A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study

Yazdanparast, Reza; Tavakkoli–Moghaddam, Reza; Heidari, Razieh; Aliabadi, Leyla

doi:10.1007/s10100-018-0596-x

Cited by 38 publications

(14 citation statements)

References 47 publications

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“…Although several studies have proposed frameworks for analyzing the impact of SCRE in the context of the overall supply chain, not many have focused explicitly on the supply chain capabilities and vulnerabilities. To the best of our knowledge, there are very few empirical studies of SCRE in developing countries (Kaviani et al , 2016) and, more specifically, in the Iranian automotive industry (Yazdanparast et al , 2018). Nonetheless, the supply chains in developing countries constitute a significant portion of the world's supply chain, and any vulnerabilities in the developing countries' supply chains will have an impact on the worldwide supply chain system.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Azevedo et al , 2013, 2016). Yet, this industry is typically seen by researchers as a place to develop, introduce and improve supply chain management concepts (Yazdanparast et al , 2018) and frequently becomes the reference for other industrial fields. Besides, the automotive industry is the second most active industry of Iran (after the oil and gas one), accounts for 10% of the GDP of the country and enrolls approximately 700,000 employees (Govindan et al , 2016).…”

Section: Literature Reviewmentioning

confidence: 99%

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Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry

Kaviani

Tavana

Kowsari

et al. 2020

BIJ

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PurposeThe purpose of this study is to evaluate two supply chain resilience key elements of vulnerability and capability in the automotive industry.Design/methodology/approachWe propose a fuzzy approach for statistical hypothesis testing and analyze two research hypotheses by synthesizing the results of a questionnaire given to 44 companies in the Iranian automotive industry.FindingsThe results indicate that the automotive industry in Iran should: (1) resist five elements of vulnerability, i.e. “external pressures,” “sensitivity,” “connectivity,” “supplier/customer disruptions,” and “resource limits,” and (2) embrace nine elements of capability, i.e. “flexibility in order fulfillment,” “capacity,” “efficiency,” “visibility,” “adaptability,” “recovery,” “dispersion,” “organization,” “market position” and “security” to achieve greater resiliency elasticity in the supply chain.Originality/valueThis is the first study on the supply chain resilience vulnerabilities and capabilities in the Iranian automotive industry.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry

Kaviani

Tavana

Kowsari

et al. 2020

BIJ

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“…(Jain et al 2017 ) presented a hierarchy based model for SCR and validated empirically. Few studies have also worked on the assessment of SCR through case studies (Hosseini et al 2016 ; Yazdanparast et al 2021 ). A systematic framework for assessment and strategies to foster SCR is proposed by Shashi et al ( 2020 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms

et al. 2022

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As the world has seen the impact of COVID-19, development of resilient supply chain strategies has emerged as top priority. The inconsistent demands, product consumption and the shorter lifecycle of products during the pandemic needs appropriate planning and designing to make the supply chain more resilient. In this study, an analytical model is proposed to assess the resilience of supply chain to overcome the effect of the disruption impacts. The supply chain risks will depend on the nature of the business and therefore, besides literature review on supply chain resilience the inputs from experts were required. The interdependency among the indicators was analysed by employing Interpretive Structural Modelling (ISM) and demonstrated with the help of a framework. The strength of the interdependence is assessed using Bayesian Network approach. BN transformed the qualitative expert inputs to quantitative assessment by utilising the principles of conditional probability. Three cases from Indian manufacturing industries were used to demonstrate and assess the critical supply chain resilience indicators using integrated ISM-BN approach. The cases showed that the proposed approach can assist decision makers in identifying the critical indicators to be focused towards improving the supply chain resilience to overcome the outbreak of Covid-19 pandemic. A comparative analysis of the supply chain risk indicators has also been performed, thereby extending the practical implication of supply chain resilience.

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“…However, measuring resilience is not a straightforward task, mainly due to the different nature of the disruptive events that threaten the operation of supply chains in a wide variety of forms; see e.g. Yazdanparast et al ( 2021 ), Hosseini et al ( 2019 ), and Özçelik et al ( 2021 ). Purvis et al ( 2016 ) proposed a framework for the design of resilient supply chains that underline that these systems need to be resilient both to demand volatility and to supply volatility, each of which may require a different set of metrics.…”

Section: Background and Contributionmentioning

confidence: 99%

Examining the balance between efficiency and resilience in closed-loop supply chains

Arquer

Ponte

Pino

2021

Cent Eur J Oper Res

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We study a hybrid system where the demand of customers can be satisfied by both manufacturing new products and remanufacturing used products. To manage the serviceable inventory, we implement a proportional order-up-to (POUT) replenishment policy. In this context, we first analyse the system efficiency by assessing its capacity to meet customer demand in a cost-effective manner. To this end, we consider both inventory performance (i.e., the balance between inventory holding and stock-out costs) and production smoothness (by measuring the Bullwhip effect in the supply chain). Second, we investigate the system resilience to demand volatility. In particular, we explore the impact of demand shocks on the inventory and production of the closed-loop system. Interestingly, we find that tuning the POUT controller to optimise efficiency may be problematic in terms of resilience to demand shocks. In this sense, a key trade-off exists that needs to be carefully considered by supply chain managers. Linking efficiency to resilience in such supply chains thus becomes essential to strengthen the transition towards more circular economic models. All in all, our analysis, via control-theoretic and simulation techniques, provides professionals with valuable insights into how to identify the appropriate ‘formula’ for building both efficient and resilient closed-loop supply chains.

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A hybrid Z-number data envelopment analysis and neural network for assessment of supply chain resilience: a case study

Cited by 38 publications

References 47 publications

Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry

Supply chain resilience: a benchmarking model for vulnerability and capability assessment in the automotive industry

Assessing supply chain resilience to the outbreak of COVID-19 in Indian manufacturing firms

Examining the balance between efficiency and resilience in closed-loop supply chains

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