This research seeks to identify the value of a few common factors determining the speed of economic growth in Baltic states and analyzes their impact in detail on Latvia’s lagging. Latvia’s economic starting point after regaining independence because of the collapse of the Soviet Union was at least comparable to its neighbors. Still, after the implementation of liberal reforms towards a free market’ economy and 20 years of operation as an EU full member, Latvia is lagging in growth, prosperity, and innovation. Within the analysis, this scientific paper pays special attention to the three less discussed factors, namely, the impact of post-Soviet mind-set effects as a part of local innovation culture, lasting since regaining independence in 1991; the importance of the availability of talent pull, its density, diversity, and accessibility; and readiness and capability to capture external knowledge and technology adoption. The overall approach is the systemic assessment of the national innovation system and/or innovation ecosystem, trying to understand the differences between these two models. Research is performed by analysis of the performance of the local innovation ecosystem in connection with export- and Foreign Direct Investment (FDI) policies. The authors present a novel method for visually representing economic growth and its application in analyzing process development within transitional economic nations. The study uses an analytical and synthetical literature review. It offers a new GDP data visualization method useful for monitoring economic development and forecasting potential economic crises—the outcomes from aggregative literature analysis in a consolidated concept are provided for required talent policy proposals. The post-Soviet mindset is seen as a heritage and devious underdog that has left incredibly diverse consequences on today’s society, power structures, economic growth potential, and the emergence of healthy, well-managed, and sustainable innovation ecosystems. The post-Soviet mindset is a seemingly hidden and, at the same time, an intriguing factor that has a significant impact on the desire to make and implement the right decisions related to innovation, education, and other policies promoting business development. The key outcome of the article is that sociocultural aspects and differences in innovation culture led to a slow-down of Latvia’s economic growth compared to Estonia’s and Lithuania’s slightly more successful economic reforms.

This paper provides a concise historical analysis of the political economy of privatization in Algeria, Morocco, and Tunisia from the 1980s to 2007, a period that witnessed the emergence of privatization as a primary policy tool to reform the public sector. The paper examines the influence of political history, macroeconomic considerations, and International Development Agencies (IDAs) on the early privatization processes in these North African countries. Despite shared developmental trajectories, internal and external factors had a significant impact on the outcomes of economic liberalization. The paper aims to answer the following key questions: What were the underlying political-economic factors driving privatization, and how successful was it in achieving the promised economic growth? Through a focused analysis of each country’s contextual factors, privatization processes, and outcomes, the paper contributes valuable insights into the nuanced dynamics shaping privatization in developing countries.

This study aims to explore the factors influencing people’s intention to use home fitness mobile apps in the post-pandemic era. By incorporating the perspective of playfulness into the decomposed theory of planned behavior, it seeks to construct a behavioral model for the public's use of AR sports games for home exercise. The research focuses on Active Arcade users residing in Taiwan, employing the snowball sampling method to conduct an online questionnaire survey. A total of 340 valid questionnaires were collected and analyzed using linear structural equations. The study reveals three main findings: first, the behavioral model for Active Arcade users constructed based on the decomposed theory of planned behavior demonstrates a good fit; second, users’ attitudes, subjective norms, and perceived behavioral control have a positive and significant impact on behavioral intention; third, perceived usefulness, perceived ease of use, and perceived playfulness all positively and significantly influence attitudes, with perceived playfulness having the highest impact coefficient; fourth, perceived benefits of exercise are the most crucial factor affecting subjective norms; and fifth, convenience technologies are the key factor influencing perceived behavioral control. This study provides valuable insights for theory and management practice, offering guidance on the use of home fitness apps in the post-pandemic era while addressing research limitations and suggesting future directions.

The study examines the factors shaping inflation in 2022–2023 and explores why inflation in the Hungarian economy has increased more sharply than in neighboring countries with similar structures. The research hypothesis suggests that the inflationary surge, which is notable both globally and within the European Union, is not solely due to market economy mechanisms, but also to specific circumstances in Hungary, including the state’s radical interventions aimed at curbing inflation. The study seeks to highlight these effects and provide recommendations for economic policymakers to develop a more resilient inflation policy. Additionally, it focuses on analyzing inflation in the agricultural sector. The results indicate that, alongside global inflationary pressures, several country-specific factors have driven up the inflation rate in Hungary. Energy prices have risen sharply, and some supply chains from the East have been disrupted. The country under study is less productive, and the impact of the energy price shock on the energy-intensive food industry is higher than in surrounding countries. Consequently, the exchange rate volatility in 2022–2023, combined with short- and medium-term factors, has had a significant impact on food inflation, causing substantial deviations from long-term equilibrium. The research concludes that, in addition to increasing food self-sufficiency, special attention should be given to the domestic development of the agricultural supply chain.

In rural areas, land use activities around primary arterial roads influence the road section’s traffic characteristics. Regulations dictate the design of primary arterial roads to accommodate high speeds. Hence, there is a mix of traffic between high-speed vehicles and vulnerable road users (pedestrians, bicycles, and motorcycles) around the land. As a result, researchers have identified several arterial roads in Indonesia as accident-prone areas. Therefore, to improve the road user’s safety on primary arterial roads, it is necessary to develop models of the influence of various factors on road traffic accidents. This research uses binary logistic regression analysis. The independent variables are carelessness, disorderliness, high speed, horizontal alignment, road width, clear zone, road shoulder width, signs, markings, and land use. Meanwhile, the dependent variable is the frequency of accidents, where the frequency of accidents consists of multi-accident vehicles (MAV) and single-accident vehicles (SAV). This study collects data for a traffic accident prediction model based on collision frequency in accident-prone areas. The results, road shoulder width, and road sign factor all have an impact on the frequency of traffic accidents. According to a realistic risk analysis, MAV and SAV have no risk difference. After validation, this model shows a confidence level of 92%. This demonstrates that the model generates estimations that accurately reflect reality and are applicable to a wider population. This research has the potential to assist engineers in improving road safety on primary arterial roads. In addition, the model can help the government measure the impact of implemented policies and engage the public in traffic accident prevention efforts.

In the realm of contemporary business, Business Intelligence (BI) offers significant potential for informed decision-making, particularly among executives. However, despite its global popularity, BI adoption in Malaysia’s service sector remains relatively low, even in the face of extensive data generation. This study explores the factors influencing BI adoption in this sector, employing the Technology Acceptance Model (TAM) as its conceptual framework. Drawing on relevant BI literature, the study identifies key TAM factors that impact BI adoption. Using SEM modelling, it analyses quantitative data collected from 45 individuals in managerial roles within Malaysia’s service sector, particularly in the Klang Valley. The findings highlight the crucial role of Perceived Usefulness in influencing the Behavioral Intention to adopt BI, serving as a mediating factor between Computer Self-efficacy and BI adoption. In contrast, Perceived Ease of Use does not have a direct impact on BI adoption and does not mediate the relationship between Computer Self-efficacy and Behavioral Intention. These insights demonstrate the complex nature of BI adoption, emphasizing the importance of Perceived Usefulness in shaping Behavioral Intentions. The outcomes of the study aim to guide executives in Malaysia’s service sector, outlining key considerations for successful BI adoption.