Artificial intelligence for supply chain resilience: learning from Covid-19

Modgil, Sachin; Singh, Rohit; Hannibal, Claire

doi:10.1108/ijlm-02-2021-0094

Cited by 241 publications

(160 citation statements)

References 83 publications

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“…Counterfeit drugs can appear anywhere in the PSC, where these medications are usually duplicated and sold in the underground economy. The rate of counterfeit drug production has increased due to the disruption that COVID-19 has caused to all supply chains, a lack of business resilience, and the rapid development of technologies [ 23 ]. The existence of counterfeit drugs in the legitimate PSC violates the trademark and intellectual property rights of the manufacturers of the original brands and leads to a loss of sales.…”

Section: Pharmaceutical Supply Chainsmentioning

confidence: 99%

Critical Success Factors and Traceability Technologies for Establishing a Safe Pharmaceutical Supply Chain

Haji

Kerbache

Sheriff

et al. 2021

MPs

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Drug counterfeits have been an international issue for almost two decades, and the latest statistics show that fake medications will continue to penetrate legitimate pharmaceutical supply chains (PSCs). Therefore, identifying the issues faced by PSCs is essential to combat the counterfeit drug problem, which will require the implementation of technologies in various phases of the PSC to gain better visibility. In this regard, a literature review was conducted to fulfill the following objectives: (i) review the application of traceability technologies in various PSC phases to detect counterfeits; (ii) analyze the various barriers affecting the establishment of a safe PSC and the critical success factors used to overcome those barriers; and (iii) develop a conceptual framework and guidelines to demonstrate the influence of traceability technologies and success factors on overcoming the various barriers in different phases of the PSC. The major finding of this review was that traceability technologies and the critical success factors have a significant influence on overcoming the barriers to establishing a safe PSC.

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Section: Pharmaceutical Supply Chainsmentioning

confidence: 99%

Critical Success Factors and Traceability Technologies for Establishing a Safe Pharmaceutical Supply Chain

Haji

Kerbache

Sheriff

et al. 2021

MPs

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“…This is in line with the finding that the role of Industry 4.0 tools largely augment instead of automate jobs (WEF, 2018), the role of RPA is equally found to not necessarily be to automate humans away (Viale and Zouari, 2020). Rather, robots can be assigned to do the regular process and, thereby, human tasks can be more strategic and tactical (Modgil et al. , 2021).…”

Section: Background From Literaturementioning

confidence: 99%

Robotic process automation in Maersk procurement–applicability of action principles and research opportunities

Hoek

Larsen

Lacity

2022

IJPDLM

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PurposeThe authors share a real-world case study of a multiple-year adoption process of robotic process automation (RPA) in procurement to add to the limited empirical research base on RPA in supply chain management. The Maersk case offers hard evidence of the value of RPA that can be used as a benchmark for decision-making in companies and as a basis for further research in key areas such as change management and behavioral aspects as well as return on investment on RPA and the need for RPA capability development.Design/methodology/approachTogether with the co-author from Maersk, the authors cover a multiple year RPA program in procurements, to capture lessons learned and develop research questions for the future. The authors consider 39 generic action principles for RPA adoption in a specific procurement context.FindingsThe authors find RPA for procurement to be an enabler of strategic progress and of advancing the concept of triple values (enterprise, customer and employee) in a supply chain setting. The authors offer RPA adoption scoping guidance and show how, with growth and maturity of the program, conditions such as predictability of volume become less relevant as a scoping criterium. The authors also find that RPA augments work rather than replace staff. Maersk utilizes staff time freed up by automation to focus employees on more strategic priorities. The authors consider 39 generic action principles for RPA adoption in a procurement-specific context and develop additional action principles based upon the Maersk case.Originality/valueThe authors study both a unique and rich case to complement limited empirical research on RPA in procurement and supply chain management and the limited research into RPA past early stage adoptions. The authors address Hofmann et al.'s (2019) questions about the change management involved in RPA and consider generic RPA action principles from literature in this specific procurement setting. The authors extend those action principles and develop a rich set of research opportunities.

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“…They pointed out that the research on the potential of predictive and learning AI techniques is at the nascent stage. AI can enhance SC resilience by improving transparency through continuous monitoring, minimizing the impact of sudden disruptions (Modgil et al, 2021). In this view, an AI-MCDM integrated decision-making framework was proposed to address the most significant techniques for enhancing SC resilience (Belhadi et al, 2021).…”

Section: Text-mining In Scrmmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Supply chain risk identification: a real-time data-mining approach

Ganesh

Kalpana

2022

IMDS

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PurposeThe global pandemic COVID-19 unveils transforming the supply chain (SC) to be more resilient against unprecedented events. Identifying and assessing these risk factors is the most significant phase in supply chain risk management (SCRM). The earlier risk quantification methods make timely decision-making more complex due to their inability to provide early warning. The paper aims to propose a model for analyzing the social media data to understand the potential SC risk factors in real-time.Design/methodology/approachIn this paper, the potential of text-mining, one of the most popular Artificial Intelligence (AI)-based data analytics approaches for extracting information from social media is exploited. The model retrieves the information using Twitter streaming API from online SC forums.FindingsThe potential risk factors that disrupt SC performance are obtained from the recent data by text-mining analyses. The outcomes carry valuable insights about some contemporary SC issues due to the pandemic during the year 2021. The most frequent risk factors using rule mining techniques are also analyzed.Originality/valueThis study presents the significant role of Twitter in real-time risk identification from online SC platforms like “Supply Chain Dive”, “Supply Chain Brain” and “Supply Chain Digest”. The results indicate the significant role of data analytics in achieving accurate decision-making. Future research will extend to represent a digital twin for identifying potential risks through social media analytics, assessing risk propagation and obtaining mitigation strategies.

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Artificial intelligence for supply chain resilience: learning from Covid-19

Cited by 241 publications

References 83 publications

Critical Success Factors and Traceability Technologies for Establishing a Safe Pharmaceutical Supply Chain

Critical Success Factors and Traceability Technologies for Establishing a Safe Pharmaceutical Supply Chain

Robotic process automation in Maersk procurement–applicability of action principles and research opportunities

Supply chain risk identification: a real-time data-mining approach

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