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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.

The aim of this paper is to study the effect of strategic and project related potential risks on project delivery in Qatar. Two objectives have been defined. The first is to identify potential risk indicators (manifest variables) and categorize them (constructs/latent variables) based on a literature review, while the second is to examine and rank the relationships between the indicators and constructs by developing a structural equation model.

Twenty-five indicators were identified from the literature review and categorized into five groups. To collect the data, an online questionnaire was distributed in Qatar, and 116 responses were obtained. Structural equation modeling (SEM) was used to examine the model. The model that was developed based on the research hypothesis met goodness-of-fit, reliability and validity requirements.

The results showed that all constructs contributed well to the model and that the project parties (PPs) have the highest contribution with an effect weight of 0.209 followed by economic and legal (EL) conditions with an effect weight of 0.205. Site and safety (SS) conditions were third with an effect weight of 0.200 while environmental, natural and technological (ENT) conditions were fourth with an effect weight of 0.1989. The last ranked construct is political and social (PS) conditions with an effect weight of 0.186. Based on the outcome of the SEM, recommendations were provided to industry professionals in Qatar about mitigating the impact of potential risks on construction project.

To the authors' best knowledge, this is the first study to quantify the effects of strategic and project related risks on a construction project using SEM, considering the risk management indicators of SS, EL, ENT, PS in Qatar. The study's practical implications are to enlarge the project's risk management plan by considering the strategic and project related risks to enhance the project performance for the cost overrun and delay. The study is intended for construction projects in Qatar, but it can easily be adapted to other parts of the world given the local circumstances.

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.

Expanded awareness and application of recent PLS-SEM reporting practices were again called for by Hair (2022) in his PLS 2022 Keynote Address. This paper aims to analyze and extend the application of PLS-SEM in Industrial Management and Data Systems (IMDS) to focus on trends emerging in the more recent 2016–2022 period.

A review of PLS-SEM applications in information systems studies published in IMDS and MISQ for the period 2012–2022 identifies and comments on a total of 135 articles. Selected emerging advanced analytical PLS-SEM applications are also highlighted to expand awareness of their value in more rigorously evaluating model results.

There is a continually increasing maturity of the information systems field in applying PLS-SEM, particularly for IMDS authors. Model complexity and improved prediction assessment as well as other advanced analytical options are increasingly identified as reasons for applying PLS-SEM.

Findings demonstrate the continued use and acceptance of PLS-SEM as a useful alternative research methodology within IS. PLS-SEM is the preferred SEM method in many research settings, but particularly when the research objective is prediction to the population, mediation and mediated moderation, formative constructs are specified, constructs must be modeled as higher-order and for competing model comparisons.

This update on PLS-SEM applications and recent methodological developments will help authors to better understand and apply the method, as well as publish their work. Researchers are encouraged to engage in more complete analyses and include enhanced reporting procedures.

Applications of PLS-SEM for prediction, theory testing and confirmation are increasing. Information systems scholars should continue to exercise sound practice by reporting reasons for using PLS-SEM and recognizing its wider applicability for both exploratory and confirmatory research.

Corporate social responsibility (CSR) practices frequently result in increased costs for Chinese international contractors (CICs), where profitability is the primary objective; therefore, internal corporate drivers and external pressures play a crucial role in encouraging them to engage in sustainable CSR practices. This study systematically examines the dynamic impact of internal and external stakeholders on the CSR practices of CICs.

This study adopted a structural equation model (SEM) to identify and validate a correlation between stakeholders and CSR practices. Standardized causal coefficients estimated in SEM were used to construct a fuzzy cognitive map (FCM) model to illustrate the effect of stakeholders on CSR practices with linkage direction and weights. Predictive, diagnostic, and hybrid analyses were performed to dynamically model the variation in stakeholders on the evolution of CSR practices.

The empirical results demonstrate that (1) employee participation in CSR has the greatest impact on CSR practices, followed by CSR strategies, partner and customer expectations, and finally government regulations. (2) In the early stage of CSR fulfillment, CSR strategies have the greatest influence on CSR practices; in the later stage of CSR fulfillment, employee participation in CSR has the greatest influence on CSR practices. (3) In the long run, the most effective and economical integrated interventions are those that address employee participation in CSR, partner expectations and customer expectations, and intervention in CSR strategies is needed if the level of CSR practice needs to be improved in the short term.

This study contributes to the research on the influence mechanisms of CSR practices of CICs and systematically analyzes their dynamic influence on CSR practices of CICs from the perspective of stakeholders.

The study aims to propose a predictive model that combines personality and demographic factors to predict student academic performance (SAP). This research study works on understanding, enhancing and applying techniques to enhance the prediction of SAP.

The authors gathered information from 305 university students from Al-Zintan University Libya. The study uses a survey questionnaire to collect data on essential variables. The purpose of the questionnaire is to discover variables that affect students' academic performance. The survey questionnaire has 44 closed questions with Likert scale designs that were distributed to a variety of college students at the start of the first semester of 2022. It includes questions about demographics, personality, employment and institutional aspects. The authors proposed a predictive model to identify the main fundamental components, consisting of one dependent variable (SAP) and five independent constructs. The suggested model is tested using partial least squares (PLS) and structural equation modeling (SEM), which perform better than covariance-based structural equation modeling (CB-SEM). PLS-SEM performs well with smaller sample sizes, even for complicated models.

The study results show that the proposed model accurately predicted the student's academic performance. The personality trait variables are a key factor that determines the actual student's academic performance. The student's academic performance is significantly impacted by each variable in the personality trait variables as well.

The process of validating research was done empirically through the accuracy and efficiency of model performance. The study differs from previous studies in that it accumulated a wide range of factors from different dimensions, including student demographics and personality trait factors. The authors developed a structural equation model to predict students' academic performance.

This study examines and estimates the relationship among identified factors or determinants for the adoption of water ionizers by customers.

To this end, the questionnaire is prepared to have the preferences of customers based on the factors or enablers identified for the analysis of customers' perceptions toward the adoption of water ionizers. Recipients are identified to collect their preferences for the factors responsible for the adoption. The convenience sampling method is used in administering the questionnaire for the study. The structural equation modeling (SEM) technique is used to construct the model for defining the relationship between measured and latent variables using the lavaan, haven, psych and semPlot libraries in R software.

The study reveals that product features, which include pH value, oxidation-reduction potential (ORP) and micro-clustering (MC), are influenced by environmental sustainability (ES), and as a result, product features and product outcomes (brand value (BV), customer recommendation (CR) and perceived usefulness (PU)) together influence the adoption of water ionizers by customers.

Water ionizers have appeared as consumer electronic appliances designed to alter the pH and ORP of water through an electrolysis process. There are proven benefits to improved water quality across different pHs for its health benefits (HB) and other commercial and household uses. The study recommends that potential HB perceived through water ionizers and product features, which are supported by ES, and helps customers decide on the adoption of water ionizers.

The study supports comprehending the relationships between consumer behavior, sustainable practices and innovative technologies like water ionizers as society places a greater emphasis on environmentally conscious living and sustainable living. This study aims to clarify the elements affecting the adoption and perception of water ionizers from a sustainability perspective through an extensive assessment of the literature and empirical analysis.

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.

The purpose of this study is to discuss the construction of a structural measurement model utilizing structural equation modelling (SEM) to confirm the link between Industry 4.0 technologies, sustainable manufacturing practices and organizational sustainable performance. Relationship among the paradigm has yet to be fully investigated, necessitating a more conceptual and empirical examination on what impact they have on organizational sustainable performance when used together.

Industry 4.0 and sustainable production practices aim to progress a company's business competitiveness, forming sustainable development that benefits manufacturing companies. The aim of the study is to analyze the relationship between constructs that lead to operational excellence in firms that use Industry 4.0 technologies and sustainable manufacturing techniques. Experts from diverse automotive industries, who are applying both Industry 4.0 and sustainable manufacturing practices, provided data for the study.

Statistical estimations (hypotheses) are created to substantiate the measurement model that has been developed. The structural model was analysed, and the findings were discussed. The statistical estimate is either approved or rejected based on the findings. According to the conclusions of this study, strong link exists between Industry 4.0 technologies and sustainable manufacturing practices that affect organizational sustainable performance environmentally, economically and socially.

The research was conducted in the framework of automobile component manufacturing companies in India. The outcomes of the study are practically feasible.

The authors' novel contribution is the construction of a structural model with Industry 4.0 technologies and sustainable manufacturing practices into account.

The purpose of this study is not only to develop an integrated model of subjective well-being (SWB) by using confirmatory factor analysis (CFA) and structural equation modeling (SEM) but also to prioritize the subfactors of personality and SWB that affect the contextual performance (CP) of an employee by using a fuzzy-analytical hierarchy process (FAHP), which has not been done in the past.

The data were collected from 15 field experts and 412 employees of information technology (IT) companies operating in India. The data analysis was performed in two stages. The first stage includes CFA and SEM. The second stage includes prioritizing the factor through FAHP.

The results of SEM analysis manifested that all the dimensions of personality have a significant impact on CP. However, in the case of SWB, only two components (satisfaction with life and positive affect) have a significant impact on CP. Results of FAHP show that SWB is more important in predicting CP than the Big Five personality dimensions.

This research is a novel attempt to test and prioritize the factors affecting the CP of IT employees. The findings of the research will be useful for managers in increasing the performance of their employees. Further, the findings of the research will contribute to the literature on the factors affecting CP.