Supplier Performance Evaluation for Manufacturing Industries: Re-exploring with Big Data Analysis

Matta, Purnima; Tayal, Akash

doi:10.1007/978-981-10-5427-3_53

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…The private data sources include vendor master files, RFXs, risky vendor lists, vendor bank account numbers, vendor-employee bank account matches, risky commodity lists, global clip levels, company risk reports, financial indices, and social networking data, while the public data sources are, for example, government-listed forbidden parties, country perception indices, tax haven locations, and advanced search engine searches. Mori et al, (2012), Pouraghabagher and Sarfaraz, ( 2018), Deswal and Garg (2015), and Matta and Tayal (2017) show the application of analytical models to handle BD in order to select suppliers. All four articles either base their models on or validate their models by empirical data.…”

Section: Psm Areasmentioning

confidence: 99%

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Big data in purchasing and supply management: a research agenda

Arvidsson

Jönsson

Kaipia

2021

IJPM

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is an associate professor at Chalmers university and has a PhD in industrial management and logistics engineering from Lund University. Her research is related to the supply chain collaborations with a large focus on innovation, sustainability, and digitalization. She has insight from the industrial, public and humanitarian sector. She is the author and reviewer of several peer-reviewed scientific publications in scientific purchasing, logistics, and operations management journals.Patrik Jonsson is professor in Operations & Supply Chain Management and the Head of Division at Supply and Operations Management. His research, teaching and outreach activities are in the field of operations and supply chain planning, with a specific interest in the generation of demand and supply coordination in firms and supply chains through data-and technology-enabled operations and planning processes. Patrik has a PhD in production management from Lund University. He is the author and reviewer of many scientific articles and serves as a regional, associate, or board member editor for several high ranked operations SCM journals. D.Sc. (Tech.

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Section: Psm Areasmentioning

confidence: 99%

“…We believe these will be important areas in future studies. For supplier selection, prescriptive models for handling PSM-BD are suggested (i.e., Deswal and Garg, 2015;Matta and Tayal, 2017). The majority only use internal and structured PSM-BD, and only two of these studies use empirical data.…”

Section: Process Application Perspectivesmentioning

confidence: 99%

Big data in purchasing and supply management: a research agenda

Arvidsson

Jönsson

Kaipia

2021

IJPM

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Predictive Modeling of Part Quality in the WAAM Process Using PCA Model Reduction and Machine Learning

Guizani,

Hammadi,

Yousfi

et al. 2024

Lecture Notes in Mechanical Engineering

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Recent Advances in Self-Powered Wearable Flexible Sensors for Human Gaits Analysis

Hu,

Ma,

Zhao

et al. 2024

Nanomaterials

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The rapid progress of flexible electronics has met the growing need for detecting human movement information in exoskeleton auxiliary equipment. This study provides a review of recent advancements in the design and fabrication of flexible electronics used for human motion detection. Firstly, a comprehensive introduction is provided on various self-powered wearable flexible sensors employed in detecting human movement information. Subsequently, the algorithms utilized to provide feedback on human movement are presented, followed by a thorough discussion of their methods and effectiveness. Finally, the review concludes with perspectives on the current challenges and opportunities in implementing self-powered wearable flexible sensors in exoskeleton technology.

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Supplier Performance Evaluation for Manufacturing Industries: Re-exploring with Big Data Analysis

Cited by 3 publications

References 9 publications

Big data in purchasing and supply management: a research agenda

Big data in purchasing and supply management: a research agenda

Predictive Modeling of Part Quality in the WAAM Process Using PCA Model Reduction and Machine Learning

Recent Advances in Self-Powered Wearable Flexible Sensors for Human Gaits Analysis

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