TUHH Open Research
Help
  • Log In
    New user? Click here to register.Have you forgotten your password?
  • English
  • Deutsch
  • Communities & Collections
  • Publications
  • Research Data
  • People
  • Institutions
  • Projects
  • Statistics
  1. Home
  2. TUHH
  3. Publication References
  4. Executing and interpreting applications of PLS-SEM: updates for family business researchers
 
Options

Executing and interpreting applications of PLS-SEM: updates for family business researchers

Publikationstyp
Journal Article
Date Issued
2021-09
Sprache
English
Author(s)
Hair, Joseph F.  
Binz Astrachan, Claudia  
Moisescu, Ovidiu I.  
Radomir, Lăcrămioara  
Sarstedt, Marko  
Vaithilingam, Santha  
Ringle, Christian M.  orcid-logo
Institut
Personalwirtschaft und Arbeitsorganisation W-9  
TORE-URI
http://hdl.handle.net/11420/8069
Journal
Journal of family business strategy  
Volume
12
Issue
3
Article Number
100392
Citation
Journal of Family Business Strategy 12 (3): 100392 (2021-09)
Publisher DOI
10.1016/j.jfbs.2020.100392
Scopus ID
2-s2.0-85096516490
The use of partial least squares structural equation modeling (PLS-SEM) has been gaining momentum in family business research. Since the publication of a PLS-SEM guidelines article in the Journal of Family Business Strategy’s special issue on “Innovative and Established Research Methods in Family Business” in 2014, methodological research has developed new model evaluation methods and metrics and sharpened our understanding of the method’s strengths and limitations. In light of these developments, we extend prior guidelines on PLS-SEM applications by discussing new model evaluation procedures (e.g., model selection) and metrics (e.g., PLSpredict). In addition, we highlight the usefulness of methodological extensions for discrete choice modeling and endogeneity assessment that considerably extend the scope of the PLS-SEM method, and emerging opportunities for the application of PLS-SEM with archival (secondary) data. PLS-SEM remains a valuable method in the context of family business research, especially when it comes to gaining a more sophisticated understanding of the drivers of family business behavior. Because of its properties, the PLS-SEM approach proves particularly valuable when the aim is to predict target variables (e.g., family firm performance) in the context of a causal model.
Subjects
Partial least squares
PLS-SEM
Structural equation modeling
Out-of-sample prediction
PLSpredict
Model selection
Discrete choice modeling
Endogeneity
DDC Class
000: Allgemeines, Wissenschaft
TUHH
Weiterführende Links
  • Contact
  • Send Feedback
  • Cookie settings
  • Privacy policy
  • Impress
DSpace Software

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science
Design by effective webwork GmbH

  • Deutsche NationalbibliothekDeutsche Nationalbibliothek
  • ORCiD Member OrganizationORCiD Member Organization
  • DataCiteDataCite
  • Re3DataRe3Data
  • OpenDOAROpenDOAR
  • OpenAireOpenAire
  • BASE Bielefeld Academic Search EngineBASE Bielefeld Academic Search Engine
Feedback