Capturing and Treating Unobserved Heterogeneity by Response Based Segmentation in PLS Path Modeling. A Comparison of Alternative Methods by Computational Experiments

Segmentation in PLS path modeling framework results is a critical issue in social sciences. The assumption that data is collected from a single homogeneous population is often unrealistic. Sequential clustering techniques on the manifest variables level are ineffective to account for heterogeneity in path model estimates. Three PLS path model related statistical approaches have been developed as solutions for this problem. The purpose of this paper is to present a study on sets of simulated data with different characteristics that allows a primary assessment of these methodologies.Partial Least Squares; Path Modeling; Unobserved Heterogeneity

Consistent and asymptotically normal PLS estimators for linear structural equations

A vital extension to partial least squares (PLS) path modeling is introduced: consistency. While maintaining all the strengths of PLS, the consistent version provides two key improvements. Path coefficients, parameters of simultaneous equations, construct correlations, and indicator loadings are estimated consistently. The global goodness-of-fit of the structural model can also now be assessed, which makes PLS suitable for confirmatory research. A Monte Carlo simulation illustrates the new approach and compares it with covariance-based structural equation modelin

Customer Loyalty Analysis in an heterogeneus market: a comparison between a priori segmentation and model based segmentation

Aim of Customer Loyalty Analysis is detecting suitable strategies to make loyal a customer. Like in Customer Satisfaction Analysis PLS-Path Modeling (PLSPM) is a suitable technique. As PLS-PM assumes homogeneity over population and customers\u2019 behaviors are different about loyalty, a PLS-Path model should be run in each homogeneous subgroup. Nevertheless these groups are not known. Then two way are possible: to use an a priori marketing segmentation or to adopt a model-based segmentation. The paper presents a short reflection on these different approaches

A Model of Response Strategies in Strategic Alliances :: A PLS Analysis of a Circumplex Structure

The few studies investigating partners’ response behavior in strategic alliances often fail to provide empirical support for a large proportion of the relationships they hypothesized. This discrepancy between theory and empirical findings could be attributed to a misconceptualization of response strategies as independent from each other. Indeed, response strategies could be better conceptualized as a circumplex structure rather than as discrete responses. Whereas the circumplex structure of response strategies has been empirically established, it has not yet been taken into account when detecting the effects of potential antecedents on response strategies. A model that accounts for the circumplex structure thus should exhibit superior explanatory power by reducing Type II error. PLS pathmodeling is particularly suited to substantiate the superiority of such a model, however PLS path modeling as implemented in extant software is not equipped to estimate circumplex structures. Therefore, the objective of the present study is twofold. First, we extend PLS path modeling so that it can handle circumplex structures. Second, building on a circumplex structure of response strategies, we develop and test a model of alliance partners’ response strategies and key antecedents. The results of a survey of alliance managers corroborate our expectations and demonstrate that non-significant antecedents become significant when accounting for the circumplex structure. This study thus advances PLS path modeling and contributes to a better understanding of managers’ complex decision-making processes in strategic alliances

Comments about the use of PLS path modeling in building a Job Quality Composite Indicator

A composite indicator is formed when elementary indicators are compiled into a single index, on the basis of an underlying model of the multidimensional concept that is being measured. The PLS path modeling allows the estimation of composite indicators and the measurement model could be expressed both as formative and re-ective. In this paper we construct a composite indicator of job quality using the PLS path modeling approach and compare results obtained by the formative and the re-ective measurement models of the general concept. We observe that the two approaches can give different results. Consequently, we give some suggestions in order to estimate stable and reliable models