Procedure Model for Supply Chain Digitalization Scenarios for a Data-Driven Supply Chain Risk Management

Schlüter, Florian

doi:10.1007/978-3-030-03813-7_8

Cited by 6 publications

(3 citation statements)

References 34 publications

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“…The introduction of Industry 4.0 has significantly propelled the studies of SSCM. Some review papers provided classification of the literature on smart supply chains (Schlüter & Henke, 2017). Wu et al.…”

Section: Literature Reviewmentioning

confidence: 99%

Smart supply chain management in business education: Reflection on the pandemics

Shi,

Lee,

2023

Decision Sci J Innov Edu

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Smart supply chain management (SSCM) has recently attracted significant attention from both industry and academia, particularly in light of the COVID pandemic. This article reviews current literature on information and integration, process automation, advanced analytics, and related business curriculum in SSCM. Our survey results demonstrate a concerning lack of adoption of SSCM in business curriculum and reveal several major challenges faced by educators when teaching SSCM, including a scarcity of available teaching resources, a need for cross‐disciplinary knowledge, and a lack of industry experience among students. These findings lead to our exploration of SSCM application in various supply chain and operations functions (e.g., product design, sourcing and procurement, production, quality management, warehouse management and distribution, delivery, and supply chain risk management) during the COVID‐19 pandemic. Drawing on our analysis, we conclude by offering several recommendations for promoting SSCM in business education.

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Section: Literature Reviewmentioning

confidence: 99%

Smart supply chain management in business education: Reflection on the pandemics

Shi,

Lee,

2023

Decision Sci J Innov Edu

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“…Web Analytics and Big Data Applications in the SCRM Web analytics and Big Data have triggered increasing scientific interest for their potential applications in SCRM [55]; however, a study of the extant literature on SCRM reveals that data-driven techniques receive only sporadic attention. Expert knowledge-based SCRM appears to be the mainstream method; however, the developing topic of digitization in supply chains presents a tremendous chance to develop a data-driven, smart SCRM [56]. Data availability is frequently hampered by legitimate concerns about data security, confidentiality, and privacy.…”

Section: Web Analytics and Big Datamentioning

confidence: 99%

Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data

2021

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The ongoing COVID-19 pandemic has proven to be a real challenge for courier companies on a global scale and has affected customer behavior worldwide. This paper attempts to propound a new methodology in order to predict the effect of courier companies’ e-commerce on customers’ risk perception regarding their online behavior after the outbreak, and the final effect of their behavior on the global ranking of the company’s website, utilizing passive crowdsourcing data from five world-leading courier companies as representative examples of their respective business sectors. The results will allow supply chain risk management (SCRM) managers to make effective strategic decisions regarding the efficient allocation of resources to mitigate the corporate risk to their organization during a novel crisis. In our paper, we monitored five key performance indicators (KPIs) over a 24-month period (March 2019–February 2021) as the first of a suggested three-level analysis process using statistical analysis and fuzzy cognitive mapping techniques. We propose that courier service companies should manage the risk of a potential novel crisis by improving the reputation and brand name of the company, since customers tend to trust an established brand.

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“…Supply chain delays and risks need proper decision-making on lead time and product delivery (Kumar and Kumar Singh, 2017). Especially, a more volatile supply chain seems to be at higher risk without real-time information transparency (Schlüter et al , 2018; Schlüter, 2019). Strategies and methods to handle this volatile supply chain with risk-prone outcomes become the need of the hour (Srinivasan and Swink, 2018).…”

Section: Introductionmentioning

confidence: 99%

Improving the performance of a Malaysian pharmaceutical warehouse supply chain by integrating value stream mapping and discrete event simulation

Abideen

Mohamad

2020

JM2

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Purpose Lean implementation is vastly incorporated in core manufacturing processes; however, its applicability in the supply chain and service industry is still in its infancy. To acquire performance excellence and thrive in the global competitive market, many firms are adopting newer methodologies. But, there is a stringent need for production simulation systems to analyze supply chains both inbound and outbound. The era of face validation is slowly disappearing. Lean tools and procedures that provide future state assumptions need advanced tools and techniques to measure, quantify, analyze and validate them. The purpose of this study is to enable dynamic quantification and visualization of the future state of a warehouse supply chain value stream map using discrete event simulation (DES) technique. Design/methodology/approach This study aimed to apply an integrated approach of the value stream mapping (VSM) and DES in a Malaysian pharmaceutical production warehouse. The main focus is diverted towards reducing the warehouse supply chain lead time by initially constructing a supply chain value stream map (both present state and future state) and integrating its data in a DES modelling and simulation software to dynamically visualize the changes in future state value stream map. Findings The DES simulation was able to mimic the future state lead time reductions successfully, which assists in better decision-making. Improvements were seen related to total lead time, process time, value and non-value-added percentage. Warehouse performance metrics such as receiving, put away and storage rates were substantially improved along with pallet processing time, worker and forklift throughput usage percentage. Detailed findings are clearly stated at the end of this paper. Research limitations/implications This study is limited to the warehouse environment and further additional process models and functional upgrades in the DES software systems are very much needed to directly visualize and quantify all the possible Lean assumptions such as radio frequency image identification/Andon (Jidoka), 5S, Kanban, Just-In-Time and Heijunka. However, DES has a leading edge in extracting dynamic characteristics out of a static VSM timeline and capture details on discrete events precisely by picturizing facility modification and lead time related to it. Practical implications This paper includes all the fundamental pharmaceutical warehouse supply chain processes and the simulations of the future state VSM in a real-life context by successfully reducing supply chain lead time and allowing managers in inculcating near-optimal decision-making, controlling and coordinating warehouse supply chain activities as a whole. Social implications This integrated approach of DES and VSM can involve managers and top management to support the adoption of anticipated changes. This study also has the potential to engage practitioners, researchers and decision-makers in the warehouse industry. Originality/value This study involves a powerful DES software package that can mimic the real situation as a virtual simulation and all the data and model building are based on a real warehouse scenario in the pharmaceutical industry.

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Procedure Model for Supply Chain Digitalization Scenarios for a Data-Driven Supply Chain Risk Management

Cited by 6 publications

References 34 publications

Smart supply chain management in business education: Reflection on the pandemics

Smart supply chain management in business education: Reflection on the pandemics

Estimating Risk Perception Effects on Courier Companies’ Online Customer Behavior during a Crisis, Using Crowdsourced Data

Improving the performance of a Malaysian pharmaceutical warehouse supply chain by integrating value stream mapping and discrete event simulation

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