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- Creators: Carter, Craig
- Creators: MacKinnon, David
Description
In order to analyze data from an instrument administered at multiple time points it is a common practice to form composites of the items at each wave and to fit a longitudinal model to the composites. The advantage of using composites of items is that smaller sample sizes are required in contrast to second order models that include the measurement and the structural relationships among the variables. However, the use of composites assumes that longitudinal measurement invariance holds; that is, it is assumed that that the relationships among the items and the latent variables remain constant over time. Previous studies conducted on latent growth models (LGM) have shown that when longitudinal metric invariance is violated, the parameter estimates are biased and that mistaken conclusions about growth can be made. The purpose of the current study was to examine the impact of non-invariant loadings and non-invariant intercepts on two longitudinal models: the LGM and the autoregressive quasi-simplex model (AR quasi-simplex). A second purpose was to determine if there are conditions in which researchers can reach adequate conclusions about stability and growth even in the presence of violations of invariance. A Monte Carlo simulation study was conducted to achieve the purposes. The method consisted of generating items under a linear curve of factors model (COFM) or under the AR quasi-simplex. Composites of the items were formed at each time point and analyzed with a linear LGM or an AR quasi-simplex model. The results showed that AR quasi-simplex model yielded biased path coefficients only in the conditions with large violations of invariance. The fit of the AR quasi-simplex was not affected by violations of invariance. In general, the growth parameter estimates of the LGM were biased under violations of invariance. Further, in the presence of non-invariant loadings the rejection rates of the hypothesis of linear growth increased as the proportion of non-invariant items and as the magnitude of violations of invariance increased. A discussion of the results and limitations of the study are provided as well as general recommendations.
ContributorsOlivera-Aguilar, Margarita (Author) / Millsap, Roger E. (Thesis advisor) / Levy, Roy (Committee member) / MacKinnon, David (Committee member) / West, Stephen G. (Committee member) / Arizona State University (Publisher)
Created2013
Description
In this dissertation research, I expand the definition of the supply network to include the buying firm’s competitors. Just as one buyer-supplier relationship impacts all other relationships within the network, the presence of competitor-supplier relationships must also impact the focal buying firm. Therefore, the concept of a “competitive network” made up of a focal firm, its competitors and all of their combined suppliers is introduced. Utilizing a unique longitudinal dataset, this research explores how the organic structural changes within the new, many-to-many supply network impact firm performance. The investigation begins by studying the change in number of suppliers used by global auto manufacturers between 2004 and 2013. Following the Great Recession of 2008-09, firms have been growing the number of suppliers at more than twice the rate they had been reducing suppliers just a few years prior. The second phase of research explores the structural changes to the network resulting from this explosive growth in the number of suppliers. The final investigation explores a different flow – financial flow -- and evaluates its association with firm performance. Overall, this dissertation research demonstrates the value of aggregating individual supply networks into a macro-network defined as the competitive network. From this view, no one firm is able to control the structure of the network and the change in structure directly impacts firm performance. A new metric is introduced which addresses the subtle changes in buyer-supplier relationships and relates significantly to firm performance. The analyses expand the body of knowledge through the use of longitudinal datasets and uncovers otherwise overlooked dynamics existing within supply networks over the past decade.
ContributorsHuff, Jerry (Author) / Fowler, John (Thesis advisor) / Rogers, Dale (Committee member) / Carter, Craig (Committee member) / Arizona State University (Publisher)
Created2016