CoChat
Sign Up
Cited by 259

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Dynamic capabilities for circular manufacturing supply chains—Exploring the role of Industry 4.0 and resilience

Chari, Arpita, Niedenzu, Denis, Despeisse, Mélanie, Machado, Carla Gonçalves, Azevedo, João Domingues, Boavida‐Dias, Rui, Johansson, Björn·2022·Business Strategy and the Environment
DOI 10.1002/bse.3040
Open this paper in CoChat — free account

Abstract

An organisation's sustainability performance is influenced by its capabilities (skills, resources and competences) which in turn affects the performance of its entire supply chain. However, recent research has not sufficiently explored the convergence of dynamic capabilities, circular economy, resilience and Industry 4.0 concepts for manufacturing supply chains. Therefore, this study aims to identify how dynamic capabilities theory can enable circular and resilient supply chains. A qualitative research process was deployed in three stages: literature review, European project and nine expert interviews. Key investigative variables were used to identify capabilities used in manufacturing, and five research propositions were developed to address the gaps found in literature. The empirical data helped reveal challenges to circular economy implementation and validate the literature findings. The main contributions include a dynamic capabilities model, a causal relationship model and five research propositions for circular economy implementation.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/bse.3040

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Figures

Image 1
CC-BY-NC-ND · From the PDF
Image 2
CC-BY-NC-ND · From the PDF
Image 3
CC-BY-NC-ND · From the PDF
Figure 1 Overview of the experimental setup, consisting of fabric treatment (Part 1), outdoor exposure of the textile fabrics (Part 2), and application of abrasion and washing (Part 3). All three experiments were subjected to comprehensive characterization including scanning electron microscopy (SEM), combustion ion chromatography (CIC), high performance liquid chromatographytandem mass spectrometry or high-resolution mass spectrometry (HPLC-MS/MS or HPLC-HRMS), and the total oxidizable precursor (TOP) assay. Additional changes of material properties were examined by measuring the water repellency (method: spray test) and the color change (method: gray scale).
Figure 1 Overview of the experimental setup, consisting of fabric treatment (Part 1), outdoor exposure of the textile fabrics (Part 2), and application of abrasion and washing (Part 3). All three experiments were subjected to comprehensive characterization including scanning electron microscopy (SEM), combustion ion chromatography (CIC), high performance liquid chromatographytandem mass spectrometry or high-resolution mass spectrometry (HPLC-MS/MS or HPLC-HRMS), and the total oxidizable precursor (TOP) assay. Additional changes of material properties were examined by measuring the water repellency (method: spray test) and the color change (method: gray scale).CC-BY-NC-ND · From the PDF
Figure 2 SEM pictures of a PA rip-stop fabrics treated with a C 6 F13 -SFP fi nish. Unexposed controls are shown in comparison to ' sealed controls ' and exposed fabrics with di ff erent exposure times and after applying abrasion and washing. Warps (blue frames) and weft fi bers (yellow frames) are also displayed in higher magni fi cation. Numbers in the upper right corner of the SEM pictures refer to the color change assessed with the Gray scale in comparison to the unexposed fabrics (scale 1 -5; 5 = no visual change 1 = a large visual change).
Figure 2 SEM pictures of a PA rip-stop fabrics treated with a C 6 F13 -SFP fi nish. Unexposed controls are shown in comparison to ' sealed controls ' and exposed fabrics with di ff erent exposure times and after applying abrasion and washing. Warps (blue frames) and weft fi bers (yellow frames) are also displayed in higher magni fi cation. Numbers in the upper right corner of the SEM pictures refer to the color change assessed with the Gray scale in comparison to the unexposed fabrics (scale 1 -5; 5 = no visual change 1 = a large visual change).CC-BY-NC-ND · From the PDF
Figure 3 Total fl uorine content of fabrics before and after weathering and after the additional abrasion test and washing. PA fabrics measured with CIC contained di ff erent fl uorinated textile fi nishes based on ' short-chain ' SFPs with (a1) C4F8 and (a2) C6F13 side chains as well as (a3) ' long-chain ' SFPs based on C8F17 side chains. (b) Shows untreated fabrics that were spiked with PFAAs and underwent weathering as well.
Figure 3 Total fl uorine content of fabrics before and after weathering and after the additional abrasion test and washing. PA fabrics measured with CIC contained di ff erent fl uorinated textile fi nishes based on ' short-chain ' SFPs with (a1) C4F8 and (a2) C6F13 side chains as well as (a3) ' long-chain ' SFPs based on C8F17 side chains. (b) Shows untreated fabrics that were spiked with PFAAs and underwent weathering as well.CC-BY-NC-ND · From the PDF
Figure 4 Summary of the targeted analysis of PFAAs after weathering of textiles with (a) short-chain C 4F9 -and (b) C6F13 -SFPs as well as (c) long-chain C8 F17 -SFPs.
Figure 4 Summary of the targeted analysis of PFAAs after weathering of textiles with (a) short-chain C 4F9 -and (b) C6F13 -SFPs as well as (c) long-chain C8 F17 -SFPs.CC-BY-NC-ND · From the PDF
Figure 5 In (a) the sum of PFAAs detected after roof-top weathering were compared to the sum of PFAAs detected after extraction of unexposed fabric and application of a TOP assay (on the basis of the fl uorine content of the PFAAs). The sum of PFAAs were also compared to the total fl uorine losses detected with CIC (log scale). (b) Compares targeted FTOHs in textile extracts of unexposed fabrics with the sum of PFAA precursors.
Figure 5 In (a) the sum of PFAAs detected after roof-top weathering were compared to the sum of PFAAs detected after extraction of unexposed fabric and application of a TOP assay (on the basis of the fl uorine content of the PFAAs). The sum of PFAAs were also compared to the total fl uorine losses detected with CIC (log scale). (b) Compares targeted FTOHs in textile extracts of unexposed fabrics with the sum of PFAA precursors.CC-BY-NC-ND · From the PDF
Figure 6 Schematic representation of loss mechanisms that that are likely to occur to (a) textiles with SFP fi nishes during weathering: (a1) Loss of larger textile fragments such as fi bers and particles and (a2) the oxidative conversion of PFAS impurities. (b) Displays further a simpli fi ed summary of emission pathways that lead to emission and accumulation of PFAAs in the environment.
Figure 6 Schematic representation of loss mechanisms that that are likely to occur to (a) textiles with SFP fi nishes during weathering: (a1) Loss of larger textile fragments such as fi bers and particles and (a2) the oxidative conversion of PFAS impurities. (b) Displays further a simpli fi ed summary of emission pathways that lead to emission and accumulation of PFAAs in the environment.CC-BY-NC-ND · From the PDF

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 118

  1. 10.3390/su13116501 · DOI
  2. 10.1007/978-3-030-62796-6_1 · DOI
  3. 10.1002/bse.624 · DOI
  4. 10.1108/MD-07-2018-0724 · DOI
  5. 10.1016/j.ijpe.2020.107844 · DOI
  6. 10.1108/ijoa-04-2020-2120 · DOI
  7. 10.1016/j.techfore.2020.120420 · DOI
  8. 10.1016/j.resconrec.2019.104502 · DOI · Paper page
  9. 10.1080/00207543.2019.1661532 · DOI
  10. 10.1016/j.jclepro.2019.01.091 · DOI
  11. 10.1111/j.1540-5885.2009.00675.x · DOI
  12. 10.1016/j.ijpe.2013.12.026 · DOI
  13. Blalock H. M., 1985, Causal models in the social sciences
  14. 10.2307/270941 · DOI
  15. Blunck E., 2017, Industry 4.0 – An opportunity to realize sustainable manufacturing and its potential for a circular economy, DIEM: Dubrovnik International Economic Meeting, 3, 644
  16. 10.1016/j.lrp.2019.101950 · DOI
  17. 10.1002/bse.2614 · DOI
  18. 10.1007/s11213-018-9453-z · DOI
  19. 10.1115/MSEC2021-62394 · DOI
  20. Charmaz K., 2006, Constructing grounded theory: A practical guide through qualitative analysis
  21. 10.1016/j.resourpol.2020.101596 · DOI
  22. 10.1002/smj.4250150910 · DOI · Paper page
  23. 10.1016/j.emj.2019.12.004 · DOI
  24. Creswell J. W., 2003, Research design: Qualitative, quantitative and mixed method approaches
  25. Silva I. A., 2019, Paper presented at the 26th EurOMA Conference Operations Adding Value to Society
  26. 10.1002/bse.1932 · DOI
  27. 10.1016/j.jclepro.2016.10.130 · DOI
  28. 10.1016/j.jclepro.2019.06.349 · DOI
  29. Dev N. K. Shankar R. &Qaiser F. H.(2020).Industry 4.0 and circular economy: Operational excellence for sustainable reverse supply chain performance.153.https://doi.org/10.1016/j.resconrec.2019.104583 · DOI
  30. 10.1016/j.jclepro.2020.125264 · DOI
  31. 10.1016/j.resconrec.2018.09.016 · DOI
  32. Eamonn K, 2015, Business ecosystems come of age
  33. 10.1037//1082-989X.5.2.155 · DOI
  34. 10.1080/00207543.2021.1906971 · DOI
  35. 10.1162/jiec.1997.1.1.67 · DOI
  36. 10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E · DOI
  37. Ellen MacArthur Foundation, 2016, Intelligent assets: Unlocking the circular economy potential
  38. 10.7551/mitpress/8896.001.0001 · DOI
  39. 10.1016/j.resconrec.2020.105064 · DOI
  40. Fabbe‐Costes N., 2021, Paper presented at the Euroma, Berlin (Virtual conference)
  41. 10.1016/j.jmsy.2018.03.005 · DOI
  42. 10.1016/0272-6963(90)90098-X · DOI
  43. Gatenholm G., 2021, Paper presented at the Euroma, Berlin (Virtual conference)
  44. Gaur V. & Gaiha A. (2020).Building a transparent supply chain.Harvard Business Review Magazine(May–June 2020) 94–103.
  45. 10.1016/j.jclepro.2016.12.048 · DOI · Paper page
  46. 10.1016/j.omega.2015.05.015 · DOI
  47. Graedel T. E., 2003, Industrial ecology
  48. Henriques J., 2019, “SCALER”—How to create incentives for industrial symbiosis while preventing and mitigating implementation risks (Deliverable 2.3)
  49. 10.1002/bse.739 · DOI
  50. 10.1146/annurev.es.04.110173.000245 · DOI · Paper page
  51. 10.1016/j.jclepro.2017.06.093 · DOI
  52. 10.14743/apem2018.3.287 · DOI
  53. 10.1080/13645570902996301 · DOI · Paper page
  54. 10.1108/md-09-2018-0990 · DOI
  55. 10.1002/bse.1958 · DOI
  56. Kagermann H., 2013, Recommendations for implementing Industry 4.0 data
  57. 10.4324/9781315671420 · DOI
  58. 10.1002/bse.2447 · DOI · Paper page
  59. 10.1016/j.jclepro.2020.125565 · DOI
  60. 10.1142/s1363919617400151 · DOI
  61. 10.1016/j.jbusres.2020.07.044 · DOI · Paper page
  62. Küpper D., 2016, The factory of the future
  63. 10.3390/su10113882 · DOI
  64. 10.3390/su8010043 · DOI
  65. 10.1016/0147-1767(85)90062-8 · DOI · Paper page
  66. 10.1111/j.1530-9290.2011.00444.x · DOI
  67. 10.1016/j.ijpe.2017.01.020 · DOI
  68. 10.1016/j.procir.2019.03.262 · DOI
  69. 10.1080/00207543.2019.1652777 · DOI
  70. 10.1108/09574090410700275 · DOI
  71. Miles M. B., 1994, Qualitative data analysis: An expanded sourcebook
  72. Ministry of Enterprise and Innovation, 2016, Smart industry—A strategy for new industrialisation for Sweden (N2016.06)
  73. 10.3390/su13094865 · DOI
  74. 10.3390/su10010247 · DOI
  75. 10.1016/j.spc.2020.10.019 · DOI
  76. 10.1002/bse.2776 · DOI
  77. 10.1016/j.resconrec.2020.104986 · DOI
  78. 10.1016/j.procir.2017.02.047 · DOI · Paper page
  79. 10.1002/j.2158-1592.2010.tb00125.x · DOI
  80. 10.1016/j.spc.2021.01.023 · DOI
  81. 10.1108/01443579310039533 · DOI
  82. 10.1108/ijopm-09-2017-0530 · DOI
  83. Porter M. E., 1995, Green and competitive: Ending the stalemate
  84. 10.1080/00207543.2019.1650976 · DOI
  85. Price Waterhouse Cooper, 2016, Industry 4.0—Building your digital enterprise
  86. Price Waterhouse Cooper, 2018, Skills for smart industrial specialisation and digital transformation
  87. 10.1002/csr.1761 · DOI
  88. 10.1016/j.jclepro.2019.06.169 · DOI
  89. 10.1016/j.procir.2017.03.005 · DOI
  90. 10.1109/ICE/ITMC52061.2021.9570204 · DOI
  91. SCALER, 2017, “SCALER”—Helping industries increase efficiency through resource sharing
  92. 10.1108/sampj-04-2019-0150 · DOI
  93. 10.1016/j.jclepro.2018.08.320 · DOI
  94. Schuh G., 2020, Industrie 4.0 maturity index: Managing the digital transformation of industries (Update 2020)
  95. 10.1002/bse.2884 · DOI
  96. 10.1016/j.jclepro.2020.125280 · DOI
  97. 10.3390/app10238502 · DOI
  98. Siegel A., 2014, Retail horizons—Envisioning the future of retail
  99. 10.1016/j.resconrec.2017.10.033 · DOI
  100. 10.1108/ijccsm-09-2016-0144 · DOI
  101. Storer M., 2009, Paper presented at the enhancing the innovation environment: Proceedings of the 10th International CINet Conference
  102. 10.1016/j.jom.2014.09.003 · DOI
  103. 10.3390/su13031434 · DOI
  104. 10.1002/smj.640 · DOI · Paper page
  105. 10.1525/cmr.2016.58.4.13 · DOI · Paper page
  106. 10.1093/icc/3.3.537-a · DOI · Paper page
  107. 10.1002/(SICI)1097-0266(199708)18:7<509::AID-SMJ882>3.0.CO;2-Z · DOI · Paper page
  108. Teknikföretagen, 2017, Made in Sweden 2030—Strategic agenda for innovation in production
  109. 10.1016/j.jclepro.2018.11.291 · DOI
  110. 10.1016/j.promfg.2020.11.059 · DOI
  111. 10.1016/j.jom.2018.09.004 · DOI
  112. Vladimirova D., 2018, “SCALER”—Lessons learnt & best practices for enhancing industrial symbiosis in the process industry (Deliverable 2.2)
  113. 10.1186/1748-5908-10-S1-A44 · DOI
  114. 10.1111/jpim.12394 · DOI
  115. World Manufacturing Forum, 2019, The 2019 World Manufacturing Forum Report—Skills for the future of manufacturing
  116. Yin R. K., 2014, Case study research design and methods
  117. 10.1016/j.mfglet.2015.11.005 · DOI
  118. 10.3390/su9050765 · DOI

Cited by

Sorted by citations

See all 259

Metadata

Authors
Chari, A., Niedenzu, D., Despeisse, M., Machado, C. G., Azevedo, J. D., Boavida‐Dias, R., & Johansson, B.
Affiliations
  • Department of Industrial and Materials Science Chalmers University of Technology Gothenburg Sweden
  • Institute for Manufacturing University of Cambridge Cambridge UK
  • Jönköping International Business School, Business Administration Jönköping University Jönköping Sweden
  • FEUGA, Department of Innovation &amp; Technology Transfer Campus Universitário Plaza Miralles Vigo Spain
  • Instituto de Soldadura e Qualidade (ISQ), Low Carbon and Resource Efficiency, R&amp;Di Grijó Portugal
ORCID
Venue
Business Strategy and the Environment
Publisher
Wiley
Published
2022-03-22
Volume
31
Issue
5
Pages
2500-2517
ISSN
  • 0964-4733
  • 1099-0836
DOI
10.1002/bse.3040
Cited by
259
References
7
Language
en
Licence
creativecommons.org/licenses/by-nc-nd/4.0/ (vor)

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review