Does digitalising the supply chain contribute to its resilience?
Tóm tắt
Supply chain resilience (SCR) is a key concept for managers who wish to develop the capacity to enhance their supply chain’s (SC’s) ability to cope with unexpected turbulence. SC digital tools are often seen as a solution that provides more visibility, anticipation and collaboration (SCR capability factors). The purpose of this paper is to investigate the link between SCR and SC digitalisation
A sample was considered with 300 managers in the field of SCM, and the results were analysed using factor analysis and structural equation modelling (SEM). SEM was employed to test the impact of the degree of digital maturity and SC digital tools on SCR.
SC digitalization is characterised by the degree of digital maturity and the adoption of SC digital tools. The degree of digital maturity has a strong influence on digital tool adoption. SCR is positively impacted by both the degree of digital maturity and the adoption of digital tools.
The findings do not indicate which tools contribute the most to SCR.
Managers should reflect on the need to continue digitalizing their SCs if they want greater SCR in the current uncertain environment.
This is the first quantitative study that focuses on assessing the impact of the degree of digital maturity and the SC digital tools adopted on SCR. Validation of the hypotheses model confirms the positive impact of SC digitalisation on SCR for researchers and managers.
Từ khóa
Tài liệu tham khảo
2010, Value creation in innovation ecosystems: how the structure of technological interdependence affects firm performance in new technology generations, Strategic Management Journal, 31, 306, 10.1002/smj.821
2018, Maturity and readiness model for industry 4.0 strategy, Industry 4.0: Managing the Digital Transformation, 61
2015, Designing robustness and resilience in digital investigation laboratories, Digital Investigation, 12, S111, 10.1016/j.diin.2015.01.015
2019, Blockchain technology in the energy sector: a systematic review of challenges and opportunities, Renewable and Sustainable Energy Reviews, 100, 143, 10.1016/j.rser.2018.10.014
2019, Supply chain risk management and artificial intelligence: state of the art and future research directions, International Journal of Production Research, 57, 2179, 10.1080/00207543.2018.1530476
2020, How to perform and report an impactful analysis using partial least squares: guidelines for confirmatory and explanatory IS research, Information and Management, 57, 103168, 10.1016/j.im.2019.05.003
2007, Information system architecture: a framework for a cluster of small and medium-sized enterprises (SMEs), Production Planning and Control, 18, 283, 10.1080/09537280701248578
2018, Procurement 4.0: factors influencing the digitisation of procurement and supply chains, Business Process Management Journal, 24, 965, 10.1108/BPMJ-06-2017-0139
2018, Digital supply chain: literature review and a proposed framework for future research, Computers in Industry, 97, 157
2010, How to write up and report PLS analyses, Handbook of Partial Least Squares, 655, 10.1007/978-3-540-32827-8_29
2010, An introduction to a permutation based procedure for multi-group PLS analysis: results of tests of differences on simulated data and a cross cultural analysis of the sourcing of information system services between Germany and the USA, Handbook of Partial Least Squares, 171, 10.1007/978-3-540-32827-8_8
2003, CMMI: Guidelines for Process Integration and Product Improvement
2016, Logistics and Supply Chain Management, 5th ed.
2019, Managing cyber and information risks in supply chains: insights from an exploratory analysis, Supply Chain Management, 24, 215, 10.1108/SCM-09-2017-0289
2019, A maturity assessment approach for conceiving context-specific roadmaps in the Industry 4.0 era, Annual Reviews in Control, 48, 165, 10.1016/j.arcontrol.2019.06.001
2020, Cybersecurity in the context of Industry 4.0: a structured classification of critical assets and business impacts, Computers in Industry, 114, 1
2008, Cost-benefit model for smart items in the supply chain, The Internet of Things, Lecture Notes in Computer Science, 155
Deloitte (2017), “MHI annual industry report: next-generation supply chains: digital, on-demand and always-on”, available at: https://www2.deloitte.com/content/dam/Deloitte/pl/Documents/Reports/pl_MHI_Industry_Report_2017.pdf (accessed 20 May 2020).
2016, Scale Development: Theory and Applications
2010, Cloud computing: issues and challenges, 27
2000, Mail and Internet Surveys: The Tailored Design Method
2018, Data mining-based prediction of manufacturing situations, IFAC-PapersOnLine, 51, 316, 10.1016/j.ifacol.2018.08.302
2020, Blockchain-oriented dynamic modelling of smart contract design and execution in the supply chain, International Journal of Production Research, 50, 2184
2016, The impact of big data on world-class sustainable manufacturing, The International Journal of Advanced Manufacturing Technology, 84, 631, 10.1007/s00170-015-7674-1
2019, Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience, International Journal of Production Research, 1, 10.1080/00207543.2019.1582820
2013, Systèmes d'information et résilience des chaînes logistiques globales / Information systems and resilience of global supply chains, Systèmes d'information Management, 18, 57, 10.3917/sim.131.0057
2015, Impact of RFID technology on supply chain decisions with inventory inaccuracies, International Journal of Production Economics, 159, 117, 10.1016/j.ijpe.2014.10.004
2010, When is RFID right for your service?, International Journal of Production Economics, 124, 414, 10.1016/j.ijpe.2009.12.004
2006, Sustainability and resilience: toward a systems approach, Sustainability: Science, Practice and Policy, 2, 1
2019, Industry 4.0 technologies: implementation patterns in manufacturing companies, International Journal of Production Economics, 210, 15, 10.1016/j.ijpe.2019.01.004
2002, Techniques for improving response rates in OM survey research, Journal of Operations Management, 20, 53, 10.1016/S0272-6963(02)00003-7
2016, Three stage maturity model in SME's toward Industry 4.0, Journal of Industrial Engineering and Management, 9, 1119, 10.3926/jiem.2073
2019, Digital supply chain model in industry 4.0, Journal of Manufacturing Technology Management, 10.1108/JMTM-08-2018-0280
2005, Management development: key differences between small and large businesses in Europe, International Small Business Journal, 23, 467, 10.1177/0266242605055908
2016, Information technology governance in Internet of Things supply chain networks, Industrial Management & Data Systems, 116, 1
2017, A Primer on Partial Least Squares Structural Equation Modeling, 2nd ed.
2019, Impact of transforming organizational culture and digital transformation governance toward digital maturity in Indonesian banks, International Review of Management and Marketing, 9, 51, 10.32479/irmm.8785
IEEE Corporate Advisory Group, 2017, IEEE Guide for Terms and Concepts in Intelligent Process Automation
2018, Industrie 4.0 roadmap: framework for digital transformation based on the concepts of capability maturity and alignment, 973
2018, Structural Dynamics and Resilience in Supply Chain Risk Management
2020, Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic, Annals of Operations Research, 1, 1
2019, Low-certainty-need (LCN) supply chains: a new perspective in managing disruption risks and resilience, International Journal of Production Research, 57, 5119, 10.1080/00207543.2018.1521025
2019, New disruption risk management perspectives in supply chains: digital twins, the ripple effect, and resileanness, IFAC-Papers Online, 52, 337, 10.1016/j.ifacol.2019.11.138
2020, A digital supply chain twin for managing the disruption risks and resilience in the era of Industry 4.0, Production Planning & Control, 1
2014, The ripple effect in supply chains: trade-off ‘efficiency-flexibility-resilience’ in disruption management, International Journal of Production Research, 52, 2154, 10.1080/00207543.2013.858836
Ivanov, D., Dolgui, A., Das, A. and Sokolov, B. (2019a), “Digital supply chain twins: managing the ripple effect, resilience and disruption risks by data-driven optimization, simulation, and visibility”, in Ivanov, D., Dolgui, A. and Sokolov, B. (Eds), Handbook of Ripple Effects in the Supply Chain, Springer, New York, NY, pp. 309-332.
2019, The impact of digital technology and industry 4.0 on the ripple effect and supply chain risk analytics, International Journal of Production Research, 57, 829, 10.1080/00207543.2018.1488086
2019, Digital transformation technologies as an enabler for sustainable logistics and supply chain processes – an exploratory framework, Brazilian Journal of Operations & Production Management, 16, 462, 10.14488/BJOPM.2019.v16.n3.a9
2017, Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management, International Journal of Operations & Production Management, 37, 10, 10.1108/IJOPM-02-2015-0078
2008, Value analysis of location-enabled radio-frequency identification information on delivery chain performance, International Journal of Production Economics, 112, 403, 10.1016/j.ijpe.2007.04.006
2016, The wild, distributed world: get ready for radical infrastructure changes, from blockchains to the interplanetary file system to the internet of things, Intellectual Property & Technology Law Journal, 28, 3
2017, Using Blockchain to Drive Supply Chain Innovation
2015, The Internet of Things (IoT): applications, investments, and challenges for enterprises, Business Horizons, 58, 431, 10.1016/j.bushor.2015.03.008
2020, Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture, Computers in Industry
McKinsey and Company (2015), “Industry 4.0: how to navigate digitalization of the manufacturing sector”, available at: www.mckinsey.de/files/mck_industry_40_report.pdf (accessed 20 May 2020).
2011, The NIST Definition of Cloud Computing, 800
2010, Artificial intelligence in supply chain management: theory and applications, International Journal of Logistics: Research and Applications, 13, 13, 10.1080/13675560902736537
2019, Blockchain technology for enhancing supply chain resilience, Business Horizons, 62, 35, 10.1016/j.bushor.2018.08.012
2018, Big data analytics in supply chain management: a state-of-the-art literature review, Computers & Operations Research, 98, 254, 10.1016/j.cor.2017.07.004
2018, Agile Procurement
2017, Remote real-time collaboration through synchronous exchange of digitised human-workpiece interactions, Future Generation Computer Systems, 67, 83, 10.1016/j.future.2016.08.012
2017, The role of big data in explaining disaster resilience in supply chains for sustainability, Journal of Cleaner Production, 142, 1108
2018, Fourth industrial revolution: current practices, challenges, and opportunities, digital transformation, Smart Manufacturing, Intech Open, 10.5772/intechopen.72304
2010, Ensuring supply chain resilience: development of a conceptual framework, Journal of Business Logistics, 31, 1, 10.1002/j.2158-1592.2010.tb00125.x
2013, Ensuring supply chain resilience: development and implementation of an assessment tool, Journal of Business Logistics, 34, 46, 10.1111/jbl.12009
2019, The evolution of resilience in supply chain management: a retrospective on ensuring supply chain resilience, Journal of Business Logistics, 40, 56, 10.1111/jbl.12202
2009, Understanding the concept of supply chain resilience, International Journal of Logistics Management, 20, 124, 10.1108/09574090910954873
2020, Barriers to the adoption of industry 4.0 technologies in the manufacturing sector: an inter-country comparative perspective, International Journal of Production Economics, 224, 10.1016/j.ijpe.2019.107546
2018, A survey on internet of things architectures, Journal of King Saud University-Computer and Information Sciences, 30, 291, 10.1016/j.jksuci.2016.10.003
2016, A global exploration of big data in the supply chain, International Journal of Physical Distribution & Logistics Management, 46, 710, 10.1108/IJPDLM-05-2016-0134
2007, Introduction: understanding and dealing with organizational survey nonresponse, Organizational Research Methods, 10, 195, 10.1177/1094428106294693
2016, 3D printing services: classification, supply chain implications and research agenda, International Journal of Physical Distribution & Logistics Management, 46, 886, 10.1108/IJPDLM-07-2016-0210
2016, Enterprise information systems state of the art: past, present and future trends, Computers in Industry, 79, 3, 10.1016/j.compind.2016.03.001
1995, Artificial Intelligence: A Modern Approach
2018, A conceptual framework for industry 4.0, Industry 4.0: Managing the Digital Transformation, 3
2016, The 3D printing order: variability, supercenters and supply chain reconfigurations, International Journal of Physical Distribution & Logistics Management, 46, 82, 10.1108/IJPDLM-10-2015-0257
2019, Supply chain digitisation trends: an integration of knowledge management, International Journal of Production Economics, 2020, 10.1016/j.ijpe.2019.07.012
2015, Data science, predictive analytics, and big data in supply chain management: current state and future potential, Journal of Business Logistics, 36, 120, 10.1111/jbl.12082
2017, Industrie 4.0 Maturity IndexManaging the Digital Transformation of Companies
2010, Cloud computing for autonomous control in logistics, Service Science – Neue Perspektiven für die Informatik. Band 1, 305
2016, A maturity model for assessing industry 4.0 readiness and maturity of manufacturing enterprises, Procedia CIRP, 52, 161, 10.1016/j.procir.2016.07.040
2019, PLS-based model selection: the role of alternative explanations in information systems research, Journal of the Association for Information Systems, 20, 346
2015, Preparing for disruptions through early detection, MIT Sloan Management Review, 57, 31
2005, A supply chain view of the resilient enterprise, MIT Sloan Management Review, 47, 41
2018, Characterizing supply chain visibility – a literature review, International Journal of Logistics Management, 29, 308, 10.1108/IJLM-06-2016-0150
2019, Toward a digitally dominant paradigm for twenty-first century supply chain scholarship, International Journal of Physical Distribution and Logistics Management, 49, 956, 10.1108/IJPDLM-03-2019-0076
2012, Controls, service type and perceived supplier performance in interfirm service exchanges, Journal of Operations Management, 30, 423, 10.1016/j.jom.2012.01.002
2019, The strategic role of logistics in the industry 4.0 era, Transportation Research Part E: Logistics and Transportation Review, 129, 1, 10.1016/j.tre.2019.06.004
2005, PLS path modeling, Computational Statistics and Data Analysis, 48, 159, 10.1016/j.csda.2004.03.005
2015, Supply chain resilience: definition, review and theoretical foundations for further study, International Journal of Production Research, 53, 5592, 10.1080/00207543.2015.1037934
2017, Estimating hierarchical constructs using consistent partial least squares: the case of second-order composites of common factors, Industrial Management & Data Systems, 117, 459, 10.1108/IMDS-07-2016-0286
2013, Virtualisation of floricultural supply chains: a review from an internet of things perspective, Computers and Electronics in Agriculture, 99, 160, 10.1016/j.compag.2013.09.006
2010, PLS path modeling: from foundations to recent developments and open issues for model assessment and improvement, Handbook of Partial Least Squares, 47, 10.1007/978-3-540-32827-8_3
2012, The maturity of maturity model research: a systematic mapping study, Information and Software Technology, 54, 1317, 10.1016/j.infsof.2012.07.007
1974, Intraclass reliability estimates: testing structural assumptions, Educational and Psychological Measurement, 34, 25, 10.1177/001316447403400104
2009, Using PLS path modeling for assessing hierarchical construct models: guidelines and empirical illustration, MIS Quarterly, 33, 177, 10.2307/20650284
2018, Can you measure resilience if you are unable to define it? The analysis of supply network resilience (SNRES), Supply Chain Forum: An International Journal, 19, 255, 10.1080/16258312.2018.1540248
2019, The impact of big data on supply chain resilience: the moderating effect of supply chain complexity