Special Issue: Applied Statistical Analysis using PLS Path Modelling

A Special Issue of EJASA (open access journal indexed in SCOPUS and Thomson Reuters Web of ScienceTM Core Collection - Emerging Sources Citation Index) is devoted to Applied Statistical Analysis using PLS Path Modelling: Its Advancement and Application in Human and Social Science Research

Partial Least Squares Path Modelling (PLS-PM) has become one of the analytical methods of choice in social science research in recent years (Hair et al. 2017; 2018). PLS-PM aims at maximizing the explained variance of dependent constructs in a path model (e.g., technology adoption and use) and allows the estimation of inter-relationships involving multiple constructs and indicators simultaneously (Petter, 2018). As such it is well suited for today’s data-driven economy, where social science researchers seek to deliver research outputs which not only make contribution to theories and knowledge but also carry practical utility to policy and decision-making processes (see Aria et al., 2018; Bourini and Bourini, 2016; Ingusci et al., 2016).

 

Recent research has brought forward numerous methodological extensions that allow social science researchers to generate varied statistical analyses. For example, with the use of PLS-PM, researchers today are able to conduct advanced analyses, such as assessing the mode of measurement (Gudergan et al. 2008), discriminant validity using new approaches (Henseler et al. 2015; Franke and Sarstedt, 2019), higher order construct (Ciavolino, 2012; Ciavolino and Nitti, 2013; Cheah et al. 2019; Sarstedt et al., 2019a), mediation and moderation (Becker et al., 2019; Nitzl et al. 2016), prediction-oriented segmentation analysis to identify and treat unobserved heterogeneity (Becker et al. 2013; Sarstedt et al. 2011), and invariance testing by means of measurement invariance (Henseler et al., 2016). In addition, many of the previously applied metrics can now be done via PLS-PM (Sarstedt et al., 2019b; Sharma et al., 2019; Shmueli et al., 2016; Shmueli et al., 2019). Therefore, this special issue attempts to perpetuate the discourse and application of PLS-PM by inviting papers addressing the following topics in any social science studies (such as marketing, management and tourism):

  • Application and advancement of the original PLS-PM algorithm (e.g., extended PLS, consistent PLS);
  • Model Comparison;
  • New metrics for goodness-of-fit testing and predictive power assessment;
  • Common method bias assessment;
  • Endogeneity assessment and treatment;
  • Measurement issues including confirmatory composite analysis (CCA);
  • Analysis of complex model relationships involving nonlinear effects, multiple mediation, and/or moderated mediation, higher-order models;
  • Logistic Regression in PLS-PM;
  • Addressing observed (multi-groups analysis and moderation) and unobserved heterogeneity (segmentation) in PLS-PM;
  • PLS-PM in experimental research;
  • PLS-PM on panel or longitudinal data;
  • PLS-PM and Bayesian modelling, and
  • Other advanced development of PLS-PM and their application.

 

Guest Editors

Submission and Review Process

Manuscripts should not have been previously published or be under consideration by other journals. The special issue are tied to the International Symposium on Applied Structural Equation Modeling and Methodological Matters in Melaka, Malaysia on 21 - 24 August 2019 and the same symposium in 2020 (to be announced), as well as 2020 International Conference on Partial Least Squares Structural Equation Modeling(www.pls2020.orgin Beijing, China on 17-19 March, 2020. Outstanding papers presented at this conference will be invited for submission. However, the guest editors also welcome submissions of high-quality papers that have not been submitted to or presented at the conference. Authors who submit papers that have not been presented on both conferences must explicitly state in their cover letter what is unique and valuable about the paper within the context of presenting an advanced issue in PLS-PM application.

The manuscript must fully comply with the Electronic Journal of Applied Statistical Analysis’s instructionfor authors.Authors must use the officialElectronic Journal of Applied Statistical Analysis submission portal, and select ‘Advanced Issues in PLS-PM’ special issue for their submission. The submission portal will open on April 30, 2020, and will close on June 30, 2020.

All papers will be screened by at least two guest editors (and desk rejected if not deemed suitable) before being sent to at least two referees. Papers will undergo a maximum of two rounds of revision to meet the scope and high standards of Electronic Journal of Applied Statistical Analysis (or will be rejected otherwise). There is no guarantee of publication.

For any queries regarding submission, please contact the special issue guest editors via email.

Deadlines

  • Submission due date: June 30, 2020
  • First round reviews: August 31, 2020
  • Revisions due: October 15, 2020
  • Second round reviews: December 31, 2021
  • Revisions due: February 15, 2021
  • Final editorial decision: March 15, 2021

Authors who publish with EJASA agree to the Creative Commons 3.0

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e-ISSN: 2070-5948