1979
DOI: 10.1177/002224377901600201
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Abstract: Structural equation models which include unobservable variables permit theoretical constructs to be represented by multiple indicators. The use and evaluation of such models are illustrated in an industrial salesforce study.

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Cited by 62 publications
(13 citation statements)
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“…Structural Equation Modeling (SEM) was used as the main statistical analysis tool to purify the measurement items. SEM is a powerful technique that combines the measurement model (confirmatory factor analysis) and the structural model (path analysis) into a simultaneous statistical test (Aaker and Bagozzi 1979;Garver and Mentzer 1999). SEM was used in this study because: (1) it is useful when one dependent variable becomes an independent variable in subsequent dependence relationships; (2) it provides a straightforward method of dealing with multiple relationships simultaneously while providing statistical efficiency; and (3) it is able to assess the relationships comprehensively and provides a transition from exploratory to confirmatory analysis (Hair et al 1998).…”
Section: Methodsmentioning
confidence: 99%
“…Structural Equation Modeling (SEM) was used as the main statistical analysis tool to purify the measurement items. SEM is a powerful technique that combines the measurement model (confirmatory factor analysis) and the structural model (path analysis) into a simultaneous statistical test (Aaker and Bagozzi 1979;Garver and Mentzer 1999). SEM was used in this study because: (1) it is useful when one dependent variable becomes an independent variable in subsequent dependence relationships; (2) it provides a straightforward method of dealing with multiple relationships simultaneously while providing statistical efficiency; and (3) it is able to assess the relationships comprehensively and provides a transition from exploratory to confirmatory analysis (Hair et al 1998).…”
Section: Methodsmentioning
confidence: 99%
“…H13 is thus accepted. Finally, there was a positive association between the errors of the psychological needs constructs ( β = 0.46, p < 0.01), suggesting a number of variables were not included in this model that were likely to affect psychological need satisfaction in this context (Aaker & Bagozzi, ; Vallerand, ).…”
Section: Part 2—the Role Of Wommentioning
confidence: 99%
“…Finally, item purification was done with confirmatory factor analysis (CFA) using AMOS 5.0 and qualitative assessment. The primary measurement item purification was conducted with multiple iterations of CFA through maximum likelihood estimation (MLE) (Aaker and Bagozzi 1979;Gerbing and Anderson 1988). Utilizing CFA to develop measurement scales is appropriate when the survey development is driven by a theoretical foundation and followed by scale reliability and construct validity assessments (Mentzer, Flint, and Kent 1999;Panayides 2007;Rafiq and Jaafar 2007).…”
Section: Measurement Items Developmentmentioning
confidence: 99%