Structural Equations with Latent Variables.

Consumer researchers' growing interest in consumer experiences has revealed that many consumption activities produce both hedonic and utilitarian outcomes. Thus, there is an increasing need for scales to assess consumer perceptions of both hedonic and utilitarian values. This article describes the development of a scale measuring both values obtained from the pervasive consumption experience of shopping. The authors develop and validate the scale using a multistep process. The results demonstrate that distinct hedonic and utilitarian shopping value dimensions exist and are related to a number of important consumption variables. Implications for further applications of the scale are discussed.

https://www.jstor.org/stable/pdfplus/2489765.pdf

Work and/or Fun: Measuring Hedonic and Utilitarian Shopping Value

Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly observed and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path analysis, and latent growth curve modeling. Recently, SEM has gained popularity in the analysis of complex genetic traits because it can be used to better analyze the relationships between correlated variables (traits), to model genes as latent variables as a function of multiple observed genetic variants, and to assess the association between multiple genetic variants and multiple correlated phenotypes of interest. Though the general SEM framework only allows for the analysis of independent observations, recent work has extended SEM for the analysis of data on general pedigrees. Here, we review the theory of SEM for both unrelated and family data, describe the available software for SEM, and provide examples of SEM analysis.

Structural Equation Modeling

Social dominance orientation (SDO), one's degree of preference for inequality among social groups, is introduced. On the basis of social dominance theory, it is shown that (a) men are more social dominance-oriented than women, (b) high-SDO people seek hierarchy-enhancing professional roles and low-SDO people seek hierarchy-attenuating roles, (c) SDO was related to beliefs in a lag number of social and political ideologies that support group-based hierarchy (e.g., meritocracy and racism) and to support for policies that have implications for intergroup relations (e.g., war, civil rights, and social programs), including new policies. SDO was distinguished from interpersonal dominance, conservatism, and authoritarianism

https://dash.harvard.edu/bitstream/handle/1/3207711/Sidanius_SocialDominanceOrientation.pdf

Social dominance orientation: A personality variable predicting social and political attitudes.

One of the main reasons that firms participate in alliances is to learn know-how and capabilities from their alliance partners. At the same time firms want to protect themselves from the opportunistic behavior of their partner to retain their own core proprietary assets. Most research has generally viewed the achievement of these objectives as mutually exclusive. In contrast, we provide empirical evidence using large-sample survey data to show that when firms build relational capital in conjunction with an integrative approach to managing conflict, they are able to achieve both objectives simultaneously. Relational capital based on mutual trust and interaction at the individual level between alliance partners creates a basis for learning and know-how transfer across the exchange interface. At the same time, it curbs opportunistic behavior of alliance partners, thus preventing the leakage of critical know-how between them. Copyright © 2000 John Wiley & Sons, Ltd.

/pdf/learning-and-protection-of-proprietary-assets-in-strategic-1h1lppks31.pdf

C. J. McIver

Papers

Analyzing models with unobserved variables: analysis of covariance structures