Despite having a strategic position in supporting the Indonesian economy, the productivity of SME’s is still suboptimal. The increase in the number of SME’s has not been followed by increased competitiveness due to various limitations experienced by this sector. In an effort to provide a comprehensive picture in improving the performance of food processing SME’s in developing countries such as Indonesia, the purpose of this study was to examine the function of product innovation, internet marketing, and brand identity in shaping competitive advantage having an impact on business performance. This research is focused on food processing SME’s in the city of Bogor. The number of samples used was 100 SME’s. The sampling method used the non-probability sampling method with a snowball sampling technique. The data obtained were analyzed using the Structural Equation Model (SEM). Based on the age characteristic of business actors, the majority of business actors were 40–50 years old, of which 52% had their final formal education at high school level. As many as 61% of respondents had attended business training. Based on the results of the Partially Least Square (PLS) SEM analysis, it was found that product innovation, internet marketing and brand identity all had a significant positive effect on competitive advantage and business performance. The influence of brand identity on competitive advantage had the greatest effect, with a value of 0.451. This study contributes to existing research by examining the determinants of the business performance of processed food SME’s through the holistic model offered. This research is innovative because the business raises new issues related to internet marketing by SME’s and investigates them empirically.

This paper is the third in a series focused on bridging the gap between secondary and higher education. Our primary objective is to develop a robust theoretical framework for an innovative e-business model called the Undergraduate Study Programme Search System (USPSS). This system considers multiple criteria to reduce the likelihood of exam failure or the need for multiple retakes, while maximizing the chances of successful program completion. Testing of the proposed algorithm demonstrated that the Stochastic Gradient Boosted Regression Trees method outperforms the current method used in Lithuania for admitting applicants to 47 educational programs. Specifically, it is more accurate than the Probabilistic Neural Network for 25 programs, the Ensemble of Regression Trees for 24 programs, the Single Regression Tree for 18 programs, the Random Forest Regression for 16 programs, the Bayesian Additive Regression Trees for 13 programs, and the Regression by Discretization for 10 programs.

This study examines the financial integration between Jordan and the BRIC economies (Brazil, Russia, India, and China) to determine whether long-term equilibrium relationships exist and to assess implications for portfolio diversification and policy. Drawing on daily stock index data from 01 January 2014, to 31 August 2024, the study employs econometric techniques, including Granger Causality tests, Johansen Cointegration, and Vector Autoregression (VAR). The stationarity of stock indices at the first difference level is confirmed through unit root testing. Results indicate minimal long-term cointegration between Jordan and BRIC markets, pointing to low integration and potential diversification benefits for institutional investors. However, short-term causal links—particularly between Jordan and the Russian and Indian markets—highlight these countries’ influence on Jordan’s stock fluctuations. The findings suggest that, in the absence of long-term cointegration, investors may mitigate risk by investing in less correlated markets, such as Jordan, while leveraging short-term partnerships with Russia and India. Additionally, the study provides valuable insights for business leaders considering strategic alliances with BRIC counterparts in sectors like technology, agriculture, and energy, and calls for future research into factors like regulatory frameworks and geopolitical stability that may limit long-term financial integration. These results have significant implications for institutional investors, business executives, and policymakers, suggesting targeted strategies for financial stability, risk mitigation, and economic collaboration.

This study presents a comprehensive bibliometric analysis of the literature on public financial management (PFM), aiming to identify key trends, influential publications, and emerging themes. Using data from Web of Science and Scopus, the study examines the evolution of PFM research from 1977 to 2024. The findings reveal a significant increase in PFM research output, particularly after 2010, with countries like the United States, the United Kingdom, and China contributing the most publications. Central themes such as financial management, transparency, and accountability remain prominent while emerging topics like gender budgeting, health insurance, and blockchain technology reflect shifting priorities in the field. The study employed performance analysis and science mapping techniques to assess the structure and dynamics of PFM research. The analysis highlights key focus areas, including fiscal decentralization and sector-specific management, and identifies gaps in the existing literature, particularly regarding interdisciplinary and international collaboration. The results suggest that while PFM remains rooted in traditional governance and financial control, there is a growing emphasis on modern, innovative solutions to address contemporary challenges. This study’s insights provide a roadmap for future research, emphasizing the importance of transparency, technological integration, and inclusive financial policies. In conclusion, this bibliometric analysis contributes to understanding PFM’s evolving landscape, offering scholars and policymakers a clearer perspective on current trends and future directions in the field. Future research should focus on expanding interdisciplinary approaches and exploring the practical impacts of emerging PFM trends across different regions.

Managing the spread of “disinformation” is becoming an increasingly difficult task of our time, with an emphasis on digital marketing and its influence on organizational reputation. This paper aims to analyze the phenomenon of disinformation, with emphasis on the role of digital marketing and the consequent effect on organizational image. Thus, using the systematic literature review methodology, the study defines and categorizes different types of disinformation, namely fake news, misinformation, and propaganda, and how they are spread across different channels. Using the research, it is possible to conclude that digital marketing is more effective in spreading disinformation than traditional media and word-of-mouth; social media management and content marketing are the most effective. The work also evaluates the catastrophic impact of disinformation on an organization’s image, fiscal health, and the trust of its stakeholders. Using the Chi-Square Test for Independence and Logistic Regression, the study determines the factors likely to lead to severe consequences of disinformation campaigns. Last but not least, the paper also suggests ways of preventing the spread of disinformation, which include improved education on the use of digital platforms, better fact-checking systems, and an improved code of ethics in digital marketing.

The COVID-19 crisis, which occurred in 2020, brought crisis events back to the attention of scholars. With the increasing frequency of crisis events, the influence of crisis events on stock markets has become more obvious. This paper focuses on the impact of the subprime crisis, the Chinese stock market crash crisis and the COVID-19 crisis on the volatility and risk of the world’s major stock markets. In this paper, we first fit the volatility using EGARCH model and detect asymmetry of volatility. After that, a VaR model is calculated on the basis of EGARCH to measure the impact of the crisis event on the risk of stock markets. This paper finds that the subprime crisis has a significant influence on the risk of the stock market in China, US, South Korea, and Japan. During the COVID-19 crisis, there was little change in the average risk of each country. But at the beginning of the COVID-19 crisis, there was a significant increase in the risk of each country’s stock market. The Chinese stock market crash crisis had a more pronounced effect on the Chinese and Japanese stock markets and a lesser effect on the US and Korean stock markets.