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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
被引:6
|作者:
Zhang, Yucheng Eason
[1
]
Liu, Siqi
[2
]
Xu, Shan
[3
]
Yang, Miles M.
[4
]
Zhang, Jian
[5
]
机构:
[1] Hebei Univ Technol, Sch Econ & Management, Shijiazhuang, Hebei, Peoples R China
[2] Chengdu Univ Tradit Chinese Med, Sch Nursing, 1166 Liutai Ave, Chengdu 611137, Sichuan, Peoples R China
[3] Southwestern Univ Finance & Econ, Sch Business Adm, 555 Liutai Rd, Chengdu 611130, Sichuan, Peoples R China
[4] Macquarie Univ, Sydney, NSW, Australia
[5] Shanghai Int Studies Univ, Sch Business & Management, 1550 Wenxiang Rd, Shanghai 201620, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
SAM approach;
multilevel framework;
human resource management investment;
firm performance;
MODELS;
D O I:
10.1027/2151-2604/a000345
中图分类号:
B84 [心理学];
学科分类号:
04 ;
0402 ;
摘要:
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.
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页码:274 / 283
页数:10
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