Predictor Model of the Supply Chain Effectiveness based on Critical Success Factors in a Commerce Retail Industry
DOI:
https://doi.org/10.21664/2238-8869.2022v11i2.p265-278Palavras-chave:
gestão da cadeia de suprimentos, análise fatorial, análise de caminho, fatores críticos de sucesso, modelos preditoresResumo
Os ambientes de negócios da economia globalizada apresentam complexidade crescente sob condições altamente variáveis de volatilidade, risco e incerteza que exercem intensa pressão sobre os varejistas; alguns deles desenvolvem programas para a melhoria da cadeia de suprimentos. Este artigo trata da determinação dos fatores da cadeia de suprimentos e do desenvolvimento de um modelo de equação estrutural. A primeira seção apresenta os antecedentes, a descrição do problema e uma pesquisa bibliográfica dos fatores da Cadeia de Suprimentos e sua classificação. A seção Metodologia explica o desenvolvimento de um questionário como instrumento de medição baseado nos fatores identificados. A validação do questionário foi com o índice alfa de Cronbach e, em seguida, aplicado a uma amostra de varejistas na região central do México. Utilizando a Abordagem de Modelagem de Equações Estruturais de Mínimos Quadrados Parciais, o desenvolvimento de um modelo estrutural identificou os principais fatores impulsionadores relacionados à melhoria da Cadeia de Suprimentos. Nos resultados relatam os fatores mais importantes: 1) qualidade do fornecedor das mercadorias, 2) fatores internos, 3) serviço pós-venda, e 4) infraestrutura rodoviária e 5) ambiente comercial, para o setor de comércio varejista no México.
Referências
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Ali I, Fügenschuh A, Gupta S, Modibbo UM 2020. The LR-type fuzzy multi-objective vendor selection problem in supply chain management. Mathematics 8(9):1621.
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Atnafu D, Balda A 2018. The impact of inventory management practice on firms’ competitiveness and organizational performance: Empirical evidence from micro and small enterprises in Ethiopia, Cogent Business & Management, 5:1
Babu SC, Bangur P 2020. A study on the relationship between the various components of supportive logistics and primary logistics and its impact on customer service. Int J Manag 11(11): 1929-1944.
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Bugarčić FŽ, Skvarciany V, Stanišić N 2020. Logistics performance index in international trade: case of Central and Eastern European and Western Balkans countries. Bus Theory Pract 21(2):452-459.
Chatzikontidou A, Longinidis P, Tsiakis P, Georgiadis MC 2017. Flexible supply chain network design under uncertainty. Chem Eng Res Des128:290-305.
Cho DW, Lee YH, Ahn SH, Wang MK 2012. A framework for measuring the performance of service supply chain management. Comput Ind Eng 62(3):801-812.
Chowdhury MMH, Umme NJ. Nuruzzaman M 2018. Strategies for Mitigating Supply-Side Barriers in the Apparel Supply Chain: A Study on the Apparel Industry of Bangladesh. Glob J Flex Syst Manag 19:41–52.
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Distelhorst G, Hainmueller J, Locke RM 2017. Does lean improve labor standards? Management and social performance in the Nike supply chain. Manag Sci 63(3):707-728.
Dolgui A, Ivanov D, Sokolov B 2020. Reconfigurable supply chain: The X-network. Int J Prod Res 58(13):4138-4163.
Emamisaleh K, Rahmani K 2017. Sustainable supply chain in food industries: Drivers and strategic sustainability orientation. Cogent Bus Manag 4(1):1345296.
Fawcett SE, Gregory MM, McCarter MW 2008. A three-stage implementation model for supply chain collaboration. J Bus Logist 29(1):93-112.
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Eur J Oper Res 249(1):76-92.
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Perera HN, Hurley J, Fahimnia B, Reisi M 2019. The human factor in supply chain forecasting: A systematic review. Eur J Oper Res, 274(2):574-600.
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Shekarian M, Nooraie SVR, Parast MM 2020. An examination of the impact of flexibility and agility on mitigating supply chain disruptions. Int J Prod Econ 220:107438.
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Shukla AC, Deshmukh SG, Kanda A 2009. Environmentally responsive supply chains J Adv Manag Res 6(2):154-171.
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Singh RK. Kumar R 2020. Strategic issues in supply chain management of Indian SMEs due to globalization: an empirical study, Benchmarking: An International Journal 27(3):913-932.
Sohn SY, Lim M 2008. The effect of forecasting and information sharing in SCM for multi-generation products. Eur J Oper Res 186(1):276-287.
Soni G, Prakash S, Kumar H, Singh SP, Jain V. Dhami SS 2020, An interpretive structural modeling of drivers and barriers of sustainable supply chain management: A case of stone industry, Manag. Environ. Qual 31(5):1071-1090.
Srinivasan R, Swink M 2018. An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Prod Oper Manag 27(10):1849-1867.
Sunil L, Sachin KM, Ravi S, Chandra PG, Suresh J 2018. Modelling critical success factors for sustainability initiatives in supply chains in Indian context using Grey-DEMATEL, Prod Plan & Control 29(9):705-728.
Sureeyatanapas P, Sriwattananusart K, Niyamosoth T, Sessomboon W, Arunyanart S 2018. Supplier selection towards uncertain and unavailable information: An extension of TOPSIS method. Oper. Res. Perspect. 5:69-79.
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Tan KC 2001. A framework of supply chain management literature. J Purch Supply Manag 7(1):39-48.
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Aday S, Aday MS 2020. Impact of COVID-19 on the food supply chain. Food Qual. Saf 4(4):167-180.
Ali I, Fügenschuh A, Gupta S, Modibbo UM 2020. The LR-type fuzzy multi-objective vendor selection problem in supply chain management. Mathematics 8(9):1621.
Anitha P, Patil MM 2018. A review on data analytics for supply chain management: a case study. Int J Inf Eng Electron Bus 10(5):30.
Atnafu D, Balda A 2018. The impact of inventory management practice on firms’ competitiveness and organizational performance: Empirical evidence from micro and small enterprises in Ethiopia, Cogent Business & Management, 5:1
Babu SC, Bangur P 2020. A study on the relationship between the various components of supportive logistics and primary logistics and its impact on customer service. Int J Manag 11(11): 1929-1944.
Ballou Ronald H, (2004). Logística, Administración de la cadena de suministro. Pearson Prentice Hall, 5 edición, pp. 789.
Bugarčić FŽ, Skvarciany V, Stanišić N 2020. Logistics performance index in international trade: case of Central and Eastern European and Western Balkans countries. Bus Theory Pract 21(2):452-459.
Chatzikontidou A, Longinidis P, Tsiakis P, Georgiadis MC 2017. Flexible supply chain network design under uncertainty. Chem Eng Res Des128:290-305.
Cho DW, Lee YH, Ahn SH, Wang MK 2012. A framework for measuring the performance of service supply chain management. Comput Ind Eng 62(3):801-812.
Chowdhury MMH, Umme NJ. Nuruzzaman M 2018. Strategies for Mitigating Supply-Side Barriers in the Apparel Supply Chain: A Study on the Apparel Industry of Bangladesh. Glob J Flex Syst Manag 19:41–52.
Civelek ME, 2018. Essential of Structural Equation Modeling: Zea E-Books.64
http://digitalcommons.unl.edu/zeabook/64
Cousins PD, Lawson B, Petersen KJ, Fugate B 2019. Investigating green supply chain management practices and performance: The moderating roles of supply chain ecocentricity and traceability, Int J Oper Prod Manag 39(5): 767-786.
Distelhorst G, Hainmueller J, Locke RM 2017. Does lean improve labor standards? Management and social performance in the Nike supply chain. Manag Sci 63(3):707-728.
Dolgui A, Ivanov D, Sokolov B 2020. Reconfigurable supply chain: The X-network. Int J Prod Res 58(13):4138-4163.
Emamisaleh K, Rahmani K 2017. Sustainable supply chain in food industries: Drivers and strategic sustainability orientation. Cogent Bus Manag 4(1):1345296.
Fawcett SE, Gregory MM, McCarter MW 2008. A three-stage implementation model for supply chain collaboration. J Bus Logist 29(1):93-112.
Flynn BB, Huo B, Zhao X 2010. The impact of Supply Chain Integration on Performance: A contingency and Configuration Approach. J Oper Manag 28(1):58-71.
Gu M, Yang L, Huo B 2021. The impact of information technology usage on supply chain resilience and performance: An ambidexterous view. Int J Prod Econ 232:107956.
Giusti R, Manerba D, Bruno G, Tadei R 2019. Synchromodal logistics: An overview of critical success factors, enabling technologies, and open research issues. Transp Res E: Logist Transp Rev 129:92-110.
Hair JF, Black WC, Babin BJ, Anderson RE 2019. Multivariate Data Analysis (Eighth ed): Cengage Learning EMEA
Hair Jr JF, Hult GTM, Ringle C, Sarstedt M 2016. A primer on partial least squares structural equation modeling (PLS-SEM) (2nd ed.): Thousand Oaks, CA: Sage.
Hair Jr JF, Howard MC, Nitzl C 2020. Assessing measurement model quality in PLS-SEM using confirmatory composite analysis. J Bus Res 109:101–110.
Haleem A, Sushil Qadri MA, Kumar S, 2012. Analysis of critical success factors of world class manufacturing practices: an applicationof interpretive structural modelling and interpretive ranking process Prod Plan Control 23(10-11):722-734.
Hassan M., Jiang D., Ullah S., Alam N.E., (2020). Resilient Supplier Selection in Logistics 4.0 with Heterogeneous Information. Expert Systems with Applications, Volume 139, January, doi.org/10.1016/j.eswa.2019.07.016.
Helmold M, Terry B 2021. Operations and Supply Management 4.0: Industry Insights, Case Studies and Best Practices. Springer Nature.
Hudnurkar M, Jakhar S, Rathod U 2014. Factors affecting collaboration in supply chain: A literature Review. Procedia Soc Behav Sci 133:189–202
INEGI 2022. COMERCIO: INGRESOS, https://www.inegi.org.mx/temas/comercioemp/
Jayachitra R, Parthasarathy S 2020. A case study on productivity improvement in a display cases manufacturing industry. Int J Product Qual Manag 31(2):151-166.
Jian J, Guo Y, Jiang L, An Y, Su J 2019. A multi-objective optimization model for green supply chain considering environmental benefits. Sustainability 11(21):5911.
Jimenez-Jimenez D, Martínez-Costa M, Rodriguez CS 2018. The mediating role of supply chain collaboration on the relationship between information technology and innovation. J Knowl Manag 23(3):548-567.
Keya N, Anowar S, Eluru N 2019. Joint model of freight mode choice and shipment size: A copula-based random regret minimization framework. Transp Res E: Logist Transp Rev 125: 97-115.
Khan MT, Idrees MD, Rauf M, Sami A, Ansari A, Jamil A 2022. Green Supply Chain Management Practices’ Impact on Operational Performance with the Mediation of Technological Innovation. Sustainability 14(6):3362.
Keyvanshokooh E, Ryan SM, Kabir E 2016. Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition.
Eur J Oper Res 249(1):76-92.
Koolwijk JSJ, van Oel CJ, Wamelink JWF, Vrijhoef R 2018. Collaboration and integration in project-based supply chains in the construction industry. J MANAGE ENG 34(3), 04018001.
Kotula M, Ho W, Dey PK, Lee CKM 2015. Strategic sourcing supplier selection misalignment with critical success factors: Findings from multiple case studies in Germany and the United Kingdom. Int J Prod Econ 166:238–247.
Kouhizadeh M, Sarkis J 2018. Blockchain practices, potentials, and perspectives in greening supply chains. Sustainability 10(10):3652.
Kumar M, Garg D, Agarwal A 2019. Cause and effect analysis of inventory management in leagile supply chain. J. Manag. Inf. Decis. Sci 22(2):67-100.
Kumar R, Singh R, Shankar R 2015. Critical Success factors for implementation of supply chain management in Indian Small and Medium Enterprises SMEs and their impact on performance. IIMB Management Review 27(2):92-104.
Kumar V, Bak O, Guo R, Shaw SL, Colicchia C, Garza-Reyes JA, Kumari A 2018. An empirical analysis of supply and manufacturing risk and business performance: a Chinese manufacturing supply chain perspective. Supply Chain Manage. 23(6):461-479
Landeros Hernández R, González Ramírez MT 2006. Estadística con SPSS y metodología de la Investigación, Ed. Trillas, 1ª Edición, México, D.F.
Langenwalter GA 2020. Enterprise resources planning and beyond: integrating your entire organization. CRC Press.
Liu S, Eweje G, He Q, Lin Z 2020. Turning motivation into action: A strategic orientation model for green supply chain management. Bus Strategy Environ 29(7):2908-2918.
Luthra S, Garg D, Haleem A 2015. An analysis of interactions among critical success factors to implement green supply chain management towards sustainability: An Indian perspective. Resour Policy 46(1):37-50.
Mangla S, Mandaan J, Sarma PRS, Gupta MP 2014. Multiobjective decisión modelling using interpretive structural modeling for green supply chains. Int J Logist Syst Manag 17(2):125-142.
Manley SC, Hair JF, Williams RI, McDowell WC 2021. Essential new PLS-SEM analysis methods for your entrepreneurship analytical toolbox. Int Entrep Manag J 17:1805–1825.
Marak, Z. R., & Pillai, D. (2018). Factors, outcome, and the solutions of supply chain finance: review and the future directions. J Risk Financial Manag 12(1), 3.
Mavi RK, Goh M, Mavi NK 2016. Supplier selection with Shannon entropy and fuzzy TOPSIS in the context of supply chain risk management. Procedia Soc Behav Sci 235:216-225.
Min S, Zacharia ZG, Smith C 2019. Defining supply chain management: in the past, present, and future. J. Bus. Logist. 40(1):44-55.
Mönch L, Uzsoy R, Fowler JW 2018. A survey of semiconductor supply chain models part III: master planning, production planning, and demand fulfilment. Int J Prod Res 56(13):4565-4584.
Murali S, Pugazhendhi S, Muralidharan C 2016. Modelling and investigating the relationship of after sales service quality with customer satisfaction, retention and loyalty–a case study of home appliances business. J Retail Consum Serv 30:67-83.
Muralidharan C, Anantharaman N, Deshmukh SG 2006. A multi-criteria group decisionmaking model for supplier rating. J Supply Chain Manag 38(3):22-33.
Naim MM, Potter AT, Mason RJ, Bateman N 2006. The role of transport flexibility in logistics provision. Int J Logist Manag 17(3):297-311.
Nimeh HA, Abdallah AB, Sweis R 2018. Lean supply chain management practices and performance: empirical evidence from manufacturing companies. Int. J. Supply Chain Manag. 7(1):1-15.
Öberg C., & Graham G., (2016). How smart cities will change supply chain management: a technical viewpoint. Production Planning & Control, 27:6, 529-538.
Peng DX, Lu G 2017. Exploring the impact of delivery performance on customer transaction volume and unit price: evidence from an assembly manufacturing supply chain. Prod Oper Manag 26(5):880-902.
Perera HN, Hurley J, Fahimnia B, Reisi M 2019. The human factor in supply chain forecasting: A systematic review. Eur J Oper Res, 274(2):574-600.
Prajogo D, Olhager J 2012. Supply chain integration and performance: The effects of long-term relationships information technology and sharing and logistics integration. Int J Prod Econ 135(1):514–522.
Rejeb A, Keogh JG, Treiblmaier H 2019. Leveraging the internet of things and blockchain technology in supply chain management. Future Internet 11(7):161.
Remko VH. 2020. Research opportunities for a more resilient post-COVID-19 supply chain – closing the gap between research findings and industry practice, Int J Oper Prod Manag 40(4):341-355.
Ringle CM, Wende S, Becker JM 2015. SmartPLS 3. SmartPLS GmbH, Boenningstedt. J Serv Sci Manag 10(3), 32-49.
Rojas S R 2013. Guía para realizar investigaciones sociales (9va edición): Plaza y Valdez.
Schönsleben P 2018. Integral logistics management: operations and supply chain management within and across companies. CRC Press.
Shekarian M, Nooraie SVR, Parast MM 2020. An examination of the impact of flexibility and agility on mitigating supply chain disruptions. Int J Prod Econ 220:107438.
Sholeh MN, Nurdiana A, Dharmo B 2021. Implementation of construction supply chain flow based on SCOR 12.0 performance standards. J. Phys.: Conf. Ser. 1833 012012.
Shukla AC, Deshmukh SG, Kanda A 2009. Environmentally responsive supply chains J Adv Manag Res 6(2):154-171.
Singh J, Singh H, Kumar A 2020. Impact of lean practices on organizational sustainability through green supply chain management – an empirical investigation, Int. J. Lean Six Sigma, 11 (6):1035-1068.
Singh RK. Kumar R 2020. Strategic issues in supply chain management of Indian SMEs due to globalization: an empirical study, Benchmarking: An International Journal 27(3):913-932.
Sohn SY, Lim M 2008. The effect of forecasting and information sharing in SCM for multi-generation products. Eur J Oper Res 186(1):276-287.
Soni G, Prakash S, Kumar H, Singh SP, Jain V. Dhami SS 2020, An interpretive structural modeling of drivers and barriers of sustainable supply chain management: A case of stone industry, Manag. Environ. Qual 31(5):1071-1090.
Srinivasan R, Swink M 2018. An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Prod Oper Manag 27(10):1849-1867.
Sunil L, Sachin KM, Ravi S, Chandra PG, Suresh J 2018. Modelling critical success factors for sustainability initiatives in supply chains in Indian context using Grey-DEMATEL, Prod Plan & Control 29(9):705-728.
Sureeyatanapas P, Sriwattananusart K, Niyamosoth T, Sessomboon W, Arunyanart S 2018. Supplier selection towards uncertain and unavailable information: An extension of TOPSIS method. Oper. Res. Perspect. 5:69-79.
Taghipour A, Hoang P, Cao X 2020. Just in time/lean purchasing approach: an investigation for research and applications. J. Adv. Manag. Sci. 8(2):43-48.
Tavana M, Shabani A, Singh R 2019. The impact of interwoven integration practices on supply chain value addition and firm performance. J Ind Eng Int, 15(1), 39-5.
Tan KC 2001. A framework of supply chain management literature. J Purch Supply Manag 7(1):39-48.
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2022-08-02
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DA GAMA, Scott; HERNÁNDEZ-GÓMEZ, Jesús Andrés; ESCOBETO-PORTILLO, María Teresa; NORIEGA, Salvador. Predictor Model of the Supply Chain Effectiveness based on Critical Success Factors in a Commerce Retail Industry. Fronteira: Journal of Social, Technological and Environmental Science, [S. l.], v. 11, n. 2, p. 265–278, 2022. DOI: 10.21664/2238-8869.2022v11i2.p265-278. Disponível em: https://revistas2.unievangelica.edu.br/index.php/fronteiras/article/view/6301. Acesso em: 22 dez. 2024.
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