Impact of Bullwhip Effect in Quality and Waste in Perishable Supply Chain

Peña, Julián Andrés Durán; Ortíz, Ángel; Maldonado, Nydia Marcela Reyes

doi:10.3390/pr9071232

Cited by 13 publications

(8 citation statements)

References 81 publications

(125 reference statements)

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“…In the present study, the e ect of combined use of various forecasting methods on the bullwhip e ect in a four-level supply chain, including retailers, wholesalers, manufacturers, and suppliers, is investigated. Although a similar issue has been explored in many previous research studies, considering the nature of supply chain components, it is more consistent with reality [1]. For this purpose, rst, the supply chain was simulated.…”

Section: Introductionmentioning

confidence: 89%

“…Also, she compared the two neural network methods with the ARIMA method and concluded that the neural network method reduces the bullwhip effect. Durán Peña et al [9] carried out a literature review to determine the causes of the bullwhip effect and the supply chain's quality factors of this phenomenon's perishable products. Updating the demand, the level of deterioration of the product, and the number of intermediaries is the causes of the bullwhip effect most investigated.…”

Section: Literature Reviewmentioning

confidence: 99%

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The Analysis of the Role of Bullwhip Effects on the Four‐Level Supply Chain in Industry Using Statistical Methods

Keliji

Aghajani

Movahedi

et al. 2022

Discrete Dynamics in Nature and Society

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Nowadays, regarding the technology development and communication means, supply chain management has gained special significance among different industries. The impact of bullwhip is one of the factors that could lessn the supply chain efficiency and increase the cost and delivery time of products and services. In this study, we explored the demand forecasting in supply chain, a four-level chain of retailers, wholesalers, manufacturers, and suppliers. Each level of the chain forecasted demand by moving average method, exponential smoothing, multilayer perceptron artificial neural network, and regression. Also, we provide a hybrid model based on statistics and mathematics to reduce the effect of bullwhip. For this purpose, at first, the supply chain simulation was performed. The results were then evaluated applying analysis of variance and the best combined model to reduce the amount of bullwhip effect was introduced. The model of this research could be useful for other studies. Finally, forecast for retail demand using the regression model; wholesale demand using the exponential smoothing model; manufacture demand using the neural network; and supplier demand using the moving average method have been done.

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Section: Introductionmentioning

confidence: 89%

Section: Literature Reviewmentioning

confidence: 99%

The Analysis of the Role of Bullwhip Effects on the Four‐Level Supply Chain in Industry Using Statistical Methods

Keliji

Aghajani

Movahedi

et al. 2022

Discrete Dynamics in Nature and Society

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“…(2) Demand information: Some agricultural products are challenging to store, and information asymmetry can cause the bullwhip effect. Therefore, effective demand information feedback from downstream SCs to upstream enterprises is crucial for predicting market demand, adjusting production plans, enhancing risk mitigation capabilities, and ultimately improving the operational efficiency of agricultural SCs [22].…”

Section: Establishment Of the Theoretical Modelmentioning

confidence: 99%

Performance Evaluation of Intelligent Agricultural Supply Chain Based on Structural Equation Model

Zhang,

2024

Decis. Mak. Appl. Manag. Eng.

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To solve the problems of unstable chain and poor supply chain (SC) function in the China’s agriculture industry, the relevant study is carried out on the function evaluation of the sustainable agricultural SC by structural equation modelling (SEM) under the background of digital technology. Primarily, the analysis is implemented on the research status of the sustainable SC and SC function. Then, starting with the relationship among big data (BD) application, information sharing, and sustainable SC function of agricultural production, a function evaluation model is implemented for the sustainable SC of SEM-based agricultural production. Next, a questionnaire is designed for the research on the impact of BD applications on the function of the sustainable agricultural SC. Ultimately, the statistical analysis of the obtained data reveals the correlation between the interaction and influence among the BD application, information sharing, and sustainable SC function of agricultural production. The results show that the BD application dimension, information sharing dimension, and all sub-dimensions have is beneficial to the function of the agricultural sustainable SC. The application of multidimensional cloud technology in BD has no obvious relationship with the dimensionality and level of information sharing, and the relationship between other corresponding dimensions shows a significant positive impact. A referenceable method is provided for the practice of sustainable SC management of agricultural production.

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“…To solve the model, the NSGA-II was enhanced. Managing the SCs of perishable products has also been the subject of recent review publications (e.g., Amini et al 2020 ; Awad et al 2020 ; Durán Peña et al 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

Designing a sustainable fish closed-loop supply chain network under uncertainty

Fasihi

Tavakkoli–Moghaddam

Hajiaghaei–Keshteli

et al. 2023

Environ Sci Pollut Res

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There is increasing attention to the sustainable development of supply chain (SC) and reverse logistics (RL) in the contemporary competitive economy, notably in the food sector, by scholars and stakeholders. This study investigates a sustainable closed-loop supply chain (CLSC) for fish due to its high value in the family food basket, its perishability, and the importance of waste product recycling. A multi-objective mathematical model is developed under uncertainty and sustainability criteria to optimize production rates with the aim of better distribution among different demand markets, total costs, social issues, and negative environmental effects (e.g., CO 2 emissions and unused/waste products). A combination of exact, meta-heuristic, and hybrid meta-heuristic algorithms are used to solve the suggested model. Then, the optimal solutions are found using the Taguchi method by evaluating the best initial replies. The solutions are evaluated based on various performance metrics. The analysis of variance (ANOVA) and the “filtering/displaced ideal solution” methods determine the best solution approach. Moreover, a case study with a trout CLSC in Northern Iran is examined. In addition, the Lingo software utilizes the ε-constraint method to evaluate and check the performance of the algorithms under different levels of uncertainty. Finally, sensitivity analyses are carried out to confirm the efficacy of the proposed algorithms. The findings demonstrate the proposed network’s outstanding consistency with the algorithms used and its application and efficiency.

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Impact of Bullwhip Effect in Quality and Waste in Perishable Supply Chain

Cited by 13 publications

References 81 publications

The Analysis of the Role of Bullwhip Effects on the Four‐Level Supply Chain in Industry Using Statistical Methods

The Analysis of the Role of Bullwhip Effects on the Four‐Level Supply Chain in Industry Using Statistical Methods

Performance Evaluation of Intelligent Agricultural Supply Chain Based on Structural Equation Model

Designing a sustainable fish closed-loop supply chain network under uncertainty

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