Integrating the split/analyze/meta-analyze (SAM) approach and a multilevel framework to advance big data research in psychology

guidelines and an empirical illustration via the human resource management investment-firm performance relationship

Yucheng Eason Zhang, Siqi Liu, Shan Xu, Miles M. Yang, Jian Zhang

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Though big data research has undergone dramatic developments in recent decades, it has mainly been applied in disciplines such as computer science and business. Psychology research that applies big data to examine research issues in psychology is largely lacking. One of the major challenges regarding the use of big data in psychology is that many researchers in the field may not have sufficient knowledge of big data analytical techniques that are rooted in computer science. This paper integrates the split/analyze/meta-analyze (SAM) approach and a multilevel framework to illustrate how to use the SAM approach to address multilevel research questions with big data. Specifically, we first introduce the SAM approach and then illustrate how to implement this to integrate two big datasets at the firm level and country level. Finally, we discuss theoretical and practical implications, proposing future research directions for psychology scholars.

Original languageEnglish
Pages (from-to)274-283
Number of pages10
JournalZeitschrift für Psychologie - Journal of Psychology
Volume226
Issue number4
DOIs
Publication statusPublished - Oct 2018

Keywords

  • firm performance
  • human resource management investment
  • multilevel framework
  • SAM approach

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