Current research largely focuses on the role of allotment gardens, the challenges facing them, and the direction of their future development in urban environments. The main idea behind the introduction of allotment gardens was to improve the living conditions and food supply of workers and the underprivileged. The impact of allotment gardening does not only concern the allotment gardeners but also the general public and the environment. It is important to emphasise that allotments have impacts not only on food production and outdoor physical activity, but also on the reuse of idle or neglected land, community development, therapeutic and nutritional benefits, and psychological benefits for allotment holders and residents. For this reason, this study captures six broad themes related to allotments: (1) community participation and cohesion, (2) health and well-being, (3) economic opportunities, (4) pollution, (5) urban planning and development, and (6) sustainable environment. The research is a systematic review in which steps were taken to minimise bias in the identification, selection, and summarisation of studies. The initial literature selection was based on a keyword search (title, abstract, and keywords) of the comprehensive literature databases Web of Science (all years) and Scopus (all years). The total scientific literature on which this review is based includes 162 research articles published between 1978 and July 2022. This work aims to fill these gaps and analyse existing knowledge by providing a detailed review of the academic literature, focusing not only on the benefits of community gardens and allotments in urban areas, but also on the existing problems related to allotments and urban gardening. Possible directions of development are also analysed based on the legal regulations in each country.

Traffic has a direct impact on local and regional economies, on pollution levels and is also a major source of discomfort and frustration for the public who have to deal with congestion, accidents or detours due to road works or accidents. Congestion in urban areas is a common phenomenon nowadays, as the main arteries of cities become congested during peak hours or when there are additional constraints such as traffic accidents and road works that slow down traffic on road sections. When traffic increases, it is observed that some roads are predisposed to congestion, while others are not. It is evident that both congestion and urban traffic itself are influenced by several factors represented by complex geospatial data and the spatial relationships between them. In this paper were integrated mathematical models, real time traffic data with network analysis and simulation procedures in order to analyze the public transportation in Oradea and the impact on urban traffic. A mathematical model was also adapted to simulate the travel choices of the population of the city and of the surrounding villages. Based on the network analysis, traffic analysis and on the traveling simulation, the elements generating traffic congestion in the inner city can be easily determined. The results of the case study are emphasizing that diminishing the traffic and its effects can be obtained by improving either the public transport density or its accessibility.

In the face of pressing global challenges such as climate change, socioeconomic inequalities, and rapid urbanization, ensuring sustainable development in the regions has become essential. The COVID-19 pandemic has highlighted how vulnerable cities are to unforeseen crises and underscored the urgent need for proactive urban planning strategies capable of navigating dynamic and unpredictable futures. In this context, the use of geographic information systems (GIS) offers researchers and decision makers a distinct advantage in the study of spatial data and enables the comprehensive study of spatial and temporal patterns in various disciplines, including real estate valuation. Central to the integration of modern technology into real estate valuation is the need to mitigate the inherent subjectivity of traditional valuation methods while increasing efficiency through the use of mass appraisal techniques. This study draws on extensive academic literature comprising 103 research articles published between 1993 and January 2024 to shed light on the multifaceted application of GISs in real estate valuation. In particular, three main areas are addressed: (1) hedonic models, (2) artificial intelligence (AI), and mathematical appraisal models. This synthesis emphasizes the interdependence of numerous societal challenges and highlights the need for interdisciplinary collaboration to address them effectively. In addition, this study provides a repertoire of methodologies that underscores the potential of advanced technologies, including artificial intelligence, GISs, and satellite imagery, to improve the subjectivity of traditional valuation approaches and thereby promote greater accuracy and productivity in real estate valuation. By integrating GISs into real estate valuation methodologies, stakeholders can navigate the complexity of urban landscapes with greater precision and promote equitable valuation practices that are conducive to sustainable urban development.

As mentioned by the specialized media, in Romania, in the recent years the banking system and the companies are facing a massive reduction of the values for the commercial properties developed or acquired before the crisis. It is widely known that the value of the commercial properties is directly linked by their location. Considering these elements the current paper focuses on combining specific financial and accounting valuation techniques with location analysis techniques for a better assessment of the values for the commercial real estate properties. While the financial and accounting techniques use methods of calculation established according to the International Valuation Standards, on the other hand this task can be highly simplified if it uses land property management systems or information systems such as the GIS (Geographical Information System). The main function of the land property assessment system, is to define the quantitative and qualitative assessment of the property in order to assess the market price while the main function of GIS based systems is to use economic and cadastral information in coordination with other elements such as: physical factors, social factors, taxation, infrastructure, pollution and noise, economic factors and legal factors in order to facilitate a good assessment of the value of an industrial property. The paper analyzed both the economic factors: based on the International Valuation Standards and also the locational factors of a property valuation and identified the common factors which are used in both methods and which can provide excellent solutions in property valuation

Urban areas have developed organically over time, driven by the economic success of cities. However, this development has usually been accompanied by the side effects of urbanization, such as increased traffic and its associated problems: traffic congestion, increased accident rates and pollution. As urban populations grow and expand, the importance of GIS lies in its ability to collect a large amount of geospatial data, including human-generated data. This data is necessary to understand the complexity of the city, set priorities, solve complicated planning problems and perform a variety of spatial analysis, which shows not only the feasibility but also the consistency of the proposed infrastructure with the requirements of a sustainable city. In this paper, we demonstrate the benefits of integrating real-time traffic data with GIS technology and remote sensing data for analyzing the impact of infrastructure works and COVID-19 on traffic in Oradea, Romania. The case study was focused on the historical center of Oradea and was based on remote sensing data collected before, during, and after traffic restrictions. The study also shows the need for using GIS and crowdsourcing-based applications in traffic analysis and planning.

Likert-type scales are a common technique used in social science. Plus, the Likert scale is among the most frequently used psychometric tools in social sciences and educational research. Despite its frequently used, the Likert scale raises up many questions mark. We can say that the use of the Likert scale in its classical form is too rigid and loses valuable information. Li (2013, p. 1613) calls on previous studies that "have claimed that fuzzy scales are more accurate than traditional scales due to the continuous nature of fuzzy sets". The aim of this research is to reduce the inaccuracy caused by the use of the Likert scale, by proposing a method of more appropriate processing of data collected in this way. As shown in this paper, fuzzy methods can be a good alternative. The research methodology consists of using the usual technique on the set of fuzzy numbers by considering the input data as linguistic variables, subsequently identified by triangular fuzzy numbers. The obtained scale is more elastic with respect to the input data, therefore it better captures the reality. The newly proposed method is applied in the concrete example of the competitors in the hotel field. The Importance-Performance Competitor Analysis is utilized. A weakness of the method is due to the use in its application of data collection with the Likert scale. The results conclude on the situation of the competitors regarding each attribute considered as in the crisp version of the method, but the identification and processing of data correspond better to the aspects of subjectivity and uncertainty specific to human thinking. A novelty is also the obtaining of a hierarchy within each category of attributes from the quadrants proposed by the Important-Performance Analysis in relation to the competition.