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Alongside structural equation modeling (SEM), the complementary technique of partial least squares (PLS) path modeling helps researchers understand relations among sets of observed variables. Like SEM, PLS began with an assumption of homogeneity – one population and one model – but has developed techniques for modeling data from heterogeneous populations, consistent with a marketing emphasis on segmentation. Heterogeneity can be expressed through interactions and nonlinear terms. Additionally, researchers can use multiple group analysis and latent class methods. This chapter reviews these techniques for modeling heterogeneous data in PLS, and illustrates key developments in finite mixture modeling in PLS using the SmartPLS 2.0 package.

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

It is the general purpose of this chapter to introduce assumptions, postulates and hypotheses concerning the social nature of human emotions. I will propose some universal social causes of emotion categories by integrating Kemper’s (1978) power and status dimensions in dyadic relations to universal structures of human groups. These structures, of Self and Other meeting or not meeting expectations and receiving rewards or not, predict specific emotion categories. Power and status dimensions are added to the model and defined in terms of expectation/sanction (E/S) states, and are proposed to be universal as well. Furthermore, changing E/S conditions produce corresponding changes in power/status relations, and changes in emotion categories. These changing social structural conditions cause individual anxieties to emerge. Extending Kemper’s theoretical conceptualizations, gaining or losing power-advantage or status-advantage predicts syndromes of universal anxiety emotions.

Behavioral scientists have long sought to capture how individuals’ understandings, perceptions and beliefs affect their decisions, often through examining the underlying cognitive processes that drive action (Schendel & Hofer, 1979). Economists, for example, are interested in how individuals’ utility functions influence their actions. Marketing researchers investigate how consumers’ preferences are reflected in their purchase behaviors. Organization researchers examine individual characteristics that influence outcomes such as job satisfaction, promotion, and turnover (Aiman-Smith et al., 2002).

G. H. Mead's social, developmental, and emergent conception of language and mind is a foundational assumption that is central to the interactionist tradition. However, the validity of this model has been challenged in recent years by theorists such as Albert Bergesen, who argues that recent advances in linguistics and cognitive psychology demonstrate that Mead's social theory of language learning and his theory of the social nature of mind are untenable. In light of these critiques, and drawing on Chomsky's debates with intellectuals such as Jean Piaget, John Searle, and Michael Tomasello, this chapter compares Chomsky's and Mead's theories of language and mind in terms of their assumptions about innateness and the nature and source of meaning. This comparison aims to address the major strengths and weaknesses in both models and shed light on how interactionists might frame these conceptual challenges in future theoretical and empirical research.