Developing operations management data analytics

被引：9
|
作者：
Feng, Qi [1 ]
Shanthikumar, J. George [1 ]
机构：
[1] Purdue Univ, Krannert Sch Management, W Lafayette, PA 47907 USA
来源：
PRODUCTION AND OPERATIONS MANAGEMENT | 2022年 / 31卷 / 12期
关键词：
data analytics; data integration; learning-then-earning; learning-or-earning; HEALTH-CARE-MANAGEMENT; INVENTORY CONTROL; BIG DATA; CHOICE; ASSORTMENT; OPTIMIZATION; POLICIES; APPROXIMATION; ALGORITHMS; MODEL;
D O I：
10.1111/poms.13868
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this article, we describe representative contributions in several major application areas of data analytics in operations management to summarize the recent development, discuss the common themes, identify the current trends, and speculate the future directions. Certainly, many important contributions have been made in various application areas that are either directly or indirectly related to data analytics, and there are important theoretical developments made by scholars in our field. It is not our intention to provide a complete survey for data-analytics work in our field. Instead, we focus only on the aspect of data integration in operational decision-making by describing the most popular applications of data analytics.
引用
收藏
页码：4544 / 4557
页数：14
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