An Integrated Text Analytic Framework for Product Defect Discovery

doi:10.1111/poms.12303

CORC > 上海财经大学 > 上海财经大学

	An Integrated Text Analytic Framework for Product Defect Discovery
	Abrahams, Alan S.1,2; Fan, Weiguo 3,4; Wang, G. Alan 2; Zhang, Zhongju (John)5; Jiao, Jian 6
刊名	PRODUCTION AND OPERATIONS MANAGEMENT
	2015-06
卷号	24 期号:6 页码:975-990
关键词	social media analytics quality management
ISSN号	1059-1478
DOI	10.1111/poms.12303
英文摘要	The recent surge in the usage of social media has created an enormous amount of user-generated content (UGC). While there are streams of research that seek to mine UGC, these research studies seldom tackle analysis of this textual content from a quality management perspective. In this study, we synthesize existing research studies on text mining and propose an integrated text analytic framework for product defect discovery. The framework effectively leverages rich social media content and quantifies the text using various automatically extracted signal cues. These extracted signal cues can then be used as modeling inputs for product defect discovery. We showcase the usefulness of the framework by performing product defect discovery using UGC in both the automotive and the consumer electronics domains. We use principal component analysis and logistic regression to produce a multivariate explanatory analysis relating defects to quantitative measures derived from text. For our samples, we find that a selection of distinctive terms, product features, and semantic factors are strong indicators of defects, whereas stylistic, social, and sentiment features are not. For high sales volume products, we demonstrate that significant corporate value is derivable from a reduction in defect discovery time and consequently defective product units in circulation.
WOS研究方向	Engineering ; Operations Research & Management Science
语种	英语
出版者	WILEY-BLACKWELL
WOS记录号	WOS:000356673300008
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/2849]
专题	上海财经大学
通讯作者	Abrahams, Alan S.
作者单位	1.Virginia Tech, Business Informat Technol Dept, Blacksburg, VA 24061 USA; 2.Virginia Tech, Business Informat Technol Dept, Blacksburg, VA 24061 USA; 3.Virginia Tech, Accounting & Informat Syst Dept, Blacksburg, VA 24061 USA; 4.Shanghai Univ Finance & Econ, Sch Informat Engn & Management, Shanghai, Peoples R China; 5.Univ Connecticut, Sch Business, Operat & Informat Management Dept, Storrs, CT 06269 USA; 6.Microsoft, Bellevue, WA 98004 USA
推荐引用方式 GB/T 7714	Abrahams, Alan S.,Fan, Weiguo,Wang, G. Alan,et al. An Integrated Text Analytic Framework for Product Defect Discovery[J]. PRODUCTION AND OPERATIONS MANAGEMENT,2015,24(6):975-990.
APA	Abrahams, Alan S.,Fan, Weiguo,Wang, G. Alan,Zhang, Zhongju ,&Jiao, Jian.(2015).An Integrated Text Analytic Framework for Product Defect Discovery.PRODUCTION AND OPERATIONS MANAGEMENT,24(6),975-990.
MLA	Abrahams, Alan S.,et al."An Integrated Text Analytic Framework for Product Defect Discovery".PRODUCTION AND OPERATIONS MANAGEMENT 24.6(2015):975-990.