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Analysis of Influencing Factors on Sustainability of Textile Wastewater: a Structural Equation Approach

  • Punyasloka PattnaikEmail author
  • G. S. Dangayach
Article
  • 119 Downloads

Abstract

The purpose of this study was the identification of the major factor for sustainable development in textile industries and preferred textile wastewater management practices for environmental protection. Moreover, a structural framework for sustainable textile wastewater management concept in the textile industry was developed, and further, the proposed model was examined based on the effect of economic performance, environmental impact, and operational performance in textile sectors. Therefore, to achieve the above issues, major factors were identified through exhaustive literature, and then a test was conducted for the reliability of the proposed constructs for validation. However, there was no specific study on the sustainability of textile wastewater management principle by using exploratory structural equation modeling (SEM). Finally, the proposed structural model was validated by confirmatory factor analysis (CFA) and structural equation modeling with the help of the SPSS software package.

Keywords

Textile wastewater Sustainability Structural equation modeling SPSS AMOS 

Notes

Acknowledgments

The authors are grateful for all the HR managers and workers of textile industries for their active participation in the present survey to shape the initial draft for the sustainability of textile wastewater questioner, and their comments made for successful development of a valid structural model.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflict of interest.

References

  1. Ajayi, S. O., & Oyedele, L. O. (2018). Critical design factors for minimising waste in construction projects: a structural equation modelling approach. Resources, Conservation and Recycling, 137, 302–313.CrossRefGoogle Scholar
  2. Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103, 411–423.CrossRefGoogle Scholar
  3. Bagozzi, R., & Yi, Y. (1988). On the evaluation of structure equation models. Journal of the Academy of Marketing Science, 16, 74–94.CrossRefGoogle Scholar
  4. Cambero, C., & Sowlati, T. (2014). Assessment and optimization of forest biomass supply chains from economic, social and environmental perspectives—a review of literature. Renewable & Sustainable Energy Reviews, 36, 62–73.CrossRefGoogle Scholar
  5. Chatzisymeon, E., Xekoukoulotakis, N. P., Coz, A., Kalogerakis, N., & Mantzavinos, D. (2006). Electrochemical treatment of textile dyes and dyehouse effluents. Journal of Hazardous Materials, 137, 998–1007.CrossRefGoogle Scholar
  6. Chavan, R. B. (2001). Indian textile industry-environmental issues. Indian Journal of Fiber & Textile Research, 26, 11–21.Google Scholar
  7. Comrey, A. L., & Lee, H. B. (1992). A first course in factor analysis. Hillsdale: Erlbaum.Google Scholar
  8. Erdumlu, N., Ozipek, B., Yilmaz, G., & Topatan, Z. (2012). Reuse of effluent water obtained in different textile finishing processes. AUTEX Research Journal, 12, 23–28.CrossRefGoogle Scholar
  9. Gómez Fernández, J. F., & Crespo Márquez, A. (2012). Maintenance management in network utilities. Springer Series in Reliability Engineering.  https://doi.org/10.1007/978-1-4471-2757-4.
  10. Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Burke, R. L. T. (2006). Multivariate data analysis (6th ed.). Upper saddle River: Pearson Prentice Hall.Google Scholar
  11. Kaiser, H. F. (1974). An index of factorial simplicity. Psychometrika, 39, 31–36.CrossRefGoogle Scholar
  12. Kannan, V. R., & Tan, K. (2005). Just-in-time, total quality management, and supply chain management: understanding their linkages and impact on business performance. Omega, 33, 153–162.CrossRefGoogle Scholar
  13. Neto, S. A. S., Dantas, M. J. P., & Machado, R. L. (2017). Structural equation modeling applied to assess industrial engineering students’ satisfaction according to ENADE 2011. Production, 27, 2016–2191.Google Scholar
  14. Njoh, A. J. (2017). The SWOT model’s utility in evaluating energy technology: illustrative application of a modified version to assess the sawdust cookstove’s sustainability in sub-Saharan Africa. Renewable and Sustainable Energy Reviews, 69, 313–323.CrossRefGoogle Scholar
  15. PashaeiKamali, F., Meuwissen, M. P. M., Boer, I. J. M., Middelaar, C. E., Moreira, A., & Lansink, A. G. J. M. O. (2017). Evaluation of the environmental, economic, and social performance of soybean farming systems in southern Brazil. Journal of Cleaner Production, 142, 385–394.CrossRefGoogle Scholar
  16. Pattnaik, P., Dangayach, G. S., & Bhardwaj, A. K. (2018). A review on the sustainability of textile industries wastewater with and without treatment methodologies. Reviews on Environmental Health, 33, 163–203.CrossRefGoogle Scholar
  17. Pett, M. A., Lackey, N. R., & Sullivan, J. J. (2003). Making sense of factor analysis: the use of factor analysis for instrument development in health care research. California: Sage Publications Inc.CrossRefGoogle Scholar
  18. Schumacker, R., & Lomax, R. A. (2004). Beginner’s guide to structural equation modeling (2nd ed.). Mahwah: Lawrence Erlbaum.CrossRefGoogle Scholar
  19. Taha, M., Adetutu, E. M., Shahsavari, E., Smith, A. T., & Ball, A. S. (2014). Azo and anthraquinone dye mixture decolourization at elevated temperature and concentration by a newly isolated thermophilic fungus, Thermomucorindicae-seudaticae. Journal of Environmental Chemical Engineering, 2, 415–423.CrossRefGoogle Scholar
  20. Taran, M., Sharifi, M., & Bagheri, S. (2011). Utilization of textile wastewater as carbon source by newly isolated Haloarcula sp. IRU1: optimization of conditions by Taguchi methodology. Clean Technologies and Environmental Policy, 13, 535–538.CrossRefGoogle Scholar
  21. Vineta, S., Silvana, Z., Sanja, R., & Golomeova, S. (2014). Methods for waste waters treatment in textile industry. International Scientific Conference 21–22 November, GABROVO.Google Scholar
  22. Wijannarong, S., Aroonsrimorakot, S., Thavipoke, P., Kumsopa, C., & Sangjan, S. (2013). Removal of reactive dyes from textile dyeing industrial effluent by ozonation process. APCBEE Procedia, 5, 279–282.CrossRefGoogle Scholar
  23. Yuan, K. H., & Tian, Y. (2015). Structural equation modeling as a statistical method: an overview. JSM Mathematics and Statistics, 2, 1–6.Google Scholar
  24. Živkovi’c, S. B., Veljkovi’c, M. V., Bankovi’c-Ili’c, I. B., & Krstić, I. (2017). Technological, technical, economic, environmental, social, human health risk, toxicological and policy considerations of biodiesel production and use. Renewable and Sustainable Energy Reviews, 79, 222–247.CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Management StudiesMNITJaipurIndia
  2. 2.Department of Mechanical EngineeringMNITJaipurIndia

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