Integrating Industry 4.0 Technologies for Lean an Agile Supply Chain Performance
DOI: https://doi.org/10.65967/cpbo.v2i1.53
lean supply chain, agile supply chain, industry 4.0 technologies, ;dynamic capabilities
Abstract
Industry 4.0 (I4.0) technologies have opened new possibilities for improving supply chain management, but the way these tools are integrated into existing models to strengthen performance is still being explored. This study focuses on understanding how I4.0 base technologies cloud computing, the Internet of Things, and big data analytics relate to lean and agile supply chain strategies, and how they affect the operational performance of firms. These technologies are particularly important because of their ability to enhance data collection, storage, sharing, and analysis, which are key elements in modern supply chain processes. Using the Dynamic Capabilities Theory as a framework, the study applied structural equation modeling (SEM) to data collected from 256 Spanish manufacturing companies. The results show that I4.0 base technologies do not influence lean and agile supply chains in the same way. They significantly contribute to making supply chains leaner, but do not have a direct effect on agile implementation. In addition, findings highlight a connection between lean and agile strategies, where agile practices mediate the link between lean approaches and firm performance. These insights provide practical guidance for firms aiming to use I4.0 technologies to strengthen competitiveness
References
Abdelilah, B., El Korchi, A., Amine Balambo, M., 2021. Agility as a combination of lean and supply chain integration: how to achieve a better performance. Int. J. Logist. Res. Appl. 0, 1–29.
Alberti-Alhtaybat, L.V., Al-Htaybat, K., Hutaibat, K., 2019. A knowledge management and sharing business model for dealing with disruption: the case of Aramex. J. Bus. Res. 94, 400–407.
Anand, G., Ward, P.T., 2004. Fit, flexibility and performance in manufacturing: coping with dynamic environments. Prod. Oper. Manag. 13 (4), 369–385.
Anosike, A., Alafropatis, K., Garza-Reyes, J.A., Kumar, A., Luthra, S., Rocha-Lona, L., 2021. Lean manufacturing and internet of things – a synergetic or antagonist relationship? Comput. Ind. 129, 103464. Attaran, M., 2020. Digital technology enablers and their implications for supply chain management. Supply Chain Forum 21, 158–172.
Bag, S., Dhamija, P., Gupta, S., Sivarajah, U., 2021. Examining the role of procurement 4.0 towards remanufacturing operations and circular economy. Prod. Plann. Control 32 (16), 1368–1383.
Bag, S., Rahman, M.S., Srivastava, G., Chan, H.L., Bryde, D.J., 2022. The role of big data and predictive analytics in developing a resilient supply chain network in the South African mining industry against extreme weather events. Int. J. Prod. Econ. 251, 108541.
Ben-daya, M., Hassini, E., Bahroun, Z., 2017. Internet of things and supply chain management : a literature review. Int. J. Prod. Res. 7543, 1–23.
Bhatia, A.S., Kotorov, R., Chi, L., 2022. Casting plate defect detection using motif discovery with minimal model training and small data sets. J. Intell. Manuf. 0, 1–12.
Bi, R., Davison, R.M., Kam, B., Smyrnios, K.X., Davidson, R., Kam, B., Smyrnios, K.X., 2013. Developing organizational agility through IT and supply chain capability. J. Global Inf. Manag. 21 (4), 38–55.
Blome, D., Schoenherr, T., Rexhausen, C., 2013. Antecedents and enablers of supply chain agility and its effect on performance: a dynamic capabilities perspective. Int. J. Prod. Res. 51 (4), 1295–1318.
Bollen, K.A., Long, J.S., 1992. Tests for structural equation models. Socio. Methods Res. 21 (2), 123–131.
Bruque-camara, ´ S., Moyano-fuentes, J., Maqueira-Marín, J.M., 2016. Supply chain integration through community cloud : effects on operational performance. J. Purch. Supply Manag. 22 (2), 141–153.
Carvalho, H., Duarte, S., Machado, V.C., 2011. Lean, agile, resilient and green: divergencies and synergies. International Journal of Lean Six Sigma 2 (2), 151–179.
Choi, T.-M., Wallace, S.W., Wang, Y., 2018. Big data analytics in operations management. Prod. Oper. Manag. 27 (10), 1868–1883.
Ciano, M.P., Dallasega, P., Orzes, G., Rossi, T., 2021. One-to-one relationships between Industry 4.0 technologies and Lean Pro-duction techniques: a multiple case study. Int. J. Prod. Res. 59 (5), 1386–1410.
Culot, G., Nassimbeni, G., Orzes, G., Sartor, M., 2020. Behind the definition of Industry 4.0: analysis and open questions. Int. J. Prod. Econ. 226, 107617.
Dalenogare, L.S., Benitez, G.B., Ayala, N.F., Frank, A.G., 2018. The expected contribution of Industry 4.0 technologies for industrial performance. Int. J. Prod. Econ. 204, 383–394.
Danese, P., Romano, P., Bortolotti, T., 2012. JIT production, JIT supply and performance: investigating the moderating effects. Ind. Manag. Data Syst. 112 (3), 441–465. DeGroote, S.E., Marx, T.G., 2013. The impact of IT on supply chain agility and firm performance: an empirical investigation. Int. J. Inf. Manag. 33 (6), 909–916.
Di Maria, E., De Marchi, V., Galeazzo, A., 2022. Industry 4.0 technologies and circular economy: the mediating role of supply chain integration. Bus. Strat. Environ. 31, 619–632.
Dubey, R., Gunasekaran, A., Childe, S.J., 2019. Big data analytics capability in supply chain agility: the moderating effect of or-ganizational flexibility. Manag. Decis. 57 (8), 2092–2112.
Eckstein, D., Goellner, M., Blome, C., Henke, M., 2015. The performance impact of supply chain agility and supply chain adapta-bility: the moderating effect of product complexity. Int. J. Prod. Res. 53, 3028–3046.
Enrique, D.V., Lerman, L.V., Sousa, P. R. de, Benitez, G.B., Bigares Charrua Santos, F.M., Frank, A.G., 2022. Being digital and flexible to navigate the storm: how digital transformation enhances supply chain flexibility in turbulent environments. Int. J. Prod. Econ. 250, 108668.
Eslami, M.H., Jafari, H., Achtenhagen, L., Carlb¨ ack, J., Wong, A., 2021. Financial performance and supply chain dynamic capa-bilities: the Moderating Role of Industry 4.0 technologies. Int. J. Prod. Res. Fadaki, M., Rahman, S., Chan, C., 2020. Leagile supply chain: design drivers and business performance implications. Int. J. Prod. Res. 58 (18), 5601–5623.
Fay, M., Kazantsev, N., 2018. When smart gets smarter: how big data analytics creates business value in smart manufacturing. In: International Conference on Information Systems 2018, ICIS 2018.
Frank, A.G., Dalenogare, L.S., Ayala, N.F., 2019. Industry 4.0 technologies: implementation patterns in manufacturing companies. Int. J. Prod. Econ. 210, 15–26. Frederico, G.F., Garza-Reyes, J.A., Anosike, A., Kumar, V., 2020. Supply Chain 4.0: concepts, maturity and research agenda. Supply Chain Manag. 25 (2), 262–282.
Garcia-Buendia, N., Moyano-Fuentes, J., Maqueira-Marín, J.M., 2021. Lean supply chain management and performance relation-ships: what has been done and what is left to do. CIRP J. Manufactur. Sci. Technol. 32, 405–423.
Ghobakhloo, M., 2020. Determinants of information and digital technology implementation for smart manufacturing. Int. J. Prod. Res. 58 (8), 2384–2405.
Ghobakhloo, M., Azar, A., 2018. Business excellence via advanced manufacturing technology and lean-agile manufacturing. J. Manuf. Technol. Manag. 29 (1), 2–24.
Ghobakhloo, M., Fathi, M., 2020. Corporate survival in Industry 4.0 era: the enabling role of lean-digitized manufacturing. J. Manuf. Technol. Manag. 31, 1–30.
Gillani, F., Chatha, K.A., Sadiq Jajja, M.S., Farooq, S., 2020. Implementation of digital manufacturing technologies: antecedents and consequences. Int. J. Prod. Econ. 229, 107748.
Gligor, D.M., Holcomb, M.C., Stank, T.P., 2013. A multidisciplinary approach to supply chain agility : conceptualization and scale development. J. Bus. Logist. 34 (2), 94–108.
Gunasekaran, A., Papadopoulos, T., Dubey, R., Wamba, S.F., Childe, S.J., Hazen, B., Akter, S., 2017. Big data and predictive analytics for supply chain and organizational performance. J. Bus. Res. 70, 308–317.
Gutierrez, L., Lameijer, B.A., Anand, G., Antony, J., Sunder, M.V., 2022. Beyond efficiency: the role of lean practices and cultures in developing dynamic capabilities microfoundations. Int. J. Oper. Prod. Manag. 42, 506–536.
Hermann, M., Pentek, T., Otto, B., 2015. Design Principles for Industrie 4.0 Scenarios: A Literature Review, vol. 1. Technische Universitat Dortmund, pp. 4–16. Hines, P., Holwe, M., Rich, N., 2004. Learning to evolve: a review of contemporary lean thinking. Int. J. Oper. Prod. Manag. 24 (10), 994–1011.
Hitt, M.A., Xu, K., Carnes, C.M., 2016. Resource based theory in operations management research. J. Oper. Manag. 41, 77–94. Hofmann, E., Rüsch, M., 2017. Industry 4.0 and the current status as well as future prospects on logistics. Comput. Ind. 89, 23–34.
Hofmann, E., Sternberg, H., Chen, H., Pflaum, A., Prockl, G., 2019. Supply chain management and Industry 4.0: conducting research in the digital age. Int. J. Phys. Distrib. Logist. Manag. 49 (10), 945–955.
Inman, R.A., Sale, R.S., Green, K.W., Whitten, D., 2011. Agile manufacturing: relation to JIT, operational performance and firm performance. J. Oper. Manag. 29 (4), 343–355.
Iqbal, T., Jajja, M.S.S., Bhutta, M.K., Qureshi, S.N., 2020. Lean and agile manufacturing: complementary or competing capabilities? J. Manuf. Technol. Manag. 31 (4), 749–774.
Iyer, K.N.S., Srivastava, P., Srinivasan, M., 2019. Performance implications of lean in supply chains: exploring the role of learning orientation and relational resources. Int. J. Prod. Econ. 216, 94–104.
Kagermann, H., Wahlster, W., 2022. Ten years of industrie 4.0. Sci 4 (26), 1–10.
Kagermann, H., Wahlster, W., Helbig, J., 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0. https://www.din.de/blob/76902/e8cac883 f42bf28536e7e8165993f1fd/recommendations-for-implementing-industry-4-0-data. pdf.
Kamble, S., Gunasekaran, A., Dhone, N.C., 2019. Industry 4.0 and lean manufacturing practices for sustainable organisational performance in Indian manufacturing companies. Int. J. Prod. Res. 58 (5), 1319–1337.
Kolberg, D., Knobloch, J., Zühlke, D., 2017. Towards a lean automation interface for workstations. Int. J. Prod. Res. 55, 2845–2856.
Lamming, R., 1996. Squaring lean supply with supply chain management. Int. J. Oper. Prod. Manag. 16 (2), 183–196.
Liu, G., McKone-Sweet, K., Shah, R., 2009. Assessing the performance impact of supply chain planning in net-enhanced organiza-tions. Oper. Manage. Res. 2 (1), 33–43.
Liu, H., Ke, W., Wei, K.K., Hua, Z., 2013. The impact of IT capabilities on firm performance: the mediating roles of absorptive capacity and supply chain agility. Decis. Support Syst. 54 (3), 1452–1462.
Liu, S., Chan, F.T.S., Yang, J., Niu, B., 2018. Understanding the effect of cloud computing on organizational agility: an empirical examination. Int. J. Inf. Manag. 43, 98–111.
Manavalan, E., Jayakrishna, K., 2019. A review of Internet of Things (IoT) embedded sustainable supply chain for industry 4.0 requirements. Comput. Ind. Eng. 127, 925–953.
Mandal, S., 2018. An examination of the importance of big data analytics in supply chain agility development: a dynamic capability perspective. Manage. Res. Rev. 41, 1201–1219.
Maqueira, J.M., Moyano-Fuentes, J., Bruque, S., 2019. Drivers and consequences of an innovative technology assimilation in the supply chain: cloud computing and supply chain integration. Int. J. Prod. Res. 57 (7), 2083–2103.
Maqueira, J.M., Novais, L., Bruque-Camara, ´ S., 2021. Total eclipse on business performance and mass personalization: how supply chain flexibility eclipses lean production direct effect. Supply Chain Manag.: Int. J. 26, 256–278.
Moyano-Fuentes, J., Bruque-Camara, ´ S., Maqueira-Marín, J.M., 2019. Development and validation of a lean supply chain man-agement measurement instrument. Prod. Plann. Control 30 (1), 20–32. Moyano-Fuentes, J., Maqueira-Marín, J.M., Mar-tínez-Jurado, P.J., Sacrist´ an-Díaz, M., 2021. Extending lean management along the supply chain: impact on efficiency. J. Manuf. Technol. Manag. 32 (1), 63–84.
Narasimhan, R., Swink, M., Kim, S.W., 2006. Disentangling leanness and agility: an empirical investigation. J. Oper. Manag. 24 (5), 440–457.
Narayanamurthy, G., Tortorella, G., 2021. Impact of COVID-19 outbreak on employee performance – moderating role of industry 4.0 base technologies. Int. J. Prod. Econ. 234, 108075.
Ngai, E.W.T., Chau, D.C.K., Chan, T.L.A., 2011. Information technology, operational, and management competencies for supply chain agility: findings from case studies. J. Strat. Inf. Syst. 20 (3), 232–249.
Novais, L., Maqueira, J.M., Ortiz-bas, A., ´ 2019. A systematic literature review of cloud computing use in supply chain integration. Comput. Ind. Eng. 129, 296–314.
Novais, L., Maqueira-Marín, J.M., Moyano-Fuentes, J., 2020. Lean production implementation, cloud-supported logistics and supply chain integration: interrelationships and effects on business performance. Int. J. Logist. Manag. 31 (3), 629–663.
Núnez-Merino, ˜ M., Maqueira-Marín, J.M., Moyano-Fuentes, J., Martínez-Jurado, P.J., 2020. Information and digital technologies of Industry 4 . 0 and Lean supply chain management : a systematic literature review. Int. J. Prod. Res. 58 (16), 5034–5061.
Nunnally, J.C., Bernstein, I.H., 1994. The assessment of reliability. Psycometric Theory 3, 248–292.
Oliveira-Dias, D., Maqueira-Marín, J.M., Moyano-Fuentes, J., 2022a. The link between information and digital technologies of industry 4.0 and agile supply chain: mapping current research and establishing new research avenues. Comput. Ind. Eng. 167, 108000.
Oliveira-Dias, D., Maqueira-Marín, J.M., Moyano-Fuentes, J., 2022b. Lean and agile supply chain strategies: the role of Mature and Emerging Information Technologies. Int. J. Logist. Manag. 33, 221–243.
Oliveira-Dias, D., Moyano-Fuentes, J., Maqueira-Marín, J.M., 2022c. Understanding the relationships between information tech-nology and lean and agile supply chain strategies: a systematic literature review. Ann. Oper. Res. 312, 973–1005.
Papanagnou, C., Seiler, A., Spanaki, K., Papadopoulos, T., Bourlakis, M., 2022. Datadrivendigital transformation for emergency situations: The case of the UK retail sector. Int. J. Prod. Econ. 250, 108628.
Podsakoff, P.M., MacKenzie, S.B., Lee, J.Y., Podsakoff, N.P., 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88, 879–903.
Powell, T.C., Dent-Micallef, A., 1997. Information technology as competitive advantage: the role of human, business, and tech-nology resources. Strat. Manag. J. 18 (5), 375–405.
Putnik, G.D., Putnik, Z., 2012. Lean vs agile in the context of complexity management in organizations. Learn. Organ. 19, 248–266.
Qi, Y., Zhao, X., Sheu, C., 2011. The impact of competitive strategy and supply chain strategy on business performance: the role of environmental uncertainty. Decis. Sci. J. 42 (2), 371–389.
Qrunfleh, S., Tarafdar, M., 2013. Lean and agile supply chain strategies and supply chain responsiveness: the role of strategic supplier partnership and postponement. Supply Chain Manag.: Int. J. 18 (6), 571–582.
Qrunfleh, S., Tarafdar, M., 2014. Supply chain information systems strategy: impacts on supply chain performance and firm per-formance. Int. J. Prod. Econ. 147, 340–350.
Queiroz, M., Tallon, P.P., Sharma, R., Coltman, T., 2018. The role of IT application orchestration capability in improving agility and performance. J. Strat. Inf. Syst. 27, 4–21.
Raji, I.O., Shevtshenko, E., Rossi, T., Strozzi, F., 2021a. Industry 4.0 technologies as enablers of lean and agile supply chain strategies: an exploratory investigation. Int. J. Logist. Manag. 32 (4), 1150–1189.
Raji, I.O., Shevtshenko, E., Rossi, T., Strozzi, F., 2021b. Modelling the relationship of digital technologies with lean and agile strategies. Supply Chain Forum 22 (4), 323–346.
Raut, R.D., Mangla, S.K., Narwane, V.S., Dora, M., Liu, M., 2021. Big data analytics as a mediator in lean, agile, resilient, and green (LARG) practices effects on sustainable supply chains. Transport. Res. E Logist. Transport. Rev. 145, 102170.
Reyes, J., Mula, J., Díaz-Madronero, ˜ M., 2021. Development of a conceptual model for lean supply chain planning in industry 4.0: multidimensional analysis for operations management. Prod. Plann. Control 0 (0), 1–16.
Rojo, A.G.B., Llorens-Montes, F.J., Perez-Arostegui, M.N., Stevenson, M., 2020. Ambidextrous supply chain strategy and supply chain flexibility: the contingent effect of ISO 9001. Ind. Manag. Data Syst. 120, 1691–1714.
Rojo, A., Stevenson, M., Llor´ens Montes, F.J., Perez-Arostegui, M.N., 2018. Supply chain flexibility in dynamic environments: the enabling role of operational absorptive capacity and organisational learning. Int. J. Oper. Prod. Manag. 38, 636–666.
Samdantsoodol, A., Cang, S., Yu, H., Eardley, A., Buyantsogt, A., 2017. Predicting the relationships between virtual enterprises and agility in supply chains. Expert Syst. Appl. 84, 58–73.
Sanders, A., Elangeswaran, C., Wulfsberg, J., 2016. Industry 4.0 implies lean manufacturing: research activities in industry 4.0 function as enablers for lean manufacturing. J. Ind. Eng. Manag. 9, 811–833.
Sangari, M.S., Razmi, J., 2015. Business intelligence competence, agile capabilities, and agile performance in supply chain an em-pirical study. Int. J. Logist. Manag. 26 (2), 356–380.
Satorra, A., 1993. Multi-sample analysis of moment-structures: asymptotic validity of inferences based on second-order moments. In: Haagen, M., Bartholomeusz, K., Deistler, A. (Eds.), Statistical Modelling and Latent Variables. Elsevier, North Holland, Amsterdam, pp. 283–298.
Schniederjans, D.G., Ozpolat, K., Chen, Y., 2016. Humanitarian supply chain use of cloud computing. Supply Chain Manag.: Int. J. 21 (5), 569–588.
Sharma, V., Raut, R.D., Mangla, S.K., Narkhede, B.E., Luthra, S., Gokhale, R., 2021. A systematic literature review to integrate lean, agile, resilient, green and sustainable paradigms in the supply chain management. Bus. Strat. Environ. 30 (2), 1191–1212.
Srinivasan, M., Srivastava, P., Iyer, K.N.S., 2020. Response strategy to environment context factors using a lean and agile approach: implications for firm performance. Eur. Manag. J. 38 (6), 900–913.
Swafford, P.M., Ghosh, S., Murthy, N., 2008. Achieving supply chain agility through IT integration and flexibility. Int. J. Prod. Econ. 116, 288–297.
Tachizawa, E.M., Gimenez, C., 2010. Supply flexibility strategies in Spanish firms: results from a survey. Int. J. Prod. Econ. 124 (1), 214–224.
Tarafdar, M., Qrunfleh, S., 2017. Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility. Int. J. Prod. Res. 55, 925–938.
Teece, D.J., 2012. Dynamic capabilities: routines versus entrepreneurial action. J. Manag. Stud. 49, 1395–1401.
Teece, D.J., 2007. Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance. Strat. Manag. J. 28 (13), 1319–1350.
Teece, D.J., Pisano, G., Shuen, A., 1997. Dynamic capabilities and strategic management. Strategic Mangement Journal 18, 509–533.
Tortorella, G.L., Cawley Vergara, A., Mac Garza-Reyes, J.A., Sawhney, R., 2020. Organizational learning paths based upon industry 4.0 adoption: an empirical study with Brazilian manufacturers. Int. J. Prod. Econ. 219, 284–294.
Tortorella, G.L., Fettermann, D., 2018. Implementation of industry 4.0 and lean production in brazilian manufacturing companies. Int. J. Prod. Res. 56 (8), 2975–2987.
Tortorella, G.L., Miorando, R., Marodin, G., 2017. Lean supply chain management: empirical research on practices, contexts and performance. Int. J. Prod. Econ. 193, 98–112.
Tortorella, G.L., Saurin, T.A., Filho, M.G., Samson, D., Kumar, M., 2021. Bundles of Lean Automation practices and principles and their impact on operational performance. Int. J. Prod. Econ. 235, 108106. van der Vaart, T., van Donk, D.P., Gimenez, C., Sierra, V., 2012. Modelling the integration-performance relationship: collaborative practices, enablers and contextual factors. Int. J. Oper. Prod. Manag. 32, 1043–1074.
Vinodh, S., Sundararaj, G., Devadasan, S.R., 2009. Total agile design system model via literature exploration. Ind. Manag. Data Syst. 109 (4), 570–588.
Vonderembse, M.A., Uppal, M., Huang, S.H., Dismukes, J.P., 2006. Designing supply chains: towards theory development. Int. J. Prod. Econ. 100, 223–238.
Wamba, S.F., Akter, S., 2019. Understanding supply chain analytics capabilities and agility for data-rich environments. Int. J. Oper. Prod. Manag. 39 (6), 887–912.
Wamba, S.F., Dubey, R., Gunasekaran, A., Akter, S., 2020. The performance effects of big data analytics and supply chain ambi-dexterity: the moderating effect of environmental dynamism. Int. J. Prod. Econ. 222, 107498.
Wei, J., Lowry, P.B., Seedorf, S., 2015. The assimilation of RFID technology by Chinese companies: a technology diffusion per-spective. Inf. Manag. 52, 628–642.
Wilson, H., Daugherty, P., 2020. Small data can play A big role in ai. Harv. Bus. Rev. https://hbr.org/2020/02/small-data-can-play-a-big-role-in-ai.
Winter, S.G., 2003. Understanding dynamic capabilities. Strat. Manag. J. 24, 991–995.
Yan, J., Xin, S., Liu, Q., Xu, W., Yang, L., Fan, L., et al., 2014. Intelligent supply chain integration and management based on cloud of things. Int. J. Distributed Sens. Netw. 2014, 1–15.
Yu, W., Jacobs, M.A., Chavez, R., Yang, J., 2019. Dynamism, disruption orientation, andresilience in the supply chain and the impacts on financial performance: A dynamiccapabilities perspective. Int. J. Prod. Econ. 218, 352–362.
Yusuf, Y.Y., Adeleye, E.O., 2002. A comparative study of lean and agile manufacturing with a related survey of current practices in the UK. Int. J. Prod. Res. 40 (17), 4545–4562.
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