How Blockchain Enhances Supply Chain Management: A Survey

Shakhbulatov, Denisolt; Medina, Jorge; Dong, Ziqian; Rojas‐Cessa, Roberto

doi:10.1109/ojcs.2020.3025313

Cited by 39 publications

(10 citation statements)

References 111 publications

(135 reference statements)

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“…To date, extensive research has been organized to illustrate the benefits and impact of disruptive technologies on supply chains (Frederico, 2021b). Of note are the studies related to the field of AI/machine learning (Toorajipour et al , 2021), additive manufacturing (Luomaranta and Martinsuo, 2020), blockchain (Shakhbulatov et al , 2020), robotics (Jain, 2019), IoT (Mostafa et al , 2019), cloud computing (Tiwari and Jain, 2013) and Big data analytics (Queiroz and Telles, 2018).…”

Section: Discussion and Research Gapsmentioning

confidence: 99%

A systematic review of AR/VR in operations and supply chain management: maturity, current trends and future directions

Akbari

Kok

2022

JGOSS

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Purpose This research aims to provide systematic insight into the current maturity of augmented reality (AR) and virtual reality (VR) in operations and supply chain management (OSCM), by analyzing the existing literature, contemporary concepts, data and gaps for future research directions. Design/methodology/approach This research uses information from existing literature regarding timeline trends, publishers, research design and method, industry engagement, geographic location, active authors and affiliated universities, concentrated topics, theories and maturity in its review. A collection of publishing databases from 1997 to 2021 were explored using the keywords “Augmented Reality,” “Virtual Reality” and “Operations” and/or “Supply Chain” in their title and abstract to examine which publications to be included. Based on the search, a total of 164 journal articles were selected, and information on a chain of variables was collected. Findings There has been a significant publication growth over the past 25 years regarding the adoption of AR/VR in OSCM. Key findings indicate that 52% of the publications were focused on manufacturing, with only 10% of the existing literature using background theories. AR/VR can be observed at the introduction and growth phase and have yet to reach their maturity. Furthermore, there is limited utilization of AR/VR as drivers in facilitating sustainable practices in OSCM by academics and practitioners, albeit a strong promise exists. Finally, the prospective applications of AR/VR toward post-COVID-19 supply chains recovery require special attention. Research limitations/implications This systematic review is limited to considering only academic articles available from Emerald, Elsevier, Taylor and Francis, Springer, Scopus, JSTOR and EBSCO containing the keyword parameters. Originality/value The study used a bibliometric review to identify the trends and maturity in the evolution of AR/VR in OSCM. This research provides a better understanding of current research practices and offers directions toward the adoption of AR/VR in OSCM.

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Section: Discussion and Research Gapsmentioning

confidence: 99%

A systematic review of AR/VR in operations and supply chain management: maturity, current trends and future directions

Akbari

Kok

2022

JGOSS

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“…La cadena de suministro es un conjunto de etapas relacionadas entre sí, que trabajan con la finalidad de satisfacer al cliente. En las diferentes industrias existe una gran importancia en la cadena de suministros, ya que comprende un gran número de etapas para el suministro de los productos, y cada vez se encuentran con diferentes desafíos en cada una de las actividades de los participantes, como lo son los proveedores o partes interesadas que participan en la Digital Object Identifier (DOI): http://dx.doi.org/10.18687/LACCEI2022.1.1.591 ISBN: 978-628-95207-0-5 ISSN: 2414-6390 fabricación, almacenamiento, transporte o distribución de productos al cliente final [2]. Además, las organizaciones en la actualidad se enfrentan a gran variedad de problemáticas debido a los cortos ciclos de vida del producto, la competencia y nuevas expectativas del cliente; lo que ha conllevado a que las empresas cuenten con una mejor gestión de cada una de las etapas de la cadena de suministro, a fin de aumentar la productividad, reducir tiempo y hasta costos [3].…”

Section: A Cadena De Suministrounclassified

Development of a strategic planning model through historical demand in an expanded polystyrene product company

Arredondo¹,

Cruz²,

Eredias³

2022

Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research A

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Resumen-Los planes de producción en las organizaciones son clave y marcan la diferencia en toda la cadena de suministro en las necesidades de los clientes debido a la exigencia de calidad y tiempos de entrega de sus pedidos; por ello, muchas empresas se ven afectadas por no contar con las capacidades suficientes para responder a las exigencias del mercado. En este artículo se presenta un modelo de pronósticos en una empresa fabricante de productos de poliestireno expandido en el cual se evalúa el método de promedio móvil, suavizado exponencial simple y suavizado exponencial doble, con el fin de predecir la demanda futura y así apoyar las decisiones para una gestión de inventario adecuada en la empresa y reducir las quejas de los clientes por motivo de los tiempos

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“…Recommendations to improve blockchain scalability for SCM are discussed in [7], wherein sidechaining, deep learning, and other machine learning based models are proposed. These models are further reviewed in [8,9,10], wherein blockchain for logistics, general purpose blockchains for SCM, and healthcare SCM using smart contracts (SC)are discussed. Efficiency of these models is further enhanced in terms of delay, and throughput performance via the work in [11,12,13], where researchers have proposed simplified user interfaces, strategic product deployments, and decentralized digital manufacturing during CoVID (DDM SCM) are discussed.…”

Section: Literature Reviewmentioning

confidence: 99%

SCMBQA: Design of a Customised SCM-Aware Sidechaining Model for QoS Enhancement under Attack Scenarios

Shinkar

Thankachan

2022

IJRITCC

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Storing& processing data for supply chain management (SCM) systems requires design of high-security and quality of service (QoS) aware models. These modelsassist in improving traceability performance of SCM deployments via integration of transparent & distributed mechanisms. A wide variety of security models are proposed by researchers to perform these tasks, and it is observed that blockchain-based SCM implementations outperform other models in terms of security & QoS metrics.But most of these implementationsare general-purpose and do not incorporate SCM-specific consensus & mining rules. It is also observed that, mining speed& throughput performance of these blockchain-based implementations reduces exponentially w.r.t. number of SCM transactions. To resolve these issues, this paper discusses design of a novel Proof-of-Supply Chain (PoSC) based consensus model, which is specifically designed for sidechain based SCM deployments. The PoSC consensus model is used for high-efficiency SCM-based data storage and communication scenarios. The proposed PoSC consensus model is capable of resisting selfish mining, time jacking, and sybil attacks, which are targeted towards SCM deployments. The model uses temporal performance metrics of miner nodes, and combines them with relationship graphs to form an SCM miner rank. Based on this rank, miner nodes are selected, and their consensus responses are recorded. These responses are processed using an augmented deep learning model, that is trained over 8 different SCM implementations via machine learning. After successful mining, responses obtained from these miners are used to incrementally train the machine learning model which assists in continuous performance improvement. The SCMBQA model was tested on milk supply chain, agriculture supply chain, and electronic supply chain applications, in terms of computational speed, throughput, energy requirement, retrieval & verification delay, and storage requirements. It was observed that the proposed PoSC consensus was capable of improving the computational speed by 8.5%, reduce energy consumption by 4.9%, improve throughput by 9.6%, and reduce storage costs by 15.4% when compared with standard blockchain-based SCM consensus models. This is because the proposed model deploys an intelligent sidechaining approach, that is capable of optimizing number of generated sidechains via temporal QoS & security performance metrics. Due to use of smaller chain lengths, the proposed model is capable of integrating privacy-aware & secure approaches depending upon different SCM stages. Thus, distributor-level security models are different than retailer-level security models, which assists in context-sensitive block deployments. Due to use of PoSC, the proposed model was observed to be 99.5% resilient against internal and external attacks, which makes it useful for real-time SCM deployments.

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How Blockchain Enhances Supply Chain Management: A Survey

Cited by 39 publications

References 111 publications

A systematic review of AR/VR in operations and supply chain management: maturity, current trends and future directions

A systematic review of AR/VR in operations and supply chain management: maturity, current trends and future directions

Development of a strategic planning model through historical demand in an expanded polystyrene product company

SCMBQA: Design of a Customised SCM-Aware Sidechaining Model for QoS Enhancement under Attack Scenarios

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