This research aims to investigate the impact of structural transformation and economic freedom on non-oil economic growth in Saudi Arabia over the period 1996–2023. Using an Autoregressive Distributed Lag (ARDL) framework, we examine both short-run dynamics and long-run equilibrium relationships among key determinants, including industrial structural change, economic freedom, industrial employment, domestic credit, foreign direct investment, and urban population. The research model consists of measures of industrial structural change, economic freedom, industrial employment, domestic credit to the private sector, foreign direct investment, and urban population, along with interaction terms between structural change and economic freedom. The results show that structural transformation and economic freedom are significant drivers of non-oil GDP growth, with their interaction amplifying the positive effects of industrial diversification under strong institutional conditions. The findings suggest that Saudi Arabia’s Vision 2030 objectives can be achieved by promoting high-productivity sectors, strengthening market-oriented institutions, and supporting industrial employment, investment, and urban-based economic activities to sustain long-term non-oil growth and reduce reliance on oil revenues.
This study aims to examine and understand the influence of situational leadership, competence, and organizational culture on the performance of civil servants in the Indonesian National Police at Biddokkes Polda Southeast Sulawesi, with work motivation as an intervening variable. The population in this study consists of civil servants and police personnel working at Biddokkes Polda Southeast Sulawesi, totaling 135 individuals, all of whom were used as research respondents. The analytical tool used in this study is SmartPLS. The results show that situational leadership has a positive and significant effect on the work motivation of civil servants in the Indonesian National Police at Biddokkes Polda Southeast Sulawesi. Situational leadership also has a positive and significant effect on employee performance. Competence has a positive and significant influence on work motivation, and further, competence significantly affects the performance of civil servants in the Indonesian National Police at Biddokkes Polda Southeast Sulawesi. Organizational culture positively and significantly influences work motivation, and also exerts a positive and significant effect on employee performance. Work motivation itself has a positive and significant impact on the performance of civil servants at Biddokkes Polda Southeast Sulawesi. Furthermore, situational leadership has a positive and significant effect on employee performance when mediated by work motivation. This means that situational leadership not only enhances performance directly but its effect becomes substantially stronger when channeled through work motivation. Competence also has a positive and significant influence on performance when mediated by work motivation, indicating that employees with strong competencies tend to feel more confident, more capable of completing tasks, and more prepared to meet job demands—conditions that naturally elevate motivation and encourage improved performance. Additionally, organizational culture has a positive and significant impact on employee performance when mediated by work motivation, implying that a strong and supportive organizational culture fosters higher motivation, which in turn enhances employee performance.
Professional scepticism is a critical attribute for future accountants because it underpins sound audit judgment and ethical decision-making (IAASB, 2022). However, recent concerns raised by the Malaysian Institute of Accountants (MIA, 2020) and the Committee to Strengthen the Accountancy Profession (CSAP, 2014) indicate that many accounting graduates lack the sceptical disposition required by the profession. Drawing on Hurtt’s (2010) model of professional scepticism, this study investigates the influence of two major domains which are sceptical mindset that consists of questioning mind, search for knowledge and suspension of judgement, and sceptical attitude that consists of self-determination, self-confidence and interpersonal understanding on the level of professional scepticism among accounting students. Furthermore, this study introduces university engagement as a moderating variable and proposes that active academic and co-curricular participation strengthens the relationship between students’ sceptical traits and their professional scepticism. This study will employ a quantitative research design using survey data collected from final-year accounting students at a Malaysian public university. Partial Least Squares Structural Equation Modelling (PLS-SEM) will be applied to test the hypothesised relationships and to examine the moderating effect of university engagement. The findings are expected to contribute to theory by extending Hurtt’s (2010) model within the context of Malaysian higher education and to practice by offering insights for universities and policymakers to enhance professional scepticism development through curriculum design and student engagement strategies.
This study investigates the impact and spillover effects on major cryptocurrencies, namely Bitcoin (BTC), Ethereum (ETH) and Tether (USDT) amid geopolitical shocks, employing a Vector Autoregressive, Granger Causality, Variance Decomposition and to test the spillover impact, the approach Time-Varying Parameter Vector Autoregression (TVP-VAR) model is implemented. Drawing on daily data from November 25th, 2019, to September 19th, 2025, we incorporate traditional safe-haven proxies (GC.F) and risky assets (CL.F); global equi-ty (URTH) and benchmarks like the (VIX) volatility index, Economic Policy Uncertainty (EPU) index. Our findings reveal that BTC and ETH exhibit time-varying hedge properties during low-to-moderate volatile episodes but fail as safe havens during extreme shocks. USDT demonstrates superior stability as a digital safe-haven. Policy implications underscore the maturation of crypto markets for portfolio diversification, contingent on shock intensity.
It is of utmost importance to monitor the financial performance of banks to ensure that they are adhering to regulatory compliance guidelines set by the Reserve Bank of India. Small finance banks fall under the niche category of banks that are established in order to pro-mote financial inclusion. Capital Small Finance Bank is the first bank that was licensed as an SFB in 2016. Currently, there are 11 small fi-finance banks licensed by the RBI. Recently, Fincare SFB was merged with AU SFB. This study is going to measure the financial performance of all 11 small finance banks on the basis of the CAMEL model framework, which includes the parameters of capital adequacy, asset quality, management efficiency, earnings, and liquidity. Various financial indicators have been used to comprehensively analyse all the parameters. Secondary data has been collected for the year 2024 from the RBI’s database and annual reports of all the SFBs. Ranking method and ANOVA have been used for research analysis. It finds out that the overall performance of Capital SFB and ESAF SFB has been the best; however, North East SFB has to work vigorously on its Asset quality and its management efficiency.
Blended learning has become a crucial factor in corporate training, yet its precise pathway to enhancing employee performance remains unexplored. This study investigates the indirect mechanisms through which blended learning effectiveness (BLE) impacts employee performance (EP), proposing soft skill development (SSD) and knowledge acquisition (KA) as mediating variables. Data were collected from 150 employees with prior blended learning experience. Structural equation modeling was deployed to test a parallel mediation model. The results show that blended learning strongly and positively affects both soft skill development and knowledge acquisition. However, it shows no significant direct effect on employee performance. Instead, soft skill development and knowledge acquisition fully mediate this relationship, serving as the mechanisms through which blended learning translates into improved performance. The model exhibits a robust fit and explains a significant portion of performance variance. The study posits that blended learning enhances employee performance not directly, but by first building essential interpersonal competencies and job-relevant understanding. These findings offer both theoretical clarity for training models and practical guidance for designing impactful corporate learning programs.
The Resource-Based View (RBV) has long been recognized as a cornerstone of strategic management, emphasizing the role of firm-specific resources in achieving sustainable competitive advantage (SCA). Two prominent frameworks derived from RBV, VRIN and VRIO, offer systematic approaches to evaluating resources based on Value, Rarity, Inimitability, Non-substitutability (VRIN), and Organization (VRIO). This conceptual paper critically examines the theoretical underpinnings, comparative distinctions, and strategic implications of VRIN and VRIO frameworks. By integrating insights from both models, a unified conceptual framework is proposed, elucidating the process through which resources are transformed into sustained competitive advantage. The paper also identifies managerial applications and highlights potential avenues for future research, particularly in dynamic and technology-driven industries. This unified perspective is particularly relevant for firms operating in dynamic industries requiring both resource uniqueness and adaptive organizational capacity. The paper aims to bridge the gap between theoretical resource evaluation and actionable strategy, offering an updated contribution to resource-based strategic management literature. The study also contributes to the literature by providing a comprehensive, real conceptual analysis, offering academics and practitioners a practical lens to evaluate and leverage organizational resources effectively.
The United Nations introduced 17 Sustainable Development Goals in 2015, which provide a blueprint for peace and prosperity for the people and planet. Within these, 8 goals can be achieved through the utilisation of blockchain technology. Thus, current research aims to identify trends in blockchain technology to achieve sustainable development. For this purpose, literature available in the current decade (2016 to 2025) was extracted from the Scopus database after systematic filtering and analysed using software such as RStudio, VOSviewer, and Microsoft Excel. The results of this research show that blockchain technology for sustainable development is growing and attracting increasing attention from researchers. Additionally, the study identified the domination of articles and conference papers; however, review articles have a significant influence. Based on this research, the authors suggest that future researchers continue their work, especially in qualitative studies on blockchain technology, to achieve sustainable development, bridge the gap between qualitative and quantitative research, and garner researchers' attention. Furthermore, researchers can focus on integrating blockchain technology into supply chain management, particularly in the agricultural sector, given its significant impact.
This study aims to analyze the extent to which system quality and information quality influence users’ perceived usefulness and user satisfaction with the SISKEUDES system. An explanatory quantitative approach was employed, using Structural Equation Modeling–Partial Least Squares (SEM-PLS) as the analytical technique. The study population consisted of village officials who use SISKEUDES in regency-level governments across North Sumatra Province, with a sample of 303 respondents. Data were collected through questionnaires distributed via Google Forms and analyzed using SmartPLS version 4. The results indicate that both system quality and information quality have a positive and significant effect on perceived usefulness and user satisfaction. Furthermore, perceived usefulness significantly influences user satisfaction and acts as a partial mediating variable in the relationship between system quality, information quality, and user satisfaction. These findings are consistent with the Technology Acceptance Model (TAM), which emphasizes that information system effectiveness is shaped by technical system quality, the quality of information produced, and users’ perceptions of system usefulness. The findings of this study are expected to provide a foundation for policy formulation and for improving both system performance and information quality in the future development of SISKEUDES.
This paper will focus on the role played by the electronic human resource management (E-HRM) in business performance using a combined mediate-moderate model. The study examines the immediate effect of E-HRM practices on the outcome and measures the mediating force that strengthens the relationship and the moderating force that changes the strength of the relationship. There were five hypotheses that were formulated to explain the role of E-HRM in enhanced performance in digitally inclined and fast-paced trading environment. The research design used was the quantitative descriptive method of study, where 387 valid responses were obtained by distributing 500 questionnaires. The results show that E-HRM is positively related to the performance of the business, and the mediating construct enhances the impact since it increases the strength of internal processes associated with digital workflow, decision accuracy, and consistency of operations. The moderating variable also has an effect on the relationship as it increases or decreases effectiveness of E-HRM based on the degree of the moderating variable within the trading environment. This study benefits the literature that exists by presenting E-HRM as a resource that can facilitate the progress of performance by digital structuring, better responsiveness, and operational alignment. It further highlights the concurrent nature of the role of mediation and moderation in creating flexibility and business lasting leverage. The limitations and future study directions are provided in the conclusion.
Background: The integration of intelligent manufacturing technologies and corporate sustainability has emerged as a critical research frontier in the era of Industry 4.0. While Environmental, Social, and Governance (ESG) performance increasingly shapes corporate valuation and stakeholder relations, the economic mechanisms through which intelligent manufacturing influences ESG outcomes remain theoretically underdeveloped and empirically underexplored, particularly in emerging market contexts where institutional environments differ substantially from developed economies. Methods: Exploiting China's Intelligent Manufacturing Pilot Demonstration Projects (IMPP) as a quasi-natural experiment, this study employs a staggered difference-in-differences (DID) design with 18,426 firm-year observations from 2,149 Chinese A-share manufacturing companies during 2009-2023. We examine direct effects using two-way fixed effects models, investigate mediating mechanisms through the Baron-Kenny approach supplemented by Sobel tests, and explore heterogeneous effects across ownership structures, pollution intensities, and competitive environments using split-sample analysis with Chow tests for coefficient equality. Results: Intelligent manufacturing significantly enhances enterprise ESG performance (β = 0.245, p < 0.01), representing a 5.3% improvement relative to the sample mean. This finding demonstrates robust consistency across parallel trend tests, placebo simulations (500 iterations), propensity score matching (PSM-DID), and instrumental variable (IV-2SLS) estimations. Mechanism analysis reveals three significant transmission channels: green innovation (mediating 24.6% of total effect, β = 0.186, p < 0.01), resource allocation efficiency (16.6%, β = 0.142, p < 0.01), and synergistic governance (7.9%, β = 0.098, p < 0.05). Heterogeneity analysis demonstrates significantly stronger effects for non-state-owned enterprises (β = 0.312 vs. 0.168, χ² = 8.45, p < 0.01), heavy-polluting industries (β = 0.356 vs. 0.186, χ² = 12.67, p < 0.01), and high-competition markets (β = 0.298 vs. 0.152, χ² = 5.23, p < 0.05). Sub-dimensional analysis reveals that environmental performance benefits most substantially (β = 0.324), followed by social (β = 0.218) and governance (β = 0.142) dimensions. Conclusions: This study establishes intelligent manufacturing as an economically significant pathway for enhancing corporate ESG performance in emerging markets, with heterogeneous effects contingent upon ownership structure, industrial characteristics, and competitive dynamics. These findings advance theoretical understanding of technology-sustainability linkages, provide empirical foundations for evidence-based industrial policy design, and offer practical guidance for managers navigating the dual imperatives of technological transformation and sustainable development.
Background: Augmented and Virtual Reality are quickly becoming key players in the cosmetics industry, offering consumers more interactive and engaging shopping experiences. Despite their growing use, there is still a gap in Research on how these technologies influence consumer behaviour, especially when it comes to buying cosmetic products. This systematic review brings together existing studies to examine the effects of AR/VR on the ease of use, consumer attitudes, and purchase intentions in digital cosmetic shopping. Objective: The main aim of the study is to examine the way AR and VR influences perceived ease of use in cosmetics shopping, to analyse the influence of AR and VR technologies on consumer attitudes toward cosmetic products, to evaluate how AR and VR affects purchase intentions in the cosmetics industry and to explore the psychological and emotional factors of consumers using AR and VR for cosmetic purchases. Methods: Following PRISMA guidelines, studies published between 2010 and 2025 were analysed. A thorough search was conducted using databases such as PubMed, Scopus, and Web of Science, with carefully constructed Boolean search strings targeting key concepts in AR/VR, cosmetics, and consumer Behaviour. The selection process was clearly outlined with a PRISMA flowchart, and the quality of the studies was assessed using the Mixed Methods Appraisal Tool (MMAT). Out of 180 studies initially identified, 140 were included in the qualitative synthesis and 40 in the quantitative analysis. Results: The results reveal that AR/VR significantly enhance the perceived ease of use in digital cosmetic shopping, which in turn leads to more positive consumer attitudes and higher purchase intentions. Immersive experiences—such as virtual makeup try-ons and 3D product visualizations—not only ease the mental effort required but also help build trust and forge an emotional connection with the brand. Significantly, most of the studies reviewed met high methodological standards. Conclusions: AR/VR technologies are transforming the cosmetic shopping experience by making it more user-friendly and engaging, while also increasing consumer confidence in their purchases. Future research should include longitudinal studies to evaluate the sustained impact of AR/VR on brand loyalty, investigate the integration of AI for enhanced personalization of those experiences and conduct cross cultural analyses to capture variations in consumer response.
Purpose: This study investigates how external integration, supplier and customer integration, shape supply chain capabilities in Indonesian manufacturing firms, using the Dynamic Capability View as the theoretical foundation. Methodology: A quantitative approach was applied using survey data collected from 115 supply chain professionals. The proposed model was analyzed through Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings: Supplier integration significantly enhances sensing and seizing capabilities, while customer integration shows no significant effect. Neither integration type influences reconfiguration capability, highlighting the role of internal organizational mechanisms in capability development. Originality: This study clarifies how upstream and downstream integration contribute differently to the formation of dynamic capability. It extends theoretical understanding of supply chain capability development in emerging economies and offers practical guidance for strengthening cross-boundary collaboration.
This study examines the role of overconfidence bias in shaping financial decision-making among culinary MSMEs in Banjarmasin, Indonesia. Although overconfidence has been recognized as a behavioral bias influencing financial decisions, empirical evidence in the context of MSMEs in developing countries is still limited. This study used a quantitative approach, collecting data from 80 culinary MSMEs, which were then analyzed using Partial Least Squares–Structural Equation Modeling (PLS-SEM). Overconfidence was operationalized as a multidimensional construct consisting of overestimation, overprecision, and illusion of control. The results showed that only the illusion of control dimension had a positive and significant effect on financial decision-making, while overestimation and overprecision did not show a significant effect. This finding indicates that MSMEs tend to rely on subjective perceptions of self-control rather than measurable financial analysis in making financial decisions. This study contributes to the behavioral finance literature by highlighting the heterogeneity of overconfidence dimensions in the micro-enterprise context and providing practical implications for the development of behavior-based financial literacy programs for entrepreneurs in emerging markets.
Accurate macroeconomic forecasting is essential for effective policy formulation, financial planning, and economic stability, yet it remains challenging due to structural changes, economic shocks, and complex nonlinear interactions among economic indicators. Traditional time series models often struggle to capture such complexities, while standalone machine learning approaches may overlook temporal dependencies. To address these limitations, this study proposes a Hybrid Predictive Framework for Macroeconomic Forecasting (HPFMF) that integrates complementary strengths of time series and machine learning models. Using annual macroeconomic data for more than 200 countries spanning 2010–2025 from the World Bank Open Data API, the framework applies systematic preprocessing, including missing value handling, winsorization, logarithmic transformation, and feature scaling. A time series hybrid combining ARIMA, Prophet, and Exponential Smoothing captures temporal dynamics and structural shifts, while a stacked machine learning ensemble of Random Forest, XGBoost, and Support Vector Regression models nonlinear interdependencies. These layers are integrated through validation-based weighting to generate robust forecasts. Empirical results show that the proposed framework achieves superior performance, with significant reductions in forecasting errors and an R² of 0.92. Country-wise and temporal validations confirm strong generalizability, demonstrating the framework’s effectiveness for reliable, policy-oriented macroeconomic forecasting.
This study examines the impact of Agile Coaching on Organizational Agility and Organizational Performance, with particular attention to the moderating roles of Neurological Dominance, Spirituality in the Workplace, and Organizational Culture. Using a quantitative research design, the study applies Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze the direct relationships among the constructs and the moderating effects within the proposed model. Data were collected from 160 volunteers and employees of the Halaqah Silsilah Ilmiah (HSI) Foundation in Indonesia who participated in the Agile Hijrah Coaching program conducted in collaboration with the International Open University. The findings indicate that Agile Coaching significantly enhances both Organizational Agility and Organizational Performance. Organizational Agility also shows a significant positive association with Organizational Performance. Moreover, Neurological Dominance and Spirituality significantly moderate the effects of Agile Coaching on agility and performance, thereby strengthening coaching effectiveness. In contrast, Organizational Culture does not exhibit a significant moderating effect. Although the study is limited to a single organizational context, the results offer important implications for both theory and practice. Organizations are encouraged to implement agile coaching initiatives with greater awareness of cognitive and spiritual diversity to improve adaptability and performance, while aligning cultural values more deliberately with agile principles. This study contributes to the literature by highlighting the roles of cognitive and spiritual factors as key contextual moderators in agile coaching, providing a comprehensive perspective on agile transformation in dynamic organizational environments.
This study examines the dynamic interdependence between Clean Energy indices, AI Robotics Index, and selected NFT and DeFi tokens across three major geopolitical crises: COVID-19 pandemic (January 2020–April 2021), Russia-Ukraine war (February 2022–December 2022), and Iran-Israel conflict (October 2023–June 2024). Employing continuous wavelet transform, wavelet coherence, and partial wavelet coherence techniques, we decompose relationships across short-term, medium-term, and long-term horizons using daily data from Bloomberg. Descriptive statistics reveal fundamental differences between sustainable investments and digital assets: Clean Energy (mean: 0.0008, variance: 0.0004) and AI Index (mean: 0.0003, variance: 0.0002) demonstrate positive returns with low volatility, while NFT and DeFi tokens exhibit negative average returns and substantially higher volatility, with AAVE showing extreme kurtosis (773.27) and variance (0.0167). Wavelet coherence analysis reveals crisis-dependent and scale-specific patterns. During COVID-19, only short-term and medium-term coherence emerged, indicating transitory speculative relationships. The Russia-Ukraine war marked a structural shift, with AAVE demonstrating long-term coherence with Clean Energy, suggesting deeper market integration driven by energy market disruptions. The Iran-Israel conflict exhibited the most complex patterns, with broader long-term coherence across ENJ Coin, Theta, Synthetix, Maker, and SUPERf, indicating structural convergence between energy transition narratives and selected DeFi/NFT projects. These findings demonstrate that NFT/DeFi-sustainable investment relationships are crisis-dependent, scale-specific, and selectively integrative, with significant implications for portfolio diversification strategies and systemic risk monitoring during geopolitical crises.
Gender equality is a key focus of the Sustainable Development Goals (SDGs), as stated in Goal 5, which aims to end discrimination against women and ensure that women can participate and have equal opportunities to become leaders. According to the Global Gender Gap Report 2022, Indonesia ranks 92nd out of 146 countries, with a Global Gender Gap Index (GGGI) score of 69.7%. This study aims to: (1) Evaluating glass ceiling perception towards women’s career advancement for accounting profession through survey; (2) Providing empirical evidence whether women experience glass ceiling perception in the workplace; and (3) Providing empirical evidence confirming whether the perception of glass ceiling towards women in the workplace are recognized by men. The method used in this study was quantitative, utilizing primary data collected through a questionnaire distributed to respondents. Hypothesis testing was conducted using logistic regression analysis. Four variables tested were bias, marital status, parenthood, and external. Based on the results, it was found that bias, marital status, parenthood, and external variables had a significant influence on the perception of the glass ceiling towards women’s career advancement for the accounting profession in Indonesia. This conclusion has been drawn according to data collected from 106 respondents, who are currently working in the accounting field in Indonesia.
This study investigates the volatility dynamics of equity and debt mutual funds using advanced econometric techniques, specifically GARCH, EGARCH, and MGARCH models. By analysing daily returns of nifty fifty index and selected mutual funds comprising both debt and equity, the research aims to uncover patterns of volatility persistence, sensitivity to market shocks, and the distinct behaviors exhibited by different fund types. The findings reveal that both equity and debt funds display significant, though moderate, volatility clustering, as indicated by a consistent GARCH term across models. The arch term catches the short-term shocks that have a consistent effect on all funds, highlighting the pervasive effect of sudden market events. Notably, equity funds demonstrate a quicker stabilization following shocks, reflecting their adaptive nature, while debt funds exhibit prolonged volatility responses, underscoring their sensitivity to macroeconomic conditions. The MGARCH analysis further distinguishes the volatility profiles within the debt segment, showing that not all debt instruments react similarly to market disturbances. Portfolio managers and investors can use these results as equity funds may be better suited for dynamic investment strategies and higher risk tolerance, whereas debt funds require more conservative management and careful monitoring of external economic factors. The study also discusses the practical challenges and limitations of applying GARCH-family models, such as data constraints, model assumptions, and the omission of exogenous variables. Despite these limitations, the research provides a robust framework for understanding and managing mutual fund volatility, offering actionable insights for optimizing asset allocation, enhancing risk management, and improving investor communication. Future research is encouraged to incorporate broader datasets, alternative modelling approaches, and additional market factors to further refine volatility forecasting and portfolio strategy.
This research examines the connection between information ambiguity, information overload, and purchase intention in the context of Micro, Small and Medium Enterprises (MSMEs) in East Java. Utilizing the Stimulus-Organism-Response (SOR) theory, the study employs me-diation regression with SPSS PROCESS, to test the proposed hypothesis. Data was collected from 535 participants out of the total of 550 who were successfully recruited, with an overall response rate of 97%. The results indicate that information ambiguity has a low direct im-pact on purchase intention (β = 0.0821). Nevertheless, when assessing the indirect effect, it was discovered that information ambiguity can-not affect purchase intention in the absence of information overload (β = 0.3641). These findings have theoretical implications, highlighting the importance of extending or modifying the SOR concept to account for the role of information overload as a mediator in the relationship between stimulus (information ambiguity) and response (purchase intention). From a managerial perspective, these findings emphasize the significance of MSMEs carefully managing the information they convey to consumers and improving their understanding of consumer behavior and the factors that influence purchasing decisions. By doing so, they can develop more effective marketing strategies and strengthen their relationships with consumers, thus supporting the growth of their business in a competitive environment.
