AI technologies and their impact on supply chain resilience during COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Shivam Gupta ◽  
Rébecca Stekelorum ◽  
Issam Laguir
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Information Processing ◽  
Supply Chains ◽  
Failure Modes ◽  
Stress Test ◽  
Weak Links ◽  
Content Type ◽  
Supply Chain Resilience

PurposeCOVID-19 has pushed many supply chains to re-think and strengthen their resilience and how it can help organisations survive in difficult times. Considering the availability of data and the huge number of supply chains that had their weak links exposed during COVID-19, the objective of the study is to employ artificial intelligence to develop supply chain resilience to withstand extreme disruptions such as COVID-19.Design/methodology/approachWe adopted a qualitative approach for interviewing respondents using a semi-structured interview schedule through the lens of organisational information processing theory. A total of 31 respondents from the supply chain and information systems field shared their views on employing artificial intelligence (AI) for supply chain resilience during COVID-19. We used a process of open, axial and selective coding to extract interrelated themes and proposals that resulted in the establishment of our framework.FindingsAn AI-facilitated supply chain helps systematically develop resilience in its structure and network. Resilient supply chains in dynamic settings and during extreme disruption scenarios are capable of recognising (sensing risks, degree of localisation, failure modes and data trends), analysing (what-if scenarios, realistic customer demand, stress test simulation and constraints), reconfiguring (automation, re-alignment of a network, tracking effort, physical security threats and control) and activating (establishing operating rules, contingency management, managing demand volatility and mitigating supply chain shock) operations quickly.Research limitations/implicationsAs the present research was conducted through semi-structured qualitative interviews to understand the role of AI in supply chain resilience during COVID-19, the respondents may have an inclination towards a specific role of AI due to their limited exposure.Practical implicationsSupply chain managers can utilise data to embed the required degree of resilience in their supply chains by considering the proposed framework elements and phases.Originality/valueThe present research contributes a framework that presents a four-phased, structured and systematic platform considering the required information processing capabilities to recognise, analyse, reconfigure and activate phases to ensure supply chain resilience.

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

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sachin Modgil ◽  
Rohit Kumar Singh ◽  
Claire Hannibal
Keyword(s):  
Artificial Intelligence ◽  
Supply Chain ◽  
Supply Chains ◽  
Dynamic Capabilities ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Rich Data ◽  
Theory Practice Gap ◽  
Last Mile Delivery ◽  
The Impact

PurposeMany supply chains have faced disruption during Covid-19. Artificial intelligence (AI) is one mechanism that can be used to improve supply chain resilience by developing business continuity capabilities. This study examines how firms employ AI and consider the opportunities for AI to enhance supply chain resilience by developing visibility, risk, sourcing and distribution capabilities.Design/methodology/approachThe authors have gathered rich data by conducting semistructured interviews with 35 experts from the e-commerce supply chain. The authors have adopted a systematic approach of coding using open, axial and selective methods to map and identify the themes that represent the critical elements of AI-enabled supply chain resilience.FindingsThe results of the study highlight the emergence of five critical areas where AI can contribute to enhanced supply chain resilience; (1) transparency, (2) ensuring last-mile delivery, (3) offering personalized solutions to both upstream and downstream supply chain stakeholders, (4) minimizing the impact of disruption and (5) facilitating an agile procurement strategy.Research limitations/implicationsThe study offers interesting implications for bridging the theory–practice gap by drawing on contemporary empirical data to demonstrate how enhancing dynamic capabilities via AI technologies further strengthens supply chain resilience. The study also offers suggestions for utilizing the findings and proposes a framework to strengthen supply chain resilience through AI.Originality/valueThe study presents the dynamic capabilities for supply chain resilience through the employment of AI. AI can contribute to readying supply chains to reduce their risk of disruption through enhanced resilience.

The role of big data analytics capabilities in bolstering supply chain resilience and firm performance: a dynamic capability view

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohamad Bahrami ◽  
Sajjad Shokouhyar
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Firm Performance ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture

PurposeBig data analytics capability (BDAC) can affect firm performance in several ways. The purpose of this paper is to understand how BDA capabilities affect firm performance through supply chain resilience in the presence of the risk management culture.Design/methodology/approachThe study adopted a cross-sectional approach to collect survey-based responses to examine the hypotheses. 167 responses were collected and analyzed using partial least squares in SmartPLS3. The respondents were generally senior IT executives with education and experience in data and business analytics.FindingsThe results show that BDA capabilities increase supply chain resilience as a mediator by enhancing innovative capabilities and information quality, ultimately leading to improved firm performance. In addition, the relationship between supply chain resilience and firm performance is influenced by risk management culture as a moderator.Originality/valueThe present study contributes to the relevant literature by demonstrating the mediating role of supply chain resilience between the BDA capabilities relationship and firm performance. In this context, some theoretical and managerial implications are proposed and discussed.

Supply chain resilience

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Case Studies ◽  
Design Methodology ◽  
Reading Time ◽  
Cutting Edge ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Pertinent Information ◽  
Practical Implications

Purpose This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings COVID-19 has had a dramatic and damaging effect on supply chains and distributors. This briefing considers why, and what strategies there may be to cope. Originality/value The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

Intellectual capital and supply chain resilience

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Shujaat Mubarik ◽  
Nick Bontis ◽  
Mobasher Mubarik ◽  
Tarique Mahmood
Keyword(s):  
Supply Chain ◽  
Least Squares ◽  
Partial Least Squares ◽  
Intellectual Capital ◽  
Structural Equation ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Structural Capital ◽  
The Impact

PurposeThe main objective of this study is to test whether firms with a higher level of intellectual capital (IC) perform better in terms of their supply chain resilience compared to those with lower levels of IC. Likewise, the study also examines the impact of IC (characterized by human capital, relational capital and structural capital) on supply chain resilience directly and through supply chain learning.Design/methodology/approachData were collected from the 159 processed-food sector firms using a close-ended questionnaire during the corona virus 2019 (COVID-19) pandemic. Partial least squares structural equation modelling (PLS-SEM), partial least squares multigroup analysis (PLS-MGA) and one-way analysis of variance (ANOVA) were used to test a set of hypotheses emanating from a conceptual model of IC and supply chain resilience.FindingsEmpirical results revealed a significant influence of all dimension of IC on a firm's supply chain learning and supply chain resilience. Likewise, findings also exhibit a momentous role of supply chain learning in reinforcing the impact of IC on supply chain resilience. Cross-firm size comparison reveals that supply chain resilience of firms with a higher level of IC performed significantly better than those with lower levels of IC. Firms with a higher level of structural capital had a highly resilient supply chain.Practical implicationsFindings of the study imply that IC and supply chain learning should be considered as a strategic tool and should be strategically developed for uplifting a supply chain performance of a firm. The development of IC and supply chain learning (SCL) not only improves the supply chain resilience of a firm but also can help to integrate the internal and external knowledge for harnessing supply chain resilience.Originality/valueThis research study was conducted during the COVID-19 pandemic which provides a unique setting to examine resiliency and learning.

The structure of knowledge management in inter-organisational exchanges for resilient supply chains

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Muhammad Umar ◽  
Mark Wilson ◽  
Jeff Heyl
Keyword(s):  
Knowledge Management ◽  
Supply Chain ◽  
Supply Chains ◽  
Knowledge Generation ◽  
Collaborative Culture ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Food Supply Chains ◽  
Study Approach ◽  
Structure Of Knowledge

Purpose This study aims to build on the extant literature of knowledge management (KM) capabilities, notably infrastructure and processes, and examine how these capabilities influence the resilience of supply chains that experience regular natural disasters. Design/methodology/approach A multiple case study approach has been adopted to investigate the role of KM within foods supply chains of two different South Asian regions. This context was selected as these regions are prone to regular natural disruptions and these food supply chains also play a crucial role in the relief process. Findings The data shows that supply chain resilience can be enhanced when supply chain members collaborate to generate, share and use knowledge. These KM processes are greatly facilitated by KM infrastructure capabilities. IT advancements, a cohesive collaborative culture and the presence of strong central hubs firms in the network facilitate knowledge generation, knowledge sharing and knowledge utilisation, thus building supply chain resilience. Given the abductive nature of this research, these findings form the most likely associations, but with a degree of uncertainty. Hence, the authors provide propositions for further detailed research in this important area. Originality/value This study is one of the few, as far as the authors can tell, that seeks to examine the influence of KM on the resilience of supply chains. Further, uncovering the sub-structure of KM in this context adds to this emerging body of literature.

Supply chain resilience for vaccines: review of modeling approaches in the context of the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maureen S. Golan ◽  
Benjamin D. Trump ◽  
Jeffrey C. Cegan ◽  
Igor Linkov
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Securities And Exchange Commission ◽  
Matrix Analysis ◽  
Stress Tests ◽  
Critical Function ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Production And Distribution ◽  
The Face

PurposeDespite rapid success in bringing SARS-CoV-2 vaccines to distribution by multiple pharmaceutical corporations, supply chain failures in production and distribution can plague pandemic recovery. This review analyzes and addresses gaps in modeling supply chain resilience in general and specifically for vaccines in order to guide researchers and practitioners alike to improve critical function of vaccine supply chains in the face of inevitable disruptions.Design/methodology/approachSystematic review of the literature on modeling supply chain resilience from 2007 to 2020 is analyzed in tandem with the vaccine supply chain manufacturing literature. These trends are then used to apply a novel matrix analysis to seven Securities and Exchange Commission (SEC) annual filings of pharmaceutical corporations involved in COVID-19 vaccine manufacture and distribution.FindingsPharmaceutical corporations favor efficiency as they navigate regulatory, economic and other threats to their vaccine supply chains, neglecting resilience – absorption, adaptation and recovery from inevitable and unexpected disruptions. However, explicitly applying resilience analytics to the vaccine supply chain and further leveraging emerging network science tools found in the academic literature, such as artificial intelligence (AI), stress tests and digital twins, will help supply chain managers to better quantify efficiency/resilience tradeoffs across all associated networks/domains and support optimal system performance post disruption.Originality/valueThis is the first review addressing resilience analytics in vaccine supply chains and subsequent extension to operational management through novel matrix analyses of SEC Filings. The authors provide analyses and recommendations that facilitate resilience quantification capabilities for vaccine supply chain managers, regulatory agencies and corporate stakeholders and are especially relevant for pandemic response, including application to the SARS-CoV-2 vaccines.

Understanding the relationships between global supply chain risk and supply chain resilience: the role of mitigating strategies

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Juneho Um ◽  
Neungho Han
Keyword(s):  
Supply Chain ◽  
Global Supply Chain ◽  
Theoretical Development ◽  
Supply Chain Risk ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Supply Chain Risks ◽  
The Impact ◽  
Practical Implications

Purpose This study aims to theoretically hypothesise and empirically explore the relationships amongst global supply chain risks, supply chain resilience and mitigating strategies. Design/methodology/approach The study adopts supply chain resilience as a dynamic capability and resilience capability as a mediating prerequisite in addressing supply chain risk in sourcing, manufacturing and delivery. The moderating role of diverse mitigating strategies is tested to enhance supply chain resilience. Data collected via survey was used for structural equation modelling and additional tests to explore appropriate mitigating strategies for differing risk environments. Findings Achieving better supply chain resilience capability plays an important mediating role between supply chain risks and resilience, while the relationships depend on the performance of seven mitigating strategies. Research limitations/implications The findings contribute to the theoretical development of risk management issues in global supply chains by suggesting the role of supply chain resilience capability. Practical implications The findings offer managerial guidance on how to mitigate the global supply chain risk through the appropriate practice of strategies to strengthen supply chain resilience in an uncertain environment. Originality/value This is the first empirical research examining the impact of mitigating strategies on supply chain resilience. The results provide practical implications for managing uncertain events and offering theoretical insight for future research in supply chain resilience.

Network resilience modelling: a New Zealand forestry supply chain case

2020 ◽  
Vol 31 (2) ◽  
pp. 291-311
Author(s):  
Paul Childerhouse ◽  
Mohammed Al Aqqad ◽  
Quan Zhou ◽  
Carel Bezuidenhout
Keyword(s):  
Linear Programming ◽  
Supply Chain ◽  
Supply Chains ◽  
Discrete Event Simulation ◽  
Discrete Event ◽  
Network Resilience ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Event Simulation ◽  
Export Supply

PurposeThe objective of this research is to model supply chain network resilience for low frequency high impact disruptions. The outputs are aimed at providing policy and practitioner guidance on ways to enhance supply chain resilience.Design/methodology/approachThe research models the resilience of New Zealand's log export logistical network. A two-tier approach is developed; linear programming is used to model the aggregate-level resilience of the nation's ports, then discrete event simulation is used to evaluate operational constraints and validate the capacity of operational flows from forests to ports.FindingsThe synthesis of linear programming and discrete event simulation provide a holistic approach to evaluate supply chain resilience and enhance operational efficiency. Strategically increasing redundancy can be complimented with operational flexibility to enhance network resilience in the long term.Research limitations/implicationsThe two-tier modelling approach has only been applied to New Zealand's log export supply chains, so further applications are needed to insure reliability. The requirement for large quantities of empirical data relating to operational flows limited the simulation component to a single regionPractical implicationsNew Zealand's log export supply chain has low resilience; in most cases the closure of a port significantly constrains export capacity. Strategic selection of location and transportation mode by foresters and log exporters can significantly enhance the resilience of their supply chains.Originality/valueThe use of a two-tiered analytical approach enhances validity as each level's limitations and assumptions are addressed when combined with one another. Prior predominantly theoretical research in the field is validated by the empirical investigation of supply chain resilience.

Doing good across organizational boundaries

2018 ◽  
Vol 38 (12) ◽  
pp. 2389-2412 ◽  
Author(s):  
Hugo K.S. Lam
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Financial Risk ◽  
Theoretical Perspective ◽  
Secondary Data ◽  
Content Type ◽  
Signalling Theory ◽  
The Impact ◽  
Moderating Role

Purpose The purpose of this paper is to theoretically hypothesise and empirically test the impact of sustainable supply chain practices (SSCPs) on firms’ financial risk. Design/methodology/approach This research adopts signalling theory to explain the signalling role of SSCPs and the moderating role of the signalling environment in terms of supply chain characteristics. It collects and combines longitudinal secondary data from multiple sources to test the direct impact of SSCPs on firms’ financial risk and the moderating role of supply chain complexity and efficiency. It conducts various additional tests to check the robustness of the findings and to account for alternative explanations. Findings This research shows that SSCPs help firms reduce financial risk but do not affect their returns. Moreover, the risk reduction of SSCPs is greater for firms with more complex and efficient supply chains. The findings are robust to alternative variable measurements and analysing strategies. Research limitations/implications This research reveals the role of SSCPs in reducing financial risk, urging researchers to pay more attention to the financial risk implications of supply chain practices in general and SSCPs in particular. Practical implications This research encourages firms to engage in SSCPs to reduce financial risk and enables them to assess the urgency of their SSCPs investments in view of the complexity and efficiency of their supply chains. Originality/value This is the first research examining the impact of SSCPs on financial risk, based on longitudinal secondary data and signalling theory. The empirical evidence documented and the theoretical perspective adopted offer important implications for future practice and research on SSCPs.

Antecedents and consequences of supply chain resilience and reconfiguration: an empirical study in an emerging economy

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maryam Al Naimi ◽  
Mohd Nishat Faisal ◽  
Rana Sobh ◽  
S.M. Fatah Uddin
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Structural Equation ◽  
Equation Modeling ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Culture ◽  
Major Disruption ◽  
Antecedents And Consequences ◽  
The Impact

PurposeThe purpose of this paper is twofold: to investigate the antecedents of resilience and to highlight the importance of resilience in achieving reconfiguration in supply chains.Design/methodology/approachThis paper draws on literature on supply chain resilience and collects data from 253 companies in Qatar to understand the influence of the antecedents of supply chain resilience and the impact of resilience on reconfiguration using partial least squares structural equation modeling.FindingsThe findings show that antecedents like risk management culture, agility and collaboration positively affect the supply chain resilience. Further, the study establishes that companies can leverage their supply chain resilience to reconfigure supply chain in case of disruptions.Practical implicationsThis study is important for supply chain managers in Qatar, as the country faced major disruption of supply chains in wake of the blockade imposed by its neighbors with which it had the only land route and maximum trade. The findings from this study should aid mangers in developing resilient supply chains.Originality/valueThis paper highlights the role of supply chain resilience in achieving reconfiguration. Further, novelty of the work reported in this paper lies in its context where supply chains recently faced actual disruptions.

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