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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.

Considering the construction industry’s vital role in economic development and social consequences, this study seeks to pinpoint critical barriers hindering Turkey’s sustainable construction (SC). Although several studies highlighted the barriers to SC worldwide, none identified the critical factors. By identifying and understanding these barriers, the research aims to comprehensively understand practices and formulate strategic recommendations to promote sustainable construction.

A systematic approach is adopted to achieve the research objectives. The study involves identifying potential barriers to SC with a systematic literature review. A questionnaire was organized and distributed via e-mail to architects, civil engineers, and contractors. The criticality of identified barriers was determined with normalized mean value analysis, and critical barrier factors (CBFs) to SC were isolated with exploratory factor analysis. Finally, the effect size of these factors was quantified through structural equation modeling.

This study identified 32 critical barriers hindering the SC in the Turkish construction industry among 49 barriers. Furthermore, this study revealed six CBFs to SC that are “inadequate supervision and control of SC,” “fear of transition to sustainable construction and disruptions in adoption,” “lack of educational opportunities,” “return on investment and financial bias,” “awareness and knowledge gap about SC,” and “lack of demand from stakeholders.” Among them, “awareness and knowledge gap about SC,” “fear of transition to SC,” “lack of educational opportunities,” “lack of demand from stakeholders,” and “inadequate supervision and control of SC” were determined as the very highly crucial CBFs hindering SC.

Although some studies have identified the barriers to SC qualitatively and quantitatively, studies have yet to provide insights into the critical barrier factors hindering SC. Therefore, this study comprehensively and quantitatively determines the relevant CBFs to SC using exploratory factor analysis and utilizes confirmatory factor analysis and structural equation modeling to present a structural model of how critical factors affect the SC.

This paper aims to discuss recent criticism related to partial least squares structural equation modeling (PLS-SEM).

Using a combination of literature reviews, empirical examples, and simulation evidence, this research demonstrates that critical accounts of PLS-SEM paint an overly negative picture of PLS-SEM’s capabilities.

Criticisms of PLS-SEM often generalize from boundary conditions with little practical relevance to the method’s general performance, and disregard the metrics and analyses (e.g., Type I error assessment) that are important when assessing the method’s efficacy.

We believe the alleged “fallacies” and “untold facts” have already been addressed in prior research and that the discussion should shift toward constructive avenues by exploring future research areas that are relevant to PLS-SEM applications.

All statistical methods, including PLS-SEM, have strengths and weaknesses. Researchers need to consider established guidelines and recent advancements when using the method, especially given the fast pace of developments in the field.

This research addresses criticisms of PLS-SEM and offers researchers, reviewers, and journal editors a more constructive view of its capabilities.

This study aims to address the challenge of sustainability in Catholic schools quantitatively, even more so knowing that there are few systematized and quantitatively elaborated approaches that help to determine their sustainability dimensions. Therefore, this study aims to estimate the structural relationships of organizational sustainability in primary and secondary religious schools in Latin America based on the substantive functions of the school, such as care, upbringing and education from an organizational approach.

Deductive reasoning was used. In the preliminary phase, data were extracted from 420 educational leaders of primary and secondary schools in Latin America from the Lasallian Network, leading a school population of 200,500 students and impacting 166 schools; these previous results were again contrasted with the forthcoming literature with research from the Ramon Llull University, Barcelona, Spain, to achieve the sustainability framework, which has an endogenous variable called the school organizational sustainability framework.

The results reveal four dimensions of the first-order structural model: management, association, communication, well-being and curriculum, And eight second-order dimensions: governance, communication, resources, secular association, secular partnership, health, social commitment, and campus operation. The investigation results show that secular association and well-being are two dimensions that are constituted as the main elements of a sustainability framework for this type of organization.

The Catholic school has specific dimensions that need to be cared for with special attention, such as association, which comes from the laity and comes from the experience of the religious. In addition to this vital dimension, well-being, constituted as care for the people of the community, as care for all, is connatural to the religious school. Still, it is constituted by an edge that completes it, and that is the concern for the well-being of those outside regarding social justice. A limitation in the pretension of totality is that the study is conducted in a small portion of Catholic schools in Latin America.

A practical impact in the schools investigated is to present this sustainability framework as a reference to incorporate these dimensions as a strategy to bet on sustainability. Although the realities and contexts of the Latin American school are very different, some factors can impact low-income schools and schools with more significant financial resources if they are strengthened and worked on with dedication. In addition, this framework can lead to roads and the construction of indicators within the school, which can measure the sustainable commitment of the whole school. Finally, a clear finding of the framework is the need for good governance processes related to leadership and leaders' commitment to school-wide sustainability.

The present study impacts the depth that the proposal of the global educational pact can reach in the reality of Catholic schools in Latin America. The seriousness with which its leaders take the issue of sustainability from this perspective can contribute to the sustainability of life itself.

The originality of this research is that it constitutes the first Sustainability framework in Latin America in Catholic schools from an organizational approach.

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 study aims to assess whether technological incentives inspire communities in the process of digital inclusion. The factors analyzed by the authors assess five dimensions: technology incentives, technology utilization, searching skills, social integration, and capabilities.

Data were collected from 329 respondents in 14 public libraries and analyzed using structural equation modeling to validate the proposed research model and its relationships with the factors the authors analyzed.

The results showed that technological incentives significantly impact on technology utilization, searching skills, social integration, and capabilities to support community digital inclusion in Pakistan.

Technological incentives to the community will lead to the improvement of network technology for things like online taxation, banking transactions, social integration, participation in government, and modern health and education benefits. In addition, technological incentives will also enhance information literacy and digital access, helping people improve cognitive skills and critical thinking and also helping to develop skills.

This research is based on raw data first collected from various people with different opinions from the Khyber Pakhtunkhwa public libraries. This study was conducted to gain a deeper understanding of the overall situation related to the use of technology in Pakistan and the complications involved.

This paper aims to identify key factors influencing the development of advanced manufacturing clusters and propose governance pathways for their digital innovation ecosystems.

A quantitative analysis of the Tai-Xin Integrated Economic Zone in China is conducted using data collected through a questionnaire survey. An evaluation index for the development level of advanced manufacturing clusters is constructed, and a structural equation model is used to identify key influencing factors and governance pathways.

This paper reveals that factors such as industrial foundation, technological innovation capability, social institution environment and government policies have a significant positive impact on the development of digital innovation ecosystem in advanced manufacturing clusters. It constructs a governance model for the digital innovation ecosystem and proposes three major pathways: integration of heterogeneous innovation resources, enhancement of digital capabilities, and fostering digital collaborative governance. The crucial role of digital technology in improving data processing efficiency, optimizing resource allocation and promoting collaboration among entities is emphasized. These pathways can optimize resource allocation, boosting the competitiveness and innovation capacity of clusters.

By incorporating advanced manufacturing clusters into the digital innovation ecosystem framework, this paper enriches theoretical research on both fronts. It offers specific governance pathways and policy recommendations, providing valuable references and guidance for promoting the digital transformation and ecosystem construction of manufacturing clusters.

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 research highlights the ongoing concern about organizational productivity and the lack of focus on designing an optimal model. The authors aim to create a comprehensive model for managing organizational productivity, considering its impact on profitability, customer satisfaction, and employee morale. They use qualitative research methods, including Systematic Literature Review and Interpretive Structural Modeling (ISM).

In this research using the qualitative research method of Systematic Literature Review, 57 variables affecting productivity were identified. These variables were placed in 16 layers by using the ISM method, which were classified analytically in four sections: INPUTS, OUTPUTS, OUTCOMES and IMPACTS. By determining the relationship between the sections, the research model was designed.

The potential model for organizational productivity management provides a comprehensive framework addressing critical factors like technology adoption, employee empowerment, organizational culture, and more. It identifies Linkage, Dependent, and independent variables. The lower layers consist of INPUTS such as Technological Tools, Organizational Values, and more. In the highest layer, impactful variables like Enhanced competitiveness, Improved decision-making, and Improved organizational culture are labeled as IMPACTS. Middle layer variables are categorized as OUTPUTS and OUTCOMES.

In this study, the concept of productivity management was redefined for the first time, and a multi-layered model for productivity management was creatively explicated using the structural equation modeling method.