نتایج جستجو برای: partial least square structural equation modeling

تعداد نتایج: 1586149  

Journal: :international journal of information science and management 0
m. hajli birkbeck, university of london

advancement in e-commerce technologies and emerge of web 2.0 applications developed e-commerce. nowadays, customers are entering new platform, where they are more active than before through participating in business process with the web 2.0 applications. by the impact of the new stream in e-commerce, social commerce, we propose and test an adoption model at the customer level. impact of social ...

2012
Mikko Rönkkö Kaisa Parkkila Jukka Ylitalo

Motivated by recent critique toward partial least squares path modeling (PLS), we present a research question if the PLS method, as used currently, is at all an appropriate tool for theory testing. We briefly summarize some of the recent critique of the use of PLS in IS as a theory testing tool. Then we analyze the results of 12 PLS analyzes published in leading IS journals testing if these mod...

2013
Karin Schermelleh-Engel Christina S. Werner Andreas G. Klein Helfried Moosbrugger

Nonlinear structural equation modeling provides many advantages over analyses based on manifest variables only. Several approaches for the analysis of latent interaction effects have been developed within the last 15 years, including the partial least squares product indicator approach (PLS-PI), the constrained product indicator approach using the LISREL software (LISREL-PI), and the distributi...

2017
Ned Kock

Partial least squares (PLS) methods have desirable characteristics that have led to their extensive use in the field of information systems for path analyses with latent variables. Such variables are typically conceptualized as factors in structural equation modeling (SEM). In spite of their desirable characteristics, PLS methods suffer from a fundamental problem: unlike the classic covariance-...

2012

With the ever-increasing acceptance of the need to empirically validate theories in the social science disciplines (e.g., Sheth, 1971), data and multivariate analysis techniques (e.g., Hair et al., 2010; Hair et al., 2011b; Mooi and Sarstedt, 2011) play a central role in today’s research. The evolution of structural equation modeling (SEM) methods is perhaps the most important and influential s...

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