Sustainable Performance through Digital-Supply-Chains in Industry 4.0 Era: History
View Latest Version
Please note this is an old version of this entry, which may differ significantly from the current revision.
Contributor:
Sudhanshu Joshi
,
Manu Sharma

Amidst the COVID-19 pandemic disruption, industry 4.0 technologies (I4TEs) and digital supply chains (DSCs) are reinforcing businesses to gain economic stability and agility to enrich their sustainable performance 

  • industry 4.0 technologies (I4TEs)
  • digital supply chain (DSC)
  • supply chain 4.0

1. Industry 4.0 Technologies (I4TEs)

Due to changing market dynamics and consumer needs, organizations are revisiting and adapting their existing processes. Managers are constantly looking toward adopting advanced technologies to improve their S.C.s and achieve their sustainability goals [1][2][3][4][5]. The sustainability perspective of systems needs to be understood, and thus, organizations are exploring new technologies that might help them succeed [6]. Various digital technologies under IE 4.0 are adapted by organizations to improve their processes. These technologies have emerged as highly productive technologies to attain sustainable business performance. The key objective of I4TEs is to develop a highly integrated, real-time responsive, and efficient manufacturing system [7]. These technologies enabled backward and forwarded integration in the value chain. Multiple technologies result in robust data extraction, storage, and dissemination, with or without human intervention [8][9]. I4TEs enable the high quality of data to bring economies of operation and faster and flawless services among S.C. partners. The other commercial advantage of I4TE is enhancing information quality for routine business communication in S.C. and training purposes. I4TE-lead digital technologies can improve operations in a disruptive environment amidst a pandemic.

2. Digital Supply Chains

The impact of digitalization has been assessed and found to be significant for decision-making through a distributed network of integrated digital and physical loops [10][11]. Straub [12] evaluated the significance of digital supply chains for information generation and sharing among suppliers. The study showed that the supply network could be improvised with digital technologies, primarily through I4TEs. Over time, the need for supply networks to obtain upgraded will be due to the convergence with digital technologies. Supply chain networks have become real-time, agile, resilient, and lean [13][14]. The primary property of such networks is that they become more customer-oriented and cater to the more significant needs of the stakeholders, including vendors, third parties, products, and services [14]. The digital data are accessible to all stakeholders and allow users to synchronize operational decisions [15]. The other advantage of DSC is a strategic combination of human–machine interaction for designing and developing products and services in collaboration across various levels of the supply chains [16]. It helps S.C. firms to trace and improve the material flows and the value chains. This transformation from conventional to digital supply chains involves stakeholders interacting with each other [17]. That, in turn, helps the business firm in strategic decision-making through data insights from the digital ecosystem [18]. An organization’s decision-making capabilities depend on lean, agile, resilient, and green operations. Companies will make specific decisions based on the absorption capabilities of the firm [19]. In a dynamic setting, decision-makers must identify the focus areas in DSCs to prioritize their efforts [20]. Table 1 exhibits the dimensions of DSCs. Based on the literature, the dimensions of DSCs to deal with disruption are as below.
Table 1. Dimensions of DSCs to deal with disruption.
Dimension The Implication in a Disruptive Environment Sustainable Performance References
Agility and Responsiveness (AaR) The responsiveness and agility enhance the firms’ preparedness to deal with disruption. It will also make S.C.s responsive in post-pandemic situations.
-
Helps to anticipate customer demand and optimize inventory
-
Helps in designing optimal supply networks
-
Ensures on-time fulfillment of demand
 [13][20][21][22]
Digital Collaboration (D.C.) Advanced technologies to collaborate with strategic partners to improve the customer and supplier experiences for reducing risk during the pandemic. It reduces cost and human contact and enhances efficiency.
-
Prediction of cost fluctuations
-
Digital platforms for invoices and requisitions
-
Anticipating SC risk
-
Selection of best sourcing for cost optimization
 [23][24][25][26][27]
Intelligent Optimization (IO) Closed loop of combined humans and machines. It aids in appropriate decision-making for balancing demand and supply during the disruption.
-
Optimized human–machine decision making
 [25][26][27][28][29][30][31][32]
End-to-end Transparency (E.E.) To enhance transparency throughout the S.C.s. The tracking becomes easier during stock-out situations and develops trust among the stakeholders.
-
Helps in predicting demand forecasting
-
Avoids stock-out situations
-
Matching changes with customers shifting channels
 [17][23][29][33][34][35]
Holistic Decision-making (H.D.) An integrated approach for decision-making. It enhances overall efficiency during the disruptive environment.
-
Helps in performance optimization
-
Delivers parallel visibility
 [30][32][33]

3. Sustainable Performance (S.P.)

I4TEs broadly change the landscape of supply chain activities with more value addition that positively influences a firm’s economy. The enhancement brings dynamic development to the supply chain ecosystem. Thus, firms started realizing sustainable performance for economic and social benefits. Various tools, including the triple bottom line, became significant in evaluating the S.P. of firms [36]. DSC is evolving as a tool to generate a sustainable competitive advantage for the firm through an intelligent, autonomous, and highly responsive supplier network [37]. Various underlined technologies, including big data and additive manufacturing, are used for process integration and productivity enhancement. I4TE is a portfolio of digital technology that abides by the IPT and dynamic capability of the firm to generate sustainable business performance [38][39]. 

4. Supply Chain Disruptions amid COVID-19 Pandemic

The pandemic has created market shrinkage, with managers looking for new processes to maintain production levels. Notably, this pandemic has challenged organizational environmental sustainability, downsized the consumer base, and raised enormous questions for industrial management. The latest works by Govindan et al. [40] and Ivanov [28] have highlighted the devastating impact of COVID-19 on GSCs. Based on findings from this study, the S.C. network has shown poor resilience to the pandemic, with approximately 35% of manufacturers reporting S.C. network failure due to COVID-19. Thus, decision-makers have been forced to explore technological transformations to enhance agility, readiness, and resilience in their S.C.s. I4TEs have developed a framework to adopt cyber–physical integration principles in various processes, such as manufacturing, SCM, and logistics [34][41]. The pandemic has accelerated the need for real-time data to develop resilient S.C.s for the future.
BDA has provided much support in decision-making to organizations in areas such as logistics operations [42][43] and emergency operations decisions [44][45] to minimize the pandemic impact. Ivanov [16] identified the effects of disruption on S.C. responses. Additionally, recent studies suggest that I4TEs can enhance resilience and ripple effect control [28][30]. Moreover, firms with successful digital networks are better positioned during the pandemic and show a more positive indication of recovery processes [46][47]. S.C. operations are also indirectly affected by the disruption. These operations propagate through S.C. and cause a ripple effect. The study by Ivanov and Dolgui [28] shows that the ripple effect is more prevalent in GSCs with multi-tier organizational networks. To find balance, robust S.C. resilience strategies need to be built. Thus, companies are exploring solutions to predict risks and assess vulnerability to protect S.C. operations during these uncertain times. The main papers examined for this study to understand the current scenario of I4TEs, DSCs, and S.P. during the pandemic are listed in Table 2. Bier et al. [48] described a systematic study review and content analysis that has been carried out to evaluate the methods for mitigating supply chain disruptions.
Table 2. The main contributions are focused on COVID-19 impact.
Author (s) The Objective of the Study Industry
[48] To explore risk management in SCs SC
[34] Application of I4TEs to develop a framework for cyber–physical integration adoption Manufacturing
[40] Development of decision support system for healthcare S.C. Healthcare
[28] To predict the effect of COVID-19 on GSCs SC
[49] How I4Te can deal with the COVID-19 pandemic Manufacturing
[50] Role of COVID-19 in transition to sustainable S.C. production Production and SC
[45] Impact of the pandemic on sustainable production and consumption S.C. and operation management
[51] How pharmaceutical S.C.s sustain in the COVID-19 Pharmaceutical SCs
Various theories and future research directions were discussed in the risk structure. Ghadge et al. [34] evaluated the impact of industry 4.0 on supply chain sustainability using simulation. Govindan et al. [40] proposed a decision support system for demand fulfillment in the public health supply chain during the disruption. The authors proposed a real-time fuzzy inference system for controlled groups. Javed et al. [49] discussed the safety concerns of automation and digitalization. The research illustrates use cases to demonstrate the interaction between autonomous machines and hazardous materials during manufacturing operations. Industry 4.0 technologies (IIoT, cloud, and fog computing) with HAZOP and fault tree analysis support flexible production operations. Sharma et al [50] explained research themes for investigating sustainable supply chains.
Similarly, Kumar et al. [45] explained using digital technologies for humanitarian operations through real-time online platforms. Liza et al. [51] discussed lean production and the usage of IE 4.0 technologies for sustainable and intelligent operations to obtain sustainable performance. These studies have contributed to insights into the disruption and suggest possible solutions to develop sustainable S.C.s for the long term.

This entry is adapted from the peer-reviewed paper 10.3390/su142416726

References

  1. Joshi, S.; Sharma, M.; Agarwal, R.; Madan, P. Sustainable Manufacturing and Services in Industry 4.0: Research Agenda and Directions. In Computing Predictive Analytics, Business Intelligence, and Economics, 1st ed.; Apple Academic Press: Waretown, NJ, USA, 2019; pp. 97–120.
  2. Joshi, S.; Sharma, M. Digital technologies (DT) adoption in agri-food supply chains amidst COVID-19: An approach towards food security concerns in developing countries. J. Glob. Oper. Strat. Sourc. 2021, 15, 262–282.
  3. Unhelkar, B.; Joshi, S.; Sharma, M.; Prakash, S.; Mani, A.K.; Prasad, M. Enhancing Supply Chain Performance using RFID Technology and Decision Support Systems in the Industry 4.0—A Systematic Literature Review. Int. J. Inf. Manag. Data Insights 2022, 2, 100084.
  4. Sharma, M.; Joshi, S.; Luthra, S.; Kumar, A. Analysing the Impact of Sustainable Human Resource Management Practices and Industry 4.0 Technologies Adoption on Employability Skills. Int. J. Manpow. 2022, 43, 463–485.
  5. Joshi, S.; Sharma, M.; Das, R.P.; Rosak-Szyrocka, J.; Żywiołek, J.; Muduli, K.; Prasad, M. Modeling Conceptual Framework for Implementing Barriers of AI in Public Healthcare for Improving Operational Excellence: Experiences from Developing Countries. Sustainability 2022, 14, 11698.
  6. Oluyisola, O.E.; Bhalla, S.; Sgarbossa, F.; Strandhagen, J.O. Designing and developing smart production planning and control systems in the industry 4.0 era: A methodology and case study. J. Intell. Manuf. 2022, 33, 311–332.
  7. Atieh, A.M.; Cooke, K.O.; Osiyevskyy, O. The role of intelligent manufacturing systems in the implementation of Industry 4.0 by small and medium enterprises in developing countries. Eng. Rep. 2022, e12578.
  8. Bag, S.; Yadav, G.; Wood, L.C.; Dhamija, P.; Joshi, S. Industry 4.0 and the circular economy: Resource melioration in logistics. Resour. Policy 2020, 68, 101776.
  9. Sinha, A.; Bernardes, E.; Calderon, R.; Wuest, T. Digital Supply Networks; McGraw Hill-Ascent Audio: London, UK, 2021.
  10. Frazzon, E.M.; Agostino, R.S.; Broda, E.; Freitag, M. Manufacturing networks in the era of digital production and operations: A socio-cyber-physical perspective. Annu. Rev. Control 2020, 49, 288–294.
  11. Dolgui, A.; Ivanov, D. 5G in digital supply chain and operations management: Fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. Int. J. Prod. Res. 2022, 60, 442–451.
  12. Yang, Y.; Jiang, Y. Buyer-supplier CSR alignment and firm performance: A contingency theory perspective. J. Bus. Res. 2023, 154, 113340.
  13. Ogbuke, N.J.; Yusuf, Y.Y.; Dharma, K.; Mercangoz, B.A. Big data supply chain analytics: Ethical, privacy and security challenges posed to business, industries and society. Prod. Plan. Control. 2022, 33, 123–137.
  14. Oliveira-Dias, D.; Maqueira-Marín, J.M.; Moyano-Fuentes, J. 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. 2022, 167, 108000.
  15. Rodrigues, F.; Borges, M.; Rodrigues, H. Risk management in water supply networks: Aveiro case study. Environ. Sci. Pollut. Res. 2020, 27, 4598–4611.
  16. Ivanov, D. Digital Supply Chain Management and Technology to Enhance Resilience by Building and Using End-to-End Visibility During the COVID-19 Pandemic. IEEE Trans. Eng. Manag. 2021, 11, 1–11.
  17. Bai, C.; Sarkis, J. A supply chain transparency and sustainability technology appraisal model for blockchain technology. Int. J. Prod. Res. 2020, 58, 2142–2162.
  18. Arora, A.; Arora, A.S.; Sivakumar, K.; Burke, G. Strategic sustainable purchasing, environmental collaboration, and organizational sustainability performance: The moderating role of supply base size. Supply Chain Manag. Int. J. 2020, 25, 709–728.
  19. Sharma, M.; Luthra, S.; Joshi, S.; Kumar, A. Accelerating retail supply chain performance against pandemic disruption: Adopting resilient strategies to mitigate the long-term effects. J. Enterp. Inf. Manag. 2021, 34, 1844–1873.
  20. Alzoubi, H.M.; Yanamandra, R. Investigating the mediating role of information sharing strategy on agile supply chain. Uncertain Supply Chain Manag. 2020, 8, 273–284.
  21. Shashi; Centobelli, P.; Cerchione, R.; Ertz, M. Agile supply chain management: Where did it come from and where will it go in the era of digital transformation? Ind. Mark. Manag. 2020, 90, 324–345.
  22. Ghezzi, A.; Cavallo, A. Agile Business Model Innovation in Digital Entrepreneurship: Lean Startup Approaches. J. Bus. Res. 2020, 110, 519–537.
  23. Farajpour, F.; Hassanzadeh, A.; Elahi, S.; Ghazanfari, M. Digital supply chain blueprint via a systematic literature review. Technol. Forecast. Soc. Chang. 2022, 184, 121976.
  24. Pardo, C.; Ivens, B.S.; Pagani, M. Are products striking back? The rise of smart products in business markets. Ind. Mark. Manag. 2020, 90, 205–220.
  25. Haddad, A.; Khare, A. Digitalizing supply chains potential benefits and impact on lean operations. Int. J. Lean Six Sigma 2020, 11, 731–765.
  26. Tao, F.; Zhang, Y.; Cheng, Y.; Ren, J.; Wang, D.; Qi, Q.; Li, P. Digital twin and blockchain enhanced smart manufacturing service collaboration and management. J. Manuf. Syst. 2020, 62, 903–914.
  27. Katsaliaki, K.; Galetsi, P.; Kumar, S. Supply chain disruptions and resilience: A major review and future research agenda. Ann. Oper. Res. 2022, 395, 965–1002.
  28. Ivanov, D.; Dolgui, A. Viability of intertwined supply networks: Extending the supply chain resilience angles towards survivability. A position paper motivated by the COVID-19 outbreak. Int. J. Prod. Res. 2020, 58, 2904–2915.
  29. Gupta, S.; Modgil, S.; Gunasekaran, A.; Bag, S. Dynamic capabilities and institutional theories for Industry 4.0 and digital supply chain. Supply Chain Forum Int. J. 2020, 21, 139–157.
  30. Sawik, T. Stochastic optimization of supply chain resilience under ripple effect: A COVID-19 pandemic related study. Omega 2022, 109, 102596.
  31. Corsini, R.R.; Costa, A.; Fichera, S.; Framinan, J.M. A new data-driven framework to select the optimal replenishment strategy in complex supply chains. IFAC-PapersOnLine 2022, 55, 1423–1428.
  32. Priore, P.; Ponte, B.; Rosillo, R.; de la Fuente, D. Applying machine learning to the dynamic selection of replenishment policies in fast-changing supply chain environments. Int. J. Prod. Res. 2019, 57, 3663–3677.
  33. Marcucci, G.; Antomarioni, S.; Ciarapica, F.E.; Bevilacqua, M. The impact of Operations and IT-related Industry 4.0 key technologies on organizational resilience. Prod. Plan. Control 2022, 33, 1417–1431.
  34. Ghadge, A.; Kara, M.E.; Moradlou, H.; Goswami, M. The impact of Industry 4.0 implementation on supply chains. J. Manuf. Technol. Manag. 2020.
  35. de Sousa Jabbour, A.B.L.; Jabbour, C.J.C.; Hingley, M.; Vilalta-Perdomo, E.L.; Ramsden, G.; Twigg, D. Sustainability of supply chains in the wake of the coronavirus (COVID-19/SARS-CoV-2) pandemic: Lessons and trends. Mod. Supply Chain Res. Appl. 2020, 2, 117–122.
  36. Liute, A.; De Giacomo, M.R. The environmental performance of UK-based B Corp companies: An analysis based on the triple bottom line approach. Bus. Strat. Environ. 2022, 31, 810–827.
  37. Zhu, G.; Chou, M.; Tsai, C. Lessons Learned from the COVID-19 Pandemic Exposing the Shortcomings of Current Supply Chain Operations: A Long-Term Prescriptive Offering. Sustainability 2020, 12, 5858.
  38. Kamble, S.S.; Gunasekaran, A.; Parekh, H.; Joshi, S. Modeling the internet of things adoption barriers in food retail supply chains. J. Retail. Consum. Serv. 2019, 48, 154–168.
  39. Ali, S.S.; Kaur, R.; Khan, S. Evaluating sustainability initiatives in warehouse for measuring sustainability performance: An emerging economy perspective. Ann. Oper. Res. 2022, 1–40.
  40. Govindan, K.; Mina, H.; Alavi, B. A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19). Transp. Res. Part E Logist. Transp. Rev. 2020, 138, 101967.
  41. Joshi, S.; Sharma, M.; Chatterjee, P. Omni-Channel retailing enhancing unified experience amidst pandemic: An emerging market perspective. Decis. Mak. Appl. Manag. Eng. 2022.
  42. Albqowr, A.; Alsharairi, M.; Alsoussi, A. Big data analytics in supply chain management: A systematic literature review. VINE J. Inf. Knowl. Manag. Syst. 2022. online ahead-of-print.
  43. Pawar, P.V.; Paluri, R.A. Big Data Analytics in Logistics and Supply Chain Management: A Review of Literature. Vision J. Bus. Perspect. 2022.
  44. Joshi, S.; Sharma, M.; Das, R.P.; Muduli, K.; Raut, R.; Narkhede, B.E.; Shee, H.; Misra, A. Assessing Effectiveness of Humanitarian Activities against COVID-19 Disruption: The Role of Blockchain-Enabled Digital Humanitarian Network (BT-DHN). Sustainability 2022, 14, 1904.
  45. Kumar, A.; Joshi, S.; Sharma, M.; Vishvakarma, N. Digital humanitarianism and crisis management: An empirical study of antecedents and consequences. J. Humanit. Logist. Supply Chain Manag. 2022, 12, 570–593.
  46. Nassani, A.A.; Sinisi, C.; Paunescu, L.; Yousaf, Z.; Haffar, M.; Kabbani, A. Nexus of Innovation Network, Digital Innovation and Frugal Innovation towards Innovation Performance: Investigation of Energy Firms. Sustainability 2022, 14, 4330.
  47. Stroumpoulis, A.; Kopanaki, E. Theoretical Perspectives on Sustainable Supply Chain Management and Digital Transformation: A Literature Review and a Conceptual Framework. Sustainability 2022, 14, 4862.
  48. Bier, T.; Lange, A.; Glock, C.H. Methods for mitigating disruptions in complex supply chain structures: A systematic literature review. Int. J. Prod. Res. 2020, 58, 1835–1856.
  49. Javed, M.A.; Muram, F.U.; Hansson, H.; Punnekkat, S.; Thane, H. Towards dynamic safety assurance for Industry 4.0. J. Syst. Arch. 2021, 114, 101914.
  50. Sarkis, J. Supply chain sustainability: Learning from the COVID-19 pandemic. Int. J. Oper. Prod. Manag. 2020, 41, 63–73.
  51. Liza, S.A.; Chowdhury, N.R.; Paul, S.K.; Morshed, M.; Morshed, S.M.; Bhuiyan, M.T.; Rahim, A. Barriers to achieving sustainability in pharmaceutical supply chains in the post-COVID-19 era. Int. J. Emerg. Mark. online ahead-of-print. 2022.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license; additional terms may apply. By using this site, you agree to the Terms and Conditions and Privacy Policy.
This entry is offline, you can click here to edit this entry!
Video Production Service
Feedback