Sustainability in Pakistan's textile industry: analyzing barriers and strategies for green supply chain management implementation.

Du Jianguo, Yasir Ahmed Solangi
Author Information
  1. Du Jianguo: School of Management, Jiangsu University, Zhenjiang, 212013, China.
  2. Yasir Ahmed Solangi: School of Management, Jiangsu University, Zhenjiang, 212013, China. yasir.solangi86@hotmail.com. ORCID

Abstract

The industries view green supply chain management (GSCM) as a viable means of achieving sustainable operations by reducing environmental impact and enhancing operational performance. Although conventional supply chains still dominate many industries, integrating eco-friendly practices through green supply chain management (GSCM) is crucial. Nonetheless, there are several barriers that hinder the successful adoption of GSCM practices. Therefore, this study proposes fuzzy-based multi-criteria decision-making approaches comprised of the Analytical Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). The study evaluates and overcomes barriers to the adoption of GSCM practices in the textile manufacturing sector of Pakistan. After the comprehensive literature review, this study identifies 6 barriers, 24 sub-barriers, and 10 strategies. The FAHP method employs to analyze the barriers and sub-barriers. Then, the FTOPSIS method ranks the strategies to overcome various identified barriers. Based on the FAHP results, the most significant barriers to the adoption of GSCM practices are technological (MB4), financial (MB1), and information and knowledge (MB5). Further, the FTOPSIS indicates that increasing the research and development capacity (GS4) is the most vital strategy for implementing GSCM. The study's findings have important implications for policymakers, organizations, and other stakeholders interested in promoting sustainable development and implementing GSCM practices in Pakistan.

Keywords

References

  1. Agarwal A, Giraud-Carrier FC, Li Y (2018) A mediation model of green supply chain management adoption: the role of internal impetus. Int J Prod Econ 205:342–358. https://doi.org/10.1016/j.ijpe.2018.09.011 [DOI: 10.1016/j.ijpe.2018.09.011]
  2. Agyemang M, Zhu Q, Adzanyo M et al (2018) Evaluating barriers to green supply chain redesign and implementation of related practices in the West Africa cashew industry. Resour Conserv Recycl 136:209–222. https://doi.org/10.1016/j.resconrec.2018.04.011 [DOI: 10.1016/j.resconrec.2018.04.011]
  3. Ahmed W, Ashraf MS, Khan SA et al (2020a) Analyzing the impact of environmental collaboration among supply chain stakeholders on a firm’s sustainable performance. Oper Manag Res. https://doi.org/10.1007/s12063-020-00152-1
  4. Ahmed W, Tan Q, Shaikh GM et al (2020b) Assessing and prioritizing the climate change policy objectives for sustainable development in Pakistan. Symmetry (Basel) 12:1203. https://doi.org/10.3390/sym12081203 [DOI: 10.3390/sym12081203]
  5. Alay E, Duran K, Korlu A (2016) A sample work on green manufacturing in textile industry. Sustain Chem Pharm 3:39–46. https://doi.org/10.1016/j.scp.2016.03.001 [DOI: 10.1016/j.scp.2016.03.001]
  6. Beton A, Dias D, Farrant L et al (2014) Environmental improvement potential of textiles (IMPRO Textiles). Rep EUR 26316 EN. https://doi.org/10.2791/52624
  7. Bocken N, Boons F, Baldassarre B (2019) Sustainable business model experimentation by understanding ecologies of business models. J Cleaner Prod 208:1498–1512. https://doi.org/10.1016/j.jclepro.2018.10.159 [DOI: 10.1016/j.jclepro.2018.10.159]
  8. Cayir Ervural B, Zaim S, Demirel OF et al (2018) An ANP and fuzzy TOPSIS-based SWOT analysis for Turkey’s energy planning. Renew Sustain Energy Rev 82:1538–1550. https://doi.org/10.1016/j.rser.2017.06.095 [DOI: 10.1016/j.rser.2017.06.095]
  9. Chen PK, Ye Y (2022) Influence of creating an oligopoly through government intervention to improve partner collaboration intentions in the context of green supply chains. Environ Sci Pollut Res 29:6433–6448. https://doi.org/10.1007/s11356-021-16064-x [DOI: 10.1007/s11356-021-16064-x]
  10. Chen Z, Ming X, Zhou T, Chang Y (2020) Sustainable supplier selection for smart supply chain considering internal and external uncertainty: an integrated rough-fuzzy approach. Appl Soft Comput J 87. https://doi.org/10.1016/j.asoc.2019.106004
  11. Cristini G, Zerbini C, Salvietti G (2021) Sustainable supply chain management: a literature review. Micro Macro Mark 30:19–42
  12. de Oliveira UR, Espindola LS, da Silva IR et al (2018) A systematic literature review on green supply chain management: research implications and future perspectives. J Cleaner Prod 187:537–561 [DOI: 10.1016/j.jclepro.2018.03.083]
  13. Diabat A, Kannan D, Mathiyazhagan K (2014) Analysis of enablers for implementation of sustainable supply chain management - a textile case. J Cleaner Prod 83:391–403. https://doi.org/10.1016/j.jclepro.2014.06.081 [DOI: 10.1016/j.jclepro.2014.06.081]
  14. Fahimnia B, Sarkis J, Davarzani H (2015) Green supply chain management: a review and bibliometric analysis. Int. J. Prod. Econ 162:101–114 [DOI: 10.1016/j.ijpe.2015.01.003]
  15. Gogus O, Boucher TO (1998) Strong transitivity, rationality and weak monotonicity in fuzzy pairwise comparisons. Fuzzy Sets Syst 94:133–144. https://doi.org/10.1016/S0165-0114(96)00184-4 [DOI: 10.1016/S0165-0114(96)00184-4]
  16. Govindan K, Kaliyan M, Kannan D, Haq AN (2014) Barriers analysis for green supply chain management implementation in Indian industries using analytic hierarchy process. Int J Prod Econ 147:555–568. https://doi.org/10.1016/j.ijpe.2013.08.018 [DOI: 10.1016/j.ijpe.2013.08.018]
  17. Govindan K, Muduli K, Devika K, Barve A (2016) Investigation of the influential strength of factors on adoption of green supply chain management practices: an Indian mining scenario. Resour Conserv Recycl 107:185–194. https://doi.org/10.1016/j.resconrec.2015.05.022 [DOI: 10.1016/j.resconrec.2015.05.022]
  18. Green KW, Zelbst PJ, Meacham J, Bhadauria VS (2012) Green supply chain management practices: Impact on performance. Supply Chain Manag 17:290–305. https://doi.org/10.1108/13598541211227126 [DOI: 10.1108/13598541211227126]
  19. Han H, Trimi S (2018) A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms. Expert Syst Appl 103:133–145. https://doi.org/10.1016/j.eswa.2018.03.003 [DOI: 10.1016/j.eswa.2018.03.003]
  20. Hong Z, Guo X (2019) Green product supply chain contracts considering environmental responsibilities. Omega (United Kingdom) 83:155–166. https://doi.org/10.1016/j.omega.2018.02.010 [DOI: 10.1016/j.omega.2018.02.010]
  21. Huo B, Gu M, Wang Z (2019) Green or lean? A supply chain approach to sustainable performance. J Cleaner Prod 216:152–166. https://doi.org/10.1016/j.jclepro.2019.01.141 [DOI: 10.1016/j.jclepro.2019.01.141]
  22. Hussain D (2017) Pakistan could become 16th largest economy by 2050: PwC - Pakistan - DAWN.COM. In: Dawn. https://www.dawn.com/news/1313636 . Accessed 16 Apr 2020
  23. Hwang C-L, Yoon K (1981) Methods for multiple attribute decision making. In: Multiple attribute decision making: methods and applications a state-of-the-art survey. pp 58–191
  24. Kaur J, Sidhu R, Awasthi A et al (2018) A DEMATEL based approach for investigating barriers in green supply chain management in Canadian manufacturing firms. Int J Prod Res 56:312–332. https://doi.org/10.1080/00207543.2017.1395522 [DOI: 10.1080/00207543.2017.1395522]
  25. Kilic HS, Yalcin AS (2020) Modified two-phase fuzzy goal programming integrated with IF-TOPSIS for green supplier selection. Appl Soft Comput J 93. https://doi.org/10.1016/j.asoc.2020.106371
  26. Koberg E, Longoni A (2019) A systematic review of sustainable supply chain management in global supply chains. J Cleaner Prod 207:1084–1098 [DOI: 10.1016/j.jclepro.2018.10.033]
  27. Kul C, Zhang L, Solangi YA (2020) Assessing the renewable energy investment risk factors for sustainable development in Turkey. J Cleaner Prod 276. https://doi.org/10.1016/j.jclepro.2020.124164
  28. Kumar A, Dixit G (2018) An analysis of barriers affecting the implementation of e-waste management practices in India: a novel ISM-DEMATEL approach. Sustain Prod Consum 14:36–52. https://doi.org/10.1016/j.spc.2018.01.002 [DOI: 10.1016/j.spc.2018.01.002]
  29. Lahane S, Kant R (2022) Investigating the sustainable development goals derived due to adoption of circular economy practices. Waste Manag 143:1–14. https://doi.org/10.1016/j.wasman.2022.02.016 [DOI: 10.1016/j.wasman.2022.02.016]
  30. Li C, Solangi YA, Ali S (2023) Evaluating the factors of green finance to achieve carbon peak and carbon neutrality targets in China: a Delphi and fuzzy AHP approach. Sustainability 15
  31. Li Y, Mathiyazhagan K (2016) Application of DEMATEL approach to identify the influential indicators towards sustainable supply chain adoption in the auto components manufacturing sector. J Cleaner Prod 172:2931–2941. https://doi.org/10.1016/j.jclepro.2017.11.120 [DOI: 10.1016/j.jclepro.2017.11.120]
  32. Luthra S, Garg D, Haleem A (2013) Identifying and ranking of strategies to implement green supply chain management in Indian manufacturing industry using analytical hierarchy process. J Ind Eng Manag 6:930–962. https://doi.org/10.3926/jiem.693 [DOI: 10.3926/jiem.693]
  33. Luthra S, Mangla SK, Xu L, Diabat A (2016) Using AHP to evaluate barriers in adopting sustainable consumption and production initiatives in a supply chain. Int J Prod Econ 181:342–349. https://doi.org/10.1016/j.ijpe.2016.04.001 [DOI: 10.1016/j.ijpe.2016.04.001]
  34. Majumdar A, Sinha S (2018) Modeling the barriers of green supply chain management in small and medium enterprises: a case of Indian clothing industry. Manag Environ Qual An Int J 29:1110–1122 [DOI: 10.1108/MEQ-12-2017-0176]
  35. Majumdar A, Sinha SK (2019) Analyzing the barriers of green textile supply chain management in Southeast Asia using interpretive structural modeling. Sustain Prod Consum 17:176–187. https://doi.org/10.1016/j.spc.2018.10.005 [DOI: 10.1016/j.spc.2018.10.005]
  36. Mangla SK, Govindan K, Luthra S (2017) Prioritizing the barriers to achieve sustainable consumption and production trends in supply chains using fuzzy Analytical Hierarchy Process. J Cleaner Prod 151:509–525. https://doi.org/10.1016/j.jclepro.2017.02.099 [DOI: 10.1016/j.jclepro.2017.02.099]
  37. Mathiyazhagan K, Govindan K, Noorul Haq A (2014) Pressure analysis for green supply chain management implementation in Indian industries using analytic hierarchy process. Int J Prod Res 52:188–202. https://doi.org/10.1080/00207543.2013.831190 [DOI: 10.1080/00207543.2013.831190]
  38. Mirhedayatian SM, Azadi M, Farzipoor Saen R (2014) A novel network data envelopment analysis model for evaluating green supply chain management. Int J Prod Econ 147:544–554. https://doi.org/10.1016/j.ijpe.2013.02.009 [DOI: 10.1016/j.ijpe.2013.02.009]
  39. Moktadir MA, Ali SM, Rajesh R, Paul SK (2018) Modeling the interrelationships among barriers to sustainable supply chain management in leather industry. J Cleaner Prod 181:631–651. https://doi.org/10.1016/j.jclepro.2018.01.245 [DOI: 10.1016/j.jclepro.2018.01.245]
  40. Narayanan AE, Sridharan R, Ram Kumar PN (2019) Analyzing the interactions among barriers of sustainable supply chain management practices: a case study. J Manuf Technol Manag 30:937–971. https://doi.org/10.1108/JMTM-06-2017-0114 [DOI: 10.1108/JMTM-06-2017-0114]
  41. Pieroni MPP, McAloone TC, Pigosso DCA (2019) Business model innovation for circular economy and sustainability: a review of approaches. J Cleaner Prod 215:198–216 [DOI: 10.1016/j.jclepro.2019.01.036]
  42. Prakash C, Barua MK (2015) Integration of AHP-TOPSIS method for prioritizing the solutions of reverse logistics adoption to overcome its barriers under fuzzy environment. J Manuf Syst 37:599–615. https://doi.org/10.1016/j.jmsy.2015.03.001 [DOI: 10.1016/j.jmsy.2015.03.001]
  43. Rostamzadeh R, Govindan K, Esmaeili A, Sabaghi M (2015) Application of fuzzy VIKOR for evaluation of green supply chain management practices. Ecol Indic 49:188–203. https://doi.org/10.1016/j.ecolind.2014.09.045 [DOI: 10.1016/j.ecolind.2014.09.045]
  44. Saaty TL (1990) The analytic hierarchy process
  45. Sinaga O, Mulyati Y, Darrini A et al (2019) Green supply chain management organizational performance. Int J Supply Chain Manag 8:76–85
  46. Solangi YA, Shah SAA, Zameer H et al (2019a) Assessing the solar PV power project site selection in Pakistan: based on AHP-fuzzy VIKOR approach. Environ Sci Pollut Res 26:30286–30302. https://doi.org/10.1007/s11356-019-06172-0 [DOI: 10.1007/s11356-019-06172-0]
  47. Solangi YA, Tan Q, Mirjat NH et al (2019b) An integrated Delphi-AHP and fuzzy TOPSIS approach toward ranking and selection of renewable energy resources in Pakistan. Processes 7. https://doi.org/10.3390/pr7020118
  48. Su Z, Zhang M, Wu W (2021) Visualizing sustainable supply chain management: a systematic scientometric review. Sustain 13
  49. Tseng ML, Chiu ASF (2013) Evaluating firm’s green supply chain management in linguistic preferences. J Cleaner Prod 40:22–31. https://doi.org/10.1016/j.jclepro.2010.08.007 [DOI: 10.1016/j.jclepro.2010.08.007]
  50. Uygun Ö, Dede A (2016) Performance evaluation of green supply chain management using integrated fuzzy multi-criteria decision making techniques. Comput Ind Eng 102:502–511. https://doi.org/10.1016/j.cie.2016.02.020 [DOI: 10.1016/j.cie.2016.02.020]
  51. Vafadarnikjoo A, Badri Ahmadi H, Liou JJH et al (2021) Analyzing blockchain adoption barriers in manufacturing supply chains by the neutrosophic analytic hierarchy process. Ann Oper Res. https://doi.org/10.1007/s10479-021-04048-6
  52. Wang Z, Mathiyazhagan K, Xu L, Diabat A (2016) A decision making trial and evaluation laboratory approach to analyze the barriers to green supply chain management adoption in a food packaging company. J Cleaner Prod 117:19–28. https://doi.org/10.1016/j.jclepro.2015.09.142 [DOI: 10.1016/j.jclepro.2015.09.142]
  53. Xu L, Shah SAA, Zameer H, Solangi YA (2019) Evaluating renewable energy sources for implementing the hydrogen economy in Pakistan: a two-stage fuzzy MCDM approach. Environ Sci Pollut Res 26:33202–33215. https://doi.org/10.1007/s11356-019-06431-0 [DOI: 10.1007/s11356-019-06431-0]
  54. Zhu Q, Sarkis J, Hung LK (2007) Green supply chain management: pressures, practices and performance within the Chinese automobile industry. J Cleaner Prod 15:1041–1052. https://doi.org/10.1016/j.jclepro.2006.05.021 [DOI: 10.1016/j.jclepro.2006.05.021]

MeSH Term

Commerce
Conservation of Natural Resources
Industry
Pakistan
Textile Industry

Word Cloud

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