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

Q3 Business, Management and Accounting

International Journal of Services Operations and Informatics Pub Date : 2018-01-01 DOI:10.1504/IJSOI.2018.10018739

You-Shyang Chen, Chien-Ku Lin, J. Chou, Wen Chen

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引用次数: 0

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.

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基于高级分类器计算的ERP系统选型与采用的大规模数据管理与应用分析

企业资源规划(ERP)是新兴的大规模数据管理的发展趋势，是企业在外部环境和全球化趋势下面临竞争的迫切需要。利用智能模型帮助ERP系统供应商选择合适的客户是一个有趣的问题。这是这项研究的动机。我们比较了模型1和模型2两种分类模型构建的决策特征数据库的实证结果，从分析结果和假设中总结出ERP系统选择的关键因素。实证结果包括:1)模型1:不加特征选择的百分比分割准确率最高可达89.7810%;2)模型2:专家特征选择百分比分割的准确率最高也达到89.7810%。本研究得出两个管理启示:1)ERP供应商可以通过提案模型发现隐藏的潜在客户;2)对给定数据进行专家特征选择是提高分类质量的有效方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Services Operations and Informatics Business, Management and Accounting-Management Information Systems

CiteScore

1.60

自引率

0.00%

发文量

期刊介绍： The advances in distributed computing and networks make it possible to link people, heterogeneous service providers and physically isolated services efficiently and cost-effectively. As the economic dynamics and the complexity of service operations continue to increase, it becomes a critical challenge to leverage information technology in achieving world-class quality and productivity in the production and delivery of physical goods and services. The IJSOI, a fully refereed journal, provides the primary forum for both academic and industry researchers and practitioners to propose and foster discussion on state-of-the-art research and development in the areas of service operations and the role of informatics towards improving their efficiency and competitiveness.