60 research outputs found
A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey
[EN] The paper aims to compare the results of the selection/choice of cream separators by using multi-criteria decision-making methods in an integrated manner for an enterprise with a dairy processing capacity of 80 to 100 tons per day operating in the Turkish food sector. A total of 7 alternative products and 7 criteria for milk processing were determined. Criterion weights were calculated using entropy method and then integrated into TOPSIS (Technique for Order Preference by Similarity to Ideal Solutions), GRA (Grey Relational Analysis) and COPRAS (Complex Proportional Assessment) methods. Sensitivity analyses were carried out on the results obtained from the three methods to check for their reliability. At the end of the study, similar alternative and appropriate results were found from the TOPSIS and COPRAS methods. However, different alternative but appropriate or suitable results were obtained from the GRA method. Sensitivity analysis of the three methods showed that all the methods used were valid. In the review of available and related literature, very few studies on machine selection in the dairy and food sector in general were found. For this reason, it is thought that the study will contribute to the decision-making process of companies in the dairy sector in their choice of machinery selections. As far as is known, this paper is the first attempt in extant literature to compare in an integrated manner the results of TOPSIS, COPRAS and GRA methods considered in the study.Özcan, S.; Çelik, AK. (2021). A comparison of TOPSIS, grey relational analysis and COPRAS methods for machine selection problem in the food industry of Turkey. International Journal of Production Management and Engineering. 9(2):81-92. https://doi.org/10.4995/ijpme.2021.14734OJS819292Ahmed, M., Qureshi, M.N., Mallick, J., Kahla, N.B. (2019). Selection of sustainable supplementary concrete materials using OSM-AHP-TOPSIS approach. Advances in Materials Science and Engineering, 2019, 1-12. https://doi.org/10.1155/2019/2850480Aloini, D., Dulmin, R., Mininno, V. (2014). A peer IF-TOPSIS based decision support system for packaging machine selection. Expert Systems with Applications, 41(5), 2157-2165https://doi.org/10.1016/j.eswa.2013.09.014Alpay, S., Ihpar, M. (2018). Equipment selection based on two different fuzzy multi criteria decision making methods: Fuzzy TOPSIS and fuzzy VIKOR. Open Geosciences, 10(1), 661-677. https://doi.org/10.1515/geo-2018-0053Antucheviciene, J., Zavadskas, E.K., Zakarevičius, A. (2012). Ranking redevelopment decisions of derelict buildings and analysis of ranking results. Economic Computation and Economic Cybernetics Studies and Research, 46(2), 37-63. Retrieved June 08, 2020 from http://www.ecocyb.ase.ro/22012/Edmundas%20ZAVADSKAS%20_DA_.pdfAyağ, Z., Özdemir, R.G. (2006). A fuzzy AHP approach to evaluating machine tool alternatives. Journal of Intelligent Manufacturing, 17(2), 179-190. https://doi.org/10.1007/s10845-005-6635-1Belton, V., Stewart, T.J. (2002). Multiple criteria decision analysis: An integrated approach. Berlin: Kluwer Academic Publishers.https://doi.org/10.1007/978-1-4615-1495-4Camcı, A., Temur, G.T., Beşkese, A. (2018). CNC router selection for SMEs in woodwork manufacturing using hesitant fuzzy AHP method. Journal of Enterprise Information Management, 31(4), 529-549. https://doi.org/10.1108/JEIM-01-2018-0017Çakır, S. (2018). An integrated approach to machine selection problem using fuzzy SMART-fuzzy weighted axiomatic design. Journal of Intelligent Manufacturing, 29(7), 1433-1445. https://doi.org/10.1007/s10845-015-1189-3Çelen, A. (2014). Comparative analysis of normalization procedures in TOPSIS method: With an application to Turkish deposit banking market. Informatica, 25(2), 185-208. https://doi.org/10.15388/Informatica.2014.10Chandan, R.C. (2008). Dairy Processing and Quality Assurance: An Overview. Ramesh C. Chandan, Arun Kilara, Nagendra Shah (Eds.), In Dairy Processing and Quality Assurance (pp. 1-40). New Jersey: Wiley-Blackwell. https://doi.org/10.1002/9780813804033Chatterjee, P., Chakraborty, S. (2014). Investigating the effect of normalization norms in flexible manfacturing sytem selection using Multi-Criteria Decision-Making methods. Journal of Engineering Science and Technology Review, 7(3), 141-150. https://doi.org/10.25103/jestr.073.23Clarke, M.P., Denby, B., Schofield, D. (1990). Decision making tools for surface mine equipment selection. Mining Science and Technology, 10(3), 323-335. https://doi.org/10.1016/0167-9031(90)90530-6Datta, S., Sahu, N., Mahapatra, S. (2013). Robot selection based on grey-MULTIMOORA approach. Grey Systems: Theory and Application, 3(2), 201-232. https://doi.org/10.1108/GS-05-2013-0008Deng, H., Yeh, C.H., Willis, R. J. (2000). Inter-company comparison using modified TOPSIS with objective weights. Computers and Operations Research, 27(10), 963-973. https://doi.org/10.1016/S0305-0548(99)00069-6Doğan, M., Aslan, D., Aktar, T., Sarac, M.G. (2016). A methodology to evaluate the sensory properties of instant hot chocolate beverage with different fat contents: multi-criteria decision-making techniques approach. European Food Research and Technology, 242(6), 953-966. https://doi.org/10.1007/s00217-015-2602-zErtuğrul, İ., Güneş, M. (2007). Fuzzy multi-criteria decision making method for machine selection. P. Melin, O. Castillo, E.G. Ramirez, J. Kacprzyk and W. Pedrycz (Eds.), In Analysis and Design of Intelligent Systems Using Soft Computing Techniques (pp. 638-648). Berlin, Germany: Springer. https://doi.org/10.1007/978-3-540-72432-2_65Ertuğrul, İ., Öztaş, T. (2015). The application of sewing machine selection with the multi-objective optimization on the basis of ratio analysis method (MOORA) in apparel sector. Textile and Apparel, 25(1), 80-85. Retrieved May 17, 2020 from https://dergipark.org.tr/tr/pub/tekstilvekonfeksiyon/issue/23647/251887FAO. (2019a). Dairy Market Review. FAO Publishing, Rome.FAO. (2019b). Food Outlook - Biannual Report on Global Food Markets. FAO Publishing, Rome.Feizabadi, A., Doolabi, M.S., Sadrnezhaad, S.K., Zafarani, H.R., Doolabi, D.S. (2017). MCDM selection of pulse parameters for best tribological performance of Cr-Al2O3 nano-composite co-deposited from trivalent chromium bath. Journal of Alloys and Compounds, 727, 286-296. https://doi.org/10.1016/j.jallcom.2017.08.098Feng, C.M., Wang, R.T. (2000). Performance evaluation for airlines including the consideration of financial ratios. Journal of Air Transport Management, 6(3), 133-142. https://doi.org/10.1016/S0969-6997(00)00003-XGuo, X., Sun, Z. (2016). A novel evaluation approach for tourist choice of destination based on grey relation analysis. Scientific Programming, 2016, 1-10. https://doi.org/10.1155/2016/1812094Gurmeric, V.E., Dogan, M., Toker, O.S., Senyigit, E., Ersoz, N.B. (2013). Application of different multi-criteria decision techniques to determine optimum flavour of prebiotic pudding based on sensory analyses. Food and Bioprocess Technology, 6(10), 2844-2859. https://doi.org/10.1007/s11947-012-0972-9Hwang, C.L., Yoon, K. (1980). Multiple attribute decision making methods and applications: A state-of-the-art survey. New York: Springer-Verlag.Jahan, A., Yazdani, M., Edwards, K.L. (2021). TOPSIS-RTCID for range target-based criteria and interval data. International Journal of Production Management and Engineering, 9(1), 1-14. https://doi.org/10.4995/ijpme.2021.13323Kabak, M., Dağdeviren, M. (2017). A hybrid approach based on ANP and Grey Relational Analysis for machine selection. Technical Gazette, 24(Supplement 1), 109-118. https://doi.org/10.17559/TV-20141123105333Kang, H.Y., Lee, A.H.I., Yang, C.Y. (2012). A fuzzy ANP model for supplier selection as applied to IC packaging. Journal of Intelligent Manufacturing, 23(5), 1477-1488.https://doi.org/10.1007/s10845-010-0448-6Karaman, S.,Toker, Ö.S., Yüksel, F., Çam, M., Kayacier, A., Dogan, M. (2014). Physicochemical, bioactive, and sensory properties of persimmon-based ice cream: Technique for order preference by similarity to ideal solution to determine optimum concentration. Journal of Dairy Science, 97(1), 97-110. https://doi.org/10.3168/jds.2013-7111Karim, R., Karmaker, C.L. (2016). Machine selection by AHP and TOPSIS methods. American Journal of Industrial Engineering, 4(1), 7-13. https://doi.org/10.12691/ajie-4-1-2Kumru, M., Kumru, P.Y. (2015). A fuzzy ANP model for the selection of 3D coordinate-measuring machine. Journal of Intelligent Manufacturing, 26(5), 999-1010. https://doi.org/10.1007/s10845-014-0882-yNguyen, H.T., Dawal, S. Z. Md., Nukman, Y., Aoyama, H. (2014). A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes. Expert Systems with Applications, 41(6), 3078-3090. https://doi.org/10.1016/j.eswa.2013.10.039OECD/FAO. (2019). OECD-FAO Agricultural Outlook 2019-2028. OECD Publishing, Paris.Önüt, S., Kara, S.S., Işik, E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2), 3887-3895. https://doi.org/10.1016/j.eswa.2008.02.045Özceylan, E., Kabak, M., Dağdeviren, M. (2016). A fuzzy-based decision making procedure for machine selection problem. Journal of Intelligent and Fuzzy Systems, 30(3), 1841-1856. https://doi.org/10.3233/IFS-151895Özdağoğlu, A., Yakut, E., Bahar, S. (2017). Machine selection in a dairy product company with Entropy and SAW methods integration. Faculty of Economics and Administrative Sciences Journal, 32(1), 341-359. https://doi.org/10.24988/deuiibf.2017321605Özgen, A., Tuzkaya, G., Tuzkaya, U.R., Özgen, D. (2011). A multi-criteria decision making approach for machine tool selection problem in a fuzzy environment. International Journal of Computational Intelligence Systems, 4(4), 431-445. https://doi.org/10.1080/18756891.2011.9727802Ozturk, G., Dogan, M., Toker, O.S. (2014). Physicochemical, functional and sensory properties of mellorine enriched with different vegetable juices and TOPSIS approach to determine optimum juice concentration. Food Bioscience, 7, 45-55. https://doi.org/10.1016/j.fbio.2014.05.001Pang, B., Bai, S. (2013). An integrated fuzzy synthetic evaluation approach for supplier selection based on analytic network process. Journal of Intelligent Manufacturing, 23(5), 163-174. https://doi.org/10.1007/s10845-011-0551-3Paramasivam, V., Senthil, V., Ramasamy, N.R. (2011). Decision making in equipment selection: an integrated approach with digraph and matrix approach, AHP and ANP. The International Journal of Advanced Manufacturing Technology, 54(9-12), 1233-1244. https://doi.org/10.1007/s00170-010-2997-4Pavličić, D.M. (2001). Normalisation affects the results of MADM methods. Yugoslav Journal of Operations Research, 11(2), 251-265. Retrieved May 6, 2020 from http://scindeks.ceon.rs/article.aspx?artid=0354-02430102251PSamanta, B., Sarkar, B., Mukherjee, S.K. (2002). Selection of opencast mining equipment by a multi-criteria decision-making process. Mining Technology, 111(2), 136-142. https://doi.org/10.1179/mnt.2002.111.2.136Seçme, N.Y., Bayrakdaroğlu, A., Kahraman, C. (2009). Fuzzy performance evaluation in Turkish Banking Sector using Analytic Hierarchy Process and TOPSIS. Expert Systems with Applications, 36(9), 11699-11709. https://doi.org/10.1016/j.eswa.2009.03.013Sharma, A., Yadava, V. (2011). Optimization of cut quality characteristics during nd:yag laser straight cutting of ni-based superalloy thin sheet using grey relational analysis with entropy measurement. Materials and Manufacturing Processes, 26(12), 1522-1529. https://doi.org/10.1080/10426914.2011.551910Shih, H. S., Shyur, H.J., Lee, E.S. (2007). An extension of TOPSIS for group decision making. Mathematical and Computer Modelling, 45(7-8), 801-813. https://doi.org/10.1016/j.mcm.2006.03.023Stanujkic, D., Đorđević, B., Đorđević, M. (2013). Comparative analysis of some prominent MCDM methods: A case of ranking Serbian Banks. Serbian Journal of Management, 8(2), 213-241. https://doi.org/10.5937/sjm8-3774Štirbanović, Z., Stanujkić, D., Miljanović, I., Milanović, D. (2019). Application of MCDM methods for flotation machine selection. Minerals Engineering, 137, 140-146. https://doi.org/10.1016/j.mineng.2019.04.014Sun, C.C. (2014). Combining grey relation analysis and entropy model for evaluating the operational performance: An empirical study. Quality and Quantity, 48(3), 1589-1600. https://doi.org/10.1007/s11135-013-9854-0Taha, Z., Rostam, S. (2011). A fuzzy AHP-ANN-based decision support system for machine tool selection in a flexible manufacturing cell. International Journal of Advanced Manufacturing Technology, 57(5-8), 719-733. https://doi.org/10.1007/s00170-011-3323-5Temiz, I., Çalış, G. (2017). Selection of construction equipment by using multi-criteria decision making methods. Procedia Engineering, 196, 286-293. https://doi.org/10.1016/j.proeng.2017.07.201Tosun, N. (2006). Determination of optimum parameters for multi-performance characteristics in drilling by using grey relational analysis. The International Journal of Advanced Manufacturing Technology, 28(5-6), 450-455. https://doi.org/10.1007/s00170-004-2386-yUğur, L.O. (2017). Application of the VIKOR multi-criteria decision method for construction machine buying. Journal of Polytechnic, 20(4), 879-885. https://doi.org/10.2339/politeknik.369058Ulubeyli, S., Kazaz, A. (2009). A multiple criteria decision-making approach to the selection of concrete pumps. Journal of Civil Engineering and Management, 15(4), 369-376. https://doi.org/10.3846/1392-3730.2009.15.369-376Vafaei, N., Ribeiro, R.A., Camarinha-Matos, L.M. (2018). Data normalisation techniques in decision making: Case study with TOPSIS method. International Journal of Information and Decision Sciences, 10(1), 19-38. https://doi.org/10.1504/IJIDS.2018.090667Vatansever, K., Kazançoğlu, Y. (2014). Integrated usage of fuzzy multi criteria decision making techniques for machine selection problems and an application. International Journal of Business and Social Science, 5(9), 12-24. https://doi.org/10.1504/IJIDS.2018.090667https://doi.org/10.1504/IJIDS.2018.090667Wang, T.C., Lee, H.D. (2009). Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Systems with Applications, 36(5), 8980-8985. https://doi.org/10.1016/j.eswa.2008.11.035Wu, J., Sun, J., Liang, L., Zha, Y. (2011). Determination of weights for ultimate cross efficiency using Shannon entropy. Expert Systems with Applications, 38(5), 5162-5165. https://doi.org/10.1016/j.eswa.2010.10.046Wu, W., Peng, Y. (2016). Extension of grey relational analysis for facilitating group consensus to oil spill emergency management. Annals of Operations Research, 238(1-2), 615-635. https://doi.org/10.1007/s10479-015-2067-2Wu, Z., Ahmad, J., Xu, J. (2016). A group decision making framework based on fuzzy VIKOR approach for machine tool selection with linguistic information. Applied Soft Computing, 42, 314-324. https://doi.org/10.1016/j.asoc.2016.02.007Yazdani-Chamzini, A., Yakhchali, S.H. (2012). Tunnel Boring Machine (TBM) selection using fuzzy multicriteria decision making methods. Tunnelling and Underground Space Technology, 30, 194-204. https://doi.org/10.1016/j.tust.2012.02.021Yılmaz, B., Dağdeviren, M. (2010). Comparative analysis of PROMETHEE and fuzzy PROMETHEE methods in equipment selection problem. Journal of the Faculty of Engineering and Architecture of Gazi University, 25(4), 811-826. Retrieved May 6, 2020 from https://avesis.gazi.edu.tr/yayin/989e528e-9184-4d8e-8970-fccfabbbed73/comparative-analysis-of-promethee-and-fuzzy-promethee-methods-in-equipment-selection-problemYılmaz, B., Dağdeviren, M. (2011). A combined approach for equipment selection: F-PROMETHEE method and zero-one goal programming. Expert Systems with Applications, 38(9), 11641-11650. https://doi.org/10.1016/j.eswa.2011.03.043Zavadskas, E.K., Kaklauskas, A., Banaitis, A., Kvederyte, N. (2004). Housing credit access model: The case for Lithuania. European Journal of Operational Research, 155(2), 335-352. https://doi.org/10.1016/S0377-2217(03)00091-2Zhang, H., Gu, C.L., Gu, L. W., Zhang, Y. (2011). The evaluation of tourism destination competitiveness by TOPSIS and information entropy: A case in the Yangtze River Delta of China. Tourism Management, 32(2), 443-451. https://doi.org/10.1016/j.tourman.2010.02.00
Evaluation of the Effect of Body Position on Intraocular Pressure Measured with Rebound Tonometer
Objectives:It is important to determine variables that influence intraocular pressure (IOP) measurement. This study aimed to evaluate the effect of body position on IOP.Materials and Methods:The study included 52 right eyes of 52 patients who presented to the ophthalmology department of our hospital and had no ocular disease except refractive errors. IOP was measured with an Icare PRO tonometer while patients were in sitting, standing, and supine positions, with intervals of 10 minutes between the positions. Correlations between the results were evaluated using Spearman’s correlation analysis and Wilcoxon tests.Results:Thirty-six of the 52 patients were female, 16 were male. Mean age was 31.65±6.30 (23-47) years. Mean IOP values in the sitting, standing, and lying positions were 17.76±3.41 (12.70-25.60) mmHg, 17.10±3.27 (11.50-25.20) mmHg, and 18.46±4.67 (10.50-29.40) mmHg, respectively. There were no statistically significant differences between measurements taken in the different positions (p=0.112, p=0.472, p=0.071). We observed that there was no relationship between age and body position (p>0.45, p>0.79, p>0.77) or between gender and position (p>0.59, p>0.69, p>0.54).Conclusion:Gender and age had no effect on IOP measured in different body positions. There were also no significant differences between IOP values measured in the different positions. Therefore, we believe the portable Icare PRO tonometer can be used for patients who are confined to bed and will provide IOP measurements that are concordant with values obtained while sitting
Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study
Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat
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Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study
Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat
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Correction to: Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study
The original version of this article unfortunately contained a mistake
Kurumsal sürdürülebilirliğin finansal performans üzerindeki etkisinde AR-GE yoğunluğunun aracı rolü
Özellikle son yıllarda görülen yangınlar, kuraklıklar, sel ve hortum felaketleri vb. iklim değişikliğinin sonuçları bariz bir şekilde görülmeye başlanmış ve insanlarda sürdürülebilirlik konusundaki farkındalık ciddi bir artış göstermiştir. Benzer şekilde COVID 19 pandemisiyle birlikte tüm dünyadaki salgın koşullarının iyileştirilmesinin özellikle az gelişmiş ülkelere sosyal desteklerin sağlanmasıyla gerçekleşebileceği net bir şekilde görülmüştür. Bu iki gelişme birlikte değerlendirildiğinde uzun yıllardır öenmi gittikçe artan sürdürülebilirlik düşüncesinin bir göstergesi olduğu düşünülebilir. Bu sebeple çalışma kapsamında sürdürülebilirliğin firmalar düzeyindeki karşılığı olan kurumsal sürdürülebilirlik uygulamalarının finansal performans üzerindeki etkisinde Araştırma ve Geliştirme faaliyetlerinin aracı rolünün belirlenmesi amaçlanmıştır. Bu amaçla Türkiye’de faaliyet gösteren 23 firmanın 2014 – 2019 yılları arasındaki kurumsal sürdürülebilirlik ve 2015 – 2020 yılları arasındaki finansal verileri incelenmiştir. Çalışma kapsamında kurumsal sürdürülebilirlik faaliyetlerinin ölçümünde Küresel Raporlama Girişimi (GRI)’nin G4 standartları baz alınarak içerik analizi yöntemi kullanılmıştır. Firmaların sürdürülebilirlik raporlarındaki GRI içerik endeksleri incelenmiş ve firma beyanlarına göre ilgili kriterden bahsedilip bahsedilmeme durumuna göre 0/1 şeklinde kodlamalar yapılmıştır. Devamında, firmaların her bir kriter için toplamları alınarak Entropi yöntemiyle kriter ağırlıkları belirlenmiştir. Son aşamada ise kriter ağırlıklarıyla toplam puanlar çarpılarak tüm firmalar için ayrı ayrı olmak üzere boyut puanları hesaplanmıştır. Finansal performansın ölçümü için ise Tobin Q ve Piyasa Değeri (PD) oranları kullanılmıştır. Finansal performans ölçümünde gerekli olan bilgiler firmaların bilançolarından ve gelir tablolarından elde edilmiştir. Analiz kısmında ise doğrudan ve dolaylı etkiler bağımlı değişkenin özelliğine göre panel regresyon ve panel tobit regresyon analizleriyle test edilmiştir. Elde edilen bulgulara göre, Türkiye’de kurumsal sürdürülebilirlik uygulamalarının finansal performansı olumsuz etkilediği, ancak Ar-Ge yoğunluğunun araya girmesiyle bu etkinin dolaylı olarak pozitif olduğu sonucuna ulaşılmıştır.Especially in recent years, the consequences of climate change such as fires, droughts, floods and tornadoes etc. have started to be realized clearly and awareness of sustainability in humans has increased significantly. Similarly, it has been clearly seen that the improvement of epidemic conditions all over the world with COVID 19 pandemic, can be achieved by providing social supports especially to underdeveloped countries. When these two improvements are evaluated together, it can be thought of as an indicator of sustainability idea which gains importance day by day for many years. For this reason, in this study, it is aimed to determine the intermediary role of Research and Development activities in the effect of corporate sustainability practices, which are equivalent of sustainability at the firm level, on financial performance. For this purpose, corporate sustainability data of 23 firms operating in Turkey for the period of 2014-2019 and financial data for the period of 2015-2020 were examined. Within the scope of study, content analysis method was used, based on the G4 standards of Global Reporting Initiative (GRI) in the measurement of corporate sustainability activities. The GRI content indexes in the sustainability reports of firms were examined and coding was done as 0/1, according to whether the relevant criterion is mentioned or not in company statements. Afterwards, criteria weights were determined by entropy method by taking the sums of companies for each criterion. In the last phase, criteria weights were multiplied by the total scores and the large-scaled scores were calculated separately for all companies. Tobin Q and Market Value ratios were used to measure the financial performance. Information needed for measuring financial performance was taken from firms’ balance sheets and income statements. In the analysis phase, direct and indirect effects were tested with panel regression and panel tobit regression analyses according to the characteristics of dependent variables. According to the findings, it was concluded that corporate sustainability practices in Turkey negatively affect financial performance, but this effect is indirectly positive with the participation of R&D intensity
İnternetin işletmelerin pazarlama faaliyetleri üzerine etkileri: Denizli doğal taş ve mermer sektöründe bir araştırma
At first emerged as a communication technology, internet, has improved rapidly in a short time because of it?s benefits. Especially providing high interaction level between users, internet grew up much more rapidly than the other communication technologies. As a result of this improvement, everyday more and more people use internet. Also internet technologies improve continuously and new practises are emerging.In this study, local and internetational literature is reviewed and how the advances in the Internet environment affects enterprises? marketing activities is investigated. At the same time with the performed fieldwork, it is invesitgated that how enterprises use the Internet on their marketing activities. As a result of research, importance of internet marketing for businesses is revealed according to various aspects of these businesses.It should be carefully monitored what the future will bring to the enterprises? marketing activities according to currently evolving and developing Internet technologies. Internet should not only seen as a technological phenomenon, it should be taken into consideration, Internet is a power that should change masses lifestyles deeply. It is inevitable that the enterprises which are aware of this power will be one step ahead and gain competitive advantage.Başlangıçta bir iletişim teknolojisi olarak ortaya çıkan internet sunduğu fırsatlar nedeniyle kısa sürede hızlı bir şekilde gelişme kaydetmiştir. Özellikle kullanıcılar arasında sağladığı zengin etkileşim yönü, internetin diğer iletişim araçlarından çok daha hızlı yaygınlaşmasını sağlamıştır. Bu hızlı gelişme ile birlikte her geçen gün daha fazla kullanıcı interneti kullanırken, internet teknolojileri de sürekli gelişerek evrimleşmiş ve yeni uygulamalar ortaya çıkmıştır.Bu çalışmada yerli ve yabancı literatür incelenmiş ve internet ortamındaki gelişmelerin, işletmelerin pazarlama faaliyetlerine ne şekilde etki ettiği saptanmaya çalışılmıştır. Aynı zamanda gerçekleştirilen saha çalışması ile işletmelerin interneti, pazarlama faaliyetlerinde ne kadar etkin kullandıkları araştırılmıştır. Araştırma neticesinde işletmelerin çeşitli özelliklerine göre internet pazarlamaya verdikleri önem dereceleri de ortaya konmuştur.Halen hızlı bir şekilde gelişim ve değişim gösteren internet teknolojilerinin, işletmelerin gelecekteki pazarlama faaliyetleri açısından neler getireceği dikkatle izlenmelidir. İnternet sadece teknolojik bir olgu olarak görülmemeli, kitlelerin yaşam biçimlerini derinden etkileyen bir güç olduğu göz önünde bulundurulmalıdır. Bu gücün farkında olan işletmelerin bir adım öne çıkarak rekabet avantajı sağlamaları kaçınılmazdır
İNTERNET PAZARLAMA FAALİYETLERİNDE TÜKETİCİ SATIN ALMA KARAR SÜRECİ
Son yıllarda İnternet, işletmecilik ve sosyal hayatta radikal değişikliklerin yaşanmasına neden olmuştur. Bugün, artık İnternet pazarlamanın önemli bir iletişim aracıdır. İnternet'in yoğun yaygın olarak kullanılmaya başlanmasının en önemli nedeni kullanım maliyetinin ucuz olmasıdır. Bu nedenle tüketiciler de İnternet'i sıklıkla kullanmaktadır. Dolayısıyla pazarlama açısından da İnternet son derece önemlidir. Bu çalışmada ise İnternet'te pazarlama faaliyetlerinde tüketici satın alma karar süreci değerlendirilmişti
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