Prospects of Purchasing—An Evaluation Model for Data Mining Approaches for Preventive Quality Assurance

Frank Straube (), Anna Lisa Junge and Tu Anh Tran Hoang
Additional contact information
Frank Straube: Institute of Technology and Management, Technical University Berlin
Anna Lisa Junge: Institute of Technology and Management, Technical University Berlin
Tu Anh Tran Hoang: Institute of Technology and Management, Technical University Berlin

A chapter in The Nature of Purchasing, 2020, pp 251-266 from Springer

Abstract: Abstract This contribution conceptualizes an evaluation model for data mining approaches for preventive quality assurance in purchasing. Future purchasing heavily relies on data analytics and purchasers need to be equipped with suitable tools and skills. A major prerequisite is to collect the respective data and to apply suitable algorithms to generate added value. This will free human capacity for more strategic initiatives and will provide an increase in flexibility and productivity within the company. To derive a valid evaluation model, data mining methods apt for preventive quality assurance being a binary classification problem are presented. Based on a seven steps data mining approach and a literature analysis, requirements for the data mining methods are derived. Subsequently, the criteria are aligned with exigencies in purchasing. This leads to a weighting of the respective criteria. The application of the evaluation model shows that support vector machines and k-nearest neighbors seem to be the best suitable data mining methods for preventive quality assurance in purchasing.

Date: 2020
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:mgmchp:978-3-030-43502-8_12

Ordering information: This item can be ordered from
http://www.springer.com/9783030435028

DOI: 10.1007/978-3-030-43502-8_12

Access Statistics for this chapter

More chapters in Management for Professionals from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().