Recent Advances in Causal Modeling Methods for Organizational and Management Research

Abstract

The purpose of this article is to review recent advanced applications of causal modeling methods in organizational and management research. Developments over the past 10 years involving research on measurement and structural components of causal models will be discussed. Specific topics to be addressed include reflective vs. formative measurement, multidimensional construct assessment, method variance, measurement invariance, latent growth modeling (LGM), moderated structural relationships, and analysis of latent variable means. For each of the areas mentioned above an overview of developments will be presented, and examples from organizational and management research will be provided.

Focus on opportunities as a mediator of the relationship between business owners' age and venture growth

“…To simultaneously test these effects, we calculated a path model using LISREL 8.70 (Jöreskog & Sörbom, 2001). We tested the moderating effect of mental health on the relationship between business owners' age and focus on opportunities using the approach recommended by Cortina, Chen, and Dunlap (2001; see also Williams, Edwards, & Vandenberg, 2003). This approach suggests to use aggregate measures as variables in the model and to fix factor loadings and error variances based on scale reliabilities and scale variances to correct for measurement errors.…”

“…In the final step, we compared a nested baseline model without the path from the interaction term to the dependent variable of focus on opportunities with a model that included the path. The null hypothesis that there is no moderation is rejected when the second model has a significant better model fit (Cortina et al, 2001;Williams et al, 2003). The relevant test statistic is the corrected Chi 2 -statistics.…”

Older Adults Use of Online Health Information - Do They Even Try?

“…First, Harman's single factor test indicated that only 43% of the variance accounted to one factor, which is below the threshold of 50% and, thus, gives initial support for the absence of high CMB [60]. Second, we performed a latent common method factor analysis [60,61,62], a frequently employed test in IS research [e.g., 26,63]. Hereto, an additional CMB factor containing all indicators is added to the model and all indicators of the theoretical constructs are transformed into singleitem factors [62].…”

“…Second, we performed a latent common method factor analysis [60,61,62], a frequently employed test in IS research [e.g., 26,63]. Hereto, an additional CMB factor containing all indicators is added to the model and all indicators of the theoretical constructs are transformed into singleitem factors [62]. Then, the influence of the CMB factor on each single-item factor is compared with the influence of its theoretical construct by observing 3 items; e.g., 'I believe computer-technologies are easy for me to use, when using them for health-related purposes.'…”

Analyzing the moderating effects of respondent type and experience on the fuel efficiency improvement in air transport using structural equation modeling

“…SEM is a handy statistical tool for evaluating the whole set of relationships among the latent constructs that are indicated by multiple measures defining a research model and for differentiating between the indirect and direct relationships between the latent constructs [24,73,79].…”