scholarly journals A resilience model for cold chain logistics of perishable products

2018 ◽  
Vol 29 (3) ◽  
pp. 922-941 ◽  
Author(s):  
Imran Ali ◽  
Sev Nagalingam ◽  
Bruce Gurd
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Negative Relationship ◽  
Cold Chain ◽  
Integrative Approach ◽  
Theoretical Frameworks ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Perishable Product ◽  
Definition Of

Purpose Most of the extant literature on resilience builds on normative, conceptual or silo approaches, thereby lacking an integrative approach to cold chain logistics risks (CCLRs) and resilience. The purpose of this paper is to bridge the current research gap by developing a model, based on broad empirical evidence, of the interplay between CCLRs, resilience and firm performance (FP) in perishable product supply chains (PPSCs). Design/methodology/approach A mixed method approach is used with qualitative data from interviews and quantitative data from a survey across the supply chain. The analysis is framed by contingency theory and resource-based theory. Findings Four significant sources of CCLRs and six resources used to build resilience are identified. Then, supply chain resilience (SCR) as a moderator of the negative relationship between CCLRs and FP is corroborated. Practical implications The findings will help improve managerial understandings of critical sources of risks in cold chain logistics and resources indispensable to build resilience. The scope of the research is cold chain logistics for PPSCs, which has relevance to other cold supply chains as well. Originality/value While some theoretical frameworks suggest resilience being a moderator in the negative relationship between cold chain risks and a firm’s performance, this study empirically tests this relationship using the survey across the entire supply chain. A new empirically and theoretically driven definition of SCR is also developed.

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.

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.

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.

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.

Realising supply chain resilience: an exploratory study of Irish firms' priorities in the wake of Brexit

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Maurice Brady
Keyword(s):  
Supply Chain ◽  
Exploratory Study ◽  
Survey Method ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Phase Cycle ◽  
Successful Execution ◽  
Wide Definition ◽  
Definition Of ◽  
Practical Implications

PurposeThe purpose of this research is to validate an industry-wide definition of supply chain resilience (SCRES) within the Irish supply chain sector and measure the key elements of SCRES and their relative importance for Irish firms in light of Brexit.Design/methodology/approachSurvey method is used in this research. Data were collected from supply chain managers in Irish firms. Findings were analysed in accordance with industry sector and exposure to Brexit.FindingsThe results from the respondents confirm a willingness to define and utilise SCRES under a four-phase cycle; ready, respond, recover and grow. Focus on SCRES enablers shifts in accordance with cycle position. Understanding cycle position is paramount for successful execution of a SCRES strategy. Findings can be used as a basis for the development, implementation and management of a SCRES strategy.Research limitations/implicationsResearch was conducted at one specific point during Brexit negotiations. Sector specific and longitudinal studies are required to build upon this exploratory study.Practical implicationsSupply chain managers must ensure that phase position and enabler implementation are aligned to maximise the investment in a SCRES strategy. As a disruption event and its associated response evolve, management must demonstrate an ability to deploy and focus efforts on different SCRES enablers throughout the four-phase cycle.Originality/valueThis is the first research focussing on an industry-wide accepted definition of SCRES and its key enablers within Irish supply chains.

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.

Analysis of supply chain resilience barriers in Indian automotive company using total interpretive structural modelling

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nishtha Agarwal ◽  
Nitin Seth
Keyword(s):  
Supply Chain ◽  
Second Phase ◽  
Structural Modelling ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Interpretive Structural Modelling ◽  
Micmac Analysis ◽  
Root Barrier ◽  
Definition Of ◽  
Total Interpretive Structural Modelling

PurposeThe study tries to identify the barriers influencing supply chain resilience and examine the inter-relationships between them. These relationships are built on the basis of how one barrier drives or is driven by the changes in another barriers.Design/methodology/approachIn the first phase, literature review and with due discussion with experts, the barriers have been identified and shortlisted for an Indian automotive case company. In the second phase, total interpretive structural modelling (TISM) has been applied to examine inter-relationships between the barriers for an Indian automobile case company. Matrice d'impacts croisés multiplication appliquée á un classment (MICMAC) analysis has also been performed to analyse the driving and dependence power of the barriers.FindingsIn total, 11 barriers are identified from the first phase of the study. In the second phase, the TISM digraph is created which qualitatively explains the reason behind how one barrier leads to another. MICMAC analysis classifies these variables in four clusters namely autonomous, linkage, dependent and independent. These clusters characterise the barriers based on their driving and dependent power which helps managers in strategically tackling them while taking understanding from the TISM digraph.Research limitations/implicationsThree research implications can be made from the study. First, a comprehensive definition of supply chain which helps in understanding of resilience based on disruption phases and recovery. Second, 11 barriers are identified which hinder resilience in automotive sector. Their relationships are modelled using TISM which also gives why a particular relationship exists. Last, MICMAC analysis classifies barriers based on how high or low the driving and dependence power exists.Practical implicationsThe study offers significant implications for supply chain managers helping them in building resilience by identifying barriers and reducing their effect. Barriers are identified for case company which might help managers to tackle them during disruptions. The final TISM digraph depicts the “why” between the inter-relationships between the barriers to resilient supply chains. TISM shows that non-commitment of top management is the major root barrier which has been causing the other problems. MICMAC analysis is also performed along with discussion as to how autonomous, linkage, dependent and independent barriers can be tackled to build resilience.Originality/valueTISM is considered as an effective methodology for conceptual framework development as it also explains “why” between the relationships besides explaining the “what” as against ISM. Identification and understanding of barriers and their interrelationship will help supply chain managers to analyse the influence and inter-dependence of barriers on the resilience of the supply chain. Such understanding will help in mitigating/averting these barriers hence improving the resilience capability. It also adds to the knowledge base in the area of supply chain resilience where several authors have pointed the lack of research.

Supply chain resilience during pandemic disruption: Evidence from healthcare

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Barbara Scala ◽  
Claire Frances Lindsay
Keyword(s):  
Supply Chain ◽  
Public Sector ◽  
Supply Chains ◽  
Structured Interviews ◽  
Collaborative Relationships ◽  
Content Type ◽  
Supply Chain Resilience ◽  
The Public ◽  
Pandemic Response

Purpose This paper aims to explore how resilience is evident in healthcare supply chains in the public sector when faced with pandemic disruption and to identify any learnings to inform recovery and future-readiness phases. Design/methodology/approach An exploratory case study was conducted, consisting of seven semi-structured interviews with public sector supply chain actors in the healthcare personal protective equipment supply chain. The data included document analysis. Findings Key findings show how specific resilience strategies such as agility, collaboration, flexibility and redundancy, contributed to supply chain resilience during the COVID-19 pandemic response. Collaboration is identified as a key mechanism for resilience with public sector networks viewed as facilitating this. Established collaborative relationships with suppliers pre-pandemic did not support increased visibility of tiers within the supply chain. Originality/value This is one of the first papers to provide in-depth resilience insights through an example of healthcare supply chains during the COVID-19 pandemic.

How big data analytics can help manufacturing companies strengthen supply chain resilience in the context of the COVID-19 pandemic

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Surajit Bag ◽  
Pavitra Dhamija ◽  
Sunil Luthra ◽  
Donald Huisingh
Keyword(s):  
Risk Management ◽  
Big Data ◽  
Supply Chain ◽  
Supply Chains ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Hypothetical Model ◽  
Content Type ◽  
Supply Chain Resilience ◽  
Management Capabilities

PurposeIn this paper, the authors emphasize that COVID-19 pandemic is a serious pandemic as it continues to cause deaths and long-term health effects, followed by the most prolonged crisis in the 21st century and has disrupted supply chains globally. This study questions “can technological inputs such as big data analytics help to restore strength and resilience to supply chains post COVID-19 pandemic?”; toward which authors identified risks associated with purchasing and supply chain management by using a hypothetical model to achieve supply chain resilience through big data analytics.Design/methodology/approachThe hypothetical model is tested by using the partial least squares structural equation modeling (PLS-SEM) technique on the primary data collected from the manufacturing industries.FindingsIt is found that big data analytics tools can be used to help to restore and to increase resilience to supply chains. Internal risk management capabilities were developed during the COVID-19 pandemic that increased the company's external risk management capabilities.Practical implicationsThe findings provide valuable insights in ways to achieve improved competitive advantage and to build internal and external capabilities and competencies for developing more resilient and viable supply chains.Originality/valueTo the best of authors' knowledge, the model is unique and this work advances literature on supply chain resilience.

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