42 10 3494 https://omeka.ibu.edu.ba/files/original/bc404f9c7ed894ff5fe98b388c2a56c6.pdf 105129bfb776d49d731574b18a29f481 PDF Text Text 2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Creating Morally-minded Organizations in a Machiavellian Work Environment N. Derya Ergun ÖZLER Dumlupinar University, Department of Administration, Turkey deryaergun69@hotmail.com Nuray MERCAN snmmercan@yahoo.com Abstract: Organizations are highly rational constructs operating in a competitive market and bureaucratic entities designed to attain first organizational-collective and individual-private ends in an orderly fashion. In an entity as such there is little formally accepted and approved room for personal maneuvers which may jeopardize much larger goals of organizations. However, organizations have an internally and interpersonally highly competitive environment, more like a war place for power and influence. Organizations are increasing looking for competent, competitive and achievement oriented individuals yet expect them to work in teams as resource sharing saints. It is time to ask whether it is exactly this paradoxical tendency of modern organizations that encourage Machiavellian behaviors. What type of business organizations and environments are more conducive to Machiavellianism? What types of negative and positive incentives are there in regard to Machiavellianism? And what needs to be done? The aim of this work is to develop above argument further, answer some of above questions and then make workable suggestions for practitioners to help in their attempts to identify Machiavellian tendencies and differentiate Machiavellian behaviors from non-Machiavellian ones. Relavance Of Machiavellianism In Modern Organizations Niccolo Machiavelli (1469-1527) is one of the most influential and controversial personality in the history of philosophical literature. The term Machiavellian originates from the name of Machiavelli, the author of the 1513 treatise, The Prince. He possessed a negative and a pessimistic belief about human nature. He neither liked nor promoted such a nature. Machiavelli believed that he chose a realistic approach than a fairy tale to solve political problems of his time and country. According to Machiavelli individuals in general are selfish and lack wisdom and therefore they should be regarded as vicious, lazy, and untrustworthy and that a ruler should use cruelty, exploitation, and deceit to maintain power. Therefore, unless people are vise in general the ruler needs not to behave in ethical or moral manner. Although his general stance is considered to be amoral (not immoral), Machiavelli maintained that ethics and professional requirements are, by and large, irreconcilable with real politic. Since he drew a line between private (individual) sphere and the public - institutional sphere, there emerged radically different ways of evaluating the respective behaviors of each sphere. As Galie and Bopst (2006) promptly argue, Machiavelli‘s teachings have never gone out of fashion; no doubt because power remains a central aspect of modern political and corporate life. The writings of this 16th century thinker seem as relevant today as they were a half millennium ago. Indeed, numerous monographs published in the last decade still argue for Machiavelli‘s relevance to modern management and corporate leadership. It is a truth that management textbooks concerning morality in corporate life seem to be inconsistent with the actual teachings of Machiavelli and paradoxically they fail to acknowledge that the teachings of Machiavelli are still most relevant to the modern corporate world. In this world occupational careers are filled with face to face interactions which allow almost endless opportunities for interpersonal manipulation and improvisation. The process of obtaining promotions and salary increases seems inevitably to arouse emotions and induce goal directed behaviors (Turner and Martinez, 1977, p. 326). Despite his relevance in modern management the literature is inconsistent about Machiavellianism. It is not clear what Machiavellianism is. Is it a personality trait, a strategy, a type of relationship, a system, behavior or something else? To Christie and Geis (1970) for instance it is a world view which has three distinct themes. The first theme involves using manipulative strategies such as deceit and flattery in interpersonal relations. The second theme involves a cynical perception of others as weak and untrustworthy. The third theme involves indifference toward conventional morality in thought and action (Shepperd and Socherman 1997, p.1448). Machiavelli says "Any person 155 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo who decides in every situation to act as a good man is bound to be destroyed in the company of so many men who are not good. Wherefore, if the Prince desires to stay in power, he must learn how to be not good, and must avail himself of that ability, or not, as the occasion requires"(as Cited in Cyriac and Dharmaraj 1994, p.281). Machiavellianism is also defined by the same authors as ―a trait that involves strategically manipulating others for personal gain often against the other‘s self-interest‖ as conceptualized by Christie and Geis (1970). According to Christie and Geis (1970), high Machs tend to manipulate people for personal gain and have little emotional involvement in interpersonal relationships. High Machs are less altruistic, more likely to cheat, more flexible in tactic usage, less moral and less empathetic. Right after this Christie and Geis then consider Machiavellianism as a type of interpersonal relationship. In their measure of Machiavellianism, high-rated Machiavellians were those who are better positioned as manipulators (Porter, Allen ve Angle, 1981, p.122). Some others take Machiavellianism as a skillful management of interpersonal relations because they have a tendency to initiate and take control in interpersonal relations. Rationality and persuasive skills are essential for their success in face to face relations. Normative pressures have little impact on these people (Schermerhorn, Hunt and Osborn, 1995:56). For some Machiavellianism can be seen as an instrumental action since high Machs also spend more effort to gain political influence (Porter, Allen ve Angle, 1981, p.139). In common usage Machiavellianism and Ethics are thought to be two distinct edges of a scale. In other words Machiavellianism is perceived as an anti-ethic. Machiavelli himself argued that if a ruler wishes to attain his ultimate objectives he would find morality as irrational. Following the morality of the people will turn every attempt of a ruler into a terribly irrational policy (Skinner 2002, p.60). Machiavellianism has been seen by most thinkers from Marx to Shakespeare as the most fatal blow at ethical foundations of political life (Skinner 2002, p.11). Yet this is an unfair attack. First Machiavelli provided eye-opening ideas about real politics. The exemplary politicians he described in his writings actually lived before him not after him. He warned against excessive use of power and punishment, thus we cannot blame him for the despots of the 20 th century. He was not a revolutionary but promoted a moderate politics to gain and maintain power and order. He also showed the way for ordinary man to climb up the ladder of hierarchy to be elite. And this is why he is still relevant. He was not against individual ethics or morality in general. He thought them as instrumental, a mask for the ruler to wear or sometimes a hindrance. More in line with these point of view Machiavellian individuals can be seen as lacking conventional moral sense and adopt the angle of individualist utilitarianism when relating with other people. Machiavellians may not be devoid of morality, they just do not behave consistently with traditional moral values. Machiavellian leaders seem to be more successful in negotiations and persuasion so much so that they can be handy for organizations. They can concentrate on analyzing the situation and developing winning strategies (Christie ve Geis, 1970). However corporation must confine Machiavellian tendencies and strategies to certain boundaries in which achievement orientation, persuasive skills and goal attainment stay alive and also possible harms of opportunist, selfish and deceitful behavior can be avoided (Mandacı, 2007, p.54). Association of Machiavellianism with Other Personality Traits What kinds of individual dispositional factors are there to facilitate Machiavellianism? Barlow and QualterStylianou‘s (2010) recently investigated the association of Machiavellianism (Mach) with emotional intelligence (EI) and the theory of mind (ToM) on 109 primary school children. High Machs think first then act while low Mach first act than amend their consciousness. Although Machiavellians do not necessarily score high on intelligence tests they are more likely to be perceived clever and astonishing. Consistent with previous research on adults, a negative association was found between Machiavellianism and social-emotional intelligence. Subsequent regression analyses showed that being more adept at emotional and social intelligence do not lead girls to manipulate others in social encounters. This was not the case for boys. Paulhus et all (2001) showed that Machiavellianism and psychopathic behaviors are negatively associated with conscientiousness. The Machiavellian remains most realistic while the Narcissists are least realistic about their own character. Paal and Bereczkei (2007) showed that (1) a strong negative correlation between Machiavellianism and social cooperative skills; (2) a connection between the extent of cooperative tendency and the level of mindreading; and (3) a lack of significant correlation between theory of mind (an understanding that other people have beliefs and desires) and Machiavellianism. Rayburn and Rayburn (1996) found that the relation between personality traits and ethical-orientation indicate sex is not a good predictor for differences in Machiavellian and Type A personality and ethical-orientation. Intelligence is found to be positively associated with Machiavellian- and Type A personality-orientation but negatively associated with ethical-orientation. Machiavellians tend to have Type A personalities, but tend to be less ethically-oriented than non-Machiavellians. Type A personalities are more ethically-orientated than Type B 156 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo personalities. There is a lack of agreement as to what constitutes ethical behavior and whether there is a relation between personality traits and ethical orientation. Rayburn et all (2003) compares academic achievement, Machiavellian levels, Type A or Type B personality traits, ethical orientation, and charisma of female and male students. Female students report higher academic achievement, but male students are statistically more charismatic than female students. However, female respondents are more ethical. There is no significant difference in the Machiavellian score and Type A/B personality between female and male respondents. Higher academic achievers have higher Machiavellian scores while Type A personalities are more ethical, but are less charismatic. Shepperd and Socherman (1997) pointed at some paradoxical issues. For example, people scoring high in Machiavellianism (high Machs) can be manipulative and domineering. Yet the domineering style of high Machs may stop them from using manipulations that require a display of weakness. The authors examined whether Machiavellianism moderates the use of sandbagging—a manipulative strategy in which people display low ability to induce an opponent to reduce effort or lower his or her guard. In Experiment 1, participants reported that they would reduce effort in response to a disadvantaged opponent and anticipated that their opponent would behave similarly if they were disadvantaged. In Experiment 2 low Machs in competition sandbagged their opponent when they were uncertain that they could otherwise beat him. High Machs, in contrast, preferred a show of strength to weakness, displaying high ability even when sandbagging might have been an advantageous strategy. In terms of ethical perception, studies suggest that people with high level of ethical perceptivity tend to demonstrate lower levels of Machiavellian tendencies (Christie ve Geis, 1970). According to Christie and Geis (1970) social pressure is less constraining for Machiavellian personalities and thus they are less likely to conform to ethical standards. Ural (2003, p.102) lists the following Machiavellian principles from ―Prince‖ and ―Discourses‖: • • • • • • • • • • • • • • To win people, tell them what they want to hear It‘s better to make up a substantial reason than telling the truth when asking someone to do something An unqualified trust on someone will bring harms rather than goods It is hard to progress without holding the corners Honesty is not always the best policy The safest way is to acknowledge that every individual is evil but they lack opportunity to relinquish that evil When you see no benefit do not ever tell your reasons Don‘t try to justify deeds to yourself with a moral angle Flattering important people is a vise thing to do It is not vise to be humble and honest all the time People having incurable illness should be able to choose painless death It is impossible to be good in every aspects Men will not work unless they are induced The biggest difference between guilty and not guilty is the former is stupid enough to be caught Machiavellianism in Different Cultures Cyriac and Dharmaraj‘s (1994) findings indicate that Indian businessmen in industrialized towns show Machiavellian characteristics more. Siu‘s (1999) research on bankers in Hon Kong concludes that high Mach posses higher levels of job satisfaction than the low Machs. Corzione and Buntzman (1999) found that among the employees working in American Finance sector there is no significant difference between genders on their levels of Machiavellianism. A comparison between American and Hon Kong banking sector showed that both cultures indicate similar level of Machiavellianism. Kavak‘s (2001) research in Turkey concludes that average Machiavellianism score is 97.13 in general, 86 for public servants and 85 for private sector. That means the level of Machiavellianism in Turkey is higher than USA (84.5) and lower than Austria (98.6). Yıldız and Gültekin (1998) argue that mid-level managers show comparatively low level of Machiavellianism. Their study implies that collectivist attitudes might be less Machiavellian than individualist ones. Machiavellianism and Organizational Behavior Research suggests that employees possessing a Machiavellian personality have both advantages and disadvantages in the workplace. With respect to deception, high Machs are much less likely to be caught, more convincing liars, harder to judge and were believed to be telling the truth more than low Machs liars. The flexibility 157 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo of the high Mach is another advantageous characteristic. For example, high Machs with an external locus of control supposed to be better managers according to Goodboy and Mccroskey (2007, p.290). Jellinek (1985) found the interaction of high school principals' degrees of Machiavellianism and their schools‘ organizational structure with their experience of occupational stress. In general, principals in schools which had less than 1,500 students were lower in Machiavellianism and also experienced less stress. The relationship between school size and experienced stress suggested that Machiavellianism may be a response to current problems faced by high school principals, rather than being solely an enduring personality characteristic. Subramaniam (2009) found the relationship between Machiavellianism orientation and job involvement among employees of an airline company in Malaysia. Machiavellianism orientation and job involvement are positively and significantly correlated. It is found that there was a significant relationship between age and level of job involvement, however, no significant relationship is detected between gender and Machiavellianism orientation. Shome and Rao‘s (1996) research results indicate a significant difference among accountants holding different positions within the firm (i.e., partners, managers and seniors) in terms of Machiavellian orientation. In addition, audit seniors were found to have the highest Mach scores, partners have the lowest, and the managers have intermediate scores. Liu (2008) determined the relationship between Machiavellian orientation and knowledge sharing willingness and found that there are significant negative correlations between the two. The correlation coefficients are all significantly negative. Bodey and Grace (2007) examined personality characteristics, such as self-monitoring, perceived control, self-efficacy and Machiavellianism, within the realms of complaint behavior. The results indicate significant relationships between self-monitoring, perceived control and self-efficacy with attitude to complaining while selfefficacy and Machiavellianism was significantly related to propensity to complain. Becker (2007) determined the relationship between Machiavellianism and organizational citizenship behavior (OCB). The negative association between Machiavellianism and organizational citizenship behaviors toward the organization (OCBO) is stronger than the negative association between Machiavellianism and organizational citizenship behaviors toward individuals or groups (OCBI). Additionally, Machiavellianism is associated with the OCB motive of impression management, but negatively associated with the OCB motives of organizational concern and pro-social values. Latif‘s (2000) study indicate that higher levels of moral reasoning were significantly related to ―internal‖ scores on Rotter‘s internal/external locus of control scale. Both higher levels of moral reasoning and ―internal‖ scores on the locus of control scale were significantly related in the negative direction with Machiavellianism. However, only moral reasoning accounted for a significant amount of the variance associated with students‘ ethical behavior. Goodboy and McCroskey (2007) study examined the relationships of organizational orientations and Machiavellianism with nonverbal immediacy and job satisfaction in the organizational context. Participants included 160 full-time employees who worked at various for profit or non-profit organizations in the Mid-Atlantic area. Results indicated that the organizational orientations (i.e., upward mobile, ambivalent, and indifferent) and Machiavellianism were significant predictors of employee nonverbal immediacy and job satisfaction. Conclusion The above accounts of Machiavellianism show that Machiavellianism is not simply a personality trait. Those who have high emotional intelligence show less Machiavellian behaviors. There is no significant difference between genders in term of Machiavellianism. However, the managerial position, business sector, the organizational size, economic development of countries and probably many other exogenous factors are more important facilitators of Machiavellian behaviors. We believe that ethical awareness is not simply an individual factor but actually more relevant with the cultural-normative factors and incentive situations within a social structure. References Becker J. A. & Dan O.H. (2007). Machiavellians‘ Motives in Organizational Citizenship Communication Research, 35 (3), pp. 246-267. Behavior, Journal of Applied Bodey, K.& Grace D. (2004). Examining Self-Monitoring, Perceived Control, Self-Efficacy and Machiavellianism in the Context of Complaint Behaviour, Griffith Business School, Conference Publications. 158 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Barlow, A. & Qualter, S. M. (2010). Relationships Between Machiavellianism, Emotional Intelligence and Theory Of Mind in Children, Personality and Individual Differences, (48), pp. 78-82. Cherulnik, P.D.& Way, J. H.& Ames, S. & Hutto D. B. (1981). Impressions of High and Low Machiavellian Men, Journal of Personality, (49), pp. 388-400. Christie R. & Geis F. L. (1970). Studies in Machiavellianism, New York Academic Pres, New York. Cooper, R. & Hands, D. & Wootton, A. & Bruce, M.& Daly, L. & Harun, R. (2003). Machiavelli and Innovation: The Politics of Design?, Desing Management, 5th European Academy of Design, Barcelona, Espanha, pp.1-16. Corzione, J. C. & Buntzman, G. F. & Busch, E. T. (1999). Machiavellianism in U.S.Bankers, The Journal of Organisational Analysis, 7, pp. 72-83. Cyriac K. J. & Dharmaraj R. (1994). Machiavellianism in Indian Management, Journal of Business Ethics, 13, pp. 281-280. Galie P. J. & Bopst C. (2006). Machiavelli and Modern Business: Realist Thought in Contemporary Corporate Leadership Manuals, Journal of Business Ethics, 65, pp. 235-250. Goodboy A. K.& Mccroskey J. C. (2007). Toward a Theoretical Model of the Role of Organizational Orientations and Machiavellianism on Nonverbal Immediacy Behavior and Job Satisfaction, Human Communication. A Publication of the Pacific and Asian Communication Association, 11 (3), pp.287 - 302. Kavak, B. (2001). Makyavelizm ile Tüketicinin Ahlaki Yargıları Arasındaki iliĢkiye Yönelik Amprik Bir Ġnceleme, Ev Ekonomisi Dergisi, 7(8), ss. 11-20. Jellinek, R. (1985). Machiavellianism, Organizational Structure And Principals' Occupational Stress (Job Satisfaction), Etd Collection For Fordham University. Paper Aaı8508118. Http://Fordham.Bepress.Com/Dissertations/Aaı8508118 Latif, D. A. (2000). The Relationship Between Pharmacy Students‘ Locus of Control, Machiavellianism, and Moral Reasoning, American Journal of Pharmaceutical Education, 64, pp. 33-37. Liu, C. C. (2008). The Relationship Between Machiavellianism and Knowledge Sharing Willingness, J Bus Psychol, 22, pp. 233240. Mandacı, G.(2007). Makyavelist Tutumların Etik Algısı Ve Demografik Faktörler Açısından Değerlendirilmesi: Bankacılık Sektöründe Bir AraĢtırma, Hacettepe Üniversitesi Sosyal Bilimler Enstitüsü ĠĢletme Anabilim Dalı Yönetim Organizasyon ve Örgütsel DavranıĢ Bilim Dalı, Yüksek Lisans Tezi, Ankara. Paal, T.& Bereczkei, T. (2007). Adult Theory of Mind, Cooperation, Machiavellianism: The Effect of Mindreading on Social Relations, Personality and Individual Differences, 43, pp. 541–551. Paulhus, D. L.& Williams, K.& Harms P. (2001). Shedding Light on the Dark Triad of Personality: Narcissism,Machiavellianism and Psychopathy, University of British Columbia Presented at 2001 SPSP Convention in San Antonio Society for Personality and Social Psychology. Porter, L. W.& Allen, R.W. & Angle H. L. (1981). The Politics of Upward Influence in Organizations, Research in Organizational Behavior, 3, pp. 109-149. Rayburn, M. J.& Rayburn, G. L. (1996). Relationship Between Machiavellianism And Type A Personality And EthicalOrientation, Journal of Business Ethia, 15, pp. 1209-1219. Rayburn, M.& Overby J. & Hammond, K. (2003). Differences in Charisma, Ethics, Personality, And Machiavellian Characteristics of Male And Female Marketing Students, Academy of Marketing Studies Journal, 7 ( 2), pp. 107-125. Shepperd, J. A. & Socherman, R. E. (1997). On the Manipulative Behavior of Low Machiavellians: Feigning Incompetence to "Sandbag" an Opponent‖ , Journal of Personality and Social Psychology, 72 (6), pp. 1448-1459. Schermerhorn, J. R.& Hunt, J. G.& Osborn, R. N. (1995). Basic Organizational Behavior, New York:John Wiley & Sons, Inc. Shome, A.& Rao, H. (2000). The Relatıonshıp Between Machiavellianism And Work Experience in Public Accountants: An Empirical Study, aaahq.org/northeast/2000/q65.pdf. 159 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Skinner, Q. (2002). ―DüĢüncenin Ustaları: Machiavelli‖ Türkçesi: Cemal Atila, Ġstanbul: Altın Kitaplar Yayınevi. Siu, W. (1998). Machiavellianism and Retail Banking Executives in Hong Kong, Journal of Managerial Psychology, 13 (1/2), pp.28-37. Subramaniam, V. M. (2009). The Relationship Between Machiavellianism and Job Involvement Among Employees in An Airline Company in Malaysia Faculty of Business and Accountancy, University of Malaya. Turner, C. F. & Martinez, D. C. (1977). Socieconomic Achievement and the Machiavellian Personality, Socimetry, 40 (4), pp. 325-336. Ural, T. (2003). ĠĢletme ve Pazarlama Etiği. Ankara: Detay Yayınları. Yıldız, G. & ErdoğmuĢ, N. (1998). Toplulukçu Kültürde Makyavelist DavranıĢ ve Bir Uygulama, Siyasette ve Yönetiminde Etik. Adapazarı. www.nihaterdogmus.com/.../6toplulukau-kaoeltaoerde-makyavelast-davraniaz-ve-bar-uygulama1.doc 160 � 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. 202 Title A name given to the resource Creating Morally-minded Organizations in a Machiavellian Work Environment Author Author ÖZLER, N. Derya Ergun MERCAN, Nuray Abstract A summary of the resource. Organizations are highly rational constructs operating in a competitive market and bureaucratic entities designed to attain first organizational-collective and individual-private ends in an orderly fashion. In an entity as such there is little formally accepted and approved room for personal maneuvers which may jeopardize much larger goals of organizations. However, organizations have an internally and interpersonally highly competitive environment, more like a war place for power and influence. Organizations are increasing looking for competent, competitive and achievement oriented individuals yet expect them to work in teams as resource sharing saints. It is time to ask whether it is exactly this paradoxical tendency of modern organizations that encourage Machiavellian behaviors. What type of business organizations and environments are more conducive to Machiavellianism? What types of negative and positive incentives are there in regard to Machiavellianism? And what needs to be done? The aim of this work is to develop above argument further, answer some of above questions and then make workable suggestions for practitioners to help in their attempts to identify Machiavellian tendencies and differentiate Machiavellian behaviors from non-Machiavellian ones. Date A point or period of time associated with an event in the lifecycle of the resource 2010-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory https://omeka.ibu.edu.ba/files/original/355c5ef218e20e7a76bf73eb84e09ffd.pdf 9b04d64542d304f6725bb1050366f283 PDF Text Text An Investigation on Improvement of Yield Potential of TMP-2 Composite Maize Gene Pool Ahmet ÖZ Çankırı Karatekin University, Science and Art Faculty, Çankırı-Turkey ahmetoz01@hotmail.com Halil KAPAR Black Sea Agricultural Research Institute, Samsun-Turkey halilkapar@yahoo.com Nevzat AYDIN Karamanoğlu Mehmetbey University, Vocational School, Karaman-Turkey nevzataydin@gmail.com Abstract: This study was conducted at the Black Sea Agricultural Research Institute in SamsunTurkey in 2005 and 2006. The aim of this research was to improve the yield potential of the TMP2 corn gene pool. A composite corn cultivar with high adaptation potential called 'Karadeniz Yildizi' in Turkish was enhanced using genetic source material (TMP-2). Nineteen maize source materials with high yield potential and similar agronomic traits to TMP-2 corn gene pool were obtained from Sakarya Agricultural Research Institute. These materials were then crossed with TMP-2 corn gene pool as female parents in 2005. Obtained hybrids were tested and experiment was conducted by randomized block design with three replications. Data was recorded for grain yield and yield components. In the experiment, the seeds of high yielding hybrids were mixed with seeds of TMP-2 gene pool at the rate of 5 % and used as male parents for next generation crossing. Introduction Maize is the world’s third most important crop after rice and wheat. Recently, its production and yield has increased significantly. Maize is generally used as a food product and for animal feed. Maizecobs are also used as a biomass fuel source. Recent developments in quantitative genetics and experimental data in the last century have helped in the development of alternative approaches to the conventional hybrid methodology. Composite varieties have given yield levels which closely approach those of commercial hybrids (Singh, 1987). Composite varieties are important for countries where the hybrid seed industry has not been organized and regular hybrid seed replacement programs are not convenient. Composite cultivars are also important for regions where the climate is not very adequate for corn growing. The major advantages in the use of composites are; a) The seed of composite varieties is cheap and simple, b) Farmers can use their own seed for growing the next crops, c) Composites can be further improved for important characters, d) Because of wider genetic base composites are more stable to major biotic stresses and negative climatic conditions, and e) Elite composites can serve as base population for inbred lines (Singh, 1987). The genetic variability of breeding materials is very important for maize breeders. Germplasm complexes and composites were developed and used as a genetic resource for the improvement of grain yield and other desirable characteristics. Different breeding methods and approaches were used for composite corn cultivars. Sprague and Eberhart (1977) showed that response to selection for yield improvement was similar for the different intra and inter-population recurrent selection schemes. S1 family selection seems to provide better opportunity to screen out the poorest progenies and thus, make more rapid progress (Hallauer and Miranda, 1987). Recurrent selection methods have been widely used by maize breeders for population improvement. Maize breeders used recurrent selection methods for improvement of population mean performance and maintenance of genetic variation for continued selection (Weyhrich et al., 214 �1998). Increasing grain yield potential of maize is due to the successive development of better adapted varieties. Estimates of increased productivity due to genetic gain in U.S. maize production are about 77 kg ha-1 (Duvick et al., 2004). The aim of this research is to improve the yield potential of the TMP-2 composite maize gene pool by using high yielding source materials obtained from Sakarya Agricultural Research Institute. Materials and Method Nineteen maize source materials were obtained from Sakarya Agricultural Research Institute to use in this study (Table 1). These materials had high yield potential and similar agronomic traits to TMP-2 composite maize gene pool. Hybrids were produced by crossing each nineteen source material with the materials from TMP-2 composite maize gene pool. The materials obtained from Sakarya were used as female parents in 2005. From this crossing effort, nineteen hybrids were developed. The composite cultivar “Karadeniz Yıldızı” was used as the control in the trial. Experiment was conducted in Samsun (Lat. 36°20’E, long. 41°17’N, 4 m above sea level) in the 2006 growing season. The experimental design was a Completely Randomized Block Design with three replications. Each experimental plot included four fivemeter long rows spaced 0.70 m apart, with 25 single-plant hills spaced 0.20 m apart. TMP-2 composite maize gene pool has a high plant height and the seed structure likes yellow flint. Composite cv. Karadeniz Yildizi, developed from TMP-2 composite maize gene pool is grown for silage and grain. Data was recorded for grain yield and yield components. According to the experiment results, the high yielding hybrids were selected. Stock seeds of selected source materials were mixed with seeds of TMP-2 composite maize gene pool at the rate of 5 % and used as male parents for next generation crossing. Data were taken on tasselling time (days from planting to 50 % of plants tasselling), grain yield (kg da-1). Plant height (cm), ear height (cm), grain moisture (%), yield/ear ratio (%), plant and ear appearance were estimated from a sample of 10 plants from each plot. All the data were analyzed with analysis of variance (ANOVA) procedures using the Statistical Software Package. The comparison of the treatment means was made by using the Least Significant Difference (LSD) test. 1- KDEB.PN55 6- KDEB.PN155 2- KDEB.PN6 7- KDEB.PN165 3- KDEB.PN48 8- KDEB.PN176 4- KDEB.PN84 9- KDEB.PN187 5- KDEB.PN140 10- KDEB.PN261 Table 1. Maize source materials 11- KDEB.PN275 12- KDEB.PN350 13- KDEB.PN488 14- KDEB.PN587 15- KDEB.PN603 16- KDEB.PN632 17- KDEB.PN643 18- KDEB.PN644 19- KDEB.PN648 20- Karadeniz Yıldızı Findings and Discussion Grain yield, some yield related and morphological traits were investigated in this study. The results and statistical analysis were given in Table 1 and 2. Grain Yield The differences of grain yield of the hybrids were statistically significant (Table 1). The grain yields of hybrids ranged from 775 to 1155 kg/da, and averaged 984 kg/da. The highest grain yield was obtained from KDEB.PN187 x TMP-2 hybrid, and KDEB.PN643 x TMP-2 and KDEB.PN350 x TMP-2 hybrids followed it. Karadeniz Yildizi improved from TMP-2 composite maize gene pool yielded 1004 kg/da. Grain yield is the most important trait for selection of genetic source material. The aim of this study was to improve the grain yield potential of TMP-2 composite maize gene pool, and high yielding genotypes were determined for this aim. It is expected that cultivars coming from different genetic background might have different yield potentials, however the yields of cultivars correlated with their adaptation ability to different environment (Emeklier, 1987). Some researchers reported that hybrids between inbred lines with 215 �high yield potential might have high yield potential (Lonnquist and Lindsey, 1964; Lamkey and Hallauer, 1986). Tasseling Time Tasseling time is an important trait in this study, because tasseling time of selected source materials should be same or very close to tasseling time of TMP-2 composite maize gene pool. The tasseling time of source materials ranged from 64.3 days to 76.3 days, and difference of genotypes for tasseling time was statistically significant (p<0.01, Table 1). While some source material flowered earlier than Karadeniz Yildizi, some materials flowered later than it. The materials with high yield and similar tasseling time to TMP-2 composite maize gene pool were selected. Tasseling time can change according as genotype and climate. Martin et al. (1976) reported that ideal temperature for growing in corn was 21-27 0C for daylight and 13 0C for night. Corn is generally grown in hot climate, the temperature over 27 0C can decrease grain yield. Altinbas and Tosun (1998) found that late flowering cultivars generally had higher grain yield. Genotypes Grain yield Tasseling time Plant height Ear height (kg/da) (day) (cm) (cm) 1- KDEB.PN55 x TMP-2 1015 ae** 67.7 ij** 282 cf** 115 bd** 2- KDEB.PN6 x TMP-2 877 df 66.0 jk 270 eg 103 ce 3- KDEB.PN48 x TMP-2 983 be 69.3 gi 292 be 103 ce 4- KDEB.PN84 x TMP-2 1080 ab 69.7 fh 305 ab 112 bd 5- KDEB.PN140 x TMP-2 916 cf 74.0 b 307 ab 132 ab 6- KDEB.PN155 x TMP-2 870 ef 69.3 gi 277 df 108 bd 7- KDEB.PN165 x TMP-2 991 be 69.0 gi 280 df 118 bc 8- KDEB.PN176 x TMP-2 1000 be 71.3 df 293 bd 105 cd 9- KDEB.PN187 x TMP-2 1155 a 72.0 ce 282 cf 108 bd 10- KDEB.PN261 x TMP-2 1068 ab 71.7 de 278 df 92 df 11- KDEB.PN275 x TMP-2 775 f 70.3 eg 273 df 92 df 12- KDEB.PN350 x TMP-2 1100 ab 72.0 ce 293 bd 120 bc 13- KDEB.PN488 x TMP-2 978 be 73.0 bd 292 be 110 bd 14- KDEB.PN587 x TMP-2 1023 ad 76.3 a 320 a 153 a 15- KDEB.PN603 x TMP-2 1081 ab 74.7 ab 288 be 107 cd 16- KDEB.PN632 x TMP-2 803 f 64.3 k 247 h 73 f 17- KDEB.PN643 x TMP-2 1104 ab 73.7 bc 310 ab 117 bc 18- KDEB.PN644 x TMP-2 818 f 64.3 k 250 gh 80 ef 19- KDEB.PN648 x TMP-2 1044 ac 68.0 hi 260 fh 107 cd 20- Karadeniz Yıldızı 1004 be 68.7 gi 303 ac 112 bd Mean 984 72.3 285 108 CV (%) 9.0 1.61 4.71 13.8 **, Means within a column followed by the same letter are not significantly different at 1% level. Table 2. Tasseling time, plant height, ear height and grain yield of genotypes. Plant Height The differences between plant height of genotypes were statistically significant (p<0.01) (Table 1). Plant height changed from 247 to 320 cm, and average plant height was found as 285 cm in the trial. The highest plant height was obtained from hybrid KDEB.PN587 x TMP-2. Plant height and ear height are important agronomic traits for cultivars and there is a close correlation between them. Plant height was a crucial trait to select for this source material. Selected material should have plant height close to the plant height of TMP-2 composite maize gene pool, because ‘Karadeniz Yildizi’ is grown for both grain and silage. 216 �Ear Height Significant differences among genotypes were observed for ear height. Obtained data for ear height ranged from 73 cm to 153 cm. Average ear height was 108 cm in the study. Hybrid KDEB.PN587 x TMP-2 had the highest ear height such as plant height. Genotypic factor are known to influence ear and plant height more than environmental factor (Hallauer and Miranda, 1987). Attention was also given to select source material with similar ear and plant height to TMP-2 composite maize gene pool to obtain morphologic similarity. Hallauer and Sears (1972) reported that mass selection for early silking concluded with an average decrease of 15 cm per cycle of selection for ear height. They also found that there was a simple correlation between early silking and lower ear height (r = 0.89). Grain Moisture Grain moisture of genotypes changed from 20.3% to 31.3% in the harvest (Table3). Significant variation was found among genotypes for grain moisture (p<0.01). Grain moisture is an important trait for location conducted the trial. The lowest grain moisture was recorded for hybrid KDEB.PN6 x TMP-2, while the highest for hybrid KDEB.PN587 x TMP-2. Karadeniz Yildizi had 24.3% grain moisture and mean grain moisture was 24.3% in the trial. We selected the source material with close or lower grain moisture content to TMP-2 composite maize gene pool. Yield/Ear Ratio Yield/ear ratio were recorded as 76.1% to 83.9% and averaged 79.3% (Table 3). Differences of yield/ear ratio among genotypes were significant (p<0.01). The hybrid KDEB.PN187 x TMP-2 with highest grain yield had the highest yield/ear ratio. Yield/ear ratio is a crucial trait for corn breeders and high yield/ear ratio is desired to develop high yielding hybrids. Plant and Ear Appearance Data for plant and ear appearances were not statistically analyzed (Table 3). Plant and ear appearance is an important criterion to selection for breeders. The genetic source materials having value 1 and close to 1 for plant and ear appearance were selected. Genotypes 1- KDEB.PN55 x TMP-2 2- KDEB.PN6 x TMP-2 3- KDEB.PN48 x TMP-2 4- KDEB.PN84 x TMP-2 5- KDEB.PN140 x TMP-2 6- KDEB.PN155 x TMP-2 7- KDEB.PN165 x TMP-2 8- KDEB.PN176 x TMP-2 9- KDEB.PN187 x TMP-2 10- KDEB.PN261 x TMP-2 11- KDEB.PN275 x TMP-2 12- KDEB.PN350 x TMP-2 13- KDEB.PN488 x TMP-2 14- KDEB.PN587 x TMP-2 15- KDEB.PN603 x TMP-2 16- KDEB.PN632 x TMP-2 Grain moisture (%) 26,3 cd** 20,3 k 24,9 gh 23,5 i 24,5 gh 22,3 j 24,1 hi 26,9 c 26,3 cd 25,9 de 25,2 ef 26,9 c 27,9 b 31,3 a 26,9 c 23,9 hi Yield/ear ratio (%) 76,2 k** 76,1 k 79,5 gh 82,4 ce 76,4 k 79,4 gh 82,5 ac 78,4 hi 83,9 a 81,1 df 80,7 eg 76,5 k 77,3 ik 76,8 jk 76,5 k 79,6 fh 217 Plant appearance (1-5) 1,33 1,67 1,83 1,17 1,17 1,83 1,83 1,00 1,50 1,17 2,17 1,00 1,00 1,17 1,33 2,50 Ear appearance (1-5) 1,67 1,83 1,67 1,67 1,83 2,00 2,00 1,83 1,33 1,50 2,17 1,50 1,50 1,50 1,67 2,00 �17- KDEB.PN643 x TMP-2 25,8 de 81.0 df 1,33 1,83 18- KDEB.PN644 x TMP-2 21,9 j 78,2 hj 2,00 2,50 19- KDEB.PN648 x TMP-2 23,9 hi 83,3 ab 1.67 1,50 20- Karadeniz Yıldızı 24,3 gh 81,4 ce 2.00 1,67 Mean 25.1 79.3 1.53 17.6 CV (%) 1.76 1.13 **, Means within a column followed by the same letter are not significantly different at 1% level. Table 3. Grain moisture, yield/ear ratio, plant appearance and ear appearance of source materials hybrids. Conclusion The genetic materials of KDEB.PN187, KDEB.PN644, KDEB.PN350, KDEB.PN261, KDEB.PN84, KDEB.PN648 and KDEB.PN55 were selected to use for improving of yield potential of TMP-2 composite maize gene pool. The seeds of selected source materials at the rate of 5% could be mixed to the seeds of TMP-2 gene pool, and could be used as male parents. The hybrids of KDEB.PN603 x TMP-2 and KDEB.PN587 x TMP-2 with high grain yield were not selected because of their late tasseling time. The hybrid of KDEB.PN6 x TMP-2 had the lowest grain moisture, however it had lower grain yield. References Altınbaş, M. and M. Tosun, (1998). Melez mısır (Zea mays L.) ıslahında kombinasyon yeteneiği kovaryanslarından yararlanma olanağı üzerine bir çalışma. Anadolu, 8 (2) 90-100. Duvick, D. N., J. S. C. Smith, and M. Cooper, (2004). Long-term selection in a commercial hybrid maize breeding program, Plant Breed. Rev., 24:109–151. Emeklier, H.Y, (1997). Erkenci hibrid mısır çeşitlerinin verim ve fenotipik özellikleri üzerine araştırmalar. Ankara Üniversitesi, Ziraat Fakültesi Yayınları, No:1493, Bilimsel Araştırma ve Đncelemeler: 817, Ankara. Hallauer A. R. and J. B. Miranda, (1987). Quantitative Genetics in Maize Breeding. Iowa State University Press, Ames, Iowa. Hallauer, A. R. and J. H. Sears, (1972). Integrating Exotic Germplasm into Corn Belt Maize Breeding Programs. Crop Sci 12:203-206 Lamkey K. R. and A. R. Hallauer, (1986). Performance of high x high, high x low, low x low crosses of lines from the BSSS maize synthetic. Crop Sci. 26: 1114-1118. Lonnquist, J. H. and M. F. Lindsey, (1964). Topcross versus S1 line performance in corn. Crop Sci. 4: 580-584. Martin, J.H., W.H. Leonard and D.L. Stamp, (1976). Principles of Field Crop Production. Third edition. Macmillan Publishing Co. Inc., New York. Singh, J, (1987). Field Manuel of Maize Breeding Procedures. Food and Agriculture Organization of The United Nations, Rome. Sprague, G. F and S. A. Eberhart, (1977). Corn Breeding. American Social Agronomy. Madison. Wisconsin. Weyhrich, R. A., K. R. Lamkey, and A.R. Hallauer, (1998). Effective Population Size and Response to S1- Progeny Selection in the BS11 Maize Population. Crop Science, Vol. 38, 1149-1158. 218 � 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. 392 Title A name given to the resource An Investigation on Improvement of Yield Potential of TMP-2 Composite Maize Gene Pool Author Author ÖZKUL, Ahmet Sait KAPAR, Halil AYDIN, Nevzat Abstract A summary of the resource. This study was conducted at the Black Sea Agricultural Research Institute in Samsun- Turkey in 2005 and 2006. The aim of this research was to improve the yield potential of the TMP- 2 corn gene pool. A composite corn cultivar with high adaptation potential called 'Karadeniz Yildizi' in Turkish was enhanced using genetic source material (TMP-2). Nineteen maize source materials with high yield potential and similar agronomic traits to TMP-2 corn gene pool were obtained from Sakarya Agricultural Research Institute. These materials were then crossed with TMP-2 corn gene pool as female parents in 2005. Obtained hybrids were tested and experiment was conducted by randomized block design with three replications. Data was recorded for grain yield and yield components. In the experiment, the seeds of high yielding hybrids were mixed with seeds of TMP-2 gene pool at the rate of 5 % and used as male parents for next generation crossing. 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/02561645e087048a714c3bec6f667527.pdf 3ae16e1cf405010fea0a3ef6f786ce4e PDF Text Text Determination of The Effects of Loads on Some Engine Parameters for Agricultural Tractors Zafer ÖZGÜR Çanakkale Onsekiz Mart University, Biga Vocational College zozgur@comu.edu.tr Abstract : The objective of this study is to determine the load based engine exhaust temperature, cooling water temperature, fuel consumption and specific fuel consumption parameters and to examine the relationship between them. To this end, partial loads have been applied to three different tractor brands that are widely used in our country (Massey Ferguson 3085, New Holland TD85 and John Deere 5625) under workshop conditions at different PTO speeds (540, 540E, 750) by using an Eddy Current dynamometer. The trials have been carried out separately for each tractor and the engine parameters have been measured concurrently with the applied loads. In all trials the exhaust gas temperature has been found to be between 181.10-603.40 °C, the engine cooling water temperature between 63.20-83.40 °C, the fuel consumption between 3.15-15.68 L/h and the specific fuel consumption to be between 230.371112.79 g/kWh. According to the results of the research there is a distinct increase in the exhaust gas temperature and fuel consumption parameters due to the increase of PTO and there is a decrease with similar ratios in specific fuel consumption. Whereas cooling water temperature values tend to decrease very slightly due to power change. According to variance analysis results it has been determined that the PTO speed and PTO power factors and their interactions have statistically significant (P<0.01) effects on all the measured parameters. As a result of the study it has been concluded that even though the three PTO speeds have different engine operation parameters, they can be used as alternatives for each other for many PTO driven agricultural machines. Keywords: Tractor, PTO, engine performance parameters Introduction Nowadays in the world against the energy shortages, quality and quantity of production, as well conscious of the mechanization of agricultural production to achieve the most ideal conditions is obligatory. Mechanization of agricultural practices to ensure efficiency, knowledge of the ability of the tractor in agricultural enterprises, and accordingly the use of tractors conveniently, the use of tractors and business machines by increasing efficiency can help reduce operating costs Aging of engine and the reduction in work efficiency depending on the annual working hours and working conditions of tractor usually are not being noticed or not ignored by the users. This situation is realized by the consume of more fuel for the same work of the tractor or unable to fulfill the work. These conditions causing significant losses in business is need to be foreseen and taken precautions. To detect and evaluate negative changes mentioned by the tractor engine periodically parameters such as temperature and fuel consumption are required to determine. Because he loss of efficiency in engines are directly effective on tail shaft torque and power transferred from the agricultural machine, periodcally and practically the efficiency of PTO should be meassured. For this process, in static conditions usually workshop-type hydraulic dynamometer is used. With dynamometer, maximum tractor PTO power can be determined. The measurements will be made periodically, it informs users about the efficiency of the tractor engine. 198 �In this study partial loads have been applied to three different tractor brands that are widely used in our country (Massey Ferguson 3085, New Holland TD85 and John Deere 5625) under workshop conditions at different PTO speeds (540, 540E, 750) by using an Eddy Current dynamometer. The objective of this study is to determine the load based engine exhaust temperature, cooling water temperature, fuel consumption and specific fuel consumption parameters and to examine the relationship between them. Specific Fuel Consumption and Fuel Consumption Motor is a machine that converts heat energy resulting in the burning of fuel in cylinders to mechanical energy. Power produced per unit time to the amount of fuel consumed is called the specific fuel consumption. Specific fuel consumption varies depending on engine load conditions. For example, the fuel consumption at full is less than the half that of gas. Engine Exhaust Gas and Water Temperature In ınternal combustion engines, the ratio of beneficial work from the motor shaft to the energy supplied with fuel to machine is defined as brake thermal efficiency. The fuel to the engine that convert heat energy into mechanical energy, some losses have occurred. These losses occur by exhaust, cooling, friction and radiation. To increase the brake thermal efficiency, it is necessary to reduce these losses and to know the share of total losses. Kayıp enerjilerin ve efektif gücün belirlenerek değerlendirilmesine ısı balansı denilmektedir. Evaluation of energy loss and effective power is called as heat balance. Heat balance that define the economy in engine also give idea about the various losses. In ınternal combustion engines, the maximum cycle temperature is limited due to the structural features of the engine. Therefore, in reciprocating internal combustion engines, it is necessary cooling systems to check the temperature of engine parts. For four-stroke diesel engines, the heat loss through the cooling is ranged from 20-28%. This heat loss comprises the heat passing to cooling water and lubricating oils. An average of only 8% loss of lubricating oil is in question. Material and Method In workshops, experiments conducted at static conditions, full and partial load is applied to three test trials of the tractor tail spindle and the necessary parameters have been determined. Measurement systems used for this purpose is given schematically in Figure 1.1 In experiments carried out in workshop conditions, loads connected to the tractor PTO engine exhaust gas temperature, cooling temperature, fuel consumption and specific fuel consumption parameters are examined, evaluated the relationship between them. 199 �Figure 1.1. Schematic illustration of measurement systems used in research Relations Between PTO Power and the Exhaust Gas Temperature Engine exhaust gas temperatures measured for each load level applied to the tractor PTO are given in Table 2.1. PTO power (kW) 5 10 15 20 25 30 35 40 45 JD 5625 238.00 253.10 278.20 299.30 323.30 348.50 373.80 405.30 422.50 540 NH TD85 248.30 277.60 311.80 345.60 378.90 412.00 446.10 481.00 514.70 exhaust gas temperatures (°C) 540E JD NH MF MF 3085 5625 TD85 3085 267.80 181.10 203.70 219.30 302.20 209.80 244.00 270.50 337.30 248.80 286.90 320.00 373.90 281.60 330.40 372.40 404.60 310.50 368.80 420.00 437.00 339.50 411.20 474.80 471.20 368.50 452.80 518.00 501.00 407.20 494.40 570.90 531.90 439.90 540.30 603.40 Table 2.1. Engine exhaust gas temperatures 200 JD 5625 232.00 256.60 281.30 302.00 331.40 356.70 374.20 406.90 428.60 750 NH TD85 267.20 293.90 324.80 354.80 387.90 419.10 448.90 480.20 511.50 MF 3085 276.80 308.30 342.90 376.00 414.80 443.00 477.00 504.20 532.70 �When the charts examined, exhaust gas temperatures obtained for John Deere 5625, New Holland TD85 ve Massey Ferguson 3085 tractors was found to increase in application of three PTO depending on the load levels. Relations Between PTO Power and Cooling Water Temperature Engine cooling water temperatures measured each load level applied to the tractor PTO are given in Table 2.2 PTO power (kW) 5 10 15 20 25 30 35 40 45 JD 5625 81.90 82.20 82.30 82.10 81.80 82.60 82.90 83.40 83.40 540 NH TD85 67.00 67.50 68.00 69.00 69.40 70.00 70.00 71.00 71.20 MF 3085 64.10 67.30 70.70 74.10 74.60 74.70 76.00 75.10 76.00 cooling water temperatures(°C) 540E JD NH MF 5625 TD85 3085 79.40 65.00 63.20 80.10 65.10 66.60 80.10 66.00 69.40 80.00 66.00 72.20 80.00 67.00 75.00 80.30 67.50 76.00 80.80 68.00 76.40 81.40 69.00 77.00 81.50 70.00 76.80 JD 5625 82.80 81.90 82.20 81.90 82.90 82.60 82.80 82.10 83.00 750 NH TD85 66.00 66.00 66.80 67.00 67.30 68.00 68.00 69.00 69.00 MF 3085 63.20 64.80 71.60 74.10 74.60 74.70 76.00 75.10 76.00 Table 2.2. Engine cooling water temperature values Cooling water temperatures obtained for he John Deere 5625 ve Massey Ferguson 3085 tractors was not found significant difference in the application of three PTO depending on the load levels. Relations Between PTO Power and Fuel Consumption Engine fuel consumption measured each load level applied to the tractor PTO is given in Table 2.3 PTO power (kW) 5 10 15 20 25 30 35 40 45 JD 5625 6.62 7.45 8.44 9.52 10.55 11.66 12.92 14.33 15.38 540 NH TD85 5.09 5.95 6.90 8.02 9.08 10.21 11.30 12.53 13.78 MF 3085 4.76 5.72 6.73 7.79 9.00 10.17 11.34 12.70 13.93 Fuel consumption (L/h) 540E JD NH MF 5625 TD85 3085 3.93 3.55 3.15 4.81 4.58 4.14 5.79 5.60 5.22 6.85 6.75 6.38 7.89 7.81 7.50 8.98 8.95 8.73 10.08 10.06 9.88 11.36 11.33 11.17 12.59 12.67 12.54 Table 2.3. Motor fuel consumption values 201 JD 5625 6.73 7.52 8.52 9.63 10.74 11.96 13.28 14.50 15.68 750 NH TD85 5.83 6.75 7.82 9.00 10.08 11.38 12.54 13.63 14.92 MF 3085 5.36 6.27 7.45 8.73 9.96 11.15 12.43 13.80 15.02 �Fuel consumption values for John Deere 5625, New Holland TD85 ve Massey Ferguson 3085 tractors was found to increase in application of three PTO depending on the load levels. Relations Between PTO Power and the Specific Fuel Consumption Engine specific fuel consumption values measured each load level applied to the tractor PTO is given in Table 2.4 PTO power (kW) 5 10 15 20 25 30 35 40 45 JD 5625 1095.64 616.01 465.19 393.68 349.10 321.35 305.29 296.23 282.58 Specific fuel consumption (L/h) 540 540E NH MF JD NH MF JD TD85 3085 5625 TD85 3085 5625 841.17 786.86 649.90 586.84 520.82 1112.79 492.45 472.74 398.19 378.53 342.31 622.29 380.50 370.78 319.01 308.48 287.62 469.78 331.59 322.21 283.19 279.06 263.81 398.09 300.27 297.65 261.03 258.42 248.10 355.14 281.43 280.33 247.52 246.80 240.78 329.63 266.99 267.92 238.15 237.65 233.48 313.85 259.02 262.51 234.80 234.26 231.01 299.85 253.26 256.04 231.36 232.90 230.37 288.20 Table 2.4. Engine specific fuel consumption values 750 NH TD85 964.33 558.24 431.18 372.12 333.52 313.64 296.19 281.86 274.11 MF 3085 886.27 518.90 410.83 361.02 329.64 307.31 293.63 285.36 276.05 Specific fuel consumption values obtained for the John Deere 5625, New Holland TD85 ve Massey Ferguson 3085 tractors was found to decrease in application of three PTO depending on the load levels. Conclusions and Recommendations Study, for 540 rpm , the tail of a tractor PTO shaft speed to the load applied in the experiment in the with the tail.In this study, for loads applied to the trial tractors which are in 540 rpm PTO speed , tractor fuel consumption, specific fuel consumption and PTO torque variables were determined. Torqu values depending on the loadings for 540 rpm PTO speed are varied among the 88 888 Nm. That implies the change in PTO speed with the same power levels will also change the torque values. In other words, because of the different torgque needs of agriculturel machinery moving from PTO, operating characteristics of an agricultural machine working with 540 rpm speed may vary with 750 rpm speed. 750 rpm PTO option is used for agricultural machines that not require more torque as an alternative speed option for 540 rpm and 1000 rpm PTO speed. During the dynamometer test, torque power and speed measurements in parallel with the fuel consumption values were also measured. The data obtained by processing the results of calculations , specific fuel consumption was also determined. Values for fuel consumption increased proportionally with the power values despite specific fuel consumption decreased with increasing levels of power. For Massey Ferguson 3085, New Holland TD85 ve John Deere 5625 tractors with the same speed level, avarage special fuel consumption value increased 9.92%, 11.16% ve 1.70% respectively when it is passed from 540 rpm PTO to 750 rpm PTO. Fuel consumption values of 750 rpm instead of 540 rpm PTO speed with the case has shown a certain tendency to increase. When all the applied load is taken into account (5 50kW), the fuel consumption increase rate between two PTO speed varied between the values 7.56-12.63% for Massey Ferguson 3085, 7.59 14.64% for New Holland TD85 and 1.00-2.80% or John Deere 5625 tractor. Cooling water temperatures are 63–77 ºC, 66–72 ºC and 79–87 ºC respectively for Massey Ferguson 3085, New Holland TD85 ve John Deere 5625 tractors respectively. These difference between cooling water temperatures are thought to be arised from the different thermostat features. 202 �In this study, 540 rpm and 750 rpm PTO speed were compared statically only workshop conditions. From the evaluations, especially fuel consumption and specific fuel consumption parameters are emphasized. However, this study should be support with the field work. For example when disk fertilizer distribution machine is run with 750 rpm instead of 540 rpm PTO speed, it would be possible that work wildth will increase and work completion time will be influenced. For these reasons, the differences between the two PTO speed (work size, operating time, fuel consumption, torque, etc) should be compared for various agricultural machinery moving from PTO in actual working conditions. References Anonim, 2004. New Holland TD 85 Kullanım kitabı. New Holland Trakmak A.Ş. (In Turkish) Anonim, 2008a., (08.Kasım 2008) Tarım ve Köy işleri Bakanlığı yayınları, Traktör Tekniği kitabı (http://www.tarim.gov.tr/sanal_kutuphane/basili/permem/ kitapweb/tarmekkit/bilgi/b210.pdf) (In Turkish) Balcı, Y., 1982. Traktör Motor Gücü ve Egzoz Gazı Sıcaklığı Arasındaki Đlişkilerin Saptanması Üzerine Bir Araştırma. Ç.Ü. Ziraat Fakültesi Tarım Makinaları Bölümü. Lisans Tezi. (18)s. (In Turkish) Bastaban S., 1994. Traktör Performansını Belirlemek Đçin Kullanılan Genel Amaçlı Ölçüm ve Datalogger Seti. Tarımsal Mekanizasyon 15. Ulusal kongresi, Antalya, 10–22 Eylül, Sayfa: 14–23(In Turkish) Downs H.W., Hansen R.W., 2006. Selecting Energy-Efficient Tractors. Colorado State University. Cooperative Extension. 9/98. Reviewed 1/05. no. 5.007. Engürülü, B., Ö. Çiftçi, M. Gölbaşı, H.Ç. Başaran and M. Akkurt. 2005. Traktör Tekniği. Tarım ve Köyişleri Bakanlığı Ankara Zirai Üretim Đşletmesi, Personel ve Makina Eğitim Merkezi Müdürlüğü Yayınları. Ankara. (In Turkish) Evcim, Ü.,Ulusoy, E., Gülsoylu, E., Sındır, K. O., Đçöz, E., 2004. Türkiye tarımı makinalaşma durumu. (In Turkish) Gil-Sierra, J. Ortiz-Cañavate, J., Gil-Quirós, V., Casanova-Kindelán J., 2007. Energy Effıcıency in Agrıcultural Tractors: a Methodology for Theır Classıfıcatıon. Applied Engineering in Agriculture. Vol. 23(2): 145-150. Grisso, R. D., Kocher,M. F., Vaughan D. H., 2004. Predicting Tractor Fuel Consumption. Applied Engineering in Agriculture. Vol. 20(5): 553−561. Koertner, R.G., Bashford, L.L., Lane, D.E., 1977. Tractor Instrumentation for Measuring Fuel and Energy Requirements. Transactions of the ASAE. Vol. 20(3): 402-405. Lin, T., Buckmaster, D.R., 1996. Evaluation of an Optimized Engine-Fluid Power Drive System to Replace Mechanical Tractor Power Take-Offs. Transactions Sabancı, A. 1997. Tarım Traktörleri. Ç.Ü. Ziraat Fakültesi Ders Kitapları Genel Yayın No: 46. Adana. (In Turkish) Sümer S.K., Has, M., Sabanci, A., 2004. Türkiye’de Üretilen Tarım Traktörlerine Ait Teknik Özellikler. Ç.Ü. Ziraat Fakültesi Dergisi. 19(1):17-26. Adana. (In Turkish) Sümer, S.K., Sabancı, A., Ükler, K., 1998. Tarım Traktörlerinde, Güç ve Tarımsal Mekanizasyon Kongresi, Tekirdağ. (In Turkish) Thomas, R. S., Buckmaster, D. R., 2005. Development of a Computer-Controlled, Hydraulıc, Power Take-Off (PTO) System. Transactions of the ASAE. Vol. 48(5): 1669−1675. 203 � 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. 384 Title A name given to the resource Determination of The Effects of Loads on Some Engine Parameters for Agricultural Tractors Author Author ÖZGÜR, Zafer Abstract A summary of the resource. The objective of this study is to determine the load based engine exhaust temperature, cooling water temperature, fuel consumption and specific fuel consumption parameters and to examine the relationship between them. To this end, partial loads have been applied to three different tractor brands that are widely used in our country (Massey Ferguson 3085, New Holland TD85 and John Deere 5625) under workshop conditions at different PTO speeds (540, 540E, 750) by using an Eddy Current dynamometer. The trials have been carried out separately for each tractor and the engine parameters have been measured concurrently with the applied loads. In all trials the exhaust gas temperature has been found to be between 181.10-603.40 °C, the engine cooling water temperature between 63.20-83.40 °C, the fuel consumption between 3.15-15.68 L/h and the specific fuel consumption to be between 230.37- 1112.79 g/kWh. According to the results of the research there is a distinct increase in the exhaust gas temperature and fuel consumption parameters due to the increase of PTO and there is a decrease with similar ratios in specific fuel consumption. Whereas cooling water temperature values tend to decrease very slightly due to power change. According to variance analysis results it has been determined that the PTO speed and PTO power factors and their interactions have statistically significant (P<0.01) effects on all the measured parameters. As a result of the study it has been concluded that even though the three PTO speeds have different engine operation parameters, they can be used as alternatives for each other for many PTO driven agricultural machines. 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/e897ed456f552d90e262a857509e2e9c.pdf 2531466ac2a6efeb22ab3c747a3fc757 PDF Text Text Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Assistant Prof. Dr. Ersan ÖZGÜR Afyon Kocatepe University Sandıklı M.Y.O. ersanozgur@yahoo.com Abstract: Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today’s decision makers has to be able to think and plan the futures resources for not to danger future’s generations. In this perspective sustainable development policies can be considered as a solution for the next generation’s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. Introduction Nowadays, industrialized countries have recognized that their economical growth has a limit. At this point they also recognized that even though there was an economic growth there are also limits for economic development. Developed countries, are taking procoutions against the risks in relation to sustainablility. However developing countries has not been recognized that the importance of the subject. On the other hand it can be assumed that there are limited activities in relation to the subject. Contries are trying to impliment new sustainable development strategies. This could be as a solution for to reach their targets. In this perspective Turkey as a developing country has to set up similar development strategies and plans. Sustainable development has a direct relationship with the development of reel sector. Textile sector is a high significant sector for Turkish economy. Turkish textile sector is dinamic and has a high potantial for the growth. Espacialy after 1980’s with establishment of open economic policies exportation is increased and textile sector became the engine of the economy. Cotton production in Turkey has played a crucial role in the development of the economy. In consideration of globalization which increased the competition, assesment of effiency and effectiveness has became more important for the decision makers. Textile sector is contributing to the Turkish economy in terms of value add, employment and exportation. It is suggested that for sustainablity of textile sector performance measurement of efficiency and effectiveness of the sector has became more significant. Sustanable development, productivity and efficiency are related consepts. Productivity can be described as obtaining an output by using least input. Which means efficient uses of limited resouces. Performance can be considered as degree of success with in certain period of time. Managers can not /should not take desicions without having performance information. Hence it might be suggested that using performance measuring methods are significant for decision makers. One of the methods used for measuring performance is Data Enveloping Analyses. Sustainable Development The structures of imperial and colonial power which dominated the world in the nineteenth and early twentieth centuries made little provision for economic and social advance in what we now call the developing world. Colonial regions functioned primarily to supply imperial powers with raw materials and cheap labor – including slave labor as late as the mid-nineteenth century (Harris, 2000). Industrialization is an important target for the countries, however, there are some problems they face in this process inevitably. Environmental problem is one of them. Although it has some negative effects on environment, industrialization may not be abandoned. But it is obvious that some necessary measures should be taken for a sustainable development.(Ekinci, 2007) 761 �Whilst earlier literature discussed a wide range of issues around the emerging concept of sustainable development, the following statement from the World Conservation Strategy (IUCN/WWF/UNEP, 1980) appears to be the first actual attempt to define sustainable development: "For development to be sustainable, it must take account of social and ecological factors, as well as economic ones; of the living and non-living resource base; and of the long-term as well as the short-term advantages and disadvantages of alternative action" The World Conservation Strategy was frequently criticised for being concerned mainly with ecological sustainability rather than sustainable development per se. The most universally quoted definition is that produced in 1987 by the World Commission on Environment and Development (WCED), otherwise known as the Brundtland Commission (after its Chairperson, Gro Harlem Brundtland, Prime Minister of Norway): "Economic and social development that meets the needs of the current generation without undermining the ability of future generations to meet their own needs". (Dalal-Clayton, 2000) In the extensive discussion and use of the concept since then, there has generally been a recognition of three aspects of sustainable development:(Harris, 2000) - Economic: An economically sustainable system must be able to produce goods and services on a continuing basis, to maintain manageable levels of government andexternal debt, and to avoid extreme sectoral imbalances which damage agricultural or industrial production. - Environmental: An environmentally sustainable system must maintain a stable resource base, avoiding over-exploitation of renewable resource systems or environmental sink functions, and depleting nonrenewable resources only to the extent that investment is made in adequate substitutes. This includes maintenance of biodiversity, atmospheric stability, and other ecosystem functions not ordinarily classed as economic resources. - Social: A socially sustainable system must achieve distributional equity, adequate provision of social services including health and education, gender equity, and political accountability and participation. With these aspects sustainable development has got some strategies. Sustainable development strategies can be summarized under 9 headings: (Özyol, 2007) - Environment: Nature has its own value. None of the creature should not abuse the nature for their own needs. - The Future: While satisfying our needs we should think and take care of next generations needs and we should not forget that we have to live a world where the next generations could be able to satisfy their own needs. - Living Standards: We should not forget that living standarts of the people is not rely on materialistic needs but also it relies on social, cultural, ethical and spiritual needs. - Justice: Prosperity, chances, rights and responsibilities should be divided in between the nations, different social groups in a fairway. The needs of the poor and discriminated people’s needs has to be put in the consideration. Similar fair sharing should be made in between existing generation and future generation. - Cautions: If we are not sure about environmental results of our behaviors we should take precautions. Because the environmental problems are global the precautions has to be taken inconsideration of social responsibilities. - Holistic Thinking: Environmental problems includes unnumbered factors and while solving these problems all these factors and stake holders should be taken in to consideration. - Social Dimension: Educational activities should be informed about the sustainable development aspects to increase for their and next generation’s living standards. - Economical Dimension: Every resources on earth is limited. That is why they should be used efficiently and in a way that does not destruct the nature. Fair distribution of the resources is also an other aspect should be taken in to consideration. - Environmental Dimension: Every natural resources, whether or not it is recyclable, should be used in a way that ensures the continuity of resources. Sustainable development is significant factor for economies. These strategies should considered in the economy. Textile sector has great place in the Turkish economy than we can give some information regarding textile sector in Turkey. Turkish Textile Sector Turkish textile and apparel industry is a very dynamic one, in fact it is the most dynamic industry in Turkey. Becouse of having the advantage of producing the raw materials required by the industry textiles and apparels are always going to be one of the most important industries for the Turkish economy (Akalın, 2001). As in many other developing countries, the textile and clothing industries have played an important role in the 762 �process of industrialization of Turkey. Textile sectors are now the driving force in the Turkish export industry, and they have become one of the key players in the world over the years. (Çukul, 2008) We can evaluate Turkish economy in terms of GDP, employment and exports. The share of this sector in the country’s GDP is more than 10 % , share in the total employment is around 10 %. There are about 40 thousand manufacturing companies and around 2 million employees in the sector. Turkish textile and clothing exports reached to US$ 20 billion in 2008. With this amount, it had a share of 22% in total exports of Turkey (ĐGĐAD, 2009) . Turkish textile industry uses modern technology. Existance of a well-developed textile finishing industry in Turkey makes also possible production and marketing of highly value added fashionable and quality production. The main items are knitted fabrics, cotton woven fabrics, woven fabrics of synthetic filament yarns, bed sheets and bags-sacks for packaging. Main advanteges of Turkish textile industry in production and supply of raw materials: (ITKIP, 2010) - Reachness in basic raw materials, - Geographical proximity to main markets, especially European markets, - Short logistics period due to geographical proximity, - Qualified and well-educated labor force - Liberal trade policies - Well-developed textile finishing industry - Giving importance to quality, environment and human health, sensitivity on working conditions of workers - Customs Union agreement with the European Union and free trade agreements with many other countries Turkey as being one of the most prominent textile and clothing producers in the world, now, has the production capacity to meet almost all the raw material needs of clothing industry. Some part of cotton and artificial and synthetic fibers needed by the industry are met by means of importation. Turkey has also gained valuable experience in fabric design and it is started to present its special designs with fashion shows in prominent markets. Turkish textile industrialists most of whom has created their own trademark together with the patent rights, provide the most important foreign home textile and clothing companies with their fabric. (ITKIP, 2010) Turkey is currently the second larger exporter of textile to the European Union following China. It has the largest production capacity in the EU and the fourth largest in the world. Since the EU and U.S are major markets for Turkish textile and clothing products, it is necessary to explore the competitive position of Turkish products in these markets, and they have to be prepared to the attack of its competitor such as China, India and other Asian countries. There is no doubt that China will be the largest force in the global textile sector. According to a forecast by World Bank, China is likely to raise its current share of 20 % in the world textile market to 50 % in recent years. (Çukul, 2008) Many pattern design competitions that make important contributions to development of fabric design in Turkey are organized by different institutions leading to emergence of young designers and creation of product diversity. Turkey takes part in many famous international fairs in textile sector, international textile fairs were organized within Turkey and Turkey’s potential is shown successfully all over the world. (ITKIP, 2010) Textile sector is significant for the Turkish economy. So doing a research for textile sector is necessary. We can evaluate the sector with performance, efficiency and effectiveness values. In this study it is practicing Data Envelopment Analyses (DEA) for finding efficiency rates. Data Envelopment Analysis DEA is an extension of Farrell's (1957) idea of linking the computation of technical efficiency with production frontiers. The first DEA model was developed by Charnes Cooper and Rhodes (1978) (CCR). The CCR model is a fractional programming model, which measures the relative technical efficiency of a firm by calculating the ratio of weighted sum of its outputs to the weighted sum of its inputs. The fractional program is run for each firm to determine the set of input-output weights, which maximizes the efficiency of that firm subject to the condition that no firm can have a relative efficiency score greater than unity for that set of weights. Thus, the DEA model calculates a unique set of factor weights for each firm. The set of weights has the following characteristics: (Kabnurkar, 2001) - It maximizes the efficiency of the firm for which it is calculated and - It is feasible for all firms. Since DEA does not incorporate price information in the efficiency measure, it is appropriate for not for profit organizations where price information is not available. These not for profit organizations are referred to as Decision-Making Units (DMUs) by Charnes Cooper and Rhodes (1978). Since the efficiency of each DMU is 763 �calculated in relation to all other DMUs and using actual observed input-output values, the efficiency calculated in DEA is called relative efficiency. Charnes, Cooper and Seiford (1994) define DEA as "DEA produces a piecewise empirical extremal production surface which in economic terms represents the revealed best-practice production frontier – the maximum output empirically obtainable from any DMU in the observed population, given its level of inputs." In addition to calculating the efficiency scores, DEA also determines the level and amount of inefficiency for each of the inputs and outputs. The amount of inefficiency is determined by comparison with a convex combination of two or more DMUs, which lie on the efficient frontier, utilize the same level of inputs, and produce the same or higher level of outputs. The aim of DEA is to quantify the distance to the efficient frontier for every DMU. The measure of performance is expressed in the form of efficiency score. After the evaluation of the relative efficiency of the present set of units, the analysis shows how inputs and outputs have to be changed in order to maximize the efficiency of the target DMU. DEA suggest the bencmark for each inefficient DMU at the level of its individual mix of inputs and outputs (Mantri, 2008) DEA is a typical statistical approach and characterized as a central tendency approach. It evaluates producers relative to an average producer. In contrast DEA campares each producer with only the “best” producers. A fundamental assumption behind this method is that if a given producer, A, is capable of producing Y(A) units of output with X(A) inputs, then other producers should also be able to do the same if they were to operate efficiently. Similarly, if producer B is capable of the same production schedule. Producers A, B, and others can then be combined to form a composite producer with composite inputs and composite outputs. Since this composite producer does not necessarily exist, it is typically called a virtual producer. The heart of the analysis lies in finding the “best” virtual producer for each real producer. If the virtual producer is beter than the orginal producer by either making more output with the same input or making the same output with less input then the orginal producer is inefficient. The subtleties of DEA are introduced in the various ways that producers A and B can be scarld up or down and combined. (Cornuejols & Trick, 1998) In this study DEA practiced. Aims and methods of the research is as follows. Aims and Methods of Research In this study it is tried to be evaluated the textile sector firms financial efficiencies that are quoted to ISE. In the study DEA method is used. The aim of the study is to investigate financial efficiency and effectiveness of leading Turkish textile sector companies. Economical dimension of sustainable development includes fair distiribution of the resources, avoidance of unnecessary usage of resources and efficient usage of resources. Financial resources are also significant inputs of companies and they should be used efficiently. The steps while practicing DEA can be listed as follows; - Selection of decision making units, - Determination of inputs and output sets - Relative efficiency measurement by DEA o Availability and reliability of the data o Relative efficiency measurement o Efficiency degree-efficiency limits o Evaluation of the results In first step of the study decision making units are selected. For the study balance sheets and income statements that are belong to the firms gathered from the ISE. These data includes the time period in between 2004 and 2008. Decision making units which were the subject of the study is listed in Table 1. BOSSA Bossa Ticaret ve Sanayi Đşletmeleri T.A.Ş. CEYLAN Ceylan Giyim Sanayi ve Ticaret A.Ş. DERĐMOD Derimod Konfeksiyon Ayakkabı Deri Sanayi ve Ticaret A.Ş. EDĐP Edip Đplik Sanayi ve Ticaret A.Ş. ESEM Esem Spor Giyim Sanayi ve Ticaret A.Ş. KARTEKS Karsu Tekstil Sanayii ve Ticaret A.Ş. LUKS Lüks Kadife Ticaret ve Sanayi A.Ş. OKAN Okan Tekstil Sanayi ve Ticaret A.Ş. SASA Advansa Sasa Polyester Sanayi A.Ş. VAKKO Vakko Tekstil ve Hazır Giyim Sanayi Đşletmeleri A.Ş. YATAS Yataş Yatak ve Yorgan Sanayi ve Ticaret A.Ş. YUNSA Yünsa Yünlü Sanayi ve Ticaret A.Ş. 764 �Table 1: Decision Making Units That Were The Subject of the Study Second step of the study was the determination of input and output sets. These are used for measurement of financial efficiency of textile firms. Input and Output sets which were the subjects of the study is listed in Table 2. INPUT Short-Term Dept Long-Term Dept OUTPUT Sales Revenues Non-Operating Income Capital Stock Table 2: Input and Output Data Sets Used in Research These set of input and output units are used to determine the financial efficiency of the textile sector firms. For this study textile sector inputs were determined as: Short Term Debts, Long Term Debts and Capital Stock. Where as the outputs were: Sales Revenues and Non Operating Income. Analysing the Model In this study, it is perefered to used the data gathered from textile firms that are belong to ISE, because of the availability and reliability of data. For the analysis DEAP Version 2.1 is used for processing mathematical data. Inputs of the textile sector are considered as manageable data. So in the analysis input focused method is used. Lack of free market conditions prevented the firms to identify the financial problems that causes difficulties in reaching optimum levels. That is why variable income scaled efficiency model is used for solution. In this search 5 different solutions are generated by linear programming. There are three different factors are used to describe the efficiency levels; Constant Income Technical Efficiency, Variable Income Technical Efficiency and Scale Efficiency. Here technical efficiency could be described as every input’s impact on output. Whereas scale efficiency describes the aggregate impact of all inputs to compound outputs. Scale Efficiency is measured with dividing Constant Income Technical Efficiency by Variable Income Technical Efficiency. After processing the data, DEA efficiency results, from the year 2004 and 2008, belong to the decision making units are determined and listed on the Table 3 as below. 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,408 1 1 1 1 DERĐMOD 1 1 1 1 0,863 EDĐP 0,859 0,9 0,325 0,245 0,045 ESEM 1 1 0,147 0,068 0,087 KARTEKS 0,613 0,752 0,658 0,818 0,640 LUKS 1 1 1 1 0,535 OKAN 1 1 1 1 0,774 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,556 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,858 0,856 0,756 0,764 0,653 Table 3: Constant Income Technical Efficiency (2004-2008) 765 �There is a reduction in Constant Income Technical Efficiency in between 2004 and 2008. This reduction could be interpreted as Chinese factor in the international trade. Regarding to Turkish textile sector Variable Income Technical Efficiency values are as below. 2004 2005 2006 2007 2008 BOSSA 1 1 1 1 1 CEYLAN 0,435 1 1 1 1 DERĐMOD 1 1 1 1 1 EDĐP 0,902 1 0,560 0,246 0,047 ESEM 1 1 0,153 0,087 0,129 KARTEKS 0,671 1 1 0,863 0,676 LUKS 1 1 1 1 0,553 OKAN 1 1 1 1 0,780 SASA 1 1 1 1 1 VAKKO 1 1 1 1 1 YATAS 1 1 1 1 0,791 YUNSA 1 1 1 1 1 ORTALAMA 0,917 1 0,893 0,850 0,748 Table 4: Variable Income Technical Efficiency (2004-2008) In terms of Variable Income Technical Efficiency there is a steady decrease in averages from 20062008. Large and famous firms like BOSSA, VAKKO, SASA, YÜNSA are still keeping their high stakes in the market. Regarding to Turkish textile sector Scale Efficiency values are as below. 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,939 1 1 1 1 DERĐMOD 1 1 1 1 0,863 EDĐP 0,953 0,9 0,580 0,997 0,974 ESEM 1 1 0,960 0,778 0,675 KARTEKS 0,914 0,752 0,658 0,948 0,946 LUKS 1 1 1 1 0,967 OKAN 1 1 1 1 0,993 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,703 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,935 0,856 0,845 0,897 0,871 Table 5: Scale Efficiency (2004-2008) As you can see from the Table 5. there is a steady decrease in the values of scale efficiencies in between 2004 and 2008. Internal and external results are also indicates that leading Turkish textile companies efficiencies 766 �are decreased. In addition to Chinese factor in textile sector, structural deficiencies in the Turkish textile sector, deficiencies in branding, financial problems and deficiencies in marketing would be other reasons for the reduction. Conclusion Textile sector plays a crucial role in the Turkish economy. Sector seriously affected from the several threads: Chinese factor which criticly reduced the competitiveness of the Turkish textile sector, domestic structural deficiencies in textile sector and reductions in domestic cotton production because of the market forces. Deficiencies in investment climate lead the textile investers to invest more competitive countries in terms of wages, input costs ( like electricity etc.) gradual weaknesses of the textile sector in Turkey is a serious problem. Because textile sector can be considered as engine of the economy. It used to provide considerable amount of employment, export revenue, value add, tax revenue. Result of the study clearly indicates that Turkish textile companies can not efficiently uses the financial resources they have. Government interventions would be as suggestion for more efficient sector for instance tax reductions, direct and indirect financial supports, lower currency policy and improvements in investing climate. References Akalın, M. (2001). Insight into The Turkish Textile and Apparel Industry, Electronic Journal of Textile. Volume: 1, No: 1, 5-6. Charnes, A., W.W. Cooper, and E. Rhodes. (1978). Measuring the eficiency of decision making units, European Journal of Operations Research: 429-444. Charnes, A., W.W. Cooper, A.Y. Lewin, and L.M. Seiford. (1994). Data Envelopment Analysis: Theory, Methodology, and Applications. Boston: Kluwer Academic Publishers., 221-222 Cornuejols G. & Trick M. (1998). Quantitative Methods for the Management Sciences, Graduate School of Industrial Administration Carnegie Mellon University, Pittsburgh, PA 15213 USA, 345-351 Çukul D. (2008). Competıtıve Aspects Of Turkısh And Chınese Textıle And Clothıng Industrıes, 8th Global Conference on Business & Economics, 1-9 Dalal-Clayton B. (2000). What Is Sustaınable Development ?, Strategies for National Sustainable Development 1-2, www.nssd.net/otherdocuments/sustdev2.doc Ekinci M.B. (2007). Sanayileşme Stratejileri Çerçevesinde Çevre Boyutlu Sürdürülebilir Kalkınma Anlayışına Đlişkin Değerlendirmeler, Sosyal Siyaset Konferansları Kitap 50, 979-981 Farrell, M.J. (1957). The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, 254290 Harris J.M. (2000). Basic Principles of Sustainable Development, Global Development And Envıronment Instıtute Workıng Paper 00-04, 1-6 ĐGĐAD (Đktisadi Giriğim ve Đş Ahlakı Derneği). (2009). Tekstil Sektörü Değerlendirme Raporu, 1-3 Kabnurkar A. (2001). Mathematıcal Modelıng For Data Envelopment Analysıs Wıth Fuzzy Restrıctıons On Weıghts, Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Masters of Science in Industrial and Systems Engineering, 3134 ITKIP Đstanbul Tekstil ve Konfeksiyon Đhracatçılar Birliği. (2010). Turkish Textile Industry,1-8 www.itkib.org.tr/english/about/sectors/textile/textile_info.pdf 767 �Mantri J.K. (2008). Research Methodology on Data Envelopment Analysis DEA, Universal Publisher, Boca Raton, Florida USA, 15-16 Özyol A. (2007). Sürdürülebilir Kalkınma, Hydra Uluslar arası Proje Danışmanlık A.Ş. Yayını, 2-5 768 � 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. 626 Title A name given to the resource Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Author Author ÖZGÜR, Ersan Abstract A summary of the resource. Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today’s decision makers has to be able to think and plan the futures resources for not to danger future’s generations. In this perspective sustainable development policies can be considered as a solution for the next generation’s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. 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/e53c7223c9edde4a9c869f6f001212b5.pdf a3a62afba0d0b17a66f5c59bd35d4e19 PDF Text Text 2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Ersan ÖZGÜR Assistant Prof. Dr.,Afyon Kocatepe University Sandıklı M.Y.O. ersanozgur@yahoo.com Abstract: Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today‘s decision makers has to be able to think and plan the futures resources for not to danger future‘s generations. In this perspective sustainable development policies can be considered as a solution for the next generation‘s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. Introduction Nowadays, industrialized countries have recognized that their economical growth has a limit. At this point they also recognized that even though there was an economic growth there are also limits for economic development. Developed countries, are taking procoutions against the risks in relation to sustainablility. However developing countries has not been recognized that the importance of the subject. On the other hand it can be assumed that there are limited activities in relation to the subject. Contries are trying to impliment new sustainable development strategies. This could be as a solution for to reach their targets. In this perspective Turkey as a developing country has to set up similar development strategies and plans. Sustainable development has a direct relationship with the development of reel sector. Textile sector is a high significant sector for Turkish economy. Turkish textile sector is dinamic and has a high potantial for the growth. Espacialy after 1980‘s with establishment of open economic policies exportation is increased and textile sector became the engine of the economy. Cotton production in Turkey has played a crucial role in the development of the economy. In consideration of globalization which increased the competition, assesment of effiency and effectiveness has became more important for the decision makers. Textile sector is contributing to the Turkish economy in terms of value add, employment and exportation. It is suggested that for sustainablity of textile sector performance measurement of efficiency and effectiveness of the sector has became more significant. Sustanable development, productivity and efficiency are related consepts. Productivity can be described as obtaining an output by using least input. Which means efficient uses of limited resouces. Performance can be considered as degree of success with in certain period of time. Managers can not /should not take desicions without having performance information. Hence it might be suggested that using performance measuring methods are significant for decision makers. One of the methods used for measuring performance is Data Enveloping Analyses. Sustainable Development The structures of imperial and colonial power which dominated the world in the nineteenth and early twentieth centuries made little provision for economic and social advance in what we now call the developing world. Colonial regions functioned primarily to supply imperial powers with raw materials and cheap labor – including slave labor as late as the mid-nineteenth century (Harris, 2000). Industrialization is an important target for the countries, however, there are some problems they face in this process inevitably. Environmental problem is one of them. Although it has some negative effects on environment, industrialization may not be abandoned. But it is obvious that some necessary measures should be taken for a sustainable development.(Ekinci, 2007) 694 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Whilst earlier literature discussed a wide range of issues around the emerging concept of sustainable development, the following statement from the World Conservation Strategy (IUCN/WWF/UNEP, 1980) appears to be the first actual attempt to define sustainable development: "For development to be sustainable, it must take account of social and ecological factors, as well as economic ones; of the living and non-living resource base; and of the long-term as well as the short-term advantages and disadvantages of alternative action" The World Conservation Strategy was frequently criticised for being concerned mainly with ecological sustainability rather than sustainable development per se. The most universally quoted definition is that produced in 1987 by the World Commission on Environment and Development (WCED), otherwise known as the Brundtland Commission (after its Chairperson, Gro Harlem Brundtland, Prime Minister of Norway): "Economic and social development that meets the needs of the current generation without undermining the ability of future generations to meet their own needs". (Dalal-Clayton, 2000) In the extensive discussion and use of the concept since then, there has generally been a recognition of three aspects of sustainable development:(Harris, 2000) - Economic: An economically sustainable system must be able to produce goods and services on a continuing basis, to maintain manageable levels of government andexternal debt, and to avoid extreme sectoral imbalances which damage agricultural or industrial production. - Environmental: An environmentally sustainable system must maintain a stable resource base, avoiding over-exploitation of renewable resource systems or environmental sink functions, and depleting nonrenewable resources only to the extent that investment is made in adequate substitutes. This includes maintenance of biodiversity, atmospheric stability, and other ecosystem functions not ordinarily classed as economic resources. - Social: A socially sustainable system must achieve distributional equity, adequate provision of social services including health and education, gender equity, and political accountability and participation. With these aspects sustainable development has got some strategies. Sustainable development strategies can be summarized under 9 headings: (Özyol, 2007) - Environment: Nature has its own value. None of the creature should not abuse the nature for their own needs. - The Future: While satisfying our needs we should think and take care of next generations needs and we should not forget that we have to live a world where the next generations could be able to satisfy their own needs. - Living Standards: We should not forget that living standarts of the people is not rely on materialistic needs but also it relies on social, cultural, ethical and spiritual needs. - Justice: Prosperity, chances, rights and responsibilities should be divided in between the nations, different social groups in a fairway. The needs of the poor and discriminated people‘s needs has to be put in the consideration. Similar fair sharing should be made in between existing generation and future generation. - Cautions: If we are not sure about environmental results of our behaviors we should take precautions. Because the environmental problems are global the precautions has to be taken inconsideration of social responsibilities. - Holistic Thinking: Environmental problems includes unnumbered factors and while solving these problems all these factors and stake holders should be taken in to consideration. - Social Dimension: Educational activities should be informed about the sustainable development aspects to increase for their and next generation‘s living standards. - Economical Dimension: Every resources on earth is limited. That is why they should be used efficiently and in a way that does not destruct the nature. Fair distribution of the resources is also an other aspect should be taken in to consideration. - Environmental Dimension: Every natural resources, whether or not it is recyclable, should be used in a way that ensures the continuity of resources. Sustainable development is significant factor for economies. These strategies should considered in the economy. Textile sector has great place in the Turkish economy than we can give some information regarding textile sector in Turkey. Turkish Textile Sector Turkish textile and apparel industry is a very dynamic one, in fact it is the most dynamic industry in Turkey. Becouse of having the advantage of producing the raw materials required by the industry textiles and apparels are always going to be one of the most important industries for the Turkish economy (Akalın, 2001). As in many other 695 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo developing countries, the textile and clothing industries have played an important role in the process of industrialization of Turkey. Textile sectors are now the driving force in the Turkish export industry, and they have become one of the key players in the world over the years. (Çukul, 2008) We can evaluate Turkish economy in terms of GDP, employment and exports. The share of this sector in the country‘s GDP is more than 10 % , share in the total employment is around 10 %. There are about 40 thousand manufacturing companies and around 2 million employees in the sector. Turkish textile and clothing exports reached to US$ 20 billion in 2008. With this amount, it had a share of 22% in total exports of Turkey (ĠGĠAD, 2009) . Turkish textile industry uses modern technology. Existance of a well-developed textile finishing industry in Turkey makes also possible production and marketing of highly value added fashionable and quality production. The main items are knitted fabrics, cotton woven fabrics, woven fabrics of synthetic filament yarns, bed sheets and bagssacks for packaging. Main advanteges of Turkish textile industry in production and supply of raw materials: (ITKIP, 2010) - Reachness in basic raw materials, - Geographical proximity to main markets, especially European markets, - Short logistics period due to geographical proximity, - Qualified and well-educated labor force - Liberal trade policies - Well-developed textile finishing industry - Giving importance to quality, environment and human health, sensitivity on working conditions of workers - Customs Union agreement with the European Union and free trade agreements with many other countries Turkey as being one of the most prominent textile and clothing producers in the world, now, has the production capacity to meet almost all the raw material needs of clothing industry. Some part of cotton and artificial and synthetic fibers needed by the industry are met by means of importation. Turkey has also gained valuable experience in fabric design and it is started to present its special designs with fashion shows in prominent markets. Turkish textile industrialists most of whom has created their own trademark together with the patent rights, provide the most important foreign home textile and clothing companies with their fabric. (ITKIP, 2010) Turkey is currently the second larger exporter of textile to the European Union following China. It has the largest production capacity in the EU and the fourth largest in the world. Since the EU and U.S are major markets for Turkish textile and clothing products, it is necessary to explore the competitive position of Turkish products in these markets, and they have to be prepared to the attack of its competitor such as China, India and other Asian countries. There is no doubt that China will be the largest force in the global textile sector. According to a forecast by World Bank, China is likely to raise its current share of 20 % in the world textile market to 50 % in recent years. (Çukul, 2008) Many pattern design competitions that make important contributions to development of fabric design in Turkey are organized by different institutions leading to emergence of young designers and creation of product diversity. Turkey takes part in many famous international fairs in textile sector, international textile fairs were organized within Turkey and Turkey‘s potential is shown successfully all over the world. (ITKIP, 2010) Textile sector is significant for the Turkish economy. So doing a research for textile sector is necessary. We can evaluate the sector with performance, efficiency and effectiveness values. In this study it is practicing Data Envelopment Analyses (DEA) for finding efficiency rates. Data Envelopment Analysis DEA is an extension of Farrell's (1957) idea of linking the computation of technical efficiency with production frontiers. The first DEA model was developed by Charnes Cooper and Rhodes (1978) (CCR). The CCR model is a fractional programming model, which measures the relative technical efficiency of a firm by calculating the ratio of weighted sum of its outputs to the weighted sum of its inputs. The fractional program is run for each firm to determine the set of input-output weights, which maximizes the efficiency of that firm subject to the condition that no firm can have a relative efficiency score greater than unity for that set of weights. Thus, the DEA model calculates a unique set of factor weights for each firm. The set of weights has the following characteristics: (Kabnurkar, 2001) - It maximizes the efficiency of the firm for which it is calculated and - It is feasible for all firms. Since DEA does not incorporate price information in the efficiency measure, it is appropriate for not for profit organizations where price information is not available. These not for profit organizations are referred to as Decision-Making Units (DMUs) by Charnes Cooper and Rhodes (1978). Since the efficiency of each DMU is 696 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo calculated in relation to all other DMUs and using actual observed input-output values, the efficiency calculated in DEA is called relative efficiency. Charnes, Cooper and Seiford (1994) define DEA as "DEA produces a piecewise empirical extremal production surface which in economic terms represents the revealed best-practice production frontier – the maximum output empirically obtainable from any DMU in the observed population, given its level of inputs." In addition to calculating the efficiency scores, DEA also determines the level and amount of inefficiency for each of the inputs and outputs. The amount of inefficiency is determined by comparison with a convex combination of two or more DMUs, which lie on the efficient frontier, utilize the same level of inputs, and produce the same or higher level of outputs. The aim of DEA is to quantify the distance to the efficient frontier for every DMU. The measure of performance is expressed in the form of efficiency score. After the evaluation of the relative efficiency of the present set of units, the analysis shows how inputs and outputs have to be changed in order to maximize the efficiency of the target DMU. DEA suggest the bencmark for each inefficient DMU at the level of its individual mix of inputs and outputs (Mantri, 2008) DEA is a typical statistical approach and characterized as a central tendency approach. It evaluates producers relative to an average producer. In contrast DEA campares each producer with only the ―best‖ producers. A fundamental assumption behind this method is that if a given producer, A, is capable of producing Y(A) units of output with X(A) inputs, then other producers should also be able to do the same if they were to operate efficiently. Similarly, if producer B is capable of the same production schedule. Producers A, B, and others can then be combined to form a composite producer with composite inputs and composite outputs. Since this composite producer does not necessarily exist, it is typically called a virtual producer. The heart of the analysis lies in finding the ―best‖ virtual producer for each real producer. If the virtual producer is beter than the orginal producer by either making more output with the same input or making the same output with less input then the orginal producer is inefficient. The subtleties of DEA are introduced in the various ways that producers A and B can be scarld up or down and combined. (Cornuejols & Trick, 1998) In this study DEA practiced. Aims and methods of the research is as follows. Aims and Methods of Research In this study it is tried to be evaluated the textile sector firms financial efficiencies that are quoted to ISE. In the study DEA method is used. The aim of the study is to investigate financial efficiency and effectiveness of leading Turkish textile sector companies. Economical dimension of sustainable development includes fair distiribution of the resources, avoidance of unnecessary usage of resources and efficient usage of resources. Financial resources are also significant inputs of companies and they should be used efficiently. The steps while practicing DEA can be listed as follows; - Selection of decision making units, - Determination of inputs and output sets - Relative efficiency measurement by DEA o Availability and reliability of the data o Relative efficiency measurement o Efficiency degree-efficiency limits o Evaluation of the results In first step of the study decision making units are selected. For the study balance sheets and income statements that are belong to the firms gathered from the ISE. These data includes the time period in between 2004 and 2008. Decision making units which were the subject of the study is listed in Table 1. 697 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo BOSSA Bossa Ticaret ve Sanayi ĠĢletmeleri T.A.ġ. CEYLAN Ceylan Giyim Sanayi ve Ticaret A.ġ. LUKS Lüks Kadife Ticaret ve Sanayi A.ġ. OKAN Okan Tekstil Sanayi ve Ticaret A.ġ. DERĠMOD SASA Derimod Konfeksiyon Ayakkabı Deri Sanayi ve Advansa Sasa Polyester Sanayi A.ġ. Ticaret A.ġ. EDĠP Edip Ġplik Sanayi ve Ticaret A.ġ. ESEM Esem Spor Giyim Sanayi ve Ticaret A.ġ. KARTEKS Karsu Tekstil Sanayii ve Ticaret A.ġ. VAKKO Vakko Tekstil ve Hazır Giyim Sanayi ĠĢletmeleri A.ġ. YATAS YataĢ Yatak ve Yorgan Sanayi ve Ticaret A.ġ. YUNSA Yünsa Yünlü Sanayi ve Ticaret A.ġ. Table 1: Decision Making Units That Were The Subject of the Study Second step of the study was the determination of input and output sets. These are used for measurement of financial efficiency of textile firms. Input and Output sets which were the subjects of the study is listed in Table 2. INPUT Short-Term Dept Long-Term Dept OUTPUT Sales Revenues Non-Operating Income Capital Stock Table 2: Input and Output Data Sets Used in Research These set of input and output units are used to determine the financial efficiency of the textile sector firms. For this study textile sector inputs were determined as: Short Term Debts, Long Term Debts and Capital Stock. Where as the outputs were: Sales Revenues and Non Operating Income. Analysing the Model In this study, it is perefered to used the data gathered from textile firms that are belong to ISE, because of the availability and reliability of data. For the analysis DEAP Version 2.1 is used for processing mathematical data. Inputs of the textile sector are considered as manageable data. So in the analysis input focused method is used. Lack of free market conditions prevented the firms to identify the financial problems that causes difficulties in reaching optimum levels. That is why variable income scaled efficiency model is used for solution. In this search 5 different solutions are generated by linear programming. There are three different factors are used to describe the efficiency levels; Constant Income Technical Efficiency, Variable Income Technical Efficiency and Scale Efficiency. Here technical efficiency could be described as every input‘s impact on output. Whereas scale efficiency describes the aggregate impact of all inputs to compound outputs. Scale Efficiency is measured with dividing Constant Income Technical Efficiency by Variable Income Technical Efficiency. After processing the data, DEA efficiency results, from the year 2004 and 2008, belong to the decision making units are determined and listed on the Table 3 as below. 698 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,408 1 1 1 1 DERĠMOD 1 1 1 1 0,863 EDĠP 0,859 0,9 0,325 0,245 0,045 ESEM 1 1 0,147 0,068 0,087 KARTEKS 0,613 0,752 0,658 0,818 0,640 LUKS 1 1 1 1 0,535 OKAN 1 1 1 1 0,774 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,556 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,858 0,856 0,756 0,764 0,653 Table 3: Constant Income Technical Efficiency (2004-2008) There is a reduction in Constant Income Technical Efficiency in between 2004 and 2008. This reduction could be interpreted as Chinese factor in the international trade. Regarding to Turkish textile sector Variable Income Technical Efficiency values are as below. 2004 2005 2006 2007 2008 BOSSA 1 1 1 1 1 CEYLAN 0,435 1 1 1 1 DERĠMOD 1 1 1 1 1 EDĠP 0,902 1 0,560 0,246 0,047 ESEM 1 1 0,153 0,087 0,129 KARTEKS 0,671 1 1 0,863 0,676 LUKS 1 1 1 1 0,553 OKAN 1 1 1 1 0,780 SASA 1 1 1 1 1 VAKKO 1 1 1 1 1 YATAS 1 1 1 1 0,791 YUNSA 1 1 1 1 1 ORTALAMA 0,917 1 0,893 0,850 0,748 Table 4: Variable Income Technical Efficiency (2004-2008) In terms of Variable Income Technical Efficiency there is a steady decrease in averages from 2006-2008. Large and famous firms like BOSSA, VAKKO, SASA, YÜNSA are still keeping their high stakes in the market. Regarding to Turkish textile sector Scale Efficiency values are as below. 699 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,939 1 1 1 1 DERĠMOD 1 1 1 1 0,863 EDĠP 0,953 0,9 0,580 0,997 0,974 ESEM 1 1 0,960 0,778 0,675 KARTEKS 0,914 0,752 0,658 0,948 0,946 LUKS 1 1 1 1 0,967 OKAN 1 1 1 1 0,993 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,703 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,935 0,856 0,845 0,897 0,871 Table 5: Scale Efficiency (2004-2008) As you can see from the Table 5. there is a steady decrease in the values of scale efficiencies in between 2004 and 2008. Internal and external results are also indicates that leading Turkish textile companies efficiencies are decreased. In addition to Chinese factor in textile sector, structural deficiencies in the Turkish textile sector, deficiencies in branding, financial problems and deficiencies in marketing would be other reasons for the reduction. Conclusion Textile sector plays a crucial role in the Turkish economy. Sector seriously affected from the several threads: Chinese factor which criticly reduced the competitiveness of the Turkish textile sector, domestic structural deficiencies in textile sector and reductions in domestic cotton production because of the market forces. Deficiencies in investment climate lead the textile investers to invest more competitive countries in terms of wages, input costs ( like electricity etc.) gradual weaknesses of the textile sector in Turkey is a serious problem. Because textile sector can be considered as engine of the economy. It used to provide considerable amount of employment, export revenue, value add, tax revenue. Result of the study clearly indicates that Turkish textile companies can not efficiently uses the financial resources they have. Government interventions would be as suggestion for more efficient sector for instance tax reductions, direct and indirect financial supports, lower currency policy and improvements in investing climate. References Akalın, M. (2001). Insight into The Turkish Textile and Apparel Industry, Electronic Journal of Textile. Volume: 1, No: 1, 5-6. Charnes, A., W.W. Cooper, and E. Rhodes. (1978). Measuring the eficiency of decision making units, European Journal of Operations Research: 429-444. Charnes, A., W.W. Cooper, A.Y. Lewin, and L.M. Seiford. (1994). Data Envelopment Analysis: Theory, Methodology, and Applications. Boston: Kluwer Academic Publishers., 221-222 Cornuejols G. & Trick M. (1998). Quantitative Methods for the Management Sciences, Graduate School of Industrial Administration Carnegie Mellon University, Pittsburgh, PA 15213 USA, 345-351 Çukul D. (2008). Competıtıve Aspects Of Turkısh And Chınese Textıle And Clothıng Industrıes, 8th Global Conference on Business & Economics, 1-9 700 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Dalal-Clayton B. (2000). What Is Sustaınable Development ?, Strategies for National Sustainable Development 1-2, www.nssd.net/otherdocuments/sustdev2.doc Ekinci M.B. (2007). SanayileĢme Stratejileri Çerçevesinde Çevre Boyutlu Sürdürülebilir Kalkınma AnlayıĢına ĠliĢkin Değerlendirmeler, Sosyal Siyaset Konferansları Kitap 50, 979-981 Farrell, M.J. (1957). The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, 254-290 Harris J.M. (2000). Basic Principles of Sustainable Development, Global Development And Envıronment Instıtute Workıng Paper 00-04, 1-6 ĠGĠAD (Ġktisadi Giriğim ve ĠĢ Ahlakı Derneği). (2009). Tekstil Sektörü Değerlendirme Raporu, 1-3 Kabnurkar A. (2001). Mathematıcal Modelıng For Data Envelopment Analysıs Wıth Fuzzy Restrıctıons On Weıghts, Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Masters of Science in Industrial and Systems Engineering, 31-34 ITKIP Ġstanbul Tekstil ve Konfeksiyon Ġhracatçılar www.itkib.org.tr/english/about/sectors/textile/textile_info.pdf Birliği. (2010). Turkish Textile Industry,1-8 Mantri J.K. (2008). Research Methodology on Data Envelopment Analysis DEA, Universal Publisher, Boca Raton, Florida USA, 15-16 Özyol A. (2007). Sürdürülebilir Kalkınma, Hydra Uluslar arası Proje DanıĢmanlık A.ġ. Yayını, 2-5 701 � 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. 310 Title A name given to the resource Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Author Author ÖZGÜR, Ersan Abstract A summary of the resource. Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today‘s decision makers has to be able to think and plan the futures resources for not to danger future‘s generations. In this perspective sustainable development policies can be considered as a solution for the next generation‘s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. Date A point or period of time associated with an event in the lifecycle of the resource 2010-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory https://omeka.ibu.edu.ba/files/original/c66e3115a738a313a4b2ece7c93d6af5.pdf a3a62afba0d0b17a66f5c59bd35d4e19 PDF Text Text 2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Ersan ÖZGÜR Assistant Prof. Dr.,Afyon Kocatepe University Sandıklı M.Y.O. ersanozgur@yahoo.com Abstract: Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today‘s decision makers has to be able to think and plan the futures resources for not to danger future‘s generations. In this perspective sustainable development policies can be considered as a solution for the next generation‘s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. Introduction Nowadays, industrialized countries have recognized that their economical growth has a limit. At this point they also recognized that even though there was an economic growth there are also limits for economic development. Developed countries, are taking procoutions against the risks in relation to sustainablility. However developing countries has not been recognized that the importance of the subject. On the other hand it can be assumed that there are limited activities in relation to the subject. Contries are trying to impliment new sustainable development strategies. This could be as a solution for to reach their targets. In this perspective Turkey as a developing country has to set up similar development strategies and plans. Sustainable development has a direct relationship with the development of reel sector. Textile sector is a high significant sector for Turkish economy. Turkish textile sector is dinamic and has a high potantial for the growth. Espacialy after 1980‘s with establishment of open economic policies exportation is increased and textile sector became the engine of the economy. Cotton production in Turkey has played a crucial role in the development of the economy. In consideration of globalization which increased the competition, assesment of effiency and effectiveness has became more important for the decision makers. Textile sector is contributing to the Turkish economy in terms of value add, employment and exportation. It is suggested that for sustainablity of textile sector performance measurement of efficiency and effectiveness of the sector has became more significant. Sustanable development, productivity and efficiency are related consepts. Productivity can be described as obtaining an output by using least input. Which means efficient uses of limited resouces. Performance can be considered as degree of success with in certain period of time. Managers can not /should not take desicions without having performance information. Hence it might be suggested that using performance measuring methods are significant for decision makers. One of the methods used for measuring performance is Data Enveloping Analyses. Sustainable Development The structures of imperial and colonial power which dominated the world in the nineteenth and early twentieth centuries made little provision for economic and social advance in what we now call the developing world. Colonial regions functioned primarily to supply imperial powers with raw materials and cheap labor – including slave labor as late as the mid-nineteenth century (Harris, 2000). Industrialization is an important target for the countries, however, there are some problems they face in this process inevitably. Environmental problem is one of them. Although it has some negative effects on environment, industrialization may not be abandoned. But it is obvious that some necessary measures should be taken for a sustainable development.(Ekinci, 2007) 694 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Whilst earlier literature discussed a wide range of issues around the emerging concept of sustainable development, the following statement from the World Conservation Strategy (IUCN/WWF/UNEP, 1980) appears to be the first actual attempt to define sustainable development: "For development to be sustainable, it must take account of social and ecological factors, as well as economic ones; of the living and non-living resource base; and of the long-term as well as the short-term advantages and disadvantages of alternative action" The World Conservation Strategy was frequently criticised for being concerned mainly with ecological sustainability rather than sustainable development per se. The most universally quoted definition is that produced in 1987 by the World Commission on Environment and Development (WCED), otherwise known as the Brundtland Commission (after its Chairperson, Gro Harlem Brundtland, Prime Minister of Norway): "Economic and social development that meets the needs of the current generation without undermining the ability of future generations to meet their own needs". (Dalal-Clayton, 2000) In the extensive discussion and use of the concept since then, there has generally been a recognition of three aspects of sustainable development:(Harris, 2000) - Economic: An economically sustainable system must be able to produce goods and services on a continuing basis, to maintain manageable levels of government andexternal debt, and to avoid extreme sectoral imbalances which damage agricultural or industrial production. - Environmental: An environmentally sustainable system must maintain a stable resource base, avoiding over-exploitation of renewable resource systems or environmental sink functions, and depleting nonrenewable resources only to the extent that investment is made in adequate substitutes. This includes maintenance of biodiversity, atmospheric stability, and other ecosystem functions not ordinarily classed as economic resources. - Social: A socially sustainable system must achieve distributional equity, adequate provision of social services including health and education, gender equity, and political accountability and participation. With these aspects sustainable development has got some strategies. Sustainable development strategies can be summarized under 9 headings: (Özyol, 2007) - Environment: Nature has its own value. None of the creature should not abuse the nature for their own needs. - The Future: While satisfying our needs we should think and take care of next generations needs and we should not forget that we have to live a world where the next generations could be able to satisfy their own needs. - Living Standards: We should not forget that living standarts of the people is not rely on materialistic needs but also it relies on social, cultural, ethical and spiritual needs. - Justice: Prosperity, chances, rights and responsibilities should be divided in between the nations, different social groups in a fairway. The needs of the poor and discriminated people‘s needs has to be put in the consideration. Similar fair sharing should be made in between existing generation and future generation. - Cautions: If we are not sure about environmental results of our behaviors we should take precautions. Because the environmental problems are global the precautions has to be taken inconsideration of social responsibilities. - Holistic Thinking: Environmental problems includes unnumbered factors and while solving these problems all these factors and stake holders should be taken in to consideration. - Social Dimension: Educational activities should be informed about the sustainable development aspects to increase for their and next generation‘s living standards. - Economical Dimension: Every resources on earth is limited. That is why they should be used efficiently and in a way that does not destruct the nature. Fair distribution of the resources is also an other aspect should be taken in to consideration. - Environmental Dimension: Every natural resources, whether or not it is recyclable, should be used in a way that ensures the continuity of resources. Sustainable development is significant factor for economies. These strategies should considered in the economy. Textile sector has great place in the Turkish economy than we can give some information regarding textile sector in Turkey. Turkish Textile Sector Turkish textile and apparel industry is a very dynamic one, in fact it is the most dynamic industry in Turkey. Becouse of having the advantage of producing the raw materials required by the industry textiles and apparels are always going to be one of the most important industries for the Turkish economy (Akalın, 2001). As in many other 695 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo developing countries, the textile and clothing industries have played an important role in the process of industrialization of Turkey. Textile sectors are now the driving force in the Turkish export industry, and they have become one of the key players in the world over the years. (Çukul, 2008) We can evaluate Turkish economy in terms of GDP, employment and exports. The share of this sector in the country‘s GDP is more than 10 % , share in the total employment is around 10 %. There are about 40 thousand manufacturing companies and around 2 million employees in the sector. Turkish textile and clothing exports reached to US$ 20 billion in 2008. With this amount, it had a share of 22% in total exports of Turkey (ĠGĠAD, 2009) . Turkish textile industry uses modern technology. Existance of a well-developed textile finishing industry in Turkey makes also possible production and marketing of highly value added fashionable and quality production. The main items are knitted fabrics, cotton woven fabrics, woven fabrics of synthetic filament yarns, bed sheets and bagssacks for packaging. Main advanteges of Turkish textile industry in production and supply of raw materials: (ITKIP, 2010) - Reachness in basic raw materials, - Geographical proximity to main markets, especially European markets, - Short logistics period due to geographical proximity, - Qualified and well-educated labor force - Liberal trade policies - Well-developed textile finishing industry - Giving importance to quality, environment and human health, sensitivity on working conditions of workers - Customs Union agreement with the European Union and free trade agreements with many other countries Turkey as being one of the most prominent textile and clothing producers in the world, now, has the production capacity to meet almost all the raw material needs of clothing industry. Some part of cotton and artificial and synthetic fibers needed by the industry are met by means of importation. Turkey has also gained valuable experience in fabric design and it is started to present its special designs with fashion shows in prominent markets. Turkish textile industrialists most of whom has created their own trademark together with the patent rights, provide the most important foreign home textile and clothing companies with their fabric. (ITKIP, 2010) Turkey is currently the second larger exporter of textile to the European Union following China. It has the largest production capacity in the EU and the fourth largest in the world. Since the EU and U.S are major markets for Turkish textile and clothing products, it is necessary to explore the competitive position of Turkish products in these markets, and they have to be prepared to the attack of its competitor such as China, India and other Asian countries. There is no doubt that China will be the largest force in the global textile sector. According to a forecast by World Bank, China is likely to raise its current share of 20 % in the world textile market to 50 % in recent years. (Çukul, 2008) Many pattern design competitions that make important contributions to development of fabric design in Turkey are organized by different institutions leading to emergence of young designers and creation of product diversity. Turkey takes part in many famous international fairs in textile sector, international textile fairs were organized within Turkey and Turkey‘s potential is shown successfully all over the world. (ITKIP, 2010) Textile sector is significant for the Turkish economy. So doing a research for textile sector is necessary. We can evaluate the sector with performance, efficiency and effectiveness values. In this study it is practicing Data Envelopment Analyses (DEA) for finding efficiency rates. Data Envelopment Analysis DEA is an extension of Farrell's (1957) idea of linking the computation of technical efficiency with production frontiers. The first DEA model was developed by Charnes Cooper and Rhodes (1978) (CCR). The CCR model is a fractional programming model, which measures the relative technical efficiency of a firm by calculating the ratio of weighted sum of its outputs to the weighted sum of its inputs. The fractional program is run for each firm to determine the set of input-output weights, which maximizes the efficiency of that firm subject to the condition that no firm can have a relative efficiency score greater than unity for that set of weights. Thus, the DEA model calculates a unique set of factor weights for each firm. The set of weights has the following characteristics: (Kabnurkar, 2001) - It maximizes the efficiency of the firm for which it is calculated and - It is feasible for all firms. Since DEA does not incorporate price information in the efficiency measure, it is appropriate for not for profit organizations where price information is not available. These not for profit organizations are referred to as Decision-Making Units (DMUs) by Charnes Cooper and Rhodes (1978). Since the efficiency of each DMU is 696 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo calculated in relation to all other DMUs and using actual observed input-output values, the efficiency calculated in DEA is called relative efficiency. Charnes, Cooper and Seiford (1994) define DEA as "DEA produces a piecewise empirical extremal production surface which in economic terms represents the revealed best-practice production frontier – the maximum output empirically obtainable from any DMU in the observed population, given its level of inputs." In addition to calculating the efficiency scores, DEA also determines the level and amount of inefficiency for each of the inputs and outputs. The amount of inefficiency is determined by comparison with a convex combination of two or more DMUs, which lie on the efficient frontier, utilize the same level of inputs, and produce the same or higher level of outputs. The aim of DEA is to quantify the distance to the efficient frontier for every DMU. The measure of performance is expressed in the form of efficiency score. After the evaluation of the relative efficiency of the present set of units, the analysis shows how inputs and outputs have to be changed in order to maximize the efficiency of the target DMU. DEA suggest the bencmark for each inefficient DMU at the level of its individual mix of inputs and outputs (Mantri, 2008) DEA is a typical statistical approach and characterized as a central tendency approach. It evaluates producers relative to an average producer. In contrast DEA campares each producer with only the ―best‖ producers. A fundamental assumption behind this method is that if a given producer, A, is capable of producing Y(A) units of output with X(A) inputs, then other producers should also be able to do the same if they were to operate efficiently. Similarly, if producer B is capable of the same production schedule. Producers A, B, and others can then be combined to form a composite producer with composite inputs and composite outputs. Since this composite producer does not necessarily exist, it is typically called a virtual producer. The heart of the analysis lies in finding the ―best‖ virtual producer for each real producer. If the virtual producer is beter than the orginal producer by either making more output with the same input or making the same output with less input then the orginal producer is inefficient. The subtleties of DEA are introduced in the various ways that producers A and B can be scarld up or down and combined. (Cornuejols & Trick, 1998) In this study DEA practiced. Aims and methods of the research is as follows. Aims and Methods of Research In this study it is tried to be evaluated the textile sector firms financial efficiencies that are quoted to ISE. In the study DEA method is used. The aim of the study is to investigate financial efficiency and effectiveness of leading Turkish textile sector companies. Economical dimension of sustainable development includes fair distiribution of the resources, avoidance of unnecessary usage of resources and efficient usage of resources. Financial resources are also significant inputs of companies and they should be used efficiently. The steps while practicing DEA can be listed as follows; - Selection of decision making units, - Determination of inputs and output sets - Relative efficiency measurement by DEA o Availability and reliability of the data o Relative efficiency measurement o Efficiency degree-efficiency limits o Evaluation of the results In first step of the study decision making units are selected. For the study balance sheets and income statements that are belong to the firms gathered from the ISE. These data includes the time period in between 2004 and 2008. Decision making units which were the subject of the study is listed in Table 1. 697 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo BOSSA Bossa Ticaret ve Sanayi ĠĢletmeleri T.A.ġ. CEYLAN Ceylan Giyim Sanayi ve Ticaret A.ġ. LUKS Lüks Kadife Ticaret ve Sanayi A.ġ. OKAN Okan Tekstil Sanayi ve Ticaret A.ġ. DERĠMOD SASA Derimod Konfeksiyon Ayakkabı Deri Sanayi ve Advansa Sasa Polyester Sanayi A.ġ. Ticaret A.ġ. EDĠP Edip Ġplik Sanayi ve Ticaret A.ġ. ESEM Esem Spor Giyim Sanayi ve Ticaret A.ġ. KARTEKS Karsu Tekstil Sanayii ve Ticaret A.ġ. VAKKO Vakko Tekstil ve Hazır Giyim Sanayi ĠĢletmeleri A.ġ. YATAS YataĢ Yatak ve Yorgan Sanayi ve Ticaret A.ġ. YUNSA Yünsa Yünlü Sanayi ve Ticaret A.ġ. Table 1: Decision Making Units That Were The Subject of the Study Second step of the study was the determination of input and output sets. These are used for measurement of financial efficiency of textile firms. Input and Output sets which were the subjects of the study is listed in Table 2. INPUT Short-Term Dept Long-Term Dept OUTPUT Sales Revenues Non-Operating Income Capital Stock Table 2: Input and Output Data Sets Used in Research These set of input and output units are used to determine the financial efficiency of the textile sector firms. For this study textile sector inputs were determined as: Short Term Debts, Long Term Debts and Capital Stock. Where as the outputs were: Sales Revenues and Non Operating Income. Analysing the Model In this study, it is perefered to used the data gathered from textile firms that are belong to ISE, because of the availability and reliability of data. For the analysis DEAP Version 2.1 is used for processing mathematical data. Inputs of the textile sector are considered as manageable data. So in the analysis input focused method is used. Lack of free market conditions prevented the firms to identify the financial problems that causes difficulties in reaching optimum levels. That is why variable income scaled efficiency model is used for solution. In this search 5 different solutions are generated by linear programming. There are three different factors are used to describe the efficiency levels; Constant Income Technical Efficiency, Variable Income Technical Efficiency and Scale Efficiency. Here technical efficiency could be described as every input‘s impact on output. Whereas scale efficiency describes the aggregate impact of all inputs to compound outputs. Scale Efficiency is measured with dividing Constant Income Technical Efficiency by Variable Income Technical Efficiency. After processing the data, DEA efficiency results, from the year 2004 and 2008, belong to the decision making units are determined and listed on the Table 3 as below. 698 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,408 1 1 1 1 DERĠMOD 1 1 1 1 0,863 EDĠP 0,859 0,9 0,325 0,245 0,045 ESEM 1 1 0,147 0,068 0,087 KARTEKS 0,613 0,752 0,658 0,818 0,640 LUKS 1 1 1 1 0,535 OKAN 1 1 1 1 0,774 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,556 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,858 0,856 0,756 0,764 0,653 Table 3: Constant Income Technical Efficiency (2004-2008) There is a reduction in Constant Income Technical Efficiency in between 2004 and 2008. This reduction could be interpreted as Chinese factor in the international trade. Regarding to Turkish textile sector Variable Income Technical Efficiency values are as below. 2004 2005 2006 2007 2008 BOSSA 1 1 1 1 1 CEYLAN 0,435 1 1 1 1 DERĠMOD 1 1 1 1 1 EDĠP 0,902 1 0,560 0,246 0,047 ESEM 1 1 0,153 0,087 0,129 KARTEKS 0,671 1 1 0,863 0,676 LUKS 1 1 1 1 0,553 OKAN 1 1 1 1 0,780 SASA 1 1 1 1 1 VAKKO 1 1 1 1 1 YATAS 1 1 1 1 0,791 YUNSA 1 1 1 1 1 ORTALAMA 0,917 1 0,893 0,850 0,748 Table 4: Variable Income Technical Efficiency (2004-2008) In terms of Variable Income Technical Efficiency there is a steady decrease in averages from 2006-2008. Large and famous firms like BOSSA, VAKKO, SASA, YÜNSA are still keeping their high stakes in the market. Regarding to Turkish textile sector Scale Efficiency values are as below. 699 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo 2004 2005 2006 2007 2008 BOSSA 0,966 0,682 0,79 1 1 CEYLAN 0,939 1 1 1 1 DERĠMOD 1 1 1 1 0,863 EDĠP 0,953 0,9 0,580 0,997 0,974 ESEM 1 1 0,960 0,778 0,675 KARTEKS 0,914 0,752 0,658 0,948 0,946 LUKS 1 1 1 1 0,967 OKAN 1 1 1 1 0,993 SASA 0,939 0,862 1 0,912 0,660 VAKKO 1 1 1 1 1 YATAS 0,86 0,549 0,659 0,573 0,703 YUNSA 0,651 0,527 0,488 0,554 0,674 ORTALAMA 0,935 0,856 0,845 0,897 0,871 Table 5: Scale Efficiency (2004-2008) As you can see from the Table 5. there is a steady decrease in the values of scale efficiencies in between 2004 and 2008. Internal and external results are also indicates that leading Turkish textile companies efficiencies are decreased. In addition to Chinese factor in textile sector, structural deficiencies in the Turkish textile sector, deficiencies in branding, financial problems and deficiencies in marketing would be other reasons for the reduction. Conclusion Textile sector plays a crucial role in the Turkish economy. Sector seriously affected from the several threads: Chinese factor which criticly reduced the competitiveness of the Turkish textile sector, domestic structural deficiencies in textile sector and reductions in domestic cotton production because of the market forces. Deficiencies in investment climate lead the textile investers to invest more competitive countries in terms of wages, input costs ( like electricity etc.) gradual weaknesses of the textile sector in Turkey is a serious problem. Because textile sector can be considered as engine of the economy. It used to provide considerable amount of employment, export revenue, value add, tax revenue. Result of the study clearly indicates that Turkish textile companies can not efficiently uses the financial resources they have. Government interventions would be as suggestion for more efficient sector for instance tax reductions, direct and indirect financial supports, lower currency policy and improvements in investing climate. References Akalın, M. (2001). Insight into The Turkish Textile and Apparel Industry, Electronic Journal of Textile. Volume: 1, No: 1, 5-6. Charnes, A., W.W. Cooper, and E. Rhodes. (1978). Measuring the eficiency of decision making units, European Journal of Operations Research: 429-444. Charnes, A., W.W. Cooper, A.Y. Lewin, and L.M. Seiford. (1994). Data Envelopment Analysis: Theory, Methodology, and Applications. Boston: Kluwer Academic Publishers., 221-222 Cornuejols G. & Trick M. (1998). Quantitative Methods for the Management Sciences, Graduate School of Industrial Administration Carnegie Mellon University, Pittsburgh, PA 15213 USA, 345-351 Çukul D. (2008). Competıtıve Aspects Of Turkısh And Chınese Textıle And Clothıng Industrıes, 8th Global Conference on Business & Economics, 1-9 700 �2nd International Symposium on Sustainable Development, June 8-9 2010, Sarajevo Dalal-Clayton B. (2000). What Is Sustaınable Development ?, Strategies for National Sustainable Development 1-2, www.nssd.net/otherdocuments/sustdev2.doc Ekinci M.B. (2007). SanayileĢme Stratejileri Çerçevesinde Çevre Boyutlu Sürdürülebilir Kalkınma AnlayıĢına ĠliĢkin Değerlendirmeler, Sosyal Siyaset Konferansları Kitap 50, 979-981 Farrell, M.J. (1957). The Measurement of Productive Efficiency, Journal of the Royal Statistical Society, 254-290 Harris J.M. (2000). Basic Principles of Sustainable Development, Global Development And Envıronment Instıtute Workıng Paper 00-04, 1-6 ĠGĠAD (Ġktisadi Giriğim ve ĠĢ Ahlakı Derneği). (2009). Tekstil Sektörü Değerlendirme Raporu, 1-3 Kabnurkar A. (2001). Mathematıcal Modelıng For Data Envelopment Analysıs Wıth Fuzzy Restrıctıons On Weıghts, Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Masters of Science in Industrial and Systems Engineering, 31-34 ITKIP Ġstanbul Tekstil ve Konfeksiyon Ġhracatçılar www.itkib.org.tr/english/about/sectors/textile/textile_info.pdf Birliği. (2010). Turkish Textile Industry,1-8 Mantri J.K. (2008). Research Methodology on Data Envelopment Analysis DEA, Universal Publisher, Boca Raton, Florida USA, 15-16 Özyol A. (2007). Sürdürülebilir Kalkınma, Hydra Uluslar arası Proje DanıĢmanlık A.ġ. Yayını, 2-5 701 � 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. 265 Title A name given to the resource Significance of Efficiency for Sustainable Development : A Practice of Data Envelopment Analysis on Textile Sector Author Author ÖZGÜR, Ersan Abstract A summary of the resource. Resources in the nature are limited and mankind has to use these resources economically or otherwise next generations might have difficulty in surviving. That is why today‘s decision makers has to be able to think and plan the futures resources for not to danger future‘s generations. In this perspective sustainable development policies can be considered as a solution for the next generation‘s wealth. Sustainable development policy requires a balance while consuming the natural resources. For sustainable development efficient uses of resources is essential. In this study we try to assess the efficiency of the Turkish textile sector companies, regarding to sustainable development. In this study Data Enveloping Analyses is practiced to the data gathered from Istanbul Stock Exchange (ISE) quoted textile companies. Results of the survey indicates that efficiency rates affected negatively from the Chinese factor, domestic structural deficiencies in textile sector and economic situation. Date A point or period of time associated with an event in the lifecycle of the resource 2010-06 Keywords Keywords. Conference or Workshop Item PeerReviewed HB Economic Theory https://omeka.ibu.edu.ba/files/original/408ccf1464ee63bc71bda8fd5aae29d9.pdf f05d850245f9b67ef0f4e3702275b2ce PDF Text Text Determination of Optimum Seed Sowing Time for Six Different Sorghum Cultivars in Purpose of Silage Production in Mediterrenean Coastline Mehmet ÖTEN Batı Akdeniz Agricultural Research Instıtute, Antalya Sadık ÇAKMAKCI Akdeniz University Faculty of Agriculture, Field Crops Department, Antalya cakmakci @akdeniz.edu.tr Abstract: Six different sorghum cultivars (Gözde 80, Rox, Leoti, Early Sumac, Nes ve N 4692xRox), registered by Mediterreanean Agricultural Research Institute, were sown in different periods in order to determine the optimum sowing time. The experiment was conducted in a split plot design with three replications. Count of 50% blooming days, count of full blooming days, forage yield, dry matter production, and leaf-stem-bunch ratio were determined. The Rox cultivar comes to number one since the enhance of green foliage have been demanded. The dry matter production having been evaluated as the most important property in terms of slage quality and production. Nest comes to fore at the first and second and at fourth Rox, at fifth period Gözde 80, respectively. The first week of May was determined to be optimum time compared to other seed sowing period in view of the climatic conditions data of year, on which the experiments were conducted and the pronounced performance of cultivars within other different seedsowing time Keywords: Sorghum, sowing time, silage. Introduction Mediterranean region of Turkey has suitable climate and soil conditions for production of many forage crops. In our country, for silage production purpose, maize and sorghum are take first place. The increasing importance of sorghum as an important livestock feed in the Turkey. Sorghum is more resistant to drough, high temperatures, diseases and pests than maize (Mcginth, 1972; Anonymous 1990; Aslangiray et al. , 1991; Tüsüz et al. 1984). Various studies showed the effect of different sowing times on the quality of silage of sorghum (Çakmakçı et al. 1999). The aim of this study was to determine the effects of different sowing times on silage quality of various sorghum cultivars. Material and Methods In this study, six different sorghum (Sorghum bicolor (L.) Moench.) cultivars (Gözde 80, Rox, Leoti, Early Sumac, Nes and N 4692xRox), registered by Mediterreanean Agricultural Research Institute, were used as plant material. The research was conducted at the research field situated in Batı Akdeniz Agricultural Research Institute Field Crop Department in Antalya-Turkey. In this study, 5 different sowing time (1st sowing time (1-10 April), 2nd sowing time (20-30 April), 3rd sowing time (1-10 May), 4th (20-30 May) and 5th sowing time (20-30 May)) were tested to determine to optimum sowing time for sorghum cultivars. Trails are as follows: count of 50% blooming days, count of full blooming days, forage yield, dry matter yield and leaf-stem-bunch. The experiment was laid out with three replications in a randomized complete block design (RCBD). The main factor consisted of 6 diffirent cultivars. The second factor consisted 5 different sowing time. Data were analysed 464 �with MSTAT-C software package programme (Freed et al. 1989). The means were seperated using Duncan Multiple Range Test at 0.05 levels. Results In this study, different sowing times ( 1st, 2nd, 3rd, 4th and 5th ) in combination with various sorghum cultivars (Gözde 80, Rox, Leoti, Early Sumac, Nes and N 4692xRox), were tested. The responses of different sowing times varied with various cultivars. The effects of different sowing times on count of 50 % blooming days, count of full blooming days, green forage yield and dry matter yield are shown Table 1, 2,3 and 4. Looking into, 50 % blooming days and statistical analyses are evaluated, it can be seen that cultivars and sowing times reciprocal interaction between cultivar and sowing time are significanty effective. The count of 50 % blooming days changed between 49.00 and 72.17 days. While the highest record was determined from 1st sowing time, the lowest record was determined from 5th sowing time. Sowing time Cultivars 1st 2nd 3rd 4th 5th Leoti 72.17 a 64.33 e 61.17 g 55.83 k 53.00 n Nes 65.83 d 59.33 h 55.17 kl 58.50 ı 52.00 o Gözde 80 65.67 d 61.00 g 55.67 k 49.33 q N4692xRox 69.50 b 62.00 f 58.17 ı 53.67m mmm 58.83hı Rox 69.83 b 61.67 fg 56.50 j 58.83hı 50.83 p E.sumac 67.50 c 59.50 h 54.83 l 53.83m 49.00 q Ortalama 68.41 61.30 56.91 56.58 50.99 51.83 o LSD:0.66 Table 1. Count of 50 % blooming days responses to different sowing time with various sorghum cultivars In the study conducted on count of full blooming days, the count of full blooming days ranged from 52.83 to 77.17 depending on sowing time (Table 2). The highest count of full blooming days was recorded by 1st sowing time in Leotti cultivar. On the other side, the lowest count of full blooming days was recorded by 5st sowing time in E. Sumac cultivar. Sowing time Cultivars 1st 2nd 3rd 4th 5th Leoti 77.17 a 67.83 f 65.33 ghı 61.17 o 56.83 r Nes 72.67 cd 64.83 ı 60.17 p 62.00 mn 56.17 rs Gözde 80 72.00 de 65.83 gh 61.50 no 58.33 q 56.00 s N4692xRox 73.33 c 65.17 hı 62.50 lm 63.33 jk 55.17 t Rox 74.33 b 66.00 g 61.33 no 62.83 kl 54.50 t E.sumac 71.33 e 63.83 j 58.67 q 58.50 q 52.83 u Ortalama 73.47 65.58 61.58 61.02 55.23 LSD: 0.74 Table 2. Count of full blooming days responses to different sowing time with various sorghum cultivars 465 �Resuts obtained from the present study indicated that sowing time and cultivars had significantly effect on green forage yield (Table 3). Green forage yields were found 9428.5 by 1st sowing time and 9688.7 by 5th sowing time. Sowing time Cultivars 1st 2nd 3rd 4th 5th Leoti 9111 hıjk 8356 ıjk 9556 ghı 986 7efg 7789 jk Nes 9156 hıjk 12040 abc 11690 bcd 12070 hı 9644 fghı Gözde 80 9289 ghıj 7689 k 10360 def 11290 abc 11820 bcd N4692xRox 9200 hıjk 10800 cdefg 10800 gh 8444 bcd 5089 l Rox 10840 cdefg 11200 bcdef 13380 a 12130 ıjk 11160 bcdef E.sumac 8978 hıjk 9689 fghı 11420 bcd 12530abc 12600 ab Ortalama 9428.5 9962.3 11201.0 11055.2 9683.7 LSD: 1350 Table 3. Green forage yield (kg/da) responses to different sowing time with various sorghum cultivars The effects of different sowing times on dry matter yield of various sorghum cultivars is shown Table 4. Results reveal that the effects of sowing time and cultivars are statistically significant. Upon examination of data in Table 4, the highest dry matter yield were determined by E. Sumac cultivar with 3725 kg/da in 4th and 5th sowing time. Sowing time Cultivars 1st 2nd 3rd 4th 5th Leoti 2260 ıj 2383 hıj 3068 cdef 2369 hıj 2369 hıj Nes 3033cdefg 3655 abc 3698 ab 2715 fghı 2715 fghıj Gözde 80 2934 defgh 2416 ghıj 3140 bcd 3937 a 3937 a N4692xRox 2838 defghı 3219 bcdef 3260 bcd 1391 k 1391 k Rox 3019 defg 3176 bcdef 3958 a 2762 fghı 2762 fghı E.sumac 2758 fghı 2818 efghı 3461 abc 3725 ab 3725 ab Ortalama 2807.0 2944.5 3430.8 2816.5 2816.5 LSD: 531.6 Table 4. Dry matter yield (kg/da) responses to different sowing time with various sorghum cultivars Conclusion It was found that different sowing times effected on sorghum silage quality. The results show that the selection of sowing time depends on cultivars. Acknowledgements This reseach was financially supported by The Scientific Research Projects Administration Unit of Akdeniz University. 466 �References Anonymous, 1990b. Amerikan Sorgumunun Hayvan Yemi Olarak Kullanımı. U.S.Feed Grains Counsil.News. Sayı: 43 Aslangiray, C., Tansı, V. Ve Sağlamtimur, T. 1991. Çukurova Koşullarında II. Ürün Olarak Yetiştirilen Mısır (Sea Mays L.) Ve Sorgum (Sorghum Sp.) Tür Ve Çeşitlerinin Gelişme Dönemlerine Göre Biyolojik Üretimlerinin Saptanması Üzerine Bir Araştırma. Türkiye 2. Çayır-Mer’a Ve Yem Bitkileri Kongresi. 369-378. 28-31 Mayıs 1991, Đzmir. Çakmakçı, S., Gündüz, Đ., Çeçen, S., Aydınoğlu, B. Ve Tüsüz, M.A., 1999. Sorgumun Silajlık Kullanımında Farklı Biçim Devrelerinin Verim Ve Kalite Üzerine Etkileri. Turkısh Journal Of Agriculture&Forestry V:23, N:3 Freed, R., Eıenensmıth, S. P., Guetz, S., Reıcosky, D., Smaıl, V. W. And Wolberg, P.1989. User’s Guide To MSTAT-C Analysis Of Agronomic Research Experiments. Michigan State Universty., USA Mcginty, D. D. 1972. Sorghum Đn Animal Nutrition, Oxfort And IBH Publishing Co. 461-481. Tüsüz, M., Polat, N., Ünal, F., Aydemir, G., Ateş, M. 1984. Đkinci Üründe Silaj Sorgum Ve Sudan Otu Tarımı. Đkinci Ürün Tarımı Araştırma Yayım Projesi Konu Uzmanları Yayınları T. O. K. B. Ziraat Đşl. Gen.Md. 467 � 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. 547 Title A name given to the resource Determination of Optimum Seed Sowing Time for Six Different Sorghum Cultivars in Purpose of Silage Production in Mediterrenean Coastline Author Author ÖTEN, Mehmet ÇAKMAKCI, Sadık Abstract A summary of the resource. Six different sorghum cultivars (Gözde 80, Rox, Leoti, Early Sumac, Nes ve N 4692xRox), registered by Mediterreanean Agricultural Research Institute, were sown in different periods in order to determine the optimum sowing time. The experiment was conducted in a split plot design with three replications. Count of 50% blooming days, count of full blooming days, forage yield, dry matter production, and leaf-stem-bunch ratio were determined. The Rox cultivar comes to number one since the enhance of green foliage have been demanded. The dry matter production having been evaluated as the most important property in terms of slage quality and production. Nest comes to fore at the first and second and at fourth Rox, at fifth period Gözde 80, respectively. The first week of May was determined to be optimum time compared to other seed sowing period in view of the climatic conditions data of year, on which the experiments were conducted and the pronounced performance of cultivars within other different seedsowing time 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/eb2e68a55e51bce8c0ea978a629b71f2.pdf a3ee73b8fcd61fe22e393d7352278382 PDF Text Text Carbonation of Ulexite Ore Waste for CO2 Sequestration Mehmet Çopur Atatürk University, Department of Chemical Engineering, 25240 Erzurum,Turkey mcopur@atauni.edu.tr M.Muhtar Kocakerim Atatürk University, Department of Chemical Engineering, 25240 Erzurum,Turkey mkocakerim@yahoo.com Abstract: -3 mm ulexite ore containing 20-25 % B2O3, being a concentration waste is accumulated in mine area. Boron content of this waste dissolves by rain and snow waters and passes to soil, surface water and underground water and can be caused to pollution. For this reason, boron content of this waste must be removed or gained.As a result of industrialization, also, the amount of carbon dioxide given to atmosphere increases, day by day, and causes to global heating and climate change. For this reason, it is required to be removed carbon dioxide in flue gases. In this study, sequestration of carbon dioxide with ulexite ore waste was investigated under high pressures and at temperatures of 90 to 170oC. In the experiments, temperature, carbon dioxide pressure, solid-to-liquid ratio, particle size and stirring speed were chosen as parameters. In result, sequestration rate increased with increase in temperature and carbon dioxide pressure, and with decrease in solid-to-liquid ratio and paticle size. Stirring speed did not affect the sequestration rate. Also, boron and carbon dioxide, which form the risk for environmental were converted to sodium pentaborate and calcium carbonate by this process, respectively.Also, kinetics of reaction between carbon dioxide and ulexite waste was examined according to experimental data and determined that reaction kinetics fitted to ash diffusion control, stated as 1-3(1-X)2/3+2(1-X) = ktm and activation energy was found as 20.5 kJ.mol-1. Keywords: Waste ulexite, carbon dioxide, global warming, climate change Introduction CO2 content of the atmosphere has increased significantly and rapidly in recent years reaching 3841 ppm in 2007, with an annual mean growth rate of almost 21 ppm since 2000. In order to prevent CO2 concentrations in the atmosphere rising to unacceptable levels, carbon dioxide can be separated from the flue gases of power plants and subsequently sequestrated. Various technologies for carbon dioxide sequestration have been proposed[1]. An alternative sequestration method is mineral CO2 sequestration method in which CO2 is chemically stored in solid carbonates by the carbonation of minerals. Mineral CO2 sequestration has some fundamental advantages compared to other sequestration routes. The formed products are thermodynamically stable and therefore the sequestration of CO2 is permanent and safe. In order to be able to react with acid CO2, the mineral has to provide alkalinity[2]. The rates of carbonation reactions at atmospheric conditions are much too slow for an industrial process. Therefore, research focuses on increasing the reaction rate in order to obtain an industrial viable process[69]. 35 �Carbonation of industrial alkaline residues can be used as a CO2 sequestration technology to reduce carbon dioxide emissions. The production of valuable products by utilizing CO2 has been the objective of many studies in recent years [10-13]. Rendek et al. [14] performed their accelerated carbonation experiments in a high pressure vessel at room temperature for municipal solid waste incinerator ash. The pressure improved the kinetics of the reaction but did not affect the final amount of carbonates formed[15]. Another type of industrial solid residues that could be used for CO2 sequestration is air pollution control equipment residue, an alkaline residue that can be collected from various incinerator plant flue gas clean-up systems. In a study by Baciocchi et al it has been determined to correspond to a CO2 storage potential of about 150 kt/yr (120 g of CO2/kg of residue) of this residue [16]. However, it has been stated that this process has limited volume potential. Baciocchi et al. [17] investigated the kinetics of gas-solid carbonation of APC residues when subjected to a flux of CO2 (10 vol-%) in argon. In this study with two stages, the kinetic analysis was limited to the first stage of the carbonation process. But, it was not taken into account the second stage data associated with CO2 diffusion through a product layer. Back et al. [18] investigated the CO2 uptake potential of lignite fly ashes. They resulted in a maximum CO2 binding capacity of around 0.1 kg CO2/kg ash in 1 h, corresponding to 0.5% of the CO2 emissions from a brown coal firing plant in an experiment performed in 30 °C under atmospheric pressure (pCO2 = 0.1) and a low S/L ratio (1/80). By upgrading a waste product into a product of high commercial value, expensive CO2 sequestration processes could become economically feasible. Katsuyama et al. [19] studied the feasibility of producing CaCO3 from waste cement by first extracting calcium from pulverized waste cement in a water slurry at high CO2 pressure (several MPa), followed by the precipitation of CaCO3 from the extracted solution at lower CO2 pressures. In result, they produced high purity CaCO3 from waste cement at relatively high reaction rates. In this study presented here, -3mm ulexite ore waste was used to capture CO2 in flue gas from power stations in aqueous solutions under high pressures and at high temperatures. In result, CO2 by ore waste and boron content of ore waste was recovered. Experimental Procedure Ulexite ore waste used in these studies has been supplied from Bigadiç Boron Establishments. After the ore waste was dried in air, it was ground by a laboratory grinder and fractionned by sieving with the standard sieves. This ore waste contained 23,6% B2O3, 9,21% SiO2, 25,48% CaO, 6,67% MgO, 2,25% Na2O, 0,51% Al2O3, 0,09% Fe2O3, 1,13% SrO, 31,21% heating loss as according to XRF analysis. CO2 gas was supplied as tube from Habaş, Turkey. All tests were carried out in a two-liter magnetic-stir-drive PARR autoclave. The CO2 pressure applied was controlled by a pressure-measuring device (Fig. 1), and the temp. of the reaction in the reactor was provided by an automatically controlled heater underneath the stainless-steel vessel, which allowed the slurry to be taken out of the device for separation by filtration of the solid particles. A 50 kg CO2 tank containing the gas at 200 bar pressure was used as the CO2 source. In the experiments, after 300 mL water was taken in the reactor, a predetermined amount of the ulexite waste was placed into the vessel. After reactor was adjusted to desired temperature and the stirrer to desired speed, CO2 injection was performed up to desired pressure. The pressure was continuously monitored and more CO2 was injected as the pressure decreased either due to leaks or chemical reaction. At the end of the desired test time the stirring stopped and the slurry was cooled by running water through cooling coils in the solution. When the temperature fell below 85 oC, the pressure was bled off and the 36 �slurry was taken out of the device. The slurry was filtered, and the solids were dried at 105 oC, weighed, and sampled for analysis. Na, Ca and B2O3 analysis was performed in solution. B2O3 fractions passing to the solution were calculated as follows: B2 O3 fraction passing to the solution = amount of B2 O3 passing to the solution total amount of B2 O3 in original sample Parameters Parameter values Temperature(K) 363 378 393 413* Solid-to-liquid(g/mL) 0,15 0,20* 0,25 0,30 Stirring speed(rpm) 300 500* 700 CO2 pressure(Bar) 5 10 15 Particle size(meş) -80 +100 (1) 433 443 20* -60 +80 -45 +60* -30+45 *Parameters kept constant Table 1. Parameters and their values Results and Discussion In view of its reactivity with carbon dioxide, ulexite ore waste has been proposed for the reduction of greenhouse gas emissions from utility power plants. The reactions between ulexite and CO2 in aqueous solution are given in Equations 7, 8 and 9. (7) Na 2O ⋅ 2CaO ⋅ 5B2 O3 ⋅16H 2O(s) +2CO2 → 2CaCO3(s) +2NaB5O6 (OH) 4 +12H 2O (8) Na 2 O ⋅ 2CaO ⋅ 5B2 O 3 ⋅16H 2 O (s) +2CO 2 → 2CaCO3(s) +2NaB3O 3 (OH) 4 +4H 3 BO3 +6H 2 O Also, the reaction between colemanite and CO2 as follows; (9) 2CaO ⋅ 3B2 O3 ⋅ 5H2O(s) + 2CO2(g,aq) + 4H2O → 2CaCO3(s) + 6H3BO3( s,aq ) The ratios of the ionic borate species depending on the pH values are given in Figure 2. The pH value during the chemical reaction was recorded as between 6.5-7; at this pH value the borate species B5O6 (OH)4-, B4O5(OH)4-, B3O3(OH)4- and B(OH)3 have been found in aqueous solution [20]. The amount of CO2 captured in solution was proportional to the borate ion concentrations. The parameters used in this study were particle size, solid-to-liquid ratio, CO2 pressure, stirring speed and temperature. In examining the effect of particle size, solid-to-liquid ratio was kept constant as 0.2 g/mL, CO2 pressure as 20 bar, stirring speed as 500 rpm and temperature as 323K. Particle size levels were -30 +45, -45 +60, -60 +80, -80 +100 mesh. Results are given graphically in Figure 1. According to these results, dissolution rate increased with decreasing particle size. 37 �100 80 B2O3 (%) 60 40 -30+45 -45+60 -60+80 -80+100 20 0 0 5 10 15 20 25 30 35 time(min) Figure 1. The effect of particle size on dissolution of ulexite ore waste in CO2 containing water 50 CO2 (L/Kg) 40 30 20 -30+45 -45+60 -60+80 -80+100 10 0 0 5 10 15 20 25 30 35 time(min) Figure 2. The effect of particle size on CO2 sequestration by ulexite ore waste. The effect of solid-to-liquid ratio was investigated for 0.15, 0.20, 0.25 and 0.30 g/mL values of solid-toliquid ratio, so that particle size was kept constant in -45 +60, CO2 pressure in 20 bar, stirring speed in 500 rpm and temperature in 413 K. The results are given graphically in Figure 3. According to the results, increasing the solid-to- liquid ratio causes to decrease of dissolution rate. It is given the effect of solid-toliquid ratio on CO2 sequestration by ulexite ore waste in Figure 4.. 38 �100 80 B2O3(%) 60 40 0.15 0.20 0.25 0.30 20 g/mL g/mL g/mL g/mL 0 0 5 10 15 20 25 30 35 time(min) Figure 3. The effect of solid-to-liquid ratio on dissolution of ulexite ore waste in CO2 containing water 50 40 CO2(%) 30 20 0.15 0.20 0.25 0.30 10 g/mL g/mL g/mL g/mL 0 0 5 10 15 20 25 30 35 time(min) Figure 4. The effect of solid-to-liquid ratio on CO2 sequestration by ulexite ore waste. The effect of CO2 pressure on dissolution of ulexite ore waste was examined at the CO2 pressures, 20, 15, 10 and 5 atm. Particle size was kept constant in -45 + 60 µm, solid-to-liquid ratio in 0.2 g/mL, stirring speed in 500 rpm and temperature at 413 K. The results are given graphically in Figure 6. According to the results, as CO2 pressure increases, dissolution rate increases. It is given the effect of pressure on CO2 sequestration by ulexite ore waste in Figure 6. 39 �100 B2O3 (%) 80 60 40 2.5 5 10 20 20 Bar Bar Bar Bar 0 0 5 10 15 20 25 30 35 time(min) Figure 5. The effect of CO2 pressure on dissolution of ulexite ore waste in CO2 containing water 50 CO2 (L/Kg) 40 30 20 2.5 5 10 20 10 Bar Bar Bar Bar 0 0 5 10 15 20 25 30 35 time(min) Figure 6. The effect of pressure on CO2 sequestration by ulexite ore waste. The solubility product of calcium carbonate at STP is 5 X 10-9. First, the gas phase (CO2) must dissolve in the solution: CO 2( g ) + H 2O (10) H 2CO3( aq ) According to Henry’s Law, the concentration of H2CO3(aq) is proportional to the CO2 partial pressure (PCO2). At standard temperature and pressure (STP), Henry’s constant (KH) = 29.4 atm/mol/L. H2CO3 40 �concentration increases with increasing CO2 pressure at 25°C. Using the high-pressure correction to Henry’s law would only lower the calculated concentration by approximately a factor of 1.25[1]. H2CO3 dissociates according to the following: H 2CO3(aq) + H(aq) +HCO3(aq) (11) K a1 =4.5×10-5 HCO3- dissociates further as follows: HCO3(aq) + 2H (aq) +CO3(aq) (12) K a1 =4.5×10-11 At equilibrium, when no other acid is in the solution, [H+] and [HCO3-] are equal and 2− 3 CO  = 4.7 ⋅10−11  HCO3−  2 (13) H+ These equations indicate that increased CO2 pressure lowers pH, and this would help to leach calcium from the ulexite as it has been shown in some leaching tests of ulexite. Increasing CO2 pressure also increases [HCO3-] and, thus, CO3- which is required for the precipitation of calcium carbonate. However, because Ka2 is small compared Ka1, simply raising the pressure of CO2 only generates small amount of CO32-. In that case, the concentration of carbonic ion is very small, and thus a very high calcium ion concentration is required to precipitate calcium carbonate. The precipitation of calcium carbonate will increase by the increase in carbonic-ion concentration with Na ions passed solution with ulexite dissolution. The solubility of calcium carbonate decreases with increase in temperature. the dissolution reaction for carbonate minerals is exothermic, which results in higher temperatures favoring the solid phase over dissolved ions. The solubility of calcium carbonate in the presence of sodium carbonate is less than 0.5 p. p. m. Dissolution data from experiments were evaluated bt a statistical program and the following model was found for dissolution. As result, dissolution process fit to ash diffusioncontrols kinetics. That stirring speed isn’t effective on the dissolution and activation energy of 20.474 kj.mol-1 show that process rate is controlled by ash diffusion controls kinetics. Convenience of this model was controled by drawing a graph of dissolution values from this model versus experimental data(Figure 7). In result, it was determined that the model is suitable. 1-3(1-X)(2/3) +2(1-X) = 1091( P )0.43 ( S / L )−0.84 ( PS )−0.91 e − 20.474 0.2 RT 41 t (15) �1.0 Observed X Values 0.9 0.8 0.7 0.6 0.5 0.4 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Predicted X Values Figure 7. Graph of observed values versa predicted values from model Acknowledgements It is a great pleasure to thank TUBITAK (The Scientific and Technological Research Council of Turkey) for their financial support during our project (108Y170). References [1] Sipilä, J., Teir, S., Zevenhoven, R.,Carbon dioxide sequestration by mineral carbonation, Literature review update 2005–2007, Åbo Akademi University, Faculty of Technology Heat Engineering Laboratory [2] Huijgen, W.J.J., Comans,R.N.J. Carbon dioxide sequestration by mineral carbonation, Literature Review, (2003), The Energy research Centre of the Netherlands. [3] Butt, D.P., Lackner, K.S., Wendt, C.H., Conzone, S.D., Kung, H., Lu, Y.-C., Bremser, J.K.(1996), Kinetics of thermal dehydroxylation and carbonation of magnesium hydroxide, Journal of the American Ceramic Society. (7), 1892-1898. [4] Zevenhoven, R., Tier, S., 2004, Long term storage of CO2 as magnesium carbonate in Finland, Proceedings of the Third Annual Conference on Carbon Capture and Sequestration, May 3-6, 2004, Alexandria (VA), USA, (paper 217). [5] Zevenhoven, R., Eloneva, S., Teir, S., 2006, A study on MgO-based mineral carbonation kinetics using pressurised thermogravimetric analysis, 8th International Conference on Greenhouse Gas Control Technologies, 19-22, Trondheim, Norway, paper P02_01_09. [6] Gerdemann, S.J., O'Connor, W.K., Dahlin, D.C., Penner, L.R., Rush, H., 2007, Ex situ aqueous mineral carbonation, Environ. Sci. Technol. (41), pp. 2587-2593. [7] O'Connor, W.K., Dahlin, D.C., Nilsen, R.P., Turner, P.C., 2000, Carbon dioxide sequestration by direct mineral carbonation with carbonic acid, Proceedings of the 25th International Technical Conf. On Coal Utilization & Fuel Systems, Coal Technology Assoc. March 6-9, Clear Water, FL, Albany Research Center, Albany, Oregon. 42 �[8] Munz, I.A., Korneliussen, A., Gorset, O., Johansen, H., Kihle, J., Flaathen, T., Sandvik, K., 2006, Added value of industrial minerals and CO2 storage: New possibilities for Norwegian mineral industry, 8th International Conference on Greenhouse Gas Control Technologies, 19-22 June, Trondheim, Norway, (Paper P02_01_12). [9]Kakizawa, M., Yamasaki, A., Yanagisawa, Y., 2001, A new CO2 disposal process via artificial weathering of calcium silicate accelerated by acetic acid, Energy. (26), pp. 341-354. [10] Teir, S., Eloneva, S., Zevenhoven, R., 2005, Production of precipitated calcium carbonate from calcium silicates and carbon dioxide, Energy Conversion and Management. (46), pp. 2954-2979. [11] Domingo, C., Loste, E., Gómez-Morales, J., García-Carmona, J., Fraile, J., 2006, Calcite precipitation by a highpressure CO2 carbonation route, The Journal of Supercritical Fluids. (36), pp. 202-215. [12]Katsuyama, Y., Yamasaki, A., Iizuka, A., Fujii, M., Kumagai, K., Yanagisawa, Y., 2005, Development of a process for producing high-purity calcium carbonate (CaCO3) from waste cement using pressurized CO2, Environmental Progress. (24), pp. 162-170. [13] Feng, B., Yong, A.K., An, H., 2007, Effect of various factors on the particle size of calcium carbonate formed in a precipitation process, Materials Science and Engineering: A. (445-446), pp. 170-179. [14] Rendek, E., Ducom, G., Germain, P., 2006, Carbon dioxide sequestration in municipal solid waste incinerator (MSWI) bottom ash, Journal of Hazardous Materials. (128), pp. 73-79. [15] Rendek, E., Ducom, G., Germain, P., 2007, Influence of waste input and combustion technology on MSWI bottom ash quality, Waste Management. (27), pp. 1403-1407. [16]Baciocchi, R., Polettini, A., Pomi, R., Prigiobbe, V., VonZedwitz, V.N., Steinfeld, A., 2006, CO2 sequestration by direct gas-solid carbonation of air pollution control (APC) residues, Energy Fuels. (20), pp. 1933-1940. [17] Baciocchi, R., Polettini, A., Pomi, R., Prigiobbe, V., Zedtwitz-Nikulshyna, V., Steinfeld, A.,2006, Performance and kinetics of CO2 sequestration by direct gas-solid carbonation of APC residues, 8th International Conference on Greenhouse Gas Control Technologies, 19-22 June, Trondheim, Norway. [18] Back, M., Vosbeck, K., Kühn, M., Stanjek, H., Clauser, C., Peiffer, S., 2006, Pretreatment of CO2 with fly ashes to generate alkalinity for subsurface sequestration, 8th International Conference on Greenhouse Gas Control Technologies, 19-22 June, Trondheim, Norway. [19] Katsuyama, Y., Yamasaki, A., Iizuka, A., Fujii, M., Kumagai, K., Yanagisawa, Y., 2005, Development of a process for producing high-purity calcium carbonate (CaCO3) from waste cement using pressurized CO2, Environmental Progress. (24), pp. 162-170. [20] B.M.Adams, Boron, Metallo-Boron Compounds and Boranes, Interscience (Wiley), New York (1964) p.88[21]Zhong-Ying Chen,a William K. O’Connor,b and S.J. Gerdemannb, Chemistry of Aqueous Mineral Carbonation for Carbon Sequestration and Explanation of Experimental Results, Environmental Progress (Vol.25, No.2), July 2006,160 43 � 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. 327 Title A name given to the resource Carbonation of Ulexite Ore Waste for CO2 Sequestration Author Author Çopur, Mehmet Kocakerim, M.Muhtar Abstract A summary of the resource. -3 mm ulexite ore containing 20-25 % B2O3, being a concentration waste is accumulated in mine area. Boron content of this waste dissolves by rain and snow waters and passes to soil, surface water and underground water and can be caused to pollution. For this reason, boron content of this waste must be removed or gained.As a result of industrialization, also, the amount of carbon dioxide given to atmosphere increases, day by day, and causes to global heating and climate change. For this reason, it is required to be removed carbon dioxide in flue gases. In this study, sequestration of carbon dioxide with ulexite ore waste was investigated under high pressures and at temperatures of 90 to 170oC. In the experiments, temperature, carbon dioxide pressure, solid-to-liquid ratio, particle size and stirring speed were chosen as parameters. In result, sequestration rate increased with increase in temperature and carbon dioxide pressure, and with decrease in solid-to-liquid ratio and paticle size. Stirring speed did not affect the sequestration rate. Also, boron and carbon dioxide, which form the risk for environmental were converted to sodium pentaborate and calcium carbonate by this process, respectively.Also, kinetics of reaction between carbon dioxide and ulexite waste was examined according to experimental data and determined that reaction kinetics fitted to ash diffusion control, stated as 1-3(1-X)2/3+2(1-X) = ktm and activation energy was found as 20.5 kJ.mol-1. 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/d81943d5437961711d62b0eee53683a0.pdf 7b0f44563ee119b17cc60b833e38dde2 PDF Text Text A Survey Of Network Modelıng And Sımulatıon Tools: Devs Comparıson Bülent Çobanoğlu Sakarya University Electronics and Computer Science Department 54187 Sakarya, TURKEY bcobanoglu@sakarya.edu.tr Ahmet Zengin Sakarya University Electronics and Computer Science Department 54187 Sakarya, TURKEY azengin@sakarya.edu.tr Sinan Tüncel Sakarya University Electronics and Computer Science Department 54187 Sakarya, TURKEY stuncel@sakarya.edu.tr Hüseyin Ekiz Sakarya University Electronics and Computer Science Department 54187 Sakarya, TURKEY ekiz@sakarya.edu.tr Abstract: Speed, hardware, cost, diversity of user demands and interoperability requirements of today’s network systems cause several difficulties in network research. In design phase, due to time and cost advantage of modeling and simulation science it is widely used by researchers working on network systems. In order to expedite and simplify the design process, to design and develop network simulation tools is an active research area. Today, many modeling and simulation tools are available in computer networks research and education. In this study, to assist researchers working on computer networks in the selection of modeling and simulation tools, several best-known simulators are selected and compared. Especially to examine the advantages and disadvantages of network simulators used for training purposes, an OSPF protocol implementation was devised to discuss strengths and weaknesses of simulators. At the same time, executing a general purpose DEVS based OSPF model in DEVS-Suite simulator; the advantages of the method are summarized. 1. Introduction The primary aim of computer networks is providing connection among users to access resources. Currently, computer networks has become a very complex structure including variety of applications such as operating systems, communication protocols, link technologies, traffic flow, routing algorithms and protocols. Network design process is a difficult task in case of meeting user requirements, cost and capacity. To simplify the design process, researchers and manufacturers maintain different network modeling and simulation (M & S) tools have already developed and still under development. These network modeling and simulation tools (M & S) can be used for practical purposes and they can be also used for educational and research purposes. Modeling and simulation (M & S) methodologies play an important role in computer network research and design. Real networks can be investigated by modeling the new networking technologies that efficient development and testing, various network conditions and scenarios under the communication protocol development and evaluation [7] [8] [12]. To investigate interactions with other protocols and to make comparisons with other approaches, to study the behavior and properties of the protocols are very important. There are a wide range of network modeling and simulation tools used today. In general, these tools can be divided into four classes: analytics, simulation, network topology discovery and production tools. Analytical tools help the design of a network model calculation (eg, reliability, usability, etc.). Analytical model, among 418 �other methods have the advantage of simplicity and often simplified assumptions. If network discovery tools available to a system, real network components and their graphic or textual (text) can be obtained. Simulation tools are used to simulate the dynamic behavior a network components such as packet switch, link errors, TCP protocol, etc [1, 12]. Today, number of network simulators and simulation tools are found to design and analysis of networks (see Figure 1). Tools Analytical Topology Generation Simulation Educational tools Commercial tools Network Discovery Specialized tools Figure 1. Classification of the network design and simulation tools. 2. Network Sımulatıon Tools Network simulators were developed to help researchers in network design and development processes. The large number of network simulators for training purposes and commercial purposes are available. Their features and capabilities will be examined in this. In this study we compared OPNET, ns-22 and OMNET with specialpurpose simulator DEVS Suite. Most known simulators for training are ns-2, pdns, Netsim, GTNetS, WIPSIM, OMNET++ and commercial simulators are OPNET, QualNet, COMNET, REAL, SSFNet and Ted, special-purpose simulators are Glomosim, QUIPS-II, the ATM-TN, and Devs Suite. In this study, commonly used network simulation software and tools are given in Table 1 and a survey research conducted among the results obtained [1, 3, 9, 20]. 2.1 Educational tools 2.1.1 OMNET++ Figure 2. OMNET screenshot of the simple network consisting of router nodes and duplex links 419 �OMNET + + (Objective Modular Network Testbed in C + +), object-oriented (object-oriented) and this software is a modular discrete event network simulator itemized below can be used in the simulation of the process. - Communication modeling of traffic - Modeling of communication protocols - Multi-processor and other distributed hardware systems, modeling - Hardware structure review - Evaluation of performance analysis of complex systems - Discrete event approach is suitable for modeling of other systems. OMNeT + + software models a network as composed of interconnected modules. The top-level module is network module. The depth last module is connected to the user so that models of complex systems can be realized easily. Modules can be divided into two categories: simple and compound. A simple module is to describe the behavior of a model associated with C + + file. This file is written by the user using OMNET + + simulation class library. Compounds from a combination of the modules consists of the simple modules and are not directly associated with a C + + file. Modules communicate among themselves and with the help of the messages of the simulation time, a module receives a message from the module itself or another is progressing. The structure of modules and interfaces and the simulation parameters can be organized using Network Definition Language (Network Description Languages - NED) and are created as a startup file (. Ini) which is easily adjustable. [22], [6] 2.1.2 The network simulator ns-2 The network simulator ns-2 is developed based on REAL network simulator project. It is designed for research for local and wide-area network simulations and network education. Ns-2 is an object-oriented, open source, discrete event network simulator, which is written in C++ and uses OTcl as a command and configuration interface. It is based on a seven-layer network synthesis and designed as packet-based, which means that all packet interactions are in focus during simulation. It implements network transmission protocols such as TCP and UPD, traffic source behavior such as FTP, Telnet, Web, CBR and VBR, router queue management mechanism such as DropTail, RED and CBQ, routing algorithms such as Dijkstra , and other algorithms. Network simulator 2 provides an important support for modeling and simulation of TCP, routing, and multicast protocols over wired and wireless networks and is primarily useful for simulating local and wide area networks. Although ns-2 is fairly easy to use once you get to know the simulator, it is quite difficult for a first-time user, because there are few user-friendly manuals and it is difficult to install. Various extensions of parallel and distributed variations are developed to achieve execution scalability (e.g., pdns). Many researches including design, test and comparison of new network algorithms, protocols, and technologies are done with ns-2. Some deficiencies of ns-2 include limited support for visualization and complex simulator design. Since ns-2 is dependent on different technologies, it can be very difficult to make changes to the existing models. Furthermore, from the modeling methodology vantage point, ns-2 can be considered a domain-specific simulator which is intimately tied to the computer network concepts. 2.2 Commercial tools 2.2.1 OPNET (OPtimised Network Engineering Tool) OPNET, which was developed in 1987 is the first commercial network simulation tool. Network can be established very easily, with a graphical interface, user-friendly, widely used in industry, a powerful discrete event network simulator. Figure. 3. NAM screenshot of the simple network consisting of router nodes and duplex links OPNET software of the system behavior and the analysis of discrete event simulation can be performed. OPNET simulation program has three levels: network, node and process. These levels can be developed using the visual 420 �editor. The programs also edit the parameters of the simulation and data analysis tools to create the graph contains. Network structure, node and process models are included in a project file is created in the scenarios. Simulation tool will be collected with the help of the design is complete, statistics are determined and work. Even with the program analysis tool obtained data can be displayed in the desired chart type. Of data from more than one scenario is also possible to compare the same show on the graph [1,10,11,13]. Node model and process model, with the help of an editor for creating user-defined nodes and protocols can be created. Profile descriptions and application definitions can be changed with the help of the editors. Figure 4. OPNET screenshot of the simple network consisting of router nodes and duplex links 2.3 Specialized tools 2.3.1 DEVS Suite: To use modeling and simulation as problem solving technique, there is need for a modeling formalism. As a formal system definition, formalism renders possible to create virtual worlds in our limited computation frameworks and tools. Limitations of the computation environments demand new high performance modeling formalisms and approaches. Large scale network systems exhibit very high level complex, dynamic and parallel characteristics. Therefore, complex and distributed behaviors of the large scale systems make modeling effort of the networks difficult. However, discrete event modeling formalisms bringing abstraction and simplification mechanisms to modeling and simulation discipline facilitates modeling and simulation study systems such as computer networks demonstrating complex, dynamic, distributed and unpredicted behavior. The dynamics of network systems can be described using discrete event modeling. This is because the dynamics of network systems can be characterized in terms of components that can process and generate events. Among discrete event modeling approaches, the Discrete Event Systems Specification (DEVS) is well suited for formally describing concurrent processing and the event-driven nature of arbitrary configuration of nodes and links forming network systems. This modeling approach supports hierarchical modular model construction, distributed execution, and therefore characterizing complex, large-scale systems with atomic and coupled models. Atomic models represent the structure and behavior of individual components via inputs (X), outputs (Y), states (S), and functions. Parallel DEVS, which extends the classical DEVS, is capable of processing multiple input events and concurrent occurrences of internal and external transition functions. Parallel DEVS atomic model supports local control on the handling of simultaneous internal and external events. 421 �Figure 5. DEVS Suite OSPF Simulator screenshot of the simple network consisting of router nodes and duplex links DEVS formalism can be executed using simulation engines such as DEVS-Suite and DEVSJAVA. DEVS-Suite and DEVSJAVA are object oriented realization of Parallel DEVS and its associated simulators. They support describing complex structures and behaviors of network systems using object-oriented modeling techniques and advanced features of the Java programming language. The formal foundation of DEVS, its efficient execution, and the availability of sequential, parallel, or distributed simulation engines using alternative computational environments such as CORBA, HLA, and Web-services are important considerations. Furthermore, the DEVS models are extended with other kinds of models such as fuzzy logic. 3. Comparison Of The Simulation Tools As shown in Table 1, network simulators characteristics and their capabilities can be examined under the following aspects: Purpose: commercial, educational and private purposes to indicate the intended use. License: simulator open source (free) if you indicate whether a commercial product. Ease of Use: Graphical interface to support the flexibility of existing models and interfaces to enhance the new models can be added User Interface: Graphical user interface (GUI) to have Parallel Operation: Parallel simulator can run in a distributed environment Scalability: The maximum number of nodes that can be used in the simulation (Medium: thousands Good: Ten thousand, Very Good: hundreds of thousands) Programming language: programming language that specifies the simulator is written Documentation: Network simulator, presented in conjunction with / accessible documentation indicates Rate: indicates the operating speed of the simulation. Platform: simulator operating environment (operating system) indicates. Level Simulation (Abstraction): Simulation indicates the lowest level of abstraction. This level of package, the message transfer or may nodal. Properties OPNET QualNet NS-2 SSFNet OMNET DEVS Suite Purpose Commercial Commercial Educational , Resource Commercial, Resource Resource Specialized License Commercial Commercial Free Free Free Free Ease of Use Very Good Very Good Bad Good Good Good Flexibility Good Good Medium Good Very Good Very Good User Interface Good GUI Good GUI Poor GUI Good GUI Good GUI Good GUI 422 �Parallelism Yes Yes No Yes Yes Yes Scalability Medium Very Good Medium Very Good Good Good Programming Language Documentation C++ C++ Java, C++ C++ Java Very Good Good C++ OTcl Good Good Good Good Speed Bad Medium Medium Good Good Good Platform X window Unix Linux, Unix, Windows Windows Windows, Linux Simulation Level (Abstraction) Packet Level Linux, Unix, Windows Packet Level Packet Level IP Packet Packet level Packet Level and Table 1. Simulators comparison 4. Conclusions To choose between the existing hundreds network simulators is very difficult. In this study, modeling and simulation tools that used for studying on the network are examined, especially in network simulators used for training purposes as the advantages and disadvantages are analyzed. DEVS is also taken into consideration which is providing useful features for network community. In addition, this study can help to most researchers in the selection of appropriate network modeling and simulation tool. References [1] M.A. Rahman et al. / Simulation Modelling Practice and Theory 17 (2009) 1011–1031 [2]http://en.wikipedia.org/wiki/DEVS [3] Zeigler, B.P., Mittal, S., Modeling and Simulation of Ultra-large Networks: A Framework for New Research Directions, supported by NSF Grant ANI-0135530, ULN Workshop, July 2002 (addendum to the ULN Workshop 2001) {http://www.acims.arizona.edu/EVENTS/ULN/ULN_doc2.pdf } [4]. {http://qualnet.com/pdf/glomosim.pdf } [5].{http://www-static.cc.gatech.edu/computing/compass/pdns} [6] http://www.omnetpp.org/ [7] Bajaj, S., Breslau, L., Estrin, D., et al., Improving Simulation for Network Research, 1999, USC Computer Science Dept. Technical Report 99-702. [8] http://www.isi.edu/~johnh/PAPERS/Breslau00a.pdf [9] Richard M. Fujimoto, Kalyan Perumalla, Alfred Park, Hao Wu, Mostafa H. Ammar, George F. Riley. Large-Scale Network Simulation: How Big? How Fast?, Modeling, Analysis and Simulation of Computer Telecommunications Systems, 2003. MASCOTS 2003. 11th IEEE/ACM International Symposium on [10] B.P. Zeigler, H. Praehofer, T.G. Kim, “Theory of Modeling and Simulation,” Academic Press, 2000. [11] Zengin, A. “Dağıtık Simülasyon Sistemleri Đçin Yeni Bir Yönlendirme Algoritması ve Uygulaması” , Doktora Tezi, Fen Bilimleri Enstitüsü, Sakarya Üniversitesi, 2004 [12] Richard M. Fujimoto, Kalyan S. Perumalla and George F. Riley, “Network Simulation”, Morgan & Claypool, 2007 423 �[13] Ming Zhang , “Toward A Flexible And Reconfıgurable Dıstrıbuted Sımulatıon: A New Approach To Dıstrıbuted Devs” PhD Dissertation, Electrical and Computer Engr, University of Arizona, May. 2007.{http://acims6.eas.asu.edu/PUBLICATIONS/PDF/Thesis_Zhang.pdf} [14] Saurabh Mittal, “Devs Unified Process For Integrated Development And Testıng Of Servıce Orıented Archıtectures” PhD Dissertation, University of Arizona, 2007 [15] X. Liu and A. A. Chien, “Realistic Large-Scale Online Network Simulation”, Performance Computing Applications, 2006 International Journal of High [16] http://www.modelica.org [17] Zengin A, Ekiz H., Çobanoğlu B., Tuncel S., "Ağların Eğitimi ve Araştırılması için DEVS Tabanlı Simülatör Tasarımı ve Uygulaması" 5. Uluslararası Đleri Teknolojiler Sempozyumu (IATS’09), 13-15 Mayıs 2009, Karabük, Türkiye [18] Steenstrup, M. E. (Ed.). (1995). Routing in Communications Network. Prentice-Hall. [19] http://www.faqs.org/rfcs [20] R. Waupotitsch, S. Eidenbenz, L. Kroc, and J. Smith, “Multi-Scale Integrated Information and Telecommunications System (MIITS): First Results From A Large-Scale End-To-End Network Simulator”, wsc, pp.2132-2139, Proceedings of the 2006 Winter Simulation Conference, 2006 [21] William Buchanan, “Distributed Systems and Networks”, pp. 380-381, McGraw-Hill Pub., 2000 [22] Çakıroğlu, M. Doktora Tezi, “Kablosuz Algılayıcı Ağlar için Dinamik Kanal Atlamalı Güvenlik Sistemi Tasarımı”, Doktora Tezi, Fen Bilimleri Enstitüsü, Sakarya Üniversitesi, 2008 424 � 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. 538 Title A name given to the resource A Survey Of Network Modeling And Simulation Tools: Devs Comparison Author Author Çobanoğlu, Bülent Zengin, Ahmet Tüncel, Sinan Ekiz, Hüseyin Abstract A summary of the resource. Speed, hardware, cost, diversity of user demands and interoperability requirements of today’s network systems cause several difficulties in network research. In design phase, due to time and cost advantage of modeling and simulation science it is widely used by researchers working on network systems. In order to expedite and simplify the design process, to design and develop network simulation tools is an active research area. Today, many modeling and simulation tools are available in computer networks research and education. In this study, to assist researchers working on computer networks in the selection of modeling and simulation tools, several best-known simulators are selected and compared. Especially to examine the advantages and disadvantages of network simulators used for training purposes, an OSPF protocol implementation was devised to discuss strengths and weaknesses of simulators. At the same time, executing a general purpose DEVS based OSPF model in DEVS-Suite simulator; the advantages of the method are summarized. 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/fccba2c5a2f3c41325185b5a7c3b813b.pdf f71c5441f43dc5921cf7ca8ec30746e7 PDF Text Text The Sustainability Problems of Irrigation in Turkey Prof.Dr. Nizamettin Çiftçi Selçuk University Agricultural Faculty –Konya/Turkey nciftci@selcuk.edu.tr Assist.Prof.Dr. Bilal Acar Selçuk University Agricultural Faculty –Konya/Turkey biacar@selcuk.edu.tr Assoc.Dr. Ramazan Topak Selçuk University Agricultural Faculty –Konya/Turkey rtopak@selcuk.edu.tr Assist.Prof.Dr. Muhittin Çelebi Selçuk University Çumra MYO –Konya/Turkey mcelebi@selcuk.edu.tr Abstract: Water, a vital source for humanity and all living things throughout the history, has contributed to the formation of civilizations. It has the economical value as well as social and cultural characteristics. The land and water potentials have reduced due to rapid growing in urbanization and industrialization in Turkey. Water quality has begun to deteriorate as a result of environmental factors. Irrigated land also has been increasing every year. Turkey has arid and semi-arid climate characteristics and annual average precipitation is almost 643 mm. The total annual available surface and groundwater potential is 110 km3. Annual water potential per capita is 2565 m3, and available water potential is 1517 m3 in Turkey. According to the water per capita, Turkey is a waterstress country. Turkey covers a total land area of 78 million hectares, of which 28 million hectares is cultivated land. The economically irrigable land is 8.5 million hectares under the present condition. According to the 2009 records, irrigated land is 5.1 million hectares. Presence of large number of fragmented and small farm lands, scant water supplies, poor and insufficient infrastructures in irrigation networks, deficiency in irrigation water management and drainage problems have affected negatively to the sustainability of irrigation in Turkey. Keywords: Water, land and water potentials, available water potential, sustainable irrigation. Introduction Water is the prime element for human life on earth but, it is not exist in every place, amount and time on earth. It is the strategic natural resource and will be also very important. The utilization of water resources and related studies are as old as human history. In general, agriculture is the most water user sector in the world. The increase of the population has resulted more water requirement. There is a serious water scarcity and water stress problems in 80 countries with 40% of population. It is estimated that the world population will reach about to the 8.5 billion in the year of 2025. This shows that population will increase as 35-40% between current and 2025 year. Food problems associated by irrigation will be very serious in future. In present, water scarcity problems have been observed mainly in African and Middle East Countries as well as highly populated Asian Countries (Çiftçi et al 2009a; Çiftçi et al. 2009b). 191 �Water resources are 1.36 billion km3 in the world. Of this amount, 97 % is saline water with only 35 million km3 of this is fresh water (3%). The 68.3% of this is in poles as a freeze form and 31.4% of is as soil moisture or groundwater form. The 0.3% of total fresh water in the world is streams, lakes and swamps areas (Çiftçi & Kutlar 2007). Presence of non-uniform water distribution in world causes some problems. The reason of it water distribution is difference in hydrological cycle in different places. The development level of countries has very important role in water consumption. As we mentioned above in most countries, agriculture is the highest water user. Water is used for three different purposes. These are; - drinking and usage (in residents) - agriculture, and 3- industry . The averages of water use in the world are 70%, 20% and 10% in agriculture, industry and drinking and usage, respectively. Increase in water use has lead to reduction in water quality. Human activities may cause two type of contamination of water resources. It is very important for human health, especially for children, to use the fresh water at present. In the world, almost one million people in 40 countries have used the poor quality water. Increment in irrigated lands will also increase the water consumption. Turkey is situated in 36o-42o North latitude and 26o-45o East longitude so that it has a unique geographical and cultural position. The length of the land border is 2949 km and coastal boundary of 7816 km with total of 10765 km. The neighbors are Greece and Bulgaria in West; Georgia, Armenia, Azerbaijan, Iran in East and ; Iraq, Syria in South. Ankara, capital city of Turkey, is 875 m above the sea level (Ulus) (Anonymous 2009). The construction of huge irrigation networks started after 1950's and had very importance. These big irrigation projects are irrigated by Menderes, Gediz, Seyhan, Ceyhan, Yeşilırmak, Kızılırmak, Fırat and Dicle Rivers. The project consisted of Dicle and Fırat is called as Southeastern Anatolian Project (SAP) and is one of the huge projects in the world (Kara 2005). Turkey can be considered a ` water-stressed ‘country according to the water resources. It is estimated that available water potential of Turkey will be fully used after 20 years. Land and Water Potential in Turkey Land Potential of Turkey Agricultural production is the function of arable land and soil fertility in such area. It means that not only land size is important but also fertility of soil is very important. Turkey covers 28 million hectares of cultivated land. To make an irrigation project, arable land and water supply as well as suitability of arable land for irrigation are necessary. The land potential with the slope lower than 6% is 16.5 million hectares in Turkey. The 8.5%of this is economically irrigable land. The irrigated land at present is 5.1 million ha (Çiftçi et al. 2008) are presented in Table 1 (Kara 2005, Çiftçi & Kutlar 2007). Land Status 1. 2. 3. 4. • • • • Area (million ha) Arable land Land for field crop production Land for vineyard and Horticulture Land for meadow Irrigable Land Economically irrigable land Land suitable for irrigation after the some improvement Currently irrigated land 26.6 16.0 2.6 8.0 16.5 8.5 8.0 5.1 Table 1. The utilization patterns of lands in Turkey 192 �As seen from the Table 1 that almost 8 million ha land is exposed to fallow. As a result of this, although arable land potential is 26.6 ha, only 18.6 ha of it is under cultivation. Water Potential of Turkey In general, the climate is semi-arid in Turkey. Due to the surrounding with three directions of Turkey by seas, high mountains lies on parallel to the sea costs, rapid changes in elevation and distance to the coasts result in climate changes in small distances. Turkey has different climate characteristics due to the geographical position. In the exception of the East Black Region, the climate varies from arid to semiarid. The climate changes depend upon the seasons and regional differences. There are total 26 big river basins in Turkey. There is difference between the basins in respect to the rainfall. The annual rainfalls are 350mm and 2400m for Middle Anatolia Region and East Black Sea, respectively. Water potential of a country is the sum of surface and groundwater. As it is known that source of the water in earth is rainfall. The annual average precipitation in Turkey is almost 643 mm, corresponding to a volume of 501 km3 and the annual runoff is 186 km3. The 274 km3 of total precipitation is lost by transpiration and evaporation. Another 41 km3 of total precipitation feeds the underground water system and 186 km3 end up as surface runoff. The annual consumable surface water potential is computed as 98 km3 and extractable groundwater potential of 12 km3 should be added to this, bringing the total annual consumable potential to 110 km3 (Figure 1) (Kara 2005; Çiftçi et al. 2009b). A nn ual average precipitation: 501 k m 3 Groun dwater: 69 km 3 From precipitation : 158 km 3 Surface run off (dom estic): 186 km 3 Con sumable: 12 km 3 C on sumable: Consumable: 95 km 3 95 km 3 Flow from n eigh boring countries: 7 km 3 C on sumable: 3 km 3 Total surface run off: 193 km 3 Con sumable: 98 km 3 T otal con sumable water resources: 110 k m 3 Figure 1. Water Potential of Turkey. 193 E vaporation: 274 km 3 �Water supply is used for different purposes such as energy production, irrigation, and others. By considering increase in population requirement to the water due to the irrigation, drinking and usages with demands to water in developed industry and tourism sector, water consumption estimation has been performed in Turkey. The water consumption estimation performed by sector base, economically irrigable land potential of Turkey (8.5 million hectares) will be completely opened to the irrigation by construction of irrigation networks in the year of 2030 and also estimated that irrigation water uses will reach the 71.5 km3. On the other hand, the main target is to minimize the water uses as 65% in total water uses by using the modern irrigation technologies in 2030. Thus, in sector base, all 110 km3 water will be used completely in 2030 (Table 2). Usages of fresh water potential and situation in the future are given in Figure 2 (Anonymous 2009). Year Total water use, km3 35.645 38.900 39.300 40.000 110.000 1999 2000 2001 2002 2030 Development, % irrigation % 34 35 36 38 100 26.415 29.200 29.300 32.000 71.500 75 75 75 75 65 Water Use (km3) Drinking% usage 5.520 15 5.700 10 5.800 15 6.000 15 25.300 23 industry % 3.710 4.000 4.200 4.300 13.200 11 11 10 10 12 Table 2. The Usage of Water in Sector Base in Turkey (Anonymous 2002) water usage, km3 80 irrigation drinking-usage 60 industry 40 20 0 1 2 3 4 5 Years Figure 2. Water Usage Ratios in Turkey Water-rich country can be defined as the country that has the water potential of 10 000 m3/person per year. According record of 2009, it is estimated that the population is about to the 72.5 millions in Turkey. The annual water potential per capita is 2565 m3. The available water potential per capita is 1375 m3/person/year. Thus, Turkey can be considered a ` water-stressed ‘country by comparison to the some countries. According to the Government Statistical Institute records, it is estimated that the population will reach about to the 80 millions in Turkey in the year of 2025 year. The available water potential per capita will reduce to the 1375 m3/person/year. It is possible to estimate the importance of water potential by considering some factors such as present growth rate and variations in water consumption habits. This estimation is valid under the conditions of transferring the present resources without any destruction up to 2025. Therefore, in order to transfer the water resources properly and sufficiently to the next generation, water resources should be conserved best and used efficiently. 194 �Water Management and Sustainability Problems in Turkey The residential and industrial water uses are getting increasing and there is a competition between these two sectors and agricultural use. To improve the efficiency of irrigation, there is a need a irrigation method covered high crop yield, elements of modern irrigation technologies. Water Management Water management is defined as development , distribution and uses of water resources. Main goal in water management is improvement of the farmers income. This can be obtained by effective water distributions and uses. Water management is briefly described as the distribution and uses of water. The number of organizations are responsible in water management at Turkey. Similar responsibilities may result conflict and problems in practice. However, there are two important organizations for water management namely General Directorate of State Hydraulic Works (GDSHW) and City Private Management (CPM) are two government organizations. According to 2008 records, the area for opened to the irrigation is about 5.1 million hectares, and 2.9 million hectares and 1.3 million hectares have been irrigated by GDSHW and General Directorate of Rural Services and Public (GDRS), respectively. The rest 0.9 million hectare has opened to irrigation by farmers. The 6.5 million hectors of the total 8.5 million economically irrigable land will be managed by GDSHW in 2030. The other 1.5 and 0.5 million hectare land will be irrigated by other government organizations and public sector (Anonymous 2009). There are different management types in Turkey. These are; Government irrigation management: The first big government irrigation manager is a GDSHW and responsible for constructions of dams. These dams are not so much so that the organization has managed, maintenance-repair of such dams. Due to the not transfer of huge structures and difficulty in management those structures have only managed by GDSHW. Management with local managers; In small places where the not availability of irrigation cooperatives and water user associations (WUA) or even making the organization but not properly managed small areas, municipal or local managers or community have managed the systems. In local management, poor management of irrigation structures and not having the sufficiently information and use the irrigation systems as financial sector are the deficiency of local management. The efficiency of this management is low. Public Irrigation; Farmers are the manager in this system and is small or medium scale irrigation management. There is transfer problem in this management. Farmers solve their problem by using their facilities. They are responsible for them and effectiveness is parallel with the their experiences. Irrigation Cooperatives- Water management; Irrigation cooperatives were built with 1163 number by cooperative policy. The components of cooperative are General Community, Management Community and Control Unit. In addition, Irrigation Cooperative Superior Community and Irrigation Cooperative Central Association are available (Çiftçi et al. 2008). The purposes of irrigation cooperatives are determined by negotiations and these are follows (Çiftçi 1991) ; • These cooperatives may construction of irrigation structures for agricultural uses, management, maintenance-repair, land consolidation if necessary, supply credit in water obtaining points. • The number of the irrigation cooperative was 2386 in 2006 in Turkey and members in cooperatives, number of the association and central association were 280043, 7 and 1, respectively (Anonymous 2006). The areas served by cooperatives (1307852 ha) are presented in Table 5. • Irrigation cooperatives have appropriate management model for small-medium sized farms as well as farmers' self-government democratic management, ease of self- 195 �regulatory and public administration by the control status and have the capacity of meeting maintenance and repair expenses. However, they have the some disadvantages such as members of farmers in cooperatives could not detect the purposes of these organizations, having financially, legally and technically inadequacy. Water Use Associations (WUA) ; WUA is built by local management permission and it has the government characteristics. Personal are employed like the government criteria. However, the members of the decision makers and managers are selected by farmers in WUA. WUA can be built by required village and municipality. Each WUA has the special procedures. WUA community and community members are present in accordance of their procedures. The general secretary must be agriculture engineer and organizes works as if head of the WUA. The management of WUA is conducted by legislation, management and official decisions. GDSHW has transferred 2.090.330 ha areas of total opened irrigation of 2.9 million ha according to the 2008. The 1.883.702 ha area has transferred to the 362 WUA. GDSHW has transferred 90% of opened irrigation to the WUA (Anonymous 2008). Water Supply Irrigated Land (ha) % Small Dam 143385 10.96 Surface 858837 65.67 Groundwater 30563 23.37 Total 1307852 100 Table 3. Areas Served by Cooperatives In considering the total 5.1 million irrigated areas in Turkey, 37% of it has transferred to the WUA. There is some problems during transferring of irrigation Networks in Turkey. These are mostly legislation, financial and technical problems. Problems in irrigation management Development and management policies in soil and water resources should be rereviewed in Turkey. For sustainable irrigated agriculture, water management and management policies of government, irrigation cooperatives and WUA should be reviewed and required regulations should be performed. In recently, government is the exception for water management and it can be responsibilities of contributions to the water users and guide. The purposes of transferring irrigation water management are follows: • Facilitates farmers attendance and responsibility in management • Local management in determined rules by farmers, • Self inspection by own members, • Reduction in management-maintenance and meeting the outcomes by farmer organizations. Cooperatives are mostly ignored in irrigation water management. However, in small-scale production countries cooperatives are much more effective. Number Ratios (%) Area (ha) Ratios (%) WUA 362 42,7 1 883 702 90,1 Irrigation cooperative 100 11,8 94 148 4,5 Municipal 154 18,2 70 612 3,4 Village Community 225 26,5 40 198 1,9 Organizations 196 �Others 6 0,8 1 670 0,1 TOTAL 847 100 2 090 330 100 Table 4. Transferred Areas and Organizations (Anonymous 2008 ) Water management has transferred to the Village Community, Municipal, WUA, Services performed helps to villages, Cooperatives and Universities. The top rank is WUA between these. Various problems may be observed in irrigation water management in Turkey. These are as follows; • Deficiency in attendance of farmers to the irrigated agriculture investments and problems in re obtaining of charges, • Deficiencies in water conveyance, distribution and applications and excess water losses, • Postpone problems such as in land leveling, consolidation, electrification, • Observation of some problems in reduced yield, salinity and drainage, • Surface and groundwater contaminations via agricultural chemicals, food nutrients and industrial wastes, • Low irrigation efficiency and irrigation ratios, excess water losses and low irrigation performance due to the surface irrigation methods, • Incorrect crop patterns in region, • Maintenance-repair problems in irrigation networks, • Postpone in maintenance-repair works after the transfer or irrigation management to the WUA and irrigation cooperatives, • Financial, legislation, management and education problems in irrigation cooperatives and WUA. References Anonymous. (2002). General Directorate of Sate Hydraulic Works (GDSHW) http://www.dsi.gov.tr/ (in Turkish). Anonymous. (2006). Teşkilatlanma ve Destekleme Genel Müdürlüğü TEDGEM - Ankara Turkish). www.tedgem.gov.tr (in Anonymous. (2008). General Directorate of Sate Hydraulic Works (GDSHW) http://www.dsi.gov.tr/ (in Turkish). Anonymous. (2009). General Directorate of Sate Hydraulic Works (GDSHW) http://www.dsi.gov.tr/ (in Turkish). Çiftçi, N., Acar, B., Şahin, M., Yaylalı, I., & Yavuz, D. (2009a). Land and Water Potentials of Turkey and Major Problems in Irrigated Agriculture, Proceedings International Conference on Lakes and Nutrient Loads, 2009, Pocradec. 305-310. Çiftçi, N., Acar, B., Yaylalı, I & Çivicioğlu, N. (2009b). Groundwater Potential Usage and Contamination Problems in Turkey under Global Warming Period, Proceedings International Conference on Lakes and Nutrient Loads, 2009, Pocradec. 456-462. Çiftçi, N & Kutlar, Đ. (2007). Water potential and water resources of Konya Plain. Journal of Konya Ticaret Borsası, 24, 34-37 (in Turkish Çiftçi,N.,Kutlar,Đ., & Demir, N. (2008). Konya Đli Sulama Kooperatiflerinin Sulamadaki Etkinliği. Konya Kapalı Havzası Yer Altı Suyu ve Kuraklık Konferansı, 11-12 Eylül, 2008. S. 57-66. Konya (in Turkish) Çiftçi, N. (1991). Orta Anadolu Toprak ve Su Kooperatifleri Sulama işletmelerinde Görülen Sorunlar, Karınca Kooperatif Postası, No. 653, Ankara. Kara, M. (2005). Irrigation and irrigation systems. Selçuk University. Agricultural Faculty, ISBN 975-448-177-6: Konya-Turkey (in Turkish). 197 � 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. 378 Title A name given to the resource The Sustainability Problems of Irrigation in Turkey Author Author Çiftçi, Nizamettin Acar, Bilal Topak, Ramazan Çelebi, Muhittin Abstract A summary of the resource. Water, a vital source for humanity and all living things throughout the history, has contributed to the formation of civilizations. It has the economical value as well as social and cultural characteristics. The land and water potentials have reduced due to rapid growing in urbanization and industrialization in Turkey. Water quality has begun to deteriorate as a result of environmental factors. Irrigated land also has been increasing every year. Turkey has arid and semi-arid climate characteristics and annual average precipitation is almost 643 mm. The total annual available surface and groundwater potential is 110 km3. Annual water potential per capita is 2565 m3, and available water potential is 1517 m3 in Turkey. According to the water per capita, Turkey is a waterstress country. Turkey covers a total land area of 78 million hectares, of which 28 million hectares is cultivated land. The economically irrigable land is 8.5 million hectares under the present condition. According to the 2009 records, irrigated land is 5.1 million hectares. Presence of large number of fragmented and small farm lands, scant water supplies, poor and insufficient infrastructures in irrigation networks, deficiency in irrigation water management and drainage problems have affected negatively to the sustainability of irrigation in Turkey. 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)