International Journal of Human Capital in Urban Management
Volume:6 Issue: 1, Winter 2021

The COVID-19 pandemic has created a global health crisis that had a deep impact on the world and our everyday lives. The deadly virus i.e. SARS-CoV-2 has rapidly spread around the world, posing enormous health, social, economic, and environmental challenges to the entire human population. Countries around the world have implemented complete or partial lockdown measures to mitigate the spread of the coronavirus. Corona lockdown has profound social implications and it has sparked fears of impending economic trouble and recession.

However, this lockdown has also shown some positive effects on the natural environment due to the reduction of pollutant loading from vehicle emission, industries, and other sources. Based on a review of recent research in the relevant area, this paper assesses the effect of COVID-19 pandemic on air and water quality as well as on environmental noise.

A substantial reduction in the level of noxious NO2, particulate matter, and carbon emissions have been observed during the lockdown period, the lockdown also led to an appreciable drop in BOD (biological oxygen demand) and a significant increase in DO (dissolved oxygen) of different river water globally. In addition to this, the anthropogenic noise level has fallen by about one-third due to the COVID-19 lockdown.

This study reveals that there is a substantial possibility for healing the environment from the detrimental effects of anthropogenic activities through partial or temporary lockdown measures.

Sound is one of the most important tools for recognizing urban spaces. Zandieh area of Shiraz as one of the historic context shaped during the ages hase been chosen in order to obtain a proper response to the individual's perception of urban historic spaces soundscape. The main object of this manuscript achieves a sufficient way in order to organize urban soundscape by utilizing assessments and perception data perceived by users. The narrative interview method (a sample group of 129 users who were active in space for more than 30 minutes) and behavior observation which are subsets of the sound walking technique have been used; Also, the data which were collected in the previous stage, based on the components of the Kano model, were categorized into three categories of basic, performance and attractiveness. With regard to the findings and assessments in the case study, it can be inferred that 69% of the urban space's users perceive noises such as underpass fans' noise more than any others; Consequently, this has led to the lack of acceptance by space users; Also, it was cleared by interviewing listeners in urban space that 59% of the interviewees have preferred natural Sounds to human and 76% preferred tranquility at the urban environment While only 11% of the users preferred the development of a vibrant space. Base on that strategies such as planting vegetation in order to prevent the street noise, allocating water bodies in order to have water sound with proper shading and a Desirable view of historical spaces to increase the sense of richness have been presented. Also, in order to achieve an efficient method to improve the soundscapes of urban environments, basic strategies, performance strategies and at last strategies for increasing the attractiveness of urban environments' soundscape should be implemented.

Small and medium enterprises still exhibit dominant contribution to the economy. Small and medium enterprises manage to absorb greater labor force and to survive the economic crisis. Various efforts to empower small and medium enterprises have been less successful. Financing constraint, low quality of human resources, and limited marketing competence have been the typical problems of small and medium enterprises  that harm small and medium enterprises performance. Despite these problems, SMEs still manage to survive. Using the sampling method of stratified random sampling with area strata, this study generates 203 small business units as the sample. The research was conducted by using accidental sampling. The quantitative and qualitative data are from primary and secondary sources.  The data was collected by using observation, interview, and in-depth interview. The variables in this research was analyzed by using path analysis. Social capital positively affect small and medium enterprises ’ financing as indicated by the significance value of 0.000 (< α= 5%). The stronger social capital of small and medium enterprises implied greater access of external financing sources. Social capital, and small and medium enterprises financing positively affect small and medium enterprises  performance with 1% confidence level, and human resources positively affect small and medium enterprises performance with 6% confidence level. The finding shown the stronger social capital and human resources increases SMEs performance. The results show that social capital and SMEs’ financing positively affect SMEs’ performance, and human resources positively affect small and medium enterprises performance. The results imply that stronger social capital and human resources increases small and medium enterprises performance.  Social capital facilitates access to finance, marketing, production, and information. The results shows that human resources affect SMEs’ performance. Social capital and human resources positively affect small and medium enterprises financing. Similarly, social capital, human resources, and financing positively affect SMEs’ performance.

This study evaluated temperature and urban heat island variability in days of the week and weekends of Port Harcourt city, due to the continuous heat stress and resultant health disaster common in tropical countries such as Nigeria. The data were generated from field observation and Satellite Remote Sensing using Google Earth Engine of Landsat 5, 7, and 8 thermal infrared sensors. Temperature data from the field were captured with LCD Digital Multi-Thermometer Loggers located at different land-use types of 35 sample points in wet and dry seasons. Analysis of Variance was used to establish the temperature difference between days of the week and weekend. The rural site during days of the week had temperature of 29.30C and the weekend had 29.50C indicating a concentration of human activities at the rural fringes during the weekend. The temperature of Saturday and Sunday varied between 33.20C and 27.60C (5.60C) with an urban heat island difference of 1.90C. Saturday was the coolest day having 3.70C. During days of the week, Monday had the highest UHI of 70C with the least UHI of 4.20C recorded on Friday showing the coolest day. The temperature difference between days of the week and weekend was 0.20C and UHI variation of 0.40C indicating that days of the week were warmer. The result showed that temperature in days of the week and the weekend differed significantly. It was established that days of the week contributed 52% of the temperature condition of Port Harcourt city and weekend donated 48% showing that 3,095,342 occupants of the city experienced lesser thermal stress during the weekend. Thus, the study concluded that the temperature of urban areas decreased from the city center to the rural fringes. The land surface temperature indicated that the north-eastern part of the city was the warmest. The study recommends proactive city planning and management framework with effective urban greening implementation for a healthy city living.

One of the short-term strategies to manage the traffic and make a balance between travel supply and demand for the near future is the short-term prediction of traffic parameters and informing the passengers. Therefore passengers are more likely to avoid traveling during traffic peak hours. In this study, hourly average traffic speed and hourly traffic volume as two traffic parameters that indicate traffic state are predicted for Karaj-Chaloos road in Iran. Since traffic data have large volume, machine learning-based models have more suitable performance than traditional models. However, it is not merely possible to discover the cause and effect relationships and the importance of features. In this study, after using the artificial neural network and K-nearest neighbor models to predict traffic parameters, to analyze the sensitivity of the results, the importance of used features is investigated. Also, the effect of passing the time over the accuracy of predictions has been examined. According to the results, the highest accuracy of predicting hourly traffic volume and hourly average traffic speed is achieved by the K-nearest neighbor that is equal to 61% and 91%, respectively. Compared to the historical average as a benchmark model, a significant improvement in the accuracy of predictions has been obtained by the artificial neural network and K-nearest neighbor models.

People usually welcome the spirit of cooperation to meet their needs using different methods and goals. In cities, the formation of non-governmental councils and organizations reflects this trend with the aim of creating equal social opportunities and positions (power, dignity). Participation and e-participation offers an intellectual and doctrinal framework with major applications in social, economic, cultural, and political dimensions of a country. This article aims to explore the association between participation and moral, religious, political, and psychological variables in Iranian urban management as a model.

This is a qualitative research and a descriptive-analytical method has been adopted for modeling.

The results suggest a positive correlation between participation and four variables studied along with their applications in the Iranian urban management. Another finding of the research is the modeling of moral, religious-Islamic, political, and psychological variables related to Iranian participation and urban management toward urban governance.

The elevated social and political awareness of citizens has also led to social solidarity and the strengthening of democracy based on participation. Efforts to redistribute power in the urban system management represent another effect of social participation in urban management and urban governance in Iran. It is also experiencing the transition from urban government to urban governance with participatory, law-abiding, transparency, justice, efficiency, accountability, and decentralization approaches.

Ride-hailing is a term to describe booking rides and paying for car services through a smartphone app with a Transportation Network Company. As an innovation in the ride-hailing investigation in Iran, this paper is sought to analyze the influence of individual's demographic characteristics on their travel mode choice between ride-hailing, traditional taxi and private car. For this purpose, questionnaires in six different statuses have been designed, and 414 questionnaires have been completed in 22 districts of Tehran metropolitan region.

To check the utility of choosing private car and traditional taxi compared to ride-hailing, on short, medium, and, long travel distances with commuting and non-commuting purposes in the peak hours of morning and evening, the six multinomial logit models have been done by considering the ride-hailing option as reference alternative, and the private car and traditional taxi options as the first and second `

Initially, six logit models were generated, which fitted models are all appropriate. All of the variables used in these models in choosing private car or traditional taxis compared to ride-hailing in different models were statistically significance. But, gender, household dimension, and individuals' educational level didn’t affect the individual's choice.

The results showed that ride-hailing is more acceptable to younger people, and high-income people attract more to it. Therefore, ride-hailing services can be considered as a wealthy phenomenon and for the young generation. In addition, given the 67% response of individuals incline to use ride-hailing services in a shared way, because of the interest of individuals to use this mode of travel due to its lower cost in some situations, which can be considered as a separate mode of transportation.

The study was conducted with the objective of selecting suitable site for urban green space development of Arba Minch town in Ethiopia using geographic information system and remote sensing based multi criterion analysis. To produce suitable site, four parameters were considered, these are slope, land use land cover, distance to the main river and distance to road. Supervised classification followed by reclassification were done to classify suitable land use land cover for urban green space, digital elevation model data were used to generate slope suitability and buffering with different distance were used to produce suitable site using distance to the road and distance to the main river parameters’. Although a variety of techniques exist for the development of weight, one of the most promising techniques was the Pairwise Comparison Matrix in the context of a decision making process known as the Analytical Hierarchy Process and ratings were provided on a nine-point continuous scale, which ranges from 1 to 9. The most important parameters’ to predict the location of urban green space in the study area were distance to the main river followed by distance to the road as the experts’ rate it. Although, slope and land use land cover parameters’ are very important, they do not seem to have noticeable effect on urban green space development as of the experts’ response. So, on the bases of the ranks given by the experts the highest value was calculated for river which was 51.28%. The result shows that high suitability accounts 36.3 % of the total area, 45.5 % of the area is moderately suitable and the remaining 18.5 % of the town is not suitable for urban green space.