Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions

Badakhshan, Ehsan; Ball, Peter D.

doi:10.1080/00207543.2022.2093682

Cited by 42 publications

(11 citation statements)

References 84 publications

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“…Demand disruptions. Demand disruption refer to the phenomenon of unpredictable or sudden changes in market demand caused by natural disasters [5], policy adjustments [14], economic fluctuations [2], technological changes, competitive pressures, and other events, which have an impact on the supply chain and enterprise operations [13]. Due to fierce competition among different channels in the dual channel supply chain, demand disruptions have a particularly significant impact on enterprises [20].…”

Section: 2mentioning

confidence: 99%

Research on decision optimization of new energy vehicle supply chain considering demand disruptions under dual credit policy

Wu,

Zhang,

2024

JIMO

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The changes in demand disruptions and credit prices in the new energy vehicle (NEV) market under the dual credit policy pose challenges to the decision optimization of vehicle manufacturers and battery manufacturers in different production modes. To address this issue, based on the characteristics of the dual credit policy, this paper constructs a Stackelberg game model for both a single production mode that only produces NEV and a hybrid production mode that produces both NEVs and internal combustion engine vehicles (ICEVs), and solve for the optimal battery research and development (R&D) levels and pricing decisions of enterprises. On the basis of indepth analysis of the results, we further validate the results using numerical examples. The research results indicate that both demand disruptions and credit prices have a positive correlation with the sales prices of NEVs, battery prices, and battery R&D levels; Interestingly, demand disruptions and credit prices also have a positive correlation with the sales prices of ICEVs in a hybrid production mode; The decisions and profits of enterprises in a single production mode have higher robustness compared to a hybrid production mode; Government departments should actively continue to implement the dual credit policy and increase the credit price, which not only benefits the development of the NEV industry, but also contributes to the global environmental protection cause. 2020 Mathematics Subject Classification. 91A80.

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Section: 2mentioning

confidence: 99%

Research on decision optimization of new energy vehicle supply chain considering demand disruptions under dual credit policy

Wu,

Zhang,

2024

JIMO

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“…On the other hand, Wang, Peng and Yang (2022) and Badakhshan and Ball (2022) address the issue of inventories with lost sales and waiting times. Wang et al (2022) proposes a solution framework based on Double Deep Q-Networks (DDQN), formulating the inventory management problem as a Markov Decision Process, where the current inventory level state only depends on its previous state.…”

Section: Inventory Managementmentioning

confidence: 99%

“…Wang et al (2022) proposes a solution framework based on Double Deep Q-Networks (DDQN), formulating the inventory management problem as a Markov Decision Process, where the current inventory level state only depends on its previous state. In contrast, Badakhshan and Ball (2022) integrate machine learning and simulation to identify inventory and cash replenishment policies that minimize the impact of disruptions on supply chain performance. The simulation model generates data considering interruptions in the physical and financial flows of the supply chain, which are introduced into a decision tree algorithm to identify actions that reduce the cash conversion cycle.…”

Section: Inventory Managementmentioning

confidence: 99%

“…• Simulation model generates the data that is entered into a Decision Tree (Badakhshan & Ball, 2022) • Hybrid MCDM method that combines fuzzy logic with AHP and VIKOR classifies and selects SKUs that are fed into a Hybrid Model of Genetic Algorithm and GA-ANN Neural Network (de Paula-Vidal et al, 2022) • Principal Component Analysis (PCA) determines the predictor variables and the class variable using the Random Forest, Logistic Regression, Decision Tree, Naive Bayes, Support Vector Machines and Neural Networks algorithms (Andaur et al, 2021) • Simulation model generates the data set used by Decision Trees (Priore et al, 2019) • Markov Decision Process formulates the inventory management problem using the double-depth Q-Network (Wang et al, 2022) Demand Forecast…”

Section: Inventory Managementmentioning

confidence: 99%

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Integration of machine learning in the supply chain for decision making: A systematic literature review

Polo-Triana,

Gutierrez,

Leon-Becerra

2024

JIEM

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Purpose: This study presents a systematic literature review that provides a broad and holistic view of how machine learning can be used and integrated to enhance decision-making in various areas of the supply chain, highlighting its combination with other techniques and models.Design/methodology/approach: An exhaustive literature review used three sets of keywords in the Scopus and Web of Science (WoS) databases. Through a rigorous filtering process, 70 articles were selected from an initial total of 410, focusing on those that specifically addressed the intersection of machine learning and decision-making in supply chain management.Findings: Machine learning has proven to be an essential tool in the supply chain, with applications in inventory management, logistics, and transportation, among others. Its integration with other techniques has led to significant advances in decision-making, improving efficiency in complex environments. Combining machine learning methods with traditional techniques has been particularly effective, and integration with emerging technologies has opened up new application possibilities.Originality/value: Unlike previous studies that focused on specific areas, this study offers a broad perspective on the application of machine learning in the supply chain. Additionally, combining machine learning techniques with other models is highlighted, representing added value for the scientific community and suggesting new avenues for future research.

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“…A longer CCC indicates that sales growth is likely to be strong, translating to more significant profits and, thus, better financial performance (Tarkom, 2022). The cash conversion cycle, who disputed the notion, should be as brief as possible, as this will increase shareholder value (Badakhshan & Ball., 2022). Hypotheses of the study H1= In Pakistan's cement business, the cash conversion cycle has a detrimental impact on Tobin's Q. H2= In Pakistan's cement business, the current ratio has a detrimental impact on Tobin's Q H3= In Pakistan's cement business, the quick ratio has a detrimental impact on Tobin's Q. H4= In Pakistan's cement business, the inventory turnover ratio has a detrimental impact on Tobin's Q.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable Working Capital and Financial Performance in Cement Industry of Pakistan: An OLS Approach*

Raza,

Tursoy,

Balal

2023

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This research aims to demonstrate for the first time how the Pakistani cement sector's financial health is impacted by sustainable working capital. The cement Industry uses sustainable working capital techniques and practices for magnificent financial outcomes. Considering the importance of these profitable techniques, we practice these in cement firms with a sample size of 25 cement firms listed in the Pakistan stock market (PSX) from 1997-2022. The data is collected from annual reports available on the financial statements. The current ratio and Quick ratio are measured for liquidity. Ordinary Least Square & correlation analysis indicates that the cash conversion cycle (β1= -0.564, p= 0.00), Current ratio (β2= -0.20, p= 0.040), Quick ratio (β3= -0.585, p= 0.000) and Inventory Turnover ratio (β4= -0.244, p= 0.004) have a negative effect on financial performance (Tobin's Q). This study helps policymakers that can handle liquidity Sustainable working capital for the cement industry.

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Applying digital twins for inventory and cash management in supply chains under physical and financial disruptions

Cited by 42 publications

References 84 publications

Research on decision optimization of new energy vehicle supply chain considering demand disruptions under dual credit policy

Research on decision optimization of new energy vehicle supply chain considering demand disruptions under dual credit policy

Integration of machine learning in the supply chain for decision making: A systematic literature review

Sustainable Working Capital and Financial Performance in Cement Industry of Pakistan: An OLS Approach*

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