Partial Least Squares Structural Equation Modeling in Service Research (Special Section)

Introduction

Service research is characterized by complex theoretical frameworks involving latent variables (constructs), complex structural relationships, including higher-order models, and a growing emphasis on prediction. Under these conditions, partial least squares structural equation modeling (PLS-SEM) has gained increasing prominence as a methodological approach well suited to provide answers to research questions in the service domain. As a result, PLS-SEM has become widely adopted across a broad spectrum of applications in the service domain.

These applications span technology-enabled services—such as consumers’ responses to service robots (Köcher et al., 2025; Schepers et al., 2022), smart voice assistants (Wetzels et al., 2026), AI-based services (Nizette et al., 2025), and chatbots (Xie et al., 2023)—as well as market-related phenomena, including ownership perceptions in the sharing economy (Fritze et al., 2020). Moreover, PLS-SEM has been extensively used to examine employee- and organization-related issues, such as frontline employee characteristics (Choi et al., 2024) and servitization (Gudergan et al., 2026), service failure and recovery (Jerger & Wirtz, 2017), employee–AI collaboration (Yang et al., 2025), customer experience management (Köninger & Gouthier, 2024; Rahman et al., 2022, 2026), value co-creation (Vermehren et al., 2023), and leadership styles (Akhtar et al., 2024). 

At the same time, methodological developments in PLS-SEM have progressed rapidly. Recent advances include its combination into a necessary condition analysis framework (Becker et al., 2026; Hauff et al., 2024), advanced types of mediation analysis (Cheah et al., 2021), model comparison techniques (Liengaard et al., 2021), endogeneity assessment (Liengaard et al., 2025), and predictive model evaluation (Sharma et al., 2023; Shmueli et al., 2019). Frameworks for assessing the robustness of results (Hair et al., 2026; Sarstedt et al., 2020, 2024) have further expanded the methodological toolkit available to service researchers (see also Gudergan et al., 2025).

Together, these developments offer significant opportunities—but also challenges—for service research. They call for more transparent, theoretically grounded, and methodologically purposeful applications of PLS-SEM that clearly articulate whether models are intended to explain, predict, or both. This special section aims to leverage these opportunities by advancing the methodological sophistication and substantive contribution of PLS-SEM-based research in the service domain.​ 

List of Topic Areas 

This Journal of Service Management special section invites high-quality methodological, empirical, and conceptual contributions that extend or innovatively apply PLS-SEM to address substantive service research questions. Submissions may include, but are not limited to, the following topic areas: 
 

Methodological Advancements 
- Methodological developments in PLS-SEM with direct relevance for service research 
Scale development and diagnosing common method variance in PLS-SEM  
- Differences in model development from explanatory versus predictive perspectives 
- Explanatory versus predictive model evaluation and reporting 
- Novel metrics and guidelines for goodness-of-fit assessment and predictive power assessment 
- Endogeneity issues and remedies in PLS-SEM 
- Observed heterogeneity (e.g., multigroup analysis, moderation, conditional mediation) and unobserved heterogeneity (e.g., segmentation) in PLS-SEM 
- Applications and extensions of necessary condition analysis in PLS-SEM 
- Multimethod SEM involving PLS-SEM 
 

Innovative Applications and Best Practices in Service Research 
- Empirical studies on contemporary service research topics (e.g., technology-enabled services,  transformative service research, customer experience) employing recent advances in PLS-SEM 
- Demonstrations of best practices in the application, reporting, and interpretation of PLS-SEM results 
 

Design Extensions and Methodological Integrations 
- Extensions of PLS-SEM research designs  
- Integration of PLS-SEM with complementary analytical approaches

Submissions Information 

Submissions are made using ScholarOne Manuscripts. Registration and access are available at:  ​ https://mc.manuscriptcentral.com/josm

Author guidelines must be strictly followed. Please see: ​https://www.emeraldgrouppublishing.com/journal/josm

During the manuscript submission process, when prompted with “Please select the issue you are submitting to”, authors must select the appropriate special section from the drop-down menu to indicate that their manuscript is intended for the Special Section on “Partial Least Squares Structural Equation Modeling in Service Research”.

Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.

Key Deadlines 

Opening date for manuscripts submissions: ​15/09/2026​

Closing date for manuscripts submission: ​01/12/2026