Partial least square (PLS) analysis is the most favourite tool in chemometrics to develop calibration models. PLS technique allows us decipher even complex systems by analysing all variables instead of looking at them one a time. not only capture maximum variation associated with predictor (i.e. spectra) and predicted concentration) but also maximises correlation between them. The present artic...

this study tries to expand the understanding of the relationship between transformational leadership and organizational innovation at the organizational level. this research proposes a conceptual framework to explain the components of transformational leadership while focusing on the relationship between each component and organizational innovation. a sample of 219 managers from 63 companies in...

PLS regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. Its goal is to predict or analyze a set of dependent variables from a set of independent variables or predictors. This prediction is achieved by extracting from the predictors a set of orthogonal factors called latent variables which have the best predictive pow...

In a very competitive mobile telecommunication industry business environment, marketing managers need a business intelligence model that allows them to maintain an optimal (at least a near optimal) level of churners very effectively and efficiently while minimizing the costs throughout their marketing programs. As a first step toward optimal churn management program for marketing managers, this...

Structural Equation Modeling (SEM) is one type of multivariate analysis in the social sciences. Multivariate application statistical methods to analyze several research variables simultaneously. This community service activity was held and aimed at academic (lecturers students) from partner campuses Faculty Economics, State University Jakarta, they are FEB UHAMKA, STIE Indonesia, Tempo Polytech...

Number of latents The same number of factors will be extracted for PLS responses as for PLS factors. The researcher must specify how many latents to extract (in SPSS the default is 5). There is no one criterion for deciding how many latents to employ. Common alternatives are: 1. Cross-validating the model with increasing numbers of factors, then choosing the number with minimum prediction error...