A large-scale data management and application analysis based on advanced classifier computing for the ERP system selection and adoption. (2018)

• Record Type: Journal Article
• Authors: Chen, You-Shyang; Lin, Chien-Ku; Chou, Jerome Chih-Lung; Chen, Wen-Shan
• Is Part Of: International journal of services operations and informatics. Volume 9:Number 4(2018)
• Page Start: 312
• Page End: 327
• Publication Date: 2018
• Subjects: large-scale data management -- enterprise resource planning system -- expert feature-selection -- classification model; Service industries -- Management -- Periodicals; Service industries -- Management -- Information technology -- Periodicals; 658.5
• Languages: English
• ISSNs: 1741-539X

Abstract

Enterprise resource planning (ERP), promising trend of emerged large-scale data management, has urgent needs to enterprises that are faced with competitions under external environment and globalisation trend. It is an interesting issue to help ERP system vendor selecting a suitable customer through intelligent models. This motivates the study. We compare the empirical results of the decisional feature database constructed by two classification models, Models 1 and 2, and find out the critical factors for ERP system selection summarised from the analytical results and hypothesis. The empirical results include: 1) Model 1: the accuracy of percentage split without featureselection reaches 89.7810% at maximum; 2) Model 2: the accuracy of percentage split with expert feature-selection also reaches 89.7810% at maximum. This study yields the two management implications: 1) ERP vendors can find out hidden potential customers by the proposal models; 2) expert feature-selection of given data is an effective technique used to increase the purpose of classification quality.