Is your supply chain ready for the next disruption? Building resilient chains
Article Sidebar
Main Article Content
Abstract
The ability to recover from disruptions is important for organizations and supply chains. Empirical data were used to investigate factors that affect supply chain recovery from disruptions, including collaboration, visibility, flexibility, analytical orientation, and supply chain risk management. A literature review was conducted to build an online questionnaire that was applied to manufacturing firms in Brazil. This work’s statistical method includes confirmatory factor analysis and structural equation modeling. Our results indicate that a
package of resilience capabilities - collaboration, flexibility, visibility, and analytical orientation - positively affect supply chain resilience. Improving such capabilities, therefore, will allow supply chains to recover better from disruptions. It was also discovered, however, that
supply chains do not recover from disruptions by way of supply chain risk management alone. Mutual impacts also exist between the group of resilience capabilities and supply chain risk management.
Downloads
Metrics
Article Details
A RAE compromete-se a contribuir com a proteção dos direitos intelectuais do autor. Nesse sentido:
- adota a licença Creative Commoms BY (CC-BY) em todos os textos que publica, exceto quando houver indicação de específicos detentores dos direitos autorais e patrimoniais;
- adota software de detecção de similaridades;
- adota ações de combate ao plagio e má conduta ética, alinhada às diretrizes do Committee on Publication Ethics (COPE)
References
Ali, A., Mahfouz, A., & Arisha, A. (2017). Analysing supply chain resilience: Integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Management: An International Journal, 22(1), 16-39. doi: 10.1108/SCM-06-2016-0197
Alvarenga, M. Z., Oliveira, M. P. V. de, Zanquetto-Filho, H., & Santos, W. R. dos. (2018a, December). Analytical supply chains: Are They more resilient ? A model’ s proposition. Journal of Operations and Supply Chain Management, 11(2), 46-58. doi: 10.12660/joscmv11n2p46-58
Alvarenga, M. Z., Oliveira, M. P. V. de, Zanquetto-Filho, H., & Santos, W. R. dos. (2018b, December). Do analytically-oriented supply chains better manage risks? Journal of Operations and Supply Chain Management, 11(2), 32-45. doi: 10.12660/joscmv11n2p32-45
Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm’s resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33-34, 111-122. doi: 10.1016/j.jom.2014.11.002
Aqlan, F., & Lam, S. S. (2015). A fuzzy-based integrated framework for supply chain risk assessment. International Journal of Production Economics, 161, 54–63. doi: 10.1016/j.ijpe.2014.11.013
Barbosa, M. W., & Vicente, A. de la C. (2018). Managing supply chain resources with Big Data Analytics: A systematic review. International Journal of Logistics Research and Applications, 21(3), 177-200. doi: 10.1080/13675567.2017.1369501
Barratt, M. (2004). Understanding the meaning of collaboration in the supply chain. Supply Chain Management: An International Journal, 9(1), 30-42. doi: 10.1108/13598540410517566
Barratt, M., & Oke, A. (2007). Antecedents of supply chain visibility in retail supply chains: A resource-based theory perspective. Journal of Operations Management, 25(6), 1217-1233. doi: 10.1016/j.jom.2007.01.003
Brandon-Jones, E., Squire, B., Autry, C. W., & Petersen, K. J. (2014). A contingent resource-based perspective of supply chain resilience and robustness. Journal of Supply Chain Management, 50(3), 55-73. doi: 10.1111/jscm.12050
Bronzo, M., Resende, P. T. V. de, Oliveira, M. P. V. de, McCormack, K. P., Sousa, P. R. de, & Ferreira, R. L. (2013). Improving performance aligning business analytics with process orientation. International Journal of Information Management, 33(2), 300-307. doi: 10.1016/j.ijinfomgt.2012.11.011
Brusset, X., & Teller, C. (2017). Supply chain capabilities, risks, and resilience. International Journal of Production Economics, 184, 59-68. doi: 10.1016/j.ijpe.2016.09.008
Cao, G., Duan, Y., & Li, G. (2015). Linking business analytics to decision making effectiveness: A path model analysis. IEEE Transactions on Engineering Management, 62(3), 384-395. doi: 10.1109/TEM.2015.2441875
Cao, M., & Zhang, Q. (2011). Supply chain collaboration: Impact on collaborative advantage and firm performance. Journal of Operations Management, 29(3), 163-180. doi: 10.1016/j.jom.2010.12.008
Caridi, M., Crippa, L., Perego, A., Sianesi, A., & Tumino, A. (2010). Measuring visibility to improve supply chain performance: A quantitative approach. Benchmarking: An International Journal, 17(4), 593-615. doi: 10.1108/14635771011060602
Caridi, M., Moretto, A., Perego, A., & Tumino, A. (2014). The benefits of supply chain visibility: A value assessment model. International Journal of Production Economics, 151, 1-19. doi: 10.1016/j.ijpe.2013.12.025
Caridi, M., Perego, A., & Tumino, A. (2013). Measuring supply chain visibility in the apparel industry. Benchmarking: An International Journal, 20(1), 25-44. doi: 10.1108/14635771311299470
Ceryno, P. S., Scavarda, L. F., Klingebiel, K., & Yüzgülec, G. (2013). Supply chain risk management: A content analysis approach. International Journal of Industrial Engineering and Management, 4(3), 141-150. Retrieved from http://www.iim.ftn.uns.ac.rs/images/journal/volume4/ijiem_vol4_no3_6.pdf
Chae, K., Olson, D., & Sheu, C. (2014). The impact of supply chain analytics on operational performance: A resource-based view. International Journal of Production Research, 52(16), 4695-4710. doi: 10.1080/00207543.2013.861616
Christopher, M., & Peck, H. (2004). Building the resilient supply chain. International Journal of Logistics Management, 15(2), 1-13. doi: 10.1108/09574090410700275
CNN (2019). Domino’s stockpiling pizza ingredients ahead of “disorderly” Brexit. Retrieved from https://www.9news.com.au/world/dominos-pizza-chains-stockpiling-ingredients-ahead-brexit-crash-uk-news/48061c6b-0bdc-4d58-83db-50060923dad3
Colicchia, C., Dallari, F., & Melacini, M. (2010). Increasing supply chain resilience in a global sourcing context. Production Planning & Control, 21(7), 680-694. doi: 10.1080/09537280903551969
Colquitt, J. A., & Zapata-Phelan, C. P. (2007). Trends in theory building and theory testing: A five-decade study of the Academy of Management Journal. Academy of Management Journal, 50(6), 1281-1303. doi: 10.5465/amj.2007.28165855
Continuity Central.com, (2018). Gartner highlights ‘digital twins’ as an emerging organizational resilience tool. . Retrieved from https://www.continuitycentral.com/index.php/news/resilience-news/3560-gartner-highlights-digital-twins-as-an-emerging-organizational-resilience-tool
Cosgrove, E. (2020). Smithfield closes more plants as coronavirus cases grow among workers. Retrieved from https://www.supplychaindive.com/news/coronavirus-smithfield-plant-close/575903/
Daugherty, P. J., Richey, R. G., Roath, A. S., Min, S., Chen, H., Arndt, A. D., & Genchev, S. E. (2006). Is collaboration paying off for firms? Business Horizons, 49(1), 61-70. doi: 10.1016/j.bushor.2005.06.002
Davenport, T. H., Harris, J. G., Long, D. W. De, & Jacobson, A. L. (2001). Data to knowledge to results: Building an analytics capability. California Management Review, 43(2), 117–138. doi: 10.2307/41166078
Dubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2019). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1), 1-19. doi: 10.1080/00207543.2019.1582820
Durach, C. F., & Machuca, J. A. D. (2018). A matter of perspective: The role of interpersonal relationships in supply chain risk management. International Journal of Operations & Production Management, 38(10), 1866-1887. doi: 10.1108/IJOPM-03-2017-0157
Graeml, A. R., Peinado, J. (2014). O efeito das capacidades logísticas na construção de resiliência da cadeia de suprimentos. Revista de Administração, 49(4), 642-655. doi: 10.5700/rausp1174
Hair, J. F., Anderson, R. E., Tatham, R. L., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data analysis: Pearson Education Ltd. (7th ed.). Upper Saddle River, NJ: Prentice Hall. doi: 10.1016/j.ijpharm.2011.02.019
Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2017). A primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). In T. Oaks (Ed.), Handbook of market research (2nd ed., Vol. 26 1-374). Thousand Oaks, Los Angeles: Sage. doi: 10.1007/978-3-319-05542-8_15-1
Hallikas, J., Karvonen, I., Pulkkinen, U., Virolainen, V. M., & Tuominen, M. (2004). Risk management processes in supplier networks. International Journal of Production Economics, 90(1), 47-58. doi: 10.1016/j.ijpe.2004.02.007
Hernandez, D. F., & Haddud, A. (2018). Value creation via supply chain risk management in global fashion organizations outsourcing production to China. Journal of Global Operations and Strategic Sourcing, 11(2), 250-272. doi: 10.1108/JGOSS-09-2017-0037
Holcomb, M. C., Ponomarov, S. Y., & Manrodt, K. B. (2011). The relationship of supply chain visibility to firm performance. Supply Chain Forum: An International Journal, 12(2), 32-45. doi: 10.1080/16258312.2011.11517258
Ittmann, H. W. (2015). The impact of big data and business analytics on supply chain management. Journal of Transport and Supply Chain Management, 9(1), 1-9. doi: 10.4102/jtscm.v9i1.165
Ivanov, D., Dolgui, A., Das, A., & Sokolov, B. (2019). Digital supply chain twins: Managing the ripple effect, resilience, and disruption risks by data-driven optimization, simulation, and visibility. In 1 ed. Handbook of ripple effects in the supply chain (pp. 309-332). Gewerbestrasse, Springer. https://doi.org/10.1007/978-3-030-14302-2_15
Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: An empirical study. Supply Chain Management: An International Journal, 16(4), 246-259. doi: 10.1108/13598541111139062
Jüttner, U., Peck, H., & Christopher, M. (2003). Supply chain risk management: Outlining an agenda for future research. International Journal of Logistics: Research and Applications, 6(4), 197-210. doi: 10.1080/13675560310001627016
Kirchoff, J.. (2019). How to assess risks in a globalized supply chain. Retrieved from https://www.supplychaindive.com/news/assess-risks-globalized-supply-chain/568971/
Kohli, A. S., & Jensen, J. B. (2010). Assessing effectiveness of supply chain collaboration: An empirical study. Supply Chain Forum: An International Journal, 11(2), 2-16. doi: 10.1080/16258312.2010.11517228
Kumar, S., & Anbanandam, R. (2019). Impact of risk management culture on supply chain resilience: An empirical study from Indian manufacturing industry. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 234(2), 246–259. doi: 10.1177/1748006X19886718
Kwak, D.-W., Seo, Y.-J., & Mason, R. (2018). Investigating the relationship between supply chain innovation, risk management capabilities and competitive advantage in global supply chains. International Journal of Operations & Production Management, 38(1), 2-21. doi: 10.1108/IJOPM-06-2015-0390
Lacerda, R. T. de O., Ensslin, L., & Ensslin, S. R. (2012). Uma análise bibliométrica da literatura sobre estratégia e avaliação de desempenho. Gestão & Produção, 19(1), 59-78. doi: 10.1590/s0104-530x2012000100005
Ladeira, M. B., Resende, P. T. V. de, Oliveira, M. P. V. de, McCormack, K., Sousa, P. R. de, & Ferreira, R. L. (2016). Os efeitos da abordagem analítica e da gestão orientada para processos sobre o desempenho organizacional de micro e pequenas empresas brasileiras dos setores da indústria e de serviços. Gestão & Produção, 23(32), 486-502. doi: 10.1590/S0104-530X2012000200012
Laursen, G. H. N., & Thorlund, J. (2010). Business analytics for managers. Hoboken, NJ: John Wiley & Sons, Inc. https://doi.org/10.1002/9781118983812
Li, G., Fan, H., Lee, P. K. C., & Cheng, T. C. E. (2015). Joint supply chain risk management: An agency and collaboration perspective. International Journal of Production Economics, 164, 83-94. doi: 10.1016/j.ijpe.2015.02.021
Lopez, E. (2018). H&M’s turnaround runs through its supply chain. Retrieved from https://www.supplychaindive.com/news/HM-turnaround-runs-through-supply-chain/520495/
Mandal, S., Sarathy, R., Korasiga, V. R., Bhattacharya, S., & Dastidar, S. G. (2016). Achieving supply chain resilience: The contribution of logistics and supply chain capabilities. International Journal of Disaster Resilience in the Built Environment, 7(5), 544-562. doi: 10.1108/IJDRBE-04-2016-0010
Marafon, A. D., Ensslin, L., Lacerda, R. T. de O., & Ensslin, S. R. (2015). The effectiveness of multi-criteria decision aid methodology: A case study of R&D management. European Journal of Innovation Management, 18(1), 89-109. doi: 10.1108/EJIM-10-2013-0106
Merschmann, U., & Thonemann, U. W. (2011). Supply chain flexibility, uncertainty and firm performance: An empirical analysis of German manufacturing firms. International Journal of Production Economics, 130(1), 43-53. doi: 10.1016/j.ijpe.2010.10.013
Namdar, J., Li, X., Sawhney, R., & Pradhan, N. (2018). Supply chain resilience for single and multiple sourcing in the presence of disruption risks. International Journal of Production Research, 56(6), 2339-2360. doi: 10.1080/00207543.2017.1370149
Nooraie, S. V., & Parast, M. M. (2015). A multi-objective approach to supply chain risk management: Integrating visibility with supply and demand risk. International Journal of Production Economics, 161, 192-200. doi: 10.1016/j.ijpe.2014.12.024
Norrman, A., & Jansson, U. (2004). Ericsson’s proactive supply chain risk management approach after a serious sub-supplier accident. International Journal of Physical Distribution & Logistics Management, 34, 434-456. doi: 10.1108/09600030410545463
Ojha, R., Ghadge, A., Tiwari, M. K., & Bititci, U. S. (2018). Bayesian network modelling for supply chain risk propagation. International Journal of Production Research, 56(17), 5795-5819. doi: 10.1080/00207543.2018.1467059
Oliveira, M. P. V. de, & Handfield, R. (2019). Analytical foundations for development of real-time supply chain capabilities. International Journal of Production Research, 57(5), 1571-1589. doi: 10.1080/00207543.2018.1493240
Papadopoulos, T., Gunasekaran, A., Dubey, R., Altay, N., Childe, S. J., & Fosso-Wamba, S. (2017). The role of Big Data in explaining disaster resilience in supply chains for sustainability. Journal of Cleaner Production, 142, 1108-1118. doi: 10.1016/j.jclepro.2016.03.059
Pavlov, A., Ivanov, D., Dolgui, A., & Sokolov, B. (2018). Hybrid fuzzy-probabilistic approach to supply chain resilience assessment. IEEE Transactions on Engineering Management, 65(2), 303-315. doi: 10.1109/TEM.2017.2773574
Pettit, T. J., Croxton, K. L., & Fiksel, J. (2019). The evolution of resilience in supply chain management: A retrospective on ensuring supply chain resilience. Journal of Business Logistics, 40(1), 56-65. doi: 10.1111/jbl.12202
Pettit, T. J., Fiksel, J., & Croxton, K. L. (2010). Ensuring supply chain resilience: Development of a conceptual framework. Journal of Business Logistics, 31(1), 1-21. doi: 10.1002/j.2158-1592.2010.tb00125.x
Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124-143. doi: 10.1108/09574090910954873
Prakash, S., Gautam, A., & Soni, U. (2018). Supply chain risk management and quality: A case study and analysis of Indian automotive industry. International Journal of Intelligent Enterprise, 5(1/2), 194. doi: 10.1504/IJIE.2018.10012158
Rajesh, R. (2017). Technological capabilities and supply chain resilience of firms: A relational analysis using Total Interpretive Structural Modeling (TISM). Technological Forecasting and Social Change, 118, 161-169. doi: 10.1016/j.techfore.2017.02.017
Ribeiro, J. P., & Barbosa-Povoa, A. (2018). Supply chain resilience: Definitions and quantitative modelling approaches – A literature review. Computers and Industrial Engineering, 115, 109-122. doi: 10.1016/j.cie.2017.11.006
Ringle, C. M., Wende, S., & Becker, J.-M. (2014). SmartPLS 3.0. Hamburg, Germany: SmartPLS.
Roberson, C. M. (2019). Preparing for the unknown in your supply chain. Retrieved from https://www.forbes.com/sites/cathymorrowroberson/2019/10/07/preparing-for-the-unknown-in-your-supply-chain/#385e0d6339ff
Sáenz, M. J., Revilla, E., & Acero, B. (2018). Aligning supply chain design for boosting resilience. Business Horizons, 61(3), 443-452 doi: 10.1016/j.bushor.2018.01.009
Sánchez, A., M. & Pérez, M. P. (2005). Supply chain flexibility and firm performance. International Journal of Operations & Production Management, 25(7), 681-700. doi: 10.1108/01443570510605090
Scavarda, L. F., Ceryno, P. S., Pires, S., & Klingebiel, K. (2015). Supply chain resilience analysis: A Brazilian automotive case. RAE-Revista de Administração de Empresas, 55(3), 304-313. doi: 10.1590/S0034-759020150306
Scholten, K., Schilder, S.. (2015). The role of collaboration in supply chain resilience. Supply Chain Management: An International Journal, 20(4), 471-484. doi: 10.1108/SCM-11-2014-0386
Scholten, K., Scott, P. S., & Fynes, B. (2014). Mitigation processes: Antecedents for building supply chain resilience. Supply Chain Management: An International Journal, 19(2), 211-228. doi: 10.1108/SCM-06-2013-0191
SEBRAE (2016). Anuário do trabalho nos pequenos negócios. Retrieved from https://m.sebrae.com.br/Sebrae/Portal Sebrae/Anexos/Anuario do Trabalho nos Pequenos Negócios 2016_.pdf
Sheffi, Y., & Rice, J. B., Jr. (2005). A supply chain view of the resilient enterprise. MIT Sloan Management Review, 47(1), 41-48. Retrieved from https://sloanreview.mit.edu/article/a-supply-chain-view-of-the-resilient-enterprise
Singh, N. P., & Singh, S. (2019). Building supply chain risk resilience: Role of big data analytics in supply chain disruption mitigation. Benchmarking, 26(7), 2318-2342. doi: 10.1108/BIJ-10-2018-0346
Sodhi, M. S., Son, B.-G., & Tang, C. S. (2012). Researchers’ perspectives on supply chain risk management. Production and Operations Management, 21(1), 1-13. doi:10.1111/j.1937-5956.2011.01251.x
Souza, G. C. (2014). Supply chain analytics. Business Horizons, 57(5), 595-605. doi: 10.1016/j.bushor.2014.06.004
Srinivasan, R., & Swink, M. (2018). An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Production and Operations Management, 27(10), 1849-1867. doi: 10.1111/poms.12746
Swafford, P. M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: Scale development and model testing. Journal of Operations Management, 24(2), 170-188. doi: 10.1016/j.jom.2005.05.002
Swafford, P. M., Ghosh, S., & Murthy, N. (2008). Achieving supply chain agility through IT integration and flexibility. International Journal of Production Economics, 116(2), 288-297. doi: 10.1016/j.ijpe.2008.09.002
Tang, O., & Musa, S. N. (2011). Identifying risk issues and research advancements in supply chain risk management. International Journal of Production Economics, 133(1), 25-34. doi: 10.1016/j.ijpe.2010.06.013
Teo, T. S. H., Nishant, R., & Koh, P. B. L. (2016). Do shareholders favor business analytics announcements? Journal of Strategic Information Systems, 25(4), 259-276. doi: 10.1016/j.jsis.2016.05.001
Thomé, A. M. T., Scavarda, L. F., Pires, S. R. I., Ceryno, P., & Klingebiel, K. (2014). A multi-tier study on supply chain flexibility in the automotive industry. International Journal of Production Economics, 158, 91-105. doi: 10.1016/j.ijpe.2014.07.024
Trkman, P., Mccormack, K., Oliveira, M. P. V. de, & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318-327. doi: 10.1016/j.dss.2010.03.007
Tummala, R., & Schoenherr, T. (2011). Assessing and managing risks using the Supply Chain Risk Management Process (SCRMP). Supply Chain Management: An International Journal, 16(6), 474-483. doi: 10.1108/13598541111171165
Urciuoli, L., & Hintsa, J. (2018). Improving supply chain risk management: Can additional data help? International Journal of Logistics Systems and Management, 30(2), 195. doi: 10.1504/IJLSM.2018.091962
Vanpoucke, E., Vereecke, A., & Wetzels, M. (2014). Developing supplier integration capabilities for sustainable competitive advantage: A dynamic capabilities approach. Journal of Operations Management, 32(7-8), 446-461. doi:10.1016/j.jom.2014.09.004
Wieland, A., & Wallenburg, C. M. (2013). The influence of relational competencies on supply chain resilience: a relational view. International Journal of Physical Distribution & Logistics Management, 43(4), 300-320. doi: 10.1108/ijpdlm-08-2012-0243
Wollenhaupt, G. (2019). In disaster response, health supply chain egos melt away. Retrieved from https://www.supplychaindive.com/news/pharma-healthcare-disaster-response-hurricane/555942/
Wong, C. W. Y., Lirn, T. C., Yang, C. C., & Shang, K. C. (2019). Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization. International Journal of Production Economics, 226, 107610 doi: 10.1016/j.ijpe.2019.107610
Xu, S., Zhang, X., Feng, L., & Yang, W. (2020). Disruption risks in supply chain management: A literature review based on bibliometric analysis. International Journal of Production Research, 59(11), 1-19. doi: 10.1080/00207543.2020.1717011
Zhu, S., Song, J., Hazen, B. T., Lee, K., & Cegielski, C. (2016). How supply chain analytics enables operational supply chain transparency. International Journal of Physical Distribution & Logistics Management, 48(1), 47-68. doi: 10.1108/IJPDLM-11-2017-0341
Zineb, E., Brahim, B., & Houdaifa, A. (2017). The impact of SCRM strategies on supply chain resilience: A quantitative study in the Moroccan manufacturing industry. International Journal of Supply Chain Management, 6(4), 70-75. Retrieved from http://ijis-scm.bsne.ch/ojs.excelingtech.co.uk/index.php/IJSCM/article/download/1665/1665-6369-1-PB.pdf
