange and the Macedonian exchange. If one increases, the other one decreases. There is a statistically significant (p < 0.01) relationship of % 57,6 between the German stock exchange and the Macedonian exchange. If one increases, the other one decreases. There is a statistically significant (p < 0.01) relationship of % 74,9 between the Turkish stock exchange and the German exchange. If one increases, the other one also increases. In addition, there is a co-integrative relationship between the Turkish and Bosnia Herzegovinian, Macedonian and German closing prices. As seen, there is a significant relationship between the Balkan countries and Turkish stock exchange. The Turkish stock exchange has the highest co-interaction with the German stock exchange. This was actually expected. This is because in terms of transaction volumes, traded stocks, sophistication and size of the financial markets, it is clear that the Turkish market has a more mature level in comparison with the other sister country markets. In addition, German and Turkish investors can hedge their risks by investing in Macedonia and Bosnia & Herzegovina because of the negative correlation between their own stock markets and these Balkan stock markets. Additionally, international investors can diversify their portfolio in these stock markets. The loosening of investigation on capital flows, stock buying and selling methods, the extraordinary speed of telecommunication, varieties on financial instruments and Volume 6 Number 1 Spring 2016 121 �Cumhur Şahin the increase in the global investments of multinational companies, are determining the country’s financial markets relations. References Birau, F.R. (2013). Cointegration and International Linkage Between Greek and Romanian Stock Markets. 2nd WSEAS International Conference on Finance, Accounting and Auditing, Brasov, Romania, June 1-3. Birau, F.R. & Trivedi, J. (2013). Analyzing Cointegration and International Linkage Between Bucharest Stock Exchange and European Developed Stock Markets. International Journal of Economics and Statistics,4(1),237-246. Dickey, D. A. & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74, 427–431 Dobardžic, E., Dobardžic, A. & Brničanin, E. (2012). Co-Movement of Financial Markets in Emerging and Developed Economies. Actual Problems of Economics / Aktual'ni Problemi Ekonomìki; 129 (3), 385 Drakos, K. &Kutan, A. M. (2001). Opposites attract: the case of Greek and Turkish financial markets. Zentrum für Europäische Integrations foschung, Working paper B06 Engle, R.F., & Granger, C.W.J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing, Econometrica,55 (2), 251-276 Gradojević, N. & Dobardžić, E. (2013). Causality between Regional Stock Markets: A Frequency Domain Approach. Panoeconomicus, 5, 633–647 Guidi, F. & Uğur, M. (2014). An Analysis of South-Eastern European Stock Markets: Evidence on Cointegration and Portfolio Diversification Benefits. Journal of International Financial Markets, Institutions and Money, 30, 119–136 Hamilton, J.D. (1994). Time Series Analysis. New Jersey, Princeton Uni. Press. P. 303. 122 Journal of Economic and Social Studies �Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof from the 2010-2015 Period Horvath, R. & Petrovski, D. (2013). International Stock Market Integration: Central and South Eastern Europe Compared. William Davidson Institute Working Paper Number 1028 February 2012 (http://wdi.umich.edu/files/publications/workingpapers/wp1028.pdf) Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12, 231–254 Johansen, S. & Juselius, K. (1990). Maximum Likelihood Estimation and Inference on Cointegration with Application to the Demand For Money. Oxford Bulletin of Economics and Statistics, 52, 169–210 Karagöz, K. & Ergun, S. (2010). Stock Market Integration among Balkan Countries. MIBES Management of International Business and Economics Systems Transactions, 4 (1), 49 – 59 Onay, C. (2006). A Co-Integration Analysis Approach to European Union Integration: The Case of Acceding and Candidate Countries. Eu. In. Online Paper, 10(7): 1–16. Papavassilou, V.G. (2014). Equity Market Integration: The New Emerging Economy of Montenegro. Review of Accounting and Finance, 13 (3), 291-306. Patev, P. & Kanaryan, N. (2002). Behavior and Characteristics of the Balkan Stock Markets. http://www.econ.utah.edu/~ehrbar/erc2002/pdf/P191.pdf Pogonaru, F. & Apostol, C. (2000). Romanian Capital Markets; a decade of transition. Romanina Center for Economic Policies, Working paper No.9, October Samitas, A. & Kenourgios, D. (2011). Equity Market Integration in Emerging Balkan Markets. Research in International Business and Finance, 25, 296- 307 Samitas, A., Kenourgios, D. & Paltalidis, N. (2008). Integration and Behavioral Patterns in Emerging Balkans Stock Markets. European Financial Management Association 17th Annual Meeting (EFMA), Athens, 25-28 June 2008 Stock, J. H. & Watson, M. W. (1988). Testing for Common Trends. Journal of the American Statistical Association, 83, 1097–1107 Volume 6 Number 1 Spring 2016 123 �Cumhur Şahin Stoica, O. & Diaconașu, D.E. (2011). Analysis of Interdependencies between Austrian and CEE Stock Markets. 616–627 Syllignakis, M. & Kouretas, G. (2010). German, U.S. and Central and Eastern European Stock Market Integration. Open Economies Review, 21(4), 607–628 Syropoulos, T. (2007). Dynamic linkages between emerging European and developed stock markets: Has the EMU any impact? International Review of Financial Analysis, 16 (1), 41– 60 Syropoulos, T. & Roumpis, E. (2009). Dynamic correlations and volatility effects in the Balkan equity markets. Journal of International Financial Markets, Institutions and Money, 19 (4), 565–587. Tudor, C. (2011). Changes in Stock Markets Interdependencies as a Result of the Global Financial Crisis: Empirical Investigation on the CEE Region. Panoeconomicus, 4, 525-543. Vizek, M. & Dadic.T. (2006). Integration of Croatian, CEE and EU Equity Markets: Cointegration Approach. Economiski Pregled, 57 (9-10), 631-646. Yurdakul, F. &. Akçoraoğlu.A. (2003). Macroeconomic Variables Structural Breaks: Empirical Evidence the Turkish Economy. Gazi Üniversitesi, İ.İ.B.F. Dergisi, 5 (1), 53–62. 124 Journal of Economic and Social Studies � 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. 2937 Title A name given to the resource Co-integration Analysis between the Turkish Stock Market and its Balkan Hinterland Equivalents: Proof From the 2010-2015 Period Author Author SAHIN, Cumhur Abstract A summary of the resource. Abstract: The purpose of this study is to investigate whether there is a co-integration amongst (3) three Balkan countries; Bosnia Herzegovina, Macedonia and Turkey in relation to the German stock market (important for the Europe scale). For this purpose, the relevant stock market’s weekly closing values (in the time series) were analyzed between the periods of September 2010 and August 2015. The long-term co-integrated relationship is analyzed by the Johansen Juselius Co-integration Test. The empirical results show that these three Balkan countries have a meaningful, but moderate relationship in reference to the stock markets. In addition, the German stock market has a more powerful effect on the Turkish stock exchange in comparison to the Bosnia Herzegovinian and Macedonian stock exchanges. This paper suggests that international investors can diversify their portfolios in these (3) three Balkan stock markets. Keywords: the Balkans, emerging stock markets, indexes, market linkages, co-integration analysis 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 2016 Keywords Keywords. Article PeerReviewed DOI Digital object identifier doi: 10.14706/JECOSS155210 Identifier An unambiguous reference to the resource within a given context ISSN 1986 – 8502, HB Economic Theory https://omeka.ibu.edu.ba/files/original/853ede11174655ea3d22eddadd163a1a.docx 84b0c04fa4b8924b7898f4e6b89f99d6 https://omeka.ibu.edu.ba/files/original/68dfe33c7a6af1fccadd4366fecbfa86.pdf 6a5715bbe44c7ae5ce65558f85584225 PDF Text Text Co-Occurence of Tenses And Adverbs in Spontaneous Speech Jasmina Mirtoska SEEU / Tetovo, Macedonia Key words:tenses, adverbs, transfer, spontaneous speech ABSTRACT This study examines the co-occurrence of tenses and the accompanied adverbs by L1 Macedonian, Albanian and English students at the South European University, Macedonia. An additional aim of this research is finding out whether the students’ performance correlates with their Morphology grades, a second year course in which tenses are taught, practiced and tested, as well as whether their performance in this study correlates with their GPA (Grade Point Average). For the sake of finding out whether the co-occurrence is grammatical and appropriate, the third year students, studying English Language and Literature, at the same university, have been involved in 10 open and semicontrolled activities in the form of a recorded interview. Tense/adverb co-occurrence as well as knowledge retention from the course Morphology which they attended as first year students, was tested in three groups of 5 students with different first languages. The participants in this experiment with different L1s also provided foundation for L1 tense interference analysis. The initial anticipation was that the results will show evidence of their knowledge gained in the course Morphology in which they have been explicitly taught the English tense system. The transcribed data showed that the co-occurrence of the tenses did not mirror the anticipated performance. In other words, the comparison of the results with their Morphology 1 grades and their GPA (grade point average) showed some inconstancies � 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. 1816 Title A name given to the resource Co-Occurence of Tenses And Adverbs in Spontaneous Speech Author Author MIRTOSKA, Jasmina Abstract A summary of the resource. Key words:tenses, adverbs, transfer, spontaneous speech ABSTRACT This study examines the co-occurrence of tenses and the accompanied adverbs by L1 Macedonian, Albanian and English students at the South European University, Macedonia. An additional aim of this research is finding out whether the students’ performance correlates with their Morphology grades, a second year course in which tenses are taught, practiced and tested, as well as whether their performance in this study correlates with their GPA (Grade Point Average). For the sake of finding out whether the co-occurrence is grammatical and appropriate, the third year students, studying English Language and Literature, at the same university, have been involved in 10 open and semi-controlled activities in the form of a recorded interview. Tense/adverb co-occurrence as well as knowledge retention from the course Morphology which they attended as first year students, was tested in three groups of 5 students with different first languages. The participants in this experiment with different L1s also provided foundation for L1 tense interference analysis. The initial anticipation was that the results will show evidence of their knowledge gained in the course Morphology in which they have been explicitly taught the English tense system. The transcribed data showed that the co-occurrence of the tenses did not mirror the anticipated performance. In other words, the comparison of the results with their Morphology 1 grades and their GPA (grade point average) showed some inconstancies 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/85b91f1476eccaf56c1f5b308d0d27e4.docx 790e31ef0a008612c10d31293c42d3a9 https://omeka.ibu.edu.ba/files/original/fadf6f2d956a95048b53109aa5615ee2.pdf 18501be015fd990518f4503b30fa4cfe PDF Text Text ÇOCUK EDEBİYATINDA “KARAKTER” KAVRAMI VE AYLA KUTLU’NUN ÇOCUK KİTAPLARININ BU AÇIDAN DEĞERLENDİRİLMESİ Evren KARATAŞ Cumhuriyet Üniversitesi, Eğitim Fakültesi, Türkçe Eğitimi Bölümü, Sivas / Türkiye Anahtar Kelimeler: çocuk edebiyatı, karakter, özdeşim, Ayla Kutlu. ÖZET Platon’dan günümüze sanatın ana işlevinin izleyende/alımlayanda katharsis (arınma) oluşturmak olduğu kabul edilmiştir. Katharsis büyük ölçüde alımlayanın tahkiyenin merkezindeki karakterlerle “özdeşim” kurması yoluyla sağlanabilmektedir. Bilindiği üzere kurgunun dört temel öğesi zaman, mekân, karakter ve olaydır. Metinde zaman ve mekân, karakter ile kurgunun yapısına girebilir. Karakter aynı zamanda kurguda olayı başlatan, geliştiren ve eyleyen ana unsurdur. Karakter olmadan kurgunun diğer elemanları ölüdür, olay ise yoktur. O halde, karakter kurgunun diğer elemanlarının hareketlenmesini, hayatiyet kazanmasını mümkün kılar. Çocuk edebiyatında da karakterle özdeşim kurma meselesi, hem sorunlu bir konu olarak çokça tartışılmakta hem de çocuğa evrensel, millî ve ahlâkî değerlerin aktarılmasında verimli bir araç olduğundan sıkça gündeme getirilmektedir. Çocuklar 3-6 yaş aralığında davranışlarının büyük bir bölümünü yakın ve uzak çevrelerindeki gerçek kişileri ya da film, animasyon, kitap gibi kurgusal yapıtlardaki kahramanları örnek alarak oluşturmaktadırlar. Özellikle kurgusal karakterler sahip oldukları olağanüstü güçler ve imrenilecek fiziksel özellikleriyle çocukların gözünde ideal rol modelleri oluşturmaktadırlar. Bu “her şeye sahip olan ve her şeyi yapabilen” karakterler çocuğun gerçeklik algısını zedelemekte ve onların var olmayan, ulaşamayacakları, gerçek dışı karakterleri model almalarına neden olmaktadır. Bir de buna, son dönemlerde çocukları hedef tüketici kitlesi olarak gören şiddet, fantastik ve cinsellik örüntüleriyle dolu görsel ve yazılı ürünlerin karakterleri de eklenince durum daha tehlikeli bir hâl almaktadır. Geçmişin aşırı didaktik, davranışlar açısından kusursuz, slogancı çocuk karakterleri, çocuk eğitimi açısından ne kadar verimsiz ise çağın fiziksel ve sosyal yönden aşırı idealize edilmiş, yorulmak bilmez çocuk karakterleri de bir o kadar sakıncalıdır. Bu nedenle çocuk edebiyatında karakter oluşturma konusunda dikkatli olunmalı ve karakterlerin fiziksel ve ruhsal açıdan çocukların gelişim aşamalarına uygun çizilmelerine önem verilmelidir. Örneğin okul öncesinde animistik özellikleri ön plânda olan bitki, hayvan gibi karakterler uygunken, ilköğretim dönemi için çocuk karakterlerin başlarından geçen olayların anlatıldığı eserler daha elverişlidir. Alanyazında kişi, karakter, kahraman, antikahraman öğeleri arasındaki farkların açık olmadığı görülmektedir. Bu nedenle çalışmaya öncelikle bu öğeler arasındaki farkların belirlenmesiyle başlanması plânlanmakta, daha sonra ise animasyon, film, edebiyat gibi alanlarda çocuk karakter oluşturma yöntemlerinin örneklerle açıklanması düşünülmektedir. Son olarak elde edilen kuramsal bilgiler ışığında, örneklem olarak seçilen çağdaş Türk çocuk edebiyatı yazarlarından Ayla Kutlu’nun çocuk kitaplarındaki karakterler verilerinin yorumlanması hedeflenmektedir. Böylece çalışmada �sırasıyla doküman tarama ve betimsel analiz yöntemleriyle Ayla Kutlu kesiti üzerinden Türk çocuk edebiyatındaki karakter kavramı açıklanmaya çalışılmıştır. � 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. 2195 Title A name given to the resource ÇOCUK EDEBİYATINDA “KARAKTER” KAVRAMI VE AYLA KUTLU’NUN ÇOCUK KİTAPLARININ BU AÇIDAN DEĞERLENDİRİLMESİ Author Author KARATAŞ, Evren Abstract A summary of the resource. Anahtar Kelimeler: çocuk edebiyatı, karakter, özdeşim, Ayla Kutlu. ÖZET Platon’dan günümüze sanatın ana işlevinin izleyende/alımlayanda katharsis (arınma) oluşturmak olduğu kabul edilmiştir. Katharsis büyük ölçüde alımlayanın tahkiyenin merkezindeki karakterlerle “özdeşim” kurması yoluyla sağlanabilmektedir. Bilindiği üzere kurgunun dört temel öğesi zaman, mekân, karakter ve olaydır. Metinde zaman ve mekân, karakter ile kurgunun yapısına girebilir. Karakter aynı zamanda kurguda olayı başlatan, geliştiren ve eyleyen ana unsurdur. Karakter olmadan kurgunun diğer elemanları ölüdür, olay ise yoktur. O halde, karakter kurgunun diğer elemanlarının hareketlenmesini, hayatiyet kazanmasını mümkün kılar. Çocuk edebiyatında da karakterle özdeşim kurma meselesi, hem sorunlu bir konu olarak çokça tartışılmakta hem de çocuğa evrensel, millî ve ahlâkî değerlerin aktarılmasında verimli bir araç olduğundan sıkça gündeme getirilmektedir. Çocuklar 3-6 yaş aralığında davranışlarının büyük bir bölümünü yakın ve uzak çevrelerindeki gerçek kişileri ya da film, animasyon, kitap gibi kurgusal yapıtlardaki kahramanları örnek alarak oluşturmaktadırlar. Özellikle kurgusal karakterler sahip oldukları olağanüstü güçler ve imrenilecek fiziksel özellikleriyle çocukların gözünde ideal rol modelleri oluşturmaktadırlar. Bu “her şeye sahip olan ve her şeyi yapabilen” karakterler çocuğun gerçeklik algısını zedelemekte ve onların var olmayan, ulaşamayacakları, gerçek dışı karakterleri model almalarına neden olmaktadır. Bir de buna, son dönemlerde çocukları hedef tüketici kitlesi olarak gören şiddet, fantastik ve cinsellik örüntüleriyle dolu görsel ve yazılı ürünlerin karakterleri de eklenince durum daha tehlikeli bir hâl almaktadır. Geçmişin aşırı didaktik, davranışlar açısından kusursuz, slogancı çocuk karakterleri, çocuk eğitimi açısından ne kadar verimsiz ise çağın fiziksel ve sosyal yönden aşırı idealize edilmiş, yorulmak bilmez çocuk karakterleri de bir o kadar sakıncalıdır. Bu nedenle çocuk edebiyatında karakter oluşturma konusunda dikkatli olunmalı ve karakterlerin fiziksel ve ruhsal açıdan çocukların gelişim aşamalarına uygun çizilmelerine önem verilmelidir. Örneğin okul öncesinde animistik özellikleri ön plânda olan bitki, hayvan gibi karakterler uygunken, ilköğretim dönemi için çocuk karakterlerin başlarından geçen olayların anlatıldığı eserler daha elverişlidir. Alanyazında kişi, karakter, kahraman, antikahraman öğeleri arasındaki farkların açık olmadığı görülmektedir. Bu nedenle çalışmaya öncelikle bu öğeler arasındaki farkların belirlenmesiyle başlanması plânlanmakta, daha sonra ise animasyon, film, edebiyat gibi alanlarda çocuk karakter oluşturma yöntemlerinin örneklerle açıklanması düşünülmektedir. Son olarak elde edilen kuramsal bilgiler ışığında, örneklem olarak seçilen çağdaş Türk çocuk edebiyatı yazarlarından Ayla Kutlu’nun çocuk kitaplarındaki karakterler verilerinin yorumlanması hedeflenmektedir. Böylece çalışmada sırasıyla doküman tarama ve betimsel analiz yöntemleriyle Ayla Kutlu kesiti üzerinden Türk çocuk edebiyatındaki karakter kavramı açıklanmaya çalışılmıştır. 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 2013-05-17 Keywords Keywords. Article PeerReviewed Identifier An unambiguous reference to the resource within a given context ISSN 2203-4548 https://omeka.ibu.edu.ba/files/original/a0d8ef2342ee7d5607fbfa14c63ee438.pdf e44d39372b9d0258808a0da079ff4464 PDF Text Text BİLDİRİ ÖZETLERİ - UTEK 2014 TÜRKÇEDE TASARLAMA KİPLERİNDE ANLAM KAYMASI Tuğba Sarikaya AKSOY Muğla Sitki Koçman Üniversitesi, Muğla / Türkiye Anahtar Kelimeler: Kip, tasarlama kipleri, Türkçe, anlam kayması. ÖZET Türkçede kip, belli bir söylem ortamında konuşurun iş, olgu, durum karşısındaki tutumunu belirleyen dilbilgisi ulamıdır. Bir kip, birden çok kipsel değer anlatabilir. Bazı durumlarda sözdizimsel zorunluluklara bağlı olarak kipsel değer ortadan kalkabilir. Yapılan çalışmalar çoğu zaman kip ve zaman kavramlarının birbirine karıştığını gösterir. Araştırmacıların bazıları kip yerine tarz terimini kullanırken; bazıları zaman yerine kipi kullanmaktadır. Geleneksel dilbilgisi kitaplarında, genellikle zamana karşılık olarak kullanılan kip terimi, temel olarak bildirme kipleri (belirli geçmiş zaman, belirsiz geçmiş zaman, şimdiki zaman, gelecek zaman ve geniş zaman) ve tasarlama kipleri (istek, dilek-koşul, gereklilik, buyrum) olmak üzere ikiye ayrılmaktadır. Bildirme ve tasarlama kipleri sadece oluş ve kılışın zamanını gösteren yapılar değildir; aynı zamanda olayların ne tarzda yapıldığını da anlatan işaretleyicilerden oluşmaktadır. Türkçede tasarlama kipleri, eylemin belirttiği kavramı öznel açılardan dilek, istek, gereklilik ve buyrum biçiminde anlatır. Daha çok konuşurun tutumunu ve eylem karşısındaki niyet ve duygusunu ifade eder. Ancak, bu kiplerin her birinin dilden dile değişen çok sayıda önemli işlevi bulunmaktadır. Türkçenin çok eski dönemlerinden beri karşılaşılan tasarlama kiplerinin çoğu zaman hem biçim hem de işlevleri itibariyle iç içe geçtiği görülmektedir. Yapılan incelemeler, bütün tasarlama kiplerinin arka planında bir istek ifadesinin bulunduğunu ve aynı eklerin farklı fonksiyonlarda kullanılabildiğini göstermiştir.Çalışmada, ilk önce kip teriminin ne olduğu anlatılacak, Türkçede tasarlama kiplerinin anlamsal ve işlevsel özellikleri verildikten sonra örnekler aracılığıyla istek, dilek-koşul, gereklilik ve buyrum kiplerinin birbirinin yerine kullanılması ve aralarındaki geçişler tartışılacaktır. 142 �BİLDİRİ ÖZETLERİ - UTEK 2014 Key Words: mood, subjunctive moods, Turkish, semantic transfer. ABSTRACT Mood is the grammar category which determines the attitudes of speakers towards function, case and situation in Turkish. A mood can consist of more than one modal value. In some situations, modal value may disappear due to syntactic necessities. The studies indicate that the concepts of mood and time interfere with each other. While some of the researchers have used the term of style instead of mood, some have used the term of mood instead of time. In traditional grammar books, the term of the mood is often used instead of time and is basically divided into two sections which are indicative moods (definite past tense, indefinite past tense, present tense, future tense and aorist tense) and subjunctive moods (optative, conditional, necessity, imperative). Indicative and subjunctive moods are not only structures that Show the time of process and manner of action; but also they consist of markers showing how the actions are done. In Turkish, subjunctive moods express the concept that is defined by actions in the form of optative, conditional, necessity, imperative moods in relation to subjective aspects. Rather, they explain the speakers’ attitudes and intentions and emotions towards actions. However, these moods have many different, important functions ranging from language to language. Since the very old times of Turkish, these moods are seen to have mostly intermixed in terms of both form and function. The studies have showed that all of the subjunctive moods have the expression of desire at the background and can be used in different functions.In this study, firstly the definition of mood will be explained; after semantic and functional characteristics of subjunctive moods in Turkish will be expressed, that optative, conditional, necessity, imperative moods can be used instead of each other and transitions between them will be discussed with the help of examples. 143 � 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. 2734 Title A name given to the resource ÇOCUK TİYATROSU VE GELİŞİMİ AÇISINDAN İLKÖĞRETİM 100 TEMEL ESERİN İNCELENMESİ Author Author KARAKUŞ, Tuğba Nur ÖZUYGUN, Ali Rıza Abstract A summary of the resource. Çocuk ve tiyatro kavramlarının birleştirilmesi, çocukların tiyatro ile ilgilenmeleri ve çocukların tiyatro aracılığıyla eğitilebilmeleri düşüncesi ilk defa Meşrutiyet döneminde ortaya çıkmıştır. Bu dönemin günümüze yönelik izleri takip edildiğinde verilen değer ve çabanın azaldığı görülmektedir. Bu çalışma edebiyatımızda çocuklara yönelik hazırlanan edebi eserleri çocuklara kazandırma; bu edinimin ise tiyatro yoluyla yapılabilirliğini mümkün kılmaya yöneliktir. Başka bir açıdan ise yerli ve yabancı 100 temel eserin çocuk düzeyine uygunluğu ölçüsünde tiyatroda sahnelenmesi düşüncesine yanıt olabilecek çözüm yollarının verilecek olmasıdır.Çalışma için nitel araştırma yöntemi kullanılmıştır. Araştırma tamamlandığında ; tiyatronun çocuklar için gerekli olup olmadığı, birtakım değerler ve öğretilerin bu yolla verilip verilemeyeceği,edebi kültürün çocuklara aktarımında tiyatronun etkisinin ne kadar olabileceği sorularına yanıt vermesi beklenmektedir. 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 2014-05-23 Keywords Keywords. Article PeerReviewed Identifier An unambiguous reference to the resource within a given context ISSN 2303-582X P Philology. Linguistics,PA Classical philology,PI Oriental languages and literatures,PN Literature (General) https://omeka.ibu.edu.ba/files/original/394d7d5a7ddaf4ef8c0a79fe17f3becb.pdf f46c908c315f99bf3742c9e09f0d02d1 PDF Text Text Çocuklara Tarih Şuuru Kazandırmada Tarihi Hikayelerden Yararlanma Üzerine Bir Deneme Nesîme CEYHAN Bildiri Özeti: Toplumlar da fert fert insanlar gibi ortaya çıkışlarını, hayat maceralarını, var oluş mücadelelerini, eşik dönemlerini, mutluluklarını, parlak sayfalarını bir sonraki nesle aktarma ihtiyacı içindedir. Tarih’in henüz bir bilim olma iddiasına girişmediği dönemlerde edebiyat ve tarih, insanın/insanlığın hikâyesini aktarmada müşterek hareket ediyorlardı. Bugün, eğitimin bir parçası olarak çocuklarımıza, gençlerimize aktarmaya çalıştığımız tarihî bilgiyi, kazandırmaya çalıştığımız tarih şuurunu edebî metinlerden destek alarak gerçekleştirmeye yönelik bir anlayış, ülkemizde de yer etmeye başlıyor. Biz bu çalışmamızda tarihî hikâyelerin örgün eğitimle birlikte yaygın eğitim içerisinde farklı yaş guruplarındaki çocuklara ulaştırılmasının gerekliliğine, seçilecek/yazılacak hikâyelerin hüviyetine ve yayın dünyasının yapması gereken hamlelere dair fikir geliştirmeye çalışacağız. Anahtar Sözcükler: tarih, edebiyat, eğitim, tarihî hikâye, tarih bilinci Modern zamanların, bilimleri birbirinden kalın hatlarla ayıran ve her dalı kendi içinde onlarca şubeye bölen tavrı, problemler üzerinde bütüncül bakışı ve bütünden hareketle çözüm önerisi sunma imkânını ortadan kaldırmıştır. Bu bağlamda sosyal bilimlerin kaynağı sayılan dil, tarih ve edebiyatın, aynı kaynaktan doğdukları ve bir sacayağı hâlinde diğer sosyal bilimleri ve birbirlerini besledikleri adeta unutulmuştur. Tarih ve edebiyat bilimleri, birçok yanlarıyla birbirini tamamlayan; diğer yanda gerçeklik tartışmalarında birbirinden ayrılan iki disiplindir. Tarih bilimi, edebî metni fiktif âlemin mahsulü sayarak gerçeklik düzleminden uzaklaştırır ve kaynak göstermede ciddiye almaz; oysa tarih yazıcılarının da mutlak gerçekliği yansıtıp yansıtamadıkları tartışma konusudur. Tarih metni, insan topluluklarının başlarından geçmiş olaylardan hareketle ortaya çıkmışken, edebî metin insanların başlarından geçmiş ya da geçmesi muhtemel hadiselerle, insanların duygularından hareketle şekillenir. İkisi de dille var olur. Dil, tarihî yaşanmışlığın ve duygulanımların taşıyıcısıdır. Tarih yazıcıları, olanı kaydetmekle görevli olsalar da bilhassa devletlerin tarih yazıcılarından devletin kabul ettiği doğruları gelecek nesle aktarmalarından başka bir şey beklenemez. İnsanlar kaleme aldığı müddetçe objektif tarih yazıcılığı hiçbir zaman mümkün olamayacaktır. Edebî metni ortaya koyan sanatkâr ise, içinde bulunduğu toplumun yaşadıklarından etkilenmekle birlikte hadiseleri ve duyguyu aynıyla aktarma imkânına sanatın mahiyeti gereği zaten sahip değildir. Her toplum, ortaya çıkışını, hayat macerasını, var oluş mücadelesini, eşik dönemlerini, mutluluklarını, parlak sayfalarını bir sonraki nesle aktarma ihtiyacı içindedir. Destan devirlerinin varlığı bunu ispatlar. İnsan, hikâyesini anlatma ihtiyacı taşıyan bir varlıktır. Tarih’in henüz bir bilim olma iddiasına girişmediği dönemlerde edebiyat ve tarih insanın/insanlığın hikâyesini aktarmada müşterek hareket ediyorlardı: Destanları, İlyada ve Odisse’yi hatırlamalıyız. Bugün eğitimin bir parçası olarak çocuklarımıza, gençlerimize aktardığımız tarihî bilgiyi, kazandırmaya çalıştığımız tarih şuurunu salt tarih metinlerinden elde etmeye çalışmak yerine edebî metinlerden destek alarak gerçekleştirebileceğimize dair bilhassa Tarih Eğitimi ile meşgul olan araştırmacılar dikkat çekmeye başlamışlardır.46 Biraz Tarih, Çokça Hikâye: Tarihî Hikâye 46 Bu konuya son yıllarda dikkat çeken bazı çalışmalar şunlardır: Kurtuluş Kayalı, “Edebiyatı, Tarihi Zenginleştirici Bir Malzeme Olarak Algılama Gerekliliği”, Kültür,Nu:103, 1994, s.14-17./ Bahri Ata, “Tarih Öğretiminde Bir Araç Olarak Tarihî Romanlar”, Türk Yurdu, Nu:153-154, s.158-166./ Dursun Dilek, Gülçin Soğucaklı Yapıcı, “Öykülerle Tarih Öğretimi Yaklaşımı”, I. Sosyal Bilimler Eğitimi Kongresi (15-17 Mayıs 2003), Dokuz Eylül Üniversitesi Buca Eğitim Fakültesi, İzmir/ Ahmet Şimşek, “Tarih Eğitiminde Efsane ve Destanların Rolü”, Kırşehir Eğitim Fakültesi Dergisi, Nu:2 (3), 2001./ Ahmet Şimşek, “İlköğretim Sosyal Bilgiler Dersi Tarih Konularının Öğretiminde Hikâye Anlatım Yönteminin Etkinliği”, XI. Eğitim Bilimler Kongresi, Yakındoğu Üniversitesi, Lefkoşa, 2002./ Ahmet Şimşek, “Tarihsel Romanın Eğitimsel İşlevi”, bilig, Bahar 2006, Nu: 37, s.65-80./ A.Cüneyt Issı, Ahmet Şimşek, “İsmayıl Hakkı Baltacıoğlu’nun Çıkardığı Çocuk Hikâyeleri Dergisinin “Tarihi Fıkralar” Özel Sayısının Çocuk Edebiyatı ve Tarih Öğretimi Açısından Değeri”, htp:w3.gazi.esu.tr/web/asimsek/ismayilbalta.htm 337 �Bilhassa son yıllarda ülkemizde tarihe duyulan ilgi tarihî romanla ilgili tartışmaları edebiyat gündemine taşımıştır. Tarihî romanla ilgili değerlendirmeleri büyük ölçüde tarihî hikâye için de söyleyebiliriz; ancak iki türün uzunluk-kısalık, tek omurgalı kurgu-karmaşık kurgu, şahıs kadrosunun fazlalık ve azlığı gibi farkları tahkiyedeki kurgunun tarihî gerçekliği yansıtıp yansıtmayışı ile ilgili kısmen de olsa farklılık ortaya çıkarır. Tarihî hikâye, spesifik tek bir vak’a etrafında okuyucuya daha gerçekçi bir aktarım sunduğu izlenimi uyandırabilir. Tarihî vak’a’dan edinilen malzeme tarihî hikâye yazarının kurguyu tamamlayacak ilâveleri ile edebî metin düzlemine geçer. “Tarihî hikâye” de “tarihî roman”da olduğu gibi en az bir kuşak gelecekten geçmiş bir zamana ait oluşturulan tahkiyelerdir. Bu hikâyelerde yaşanmış ya da yaşanmış olması muhtemel olaylar, devrin yaşam tarzı, döneme uygun mekân ve dekor içerisinde, tarihî bazı simalar ya da kurgulanmış kimseler etrafında gelişir. Yazarın yazdığı dönemi yaşamamış olması tarihî roman ya da hikâye için önemli bir ölçüdür. Bu bağlamda tarihî hikâyeler için örnek olmak üzere Ömer Seyfeddin’in Eski Kahramanlar adı altında Yeni Mecmua’da yayımladığı Ferman, Kütük, Vire, Pembe İncili Kaftan, Başını Vermeyen Şehit, “Kızılelma” Neresi?, Büyücü, Teke Tek, Topuz, Diyet adlı hikâyeleri anabiliriz. Hikâyeler 1917’de yazılmıştır; ancak hadiseler birkaç asır öncesinde yaşanmış ya da yaşanması muhtemel olaylardan seçilmiştir. Birinci Dünya Savaşı’nın devam ettiği, ümitlerin her geçen gün azaldığı zor zamanlarda kaleme alınan bu hikâyeler için Hülya Argunşah şu değerlendirmede bulunur: “Destânî bir ruhla dolu olan bu hikâyeler, savaşın devam ettiği dönemde halkın ve askerin maneviyatını yükseltmek, tarihten getirilen örneklerle mücadele azmini artırmak ve ona yeni ufuklar kazandırmak fırsatını verdikleri gibi bu yıllarda tartışılan modern zamanlarda destanın olup olmayacağı konusundaki şüpheleri de cevaplar.”47 İnsanın hikâye ile bilgilendirilişi, yönlendirilişi, eğitilişi; insana hikâye ile nasihat edilişi destan devirlerinden bu yana süregelen bir hâldir. Geçmiş hadiselerden hareketle topluma kahramanlık hisleri kazandırma, toplumun ümidini yeniden tesis etme, kuvvetli vakitlerden hareketle topluma “sen bir kez daha bunu gerçekleştirebilirsin” mesajını verme mümkün görünüyor. Bugünden hareketle geçmiş devirlere ait yazılan “tarihî hikâyeler” yanında, “çağ hikâyesi/tanık hikâye” de diyebileceğimiz, yazarın şahitliklerinden doğan hikâyeler de vardır. Bugün tarihî hikâyeler arasında zannettiğimiz/gördüğümüz; ancak yazarının devrini aktardığı hikâyeler de bizim için kullanılabilecek niteliktedir. Yakup Kadri’nin Millî Savaş Hikâyeleri, yahut Hâlide Edib’in İzmir’den Bursa’ya adlı kitapta yer alan hikâyeleri, Aka Gündüz’ün Türk’ün Kitabı’ndaki hikâyeleri yaşananların hemen akabinde hikâyecilerin kaleminden çıkmıştır. Yakup Kadri, kitaba düştüğü “Hâşiye”de şunları söyler: “Küçük Hikâye, adı altında neşrettiğim bu yazılar gerçek vakalara müstenittir. Bunlar, açıktan açığa, doğrudan doğruya “Anadolu Hatıraları” ser levhasıyla çıkabilirdi. Fakat ben, onların bazılarını kendi arzu ve muhayyileme göre değiştirmek ve canlandırmak zorunda kaldığım için hepsinin birden tamamıyle edebiyata mâl olmalarını müreccah buldum.”48 Bu açıklama ile hikâyelerin kurguyla ve gerçekle ilişkisi yazarı tarafından net bir biçimde ortaya koyulmuştur. Yayımlandığı gün için “çağ anlatımı”dır bu hikâyeler, bugünden bakınca “tarihî anlatım”. Tanık hikâyeler diyebileceğimiz bu metinlerin okuyucu üzerinde, mutlak yaşanmış olduklarını düşünmekten doğan tesirleri daha kuvvetli olabilir. Tarih Şuuru ve Tarihî Hikâye Her toplum, gelen nesillerin ayaklarını ülke ve milletine dair kuvvetli bir tarihî zemine bastırarak ferde önce, bir grubun parçası olduğunu hissettirir. Bu his bireyin dünya üzerinde zaman ve mekân bağlamında varlığını temellendirebilmesini sağlar. Hiçbir millete, sosyal gruba, dîne mensubiyeti kabul etmeyen fertler bile sonuçta insanlığın ortak hikâyesine bağlılıkla bir mensubiyet taşırlar. Geçmiş, hâl ve gelecek ilgisinin sağlıklı kurulması tarih şuurunun oluşumu için temel unsurdur. Bugün orta öğrenimini tamamlamış her Türk genci Türklerin Orta Asya’dan Anadolu’ya geldiğini, Osmanoğullarından üç kıtaya yayılmış bir imparatorluk kurulduğunu, İstanbul’un fethi ile Orta Çağ’ın kapanıp Yeni Çağ’ın açıldığını, Türkiye Cumhuriyeti’nin Osmanlı Devleti’nin çöküşü ardından kurulduğunu tarih derslerinin bir neticesi olarak kaba hatlarıyla bilir. Bu sürekliliği bilmenin yanında Türklerin devlet kurma kabiliyetine, karşılaştıkları yeni insan topluluklarıyla hoşgörülü birlikteliklerine, aile hayatlarında gösterdikleri karakteristik özelliklere, İslâm’ın bayraktarlığını yapmaya dair hizmet anlayışlarına ve mukaddes değerlere gösterdikleri hürmete, başka dinlere ve inançlara tanıdıkları toleransa,diğergâmlıklarına, adalet anlayışlarına, tabiatla münasebetlerine dair her gencin zihninde uyanması gereken karelerin tamamı tarih şuurunun bir parçasını teşkil eder. Bu şuuru hiçbir tarih kitabı Tarık Buğra’nın Osmancık’ında ifadesini bulan ruhla okuyucuya aktaramaz. Örneğin romanda bütünüyle kurgu olan Osman Gazi’nin Şeyh Edebalı evindeki rüyası, üç 47 48 Hülya Argunşah, Ömer Seyfettin Bütün Eserleri, Hikâyeler2,Dergâh Yay., İst.1999. Yakup Kadri, Millî Savaş Hikâyeleri, Varlık Yayı., İst.1947, s.91. 338 �kıtaya yayılan Osmanlı çınarını okuyucunun şuuraltına yerleştirir. Yahut hiçbir tarih kitabı Zigetvar’ın fethini, başını küffara bırakmayan Deli Mehmed’in Ömer Seyfeddin kaleminden çıkan Başını Vermeyen Şehid’indeki hikâyesi gibi aktaramaz. Fertlerin, cemiyetlerinin tarihlerinin bir bölümünü benimseyip bir bölümünü reddetmeleri, o toplumda tarih bilincinin oluşturulamadığının bir işareti sayılır. Bilhassa çocukların/gençlerin tarihe salt savaşlar, zafer ve yenilgiler olarak bakmalarının önüne geçmek; tarihin bir kısmını benimseyip bir kısmını reddeden bir algıdan onları korumak; tarihi, milletin varlık serüvenini insanî bir şekilde algılama aracı olarak görmelerini sağlamak hedeflenmelidir. Toplumumuzun gençlerde tarih şuuru oluşturma noktasındaki hassasiyeti çok eskiye dayanmaktadır. Halk meclislerinde destanlara ek olarak, gazavatnâmelerin, menkıbelerin, cenknâmelerin, okunma alışkanlığı, Türk toplumunda bu şuurun oluşturulmasındaki hassasiyeti gösterir. Yakın zamanlarda bu alışkanlığın tamamen yok olduğuna dikkat çekmeliyiz. Bunda teknolojinin olumsuz tesiri birinci derecede söylenmelidir. Bunun yanında günlük alışkanlıklarımızın, misafirlik, akşam oturması, sohbet mantığımızın değişimi, şehrin ihtiyaçlarının ve zorunluluklarının baskısı da önemlidir. Eski kültürde çocukların, çocukluktan gençliğe geçenlerin model kimlik olarak bu metinlerde/anlatılarda alp, gazi, velî, ahi tipleriyle karşılaşmaları ve toplumlarının var oluş, ayakta kalış hikâyelerini öğrenmeleri önemlidir. Toplumun, gençlerin terbiyesinde bu tiplere ihtiyacı vardır.49 Model kimlik olan bu şahıslar, cömerttir, gözü pektir, doğruluktan ayrılmaz, namusludur, inançlıdır, vatanperverdir, hükümdarına sadıktır, dar zamanda kişilerin imdadına koşan ve imdadına koşulan tiplerdir. Toplumun model kimliğe olan ihtiyacı bugün de farklı değildir. Bilhassa gençler arasında Deli Yürek ve Kurtlar Vadisi dizilerinde “Yusuf” ve “Polat” karakterlerinin gördüğü ilgi, bu ihtiyacın bir yansıması sayılabilir. Bugün tarihî hikâyeler ve romanlarla toplumun bilhassa model kimliğe olan ihtiyacı karşılanabilir. Tarihî hikâyelerle çocuklara başka ne gibi hasletler kazandırılabilir? Tarihî hikâyeler vasıtasıyla çocuklarda insan varlığının devamlılığı hissi, geçmiş, hâl ve istikbal algısı daha somut hâle getirilebilir. Vatan, millet, ülke, devlet gibi olguların toplum hafızasına tabii dahli, hayatla kaynaşması tarihî hikâyeler yoluyla temin edilebilir. Çocuklarda vatan ve yurt sevgisi oluşturma; vatan için, fedakârlıkta bulunma, gerektiğinde hayatını verebilecek bir ruha sahip olma, özellikle küçük yaşlarda bu hikâyeler aracılığıyla oluşturulabilir. Milletinin temel özellikleri sayılabilecek bazı hasletler çocuklara bu hikâyelerle kazandırılabilir: Büyüklere saygı, âlime hürmet, her hâl ü kârda doğrunun yanında olma, haklıya hakkını verme… Tarihî hikâyelerle tarihin büyük isimleri tabii birer insan olarak algılatılarak empati hissi oluşturulabilir ve bu yolla tarihî kahramanlarla çocuk, birbirine yaklaştırılarak çocuğun kendine ve toplumuna güveni arttırılabilir. Bu hikâyelerle önceki nesillerin yaşama biçimleri, teknoloji ile münasebetleri, zenginlikleri yahut fakirlikleri, eğitim anlayışları, başka insanlarla, hayvanlarla ve bitkilerle ilişkileri çocuğun gündemine getirilerek önceki nesillerle ortak tavır geliştirme imkânı, bir tür gelenek taşıyıcılığı mümkün olabilir. Günümüzde artık aile büyüklerinin milletin ortak hikâyelerini anlattığı ortamlar kaybolmuştur; dolayısıyla bu hikâyeler, bu eksikliği de giderebilir. Çocuklara Yönelik Tarihî Hikâyelerin Hüviyeti Öncelikle söylememiz gereken şey, tarihî hikâye üretiminin artması gerekliliğine dairdir; çünkü, bu sahada büyük bir kısırlıkla karşı karşıyayız. Üstelik sadece tarihî hikâye yayımlanması boyutunda değil, tarihî hikâyelerin çizgi filmi, çizgi hikâye kitapları oluşturulması boyutunda da büyük eksiklik vardır. Çocukların bu sahada ağırlıklı olarak fantastik hikâyeler, yahut bilim kurgu metinlerle ya da çizgilerle karşılaşmaları zihinlerinde köksüz bir hayal ağacı oluşturulması anlamına gelecektir. Tarihî roman gündemini kısmen yaratabilmiştir; ancak tarihî hikâyede oldukça gerilerdeyiz. Çocuklara yönelik tarihî roman yazmada da yine eksiklik vardır ve çocuklara yönelik tarihî hikâyelerde ihtiyaç büyüktür. Öncelikle evvelden yazılmış tarihî hikâyelerin çocuklara uyarlanması söz konusu olabilir. Bir kez daha Ömer Seyfeddin, bir kez daha Halide Edib ve Aka Gündüz, Ahmet Hikmet Müftüoğlu, Yakub Kadri hikâyelerine yönelebiliriz. Bu hikâyelerin dilleri mümkün olduğunca hadiselerin eskiliği ile paralel tutulmalıdır. Yazılacak yeni hikâyelerde dil yine hadiselerin eskiliğini hatırlatacak özellikleri hâiz; ama sade; ayrıca bugünün çocuklarına önceki devirlerin hayatına dair ipuçları taşıyacak zenginlikte olmalıdır. 49 Bu tiplerle ilgili olarak bkz. Mehmet Kaplan, Tip Tahlilleri, Dergâh Yay., İst.1996. 339 �Bilhassa hatırat kitapları taranarak tarihin çeşitli evrelerine dair değerler eğitimine uygun, tarihî şuuru inkişaf ettirecek hadiseler çıkarılmalı ve bunlar hikâyeleştirilmelidir. Kahramanı çocuk olan hikâyeler tercih edilmelidir. Yeni hikâyelerin yazılması teşvik edilmeli; ancak hikâyeler, yeni tarihselciliğin yapı bozumcu tavrı yerine klâsik hikâye tarzında yazılmalıdır. Çocukta kahramanlık hissi oluşturmaya çalışırken şiddet içeren sahnelerden uzak durarak zekânın kuvvetten önemli olduğunu vurgulayan metinlere yönelmekte fayda vardır. Çocukta, insan varlığının dünyadaki devamlılığı hissini oluşturma; geçmişin, hâlin ve istikbâlin varlığı idrakini kolaylaştırma, hikâyelerin temel işlevlerinden biri olmalıdır. Çocukta millî şuur, kahramanlık duygusu ve vatan sevgisi hislerini oluşturmaya yönelik metinler tercih edilmelidir. Çocuğun modern dünyada kendine model olarak aldığında sıkıntı yaşamayacağı model tipler, kahramanlar teklif eden hikâyeler oluşturulmalıdır. Tarihin sadece başarılar ve kahramanlıklardan ibaret olmadığına işaret eden hatanın insanlara göre olduğunu; ancak bazı yanlışların milletlerin kaderini belirleyebildiğini gösteren metinler seçilerek çocuklarda toplumuna karşı sorumluluk hissi oluşturmaya çalışılmalıdır. Çocukta kendisinin varlığını temin için hayatlarını tehlikeye atmış eski insanlara karşı minnet ve hürmet hissi oluşturma; geçmişe vefa ve gelecek nesilleri de sahiplenme hislerini uyandırmaya yönelik metinler tercih edilmelidir. Bütün bunların yanında çocuğun, varlığı bir mekâna bağlı olarak algılamasını kolaylaştıracak, milletinin yaşadığı diğer toprak parçalarını idrak edebileceği farklı coğrafyalarda geçen metinleri de ihmal etmemek gerekiyor. Orta Asya, Balkanlar, Arap Yarımadası, Avrupa, Orta Doğu ve Afrika’da yaşanan devirlere dair hikâyelerle bu geniş coğrafya ile çocuğun/gencin ünsiyetini temin edecek metinler oluşturulmalıdır. Sonuç Zamanın getirdiği yenilikler, teknolojik imkânlar, küreselleşme, bir bütün hâlinde çocukları ortak dünya ve insanlık algısı içerisine çekerken, ülkelerinin gerçekleri, ihtiyaçları ve ideallerinden uzaklaştırmaktadır. Ortak hayalleri olmayan insanlar bir ülkeyi kalkındıramazlar, bağımsızlıklarını koruyamazlar. Bu bağlamda, bir arada yaşayan ve aynı ülkenin vatandaşları olan insanların ortak bir geçmiş, ortak bir hâl ve ortak yaşanacak bir istikbalde fikren birleşmeleri şarttır. Tarih şuuru, bu bakımdan lüzumludur. Örgün eğitimde yakalanmaya çalışılan hedeflerden biri olmakla birlikte tarih şuuru’nun dış hayattan, yaygın eğitim unsurları ve aile çevresinden edinilmesi de önem arz eder. Bu hususta yayınevlerinin programlarına tarihî hikâye ve romanları ilâve etmeleri, televizyon ve radyonun, çocuk programlarının desteği; görsel, işitsel ve yazılı medyanın gayreti ve ailelerin desteğiyle hedefe daha sağlıklı ulaşılacaktır. 340 � 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. 389 Title A name given to the resource Çocuklara Tarih Şuuru Kazandırmada Tarihi Hikayelerden Yararlanma Üzerine Bir Deneme Author Author CEYHAN, Nesîme Abstract A summary of the resource. Toplumlar da fert fert insanlar gibi ortaya çıkışlarını, hayat maceralarını, var oluş mücadelelerini, eşik dönemlerini, mutluluklarını, parlak sayfalarını bir sonraki nesle aktarma ihtiyacı içindedir. Tarih’in henüz bir bilim olma iddiasına girişmediği dönemlerde edebiyat ve tarih, insanın/insanlığın hikâyesini aktarmada müşterek hareket ediyorlardı. Bugün, eğitimin bir parçası olarak çocuklarımıza, gençlerimize aktarmaya çalıştığımız tarihî bilgiyi, kazandırmaya çalıştığımız tarih şuurunu edebî metinlerden destek alarak gerçekleştirmeye yönelik bir anlayış, ülkemizde de yer etmeye başlıyor. Biz bu çalışmamızda tarihî hikâyelerin örgün eğitimle birlikte yaygın eğitim içerisinde farklı yaş guruplarındaki çocuklara ulaştırılmasının gerekliliğine, seçilecek/yazılacak hikâyelerin hüviyetine ve yayın dünyasının yapması gereken hamlelere dair fikir geliştirmeye çalışacağız 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 L Education (General)