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).

Mecula Haroano Laa is a local wisdom that includes beliefs, norms, and practices passed down from generation to generation in the context of agricultural resource preservation and community cultural identity formation. The author is interested in investigating the practices of the Mecula Haroano Laa tradition, which is unique to North Buton Regency and has unique specifications and characteristics. This research uses a qualitative approach. The data collection techniques used in this study are in-depth interviews and participatory observations. The results of this study demonstrate that Mecula Haroano Laa in North Buton society is more than just an agricultural custom; it is also an attempt to strengthen social solidarity among community members. This practice reflects the spirit of solidarity, gotong royong together, and respect for the environment. The North Buton community is actively involved in implementing Mecula Haroano Laa as a form of participation in developing sustainable agriculture. This research contributes to understanding the importance of local wisdom in building social cohesion in communities. Research implications include sustainable planning and efforts to empower communities in developing farms in North Buton Regency. Natural resource management policies may incorporate. Mecula Haroano Laa’s effective and sustainable resource management techniques to promote wise use, environmental conservation, economic resilience, and dependency reduction.

In the context of ecological and social challenges in global food systems, this study investigates the potential of agri-food districts to foster balanced territorial development. A multi-step approach to developing sustainable agri-food districts is outlined. How these districts, as integrated systems and meso-level organizational forms, can enhance sustainability through governance is then assessed. This research uses a context-driven analysis pathway involving stakeholder participation and needs identification. The theoretical background, the Italian regulatory framework, and a case study from Lombardy are presented. Needs are identified through participatory approaches and actions are prioritized using desk research and a narrative SWOT analysis combined with key stakeholder discussions (focus group). A total of eighteen needs are identified and categorized into 3 dimensions of sustainability: economic, environmental, and socio-institutional. Findings indicate that agri-food district organization has great potential to help achieve local and regional policy goals in line with the shift to sustainable approaches in the Common Agricultural Policy (CAP). The paper proposes actions to strengthen district capacity-building, focusing on internal governance and sustainable production chains. Additionally, initiatives to attract young people to rural areas and agreements for ecosystem services in agri-food districts are suggested. These actions aim to promote sustainability and competitiveness while addressing challenges related to governance, innovation, branding, demographics, and environment. In conclusion, the study prompts critical inquiry into governance models and system dynamics. The innovative aspects of this study lie in its methodological approach, integration of theory and practice, holistic perspective, policy relevance, and critical inquiry, which collectively contribute to advancing knowledge and understanding in the field of sustainable agriculture and territorial development.

Given the importance of Information Communication Technology (ICT) in stimulating stock market development, many researchers have investigated their influences on the developed markets and high-income economies. The aim of this study is to examine the impact of ICT diffusion on stock market development for a panel of 17 selected emerging countries over the period 1990–2020 and employed the system-generalized method of moments (S-GMM) to test its objective. Three stock market development indicators are also used, namely: stock market capitalization (SMC), stock market total value traded (SMTT), and stock market turnover (SMT). Three ICT indicators are also employed, namely: Fixed telephone subscriptions (FTS), Individuals using the Internet (IUI), and Mobile cellular subscriptions (MCS). Three financial development indicators (deposit money among bank assets (DMB), liquid liabilities (LLB), and private credit by deposit money bank (PCM)) were employed as control variables. In its findings, all selected ICT dynamics positively affect stock market development and its constituents. Secondly, no proof was confirmed in relation to the impact of fixed telephone and stock market development with its elements. Thirdly, evidence of a positive relationship is sparingly apparent in financial development and its components. Fourthly, compared with fixed telephone, internet users more positively and significantly affect stock market development indicators. Policy implications are discussed.

How are telecommunications infrastructure, institutions and poverty related in a war-torn economy such as Afghanistan? Afghanistan has been plagued by poor governance, low usage of telecommunications, and extreme poverty levels which can be termed triple-challenges. High levels of political instability affected telecommunications investment and adversely affected the adoption and diffusion of modern technology. This study examines the asymmetric effect of telecommunications and governance (institutions) on poverty reduction over the period 1989–2019 using a nonlinear autoregressive distributed lag (NARDL) model. In the short run, we establish that information and communication technology, private domestic credit, governance, and educational access for males and females are essential tools that can be used for poverty reduction. In the long run, we also establish that Afghanistan can reduce poverty levels through the use of information and communication technology, governance, and educational access for both males and females. The following policy recommendations were suggested: research and development, robust policy formulation on governance and ICT, development of the ICT sector, and improved governance. These are critical in reducing the high poverty levels as well as solving the institutional challenges faced by Afghanistan.

The Consumer Price Index (CPI) is a vital gauge of economic performance, reflecting fluctuations in the costs of goods, services, and other commodities essential to consumers. It is a cornerstone measure used to evaluate inflationary trends within an economy. In Saudi Arabia, forecasting the Consumer Price Index (CPI) relies on analyzing CPI data from 2013 to 2020, structured as an annual time series. Through rigorous analysis, the SARMA (0,1,0) (12,0,12) model emerges as the most suitable approach for estimating this dataset. Notably, this model stands out for its ability to accurately capture seasonal variations and autocorrelation patterns inherent in the CPI data. An advantageous feature of the chosen SARMA model is its self-sufficiency, eliminating the need for supplementary models to address outliers or disruptions in the data. Moreover, the residuals produced by the model adhere closely to the fundamental assumptions of least squares principles, underscoring the precision of the estimation process. The fitted SARMA model demonstrates stability, exhibiting minimal deviations from expected trends. This stability enhances its utility in estimating the average prices of goods and services, thus providing valuable insights for policymakers and stakeholders. Utilizing the SARMA (0,1,0) (12,0,12) model enables the projection of future values of the Consumer Price Index (CPI) in Saudi Arabia for the period from June 2020 to June 2021. The model forecasts a consistent upward trajectory in monthly CPI values, reflecting ongoing economic inflationary pressures. In summary, the findings underscore the efficacy of the SARMA model in predicting CPI trends in Saudi Arabia. This model is a valuable tool for policymakers, enabling informed decision-making in response to evolving economic dynamics and facilitating effective policies to address inflationary challenges.