Introduction: Citizen insecurity is a complex, multidimensional and multi-causal social problem, defined as the spaces where people feel insecure mainly due to organized crime in all nations that suffer from it. Objective: To analyzes the sociodemographic factors associated with public insecurity in a Peruvian population. Methodology: The research employed a non-experimental, quantitative design with a descriptive and cross-sectional approach. A total of 11,116, citizens participated, ranging from 18 to 85 years old (young adults, adults, and the elderly), of both sexes, and with any occupation, education level, and marital status. The study employed purposive non-probability sampling to select the participants. Results: More than 50% of the population feels unsafe, in public and private spaces. All analyzed sociodemographic variables (p < 0.05), showing distinctions in the perception of citizen insecurity based on age, gender, marital status, occupation, area of residence, and education level. It was determined that young, single students, who had not experienced a criminal event and reside in urban areas, regardless of gender, perceive a greater sense of insecurity. Contribution: The study is relevant due to the generality of the results in a significant sample, demonstrating that the study contributes to understanding how various elements of the socioeconomic and demographic context can influence the way in which individuals perceive insecurity in their communities, likewise, the perception of citizen insecurity directly affects the general well-being and quality of life of residents, influencing their behaviors and attitudes towards coexistence and public policies; which will help implement more effective actions in the sector to reduce crime rates.

It is critical for urban and regional planners to examine spatial relationships and interactions between a port and its surrounding urban areas within a region’s spatial structure. This paper seeks to develop a targeted framework of causal relationships influencing the spatial structure changes in the Bushehr port-city. Hence, the study utilizes Fuzzy Cognitive Maps (FCMs), a computational technique adept at analyzing complex decision-making processes. FCMs are employed to identify concepts that act as drivers or barriers in the spatial structure changes of Bushehr port-city, thereby elucidating the causal relationships within this context. Additionally, the study evaluates these concepts’ relative significance and interrelationships. Data was collected through interviews with ten experts from diverse backgrounds, including specialists, academics, policymakers, and urban managers. The insights from these experts were analyzed using FCMapper and Pajek software to construct a collective FCM, which depicts the influential and affected concepts within the system. The resulting collective FCM consists of 16 concepts, representing the varied perspectives and expertise of the participants. Among these, the concepts of management and planning reform, economic growth of the city-port, and port development emerged as the three most central concepts. Moreover, the effects of all influential concepts on the spatial structure change in Bushehr port-city were evaluated through simulations conducted across four different scenarios. The analysis demonstrated that the system experiences the most significant impact under the fourth scenario, where the most substantial changes are observed in commercial and industrial growth and the planning of port-city separation policies.

Real estate appraisal standards provide guidelines for the preparation of reliable valuations. These standards emphasize the central role of market data collection in market-oriented valuation methodologies such as the Market Comparison Approach (MCA), which is the most commonly used. The objective of this study is to highlight the difficulties in data finding, as well as the gap between the standards and the actual appraisal practices in Italy. Thus, a detailed comparison was made between the real estate data considered necessary by the standards and those ones reasonably detectable by appraisers, showing that some important market information is not reachable due to legal, technical and economic factors. Finally, a case study is presented in which the actual appraisal of a residential property is schematically described to support what is claimed with the research question and thus the degree of uncertainty around an estimate judgment.

 Distance education (DE) has recently become a noteworthy study topic in the public education system. From the Web of Science database, 5719 articles discussing DE and published in the period of 2011–2023 were acquired. By analyzing the overall characteristics, co-citation, and keyword co-occurrence of the selected articles, which utilized Cite Space software, the history of DE could be systematically grasped, thereby reasonably predict the emphases of future development. We found that the number of papers relevant to DE had been rapidly growing since 2018. USA, China, and Turkey are the top three countries where most authors or teams were located. The map of keyword cooccurrence showed that the previous DE research mainly focused on telelearning, adult learning, and distributed learning environment. The recent burst words emerging are used to determine that distance education will continue to be studied in the field with high explosive keywords such as visual tracking, technology acceptance model, and user interface. This will provide suggestions and directions for the development of distance education.

Nawacita work program of Indonesian Governance aims to actualize a golden Indonesia by 2045 by accelerating development and human resources. However, the Indonesian people face several difficult problems of their own. Several strategic policies have been put into place in Indonesia to promote fair development and lessen regional differences. These policies include macroeconomic management, economic deregulation, the development of new resources economically, the maritime economy, and productivity enhancement. The Nawacita program’s reflection in addressing regional imbalances in Indonesian regencies and cities is covered in this report. This study employs quantitative and bibliographic techniques along with political economic analysis methodologies to investigate in-depth and information. The study’s findings indicate that although differences between Indonesia’s districts and cities are gradually narrowing, the country’s GDP per capita is still below the global average. Most of the strategic measures put in place by the Indonesian Governance have not resulted in the anticipated expansion of the economy. Nonetheless, in current period of government, connectivity in enhancing productivity across regions through Indonesia centric development is a primary objective to ease accessibility between areas, which has frequently been disregarded. particularly in the Papua region, which has not exactly developed and been left behind. According to the Analytical Hierarchy Process (AHP) analysis’s findings, increasing productivity is a task that needs to be finished right now to lessen regional differences in Indonesia.

The relationship between aid and corruption remains ambiguous. On the one hand, aid may benefit a country if the aid management system runs efficiently and transparently. On the other hand, aid tends to create new problems, namely corruption, especially in developing countries. This research examines the aid-corruption paradox in Indonesian provinces from a spatial perspective. The data was obtained from the Indonesian Ministry of Finance, the National Development Planning Agency of Indonesia, the Corruption Eradication Commission of Indonesia, and the Electronic Procurement Service, referring to 34 Indonesian provinces between 2011 and 2019. The research applies the spatial panel method and uses Haversine distance to construct the weighted matrix. The spatial error model (SEM) is the best for Model 1 (Grants) and Model 2 (Loans) and the best corruption model in Model 3 (Gratification). The spatial autoregressive model (SAR) is the best approach for Model 4 (Public Complaints) and Model 5 (Corruption). The findings show that there is no spatial dependence between provinces in Indonesia in terms of grants or loans. However, corruption in Indonesia is widespread.