
doi: 10.17705/1cais.05229
Partial least squares (PLS) path modeling is a widely used method in the information systems (IS) discipline for estimating linear structural equation models. At the same time, researchers have debated its relative merits compared to simple summed scores or to covariance-based estimation of structural equation models. In this paper, we comment on recent developments in PLS to ensure that IS researchers have up-to-date methodological knowledge and best practices if they decide to use PLS. In particular, we briefly review its mechanisms, its well-known properties, and its usage history in IS research. We briefly revisit a high-impact critique and debate a few years ago to identify the critical arguments around current PLS practices and use. That critique proved to be the driver for many advances in the PLS method and its applications which we discuss extensively and use to make 14 recommendations for how and when to use PLS or alternatives.
nonPeerReviewed
ta113, mallintaminen, ta112, Strategy and Entrepreneurship, tilastomenetelmät, Päätöksentekoa tukeva taloustiede ja talouden kilpailukyky (painoala), PLS, rakenneyhtälömallit, structural equation modeling, research methods, statistics, partial least squares, tilastotiede, tutkimusmenetelmät, Strategia ja yrittäjyys, Policy-Relevant Economics and Competitiveness of Economy (focus area), kehitys, tietojärjestelmät, estimointi
ta113, mallintaminen, ta112, Strategy and Entrepreneurship, tilastomenetelmät, Päätöksentekoa tukeva taloustiede ja talouden kilpailukyky (painoala), PLS, rakenneyhtälömallit, structural equation modeling, research methods, statistics, partial least squares, tilastotiede, tutkimusmenetelmät, Strategia ja yrittäjyys, Policy-Relevant Economics and Competitiveness of Economy (focus area), kehitys, tietojärjestelmät, estimointi
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