Authors Statistics from 10 Countries
| Country | Count of Articles |
|---|---|
| United Arab Emirates | 2 |
| Bangladesh | 1 |
| Indonesia | 10 |
| India | 1 |
| Madagascar | 1 |
| Turkey | 1 |
| Sierra Leone | 1 |
| Canada | 1 |
| Mali | 1 |
| Nigeria | 3 |
Articles
Can Digital Transformation Reduce Government Corruption? A Meta-Analysis
Abstract
This meta-analysis examines the potential of digital transformation in reducing government corruption by synthesizing findings from 17 empirical studies published in the last five years. Using the PRISMA protocol, a comprehensive literature search was conducted, and studies were screened for eligibility. The meta-analysis revealed a substantial negative correlation between corruption and digitalization/e-government, with an overall effect size of -0.93 (95% CI: -1.18 to -0.68) based on the Random Effects Model. The results suggest that higher levels of digital transformation are associated with lower levels of corruption. However, the study also highlights the complex and context-dependent nature of this relationship, as cultural, economic, and institutional factors can moderate the impact of digitalization on corruption. The findings underscore the importance of investing in digital infrastructure, promoting digital literacy, and fostering ethical governance practices to effectively combat corruption through digital transformation.
Read full articleAssessing Investment Risk in the Post-Pandemic Entertainment Industry: A Statistical Analysis of Portfolio Returns and Risk Measures
Abstract
This study examines the risk-return profiles of Warner Bros and Walt Disney stocks and analyzes their portfolio optimization potential in the post-pandemic entertainment industry landscape. Using daily stock data obtained from Yahoo Finance, we employ both traditional statistical analysis and Monte Carlo simulation techniques to derive robust estimates of expected returns and risk parameters. Our Value at Risk (VaR) analysis at multiple confidence levels (99%, 95%, and 90%) reveals distinct risk characteristics between the two stocks, with Walt Disney demonstrating more favorable downside protection despite similar historical return patterns. Monte Carlo simulations indicate significantly higher potential returns than suggested by historical data alone, with expected daily returns of 0.803% for Warner Bros and 0.789% for Walt Disney. Portfolio analysis with varying asset allocations demonstrates meaningful diversification benefits despite the substantial correlation (0.657) between the stocks. The optimal portfolio allocation favors a higher weight to Walt Disney (80%) compared to Warner Bros (20%), achieving the highest Sharpe ratio (0.247) and the lowest VaR at 99% confidence (-6.68%). These findings highlight the importance of comprehensive risk assessment tools in portfolio construction, particularly for industries undergoing structural transformation. The study contributes to sector-specific portfolio analysis literature by providing detailed insights into risk-return dynamics of major entertainment stocks in the evolving digital media landscape. For investors seeking entertainment sector exposure, our analysis suggests that a portfolio tilted toward Walt Disney offers the most efficient risk-return profile under current market conditions, though ongoing monitoring remains essential as business models continue to evolve.
Read full articleEntrepreneurial Motivation as a Mediator of Financial Literacy, Family Environment, and Love of Money on Entrepreneurial Interest in Gen Z Students
Abstract
Entrepreneurial interest reflects an individual’s intention and willingness to engage in entrepreneurial activities, often driven by personal motivation and the courage to take calculated risks. Generation Z, born between 1995 and 2012, has grown up in the digital era, shaping their mindset and access to entrepreneurial opportunities. This study investigates the extent to which financial literacy, family environment, and love of money influence the entrepreneurial interest of Gen Z students, with entrepreneurial motivation acting as a mediating variable. A quantitative research approach was employed using primary data collected through questionnaires from 99 Gen Z students. Path analysis was conducted to test the proposed relationships. The findings reveal that financial literacy, family environment, and love of money each significantly influence entrepreneurial motivation, which in turn has a strong mediating effect on entrepreneurial interest. These results highlight the critical role of internal motivation in bridging cognitive, emotional, and contextual factors in the entrepreneurial decision-making process among Gen Z students. This study provides useful insights for educators and policymakers aiming to cultivate entrepreneurship among younger generations through targeted support in financial education, family engagement, and value orientation.
Read full articleThe Impact of Work Motivation and Work Environment on Employee Performance in Organizational Contexts
Abstract
This study examines the influence of work motivation and work environment on employee performance within organizational contexts. The research focuses on CV Elsa Cahya in Gresik, involving all 30 employees as respondents through a saturated sampling technique. A quantitative approach was adopted, and data were gathered using structured questionnaires, interviews, and observations. Statistical analysis was performed using SPSS, which included descriptive analysis, instrument validity and reliability testing, classical assumption tests, and multiple linear regression analysis. The results show that both work motivation and work environment positively affect employee performance. However, only the work environment variable was statistically significant in the partial test, with a standardized beta coefficient of 0.827, making it the dominant factor compared to work motivation. The F-test indicates that the combination of both variables significantly explains 78.5% of the variance in employee performance. The regression analysis reveals that improvements in the work environment yield greater gains in performance compared to work motivation alone. The findings of this study suggest that the quality of the work environment plays a crucial role in enhancing employee productivity, making it a key consideration for organizational development and human resource strategies.
Read full articleThe Evaluation of Leadership Styles and their Effects on Employee Attitude: Evidence from a Manufacturing Company in South Eastern Nigeria
Abstract
Leadership styles are widely acknowledged as a fundamental factor in determining organizational success, influencing the performance of employees and the overall organizational culture. How leaders manage their teams can greatly impact employee attitudes, motivation, and behaviours, affecting productivity, job satisfaction, and organizational commitment. Using an online survey, this quantitative study employed data collected from 373 staff members at a Manufacturing Company in Southeast Nigeria. The data collected was analyzed using SPSS version 20. Correlation and regression analyzes were conducted to test the relationship and impact among the variables. The findings highlighted the positive influence of democratic, transactional, autocratic, and transformational leadership on employee attitude. Furthermore, significant values were obtained for the correlation and effect between the constructs (p < 0.05). Therefore, adopting a multiple approach is recommended in leadership, rather than a singular style when dealing with employees in an organization.
Read full articleDigital Literacy, Environment, and E-Commerce Use Toward Digital Entrepreneurial Intentions via Social Media among Generation Z Students
Abstract
The rapid development of digital technology is reshaping entrepreneurial landscapes, particularly among Generation Z students who are highly engaged with digital platforms. This study investigates the influence of digital literacy, environmental factors, and e-commerce usage on digital entrepreneurial intentions, with social media serving as a mediating variable. A quantitative descriptive-explanatory approach was employed, involving 105 Generation Z student respondents selected through proportional random sampling. The findings reveal that digital literacy, environment, and e-commerce use have a significant impact on digital entrepreneurial intentions, both directly and indirectly through social media. Social media enhances the connection between these factors and entrepreneurial intentions by providing a platform for idea sharing, business promotion, and networking. These insights highlight the importance of integrating digital competencies and social media utilization into entrepreneurship education to cultivate innovative and digitally empowered young entrepreneurs.
Read full articleHow Entrepreneurship Education, Social Media, and Business Capital Shape Gen Z Entrepreneurial Intentions through Income Expectations?
Abstract
The advancement of digital technology encourages transformation in various fields. This research aims to analyze the influence of entrepreneurship education, social media, and business capital on the entrepreneurial interest of Generation Z through income expectations as a mediating variable. This study employs a quantitative approach with descriptive and explanatory designs. The sample consists of 106 students from the Universitas Negeri Makassar selected through proportional random sampling techniques. Data collection was conducted using a Likert scale-based questionnaire and analyzed using path analysis with the help of SPSS software. The results indicate that entrepreneurship education, social media, and business capital significantly influence income expectations and the entrepreneurial interest of Generation Z. Directly, business capital has the greatest impact on entrepreneurial interest. Furthermore, income expectations prove to be a significant mediating variable that strengthens the relationship between entrepreneurship education, social media, and business capital on entrepreneurial interest. This study emphasizes the importance of practice-based entrepreneurship education, optimal utilization of social media, and adequate access to business capital to encourage Generation Z to become entrepreneurs. Income expectations play a key role in motivating students to start and develop businesses.
Read full articleRemittance Inflow, Digital Technology, and Human Development Index in Sub-Saharan Africa
Abstract
Personal remittances an important source of external finance to many households and countries in Sub-Saharan Africa have been hampered by cost of transfers of these funds, amidst advancement in digital technologies. This study examines the combined effect of remittance inflow and digital technology on human development index in Sub-Saharan Africa. The study employed the conditional panel quantile regression methods and a panel data of forty-five (45) SSA countries covering the period 2010 to 2022 for data analysis. The findings of this study revealed that the effect of remittance and digital technology on human development index varies across SSA countries with base on their human development index (HDI) level. The study also found that the interaction effect of remittance and digital technology on human development index has noticeable variations across the lower HDI (25th quantile), middle HDI (50th quantile) and higher HDI (75th quantile) levels. These effects of remittance and digital technology on human development index together their interaction is higher for countries at the middle HDI level (50th quantile). The study therefore recommends that to boost personal remittance inflow from abroad for improvement in human development index amidst advancement in digital technologies, Sub-Saharan African countries should introduce consumer oriented digital platforms for remittance services which should be adequately protected. The study therefore, concludes that as remittances from abroad are becoming major sources of foreign financial inflows, harnessing the drivers of these remittance inflows is vital for improvement in the human development index in SSA.
Read full articleCross-Sectoral Portfolio Optimization in Emerging Markets: Value at Risk Assessment of Indonesian Consumer and Financial Stocks
Abstract
This study examines the comparative risk profiles of single-asset investments versus portfolio strategies using two prominent Indonesian companies: PT. Mayora Indah and PT. Sinar Mas Multiartha. Employing a quantitative approach with Monte Carlo simulation and Value at Risk (VaR) methodology, the research analyzed daily stock returns over a one-year period (January-December 2023). Results reveal that despite similar historical volatility levels between the individual stocks (standard deviations of 2.65% and 2.88%), their correlation coefficient was notably low (0.13), creating significant diversification opportunities. Monte Carlo simulations generated 1,000 potential return scenarios for robust risk assessment, finding that at the 95% confidence level, maximum expected losses on a Rp 100 million investment were Rp 4.78 million for PT. Mayora Indah and Rp 4.58 million for PT. Sinar Mas Multiartha individually. However, a portfolio combining both stocks (60% PT. Mayora Indah, 40% PT. Sinar Mas Multiartha) reduced this potential loss to Rp 2.90 million—representing approximately 37% risk reduction compared to either single-asset investment. This substantial risk mitigation was consistent across all confidence levels (99%, 95%, and 90%). The portfolio also demonstrated improved return characteristics in simulation (0.39% expected return) compared to historical data (0.09%), while maintaining similar risk levels. These findings provide empirical support for the practical value of diversification strategies in the Indonesian equity market, highlighting how even limited diversification across two stocks from different economic sectors can yield substantial improvements in risk-adjusted investment outcomes.
Read full articleRegression Analysis of Panel Data on Gross Enrolment Rate (GER) At Junior High School and Equivalent Education Levels in South Sulawesi Province in 2018-2022
Abstract
Panel data regression is a combination of time series and cross section data. This research aims to determine the factors that influence the gross participation rate in South Sulawesi Province using panel data regression analysis. The data used is data from 24 districts/cities in South Sulawesi province from 2018 to 2022 which was obtained through the website of the South Sulawesi Provincial Central Statistics Agency. There are three models in panel data regression analysis, namely the Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). Based on the model selection carried out by carrying out the Chow Test, Hausman Test, and Lagrange Multiplier Test, the best model was obtained, namely the Random Effect Model. The equation of this model is Yit = 82,818 + 0,1485X1it ? 0,0784X2it + 0,0053X3it + 0,0011X4it. Based on the results of panel data regression analysis, it was found that the variables that had a significant effect on the Gross Enrollment Rate in South Sulawesi province were the student to teacher ratio (X2), and population density (X4).
Read full articleDynamic Determinants of Share Price in Emerging Markets: Evidence from System GMM Estimation in Nigeria
Abstract
This study investigates the dynamic determinants of share price among listed firms in Nigeria’s Consumer Goods and Agriculture sectors using a decade-long panel dataset covering the period from 2012 to 2023. Anchored on the theoretical perspectives of the Efficient Market Hypothesis, Signalling Theory, and Agency Theory, the study evaluates how firm-specific indicators such as earnings per share (EPS), return on equity (ROE), current ratio, debt-to-equity ratio, and total asset turnover, as well as macroeconomic variables like exchange rate and GDP per capita, influence share price in an environment characterised by institutional inefficiencies and information asymmetry. The empirical analysis begins with a static panel regression using the Fixed Effects model to establish a baseline understanding. To improve robustness and account for econometric challenges such as endogeneity, serial correlation, and unobserved heterogeneity, the study adopts the two-step System Generalised Method of Moments (System GMM) as the main estimation technique. The dynamic model reveals strong persistence in share price, as lagged share price is significantly associated with current values. While EPS shows a positive and significant effect in the static model, the dynamic GMM results indicate a negative and significant relationship, suggesting that reported earnings may reflect investor scepticism or earnings manipulation, particularly in contexts with weak governance oversight. Other variables, including ROE, leverage, and macroeconomic indicators, remain statistically insignificant in the dynamic specification. Year effects are incorporated to control for time-specific macro shocks. This study contributes to frontier market finance literature by offering sector-specific insights and demonstrating the added value of dynamic modelling. It also cautions investors and policymakers against excessive reliance on earnings-based metrics without adequate consideration of the institutional environment.
Read full articleReconstructing Entrepreneurship Learning Through a Managerial Approach Based on Local Ethnoscience
Abstract
This study looks at how students' abilities in contextual company development are affected when entrepreneurship education is reconstructed using a management style grounded on local ethnoscience. 18 students from the 2019 cohort who took the Entrepreneurship course in the Chemistry Education programme at Universitas Sembilanbelas November Kolaka provided survey data for the study. Through direct observation and group business planning, students were introduced to fundamental entrepreneurial principles and assisted in interacting with local ethnoscientific resources, including sago, cassava, green vegetables (spinach), clove, honey, shrimp, and milkfish. Standardised questionnaire encompassing eight important markers of ethnoscientific understanding in entrepreneurship was used to gather data. To understand the findings, descriptive and mapping data analysis were used. The findings show that students are highly engaged and competent in locating, evaluating, and innovatively using local resources for entrepreneurship. The most motivating resources were honey, cassava, and shrimp, and students showed great aptitude in contextual business design, product creation, and team-based entrepreneurial analysis. The main results support the idea that including local ethnoscience into entrepreneurship education increases both practical entrepreneurial abilities and cultural and ecological sensitivity. This concept is a potential educational framework for creating entrepreneurs who are innovative, locally rooted, and prepared for the future.
Read full articleImplementation of Binary Logistic Regression and Chi-Squared Automatic Interaction Detection (CHAID) to Recipients of the Prosper Family Card Program in Makassar City
Abstract
The binary logistic regression analysis method is a classification method that forms a relationship between a dichotomous dependent variable and an independent variable, while the chi-squared automatic interaction detection (CHAID) analysis method is a decision tree classification method for studying the relationship between independent variables and variables. bound by using the chi-square test statistic as the main tool. This research aims to determine the magnitude of the resulting accuracy value and what factors influence recipients of the Prosperous Family Card program in Makassar City based on National Socio-Economic Survey data in 2022 using the binary logistic regression method and the chi-squared automatic interaction detection method (CHAID). The results of this research using the binary logistic regression method show that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with an accuracy value of 75.78%, while the chi-squared automatic interaction detection (CHAID) method also shows that the variables of the highest level of education of the head of the household (X4) and defecation facilities (X7) have a significant effect on recipients of the Prosperous Family Card program in Makassar City with the resulting accuracy value of 75%. Based on the accuracy values of the two methods, the binary logistic regression method is the appropriate method for classifying recipients of the Prosperous Family Card program in Makassar City
Read full articleA Seasonal ARIMA (SARIMA) Model for Forecasting Domestic Passenger Traffic at Sultan Hasanuddin Airport
Abstract
The growth of the domestic aviation industry in Indonesia has led to a significant increase in passenger numbers, particularly at major airports such as Sultan Hasanuddin Airport. Accurate forecasting of passenger traffic is essential for effective planning and resource allocation. This study aims to develop a suitable time series model to forecast the number of domestic air passengers departing from Sultan Hasanuddin Airport. Using monthly passenger data from January 2019 to April 2024 obtained from the Indonesian Badan Pusat Statistik (BPS), the Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied. The modelling process followed the Box-Jenkins methodology, involving data exploration, stationarity testing, model identification, parameter estimation, diagnostic checking, and model validation. Among several candidate models, the ARIMA (0,1,1)(0,0,1)12 model was identified as the most appropriate, producing normally distributed, independent residuals and yielding a Mean Absolute Percentage Error (MAPE) of 4.5%. The results demonstrate that the SARIMA model provides a reliable tool for forecasting short-term domestic passenger flows at the airport.
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