Measuring semantic components in training and motivation: A methodological introduction to the semantic theory of survey response

被引:18
|
作者
Arnulf, Jan K. [1 ]
Dysvik, Anders [1 ]
Larsen, Kai R. [2 ]
机构
[1] BI Norwegian Business Sch, Dept Leadership & Org Behav, N-0442 Nydalen, Norway
[2] Univ Colorado, Leeds Sch Business, Org Leadership & Informat Analyt, Boulder, CO 80309 USA
关键词
motivation; semantic algorithms; survey data; training; BIG DATA; METAANALYSIS; PERFORMANCE; LEADERSHIP; LANGUAGE; REVIEWS; BELIEF; ALPHA;
D O I
10.1002/hrdq.21324
中图分类号
F24 [劳动经济];
学科分类号
020106 ; 020207 ; 1202 ; 120202 ;
摘要
This is a methodological presentation of the relationship between semantics and survey statistics in human resource development (HRD) research. This study starts with an introduction to the semantic theory of survey response (STSR) and proceeds by offering a guided approach to conducting such analyses. The reader is presented with two types of semantic algorithms and a brief overview of how they are calculated and how they can be accessed by interested researchers. Subsequently, we use semantic data to reanalyze a previously published study on the relationships between perceptions of a trainee program, intrinsic motivation, and work outcomes. The semantic algorithms can explain between 31 and 55% of the variation in the observed correlations. This article shows how the statistical models originally used to explore the survey data can be replicated using semantics either alone or as an identifiable source of variation in the data. All the steps are presented in detail, and the datasets as well as the statistical syntax necessary to perform the analyses are made available to the readers. Implications for methodology and the improvement of predictive validity in HRD research are discussed.
引用
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页码:17 / 38
页数:22
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