Resilience and Agility: The Crucial Properties of Humanitarian Supply Chain

Dubey, Rameshwar

doi:10.1007/978-3-030-14302-2_14

Cited by 6 publications

(4 citation statements)

References 66 publications

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“…Drawing from a resource-based view theory and extant literature bundling of tangible resources (basic resources, data, technology), human resources (technical skills and management skills), intangible resources (data-driven culture and culture of continuous learning within an organization) lead to higher order capability in BDPA (Gupta and George, 2016). Data analytics capability is itself a core component to drive and improve the supply chain resilience and gain competitive advantage (Dubey, Gunasekaran, Childe, Fosso Wamba, Roubaud and Foropon, 2019; Dubey, 2019). Moreover, BDPA has a significant effect on visibility and coordination (Dubey, Luo, Gunasekaran, Akter, Hazen and Douglas, 2018).…”

Section: Model and Discussionmentioning

confidence: 99%

“…The focus of supply chain shifts from agility to leanness as we transition from a response phase to a reconstruction phase in DM. Dubey (2019) argues that agility is relevant during a preparation phase whereas resilience is required during a post-disaster stage of HSC. Cortés et al (2019) emphasize the significance of collaboration and project management to improve humanitarian operations.…”

Section: Literature Reviewmentioning

confidence: 99%

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Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain

Jeble

Kumari

Venkatesh³

et al. 2019

BIJ

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Purpose The purpose of this paper is threefold: first, to investigate the role of big data and predictive analytics (BDPA) and social capital on the performance of humanitarian supply chains (HSCs); second, to explore the different performance measurement frameworks and develop a conceptual model for an HSC context that can be used by humanitarian organizations; and third, to provide insights for future research direction. Design/methodology/approach After a detailed review of relevant literature, grounded in resource-based view and social capital theory, the paper proposes a conceptual model that depicts the influence of BDPA and social capital on the performance of an HSC. Findings The study deliberates that BDPA as a capability improves the effectiveness of humanitarian missions to achieve its goals. It uncovers the fact that social capital binds people, organization or a country to form a network and has a critical role in the form of monetary or non-monetary support in disaster management. Further, it argues that social capital combined with BDPA capability can result in a better HSC performance. Research limitations/implications The proposed model integrating BDPA and social capital for HSC performance is conceptual and it needs to be empirically validated. Practical implications Organizations and practitioners may use this framework by mobilizing social capital, BDPA to enhance their abilities to help victims of calamities. Social implications Findings from study can help improve coordination among different stakeholders in HSC, effectiveness of humanitarian operations, which means lives saved and faster reconstruction process after disaster. Second, by implementing performance measurements framework recommended by study, donors and other stakeholders will get much desired transparency at each stage of HSCs. Originality/value The findings contribute to the missing link of social capital and BDPA to the existing performance of HSC literature, finally leading to a better HSC performance.

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Section: Model and Discussionmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain

Jeble

Kumari

Venkatesh³

et al. 2019

BIJ

View full text Add to dashboard Cite

show abstract

“…The model's output offers a worldwide resource deployment strategy for the client zones, distribution centres, and manufacturers. Dubey et al implemented a nonlinear multiobjective mathematical model for supplychain networks [24]. Ivanov [25] suggested entropy-based analysis, quantification, and maximum entropy to solve the linear function issue.…”

Section: Scn Considering Materials Flowmentioning

confidence: 99%

Modelling a Logistics and Financial Supply Chain Network during the COVID-19 Era

Abbasi,

Vlachos,

Samadzadeh

et al. 2024

Logistics

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Background: Supply chain networks (SCNs) have been interrupted by the COVID-19 pandemic, leaving them open to financial losses. SCs have been impacted by the pandemic, necessitating the adoption of sustainable practices and dynamic capacities to ensure resilience and performance. Several studies have focused on this subject, offering insights into the importance of sustainable supply-chain management, corporate governance, big data management activities, and digital technology in minimising the consequences of the pandemic and fostering sustainability. Methods: This study suggests an analytical framework for assessing environmentally friendly procedures and dynamic capacities to assure performance in a disruptive environment. Results: The following are some of the important details and contributions in this article: (1) developed a conceptual framework for assessing dynamic capacities and sustainable behaviours considering COVID-19, (2) concentrates on financial ratios during COVID-19, and (3) established drivers for sustainable practices and competencies during disruption and unpredictable business settings. Conclusions: The suggested model can assist practitioners in creating and implementing sustainable supply chain (SC) activities and tracking and assessing their effects on the sustainability of businesses. So, the proposed model can assist managers in creating and implementing sustainable supply-chain activities and tracking and analysing their effects on the sustainability of businesses.

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“…In the past two decades, several quantitative, qualitative and conceptual methods have been applied to identify, assess and mitigate SC risk Kilubi, 2016;Rajagopal et al, 2017). Few conceptual models have been proposed about the development of RMSs (Dubey, 2019;Manuj and Mentzer, 2008;Tang, 2006b). Conventional and qualitative tools such as failure mode and effect analysis (FMEA) and/or fault tree analysis (FTA) and/or event tree analysis (ETA) (Chemweno et al, 2015;Yu and Huatuco, 2016;Aqlan and Lam, 2015b) are applied to find out the operational causes (triggering events) of failure (risk) and the corresponding mitigation actions.…”

Section: Approaches Used For Risk Mitigation In Scrm Cyclementioning

confidence: 99%

Benchmarking the relationship between supply chain risk mitigation strategies and practices: an integrated approach

Tarei

Thakkar

Nag

2020

BIJ

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PurposeThe purpose of this paper is to explore the relationship between various risk management strategies and risk management practices in order to design and hence enact a suitable supply chain risk mitigation (RM) plan. Additionally, this study proposes a hierarchical framework to explain the mutual relationship between supply chain risk management (SCRM) practices and strategies by considering the underlying dimensions between them.Design/methodology/approachAn amalgamation of systematic literature analysis (SLA) and correspondence analysis (CA) has been performed to develop the conceptual framework. A real-life case of Indian petroleum supply chain has been considered to validate and explain the proposed model.FindingsThe results reveal three underlying dimensions, which associate the relationship between RM strategies. They are, risk adaptability of SC managers with a variance of 34.71%, followed by resource capability of the firm and the degree of sophistication of RM practices, with variances of 27.72 and 20.35%, respectively. Risk avoidance strategy comprises of practices such as supplier evaluation, technology adaption, flexible process and information security. On the other extreme, the risk sharing strategy includes revenue sharing, insurance, collaboration, public–private partnership and so on as essential RM practices.Research limitations/implicationsThe study not only focuses on the distinction between RM strategies and practices, which were used interchangeably in the prior literature, but also provides an association between the same by exploring the underlying dimensions. These underlying dimensions perform a crucial role while developing a risk management plan. This study explicitly focuses on the RM step of SCRM process. Pre and post risk mitigation phases of SCRM process, such as risk assessment and risk monitoring, are beyond the scope of the current research.Originality/valueThe paper develops a framework for mapping various RM strategies with their corresponding practices by considering the Indian petroleum supply chain as a viable case study. Various theoretical and business implications are derived in the context of the developing country.

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Resilience and Agility: The Crucial Properties of Humanitarian Supply Chain

Cited by 6 publications

References 66 publications

Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain

Influence of big data and predictive analytics and social capital on performance of humanitarian supply chain

Modelling a Logistics and Financial Supply Chain Network during the COVID-19 Era

Benchmarking the relationship between supply chain risk mitigation strategies and practices: an integrated approach

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