Disruption Detection for a Cognitive Digital Supply Chain Twin Using Hybrid Deep Learning

Purpose: Recent disruptive events, such as COVID-19 and Russia-Ukraine conflict, had a significant impact of global supply chains. Digital supply chain twins have been proposed in order to provide decision makers with an effective and efficient tool to mitigate disruption impact. Methods: This paper introduces a hybrid deep learning approach for disruption detection within a cognitive digital supply chain twin framework to enhance supply chain resilience. The proposed disruption detection module utilises a deep autoencoder neural network combined with a one-class support vector machine algorithm. In addition, long-short term memory neural network models are developed to identify the disrupted echelon and predict time-to-recovery from the disruption effect. Results: The obtained information from the proposed approach will help decision-makers and supply chain practitioners make appropriate decisions aiming at minimizing negative impact of disruptive events based on real-time disruption detection data. The results demonstrate the trade-off between disruption detection model sensitivity, encountered delay in disruption detection, and false alarms. This approach has seldom been used in recent literature addressing this issue

Artificial Intelligent Enabled Supply Chains as a Competitive Advantage

The focus of this paper is on the topics of artificial intelligence and supply chain management and how artificial intelligence-enabled supply chains provide organizations with competitive advantages. The supply chain’s adoption of data collection technologies as part of digital transformation and movements of industry 4.0 creates a strong foundation for artificial intelligence analytics. Artificial intelligence has three branches sensing and interacting, decision-making, and learning. Each branch uses its algorithms and serves a different purpose for the business. Artificial intelligence-enabled supply chains create unique, inimitable competitive advantages that fit Michael Porter’s five forces

Innovativeness and Innovation: Implications for the Renewable Materials Supply Chain

innovativeness, innovation, supply chain management, triple bottom line, corporate social responsibility, Agribusiness, Agricultural Finance, Demand and Price Analysis, Financial Economics, Q10, Q27, Q42, Q47,

Disrupting Illicit Supply Networks: New Applications of Operations Research and Data Analytics to End Modern Slavery

Report from a 2017 National Science Foundation workshop on promising research directions for applications of operations research and data analytics toward the disruption of illicit supply networks like human trafficking. The workshop was funded by the NSF’s Operations Engineering (ENG) and the Law & Social Sciences Program (SBE) under grant # CMMI-1726895. The report addresses the opportunity to apply advances from the fields of operations research, management science, analytics, machine learning, and data science toward the development of disruptive interventions against illicit networks. Such an extension of the current research agenda for trafficking would move understanding of such dynamic systems from descriptive characterization and predictive estimation toward improved dynamic operational control.Bureau of Business Researc

Job profiling: How artificial intelligence supports the management of complexity induced by product variety

Firms and supply chains (SC) increasingly are forced to customise products and optimise processes since today’s markets are, on average, more demanding in terms of both costs and customer satisfaction. Generally, when product variety (PV) increases not only improves sales performance, since products offered better fit customers’ expectations, but also increases the complexity in SC processes management, rising operational costs. For that reason, accurate management of product diversity is a fundamental point for the brands' success, which is why it is going to be investigated in that project. Moreover, firms’ managers apply strategies to mitigate or accommodate this complexity, avoiding the customer satisfaction and cost trade-off to remain competitive and survive. However, we were wondering if it is enough. Artificial Intelligence (AI) has emerged to stay. Digitalisation era, data availability, and the improvement in computing power have boomed AI’s potential in improving systems, controlling processes, and tackling complexity. These strengths are suitable to help managers not only to tackle the complexity arising from PV but also to boost the supply chain performance (SCP

Supply chain management 4.0: a literature review and research framework

This article presents a review of the existing state-of-the-art literature concerning Supply Chain Management 4.0 (SCM 4.0) and identifies and evaluates the relationship between digital technologies and Supply Chain Management. A literature review of state-of-the-art publications in the subject field and a bibliometric analysis were conducted. The paper identifies the impact of novel technologies on the different supply chain processes. Furthermore, the paper develops a roadmap framework for future research and practice. The proposed work is useful for both academics and practitioners as it outlines the pillar components for every supply chain transformation. It also proposes a range of research questions that can be used as a base to guide the future research direction of the field. This paper presents a novel and original literature review-based study on SCM4.0 as no comprehensive review is available where bibliometric analysis, motivations, barriers and technologies’ impact on different SC processes have been considered

The Strategic Supply Chain Management in the Digital Era, Tactical vs Strategic

The perspective of procurement and supply chain management is changing dramatically; traditionally, it was seen as a support function; however, the procurement function is receiving increased attention and investment as an essential contributor to the strategic success and a business enabler. While an end-to-end digital supply chain is an opportunity as it unleashes the next level of strategic growth and involves minimal investment in infrastructure, it is still a challenge to optimize and transform. Furthermore, the recent pandemics and geopolitical disruptions of Covid-19, the Ukraine-Russian war, Brexit and the US-China trade war; have structurally changed the global economy and revealed a new risk assessment that will result in the re-introduction of buffers, boundaries across industries and a partial return to regionalization with sort of de-globalization in which existing just-in-time getting replaced by just-in-case strategy