Legal Literacy Among Nursing Students in the Philippines: The Roles of Legal Education Exposure, Perceived Importance, and Confidence in Legal Application

Розглянуто поняття правової культури, суть правової культури студентів закладів вищої освіти, її зміст, критерії та значення у формуванні громадянського суспільства. Проаналізовано останні дослідження з питань правової культури студентської молоді. Визначено основні завдання, цілі та засоби правового виховання як умови підвищення рівня правосвідомості студентів.

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

This study explores the structural relationships among legal awareness, compliance behavior, and supply chain efficiency in the context of Thailand’s upcoming 2025 plastic waste import ban. Employing a quantitative approach and Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 200 industry professionals across key industrial zones in Thailand. The findings reveal that environmental legal awareness alone does not significantly influence compliance behavior; however, organizational readiness to comply strongly impacts legal adherence. Furthermore, compliance behavior significantly enhances the efficiency of the recycled plastic supply chain amidst evolving regulatory conditions. These insights underscore the importance of institutional preparedness, capacity building, and strategic policy formulation to facilitate industry adaptation and promote sustainable development in Thailand’s plastic recycling sector. The study offers policy recommendations to strengthen legal enforcement, industry support, and collaborative efforts for a seamless transition towards sustainable plastic waste management.

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.

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.

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.

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

The paper explores the contribution of green supply chain management practices (GSCMPs) to the performance of the organization through evaluating the mediating role of perceived competitive advantage and moderating role of supply chain leadership skills. Although the previous literature has provided contradictory evidence on direct performance impact of green practices, this study fills this knowledge gap by assuming a viewpoint (mechanism-based) in terms of how and when sustainability initiatives generate value, in this case, in an emerging economy setting. The quantitative research design was a cross sectional design based on a survey data of companies that are involved in supply chain activities. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to test the proposed mediatedmedinated model. Measurement reliability, convergent and discriminant validity, path coefficients, mediation, moderation and model fit indices were all evaluated rigorously. The findings indicate that green purchasing brings a strong direct impact to the performance of the organization (0.125, p 0.05), whereas the majority of other green practices bring a non-significant effect. The reverse logistics are very much predictors of perceived competitive advantage (p = 0.001, 0.427), and competitive advantage is a strong predictor of organizational performance (p = 0.001, 0.502), which means full mediation. The leadership ability has a positive moderating effect but is not significant. The study is valuable as it shows that green practices produce performance fundamentally in the form of strategic competitive advantage as opposed to direct impacts, providing context-sensitive findings of sustainability strategies and supply chain decision-making. It also emphasizes the need to make selective investments on green, especially in the emerging economies.

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.

Aims: The current global business landscape demands an acute commitment of international businesses’ sustainable practices to attain a global sustainability agenda. This paper examines the intricate nexus of Multinational Enterprises' (MNEs) Corporate Social Responsibility (CSR) practices, particularly environmental innovation, business ethics, CSR reporting and their environmental performance, social performance, as well as the influence of their alignment with the United Nations Sustainable Development Goals (SDGs). Study Design: This quantitative study employed a Partial Least Squares Structural Equation Modeling (PLS-SEM). Place and Duration of Study: The study used data from Refinitiv Eikon workspace for 91 MNEs from the Middle East and North Africa (MENA) in year 2023. Methodology: The study used secondary data from Refinitiv Eikon workspace for 91 MNEs from MENA region using the Partial Least Squares Structural Equation Modeling (PLS-SEM). Results and Conclusion: The PLS-SEM’s results underline the potential and significant involvement of international businesses in shaping sustainable development, especially in developing and emerging countries. The findings further show that MNEs’ CSR practices particularly environmental and social performance and their adoption or alignment with the United Nations’ SDGs emerges as a pivotal approach to enhance MNEs’ contribution to MENA countries’ sustainable development and global sustainability agenda.

Voluminous studies use Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze data. One of the reasons for using PLS-SEM is when the structural model is complex. Studies employing complex structural models with many constructs and indicators lead to PLS-SEM selection for the analysis. The purposes of assessing the measurement model are to examine basic dimensions for construct variables, validate the dimensions, and determine the number of dimensions for each construct. Assessment of measurement model includes composite reliability and average variance extracted (AVE) to assess reliability and validity, respectively. This study tests the validity and reliability of the attitude construct in the context of compliance behavior of income zakat that other studies can use. This study assesses the measurement model to examine basic dimensions for construct variables, validate the dimensions, and determine the number of dimensions for each construct. Assessment of measurement model includes composite reliability and average variance extracted (AVE) to assess reliability and validity, respectively. This study hopes future research can adapt and adopts the attitude items used in this study in their future research.

Although the number of empirical applications of partial least–squares structural equation modeling (PLS-SEM) in tourism has increased in the last two years, Assaker, Huang, and Hallak have conducted the only assessment on the use of PLS-SEM in four studies and with a limited number of criteria. Thus, this study aims to critically analyze how the PLS-SEM method has been applied in 44 articles published in 11 leading tourism journals from 2000 to 2014 in terms of four key criteria: (1) themes explored and main motivations for using PLS-SEM; (2) characteristics of proposed models; (3) how the models were evaluated; and (4) the use of more advanced analyses within the method. The findings revealed that although applications in tourism have improved in recent years, problematic aspects in the application of PLS-SEM in tourism research still exist. The article provides suggestions on how to improve the use of PLS-SEM in future tourism applications.

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.