RETRACTED ARTICLE: Evaluating sustainably resilient supply chains: a stochastic double frontier analytic model considering Netzero

Abstract

In era of reglobalization, sustainably resilient supply chains (SCs) are imperative in corporations to improve performance and meet stockholders’ expectations. However, sustainably resilient SCs could not be effective if are not assessed by using advanced frameworks, systems, and models. As such, developing a novel network data envelopment model (DEA) to appraise sustainably resilient SCs is our purpose in this article. To do so, we present a new double-frontier methodology to provide optimistic and pessimistic efficiency measures in network structures. Moreover, ideas of outputs weak disposability, chance-constrained programming, and discrete dominance are incorporated in a unified framework of modelling efficient and inefficient production technologies. The new network DEA model also can address dissimilar types of data, including undesirable and integer-valued and ratio outputs, stochastic intermediate products, and integer-valued inputs in a unified framework. Furthermore, an aggregated Farrell type efficiency measure is developed which allows to provide the complete ranking of units so that each decision-making unit (DMU) has its own rank in both overall and divisional point of view. We show the unique features of our developed model using a real case study in paint industry to evaluate the efficiency and reducing carbon dioxide (CO2) emissions. The results show that how well the proposed models can evaluate the sustainability and resilience of supply chains in the presence of uncertainty and with dissimilar types of data.

Artificial intelligence-driven supply chain resilience in Vietnamese manufacturing small- and medium-sized enterprises

“…While each of these research concepts has been studied individually or in a coupled (pairwise) form (Chopra et al, 2021;Hosseini, et al, 2020;Lücker et al, 2021;Cadden et al, 2022;, we need to look beyond the traditional technology infrastructure and focus on organizational structure and dynamics (leadership, culture, skills and competencies) to unpack antecedents for effective AI integration within organisations (such as SMEs) that will help to drive green, lean and agile decision-making for achieving SC resilience. While the importance of SC resilience, CE practices and AI-enabled digital transformation has been increasingly recognized by the research community (Baryannis, et al, 2019;Naz et al, 20212021b;Azadi et al, 2022;Wicaksana et al, 2022;Iftikhar et al, 2022: Ganesh et al, 2022, integrating these concepts to provide empirical insights is critical to making supply chain management practices sustainable, operationally productive, and resilient, while simultaneously responding to the UN sustainability development goals, the challenges posed by the pandemic, and operating in line with the governmental regulations and strategies. Zouari et al, 2021 have showed the positive influence of AI adoption on SC resilience (in a direct one-one relationship), however the position of our research is that AI adoption will facilitate operationalising and strategizing CE practices, SC risk management and SC agility through data-driven decision-making, which will lead to SC resilience.…”

“…recognized by the research community (Baryannis, et al, 2019;Naz et al, 20212021b;Azadi et al, 2022;Wicaksana et al, 2022;Iftikhar et al, 2022: Ganesh et al, 2022, integrating these concepts to provide empirical insights is critical to making supply chain management practices sustainable, operationally productive, and resilient, while simultaneously responding to the UN sustainability development goals, the challenges posed by the pandemic, and operating in line with the governmental regulations and strategies. Zouari et al, 2021 have showed the positive influence of AI adoption on SC resilience (in a direct one-one relationship), however the position of our research is that AI adoption will facilitate operationalising and strategizing CE practices, SC risk management and SC agility through data-driven decision-making, which will lead to SC resilience.…”

Transport Risks in the Supply Chains – Post Covid-19 Challenges

“…It is considered a comprehensive and useful assessment of supply chain risk (Kraude et al, 2022). DEA is commonly used in many areas, including supply chain management (Azadi et al, 2022) and transport (Akbar et al, 2020). When mentioning the applications of the DEA method, it is worth emphasising its particular usefulness for assessing objects and processes that cannot be characterised in financial terms, e.g., the public sector: foundations, education institutions, and, e.g., technology .…”