Inductive reasoning: The promise of big data

被引:76
|
作者
McAbee, Samuel T. [1 ]
Landis, Ronald S. [1 ]
Burke, Maura I. [1 ]
机构
[1] IIT, Dept Psychol, 3105 S Dearborn,LS 252, Chicago, IL 60616 USA
关键词
Big data; Theory; Inductive reasoning; Empiricism; RESOURCE INFORMATION-SYSTEMS; SOCIAL NETWORKING WEBSITES; DATA-SCIENCE; PERSONALITY; INDUSTRIAL; BEHAVIOR; EDITORS; SELECTION; RICHNESS; BUSINESS;
D O I
10.1016/j.hrmr.2016.08.005
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Theory is a cornerstone of organizational research. Recently, however, some organizational scientists have argued that there is an overemphasis on theory development in our prominent publication outlets, calling for a rejuvenation of empirically driven research. To bring empirical research back to the forefront, the organizational sciences need a shock to the system: the advent of big data analytics in organizations provides just such a shock. The purpose of the following paper is to advocate for big data analytics as tools that can be used to support inductive research methods in the organizational sciences. We then highlight areas of organizational research and practice in which big data analytics can have an impact, provide readers with a tempered perspective on big data in the organizational sciences, and suggest a number of ways that researchers, reviewers, and editors can prepare themselves for the introduction of big data research in the organizational sciences. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:277 / 290
页数:14
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