The small and medium tourism enterprises sector has experienced a decline in Indonesia’s economic conditions in recent years. This research aims to advise stakeholders regarding factors that must be considered and included in future policy formulation. The research methodology is a mixed method supported by the N-Vivo computer program, interview studies, and FGD. This research focuses on four tourism provinces in Indonesia. The research results using thematic analysis identified 133 codes, 19 categories, nine core themes, and one impact theme. This research’s novelty highlights that government policy’s effects on tourism SME marketing are not significant due to weak support. Apart from that, partnerships and collaboration between the central regional government and tourism SMEs are the main factors determining their development at the regional level. This research concludes that government intervention and support in encouraging the growth and sustainability of tourism SMEs are necessary. The Government must promote collaboration between tourism SMEs because increasing the number of tourists is crucial, as well as encouraging sustainable marketing practices and simplifying regulations. The recommendation is that the Government immediately simplify regulations, expand partnerships and collaboration, and promote innovation in tourism SMEs. By implementing these recommendations, policymakers can create an environment that supports the development of tourism SMEs, allowing the tourism sector to increase GRDP.

To address the escalating online romance scams within telecom fraud, we developed an Adaptive Random Forest Light Gradient Boosting (ARFLGB)-XGBoost early warning system. Our method involves compiling detailed Online Romance Scams (ORS) incident data into a 24-variable dataset, categorized to analyze feature importance with Random Forest and LightGBM models. An innovative adaptive algorithm, the Adaptive Random Forest Light Gradient Boosting, optimizes these features for integration with XGBoost, enhancing early Online romance scams threat detection. Our model showed significant performance improvements over traditional models, with accuracy gains of 3.9%, a 12.5% increase in precision, recall improvement by 5%, an F1 score increase by 5.6%, and a 5.2% increase in Area Under the Curve (AUC). This research highlights the essential role of advanced fraud detection in preserving communication network integrity, contributing to a stable economy and public safety, with implications for policymakers and industry in advancing secure communication infrastructure.

This study examines the determinants of inflation in Tunisia from 1998 to 2023, with a particular focus on the role of fiscal policy. The study analyzes the long-run and short-run relationships between inflation and key macroeconomic variables, including government expenditure, government revenue, money supply, balance of trade, and budget deficits using ARDL model. The empirical findings reveal that budget deficits have a significant and positive impact on inflation, underscoring the critical role of fiscal imbalances in driving price instability. In contrast, government expenditure, government revenue, money supply, and balance of trade do not exhibit statistically significant long-term effects on inflation. The results highlight the importance of fiscal discipline and effective coordination between fiscal and monetary policies to achieve price stability. These findings provide valuable insights for policymakers in Tunisia and other developing economies facing similar inflationary pressures, emphasizing the need for prudent fiscal management and structural reforms to mitigate inflation volatility and ensure macroeconomic stability.

Background: India’s rich educational heritage dates to ancient times, with popular institutions like Nalanda, Takshashila, and Banarasi-Kasi flourishing as early as the 6th century BC, which offered diverse courses spanning medicine, mathematics, astronomy, and more. Invasions by the Mughals and British during the 12th to 18th centuries disrupted India’s traditional education systems. Post-independence, India faced the challenge of transitioning from ancient to modern education. Remarkably, the country managed to preserve its popular traditional education through a strategic change management approach by the educational institutions. The Government of India has introduced in the National Education Policy 2020 (NEP 2020) in July 2020, to bring transformational reforms in school and higher education systems. In this manuscript, we have summarized the salient features of the NEP 2020 and the preparedness steps to its effective implementation in Indian educational institutions. Method: We have utilised standard databases like PubMed, Science Direct, or Google Scholar, and/or public domains and the NEP 2020 document for this literature survey. Value addition: NEP 2020 aims to ensure access, equity, quality, affordability, and accountability with more flexible curricular structure, and holistic approaches. Despite the COVID-19 pandemic’s impact, dynamic planning, and collaboration among public and private institutions, and industries supported the effective implementation of NEP 2020. Notably, the change management approach, which has been a constant throughout India’s educational journey, played a pivotal role in keeping pace with technological advancements and fostering growth in the higher education system in India.

Ride-hailing or private hire has taken the Singapore transport network by storm in the past few years. Singapore has had more than three revisions of its ride-hailing regulation in the six years since the arrival of the disruptive technology. Often quoted in the list of cities with commendable public transport policy, Singapore still manages to find a viable and significant position for ride-hailing. Cities from around the world are all searching for a model of regulation for ride-hailing that can be elevated as a benchmark. Singapore, to a large extent, has formulated a successful model based on current market parameters and, more importantly, an adaptive one that evolves constantly with the constantly disruptive technology. The experts and regulators of the Singapore transport sector were interviewed in depth, tapping into their opinions and technocratic commentaries on the city-state’s Point-to-Point, or P2P, sector regulation. The data were analyzed using the three-element model of social practice theory as an alternative to conventional behavioral studies, thereby eliminating bias on the commuters and rather shifting focus to the practice. Content analysis utilizing QDA is executed for categorization through fine-level inductive matrix coding to elaborate upon the policy derivatives of the Singapore model. The unique addition of the research to ride-hailing policy is the comprehension of the commonalities and patterns across industrial and technological disruption, practice and policy irrespective of sectoral variations, thanks to the utilization of social practice theory. The first-of-its-kind policy exercise in the sector can be repeated for any city, which is a direct testament to the simplicity and exhaustivity of the methodology, benefiting both operators and investors through equitable policy formulation.