The broader goal of this paper is to provide social researchers with some analytical guidelines when investigating structural equation models (SEM) with predominantly a formative specification. This research is the first to investigate the robustness and precision of parameter estimates of a...

Purpose – When assessing the psychometric properties of measures and estimate relations among latent variables, many studies in the social sciences (including management and marketing) often fail to comprehensively appraise the directionality of indicants. Such failures can lead to model...

The increasing emphasis on understanding the antecedents and consequences of customer-to-customer (C2C) interactions is one of the essential developments of customer management in recent years. This interest is driven much by new online environments that enable customers to be connected in...

This research examines the regulatory fit effect on perceived value and buying intentions in the context of private health insurance decisions. The so-called value-from-fit effect is assessed in conjunction with the effect of risk perceptions. Value-from-fit results from the interaction effect...

Although firms are faced by a large number of market introduction failures, research into a major driver of these failures, customer resistance to innovation, is surprisingly scarce. While most authors have investigated positive adoption decisions, this paper focuses instead on consumer...

Regulatory fit, or the match between an individual's regulatory orientation and the strategy used to sustain it, offers a pervasive predictor of customer behavior. Merely reaching a decision in a certain way influences the value of a decision or an outcome. In this research, we conduct a...

Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical data. The assumption that the data is collected from a single homogeneous population is often unrealistic. Identification of different...

When applying multivariate analysis techniques in information systems and social science disciplines, such as management information systems (MIS) and marketing, the assumption that the empirical data originate from a single homogeneous population is often unrealistic. When applying a causal...