This study examines the influence of mental accounting, financial attitudes, financial knowledge, and financial self-efficacy on the financial behavior of diligent students in using fintech. This study differs from previous research because it uses a sample of students who already have a business and often use fintech. Data collection was carried out through the distribution of questionnaires to respondents. This study found that financial attitudes and self-efficacy had a significant effect on financial behavior, while financial knowledge had no significant effect on financial self-efficacy and mental accounting. Mental accounting significantly affects financial attitudes, financial behavior, and financial self-efficacy. These findings prove the importance of mental accounting in increasing the confidence and effectiveness of students who often use fintech and have a business in making financial decisions. This research contributes to developing the theory of planned behavior in the context of financial behavior. It reveals that financial literacy does not necessarily increase financial self-efficacy and mental accounting, especially among students who often use fintech and are just starting a business.

The agriculture sector and other agribusinessescan have a long-lasting effect on the environment. The present studyinvestigates the effect of Agricultural Supply Chain Management (ASCM), fromproducer to consumer, on Environmental Sustainability (ES) in the Alkharj governorateby collecting primary data from 312 respondents in the ASCM in Alkharj and byapplying Structural Equation Modelling (SEM). Moreover, the moderating roles ofeconomic and social sustainability in the nexus between ASCM and the ES arealso tested. The results of the analyses show that ASCM directly improves theES in the agriculture sector. Moreover, ASCM also improves both economic andsocial sustainability. Consequently, economic and social sustainability improvesthe ES. Thus, economic and social sustainability have positively moderated therelationship between ASCM and the ES. The results suggest that the governmentof Alkharj governorate should further improve the economic sustainability ofagribusinesses in Alkharj by providing incentives. Moreover, education andtraining programs should be initiated to improve social sustainability. Thus,both improved social and economic sustainability of agribusinesses could encouragesustainable practices to promote the ES in the whole ASCM in Alkharj.

The purpose of this study is to investigate the direct effects of environmental sustainability orientation (ESO) on green supply chain management (GSCM), ESO on sustainable performance (SP), and GSCM on sustainable performance (SP). It also examines the indirect effect of GSCM on SP through the mediating role of GSCM. Moreover, it tests the moderating role of environmental collaboration (EC) between GSCM and SP. A total of 155 survey questionnaires were collected from firms with ISO 14000 certification in the manufacturing sector in Algeria. The gathered data was examined using (PLS-SEM) model. The findings showed positive effects between ESO, GSCM, and SP. However, no such effect was detected for the moderating role of environmental collaboration on the links between GSCM and SP. The limitation of this study was the use of only firms with ISO 14000 certification, so future studies should consider a wider range of firms and different scales. Regarding environmental problems, firms in Algeria can apply ESO and GSCM to achieve sustainable performance.

This study aims to explore the effect of data analytics quality on company sustainability through operational performance as an intervening variable of Fintech Peer to Peer Lending (P2P) companies registered and licensed at the Financial Services Authority (known as OJK) Indonesia. This study is quantitative research using primary data collected through questionnaires and interviews. The data came from 104 company leaders and involved 91 Fintech P2P Lending companies registered and licensed at OJK until December 2023. Data were processed using statistical tools Structural Equation Modeling (SEM)-Lisrel. The result of processed data indicates that data analytics quality has a positive and significant effect on company sustainability through operational performance as an intervening variable. Data analytics quality with AI-based automation makes repetitive work operations easy, efficient and effective which has implications for increasing the sustainability opportunities of fintech companies.

The present study analyzed the relationship between the average annual temperature and the area of Amazonian forest in the departments of Peru during the period 2013-2021, using a panel data model with random effects. The data used come from the National Institute of Statistics and Informatics (INEI) and include the average annual temperature in degrees Celsius and the area of Amazonian rainforest in thousands of hectares, both disaggregated by department. Additionally, CO2 emissions resulting from the loss of tree cover, measured in megatons (Mt) of carbon dioxide equivalent (CO₂e), were considered as a control variable. The results revealed a positive and statistically significant relationship between the area of Amazonian forest and the average annual temperature, denoting that an increase of one thousand hectares in the extension of the forest corresponds to an increase of 0.0004 °C in temperature. In this sense, the finding contradicts the climate-regulating role played by forests, however, this is attributed to the influence of unobserved confounding variables that are linked to both forest area and temperature.

Job satisfaction and digital talent are topics of growing interest in the context of digital transformation. Digitalization is changing the way organizations operate and how employees perceive their work. The state and its administrative staff is no exception, as these capabilities are essential to perform operational tasks that underpin the public institution's documentary processes. This study investigates the influence of digital talent (independent variable) on job satisfaction (dependent variable), employing structural equation modeling (SEM) using WarpPLS software. Digital Talent is broken down into three sub-variables: Digital Competencies of Employees (DCE), Capacity for Digital Innovation and Creativity (CIDC) and Adaptability and Continuous Learning (ACL), while Job Satisfaction is measured through two sub-variables: Work Environment (WE) and Professional Development Opportunities (PDO). The analyses revealed that Capacity for Innovation and Digital Creativity (CIDC) has a significant impact on Work Environment, with a path coefficient (β) of 0.13 (p = 0.01). Similarly, adaptability and continuous learning (ACL) positively influence the work environment, with a path coefficient (β) of 0.10 (p = 0.04). In addition, a strong relationship was found between professional development opportunities (PDO) and work environment, with a path coefficient (β) of 0.68 (p < 0.001). For the relationship between digital competencies (DCE) and career development opportunities, the path coefficient was 0.10 (p = 0.04). Digital talent is a key predictor of job satisfaction in administrative staff. The results suggest that investing in the development of digital capabilities, especially innovation and creativity, as well as adaptability, is essential to improve the work environment and career development opportunities.

This study investigates the factors influencing the actual usage of freight forwarding services in Indonesia, focusing on the roles of desire, outcome expectancy, and perceived self-efficacy, with delivery risk and perceived trust acting as moderating factors. Grounded in Social Cognitive Theory (SCT), this study examines how personal cognitive factors and external risks influence users' attitudes and behaviors toward freight forwarding services. Data were collected from 616 respondents across Jakarta, Surabaya, and Makassar utilizing a structured questionnaire. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed to test the hypothesized relationships. The findings reveal that desire significantly influences both attitude and delivery risk, while attitude has a strong direct effect on actual usage. Outcome expectancy and perceived self-efficacy demonstrated weaker effects, particularly on attitudes, suggesting that other factors, such as trust and risk perceptions, play a more significant role in this context. Additionally, delivery risk was found to moderate the relationship between desire and attitude, while perceived trust did not moderate the link between attitude and actual usage. The research underscores the importance of trust-building and risk mitigation strategies for freight forwarding service providers in Indonesia. The study also provides theoretical contributions by applying SCT to the logistics sector and offers practical implications for enhancing service adoption in emerging markets.

The swift growth of online commerce has significantly impacted the expedition service industry. As online shopping becomes increasingly prevalent, reliable shipping service has become crucial. Therefore, this study aims to determine the correlation between service quality, customer perceived value, and trust, as well as their impact on customer satisfaction within the expedition service industry. A survey was carried out through various messaging platforms, such as WhatsApp and Telegram, to reach users. Data were then obtained from 165 respondents, who were users of the 8 most popular expedition services in Indonesia (including J&T, JNE, SiCepat, Ninja Express, SAP, and others), followed by PLS-SEM analysis. The results showed that the three independent variables positively influenced customer satisfaction. In addition, trust acted as a mediator, indirectly affecting both service quality and customer perceived value. These results are expected to serve as a foundation for developing more efficient and contextually relevant strategies for expedition companies in the future.

This paper analyses the possible determinants that induced Silicon Valley and First Republic Bank to Bankruptcy. We employ financial statements for a sample of Banks in line with the business core of Silicon Valley Bank. The period under assessment ranges from 2006-2022. We estimate an indicator of Bank Efficiency using the technique Data Envelopment Analysis (DEA). The latter indicator is used as the primary step to analyze failure within sample banks. According to the CAMEL model, macroeconomic variables are non-significant but relevant variables that drive failure were: Bank Efficiency, Capital adequacy, Earning ability, and Liquidity position ratio. Our study is relevant for any policy making to prevent any future bank failure.

This study sought to determine how CAATS, corporate governance (CG), and EIAF positively and directly influence the quality of financial reports (QFR). In addition to identifying the moderating effect of EIAF on the links between CAATS, CG and QFR in Saudi commercial banks. To this end, data was collected from 293 participants, including administrative managers, board members, internal auditors, certified public accountants, and staff members from the audit and internal audit departments as well as the accounting departments. Using structural equation modelling (SEM) via SmartPls, data was analyzed. The study showed that QFR is positively and significantly affected by CAATS, CG, and EIAF. Moreover, EIAF does not moderate the effect of CAATS and CG on QFR. Hence, this study enriches accounting literature and has implications for both practitioners and policymakers.