Toward open science in PLS-SEM: Assessing the state of the art and future perspectives

被引:15
作者
Adler, Susanne Jana [1 ]
Sharma, Pratyush Nidhi [2 ]
Radomir, Lacramioara [3 ]
机构
[1] Ludwig Maximilians Univ Munchen, Inst Mkt, Ludwigstr 28 RG, D-80539 Munich, Germany
[2] Univ Alabama, Culverhouse Coll Business, Dept Informat Syst Stat & Management Sci, 361 Stadium Dr, Tuscaloosa, AL 35487 USA
[3] Babes Bolyai Univ, Fac Econ & Business Adm, Str Teodor Mihali,58-60, Cluj Napoca 400591, Romania
关键词
Partial least squares structural equation; modeling; Open Science; Replication; Reproducibility; Preregistration; PARTIAL LEAST-SQUARES; MODEL SELECTION; SYSTEMS; REPLICATION; PREREGISTRATION; REPLICABILITY; INCENTIVES; CRISIS; TRUTH;
D O I
10.1016/j.jbusres.2023.114291
中图分类号
F [经济];
学科分类号
02 ;
摘要
Driven by the high-profile failures to reproduce and replicate published findings, there have been increasing demands to adopt open science practices across scientific disciplines in order to enhance research transparency. Critics have highlighted the use of underpowered studies and researchers' analytical degrees of freedom as factors contributing to these issues. Despite methodological advances and updated guidelines, similar concerns persist regarding studies utilizing partial least squares structural equation modeling (PLS-SEM). Open science practices can help alleviate these concerns by facilitating transparency in PLS-SEM-based studies. However, the current level of adherence to these practices remains unknown. In this article, we conduct a comprehensive literature review of leading marketing journals to assess the extent to which open science practices are implemented in PLS-SEM-based studies. Based on the observed lack of adoption, we propose a PLS-SEM-specific preregistration template that researchers can use to foster transparency in their analyses, thereby bolstering confidence in their findings.
引用
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页数:13
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