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The Use of Partial Least Squares Structural Equation Model in the Evaluation of Groundwater Quality

Year 2021, Volume: 12 Issue: 1, 165 - 174, 13.01.2021
https://doi.org/10.24012/dumf.816469

Abstract

References

  • [1] M. İ. Yeşilnacar vd., “Geomedical assessment of an area having high-fluoride groundwater in southeastern Turkey”, Environmental Earth Sciences, c. 75, sayı 2, s. 162, Oca. 2016, doi: 10.1007/s12665-015-5002-6.
  • [2] P. Sahu, G. C. Kisku, P. K. Singh, V. Kumar, P. Kumar, ve N. Shukla, “Multivariate statistical interpretation on seasonal variations of fluoride-contaminated groundwater quality of Lalganj Tehsil, Raebareli District (UP), India”, Environmental Earth Sciences, 2018, doi: 10.1007/s12665-018-7658-1.
  • [3] İ. Yolcubal, Ö. C. Ataş Gündüz, ve N. Kurtuluş, “Origin of salinization and pollution sources and geochemical processes in urban coastal aquifer (Kocaeli, NW Turkey)”, Environmental Earth Sciences, 2019, doi: 10.1007/s12665-019-8181-8.
  • [4] H. Wold, “Quantitative sociology”, içinde International Perspectives on Mathematical and Statistical Modeling, H. M. Blalock, Ed. New York: Seminar Press, 1975, ss. 307–357.
  • [5] J. Hair, G. Hult, C. Ringle, ve M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: SAGE, 2017.
  • [6] J. F. Hair, C. M. Ringle, ve M. Sarstedt, “PLS-SEM: Indeed a Silver Bullet”, Journal of Marketing Theory and Practice, c. 19, sayı 2, ss. 139–152, Nis. 2011, doi: 10.2753/MTP1069-6679190202.
  • [7] M. Sarstedt, C. M. Ringle, ve J. F. Hair, “Partial Least Squares Structural Equation Modeling”, içinde Handbook of Market Research, Cham: Springer International Publishing, 2017, ss. 1–40.
  • [8] R. G. Lomax, “The Effect of Measurement Error in Structural Equation Modeling”, The Journal of Experimental Education, c. 54, sayı 3, ss. 157–162, Nis. 1986, doi: 10.1080/00220973.1986.10806415.
  • [9] W. W. Chin ve P. R. Newsted, “Structural equation modeling analysis with small samples using partial least squares”, içinde Statistical strategies for small sample research, R. H. Hoyle, Ed. Thousand Oaks: Sage Publications, 1999, ss. 307–341.
  • [10] J. F. Hair, J. J. Risher, M. Sarstedt, ve C. M. Ringle, “When to use and how to report the results of PLS-SEM”, European Business Review, c. 31, sayı 1, ss. 2–24, Oca. 2019, doi: 10.1108/EBR-11-2018-0203.
  • [11] J. Hair, C. L. Hollingsworth, A. B. Randolph, ve A. Y. L. Chong, “An updated and expanded assessment of PLS-SEM in information systems research”, Industrial Management & Data Systems, c. 117, sayı 3, ss. 442–458, Nis. 2017, doi: 10.1108/IMDS-04-2016-0130.
  • [12] V. S. Rodrigues, R. F. do Valle Júnior, L. F. Sanches Fernandes, ve F. A. L. Pacheco, “The assessment of water erosion using Partial Least Squares-Path Modeling: A study in a legally protected area with environmental land use conflicts”, Science of the Total Environment, c. 691, ss. 1225–1241, 2019, doi: 10.1016/j.scitotenv.2019.07.216.
  • [13] N. C. Viswanath, P. G. D. Kumar, ve K. K. Ammad, “Statistical Analysis of Quality of Water in Various Water Shed for Kozhikode City, Kerala, India”, Aquatic Procedia, c. 4, ss. 1078–1085, 2015, doi: 10.1016/j.aqpro.2015.02.136.
  • [14] H. Wold, Model Construction and Evaluation When Theoretical Knowledge Is Scarce. Theory and Application of Partial Least Squares. Academic Press, 1980.
  • [15] S. Akter, S. Fosso Wamba, ve S. Dewan, “Why PLS-SEM is suitable for complex modelling? An empirical illustration in big data analytics quality”, Production Planning & Control, c. 28, sayı 11–12, ss. 1011–1021, Eyl. 2017, doi: 10.1080/09537287.2016.1267411.
  • [16] D. Ghosh, A. Olewnik, ve K. Lewis, “Application of autoencoders in cyber-empathic design”, Design Science, c. 4, ss. 1–17, 2018, doi: 10.1017/dsj.2018.11.
  • [17] C. M. Ringle, S. Wende, ve J.-M. Becker, “SmartPLS 3”. SmartPLS GmbH, 2015.
  • [18] M. I. Yesilnacar ve I. Yenigun, “Effect of irrigation on a deep aquifer: a case study from the semi-arid Harran Plain, GAP Project, Turkey”, Bulletin of Engineering Geology and the Environment, c. 70, sayı 2, ss. 213–221, May. 2011, doi: 10.1007/s10064-010-0299-6.
  • [19] D. Marghade, D. B. Malpe, ve A. B. Zade, “Geochemical characterization of groundwater from northeastern part of Nagpur urban, Central India”, Environmental Earth Sciences, c. 62, sayı 7, ss. 1419–1430, Nis. 2011, doi: 10.1007/s12665-010-0627-y.
  • [20] M. Loizidou ve E. Kapetanios, “Effect of leachate from landfills on underground water quality”, The Science of The Total Environment, c. 128, sayı 1, ss. 69–81, Oca. 1993, doi: 10.1016/0048-9697(93)90180-E.
  • [21] I. Chenini ve S. Khemiri, “Evaluation of ground water quality using multiple linear regression and structural equation modeling”, International Journal of Environmental Science and Technology, 2009, doi: 10.1007/BF03326090.
  • [22] V. Esposito Vinzi, W. W. Chin, J. Henseler, ve H. Wang, Handbook of Partial Least Squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.

Kısmi En Küçük Kareler Yapısal Eşitlik Modelinin Yeraltı Suyu Kalitesinin Değerlendirilmesinde Kullanımı

Year 2021, Volume: 12 Issue: 1, 165 - 174, 13.01.2021
https://doi.org/10.24012/dumf.816469

Abstract

Bu araştırmada su kalitesi ikinci nesil çok değişkenli bir istatistik metodu olan Kısmı En Küçük Kareler Yapısal Eşitlik Modeli (KEKK-YEM) kullanılarak incelenmiştir. KEKK-YEM gözlenen değişkenlerden yola çıkıp doğrudan gözlemlenemeyen (latent) değişkenler arasındaki ilişkileri açıklamaya çalışır. KEKK – YEM modelinde kullanılan gözlenen su kalitesi faktörleri pH, TDS katyonlar (Mg2+, Na+)ve anyonlar (HCO3-, Cl-ve SO4+). Çalışmada kullanılan KEKK-YEM modeli iki aşamada değerlendirilmiştir; ölçüm modelinin uygunluğu farklı uyum indisleri ile birinci aşamada değerlendirildikten sonra ikinci aşamada yapısal model değerlendirilmiştir. YEM model sonuçlarına göre, su kalitesi üzerinde katyonların (γ=0.598, p<0.05) anyonlardan (γ=0.259, P<0.05) daha etkili olduğu ve yine pH üzerinde katyonların (γ=0.643, P<0.05) anyonlardan (γ=-0.512, P>0.05) daha etkili olduğu tahmin edilmiştir. Su kalitesi varyansının %65’i (R2=0.650) ve pH’nin varyansının %19.5’i (R2=0.195) anyonlar ve katyonlar tarafından açıklandığı görülmüştür. Sonuç KEKK-YEM’in su kalitesinin değerlendirilmesinde klasik çok değişkenli ve bazı önkoşullara sahip daha fazla örneğe ihtiyaç duyan geleneksel istatistiksel metotların yerine başarı ile kullanılabileceğini göstermiştir

References

  • [1] M. İ. Yeşilnacar vd., “Geomedical assessment of an area having high-fluoride groundwater in southeastern Turkey”, Environmental Earth Sciences, c. 75, sayı 2, s. 162, Oca. 2016, doi: 10.1007/s12665-015-5002-6.
  • [2] P. Sahu, G. C. Kisku, P. K. Singh, V. Kumar, P. Kumar, ve N. Shukla, “Multivariate statistical interpretation on seasonal variations of fluoride-contaminated groundwater quality of Lalganj Tehsil, Raebareli District (UP), India”, Environmental Earth Sciences, 2018, doi: 10.1007/s12665-018-7658-1.
  • [3] İ. Yolcubal, Ö. C. Ataş Gündüz, ve N. Kurtuluş, “Origin of salinization and pollution sources and geochemical processes in urban coastal aquifer (Kocaeli, NW Turkey)”, Environmental Earth Sciences, 2019, doi: 10.1007/s12665-019-8181-8.
  • [4] H. Wold, “Quantitative sociology”, içinde International Perspectives on Mathematical and Statistical Modeling, H. M. Blalock, Ed. New York: Seminar Press, 1975, ss. 307–357.
  • [5] J. Hair, G. Hult, C. Ringle, ve M. Sarstedt, A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: SAGE, 2017.
  • [6] J. F. Hair, C. M. Ringle, ve M. Sarstedt, “PLS-SEM: Indeed a Silver Bullet”, Journal of Marketing Theory and Practice, c. 19, sayı 2, ss. 139–152, Nis. 2011, doi: 10.2753/MTP1069-6679190202.
  • [7] M. Sarstedt, C. M. Ringle, ve J. F. Hair, “Partial Least Squares Structural Equation Modeling”, içinde Handbook of Market Research, Cham: Springer International Publishing, 2017, ss. 1–40.
  • [8] R. G. Lomax, “The Effect of Measurement Error in Structural Equation Modeling”, The Journal of Experimental Education, c. 54, sayı 3, ss. 157–162, Nis. 1986, doi: 10.1080/00220973.1986.10806415.
  • [9] W. W. Chin ve P. R. Newsted, “Structural equation modeling analysis with small samples using partial least squares”, içinde Statistical strategies for small sample research, R. H. Hoyle, Ed. Thousand Oaks: Sage Publications, 1999, ss. 307–341.
  • [10] J. F. Hair, J. J. Risher, M. Sarstedt, ve C. M. Ringle, “When to use and how to report the results of PLS-SEM”, European Business Review, c. 31, sayı 1, ss. 2–24, Oca. 2019, doi: 10.1108/EBR-11-2018-0203.
  • [11] J. Hair, C. L. Hollingsworth, A. B. Randolph, ve A. Y. L. Chong, “An updated and expanded assessment of PLS-SEM in information systems research”, Industrial Management & Data Systems, c. 117, sayı 3, ss. 442–458, Nis. 2017, doi: 10.1108/IMDS-04-2016-0130.
  • [12] V. S. Rodrigues, R. F. do Valle Júnior, L. F. Sanches Fernandes, ve F. A. L. Pacheco, “The assessment of water erosion using Partial Least Squares-Path Modeling: A study in a legally protected area with environmental land use conflicts”, Science of the Total Environment, c. 691, ss. 1225–1241, 2019, doi: 10.1016/j.scitotenv.2019.07.216.
  • [13] N. C. Viswanath, P. G. D. Kumar, ve K. K. Ammad, “Statistical Analysis of Quality of Water in Various Water Shed for Kozhikode City, Kerala, India”, Aquatic Procedia, c. 4, ss. 1078–1085, 2015, doi: 10.1016/j.aqpro.2015.02.136.
  • [14] H. Wold, Model Construction and Evaluation When Theoretical Knowledge Is Scarce. Theory and Application of Partial Least Squares. Academic Press, 1980.
  • [15] S. Akter, S. Fosso Wamba, ve S. Dewan, “Why PLS-SEM is suitable for complex modelling? An empirical illustration in big data analytics quality”, Production Planning & Control, c. 28, sayı 11–12, ss. 1011–1021, Eyl. 2017, doi: 10.1080/09537287.2016.1267411.
  • [16] D. Ghosh, A. Olewnik, ve K. Lewis, “Application of autoencoders in cyber-empathic design”, Design Science, c. 4, ss. 1–17, 2018, doi: 10.1017/dsj.2018.11.
  • [17] C. M. Ringle, S. Wende, ve J.-M. Becker, “SmartPLS 3”. SmartPLS GmbH, 2015.
  • [18] M. I. Yesilnacar ve I. Yenigun, “Effect of irrigation on a deep aquifer: a case study from the semi-arid Harran Plain, GAP Project, Turkey”, Bulletin of Engineering Geology and the Environment, c. 70, sayı 2, ss. 213–221, May. 2011, doi: 10.1007/s10064-010-0299-6.
  • [19] D. Marghade, D. B. Malpe, ve A. B. Zade, “Geochemical characterization of groundwater from northeastern part of Nagpur urban, Central India”, Environmental Earth Sciences, c. 62, sayı 7, ss. 1419–1430, Nis. 2011, doi: 10.1007/s12665-010-0627-y.
  • [20] M. Loizidou ve E. Kapetanios, “Effect of leachate from landfills on underground water quality”, The Science of The Total Environment, c. 128, sayı 1, ss. 69–81, Oca. 1993, doi: 10.1016/0048-9697(93)90180-E.
  • [21] I. Chenini ve S. Khemiri, “Evaluation of ground water quality using multiple linear regression and structural equation modeling”, International Journal of Environmental Science and Technology, 2009, doi: 10.1007/BF03326090.
  • [22] V. Esposito Vinzi, W. W. Chin, J. Henseler, ve H. Wang, Handbook of Partial Least Squares. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010.
There are 22 citations in total.

Details

Primary Language Turkish
Journal Section Articles
Authors

Zeki Doğan 0000-0002-9725-4052

Hamza Yalçin 0000-0003-0733-7821

İbrahim Yenigün 0000-0003-4742-0160

Ali Volkan Bilgili 0000-0002-4727-8283

Publication Date January 13, 2021
Submission Date October 27, 2020
Published in Issue Year 2021 Volume: 12 Issue: 1

Cite

IEEE Z. Doğan, H. Yalçin, İ. Yenigün, and A. V. Bilgili, “Kısmi En Küçük Kareler Yapısal Eşitlik Modelinin Yeraltı Suyu Kalitesinin Değerlendirilmesinde Kullanımı”, DUJE, vol. 12, no. 1, pp. 165–174, 2021, doi: 10.24012/dumf.816469.
DUJE tarafından yayınlanan tüm makaleler, Creative Commons Atıf 4.0 Uluslararası Lisansı ile lisanslanmıştır. Bu, orijinal eser ve kaynağın uygun şekilde belirtilmesi koşuluyla, herkesin eseri kopyalamasına, yeniden dağıtmasına, yeniden düzenlemesine, iletmesine ve uyarlamasına izin verir. 24456