The Impact of Managerial Performance on Effective Public Governance at Higher Education Institutions in Java, Indonesia

This research aims to investigate the factors that influence the effectiveness of Information Systems (IS) Governance in Higher Education Institutions (IPT) using the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach. The background of this research reflects the importance of IS in supporting operations, management and decision making in a higher education environment that is increasingly complex and dependent on technology.The PLS-SEM method analyzes the relationship between key variables that influence the effectiveness of IS governance at IPT. It is a powerful multivariate statistical approach that allows factor analysis and regression in a single framework, allowing researchers to holistically understand how factors relate to each other. The results of this research will likely provide valuable insight for decision-makers at IPT in improving IS management and utilization. Practical implications include the development of more effective policies, better management strategies, and improved IS infrastructure. In addition, this research is also expected to provide an essential contribution to academic literature in understanding the factors that influence the effectiveness of IS governance in the higher education context. By better understanding the factors that influence the effectiveness of IS governance, IPT can increase its competitiveness, improve the quality of educational services, and support the achievement of its strategic goals. This research is expected to significantly contribute to understanding how IS governance can be implemented and managed more effectively in higher education environments through the PLS-SEM approach.

Purpose The construction industry (CI) plays a pivotal role in economic growth but is also a significant contributor to environmental degradation due to high resource consumption, energy use and waste generation. This highlights the urgent need to transition from the traditional linear model to a Circular Economy (CE) framework, which emphasizes resource efficiency, waste minimization and sustainability. However, the adoption of CE in the construction sector remains limited due to a lack of structured understanding of the external determinants influencing its implementation. This study addresses this gap by applying the PESTEL (political, economic, social, technological, environmental and legal) framework to identify and evaluate the macro-environmental determinants that impact CE adoption in the CI. Using a hybrid methodology that combines the Analytic Hierarchy Process (AHP) and Partial Least Squares Structural Equation Modeling (PLS-SEM), the study quantifies the influence of each factor. The results indicate that environmental, political and economic aspects significantly drive CE adoption, while social and technological factors are essential for operationalizing CE practices at scale. Legal factors had a relatively lesser impact. The study presents a comprehensive and data-driven approach to understanding CE implementation, offering actionable insights for policymakers, industry practitioners and researchers. It emphasizes the need for coordinated efforts across multiple dimensions, enabling targeted interventions that support the shift toward sustainable construction practices. Design/methodology/approach The study employs a mixed-methods approach, utilizing the Analytic Hierarchical Process (AHP) and Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the external factors influencing CE adoption in the built environment. Data were collected through a structured questionnaire survey targeting key stakeholders, including project managers, engineers, contractors, architects and material suppliers. Findings The results indicate that environmental factors, government policies and economic feasibility are the most significant determinants for CE adoption in the CI. Additionally, social awareness, technological advancements and a supportive legal framework emerge as crucial enablers for promoting sustainable practices. Research limitations/implications This study is limited by its reliance on questionnaire data, which may be influenced by respondent bias and varying levels of awareness about Circular Economy (CE) practices. The sample is geographically constrained, which may affect the generalizability of the findings. Additionally, the focus is on external PESTEL factors, without considering internal organizational influences. Future research could address these gaps by expanding the study scope and exploring both internal and external drivers of CE adoption. Practical implications The findings offer actionable insights for industry stakeholders to enhance CE adoption by prioritizing resource efficiency, strengthening regulatory frameworks, increasing technological investments and fostering collaboration within the CI. Originality/value This study provides a comprehensive evaluation of external determinants shaping CE adoption in the CI, contributing to the literature on sustainable construction. The results serve as a roadmap for policymakers and industry professionals to guide the transition toward a more circular and environmentally friendly construction model.

Partial Least Squares Structural Equation Modeling (PLS-SEM) in second language and education research: Guidelines using an applied example

The cooperative sector in Malaysia plays a significant role in socio-economic development, yet governance challenges persist. This study tests at how organisational culture influences the relationship between governance performance and managerial leadership in Malaysian cooperatives. Based on the Resource-Based Theory (RBT), the study suggests that culture and leadership are key intangible resources that can improve the quality of governance. The board of directors, managers, and cooperative members from a variety of industries provided a total of 400 responses. The study examined the proposed mediating link using Partial Least Squares Structural Equation Modelling (PLS-SEM). Partial Least Squares Structural Equation Modelling (PLS-SEM) was used in the study to test the proposed mediating link. These results challenge traditional assumptions in strategic management literature and underscore the unique governance dynamics in cooperatives, where formal structure, member control, and regulatory compliance may override cultural and leadership influences. These findings suggest that, within Malaysian cooperatives, formal governance structures and regulatory compliance may have a more substantial impact on governance performance than leadership and culture alone. The paper concludes with theoretical and practical implications, suggesting the need for context-sensitive frameworks for cooperative governance.

The Academic Information System (SIAKAD) serves a pivotal function in enhancing both operational efficiency and the quality of academic services within higher education institutions, particularly amidst the accelerating shift toward digitalization in the education sector. Despite its strategic importance, the effectiveness of SIAKAD implementation is contingent upon the level of user satisfaction—most notably that of students—which remains insufficiently explored through analytical models capable of capturing intricate causal relationships. This study seeks to empirically examine the determinants of student satisfaction in utilizing SIAKAD by investigating the influence of system quality, information quality, and ease of use, with perceived usefulness positioned as a mediating construct. The research adopts the Partial Least Squares Structural Equation Modeling (PLS-SEM) approach, which is methodologically appropriate for complex models involving latent variables and non-normally distributed data. The analysis is based on survey data collected from 128 active undergraduate students at Universitas Patompo. The empirical findings indicate that information quality exerts a significant direct influence on student satisfaction (β = 0.547; p < 0.001) and an additional indirect effect mediated by perceived usefulness (β = 0.268; p < 0.001). Conversely, system quality and ease of use demonstrate no statistically significant effects. The coefficient of determination values (R² = 0.706 for satisfaction; R² = 0.615 for perceived usefulness) reflect a strong predictive capability of the model. These results affirm that information quality is the most salient predictor of user satisfaction, underscoring the imperative to prioritize content enhancement as a strategic direction in the advancement of academic information systems within the higher education landscape.

This review provides a comprehensive, step-by-step guide to the application of partial least squares structural equation modeling (PLS-SEM) for novice researchers. This is a conceptual and literature-based review that focuses on best practices and PLS-SEM literature. It highlights the rationale for using PLS-SEM, sample size, software tools, and essential metrics in PLS-SEM analysis. Drawing on best practices and recent literature, the review offers a framework for conducting and reporting PLS-SEM analysis. The review presents essential such as outer loadings, Cronbach’s alpha coefficients, average variance extracted (AVE), composite reliability, cross-loadings, Heterotrait-Monotrait ratio of correlations (HTMT), the Fornell-Larcker criterion, variance inflation factor (VIF), and redundancy analysis. Moreover, for more consistent results, the paper emphasizes on researchers to employ 10,000 bootstrap subsamples and Bias-corrected and accelerated (BCa) bootstrap in assessing the structural model. Insights regarding path coefficients, p-values, R-square (R2), f-square (f2), and Q-square (Q2), are also presented. Furthermore, the review underscores the trade-off between predictive power and model fit when applying PLS-SEM. The presented practical insights alert novice researchers in avoiding common pitfalls and enhance the methodological rigor of empirical research that utilizes PLS-SEM. This step-by-step guide supports early-career researchers and contributes to the ongoing debates on improving methodological clarity and transparency.

This study aims to develop and test the validity and reliability of a student satisfaction survey instrument at Politeknik Negeri Pontianak, focusing on three main dimensions: Academic Services, Administrative Services, and Other Services. The analysis method employed is Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationships between items and the measured dimensions. The findings indicate that most items demonstrate good reliability, as shown by Cronbach’s Alpha values above 0.9 for all dimensions. However, issues with discriminant validity were identified, particularly in the Administrative Services dimension, which requires further review. Some items with low outer loading values are suggested for revision or removal. Additionally, model fit analysis results reveal that, although the model shows adequate performance, further improvements are necessary to enhance the overall model fit. This study makes an important contribution to the development of a more effective survey instrument for measuring student satisfaction while offering insights for educational institutions to enhance their services. The implications of this research suggest the need for continuous evaluation of the instrument and the use of larger samples in future studies to improve the generalizability of the findings. Keywords: Student Satisfaction Survey, Academic Services, Data Quality Testing, Construct Validation, PLS-SEM, Reliability, Validity.

Measurement errors wield the potential to introduce uncertainties and inaccuracies, casting shadows on data quality and jeopardizing the integrity of structural relationships. Notably robust against measurement errors, Partial Least Squares Structural Equation Modelling (PLS-SEM) has historically maintained a reputation for resilience. However, recent insights have unveiled its susceptibility to these errors, instigating a revaluation of its standing in the Structural Equation Modelling landscape. Overlooking measurement errors in PLS-SEM carry consequential repercussions, notably tainting the accuracy of structural relationships and introducing bias. This effect becomes particularly pronounced when dealing with an insufficient understanding of the intricate structural dynamics. Unfortunately, PLS-SEM currently lacks an all-encompassing remedy to address this concern. Consequently, the quantification of measurement errors impact in PLS-SEM gains paramount importance, fostering a demand for innovative strategies to propel its effectiveness forward. Notably, contemporary investigations have unmasked PLS-SEM's vulnerability to non-orthogonal errors. This revelation challenges the notion of its imperviousness to the detrimental influence of measurement errors, necessitating a comprehensive evaluation of its performance under such conditions. This study leveraged simulated data to extract empirical findings and employed parameters biasedness analysis. This analysis led to the determination that the stability of the PLS-SEM algorithm is compromised when exposed to diverse measurement error scenarios. Consequently, the outcomes generated exhibit both instability and bias. This bias becomes increasingly conspicuous as the magnitude of measurement errors intensifies. Thus, the study proposes avenues for elevating the robustness of PLS-SEM.

The aviation industry faces ongoing operational risks, regulatory challenges, and sustainability pressures, necessitating the adoption of Safety Management Systems (SMS) as a structured framework for enhancing safety performance and long-term resilience. While SMS has been widely implemented, its effectiveness in driving sustainability outcomes remains underexplored, particularly in emerging aviation markets. This study examines the role of SMS components—safety policy, safety assurance, and safety promotion—in fostering sustainability while emphasizing risk management as an integral part of SMS. Grounded in the Resource-Based View (RBV), Systems Theory, Stakeholder Theory, Institutional Theory, and Contingency Theory, this study examines the interconnected role of SMS and risk management in promoting economic, environmental, and social sustainability in Jordan’s aviation industry. A structured survey was conducted with 142 aviation professionals across 11 Jordanian aviation companies, and the data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to validate causal relationships. The findings confirm that the implementation of SMS significantly enhances sustainability, particularly in terms of operational efficiency, regulatory compliance, and stakeholder trust. While risk management is vital in strengthening safety governance, its direct impact on sustainability appears to be context-dependent, reinforcing the need for a more integrated approach where risk management is fully embedded within Safety Management Systems (SMS). These insights contribute to the broader aviation safety and policy literature by providing a refined conceptualization of Safety Management Systems (SMS) and risk management within the framework of sustainability. The study provides actionable recommendations for aviation regulators, policymakers, and industry stakeholders to enhance Safety Management Systems (SMS) frameworks and risk governance strategies, ultimately fostering a safer, more resilient, and sustainable aviation industry.

Aims: This study aims to examine the impact of lean management practices on organizational competitiveness, with operational performance positioned as a mediating mechanism. Specifically, the study seeks to analyse how lean management practices influence operational performance and how these operational improvements subsequently contribute to enhancing the competitive position of small and medium-sized enterprises (SMEs). Study Design: This study employs a quantitative explanatory research design using a cross-sectional survey approach. The relationships among lean management practices, operational performance, and organizational competitiveness are examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). Place and Duration of Study: The study was conducted among small and medium-sized enterprises located in the Greater Bandung area, Indonesia. Data collection took place between 15 November to 5 December 2025. Methodology: Data were collected from 186 SME owner–managers in Bandung, Indonesia, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The measurement items were adapted from established literature on lean management, operational performance, and competitiveness. The data were analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the reliability and validity of the measurement model and to test the proposed structural relationships, including the mediating role of operational performance. Results: The results indicate that lean management practices have a significant positive effect on operational performance. Operational performance, in turn, significantly enhances organizational competitiveness. In addition, lean management practices also exert a direct positive effect on organizational competitiveness. Mediation analysis reveals that operational performance partially mediates the relationship between lean management practices and organizational competitiveness, indicating that the competitive benefits of lean management are achieved primarily through improvements in operational performance. Conclusion: The study concludes that lean management serves as an effective strategic approach for enhancing the competitiveness of SMEs when it is implemented in a manner that strengthens operational performance. The findings underscore the importance of focusing on operational improvements as a key mechanism through which lean management translates into sustainable competitive advantages.

Background: Patient satisfaction is used as an important marker of the quality of medical services. This has an impact on patient loyalty and increases patient retention. Generally, perceptions of the quality of hospital services are based on patients' assessments of the services provided by the hospital, for example the relationship between patients and nurses, doctors and staff. Purpose: To determine factors related to general patient satisfaction. Method: Quantitative research with hypothesis testing without special treatment of subjects during the research period. Data was obtained through a survey of all patients who visited the emergency room at Budi Mulia Bitung Hospital in January 2024, totaling 170 respondents. The sample in this study was taken using a non-probability sampling method with the criteria, being more than 19 years old, cooperative, having a cell phone, and being able to be guided to fill out an online questionnaire. Results: All indicators in each dimension have an outer loading value of >0.7 and an AVE value for satisfaction with doctor services (0.703), emergency staff (0.860), emergency environment (0.656), general patient satisfaction (0.674). Cronbach's alpha and Composite Reliability values for all variables are above 0.7. The R-Square value for the general satisfaction variable is 0.948 and behavioral intention (0.944), so it can be said to be overfit. Based on the t-statistic value, p-value, and path coefficient, all variables in the research model tested are all significant. Conclusion: Satisfaction with physician services, emergency department staff, and emergency department environment are factors that are associated with general patient satisfaction and behavioral intentions. Keywords: Behavioral Intention; Patient Satisfaction; Partial Least Squares Structural Equation Modeling (PLS-SEM) Pendahuluan: Kepuasan pasien digunakan sebagai penanda penting untuk kualitas layanan medis. Hal ini berdampak pada loyalitas pasien dan meningkatkan retensi pasien. Umumnya persepsi kualitas pelayanan rumah sakit didasarkan pada penilaian pasien terhadap pelayanan yang diberikan rumah sakit, misalnya hubungan antara pasien dan perawat, dokter dan staf. Tujuan: Untuk mengetahui faktor-faktor yang berhubungan dengan general satisfaction patient. Metode: Penelitian kuantitatif dengan pengujian hipotesis tanpa perlakuan khusus terhadap subjek selama periode penelitian. Data yang diperoleh melalui survei kepada seluruh pasien yang berkunjung ke IGD RS. Budi Mulia Bitung pada bulan Januari 2024 sebanyak 170 responden. Sampel dalam penelitian ini diambil menggunakan metode non-probability sampling dengan kriteria, sudah berusia lebih dari 19 tahun, kooperatif, memiliki handphone, dan dapat dipandu untuk mengisi kuesioner online. Hasil: Semua indikator pada setiap dimensi memiliki nilai outer loading >0.7 dan nilai AVE physician care satisfaction (0.703), emergency department staff (0.860), emergency department environment (0.656), general satisfaction patient (0.674). Nilai cronbach’s alpha dan composite reliability pada semua variabel telah berada di atas 0.7. Nilai R-Square pada variabel kepuasan umum sebesar 0.948 dan niat berperilaku (0.944), sehingga dapat dikatakan overfit. Berdasarkan nilai t-statistik, nilai-p, dan koefisien jalur seluruh variabel dalam model penelitian yang diuji semuanya signifikan. Simpulan: Physician care satisfaction, emergency department staff, dan emergency department environment merupakan faktor-faktor yang berhubungan dengan general satisfaction patient dan behaviour intention. Kata Kunci: Behavioral Intention; Partial Least Squares Structural Equation Modeling (PLS-SEM); Patient Satisfaction.

Introduction Successful university-industry collaboration (UIC) largely depends on the close relationship and effective engagement between higher education institutions (HEIs) and industrial practitioners. The purpose of this study is to analyze the industrial enterprise's willingness to collaborate with HEIs in the UIC regarding the development of degree curricula. Methods Data for this study were collected from HEIs using a questionnaire administered with a two-week time lag, yielding 521 valid responses, which were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results and discussion It was confirmed that both ethical and servant leadership in HEIs affect industrial practitioners' trust level in the UIC. Additionally, it was discovered that industrial practitioners' trust in HEIs could foster their willingness to collaborate with HEIs in the UIC. Leaders' self-mindfulness training for ethical or servant leadership implementations in HEIs strengthens the significant associations between these two leadership styles and increased trust among industrial practitioners at the UIC. Finally, the theoretical and practical implications of this research were presented.

Researchers across a wide range of disciplines exploited the capabilities of partial least squares structural equation modeling (PLS-SEM). The rise in popularity of PLS-SEM is particularly noticeable 2013 onwards. The banking and finance discipline, however, hardly exploits the advantages of the PLS-SEM approach. PLS-SEM can be used for prediction and exploration in complex models with relaxed expectations on data. PLS-SEM is useful in identifying relationships between constructs. If the primary objective is theory development, PLS-SEM is appropriate.

Partial Least Squares Structural Equation Modelling (PLS-SEM) in Management Accounting Research: Critical Analysis, Advances, and Future Directions

Partial Least Squares Structural Equation Modeling (PLS-SEM) serves as a comprehensive methodological framework, critically addressing theoretical underpinnings, rigorous analytical approaches, and state-of-the-art modeling techniques vital for contemporary business research. The methodological discussion includes detailed exploration of reflective and formative measurement models, structural model specification, reliability, and validity assessments, alongside advanced analytical methods such as Confirmatory Tetrad Analysis (CTA-PLS) and Importance-Performance Matrix Analysis (IPMA). Advanced algorithms including bootstrapping and blindfolding procedures are elaborated, emphasizing predictive relevance and methodological precision. Partial Least Squares Structural Equation Modeling further offers robust analytical capabilities to evaluate modern AI-driven innovations, facilitating sophisticated assessment of user trust, perceived accuracy, and satisfaction with recommender systems, voice assistants, autonomous vehicles, AI-driven healthcare diagnostics, personalized educational platforms, and fraud detection technologies. Ethical considerations, reporting best practices, computational tools (SmartPLS, SEMinR), and Explainable AI (XAI) integration enhance the comprehensive nature of this framework. Furthermore, integration of cutting-edge analytical approaches such as moderation, mediation, Multi-Group Analysis (MGA), nonlinear modeling, machine learning integration, and quantum computing potential positions PLS-SEM as indispensable for contemporary business and technology research, ultimately promoting actionable scholarly insights and ensuring maximum methodological impact.