A data mining-based framework for supply chain risk management

Kara, Merve Er; Fırat, Seniye Ümit Oktay; Ghadge, Abhijeet

doi:10.1016/j.cie.2018.12.017

Cited by 102 publications

(29 citation statements)

References 60 publications

(79 reference statements)

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“…Con la información es posible realizar reglas de razonamiento y ser aprovechadas por técnicas básicas como los sistemas expertos y la lógica difusa. Ejemplo de lo anterior, se tiene el trabajo realizado por [74] que riesgo al cual se somete el diseño de una nueva cadena de suministro.…”

Section: Sistemas De Razonamiento Y Lógica Difusaunclassified

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Palacio

2021

Rev. politec.

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La inteligencia artificial ofrece grandes oportunidades para la cadena de suministro, siendo esto una ventaja competitiva para el mercado cambiante de hoy en día. Este artículo tiene como objetivo identificar los impactos y oportunidades que puede ofrecer el software con inteligencia artificial para facilitar la operación y mejorar el desempeño de la cadena de suministro en el sector bananero de Colombia. La metodología de trabajo consta de seis pasos en donde se obtuvo un total de 72 investigaciones. Las fuentes de información fueron cuatro bases de datos. Como conclusión principal, la cadena de suministro del sector bananero tiene todo lo necesario para que se implementen soluciones basadas en software inteligente con el fin de lograr una adaptación, flexibilidad y sensibilidad al contexto y dominio de ejecución. Artificial intelligence offers great opportunities for the supply chain, making it a competitive advantage for today's changing market. This paper aims to identify the impacts and opportunities that artificial intelligence software can offer to supply chain in the Colombian banana sector to facilitate the operation and improve the performance. The searching method consists of six steps getting 72 investigations finally. The sources of information were four databases. The main conclusion is the supply chain of the banana sector has everything for implementation of solutions based on intelligent software in order to achieve adaptation, flexibility and context awarenes and execution domain.

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Section: Sistemas De Razonamiento Y Lógica Difusaunclassified

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Palacio

2021

Rev. politec.

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“…Market risk refers to the direct and indirect impact of uncertain market factors on various links in the supply chain. This paper considers the risk factors that may cause damage to the supply chain in terms of supply, demand, and the market [22,28,55,56].…”

Section: Market Risk (E1)mentioning

confidence: 99%

Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China

Yan

Zhang

et al. 2020

Sustainability

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In order to protect the environment and reduce energy consumption, new energy vehicles have begun to be vigorously promoted in various countries. In recent years, the rise of intelligent technology has had a great impact on the supply chain of new energy vehicles, which, coupled with the complexity of the supply chain itself, puts it at great risk. Therefore, it is quite indispensable to evaluate the risk of the new energy vehicle supply chain. This paper assesses the risks faced by China’s new energy vehicle supply chain in this period of technological transformation. First of all, this paper establishes an evaluation criteria system of 16 sub-criterion related to three dimensions: the market risk, operational risk, and the environmental risk. Then, variable weight theory is proposed to modify the constant weight obtained by the fuzzy analytic hierarchy process (FAHP). Finally, a risk assessment of China’s new energy vehicle supply chain is carried out by combining the variable weight and the cloud model. This method can effectively explain the randomness of matters, and avoid the influence of value abnormality on the criteria system. The results show that China’s new energy vehicle supply chain is at a high level. Through the identification of risk factors, mainly referring to the low clustering risk, technical level risk and information transparency risk, this paper can provide a risk prevention reference for corresponding enterprises.

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“…Solving the aforementioned issues requires advanced tools and techniques, and data mining (DM) could be regarded as an optimal algorithm to find potential information and extract 3PL S&D data in batchwise, real time, and near-time owing to its advanced analytic capability to make efficient, intelligent, and timely decisions [31,32]. DM is roughly classified into six categories: classification, regression, clustering, prediction, association, and diagnosis, among which the most representative is C4.5, K-means, SVM, Apriori, EM, Pag-eRank, AdaBoost, kNN, Naive Bayes, and CART [33].…”

Section: Data Mining Algorithmmentioning

confidence: 99%

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Yan

Gong

et al. 2020

Mathematical Problems in Engineering

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In the past decades, despite considerable attention having been paid to third-party logistics (3PL) owing to its specialized service, sophisticated operation, and reduced cost, research on quantitative methods for estimating the efficiency of 3PL companies is still lacking, especially for those with small or medium scale. Therefore, the purpose of this study was to establish a quantitative evaluation method to measure the efficiency of the individual nongovernmental 3PL firms and explore the valuable information for the management of 3PL business with Apriori and K-means. Taking TopChains (an emerging nongovernmental 3PL company) as an example, the monthly supply and demand (S&D) level and matching degree were evaluated via the integrating data mining algorithm (i.e., Apriori and K-means) and TOPSIS entropy weight method based on historical data. The findings demonstrate that the S&D level varied with time and space, and the customer demand in February tended to reduce substantially. Besides, the outcome of S&D matching degree in June is undesirable, indicating the unsatisfactory efficiency in resource management. The evaluation maneuver stated in this study can serve as a valuable tool to measure individual nongovernmental 3PL enterprises’ efficiency in terms of S&D, and for reference, the results can aid in rational enterprise investment plan. Besides, this attempt broadened the direction of ARM and K-means being applied in the logistics field.

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A data mining-based framework for supply chain risk management

Cited by 102 publications

References 60 publications

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Oportunidades para la transformación digital de la cadena de suministro del sector bananero basado en software con inteligencia artificial

Risk Assessment of New Energy Vehicle Supply Chain Based on Variable Weight Theory and Cloud Model: A Case Study in China

Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

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