A Critical Assessment for Sport Management Research: Comparing PLS-SEM and CB-SEM Techniques for Moderation Analysis Using Formative Measures

被引:3
|
作者
Trail, Galen T. [1 ]
Kim, Yu Kyoum [2 ]
Alfaro-Barrantes, Priscila [3 ]
机构
[1] Seattle Univ, Sport Adm & Leadership, Seattle, WA 98122 USA
[2] Seoul Natl Univ, Sport Management, Seoul, South Korea
[3] Nichols Coll, Sport Management, Dudley, MA USA
关键词
CB-SEM; PLS-SEM; formative multigroup model; formative continuous interaction model; R statistical software; BEHAVIORAL INTENTIONS; MULTIGROUP ANALYSIS; BRAND ASSOCIATIONS; CAUSAL INDICATORS; TEAM BRAND; LOYALTY; MODELS; ATTITUDE; SPONSOR; GENDER;
D O I
10.1080/24704067.2022.2098802
中图分类号
F [经济];
学科分类号
02 ;
摘要
Historically, researchers in the sport management area have used covariance based structural equation modeling (CB-SEM) when testing complex models. Recently, researchers have been using partial least squares path modeling (often called PLS-SEM) more frequently. The purpose of this paper was to advise sport management researchers about what approach to use by comparing PLS-SEM versus CB-SEM analytical techniques on the two different types of models: a formative (composite indicator) multigroup model and, a formative (composite indicator) continuous interaction model. We collected data from individuals (N = 1155) in the New England area (USA). After testing a base model, a multigroup model, and a continuous interaction model, we feel that PLS-SEM is the better choice for sport management researchers when testing formative models that use a composite variable. Our research shows when and why each technique works, in addition to showing that PLS-SEM moderation and multigroup models with formative items can work in the R statistical software.
引用
收藏
页码:248 / 268
页数:21
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