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Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

Postal Subscription Code 80-905

Front. Eng    2023, Vol. 10 Issue (2) : 360-366    https://doi.org/10.1007/s42524-023-0257-1
COMMENTS
Disruptive technologies for advancing supply chain resilience
Weihua LIU1(), Yang HE1(), Jingxin DONG2, Yuenan CAO1
1. College of Management and Economics, Tianjin University, Tianjin 300072, China
2. Business School, Newcastle University, Newcastle upon Tyne, NE1 4SE, UK
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Abstract

Disruptive technologies provide a new paradigm for supply chain risk management and bring opportunities and challenges for the improvement of supply chain resilience (SCRes). This study summarizes the application cases of some disruptive technologies in the SCRes and analyzes the benefits and damages brought by disruptive technologies to the SCRes. The results show that disruptive technologies can provide the supply chain with flexibility, visibility, agility, and other capabilities at various stages of risk management. Hence, technology advancements greatly increase the level of the SCRes. Although disruptive technologies undermine the construction of SCRes, these damages can be eliminated through technology iteration or other disruptive technologies. Furthermore, disruptive technologies will provide better stability for the SCRes. The study also makes several suggestions for the use of disruptive technologies in the construction of the SCRes.

Keywords supply chain resilience      disruptive technology      supply chain risk     
Corresponding Author(s): Weihua LIU,Yang HE   
Just Accepted Date: 19 April 2023   Online First Date: 10 May 2023    Issue Date: 29 May 2023
 Cite this article:   
Weihua LIU,Yang HE,Jingxin DONG, et al. Disruptive technologies for advancing supply chain resilience[J]. Front. Eng, 2023, 10(2): 360-366.
 URL:  
https://academic.hep.com.cn/fem/EN/10.1007/s42524-023-0257-1
https://academic.hep.com.cn/fem/EN/Y2023/V10/I2/360
TechnologyCountryIndustryMeasureReference
IoTUS and South KoreaMachine productionReal-time monitoring of informationHiggins (2015)
GermanyCar manufacturingReal-time information captureSarac et al. (2010)
USComputer softwareDistributed computingGupta and Jones (2014)
AIUK and NetherlandsDaily necessitiesMarket change forecastCFLP (2015)
UKGovernment agencyResource overrun alertMorabito (2015)
ChinaWholesale tradeIntelligent robotic deliveryYi et al. (2022)
BlockchainUSRetailInformation tracking and tracingKamath (2018)
USAgricultureHistorical information remains true and unchangedRogerson and Parry (2020)
ChinaShippingSmart contractsVerhoeven et al. (2018)
Tab.1  Some cases for disruptive technologies in the SCRes
Fig.1  Characteristics of disruptive technologies in the SCRes.
1 T K Agrawal, V Kumar, R Pal, L Wang, Y Chen, (2021). Blockchain-based framework for supply chain traceability: A case example of textile and clothing industry. Computers & Industrial Engineering, 154( 1): 107130
https://doi.org/10.1016/j.cie.2021.107130
2 V Babich, G Hilary, (2019). Blockchain and other distributed ledger technologies in operations. Foundations and Trends® in Technology, Information and Operations Management, 12( 2): 152–172
https://doi.org/10.1561/0200000084
3 G Baryannis, S Validi, S Dani, G Antoniou, (2019). Supply chain risk management and artificial intelligence: State of the art and future research directions. International Journal of Production Research, 57( 7): 2179–2202
https://doi.org/10.1080/00207543.2018.1530476
4 M Ben-Daya, E Hassini, Z Bahroun, (2019). Internet of Things and supply chain management: A literature review. International Journal of Production Research, 57( 15): 4719–4742
https://doi.org/10.1080/00207543.2017.1402140
5 D Burgos, D Ivanov, (2021). Food retail supply chain resilience and the COVID-19 pandemic: A digital twin-based impact analysis and improvement directions. Transportation Research Part E: Logistics and Transportation Review, 152( 1): 102412
https://doi.org/10.1016/j.tre.2021.102412
6 R Burns, J Thatcher, (2015). What’s so big about Big Data? Finding the spaces and perils of Big Data. GeoJournal, 80( 4): 445–448
https://doi.org/10.1007/s10708-014-9600-8
7 X Chen, C He, Y Chen, Z Xie, (2023). Internet of Things (IoT): Blockchain-enabled pharmaceutical supply chain resilience in the post-pandemic era. Frontiers of Engineering Management, 10( 1): 82–95
https://doi.org/10.1007/s42524-022-0233-1
8 F Chiacchio, D D’Urso, L M Oliveri, A Spitaleri, C Spampinato, D Giordano, (2022). A non-fungible token solution for the track and trace of pharmaceutical supply chain. Applied Sciences, 12( 8): 4019
https://doi.org/10.3390/app12084019
9 Federation of Logistics Purchasing (CFLP) China (2015). Supply chain case: The inside story of Unilever’s supply chain. Online Article (in Chinese)
10 T M Choi, (2020). Supply chain financing using blockchain: Impacts on supply chains selling fashionable products. Annals of Operations Research, 25( 4): 1–23
https://doi.org/10.1007/s10479-020-03615-7
11 M M H Chowdhury, M Quaddus, (2016). Supply chain readiness, response and recovery for resilience. Supply Chain Management, 21( 6): 709–731
https://doi.org/10.1108/SCM-12-2015-0463
12 M Christopher, H Peck, (2004). Building the resilient supply chain. International Journal of Logistics Management, 15( 2): 1–14
https://doi.org/10.1108/09574090410700275
13 Y CuiH IdotaM Ota (2019). Improving supply chain resilience with implementation of new system architecture. In: IEEE Social Implications of Technology and Information Management. Matsuyama: IEEE, 1–6
14 T H Davenport, R Ronanki, (2018). Artificial intelligence for the real world. Harvard Business Review, 96( 1): 108–116
15 J El Baz, S Ruel, (2021). Can supply chain risk management practices mitigate the disruption impacts on supply chains’ resilience and robustness? Evidence from an empirical survey in a COVID-19 outbreak era. International Journal of Production Economics, 233( 1): 107972
https://doi.org/10.1016/j.ijpe.2020.107972
16 M Fakhimi, I Miremadi, (2022). The impact of technological and social capabilities on innovation performance: A technological catch-up perspective. Technology in Society, 68( 1): 101890
https://doi.org/10.1016/j.techsoc.2022.101890
17 A Fernández, Río S del, V López, A Bawakid, Jesus M J del, J M Benítez, F Herrera, (2014). Big data with cloud computing: An insight on the computing environment, MapReduce and programming frameworks. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 4( 5): 380–409
https://doi.org/10.1002/widm.1134
18 D Gao, Z Xu, Y Z Ruan, H Lu, (2017). From a systematic literature review to integrated definition for sustainable supply chain innovation (SSCI). Journal of Cleaner Production, 142( 1): 1518–1538
https://doi.org/10.1016/j.jclepro.2016.11.153
19 Y Gao, Z Feng, S Zhang, (2021). Managing supply chain resilience in the era of VUCA. Frontiers of Engineering Management, 8( 3): 465–470
https://doi.org/10.1007/s42524-021-0164-2
20 S Gupta, E C Jones, (2014). Optimizing supply chain distribution using cloud based autonomous information. International Journal of Supply Chain Management, 3( 4): 79–90
21 S Higgins (2015). IBM reveals proof of concept for blockchain-powered Internet of Things. Online Report
22 W Ho, T Zheng, H Yildiz, S Talluri, (2015). Supply chain risk management: A literature review. International Journal of Production Research, 53( 16): 5031–5069
https://doi.org/10.1080/00207543.2015.1030467
23 E HollnagelD D WoodsN Leveson (2006). Resilience Engineering: Concepts and Precepts. London: CRC Press
24 D Ivanov, A Dolgui, B Sokolov, (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( 3): 829–846
https://doi.org/10.1080/00207543.2018.1488086
25 D Ivanov, A Dolgui, B Sokolov, M Ivanova, (2017). Literature review on disruption recovery in the supply chain. International Journal of Production Research, 55( 20): 6158–6174
https://doi.org/10.1080/00207543.2017.1330572
26 R Kamath, (2018). Food traceability on blockchain: Walmart’s pork and mango pilots with IBM. The Journal of the British Blockchain Association, 1( 1): 47–53
https://doi.org/10.31585/jbba-1-1-(10)2018
27 S H Khajavi, J Partanen, J Holmström, (2014). Additive manufacturing in the spare parts supply chain. Computers in Industry, 65( 1): 50–63
https://doi.org/10.1016/j.compind.2013.07.008
28 J S Kim, N Shin, (2019). The impact of blockchain technology application on supply chain partnership and performance. Sustainability, 11( 21): 6181
https://doi.org/10.3390/su11216181
29 W Liu, Y Liang, X Bao, J Qin, M K Lim, (2022). China’s logistics development trends in the post COVID-19 era. International Journal of Logistics Research and Applications, 25( 6): 965–976
https://doi.org/10.1080/13675567.2020.1837760
30 W Liu, X Liu, X Shi, J Hou, V Shi, J Dong, (2023). Collaborative adoption of blockchain technology: A supply chain contract perspective. Frontiers of Engineering Management, 10( 1): 121–142
https://doi.org/10.1007/s42524-022-0239-8
31 V Mani, C Delgado, B T Hazen, P Patel, (2017). Mitigating supply chain risk via sustainability using big data analytics: Evidence from the manufacturing supply chain. Sustainability, 9( 4): 608
https://doi.org/10.3390/su9040608
32 N N Misra, Y Dixit, A Al-Mallahi, M S Bhullar, R Upadhyay, A Martynenko, (2022). IoT big data and artificial intelligence in agriculture and food industry. IEEE Internet of Things Journal, 9( 9): 6305–6324
https://doi.org/10.1109/JIOT.2020.2998584
33 V (2015) Morabito. Managing change for big data driven innovation. In: Morabito V, ed. Big Data and Analytics: Strategic and Organizational Impacts. Cham: Springer, 125–153
34 I C Ng, S Y Wakenshaw, (2017). The Internet-of-Things: Review and research directions. International Journal of Research in Marketing, 34( 1): 3–21
https://doi.org/10.1016/j.ijresmar.2016.11.003
35 Y Ning, L Li, S X Xu, S Yang, (2023). How do digital technologies improve supply chain resilience in the COVID-19 pandemic? Evidence from Chinese manufacturing firms. Frontiers of Engineering Management, 10( 1): 39–50
https://doi.org/10.1007/s42524-022-0230-4
36 T Panichayakorn, K Jermsittiparsert, (2019). Mobilizing organizational performance through robotic and artificial intelligence awareness in mediating role of supply chain agility. International Journal of Supply Chain Management, 8( 5): 757–768
37 D Pavithran, K Shaalan, J N Al-Karaki, A Gawanmeh, (2020). Towards building a blockchain framework for IoT. Cluster Computing, 23( 3): 2089–2103
https://doi.org/10.1007/s10586-020-03059-5
38 S Ponis, E Koronis, (2012). Supply chain resilience? Definition of concept and its formative elements. Journal of Applied Business Research, 28( 5): 921–935
https://doi.org/10.19030/jabr.v28i5.7234
39 M Pournader, H Ghaderi, A Hassanzadegan, B Fahimnia, (2021). Artificial intelligence applications in supply chain management. International Journal of Production Economics, 241( 1): 108250
https://doi.org/10.1016/j.ijpe.2021.108250
40 E Raguseo, (2018). Big data technologies: An empirical investigation on their adoption, benefits and risks for companies. International Journal of Information Management, 38( 1): 187–195
https://doi.org/10.1016/j.ijinfomgt.2017.07.008
41 S K Reddy, W Reinartz, (2017). Digital transformation and value creation: Sea change ahead. GfK Marketing Intelligence Review, 9( 1): 10–17
https://doi.org/10.1515/gfkmir-2017-0002
42 J B Rice Jr, F Caniato, (2003). Building a secure and resilient supply network. Supply Chain Management Review, 7( 5): 22–30
43 M Rogerson, G C Parry, (2020). Blockchain: Case studies in food supply chain visibility. Supply Chain Management, 25( 5): 601–614
https://doi.org/10.1108/SCM-08-2019-0300
44 J R Roland Ortt, D J Langley, N Pals, (2007). Exploring the market for breakthrough technologies. Technological Forecasting and Social Change, 74( 9): 1788–1804
https://doi.org/10.1016/j.techfore.2007.05.009
45 A Sarac, N Absi, S Dauzère-Pérès, (2010). A literature review on the impact of RFID technologies on supply chain management. International Journal of Production Economics, 128( 1): 77–95
https://doi.org/10.1016/j.ijpe.2010.07.039
46 P Sharma, A Joshi, (2020). Challenges of using big data for humanitarian relief: Lessons from literature. Journal of Humanitarian Logistics and Supply Chain Management, 10( 4): 423–446
https://doi.org/10.1108/JHLSCM-05-2018-0031
47 J Shi, J Chen, L Xu, Z Di, Q Qu, (2023). Improving the resilience of maritime supply chains: The integration of ports and inland transporters in duopoly markets. Frontiers of Engineering Management, 10( 1): 51–66
https://doi.org/10.1007/s42524-022-0231-3
48 X ShiW LiuJ Zhang (2021). Present and future trends of supply chain management in the presence of COVID-19: A structured literature review. International Journal of Logistics Research and Applications, in press, doi:
https://doi.org/10.1080/13675567.2021.1988909
49 A Theorin, K Bengtsson, J Provost, M Lieder, C Johnsson, T Lundholm, B Lennartson, (2017). An event-driven manufacturing information system architecture for Industry 4.0. International Journal of Production Research, 55( 5): 1297–1311
https://doi.org/10.1080/00207543.2016.1201604
50 Y P Tsang, K L Choy, C H Wu, G T Ho, C H Lam, P S Koo, (2018). An Internet of Things (IoT)-based risk monitoring system for managing cold supply chain risk. Industrial Management & Data Systems, 118( 7): 1432–1462
https://doi.org/10.1108/IMDS-09-2017-0384
51 B R Tukamuhabwa, M Stevenson, J Busby, M Zorzini, (2015). Supply chain resilience: Definition review and theoretical foundations for further study. International Journal of Production Research, 53( 18): 5592–5623
https://doi.org/10.1080/00207543.2015.1037934
52 J Um, N Han, (2021). Understanding the relationships between global supply chain risk and supply chain resilience: The role of mitigating strategies. Supply Chain Management, 26( 2): 240–255
https://doi.org/10.1108/SCM-06-2020-0248
53 P Verhoeven, F Sinn, T T Herden, (2018). Examples from blockchain implementations in logistics and supply chain management: Exploring the mindful use of a new technology. Logistics, 2( 3): 20
https://doi.org/10.3390/logistics2030020
54 W Wei, W Liu, O Tang, C Dong, Y Liang, (2023). CSR investment for a two-sided platform: Network externality and risk aversion. European Journal of Operational Research, 307( 2): 694–712
https://doi.org/10.1016/j.ejor.2022.08.048
55 P E Weisenfeld, (2011). Successes and challenges of the Haiti earthquake response: The experience of USAID. Emory International Law Review, 25( 3): 1097–1120
56 Q Xia, E B Sifah, K O Asamoah, J Gao, X Du, M Guizani, (2017). MeDShare: Trust-less medical data sharing among cloud service providers via blockchain. IEEE Access, 5: 14757–14767
https://doi.org/10.1109/ACCESS.2017.2730843
57 J Yi, H Zhang, J Mao, Y Chen, H Zhong, Y Wang, (2022). Review on the COVID-19 pandemic prevention and control system based on AI. Engineering Applications of Artificial Intelligence, 114: 105184
https://doi.org/10.1016/j.engappai.2022.105184
58 R Zhao, Y Liu, N Zhang, T Huang, (2017). An optimization model for green supply chain management by using a big data analytic approach. Journal of Cleaner Production, 142( 1): 1085–1097
https://doi.org/10.1016/j.jclepro.2016.03.006
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