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Rigorous applications of analytical tools in information systems (IS) research are important for developing new knowledge and innovations in the field. Emerging tools provide building blocks for future inquiry, practice and innovation. This article summarizes the findings of an analysis of the adoption and reporting of partial least squares structural equation modeling (PLS-SEM) analytical tools by Industrial Management & Data Systems authors in the most recent five-year period.

Selected emerging advanced PLS-SEM analytical tools that have experienced limited adoption are highlighted to broaden awareness of their value to IS researchers.

PLS-SEM analytical tools that facilitate understanding increasingly complex theoretical models and deliver improved prediction assessment are now available. IS researchers should explore the opportunities to apply these new tools to more fully describe the contributions of their research.

Findings demonstrate the increasing acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is a preferred structural equation modeling (SEM) method in many research settings and will become even more widely applied when IS researchers are aware of and apply the new analytical tools.

Emerging PLS-SEM methodological developments will help IS researchers examine new theoretical concepts and relationships and publish their work. Researchers are encouraged to engage in more complete analyses by applying the applicable emerging tools.

Applications of PLS-SEM for prediction, theory testing and confirmation have increased in recent years. Information system scholars should continue to exercise sound practice by applying these new analytical tools where applicable. Recommended guidelines following Hair et al. (2019; 2022) are included.

One of the novel concepts in the management literature is intimate co-creation. Considering it as the outcome of workplace persuasion, this study examines its effect via team-member exchange and ethical climate for the assessment of multigroup analysis. Finding a relationship among variables is not the core objective of the study. The core objective was to assess multigroup analysis for examining measurement scales' uniformity or perceptual differences across the male and female groups using measurement invariance.

This was a quantitative study for a survey of faculty members from the top 10 Pakistani universities. It employed state-of-the-art statistical techniques, including the application of the foundational social exchange theory and the utilization of multigroup analysis in structural equation modeling (SEM) with the Analysis of Moment Structure (AMOS). The research methodology was designed to investigate the relationships between workplace persuasion, ethical climate, team member exchange and intimate co-creation. A specific emphasis was placed on assessing whether gender influences these relationships consistently across male and female groups, as determined by measurement invariance tests.

This study underscores the significant impact of ethical persuasion in the workplace on enhancing intimate co-creation among individuals, offering invaluable insights for organizational leaders. Importantly, it emphasizes that gender dynamics do not influence this relationship, underscoring the imperative of addressing gender-related workplace issues to optimize intimate co-creation. This holds particular relevance for service-based organizations, such as universities in this case.

This study makes a significant contribution by exploring the concept of intimate co-creation within the realm of organizational science, while also highlighting the crucial importance of considering workplace gender dynamics. It offers fresh insights into how these dynamics influence group creativity, guiding human resource practices toward fostering innovation within gender-inclusive workplaces. These insights gain added relevance in the evolving post-COVID-19 era and in the context of AI integration. Notably, a distinctive contribution of this study to social exchange theory lies in its innovative application of multigroup analysis to variables related to gender.

Partial least squares structural equation modeling (PLS-SEM) has become an established social sciences multivariate analysis technique. Since quality management researchers also increasingly using PLS-SEM, this growing interest calls for guidance.

Based on established guidelines for applying PLS-SEM and evaluating the results, this research reviews 107 articles applying the method and published in eight leading quality management journals.

The use of PLS-SEM in quality management often only draws on limited information and analysis results. The discipline would benefit from the method's more comprehensive use by following established guidelines. Specifically, the use of predictive model assessment and more advanced PLS-SEM analyses harbors the potential to provide more detailed findings and conclusions when applying the method.

This research provides first insights into PLS-SEM's use in quality management. Future research should identify the key areas and the core quality management models that best support the method's capabilities and researchers' goals.

The results of this analysis guide researchers who use the PLS-SEM method for their quality management studies.

This is the first article to systematically review the use of PLS-SEM in the quality management discipline.

This paper aims to examine project management segments based on customer satisfaction drivers and loyalty rather than traditional demographic or behavioural variables.

Data were gathered over 18 consecutive months, and 3,129 surveys were completed using a questionnaire. The statistical methods included partial least squares (PLS) structural equation modelling, finite mixture segmentation, prediction-oriented segmentation (PLS-POS) and multi-group analysis (PLS-MGA).

The findings indicate the existence of three segments among system delivery project customers based on the differences in the strengths of the path coefficients in the customer-centric structural model. In Segment 1, satisfaction based on the proposal was crucial for loyalty, with the value-for-money construct negatively impacting the repurchase intent construct. Segment 2 had a solid value-for-money orientation. In Segment 3, the critical path indicated that satisfaction drove repurchase intention, with satisfaction based mainly on the installation.

The research contributes to the segmentation theory by introducing a new way to segment the systems delivery projects customers based on the perceived strength of the relationships in a customer-centric structural model, which aligns with traditional segmentation theory in a way that most segmentation analyses do not. A new segmentation approach to the domain of project management theory is presented. Based on the results, treating the system delivery project customer base as a single homogenous group can lead to managerially misleading conclusions.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

In the digital era, the banking sector has transformed into a powerful intermediary, effectively connecting surplus and deficit units. This dynamic landscape empowers savers to secure their finances and generate returns, while simultaneously enabling businesses and individuals to access capital for investment and promoting economic growth. This study explores the relationships among banking development dimensions – represented by primary assets and liabilities, bank capital (core capital and required reserves) and economic growth as measured by components of gross domestic product (GDP).

The study consolidated monthly balance sheets from digital banks over a 20-year period, resulting in an aggregate monthly balance sheet that reflects the financial position of all digital banks in the Palestinian economy. The research employs both maximum likelihood and Bayesian structural equation modeling to measure the causal pathways of the consolidated balance sheet with the individual components of GDP.

The results revealed that bank main assets (investments and loans) and liabilities (deposits) collectively explain for 97% of bank capital. Investments and loans demonstrate significant negative correlations with bank capital, while deposits exhibit a positive impact. This leads to a fundamental conclusion that a substantial proportion of retained earnings within the banking sector is reinvested, fueling expansion and growth. Additionally, the results showed a significant relationship between bank capital and various GDP components, including private consumption, gross investment and net exports (p = 0.000). However, while the relationship between bank capital and government spending was insignificant in the maximum likelihood estimation, Bayesian estimation revealed a slight yet positive impact of bank capital on government spending.

This research stands out due to its unique exploration of the intricate relationship between bank sector development dimensions, primary assets and liabilities and their impact on bank capital in the digital era. It offers fresh insights by dividing this connection into specific dimensions and constructs, utilizing a comprehensive two-decade dataset covering the digital banks records.

This paper examines the nexus between supply chain social capital (relational social capital and structural social capital), supply chain responsiveness (operations system responsiveness and supplier network responsiveness) and firm performance. Additionally, the study examines the mediating role of supply chain responsiveness on the relationship between supply chain social capital and firm performance.

The authors test their hypotheses on a sample of 120 firms operating in Ghana. The measurement model and hypothesized paths were assessed using partial least squares structural equation modelling.

The findings revealed that structural social capital had a significant direct effect on firm performance, but relational social capital did not. It was also revealed that both relational and structural social capital have significant effects on operations system responsiveness and supplier network responsiveness. Additionally, operations system responsiveness fully mediated the effect of relational social capital on firm performance and partially mediated the effect of structural social capital on firm performance. Supplier network responsiveness, on the other hand, partially mediated the effect of both relational and structural social capital on firm performance.

This study contributes to the limited literature on supply chain social capital by unearthing the mechanisms through which supply chain social capital enhances firm performance. Specifically, the study demonstrates the intervening role of operations system responsiveness and supplier network responsiveness in the supply chain social capital–firm performance link.

Researchers have opined that the quality of commitment to pedagogical approaches by lecturers is one of the most important factors in determining student academic success. The purpose of this paper is to analyse the mediating effect of research informed teaching on the relationship between lecturer commitment to use of pedagogical approaches and teaching quality, with a view towards enabling delivery of high quality teaching and learning in HEIs.

The research is based on an online survey of the perception of 186 undergraduate and postgraduate students in four major UK universities. Covariance-based structural equation modelling (SEM) methodology was used to quantity and clarify the influence of lecturers' pedagogical attributes on teaching quality, mediated by research-informed teaching.

Findings reveal that: lecturers' pedagogical attributes have significant positive effect on teaching quality, research-informed teaching have significant positive effect on teaching quality, lecturers' pedagogical attributes have weak positive effect on research-informed teaching, and research-informed teaching partially mediates (indirect effect) the relationship between lecturers' pedagogical attributes and teaching quality.

Structural equation models are useful for clarifying concepts in pedagogy and have implications for education managers on how to improve teaching and learning in HEIs.

The paper presents a unique quantitative model for measuring the degree of teaching quality in universities.

The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.

A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.

The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.

This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.

Nowadays, the tourism industry is considered the largest and most diverse industry in the world, which can play a significant role in the economic growth and development of a country as the main source of income and employment. In this regard, the purpose of this study is to focus on evaluating the competitiveness indicators of Shiraz city tourism destination based on a combined model.

For this purpose, a questionnaire with 78 questions was used to evaluate the indicators, in which a total of 1,432 tourists participated, including 927 domestic tourists and 505 international tourists. The collected data were analyzed to determine the hierarchical relationship between the indicators using equation structural modeling.

The research findings indicate that the most effective and influential indicators in the field of tourism competitiveness are natural and handmade resources, and the most influential factors are demand conditions and cultural and natural resources. In this hierarchy, each factor affects its previous level and influences the next level.

This study offers significant potential for uncovering credible and robust approaches to further investigate the contextualization of tourism competitiveness on both national and international scales, thereby generating valuable new insights. By conceptualizing the diverse dimensions of tourism competitiveness and delving into the variations in its impacts across multiple levels, this research not only challenges existing notions but also aids destinations in maintaining and enhancing their market position and share over time. This study offers valuable insights and practical implications for both researchers and practitioners in the field of urban tourism. It enhances the understanding of destination competitiveness, informs policy decisions, facilitates benchmarking and best practices, guides strategic decision-making and promotes sustainable tourism development.