AN ALTERNATIVE ESTIMATION PROCEDURE FOR PARTIAL LEAST SQUARES PATH MODELING

Since its inception, partial least squares path modeling has suffered from the absence of a single optimization criterion for estimating component weights. A new estimation procedure is proposed to address this enduring issue. The proposed procedure aims to minimize a single least squares criterion for estimating component weights under both Mode A and Mode B. An alternating least squares algorithm is developed to minimize the criterion. This procedure provides quite similar or identical solutions to those obtained from existing Lohmöller's algorithm in real and simulated data analyses. The proposed procedure can serve as an alternative to the existing one in that it is well-grounded in theory as well as performs comparably in practice.