This study explores the spatial distribution pattern of educational infrastructure development across districts and cities in North Sumatra, identifying significant disparities between urban and rural areas. The study aims to: (1) determine the distribution of educational development across districts and cities, (2) analyze global spatial autocorrelation, and (3) identify priority locations for educational development policies in North Sumatra Province. The methodology includes quantile analysis, Moran’s Global Index, and Local Indicators of Spatial Autocorrelation (LISA) using GeoDa software to address spatial autocorrelation. The results indicate that there are nine areas with a low School Participation Rate Index (SPRI), eleven areas with a low School Facilities and Infrastructure Index (SFII), and eleven areas with a low Regional Education Index (REI). Spatial autocorrelation analysis reveals that SFII shows positive spatial autocorrelation, while SPRI and REI exhibit negative spatial autocorrelation, indicating a high level of inequality between regions. Labuhan Batu Selatan and Labuhan Batu are identified as priorities for the provincial government in overseeing educational development policies.

Despite the proliferation of corporate social responsibility (CSR) studies, it is accruing academic interest since there still remains a lot to be further explored. The purpose of the study is to examine whether/how CSR perception affect employee/intern thriving at work and its mediator through perceived external prestige in the hospitality industry. Data from 501 hospitality industry employees and interns in China were collected using a quantitative survey consisting of 35 questions. Statistical findings showed that CSR perception and thriving at work were positively related. Additionally, perceived external prestige partially mediated the connection between CSR perception and thriving at work. Furthermore, the study found that hotel interns generally exhibited lower levels of CSR perception and thriving at work compared with frontline or managerial staff. The study underscores the importance of collaborative efforts between hotel practitioners and university educators to enhance CSR perception and promote thriving among hotel interns. By prioritizing the improvement of CSR perception and thriving at work, the hotel sector can potentially mitigate workforce shortages and reduce high turnover rates.

This study aims to analyse the impact of Brexit on London’s housing market, exploring socio-economic and regional disparities. By examining property transaction data from 2012 to 2022, the research seeks to understand how Brexit has influenced real housing prices across different boroughs of London. The methodology involves aggregating transaction data from the Her Majesty (HM) Price Paid database and normalizing prices using the Consumer Price Index (CPI) to obtain real price variations. These data were segmented into three distinct periods: pre-Brexit (2012–2016), post-plebiscite Brexit (2016–2019), and post-implementation Brexit (2020–2022). Spatial analysis was conducted using the software Quantum Geographic Information System (QGIS), transforming point data (postcodes) into polygonal data (wards) for better visualization and comparison. The findings reveal significant socio-economic impacts, with traditionally affluent areas such as Westminster, Kensington, and Chelsea experiencing notable declines in real housing prices. Conversely, certain outer boroughs like Newham and Barnet showed resilience, with positive real price variations despite decreased sales. This geographical disparity underscores the uneven distribution of Brexit’s economic consequences, highlighting the critical role of localized economic policies and development projects in mitigating adverse effects. The results confirm existing literature on the polarization and regional inequalities exacerbated by Brexit while providing new insights into the complex interplay of local and global factors affecting housing markets. The findings emphasize the need for targeted policy interventions to address the diverse challenges posed by Brexit, ensuring both affluent and disadvantaged areas receive adequate support. This research is crucial for informing public policy, urban planning, and housing market strategies in a post-Brexit context, promoting equitable and sustainable development across London.

Over the past decade, the integration of technology, particularly gamification, has initiated a substantial transformation within the field of education. However, educators frequently confront the challenge of identifying suitable competitive game-based learning platforms amidst the growing emphasis on cultivating creativity within the classroom and effectively integrating technology into pedagogical practices. The current study examines students and faculty continuous intention to use gamification in higher education. The data was collected through an online survey with a sample size of 763 Pakistani respondents from various universities around Pakistan. The structural equation modeling was used to analyze the data and to investigate how continuous intention to use gamification is influenced by, extended TAM model with inclusion of variables such as task technology fit, social influence, social recognition and hedonic motivation. The results have shown that task technology has no significant influence on perceived usefulness (PU) where as it has a significant influence on perceived ease of use (PEOU). Social influence (SI) indicates no significant influence on perceived ease of use. Social recognition (SR) indicates positive influence on perceived usefulness, perceived ease of use, and continuous intention. The dimensional analysis indicated that perceived ease of use has insignificant influence on perceived usefulness. Both PEOU and PU exhibit positive influence on attitude. Hedonic motivation (HM) and attitude were observed to have a positive influence on continuous intention (CI). Moreover, gamification is found to efficiently and effectively achieve meaningful goals by tapping intrinsic motivation of the users through engaging them in playful experiences.

Preserving roads involves regularly evaluating government policy through advanced assessments using vehicles with specialized capabilities and high-resolution scanning technology. However, the cost is often not affordable due to a limited budget. Road surface surveys are highly expected to use low-cost tools and methods capable of being carried out comprehensively. This research aims to create a road damage detection application system by identifying and qualifying precisely the type of damage that occurs using a single CNN to detect objects in real time. Especially for the type of pothole, further analysis is to measure the volume or dimensions of the hole with a LiDAR smartphone. The study area is 38 province’s representative area in Indonesia. This research resulted in the iRodd (intelligent-road damage detection) for detection and classification per type of road damage in real-time object detection. Especially for the type of pothole damage, further analysis is carried out to obtain a damage volume calculation model and 3D visualization. The resulting iRodd model contributes in terms of completion (analyzing the parameters needed to be related to the road damage detection process), accuracy (precision), reliability (the level of reliability has high precision and is still within the limits of cost-effective), correct prediction (four-fifths of all positive objects that should be identified), efficient (object detection models strike a good balance between being able to recognize objects with high precision and being able to capture most objects that would otherwise be detected-high sensitivity), meanwhile, in the calculation of pothole volume, where the precision level is established according to the volume error value, comparing the derived data to the reference data with an average error of 5.35% with an RMSE value of 6.47 mm. The advanced iRodd model with LiDAR smartphone devices can present visualization and precision in efficiently calculating the volume of asphalt damage (potholes).

This paper analyzes the relevance of social accounting information for managing financial institutions, using Banca Transilvania Financial Group (BTFG) as a case study. It explores how social accounting data can enhance decision-making processes within these institutions. Social information from BTFG’s annual integrated reports was used to construct a social balance sheet, and financial data was collected to calculate economic value added (EVA) and social value added (SVA). Research question include: Does social accounting represent a lever for substantiating the managerial decision in financial institutions? Results show that SVA is a valuable indicator for financial institution managers, reflecting the institution’s contributions to social well-being, environmental impact, and community support. Policy implications suggest regulatory bodies should mandate the inclusion of social accounting metrics in financial reporting standards to encourage socially responsible practices, enhance transparency, and incentivize institutions achieving high SVA. This paper contributes to the literature by demonstrating the practical application of social accounting in financial institutions and highlighting the importance of SVA as a managerial tool. It aligns with existing research on integrating corporate social responsibility (CSR) metrics into financial decision-making, enhancing the understanding of combining social and economic indicators for comprehensive performance assessment The abstract covers motivation, methodology, results, policy implications, and contributions to the literature.