Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas

ilustraciones

Autores:
Cogollo Flórez, Juan Miguel
Tipo de recurso:
Doctoral thesis
Fecha de publicación:
2020
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/79655
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/79655
https://repositorio.unal.edu.co/
Palabra clave:
Ingeniería industrial
650 - Gerencia y servicios auxiliares::658 - Gerencia general
Control de calidad
Calidad de los productos
Gestión de la calidad en cadenas de suministro
Modelado analítico multietapa
Mapas cognitivos grises difusos
Diseño factorial fraccionado
Supply Chain Quality Management
Multi-layer Analytical Modeling
Fuzzy Grey Cognitive Maps
Fractional Factorial Design
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openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_dcab5d92831c39a267d4dceea0dbdb17
oai_identifier_str oai:repositorio.unal.edu.co:unal/79655
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
dc.title.translated.eng.fl_str_mv Modeling supply chain ouality management using a multi-stage approach
title Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
spellingShingle Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
Ingeniería industrial
650 - Gerencia y servicios auxiliares::658 - Gerencia general
Control de calidad
Calidad de los productos
Gestión de la calidad en cadenas de suministro
Modelado analítico multietapa
Mapas cognitivos grises difusos
Diseño factorial fraccionado
Supply Chain Quality Management
Multi-layer Analytical Modeling
Fuzzy Grey Cognitive Maps
Fractional Factorial Design
title_short Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
title_full Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
title_fullStr Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
title_full_unstemmed Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
title_sort Modelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas
dc.creator.fl_str_mv Cogollo Flórez, Juan Miguel
dc.contributor.advisor.none.fl_str_mv Correa Espinal, Alexander Alberto
dc.contributor.author.none.fl_str_mv Cogollo Flórez, Juan Miguel
dc.contributor.researchgroup.spa.fl_str_mv MODELAMIENTO PARA LA GESTIÓN DE OPERACIONES (GIMGO)
dc.subject.ddc.spa.fl_str_mv Ingeniería industrial
650 - Gerencia y servicios auxiliares::658 - Gerencia general
topic Ingeniería industrial
650 - Gerencia y servicios auxiliares::658 - Gerencia general
Control de calidad
Calidad de los productos
Gestión de la calidad en cadenas de suministro
Modelado analítico multietapa
Mapas cognitivos grises difusos
Diseño factorial fraccionado
Supply Chain Quality Management
Multi-layer Analytical Modeling
Fuzzy Grey Cognitive Maps
Fractional Factorial Design
dc.subject.lemb.none.fl_str_mv Control de calidad
Calidad de los productos
dc.subject.proposal.spa.fl_str_mv Gestión de la calidad en cadenas de suministro
Modelado analítico multietapa
Mapas cognitivos grises difusos
Diseño factorial fraccionado
dc.subject.proposal.eng.fl_str_mv Supply Chain Quality Management
Multi-layer Analytical Modeling
Fuzzy Grey Cognitive Maps
Fractional Factorial Design
description ilustraciones
publishDate 2020
dc.date.issued.none.fl_str_mv 2020
dc.date.accessioned.none.fl_str_mv 2021-06-19T14:22:24Z
dc.date.available.none.fl_str_mv 2021-06-19T14:22:24Z
dc.type.spa.fl_str_mv Trabajo de grado - Doctorado
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/doctoralThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.coar.spa.fl_str_mv http://purl.org/coar/resource_type/c_db06
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TD
format http://purl.org/coar/resource_type/c_db06
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/79655
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/79655
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.references.spa.fl_str_mv Ajalli, M., & Mozaffari, M. M. (2018). Appraisal the key factors of SCQM using a combined approach of SWARA-FISM. International Journal of Supply Chain Management, 7(4), 13–21.
Amer, Y., Luong, L., & Lee, S. H. (2010). Case study: Optimizing order fulfillment in a global retail supply chain. International Journal of Production Economics, 127(2), 278–291. https://doi.org/10.1016/j.ijpe.2009.08.020
Bautista-Santos, H., Martínez-Flores, L., Fernández-Lambert, G., Bernabé-Loranca, M. B., Sánchez-Galván, F., & Sablón-Cossío, N. (2015). Integration model of collaborative supply chain. Dyna, 82(193), 145–154. https://doi.org/10.15446/dyna.v82n193.47370
Bayo-Moriones, A., Bello-Pintado, A., & Merino-Díaz-de-Cerio, J. (2011). Quality assurance practices in the global supply chain: the effect of supplier localisation. International Journal of Production Research, 49(1), 255–268. https://doi.org/10.1080/00207543.2010.508953
Borner, K., Chen, C., & Boyack, K. (2003). Visualizing Knowledge Domains. Annual Review of Information Science and Technology, 37(1), 179–255.
Bowersox, D., Closs, D., Cooper, M., & Bowersox, J. (2020). Supply Chain Logistics Management (5th ed.). New York, NY: McGrawHill.
Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299–312. https://doi.org/10.1016/j.ejor.2013.09.032
Bray, R. L., Serpa, J. C., & Colak, A. (2019). Supply Chain Proximity and Product Quality. Management Science, 65(9), 4079–4099. https://doi.org/10.1287/mnsc.2018.3161
Çankaya, S. Y. (2020). The effects of strategic sourcing on supply chain strategies. Journal of Global Operations and Strategic Sourcing, 13(2), 129–148. https://doi.org/10.1108/JGOSS-01-2019-0002
Carmignani, G. (2009). Supply chain and quality management: The definition of a standard to implement a process management system in a supply chain. Business Process Management Journal, 15(3), 395–407. https://doi.org/10.1108/14637150910960639
Chaghooshi, A. J., Soltani-Neshan, M., & Moradi-Moghadam, M. (2015). Canonical correlation analysis between supply chain quality management and competitive advantages. Foundations of Management, 7(1), 83–92.
Chang, K. H., & Lin, G. (2015). Optimal design of hybrid renewable energy systems using simulation optimization. Simulation Modelling Practice and Theory, 52, 40–51. https://doi.org/10.1016/j.simpat.2014.12.002
Chardine-Baumann, E., & Botta-Genoulaz, V. (2014). A framework for sustainable performance assessment of supply chain management practices. Computers and Industrial Engineering, 76, 138–147. https://doi.org/10.1016/j.cie.2014.07.029
Chen, J., Fan, T., & Pan, F. (2021). Urban delivery of fresh products with total deterioration value. International Journal of Production Research, 59(7), 2218–2228. https://doi.org/10.1080/00207543.2020.1828638
Cheung, K. L., & Leung, K. F. (2000). Coordinating replenishments in a supply chain with quality control considerations. Production Planing and Control, 11(7), 697–705. https://doi.org/10.1080/095372800432160
Chiadamrong, N., & Wajcharapornjinda, P. (2012). Developing an economic cost model for quantifying supply chain costs. International Journal of Logistics Systems and Management, 13(4), 540–571. https://doi.org/10.1504/IJLSM.2012.050171
Chinello, E., Lee Herbert-Hansen, Z. N., & Khalid, W. (2020). Assessment of the impact of inventory optimization drivers in a multi-echelon supply chain: Case of a toy manufacturer. Computers and Industrial Engineering, 141, 106232. https://doi.org/10.1016/j.cie.2019.106232
Chopra, S. (2018). Supply Chain Management: Strategy, Planning, and Operation (7th ed.). New York: Pearson.
Choudhary, D., Shankar, R., Tiwari, M. K., & Purohit, A. K. (2016). VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints. International Journal of Production Research, 54(13), 3978–3993. https://doi.org/10.1080/00207543.2016.1168943
Christoforou, A., & Andreou, A. S. (2017). A framework for static and dynamic analysis of multi-layer fuzzy cognitive maps. Neurocomputing, 232, 133–145. https://doi.org/10.1016/j.neucom.2016.09.115
Christova, N., Stylios, C., & Groumpos, P. (2003). Production Planning for Complex Plants using Fuzzy Cognitive Maps. IFAC Proceedings Volumes, 36(3), 81–86. https://doi.org/10.1016/S1474-6670(17)37739-X
Cogollo-Flórez, Juan M., & Correa-Espinal, A. A. (2019). Analytical modeling of supply chain quality management coordination and integration: A literature review. Quality Management Journal, 26(2), 72–83. https://doi.org/10.1080/10686967.2019.1580553
Cogollo-Flórez, Juan M, & Correa-Espinal, A. A. (2017). Modeling Supply Chain Quality Management Performance. In Proceedings of the International Conference on Modeling and Applied Simulation 2017 (pp. 115–122). Barcelona, Spain.
Cogollo-Flórez, Juan Miguel, & Correa-Espinal, A. A. (2018). Rule-based Modeling of Supply Chain Quality Management. In A. Bruzzone, F. De Felice, C. Frydman, F. Longo, M. Massei, & A. Solis (Eds.), Proceedings of The International Conference on Modeling and Applied Simulation 2018 (pp. 120–125). Budapest, Hungary.
Cogollo Flórez, J. M., & Ruiz Vásquez, C. (2019). Prácticas de responsabilidad sostenible de cadenas de suministro: Revisión y propuesta. Revista Venezolana de Gerencia, 24(87), 668–683.
Cogollo, J., & Correa, A. (2019). Modeling Supply Chain Quality Management using Multi-Layer Fuzzy Cognitive Maps. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1–6). New Orleans, LA: IEEE. https://doi.org/10.1109/FUZZ-IEEE.2019.8858995
Cooper, M., Lambert, D., & Pagh, J. (1997). Supply Chain Management: More Than a New Name for Logistics. The International Journal of Logistics Management, 8(1), 1–14. https://doi.org/10.1108/09574099710805556
Council of Supply Chain Management Professionals. (n.d.). CSCMP Supply Chain Management Definitions and Glossary. Retrieved June 13, 2020, from https://cscmp.org/CSCMP/Academia/SCM_Definitions_and_Glossary_of_Terms/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms.aspx?hkey=60879588-f65f-4ab5-8c4b-6878815ef921
Coyle, J., Langley, J., Novack, R., & Gibson, B. (2017). Supply Chain Management: A Logistics Perspective (10th ed.). Boston, USA: Cengage Learning.
Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). Los Angeles, CA: SAGE.
Cruz Trejos, E., Correa Espinal, A. A., & Cogollo Florez, J. M. (2012). Supply Chain Social Responsibility. Gestión y Región, 13, 89–106.
Das, K., & Sengupta, S. (2010). Modelling supply chain network: a quality-oriented approach. International Journal of Quality & Reliability Management, 27(5), 506–526. https://doi.org/10.1108/09574090910954864
Das, Kanchan, & Lashkari, R. S. (2015). A Supply Chain Product Delivery and Distribution Planning Model. Operations and Supply Chain Management: An International Journal, 8(1), 22–27. https://doi.org/10.31387/oscm0190129
Dellana, S., & Kros, J. (2014). An exploration of quality management practices, perceptions and program maturity in the supply chain. International Journal of Operations & Production Management, 34(6), 786–806. https://doi.org/10.1108/09574090910954864
Dickerson, J. A., & Kosko, B. (1994). Virtual Worlds as Fuzzy Cognitive Maps. Presence: Teleoperators and Virtual Environments, 3(2), 173–189. https://doi.org/10.1109/VRAIS.1993.380742
Duman, E. (2007). Decision making by simulation in a parcel transportation company. Journal of The Franklin Institute, 344(5), 672–683. https://doi.org/10.1016/j.jfranklin.2006.02.030
Edmonds, W., & Kennedy, T. (2017). An Applied Guide to Research Designs: Quantitative, Qualitative, and Mixed Methods (2nd ed.). Los Angeles, CA: SAGE.
Evans, J. R., Foster, S. T., & Linderman, K. (2014). A Content Analysis of Research in Quality Management and a Proposed Agenda for Future Research. Quality Management Journal, 21(2), 17–44.
Fernandes, A. C., Sampaio, P., & Carvalho, M. do S. (2014). Quality Management and Supply Chain Management Integration: a conceptual model. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 773–780). Bali, Indonesia.
Flynn, B., & Zhao, X. (2015). Global Supply Chain Quality Management: Product Recalls and Their Impact. Boca Raton: CRC Press.
Foster, S. T. (2008). Towards an understanding of supply chain quality management. Journal of Operations Management, 26(4), 461–467. https://doi.org/10.1016/j.jom.2007.06.003
Foster, S. T. (2017). Managing Quality: Integrating the Supply Chain (6th ed.). New Jersey: Pearson.
Galindo-Pacheco, G. M., Paternina-Arboleda, C. D., Barbosa-Correa, R. A., & Llinás-Solano, H. (2012). Non-linear programming model for cost minimization in a supply chain, including non-quality and inspection costs. International Journal of Operational Research, 14(3), 301–323. https://doi.org/10.1504/IJOR.2012.047092
Gao, C., Cheng, T. C. E., Shen, H., & Xu, L. (2016). Incentives for quality improvement efforts coordination in supply chains with partial cost allocation contract. International Journal of Production Research, 54(20), 6213–6231. https://doi.org/10.1080/00207543.2016.1191691
Gumrukcu, S., Rossetti, M. D., & Buyurgan, N. (2008). Quantifying the costs of cycle counting in a two-echelon supply chain with multiple items. International Journal of Production Economics, 116(2), 263–274. https://doi.org/10.1016/j.ijpe.2008.09.006
Gutiérrez, H., & De La Vara, R. (2012). Análisis y diseño de experimentos (3rd ed.). México: McGrawHill.
Gylling, M., Heikkilä, J., Jussila, K., & Saarinen, M. (2015). Making decisions on offshore outsourcing and backshoring: A case study in the bicycle industry. International Journal of Production Economics, 162, 92–100. https://doi.org/10.1016/j.ijpe.2015.01.006
Harrison, A., Van Hoek, R., & Skipworth, H. (2014). Logistics Management and Strategy: Competing Throug the Supply Chain (5th ed.). Harlow, UK: Pearson.
Hasani, A., Zegordi, S. H., & Nikbakhsh, E. (2012). Robust closed-loop supply chain network design for perishable goods in agile manufacturing under uncertainty. International Journal of Production Research, 50(16), 4649–4669. https://doi.org/10.1080/00207543.2011.625051
Hatwagner, M. F., Buruzs, A., Torma, A., & Koczy, L. T. (2015). Introduction of Modeling Complex Management Systems using Fuzzy Cognitive Map. The 7th International Conference on Information Technology, 2015, 508–514. https://doi.org/10.15849/icit.2015.0092
Hugos, M. (2018). Essentials of Supply Chain Management (4th ed.). Hoboken, NJ: Wiley.
Huo, B., Ye, Y., Zhao, X., & Zhu, K. (2016). Supply chain quality integration: A taxonomy perspective. International Journal of Production Economics, In Press, 1–11. https://doi.org/10.1016/j.ijpe.2016.05.004
Jacobs, F., & Chase, R. (2018). Operations and Supply Chain Management (15th ed.). New York, NY: McGrawHill.
Jaqueta, S. D. J., Mashilo, E. N., Mocke, K., & Agigi, A. F. A. (2020). Physical distribution challenges and adaptations: A qualitative study of South Africa-based organisations operating in emerging African markets. Journal of Transport and Supply Chain Management, 14(1), 1–16. https://doi.org/10.4102/jtscm.v14i0.475
Jetter, A. J., & Kok, K. (2014). Fuzzy Cognitive Maps for futures studies-A methodological assessment of concepts and methods. Futures, 61, 45–57. https://doi.org/10.1016/j.futures.2014.05.002
Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Joint Technical Report. Australia: Department of Computer Science. Keele University. https://doi.org/10.1.1.122.3308
Kleijnen, J. (2005). An overview of the design and analysis of simulation experiments for sensitivity analysis. European Journal of Operational Research, 164(2), 287–300. https://doi.org/10.1016/j.ejor.2004.02.005
Kleijnen, J. P. C., & Smits, M. T. (2003). Performance metrics in supply chain management. Journal of the Operational Research Society, 54(5), 507–514. https://doi.org/10.1057/palgrave.jors.2601539
Konti, A., & Damigos, D. (2018). Exploring strengths and weaknesses of bioethanol production from bio-waste in Greece using Fuzzy Cognitive Maps. Energy Policy, 112, 4–11. https://doi.org/10.1016/j.enpol.2017.09.053
Kosko, B. (1986). Fuzzy cognitive maps. Int. J. Man-Machine Studies, 24, 65–75.
Kuei, C.-H., & Madu, C. N. (2001). Identifying critical success factors for supply chain quality management (SCQM). Asia Pacific Management Review, 6(4), 409–423. https://doi.org/10.4018/jsds.2010070104
Kuei, C.-H., Madu, C. N., & Lin, C. (2011). Developing global supply chain quality management systems. International Journal of Production Research, 49(15), 4457–4481. https://doi.org/10.1080/00207543.2010.501038
Kuei, C.-H., Madu, C. N., & Winch, J. K. (2008). Supply chain quality management: a simulation study. Information and Management Sciences, 19(1), 131–151.
Kumar, S., & Schmitz, S. (2011). Managing recalls in a consumer product supply chain - Root cause analysis and measures to mitigate risks. International Journal of Production Research, 49(1), 235–253. https://doi.org/10.1080/00207543.2010.508952
Laguna, M., & Marklund, J. (2019). Business Process Modeling, Simulation and Design (3rd ed.). Boca Raton, FL: CRC Press.
Lambertini, L. (2018). Coordinating research and development efforts for quality improvement along a supply chain. European Journal of Operational Research, 270(2), 599–605. https://doi.org/10.1016/j.ejor.2018.03.037
Lavin, E., & Giabbanelli, P. (2017). Analyzing and simplifying model uncertainty in fuzzy cognitive maps. In Proceedings of the 2017 Winter Simulation Conference (pp. 1868–1879). Las Vegas, NV, USA. https://doi.org/10.1109/WSC.2017.8247923
Law, A. (2015). Simulation Modeling and Analysis (5th ed.). New York, NY: McGrawHill.
Law, A. (2017). A tutorial on Design of Experiments for simulation modeling. In Proceedings of the 2017 Winter Simulation Conference (pp. 550–564). Las Vegas, NV, USA.
Lejarza, F., & Baldea, M. (2020). Closed-loop optimal operational planning of supply chains with fast product quality dynamics. Computers and Chemical Engineering, 132, 106594. https://doi.org/10.1016/j.compchemeng.2019.106594
León, M., Rodriguez, C., García, M. M., Bello, R., & Vanhoof, K. (2010). Fuzzy Cognitive Maps for Modeling Complex Systems. In Proceedings of 9th Mexican International Conference on Artificial Intelligence, MICAI 2010 (pp. 166–174). https://doi.org/10.1007/978-3-642-16761-4_15
Li, B., & Jiang, Y. (2019). Impacts of returns policy under supplier encroachment with risk-averse retailer. Journal of Retailing and Consumer Services, 47, 104–115. https://doi.org/10.1016/j.jretconser.2018.11.011
Lin, C., Chow, W. S., Madu, C. N., Kuei, C.-H., & Pei Yu, P. (2005). A structural equation model of supply chain quality management and organizational performance. International Journal of Production Economics, 96(3), 355–365. https://doi.org/10.1016/j.ijpe.2004.05.009
Liu, S., & Lin, Y. (2006). Grey Information: Theory and Practical Applications. London, UK: Springer.
Liu, Y., Fang, S., Fang, Z., & Hipel, K. (2012). Petri net model for supply-chain quality conflict resolution of a complex product. Kybernetes, 41(7/8), 920–928. https://doi.org/10.1108/K-01-2015-0009
Lorscheid, I., Heine, B. O., & Meyer, M. (2012). Opening the “black box” of simulations: increased transparency and effective communication through the systematic design of experiments. Computational and Mathematical Organization Theory, 18(1), 22–62. https://doi.org/10.1007/s10588-011-9097-3
Lou, P., Liu, Q., Zhou, Z., & Quan, S. (2009). Production-Outsourcing Supply Chain Quality Management Based on Multi-Agent System. In Proceedings of The 16th International Conference on Industrial Engineering and Engineering Management, 2009. IE&EM ’09. (pp. 1555–1559).
Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of Cleaner Production, 140, 1686–1698. https://doi.org/10.1016/j.jclepro.2016.09.078
Mallick, R. K., Manna, A. K., & Mondal, S. K. (2018). A supply chain model for imperfect production system with stochastic lead time demand. Journal of Management Analytics, 5(4), 309–333. https://doi.org/10.1080/23270012.2018.1530619
Marucheck, A., Greis, N., Mena, C., & Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of Operations Management, 29(7–8), 707–720. https://doi.org/10.1016/j.jom.2011.06.007
Masoudipour, E., Amirian, H., & Sahraeian, R. (2017). A novel closed-loop supply chain based on the quality of returned products. Journal of Cleaner Production, 151, 344–355. https://doi.org/10.1016/j.jclepro.2017.03.067
Melnyk, S. a., Lummus, R. R., Vokurka, R. J., Burns, L. J., & Sandor, J. (2009). Mapping the future of supply chain management: a Delphi study. International Journal of Production Research, 47(16), 4629–4653. https://doi.org/10.1080/00207540802014700
Mendes Dos Reis, J. G. (2011). Modelo de Avaliação da Qualidade para Redes de Suprimentos. Universidade Paulista: Tese de Doutoramento em Engenharia de Produção.
Merigó, J. M., & Yang, J. B. (2017). A bibliometric analysis of operations research and management science. Omega, 73, 37–48. https://doi.org/10.1016/j.omega.2016.12.004
Modak, N. M., Panda, S., & Sana, S. S. (2016). Three-echelon supply chain coordination considering duopolistic retailers with perfect quality products. International Journal of Production Economics, 182, 564–578. https://doi.org/10.1016/j.ijpe.2015.05.021
Moharana, H., Murty, J. S., Senapati, S. K., & Khuntia, K. (2012). Coordination, Collaboration and Integration for Supply Chain Management. International Journal of Interscience Management Review (IMR), 2(2), 46–50.
Montevechi, J. A. B., De Almeida Filho, R. G., Paiva, A. P., Costa, R. F. S., & Medeiros, A. L. (2010). Sensitivity analysis in discrete-event simulation using fractional factorial designs. Journal of Simulation, 4(2), 128–142. https://doi.org/10.1057/jos.2009.23
Montgomery, D. (2017). Design and Analysis of Experiments (9th ed.). Hoboken, NJ: John Wiley & Sons.
Montoya-Torres, J. R., & Ortiz-Vargas, D. A. (2014). Collaboration and information sharing in dyadic supply chains: A literature review over the period 2000–2012. Estudios Gerenciales, 30, 343–354. https://doi.org/10.1016/j.estger.2014.05.006
Montoya-Torres, J. R., & Ortiz, D. (2011). Analysis of the collaboration concept in supply chain: A scientific literature review. In Proceedings of Ninth Latin American and Caribbean Conference. (pp. 1–10). August 3-5, Medellín, Colombia.
Mota, B., Gomes, M. I., Carvalho, A., & Barbosa-Povoa, A. P. (2015). Towards supply chain sustainability: Economic, environmental and social design and planning. Journal of Cleaner Production, 105, 14–27. https://doi.org/10.1016/j.jclepro.2014.07.052
Mourhir, A., Papageorgiou, E., Kokkinos, K., & Rachidi, T. (2017). Exploring Precision Farming Scenarios Using Fuzzy Cognitive Maps. Sustainability, 9(7), 1241. https://doi.org/10.3390/su9071241
Mpelogianni, V., Marnetta, P., & Groumpos, P. P. (2015). Fuzzy Cognitive Maps in the Service of Energy Efficiency. IFAC-PapersOnLine, 48(24), 1–6. https://doi.org/10.1016/j.ifacol.2015.12.047
Nagar, L., & Jain, K. (2008). Supply chain planning using multi-stage stochastic programming. Supply Chain Management: An International Journal, 13(3), 251–256. https://doi.org/10.1108/13598540810871299
Narasimhan, R., & Nair, A. (2005). The antecedent role of quality, information sharing and supply chain proximity on strategic alliance formation and performance. International Journal of Production Economics, 96(3), 301–313. https://doi.org/10.1016/j.ijpe.2003.06.004
Narasimhan, V., Venkatasubbaiah, K., & Avadhani, P. S. (2013). Identification of Critical SSCM Activities Through Confirmatory Factor Analysis. International Journal for Quality Research, 7(2), 239–248.
Obiedat, M., & Samarasinghe, S. (2016). A novel semi-quantitative Fuzzy Cognitive Map model for complex systems for addressing challenging participatory real life problems. Applied Soft Computing Journal, 48, 91–110. https://doi.org/10.1016/j.asoc.2016.06.001
Pang, J., & Tan, K. H. (2018). Supply chain quality and pricing decisions under multi-manufacturer competition. Industrial Management & Data Systems, 118(1), 164–187. https://doi.org/10.1108/IMDS-03-2017-0092
Papageorgiou, E. I., Aggelopoulou, K. D., Gemtos, T. A., & Nanos, G. D. (2013). Yield prediction in apples using Fuzzy Cognitive Map learning approach. Computers and Electronics in Agriculture, 91, 19–29. https://doi.org/10.1016/j.compag.2012.11.008
Papageorgiou, E., Markinos, A., & Gemptos, T. (2009). Application of fuzzy cognitive maps for cotton yield management in precision farming. Expert Systems with Applications, 36(10), 12399–12413. https://doi.org/10.1016/j.eswa.2009.04.046
Parast, M. M. (2013). Supply chain quality management: An inter-organizational learning perspective. International Journal of Quality & Reliability Management, 30(5), 511–529. https://doi.org/10.1108/09574090910954864
Parast, M. M. (2019). A learning perspective of supply chain quality management: empirical evidence from US supply chains. Supply Chain Management: An International Journal, 25(1), 17–34. https://doi.org/10.1108/SCM-01-2019-0028
Park, Y. B. (2005). An integrated approach for production and distribution planning in supply chain management. International Journal of Production Research, 43(6), 1205–1224. https://doi.org/10.1080/00207540412331327718
Pelta, D. A., & Cruz Corona, C. (2018). Soft Computing Based Optimization and Decision Models. Berlin: Springer. https://doi.org/10.1007/978-3-319-64286-4
Peng, X., Prybutok, V., & Xie, H. (2019). Integration of supply chain management and quality management within a quality focused organizational framework. International Journal of Production Research, 58(2), 448–466. https://doi.org/10.1080/00207543.2019.1593548
Pettersson, A. I., & Segerstedt, A. (2013). Measuring supply chain cost. International Journal of Production Economics, 143(2), 357–363. https://doi.org/10.1016/j.ijpe.2012.03.012
Phan, A. C., Abdallah, A. B., & Matsui, Y. (2011). Quality management practices and competitive performance: Empirical evidence from Japanese manufacturing companies. International Journal of Production Economics, 133(2), 518–529. https://doi.org/10.1016/j.ijpe.2011.01.024
Poczeta, K., & Papageorgiou, E. I. (2018). Implementing Fuzzy Cognitive Maps with Neural Networks for Natural Gas Prediction. In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 1026–1032). Volos, Greece: IEEE. https://doi.org/10.1109/ICTAI.2018.00158
Rashid, K., & Aslam, M. M. H. (2012). Business excellence through total supply chain quality management. Asian Journal on Quality, 13(3), 309–324. https://doi.org/10.1108/09574090910954864
Reisman, A. (2004). How can OR/MS Educators Benefit From Creating and Using Taxonomies? INFORMS Transactions on Education, 4(3), 55–65. https://doi.org/10.1287/ited.4.3.55
Robinson, C. J., & Malhotra, M. K. (2005). Defining the concept of supply chain quality management and its relevance to academic and industrial practice. International Journal of Production Economics, 96(3), 315–337. https://doi.org/10.1016/j.ijpe.2004.06.055
Romero, J. C., Coudert, T., Geneste, L., & De Valroger, A. (2012). Collaborative methodology for supply chain quality management: Framework and integration with strategic decision processes in product development. In 6th European Conference on Information Management and Evaluation, ECIME 2012 (pp. 418–427).
Rushton, A., Croucher, P., & Baker, P. (2017). The Handbook of Logistics and Distribution Management: Understanding the Supply Chain (6th ed.). New York, NY: Kogan Page.
Salmeron, J. (2010). Modelling grey uncertainty with Fuzzy Grey Cognitive Maps. Expert Systems with Applications, 37(12), 7581–7588. https://doi.org/10.1016/j.eswa.2010.04.085
Sanders, N. (2018). Supply Chain Management: A Global Perspective (2nd ed.). Hoboken, NJ: John Wiley & Sons.
Sarkar, B., Majumder, A., Sarkar, M., Kim, N., & Ullah, M. (2018). Effects of variable production rate on quality of products in a single-vendor multi-buyer supply chain management. The International Journal of Advanced Manufacturing Technology, 99, 567–581. https://doi.org/10.1007/s00170-018-2527-3
Sayama, H. (2015). Introduction to the Modeling and Analysis of Complex Systems. New York: Open SUNY Textbooks.
Shah, J. (2016). Supply Chain Management: Text and Cases (2nd ed.). Noida, India: Pearson.
Sharma, A., Garg, D., & Agarwal, A. (2012). Quality Management in Supply Chains: the Literature Review. International Journal for Quality Research, 6(3), 193–206.
Sharma, A., Garg, D., & Agarwal, A. (2014). Product recall: Supply chain quality issue? International Journal of Intelligent Enterprise, 2(4), 277–293. https://doi.org/10.1504/IJIE.2014.069059
Simchi-Levi, D., Chen, X., & Bramel, J. (2014). The Logic of Logistics: Theory, Algorithms, and Applications for Logistics Management (3rd ed.). New York, NY: Springer.
Skład, A. (2019). Assessing the impact of processes on the Occupational Safety and Health Management System’s effectiveness using the fuzzy cognitive maps approach. Safety Science, 117, 71–80. https://doi.org/10.1016/j.ssci.2019.03.021
Slack, N., Brandon-Jones, A., & Johnston, R. (2016). Operations Management (8th ed.). Harlow, UK: Pearson.
Slack, N., & Lewis, M. (2017). Operations Strategy (5th ed.). Harlow, UK: Pearson.
Song, T., Li, Y., Song, J., & Zhang, Z. (2014). Airworthiness considerations of supply chain management from Boeing 787 Dreamliner battery issue. Procedia Engineering, 80, 628–637. https://doi.org/10.1016/j.proeng.2014.09.118
Steven, A. B., Dong, Y., & Corsi, T. (2014). Global sourcing and quality recalls: An empirical study of outsourcing-supplier concentration-product recalls linkages. Journal of Operations Management, 32(5), 241–253. https://doi.org/10.1016/j.jom.2014.04.003
Su, Q., & Liu, Q. (2011). Supply Chain Quality Management by Contract Design. In D. Önkal & E. Aktas (Eds.), Supply Chain Management - Pathways for Research and Practice (pp. 57–74). Rijeka: InTech.
Suard, S., Hostikka, S., & Baccou, J. (2013). Sensitivity analysis of fire models using a fractional factorial design. Fire Safety Journal, 62, 115–124. https://doi.org/10.1016/j.firesaf.2013.01.031
Sun, P., & Li, Q. (2010). Study on Supply Chain Quality Management Model Based on Immune Theory. 2010 International Conference on Management and Service Science, 1–4. https://doi.org/10.1109/ICMSS.2010.5576336
Susniene, D., Torma, A., Buruzs, A., Hatwágner, M. F., & Kóczy, L. T. (2014). Using Fuzzy Cognitive Map Approach to model the casual relationships in stakeholder management at companies. In 5th IEEE International Conference on Cognitive Infocommunications (pp. 121–124). Vietri sul Mare, Italy.
Tarashioon, S., Van Driel, W. D., & Zhang, G. Q. (2014). Multi-physics reliability simulation for solid state lighting drivers. Microelectronics Reliability, 54(6–7), 1212–1222. https://doi.org/10.1016/j.microrel.2014.02.019
Truong, H. Q., Sampaio, P., Sameiro, M., & Fernandez, A. (2016). An extensive structural model of supply chain quality management and firm performance. International Journal of Quality & Reliability Management, 33(4), 444–464.
Truong, H., Sampaio, P., Carvalho, M. S., Fernandes, A. C., Binh An, D. T., & Vilhenac, E. (2016). An extensive structural model of supply chain quality management and firm performance. International Journal of Quality & Reliability Management, 33(4), 444–464. https://doi.org/10.1108/IJQRM-11-2014-0188
Tsadiras, A. K. (2008). Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps. Information Sciences, 178(20), 3880–3894. https://doi.org/10.1016/j.ins.2008.05.015
Tsai, T. P., & Wang, F.-C. (2004). Improving Supply Chain Management: A Model for Collaborative Quality Control. In Advanced Semiconductor Manufacturing, 2004. ASMC ’04. IEEE Conference and Workshop (pp. 36–42). https://doi.org/10.1109/ASMC.2004.1309531
Wieland, A., Handfield, R. B., & Durach, C. F. (2016). Mapping the Landscape of Future Research Themes in Supply Chain Management. Journal of Business Logistics, 37(3), 205–212.
Wood, L. C., Wang, J. X., Olesen, K., & Reiners, T. (2017). The effect of slack, diversification, and time to recall on stock market reaction to toy recalls. International Journal of Production Economics, 193, 244–258. https://doi.org/10.1016/j.ijpe.2017.07.021
Wu, Y., Yang, Y., Wang, Z., & Yuan, J. (2013). Macro Quality Chain Management and Coordination Optimization Research. Journal of Software, 8(8), 2023–2031. https://doi.org/10.4304/jsw.8.8.2023-2031
Xiao, T., Yang, D., & Shen, H. (2011). Coordinating a supply chain with a quality assurance policy via a revenue-sharing contract. International Journal of Production Research, 49(1), 99–120. https://doi.org/10.1080/00207543.2010.508936
Yan, J., Sun, S., Wang, H., & Hua, Z. (2010). Ontology of Collaborative Supply Chain for Quality Management. World Academy of Science, Engineering and Technology, 4(4), 365–370.
Yao, D. Q., & Zhang, N. (2009). Contract design for supply chain quality management. International Journal of Value Chain Management, 3(2), 129–145. https://doi.org/10.1504/IJVCM.2009.026954
Yoo, S. H. (2014). Product quality and return policy in a supply chain under risk aversion of a supplier. International Journal of Production Economics, 154, 146–155. https://doi.org/10.1016/j.ijpe.2014.04.012
Yoo, S. H., & Cheong, T. (2018). Quality improvement incentive strategies in a supply chain. Transportation Research Part E: Logistics and Transportation Review, 114, 331–342. https://doi.org/10.1016/j.tre.2018.01.005
Yu, Y., & Huo, B. (2018). Supply chain quality integration: relational antecedents and operational consequences. Supply Chain Management: An International Journal, 23(3), 188–206. https://doi.org/10.1108/SCM-08-2017-0280
Zeng, J., Phan, C. A., & Matsui, Y. (2013). Supply chain quality management practices and performance: An empirical study. Operations Management Research, 6(1–2), 19–31. https://doi.org/10.1007/s12063-012-0074-x
Zhang, M., Guo, H., Huo, B., Zhao, X., & Huang, J. (2017). Linking supply chain quality integration with mass customization and product modularity. International Journal of Production Economics, 207, 227–235. https://doi.org/10.1016/j.ijpe.2017.01.011
Zimon, D. (2017). The Impact of TQM Philosophy for the Improvement of Logistics Processes in the Supply Chain. International Journal for Quality Research, 11(1), 3–16. https://doi.org/10.18421/IJQR11.01-01
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spelling Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Correa Espinal, Alexander Alberto1fea2ec70ac561a328308971e7f1e263600Cogollo Flórez, Juan Miguel48ca3d420ea8755f1adb302b0b4ed38d600MODELAMIENTO PARA LA GESTIÓN DE OPERACIONES (GIMGO)2021-06-19T14:22:24Z2021-06-19T14:22:24Z2020https://repositorio.unal.edu.co/handle/unal/79655Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesLa investigación en el área de gestión de la calidad en cadenas de suministro evidencia falta de desarrollos enfocados en el análisis de estructuras relacionales para la toma de decisiones táctico-estratégicas. En esta tesis se propone un modelo analítico para la coordinación e integración de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapas. La metodología de modelado propuesta integra mapas cognitivos grises difusos multicapa para la configuración estructural y diseños factoriales fraccionados para validar el desempeño dinámico del modelo. Las variables que representan el desempeño global de la gestión de la calidad en cadenas de suministro están agrupadas en la capa principal. Las variables del desempeño en calidad en las tres etapas de la cadena de suministro están agrupadas en submapas en una segunda capa. La validación del modelo vía experimentos de simulación computacional permitió identificar los factores principales estadísticamente significativos en cada mapa y determinar la asignación de valores grises o concretos a los mismos. Finalmente, los aportes realizados en esta investigación constituyen un punto de partida para futuras aplicaciones en sectores específicos y la integración de otras técnicas cuantitativas. (Tomado de la fuente)Research in Supply Chain Quality Management lacks developments focused on the analysis of relational structures for tactical-strategic decision making. This doctoral thesis proposes an analytical model for Supply Chain Quality Management coordination and integration, by using a multi-stage approach. The proposed modeling methodology integrates Multi-layer Fuzzy Grey Cognitive Maps for the structural configuration and fractional factorial designs to validate the dynamic performance of the model. The variables that represent the overall performance of Supply Chain Quality Management are grouped in the main layer. The quality performance variables in the three stages of the supply chain are grouped into submaps in a second layer. The validation of the model via computational simulation experiments made it possible to identify statistically significant factors main in each map and to determine the assignment of gray or specific values to them. Finally, the contributions made in this research constitute a starting point for future applications in specific sectors and the integration of other quantitative techniques. (Tomado de la fuente)DoctoradoDoctor en IngenieríaSe utilizó una metodología secuencial exploratoria que permite integrar referentes teóricos para un posterior análisis cuantitativoGestión de la Cadena de Suministro132 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Doctorado en Ingeniería - Industria y OrganizacionesDepartamento de Ingeniería de la OrganizaciónFacultad de MinasMedellínUniversidad Nacional de Colombia - Sede MedellínIngeniería industrial650 - Gerencia y servicios auxiliares::658 - Gerencia generalControl de calidadCalidad de los productosGestión de la calidad en cadenas de suministroModelado analítico multietapaMapas cognitivos grises difusosDiseño factorial fraccionadoSupply Chain Quality ManagementMulti-layer Analytical ModelingFuzzy Grey Cognitive MapsFractional Factorial DesignModelado de la gestión de la calidad en cadenas de suministro usando un enfoque multi-etapasModeling supply chain ouality management using a multi-stage approachTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDAjalli, M., & Mozaffari, M. M. (2018). Appraisal the key factors of SCQM using a combined approach of SWARA-FISM. International Journal of Supply Chain Management, 7(4), 13–21.Amer, Y., Luong, L., & Lee, S. H. (2010). Case study: Optimizing order fulfillment in a global retail supply chain. International Journal of Production Economics, 127(2), 278–291. https://doi.org/10.1016/j.ijpe.2009.08.020Bautista-Santos, H., Martínez-Flores, L., Fernández-Lambert, G., Bernabé-Loranca, M. B., Sánchez-Galván, F., & Sablón-Cossío, N. (2015). Integration model of collaborative supply chain. Dyna, 82(193), 145–154. https://doi.org/10.15446/dyna.v82n193.47370Bayo-Moriones, A., Bello-Pintado, A., & Merino-Díaz-de-Cerio, J. (2011). Quality assurance practices in the global supply chain: the effect of supplier localisation. International Journal of Production Research, 49(1), 255–268. https://doi.org/10.1080/00207543.2010.508953Borner, K., Chen, C., & Boyack, K. (2003). Visualizing Knowledge Domains. Annual Review of Information Science and Technology, 37(1), 179–255.Bowersox, D., Closs, D., Cooper, M., & Bowersox, J. (2020). Supply Chain Logistics Management (5th ed.). New York, NY: McGrawHill.Brandenburg, M., Govindan, K., Sarkis, J., & Seuring, S. (2014). Quantitative models for sustainable supply chain management: Developments and directions. European Journal of Operational Research, 233(2), 299–312. https://doi.org/10.1016/j.ejor.2013.09.032Bray, R. L., Serpa, J. C., & Colak, A. (2019). Supply Chain Proximity and Product Quality. Management Science, 65(9), 4079–4099. https://doi.org/10.1287/mnsc.2018.3161Çankaya, S. Y. (2020). The effects of strategic sourcing on supply chain strategies. Journal of Global Operations and Strategic Sourcing, 13(2), 129–148. https://doi.org/10.1108/JGOSS-01-2019-0002Carmignani, G. (2009). Supply chain and quality management: The definition of a standard to implement a process management system in a supply chain. Business Process Management Journal, 15(3), 395–407. https://doi.org/10.1108/14637150910960639Chaghooshi, A. J., Soltani-Neshan, M., & Moradi-Moghadam, M. (2015). Canonical correlation analysis between supply chain quality management and competitive advantages. Foundations of Management, 7(1), 83–92.Chang, K. H., & Lin, G. (2015). Optimal design of hybrid renewable energy systems using simulation optimization. Simulation Modelling Practice and Theory, 52, 40–51. https://doi.org/10.1016/j.simpat.2014.12.002Chardine-Baumann, E., & Botta-Genoulaz, V. (2014). A framework for sustainable performance assessment of supply chain management practices. Computers and Industrial Engineering, 76, 138–147. https://doi.org/10.1016/j.cie.2014.07.029Chen, J., Fan, T., & Pan, F. (2021). Urban delivery of fresh products with total deterioration value. International Journal of Production Research, 59(7), 2218–2228. https://doi.org/10.1080/00207543.2020.1828638Cheung, K. L., & Leung, K. F. (2000). Coordinating replenishments in a supply chain with quality control considerations. Production Planing and Control, 11(7), 697–705. https://doi.org/10.1080/095372800432160Chiadamrong, N., & Wajcharapornjinda, P. (2012). Developing an economic cost model for quantifying supply chain costs. International Journal of Logistics Systems and Management, 13(4), 540–571. https://doi.org/10.1504/IJLSM.2012.050171Chinello, E., Lee Herbert-Hansen, Z. N., & Khalid, W. (2020). Assessment of the impact of inventory optimization drivers in a multi-echelon supply chain: Case of a toy manufacturer. Computers and Industrial Engineering, 141, 106232. https://doi.org/10.1016/j.cie.2019.106232Chopra, S. (2018). Supply Chain Management: Strategy, Planning, and Operation (7th ed.). New York: Pearson.Choudhary, D., Shankar, R., Tiwari, M. K., & Purohit, A. K. (2016). VMI versus information sharing: an analysis under static uncertainty strategy with fill rate constraints. International Journal of Production Research, 54(13), 3978–3993. https://doi.org/10.1080/00207543.2016.1168943Christoforou, A., & Andreou, A. S. (2017). A framework for static and dynamic analysis of multi-layer fuzzy cognitive maps. Neurocomputing, 232, 133–145. https://doi.org/10.1016/j.neucom.2016.09.115Christova, N., Stylios, C., & Groumpos, P. (2003). Production Planning for Complex Plants using Fuzzy Cognitive Maps. IFAC Proceedings Volumes, 36(3), 81–86. https://doi.org/10.1016/S1474-6670(17)37739-XCogollo-Flórez, Juan M., & Correa-Espinal, A. A. (2019). Analytical modeling of supply chain quality management coordination and integration: A literature review. Quality Management Journal, 26(2), 72–83. https://doi.org/10.1080/10686967.2019.1580553Cogollo-Flórez, Juan M, & Correa-Espinal, A. A. (2017). Modeling Supply Chain Quality Management Performance. In Proceedings of the International Conference on Modeling and Applied Simulation 2017 (pp. 115–122). Barcelona, Spain.Cogollo-Flórez, Juan Miguel, & Correa-Espinal, A. A. (2018). Rule-based Modeling of Supply Chain Quality Management. In A. Bruzzone, F. De Felice, C. Frydman, F. Longo, M. Massei, & A. Solis (Eds.), Proceedings of The International Conference on Modeling and Applied Simulation 2018 (pp. 120–125). Budapest, Hungary.Cogollo Flórez, J. M., & Ruiz Vásquez, C. (2019). Prácticas de responsabilidad sostenible de cadenas de suministro: Revisión y propuesta. Revista Venezolana de Gerencia, 24(87), 668–683.Cogollo, J., & Correa, A. (2019). Modeling Supply Chain Quality Management using Multi-Layer Fuzzy Cognitive Maps. In 2019 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) (pp. 1–6). New Orleans, LA: IEEE. https://doi.org/10.1109/FUZZ-IEEE.2019.8858995Cooper, M., Lambert, D., & Pagh, J. (1997). Supply Chain Management: More Than a New Name for Logistics. The International Journal of Logistics Management, 8(1), 1–14. https://doi.org/10.1108/09574099710805556Council of Supply Chain Management Professionals. (n.d.). CSCMP Supply Chain Management Definitions and Glossary. Retrieved June 13, 2020, from https://cscmp.org/CSCMP/Academia/SCM_Definitions_and_Glossary_of_Terms/CSCMP/Educate/SCM_Definitions_and_Glossary_of_Terms.aspx?hkey=60879588-f65f-4ab5-8c4b-6878815ef921Coyle, J., Langley, J., Novack, R., & Gibson, B. (2017). Supply Chain Management: A Logistics Perspective (10th ed.). Boston, USA: Cengage Learning.Creswell, J. W., & Creswell, J. D. (2018). Research Design: Qualitative, Quantitative, and Mixed Methods Approaches (5th ed.). Los Angeles, CA: SAGE.Cruz Trejos, E., Correa Espinal, A. A., & Cogollo Florez, J. M. (2012). Supply Chain Social Responsibility. Gestión y Región, 13, 89–106.Das, K., & Sengupta, S. (2010). Modelling supply chain network: a quality-oriented approach. International Journal of Quality & Reliability Management, 27(5), 506–526. https://doi.org/10.1108/09574090910954864Das, Kanchan, & Lashkari, R. S. (2015). A Supply Chain Product Delivery and Distribution Planning Model. Operations and Supply Chain Management: An International Journal, 8(1), 22–27. https://doi.org/10.31387/oscm0190129Dellana, S., & Kros, J. (2014). An exploration of quality management practices, perceptions and program maturity in the supply chain. International Journal of Operations & Production Management, 34(6), 786–806. https://doi.org/10.1108/09574090910954864Dickerson, J. A., & Kosko, B. (1994). Virtual Worlds as Fuzzy Cognitive Maps. Presence: Teleoperators and Virtual Environments, 3(2), 173–189. https://doi.org/10.1109/VRAIS.1993.380742Duman, E. (2007). Decision making by simulation in a parcel transportation company. Journal of The Franklin Institute, 344(5), 672–683. https://doi.org/10.1016/j.jfranklin.2006.02.030Edmonds, W., & Kennedy, T. (2017). An Applied Guide to Research Designs: Quantitative, Qualitative, and Mixed Methods (2nd ed.). Los Angeles, CA: SAGE.Evans, J. R., Foster, S. T., & Linderman, K. (2014). A Content Analysis of Research in Quality Management and a Proposed Agenda for Future Research. Quality Management Journal, 21(2), 17–44.Fernandes, A. C., Sampaio, P., & Carvalho, M. do S. (2014). Quality Management and Supply Chain Management Integration: a conceptual model. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 773–780). Bali, Indonesia.Flynn, B., & Zhao, X. (2015). Global Supply Chain Quality Management: Product Recalls and Their Impact. Boca Raton: CRC Press.Foster, S. T. (2008). Towards an understanding of supply chain quality management. Journal of Operations Management, 26(4), 461–467. https://doi.org/10.1016/j.jom.2007.06.003Foster, S. T. (2017). Managing Quality: Integrating the Supply Chain (6th ed.). New Jersey: Pearson.Galindo-Pacheco, G. M., Paternina-Arboleda, C. D., Barbosa-Correa, R. A., & Llinás-Solano, H. (2012). Non-linear programming model for cost minimization in a supply chain, including non-quality and inspection costs. International Journal of Operational Research, 14(3), 301–323. https://doi.org/10.1504/IJOR.2012.047092Gao, C., Cheng, T. C. E., Shen, H., & Xu, L. (2016). Incentives for quality improvement efforts coordination in supply chains with partial cost allocation contract. International Journal of Production Research, 54(20), 6213–6231. https://doi.org/10.1080/00207543.2016.1191691Gumrukcu, S., Rossetti, M. D., & Buyurgan, N. (2008). Quantifying the costs of cycle counting in a two-echelon supply chain with multiple items. International Journal of Production Economics, 116(2), 263–274. https://doi.org/10.1016/j.ijpe.2008.09.006Gutiérrez, H., & De La Vara, R. (2012). Análisis y diseño de experimentos (3rd ed.). México: McGrawHill.Gylling, M., Heikkilä, J., Jussila, K., & Saarinen, M. (2015). Making decisions on offshore outsourcing and backshoring: A case study in the bicycle industry. International Journal of Production Economics, 162, 92–100. https://doi.org/10.1016/j.ijpe.2015.01.006Harrison, A., Van Hoek, R., & Skipworth, H. (2014). Logistics Management and Strategy: Competing Throug the Supply Chain (5th ed.). Harlow, UK: Pearson.Hasani, A., Zegordi, S. H., & Nikbakhsh, E. (2012). Robust closed-loop supply chain network design for perishable goods in agile manufacturing under uncertainty. International Journal of Production Research, 50(16), 4649–4669. https://doi.org/10.1080/00207543.2011.625051Hatwagner, M. F., Buruzs, A., Torma, A., & Koczy, L. T. (2015). Introduction of Modeling Complex Management Systems using Fuzzy Cognitive Map. The 7th International Conference on Information Technology, 2015, 508–514. https://doi.org/10.15849/icit.2015.0092Hugos, M. (2018). Essentials of Supply Chain Management (4th ed.). Hoboken, NJ: Wiley.Huo, B., Ye, Y., Zhao, X., & Zhu, K. (2016). Supply chain quality integration: A taxonomy perspective. International Journal of Production Economics, In Press, 1–11. https://doi.org/10.1016/j.ijpe.2016.05.004Jacobs, F., & Chase, R. (2018). Operations and Supply Chain Management (15th ed.). New York, NY: McGrawHill.Jaqueta, S. D. J., Mashilo, E. N., Mocke, K., & Agigi, A. F. A. (2020). Physical distribution challenges and adaptations: A qualitative study of South Africa-based organisations operating in emerging African markets. Journal of Transport and Supply Chain Management, 14(1), 1–16. https://doi.org/10.4102/jtscm.v14i0.475Jetter, A. J., & Kok, K. (2014). Fuzzy Cognitive Maps for futures studies-A methodological assessment of concepts and methods. Futures, 61, 45–57. https://doi.org/10.1016/j.futures.2014.05.002Kitchenham, B. (2004). Procedures for Performing Systematic Reviews. Joint Technical Report. Australia: Department of Computer Science. Keele University. https://doi.org/10.1.1.122.3308Kleijnen, J. (2005). An overview of the design and analysis of simulation experiments for sensitivity analysis. European Journal of Operational Research, 164(2), 287–300. https://doi.org/10.1016/j.ejor.2004.02.005Kleijnen, J. P. C., & Smits, M. T. (2003). Performance metrics in supply chain management. Journal of the Operational Research Society, 54(5), 507–514. https://doi.org/10.1057/palgrave.jors.2601539Konti, A., & Damigos, D. (2018). Exploring strengths and weaknesses of bioethanol production from bio-waste in Greece using Fuzzy Cognitive Maps. Energy Policy, 112, 4–11. https://doi.org/10.1016/j.enpol.2017.09.053Kosko, B. (1986). Fuzzy cognitive maps. Int. J. Man-Machine Studies, 24, 65–75.Kuei, C.-H., & Madu, C. N. (2001). Identifying critical success factors for supply chain quality management (SCQM). Asia Pacific Management Review, 6(4), 409–423. https://doi.org/10.4018/jsds.2010070104Kuei, C.-H., Madu, C. N., & Lin, C. (2011). Developing global supply chain quality management systems. International Journal of Production Research, 49(15), 4457–4481. https://doi.org/10.1080/00207543.2010.501038Kuei, C.-H., Madu, C. N., & Winch, J. K. (2008). Supply chain quality management: a simulation study. Information and Management Sciences, 19(1), 131–151.Kumar, S., & Schmitz, S. (2011). Managing recalls in a consumer product supply chain - Root cause analysis and measures to mitigate risks. International Journal of Production Research, 49(1), 235–253. https://doi.org/10.1080/00207543.2010.508952Laguna, M., & Marklund, J. (2019). Business Process Modeling, Simulation and Design (3rd ed.). Boca Raton, FL: CRC Press.Lambertini, L. (2018). Coordinating research and development efforts for quality improvement along a supply chain. European Journal of Operational Research, 270(2), 599–605. https://doi.org/10.1016/j.ejor.2018.03.037Lavin, E., & Giabbanelli, P. (2017). Analyzing and simplifying model uncertainty in fuzzy cognitive maps. In Proceedings of the 2017 Winter Simulation Conference (pp. 1868–1879). Las Vegas, NV, USA. https://doi.org/10.1109/WSC.2017.8247923Law, A. (2015). Simulation Modeling and Analysis (5th ed.). New York, NY: McGrawHill.Law, A. (2017). A tutorial on Design of Experiments for simulation modeling. In Proceedings of the 2017 Winter Simulation Conference (pp. 550–564). Las Vegas, NV, USA.Lejarza, F., & Baldea, M. (2020). Closed-loop optimal operational planning of supply chains with fast product quality dynamics. Computers and Chemical Engineering, 132, 106594. https://doi.org/10.1016/j.compchemeng.2019.106594León, M., Rodriguez, C., García, M. M., Bello, R., & Vanhoof, K. (2010). Fuzzy Cognitive Maps for Modeling Complex Systems. In Proceedings of 9th Mexican International Conference on Artificial Intelligence, MICAI 2010 (pp. 166–174). https://doi.org/10.1007/978-3-642-16761-4_15Li, B., & Jiang, Y. (2019). Impacts of returns policy under supplier encroachment with risk-averse retailer. Journal of Retailing and Consumer Services, 47, 104–115. https://doi.org/10.1016/j.jretconser.2018.11.011Lin, C., Chow, W. S., Madu, C. N., Kuei, C.-H., & Pei Yu, P. (2005). A structural equation model of supply chain quality management and organizational performance. International Journal of Production Economics, 96(3), 355–365. https://doi.org/10.1016/j.ijpe.2004.05.009Liu, S., & Lin, Y. (2006). Grey Information: Theory and Practical Applications. London, UK: Springer.Liu, Y., Fang, S., Fang, Z., & Hipel, K. (2012). Petri net model for supply-chain quality conflict resolution of a complex product. Kybernetes, 41(7/8), 920–928. https://doi.org/10.1108/K-01-2015-0009Lorscheid, I., Heine, B. O., & Meyer, M. (2012). Opening the “black box” of simulations: increased transparency and effective communication through the systematic design of experiments. Computational and Mathematical Organization Theory, 18(1), 22–62. https://doi.org/10.1007/s10588-011-9097-3Lou, P., Liu, Q., Zhou, Z., & Quan, S. (2009). Production-Outsourcing Supply Chain Quality Management Based on Multi-Agent System. In Proceedings of The 16th International Conference on Industrial Engineering and Engineering Management, 2009. IE&EM ’09. (pp. 1555–1559).Luthra, S., Govindan, K., Kannan, D., Mangla, S. K., & Garg, C. P. (2017). An integrated framework for sustainable supplier selection and evaluation in supply chains. Journal of Cleaner Production, 140, 1686–1698. https://doi.org/10.1016/j.jclepro.2016.09.078Mallick, R. K., Manna, A. K., & Mondal, S. K. (2018). A supply chain model for imperfect production system with stochastic lead time demand. Journal of Management Analytics, 5(4), 309–333. https://doi.org/10.1080/23270012.2018.1530619Marucheck, A., Greis, N., Mena, C., & Cai, L. (2011). Product safety and security in the global supply chain: Issues, challenges and research opportunities. Journal of Operations Management, 29(7–8), 707–720. https://doi.org/10.1016/j.jom.2011.06.007Masoudipour, E., Amirian, H., & Sahraeian, R. (2017). A novel closed-loop supply chain based on the quality of returned products. Journal of Cleaner Production, 151, 344–355. https://doi.org/10.1016/j.jclepro.2017.03.067Melnyk, S. a., Lummus, R. R., Vokurka, R. J., Burns, L. J., & Sandor, J. (2009). Mapping the future of supply chain management: a Delphi study. International Journal of Production Research, 47(16), 4629–4653. https://doi.org/10.1080/00207540802014700Mendes Dos Reis, J. G. (2011). Modelo de Avaliação da Qualidade para Redes de Suprimentos. Universidade Paulista: Tese de Doutoramento em Engenharia de Produção.Merigó, J. M., & Yang, J. B. (2017). A bibliometric analysis of operations research and management science. Omega, 73, 37–48. https://doi.org/10.1016/j.omega.2016.12.004Modak, N. M., Panda, S., & Sana, S. S. (2016). Three-echelon supply chain coordination considering duopolistic retailers with perfect quality products. International Journal of Production Economics, 182, 564–578. https://doi.org/10.1016/j.ijpe.2015.05.021Moharana, H., Murty, J. S., Senapati, S. K., & Khuntia, K. (2012). Coordination, Collaboration and Integration for Supply Chain Management. International Journal of Interscience Management Review (IMR), 2(2), 46–50.Montevechi, J. A. B., De Almeida Filho, R. G., Paiva, A. P., Costa, R. F. S., & Medeiros, A. L. (2010). Sensitivity analysis in discrete-event simulation using fractional factorial designs. Journal of Simulation, 4(2), 128–142. https://doi.org/10.1057/jos.2009.23Montgomery, D. (2017). Design and Analysis of Experiments (9th ed.). Hoboken, NJ: John Wiley & Sons.Montoya-Torres, J. R., & Ortiz-Vargas, D. A. (2014). Collaboration and information sharing in dyadic supply chains: A literature review over the period 2000–2012. Estudios Gerenciales, 30, 343–354. https://doi.org/10.1016/j.estger.2014.05.006Montoya-Torres, J. R., & Ortiz, D. (2011). Analysis of the collaboration concept in supply chain: A scientific literature review. In Proceedings of Ninth Latin American and Caribbean Conference. (pp. 1–10). August 3-5, Medellín, Colombia.Mota, B., Gomes, M. I., Carvalho, A., & Barbosa-Povoa, A. P. (2015). Towards supply chain sustainability: Economic, environmental and social design and planning. Journal of Cleaner Production, 105, 14–27. https://doi.org/10.1016/j.jclepro.2014.07.052Mourhir, A., Papageorgiou, E., Kokkinos, K., & Rachidi, T. (2017). Exploring Precision Farming Scenarios Using Fuzzy Cognitive Maps. Sustainability, 9(7), 1241. https://doi.org/10.3390/su9071241Mpelogianni, V., Marnetta, P., & Groumpos, P. P. (2015). Fuzzy Cognitive Maps in the Service of Energy Efficiency. IFAC-PapersOnLine, 48(24), 1–6. https://doi.org/10.1016/j.ifacol.2015.12.047Nagar, L., & Jain, K. (2008). Supply chain planning using multi-stage stochastic programming. Supply Chain Management: An International Journal, 13(3), 251–256. https://doi.org/10.1108/13598540810871299Narasimhan, R., & Nair, A. (2005). The antecedent role of quality, information sharing and supply chain proximity on strategic alliance formation and performance. International Journal of Production Economics, 96(3), 301–313. https://doi.org/10.1016/j.ijpe.2003.06.004Narasimhan, V., Venkatasubbaiah, K., & Avadhani, P. S. (2013). Identification of Critical SSCM Activities Through Confirmatory Factor Analysis. International Journal for Quality Research, 7(2), 239–248.Obiedat, M., & Samarasinghe, S. (2016). A novel semi-quantitative Fuzzy Cognitive Map model for complex systems for addressing challenging participatory real life problems. Applied Soft Computing Journal, 48, 91–110. https://doi.org/10.1016/j.asoc.2016.06.001Pang, J., & Tan, K. H. (2018). Supply chain quality and pricing decisions under multi-manufacturer competition. Industrial Management & Data Systems, 118(1), 164–187. https://doi.org/10.1108/IMDS-03-2017-0092Papageorgiou, E. I., Aggelopoulou, K. D., Gemtos, T. A., & Nanos, G. D. (2013). Yield prediction in apples using Fuzzy Cognitive Map learning approach. Computers and Electronics in Agriculture, 91, 19–29. https://doi.org/10.1016/j.compag.2012.11.008Papageorgiou, E., Markinos, A., & Gemptos, T. (2009). Application of fuzzy cognitive maps for cotton yield management in precision farming. Expert Systems with Applications, 36(10), 12399–12413. https://doi.org/10.1016/j.eswa.2009.04.046Parast, M. M. (2013). Supply chain quality management: An inter-organizational learning perspective. International Journal of Quality & Reliability Management, 30(5), 511–529. https://doi.org/10.1108/09574090910954864Parast, M. M. (2019). A learning perspective of supply chain quality management: empirical evidence from US supply chains. Supply Chain Management: An International Journal, 25(1), 17–34. https://doi.org/10.1108/SCM-01-2019-0028Park, Y. B. (2005). An integrated approach for production and distribution planning in supply chain management. International Journal of Production Research, 43(6), 1205–1224. https://doi.org/10.1080/00207540412331327718Pelta, D. A., & Cruz Corona, C. (2018). Soft Computing Based Optimization and Decision Models. Berlin: Springer. https://doi.org/10.1007/978-3-319-64286-4Peng, X., Prybutok, V., & Xie, H. (2019). Integration of supply chain management and quality management within a quality focused organizational framework. International Journal of Production Research, 58(2), 448–466. https://doi.org/10.1080/00207543.2019.1593548Pettersson, A. I., & Segerstedt, A. (2013). Measuring supply chain cost. International Journal of Production Economics, 143(2), 357–363. https://doi.org/10.1016/j.ijpe.2012.03.012Phan, A. C., Abdallah, A. B., & Matsui, Y. (2011). Quality management practices and competitive performance: Empirical evidence from Japanese manufacturing companies. International Journal of Production Economics, 133(2), 518–529. https://doi.org/10.1016/j.ijpe.2011.01.024Poczeta, K., & Papageorgiou, E. I. (2018). Implementing Fuzzy Cognitive Maps with Neural Networks for Natural Gas Prediction. In 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 1026–1032). Volos, Greece: IEEE. https://doi.org/10.1109/ICTAI.2018.00158Rashid, K., & Aslam, M. M. H. (2012). Business excellence through total supply chain quality management. Asian Journal on Quality, 13(3), 309–324. https://doi.org/10.1108/09574090910954864Reisman, A. (2004). How can OR/MS Educators Benefit From Creating and Using Taxonomies? INFORMS Transactions on Education, 4(3), 55–65. https://doi.org/10.1287/ited.4.3.55Robinson, C. J., & Malhotra, M. K. (2005). Defining the concept of supply chain quality management and its relevance to academic and industrial practice. International Journal of Production Economics, 96(3), 315–337. https://doi.org/10.1016/j.ijpe.2004.06.055Romero, J. C., Coudert, T., Geneste, L., & De Valroger, A. (2012). Collaborative methodology for supply chain quality management: Framework and integration with strategic decision processes in product development. In 6th European Conference on Information Management and Evaluation, ECIME 2012 (pp. 418–427).Rushton, A., Croucher, P., & Baker, P. (2017). The Handbook of Logistics and Distribution Management: Understanding the Supply Chain (6th ed.). New York, NY: Kogan Page.Salmeron, J. (2010). Modelling grey uncertainty with Fuzzy Grey Cognitive Maps. Expert Systems with Applications, 37(12), 7581–7588. https://doi.org/10.1016/j.eswa.2010.04.085Sanders, N. (2018). Supply Chain Management: A Global Perspective (2nd ed.). Hoboken, NJ: John Wiley & Sons.Sarkar, B., Majumder, A., Sarkar, M., Kim, N., & Ullah, M. (2018). Effects of variable production rate on quality of products in a single-vendor multi-buyer supply chain management. The International Journal of Advanced Manufacturing Technology, 99, 567–581. https://doi.org/10.1007/s00170-018-2527-3Sayama, H. (2015). Introduction to the Modeling and Analysis of Complex Systems. New York: Open SUNY Textbooks.Shah, J. (2016). Supply Chain Management: Text and Cases (2nd ed.). Noida, India: Pearson.Sharma, A., Garg, D., & Agarwal, A. (2012). Quality Management in Supply Chains: the Literature Review. International Journal for Quality Research, 6(3), 193–206.Sharma, A., Garg, D., & Agarwal, A. (2014). Product recall: Supply chain quality issue? International Journal of Intelligent Enterprise, 2(4), 277–293. https://doi.org/10.1504/IJIE.2014.069059Simchi-Levi, D., Chen, X., & Bramel, J. (2014). The Logic of Logistics: Theory, Algorithms, and Applications for Logistics Management (3rd ed.). New York, NY: Springer.Skład, A. (2019). Assessing the impact of processes on the Occupational Safety and Health Management System’s effectiveness using the fuzzy cognitive maps approach. Safety Science, 117, 71–80. https://doi.org/10.1016/j.ssci.2019.03.021Slack, N., Brandon-Jones, A., & Johnston, R. (2016). Operations Management (8th ed.). Harlow, UK: Pearson.Slack, N., & Lewis, M. (2017). Operations Strategy (5th ed.). Harlow, UK: Pearson.Song, T., Li, Y., Song, J., & Zhang, Z. (2014). Airworthiness considerations of supply chain management from Boeing 787 Dreamliner battery issue. Procedia Engineering, 80, 628–637. https://doi.org/10.1016/j.proeng.2014.09.118Steven, A. B., Dong, Y., & Corsi, T. (2014). Global sourcing and quality recalls: An empirical study of outsourcing-supplier concentration-product recalls linkages. Journal of Operations Management, 32(5), 241–253. https://doi.org/10.1016/j.jom.2014.04.003Su, Q., & Liu, Q. (2011). Supply Chain Quality Management by Contract Design. In D. Önkal & E. Aktas (Eds.), Supply Chain Management - Pathways for Research and Practice (pp. 57–74). Rijeka: InTech.Suard, S., Hostikka, S., & Baccou, J. (2013). Sensitivity analysis of fire models using a fractional factorial design. Fire Safety Journal, 62, 115–124. https://doi.org/10.1016/j.firesaf.2013.01.031Sun, P., & Li, Q. (2010). Study on Supply Chain Quality Management Model Based on Immune Theory. 2010 International Conference on Management and Service Science, 1–4. https://doi.org/10.1109/ICMSS.2010.5576336Susniene, D., Torma, A., Buruzs, A., Hatwágner, M. F., & Kóczy, L. T. (2014). Using Fuzzy Cognitive Map Approach to model the casual relationships in stakeholder management at companies. In 5th IEEE International Conference on Cognitive Infocommunications (pp. 121–124). Vietri sul Mare, Italy.Tarashioon, S., Van Driel, W. D., & Zhang, G. Q. (2014). Multi-physics reliability simulation for solid state lighting drivers. Microelectronics Reliability, 54(6–7), 1212–1222. https://doi.org/10.1016/j.microrel.2014.02.019Truong, H. Q., Sampaio, P., Sameiro, M., & Fernandez, A. (2016). An extensive structural model of supply chain quality management and firm performance. International Journal of Quality & Reliability Management, 33(4), 444–464.Truong, H., Sampaio, P., Carvalho, M. S., Fernandes, A. C., Binh An, D. T., & Vilhenac, E. (2016). An extensive structural model of supply chain quality management and firm performance. International Journal of Quality & Reliability Management, 33(4), 444–464. https://doi.org/10.1108/IJQRM-11-2014-0188Tsadiras, A. K. (2008). Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps. Information Sciences, 178(20), 3880–3894. https://doi.org/10.1016/j.ins.2008.05.015Tsai, T. P., & Wang, F.-C. (2004). Improving Supply Chain Management: A Model for Collaborative Quality Control. In Advanced Semiconductor Manufacturing, 2004. ASMC ’04. IEEE Conference and Workshop (pp. 36–42). https://doi.org/10.1109/ASMC.2004.1309531Wieland, A., Handfield, R. B., & Durach, C. F. (2016). Mapping the Landscape of Future Research Themes in Supply Chain Management. Journal of Business Logistics, 37(3), 205–212.Wood, L. C., Wang, J. X., Olesen, K., & Reiners, T. (2017). The effect of slack, diversification, and time to recall on stock market reaction to toy recalls. International Journal of Production Economics, 193, 244–258. https://doi.org/10.1016/j.ijpe.2017.07.021Wu, Y., Yang, Y., Wang, Z., & Yuan, J. (2013). Macro Quality Chain Management and Coordination Optimization Research. Journal of Software, 8(8), 2023–2031. https://doi.org/10.4304/jsw.8.8.2023-2031Xiao, T., Yang, D., & Shen, H. (2011). Coordinating a supply chain with a quality assurance policy via a revenue-sharing contract. International Journal of Production Research, 49(1), 99–120. https://doi.org/10.1080/00207543.2010.508936Yan, J., Sun, S., Wang, H., & Hua, Z. (2010). Ontology of Collaborative Supply Chain for Quality Management. World Academy of Science, Engineering and Technology, 4(4), 365–370.Yao, D. Q., & Zhang, N. (2009). Contract design for supply chain quality management. International Journal of Value Chain Management, 3(2), 129–145. https://doi.org/10.1504/IJVCM.2009.026954Yoo, S. H. (2014). Product quality and return policy in a supply chain under risk aversion of a supplier. International Journal of Production Economics, 154, 146–155. https://doi.org/10.1016/j.ijpe.2014.04.012Yoo, S. H., & Cheong, T. (2018). Quality improvement incentive strategies in a supply chain. Transportation Research Part E: Logistics and Transportation Review, 114, 331–342. https://doi.org/10.1016/j.tre.2018.01.005Yu, Y., & Huo, B. (2018). Supply chain quality integration: relational antecedents and operational consequences. Supply Chain Management: An International Journal, 23(3), 188–206. https://doi.org/10.1108/SCM-08-2017-0280Zeng, J., Phan, C. A., & Matsui, Y. (2013). Supply chain quality management practices and performance: An empirical study. Operations Management Research, 6(1–2), 19–31. https://doi.org/10.1007/s12063-012-0074-xZhang, M., Guo, H., Huo, B., Zhao, X., & Huang, J. (2017). Linking supply chain quality integration with mass customization and product modularity. International Journal of Production Economics, 207, 227–235. https://doi.org/10.1016/j.ijpe.2017.01.011Zimon, D. (2017). The Impact of TQM Philosophy for the Improvement of Logistics Processes in the Supply Chain. 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GVyZWNob3MgZGUgYXV0b3IgcXVlIGNvbmxsZXZlIGxhIGRpc3RyaWJ1Y2nDs24gZGUgZXN0b3MgYXJjaGl2b3MgeSBtZXRhZGF0b3MuCkFsIGhhY2VyIGNsaWMgZW4gZWwgc2lndWllbnRlIGJvdMOzbiwgdXN0ZWQgaW5kaWNhIHF1ZSBlc3TDoSBkZSBhY3VlcmRvIGNvbiBlc3RvcyB0w6lybWlub3MuCgpVTklWRVJTSURBRCBOQUNJT05BTCBERSBDT0xPTUJJQSAtIMOabHRpbWEgbW9kaWZpY2FjacOzbiAyNy8yMC8yMDIwCg==

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