On the Decision Structures and Knowledge Discovery for ANP Modeling

• 作者: Lawrence W. Lan Wei-Wen Wu Yu-Ting Lee
• 来源期刊: 智能科学国际期刊(英文)
• 学科: 医学
• 关键词: ANALYTIC NETWORK Process BAYESIAN NETWORK CLASSIFIER Enterprise RESOURCE Planning Knowledge Discovery Partial Least SQUARES Path Modeling
• 年，卷（期）: 2013,（1）
• 页码范围: 15-23
• 页数: 9页
• 分类号: R73

摘要

This paper proposes an integrative framework for network-structured analytic network process (ANP) modeling. The underlying rationales include: 1) creating the measuring items for the complex decision problems;2) applying factor analysis to reduce the complex measuring items into fewer constructs;3) employing Bayesian network classifier technique to discover the causal directions among constructs;4) using partial least squares path modeling to test the causal relationships among the items-constructs. The proposed framework is implemented for knowledge discovery to a case of high-tech companies’ enterprise resource planning (ERP) benefits and satisfaction in Hsinchu Science Park,Taiwan. The results show that the proposed framework for ANP modeling can reach a satisfactory level of convergent reliability and validity. Based on the findings, pragmatic implications to the ERP venders are discussed. This study has shed new light on the long neglected, yet critical, issue on decision structures and knowledge discovery for ANP modeling.