How Does Sustainability Governance Shape the Green Finance and Climate Nexus?

The transition toward environmentally sustainable financial systems has become a strategic imperative for organizations, particularly in emerging economies where climate vulnerabilities are high and institutional support is limited. This study examines how digital transformation drives green finance adoption among Small and Medium Enterprises (SMEs) in Pakistan, emphasizing the mediating role of Corporate Social Responsibility (CSR) and the moderating influence of Project Management Maturity (PMM). Guided by the Dynamic Capabilities Theory (DCT), the research posits that green finance adoption is not merely a technological outcome but a dynamic capability shaped by ethical commitment and organizational execution capacity. Adopting a quantitative, cross-sectional design, data were collected from 375 SME managers through structured questionnaires. Partial Least Squares Structural Equation Modeling (PLS-SEM) using SmartPLS 4 was employed to test the hypotheses. The results revealed a significant positive effect of digital transformation on green finance adoption, affirming the role of digital technologies in enhancing sustainability practices. CSR was found to mediate this relationship, illustrating that ethical and social responsibility practices are essential in translating digital capacities into green finance behaviors. PMM demonstrated a significant negative moderating effect, indicating that high levels of formalized project structures may limit the agility needed for effective green finance implementation. The study extends theoretical discourse by integrating digital, ethical, and managerial dimensions into a unified framework for understanding green finance behavior. Keywords: Digital Transformation, Green Finance Adoption, Corporate Social Responsibility, Project Management Maturity, Dynamic Capability Theory

Background: Banks are adapting their strategies to align with environmental sustainability through green finance. In Indonesia, green finance is gaining attention, but challenges like inadequate employee attitudes have hindered its progress towards green finance. Purpose: This research aims to understand bank employee’s behavioral intentions as promoters in implementing green finance by examining the impact of attitude, self-efficacy, subjective norms, and behavior control based on the theory of planned behavior, as well as testing whether internal measures moderate the relationship between independent and dependent variables. Design/methodology/approach: This research uses a quantitative approach with a sample of 250 bank employees in Batam, Indonesia. Data were collected via Google Forms from October 16, 2023, to March 6, 2024, and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings/Result: The study found that attitude, subjective norms, and behavioral control significantly impact bank employees' behavioral intentions in Batam City, while self-efficacy does not. Additionally, internal measures do not moderate the influence of attitude, self-efficacy, subjective norms, and perceived behavioral control on behavioral intention.Conclusion: This study explores how attitudes, self-efficacy, subjective norms, and perceived behavioral control influence bank employees' intentions to adopt green finance, moderated by internal measures, using the Theory of Planned Behavior. Understanding these factors can guide the banking sector in supporting the Sustainable Development Goals and achieving the 2030 Agenda.Originality/Value (State of The Art): While research on green finance in Indonesia’s banking sector is growing, studies on Batam City are limited. Given Batam's strategic economic role, understanding local banks' adoption of green finance is essential. This study explores the attitudes, behaviors, and challenges of bank employees in Batam, offering insights into the factors influencing green finance adoption in the region. Keywords: bank, behavioral intention, green finance, internal measures, theory of planned behavior

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.

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.

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.

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

Effect of strategic imperative on technology adoption in academic libraries in Pakistan: A TAM & PLS-SEM analysis.

This study investigates the interconnections between sustainability practices, innovation, market integration, and Global Value Chain (GVC) governance within Ethiopia’s Integrated Agro-Industrial Parks (IAIPs). It addresses key challenges faced by IAIPs in promoting sustainability, fostering innovation, and achieving global market integration, providing insights into how sustainability-driven innovation can enhance market access and competitiveness. A quantitative, deductive research design was adopted, utilizing a stratified sampling technique across two IAIPs, Bulbula and Yirgalem. Data were collected through questionnaires from 160 respondents, and Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to examine the direct and indirect relationships among sustainability, innovation, market integration, and GVC governance. The findings demonstrate that sustainability practices significantly promote innovation (β = 0.504, p < 0.001), which in turn boosts market integration (β = 0.422, p < 0.001) and strengthens GVC governance (β = 0.589, p < 0.001). Mediation analysis indicates that innovation partially mediates the effect of sustainability on market integration, while both innovation and market integration fully mediate sustainability’s impact on GVC governance. This research underscores the critical role of sustainability-driven innovation in improving market integration and GVC governance in IAIPs, suggesting that incorporating sustainability practices can enhance global competitiveness. The findings provide valuable insights for policymakers and industry stakeholders seeking to strengthen IAIPs' global market position.

Customers are displaying heightened awareness and involvement in their banking arrangements, and they are actively assessing and remembering information to make informed decisions regarding the allocation of their financial resources towards environmental protection solutions such as clean energy, sustainable construction, climate change control and social protection. Based on the current theoretical gap of factors influencing customer satisfaction and thereby encouraging continued engagement in green finance initiatives, this study aims to identify the factors influencing customer satisfaction as a means of fostering greater participation in green finance amongst customers of commercial banks in Ho Chi Minh City. Using data from a survey of 479 individuals who are customers at commercial banks in Ho Chi Minh City, this study analyses and evaluates the impact of factors influencing customer satisfaction and the role of customer satisfaction in green finance continuance behaviour. Combining basic analysis techniques in quantitative research such as statistics, evaluation of Cronbach’s alpha reliability, exploratory factor analysis (EFA), measurement models and Partial Least Squares structural equation modelling (PLS-SEM) from SPSS and SMART PLS software. the results of this research indicate that: (1) Green Banking initiative (GB), Information Support (IS) and Emotional Support (ES) positively impact Customer Satisfaction (SA); (2) Customer Satisfaction (SA) positively impacts Green Finance Continuance Behaviour (GF).

This study aims to analyse what factors can affect the impact of acid mine drainage on the environment and society. With a sample of research respondents being the community around the company, totalling 200 people. The variables used consist of the environmental variable (X3) as the dependent variable and independent variables, namely acid mine drainage (X1) and community social (X2), with each variable being measured by its indicators. This questionnaire is used to measure Statements compiled using the Likert scale with five respondent answers to consumer satisfaction, namely: Strongly Agree (SS), Agree (S), Hesitant (RR), Disagree (TS), and Strongly Disagree (STS). The data analysis technique used is partial least square-structural equation modelling (PLS-SEM) which is used to predict and develop theory. Partial Least Squares Structural Equation Modelling (PLS-SEM) is a robust and versatile statistical technique commonly employed for data analysis. PLS-SEM is particularly well-suited for exploratory research and when dealing with complex models, small sample sizes, or non-normal data distributions. It allows researchers to simultaneously assess the measurement and structural models, making it an effective tool for understanding complex relationships between variables. Based on the results of the analysis, it is known that Acid mine drainage affects the environment and society with a rms theta model of 0.470.

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.

The role of students is very important in developing entrepreneurship. The research aims to determine the effect of learning and institutional support on entrepreneurial behavior with self-efficacy as a moderating variable. This research is quantitative research and the sample is all 32 STIE Mars Pematangsiantar students who have participated in the entrepreneurship program. The analysis used is the Partial Least Squares Structural Equation Modeling (PLS-SEM) method. The results show a significant positive influence of institutional support on entrepreneurial behavior, a significant relationship between learning and entrepreneurial behavior, a significant relationship between learning and self-efficacy, and a significant relationship between self-efficacy and entrepreneurial behavior. There is an insignificant relationship between institutional support and self-efficacy. With these findings, it is hoped that entrepreneurial learning and institutional support can contribute to the development of entrepreneurial strategies at the University.

Globally, wetlands have been severely damaged due to natural environment and human activities. Understanding the spatiotemporal dynamics of wetlands and their driving forces is essential for their effective protection. This study proposes a research framework to explore the interaction between the natural environment and human activities and its impact on wetland changes, by introducing Partial Least Squares Structural Equation Modeling (PLS-SEM) and Geographically Weighted Regression (GWR) model, then applying the methodology in Wuhan, a typical wetland city in China. The validity and reliability evaluation indicated that the PLS-SEM model is reasonable. The results showed that the area of wetlands in Wuhan decreased by 10.98% in 1990–2018 and four obvious direct pathways of influence were found. Positive soil and terrain conditions are conducive to maintaining wetlands, while rapid urbanization drastically reduce the distribution of wetlands. It is remarkable that the impact of climate on wetlands is gradually shifting from positive to negative. Furthermore, four potential indirect impact pathways affecting wetland distribution shown that urbanization and climate enhance the negative impact of terrain on wetland distribution, while their impacts on soil weaken soil's direct positive impact. This study provides a quantitative methodology for determining the causes of wetland loss; it can also be applied to other cities or regions, which is essential for applying more effective measures to protect wetlands.