工具箱
结构方程建模
计算机科学
独创性
管理科学
数据科学
出版
领域(数学)
价值(数学)
知识管理
工程类
数学
定性研究
社会学
业务
程序设计语言
社会科学
机器学习
广告
纯数学
作者
Gabriel Cepeda‐Carrión,José L. Roldán,Misty A. Sabol,Joe F. Hair,Alain Yee‐Loong Chong
出处
期刊:Industrial Management and Data Systems
[Emerald Publishing Limited]
日期:2024-05-20
卷期号:124 (6): 2230-2250
被引量:5
标识
DOI:10.1108/imds-08-2023-0580
摘要
Purpose Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period. Design/methodology/approach Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers. Findings PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research. Research limitations/implications Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools. Practical implications Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools. Originality/value Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al . (2019; 2022) are included.
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