Search results for: housing price prediction

Authors: Tris Kee

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This research investigates social sustainability factors in transitional housing projects and their impact on fostering healthy living environments that promote physical activity and social interaction for residents. Social sustainability is integral to individual health and well-being, as emphasized by Goal 11 of the 2030 Agenda for Sustainable Development, which highlights the importance of safe, affordable, and accessible transport systems, green spaces, and public spaces catering to vulnerable populations' needs. Communal spaces in urban environments are essential for fostering social sustainability, as they serve as settings for physical activities and social interactions among diverse socio-economic groups. Factors such as neighborhood social atmosphere, historical context, social disparity, and mobility can influence the relationship between existing and transitional communities. Mental health effects can be measured through housing segregation, mobility and accessibility, and housing tenure. A significant research gap exists in understanding the living environment of transitional housing in Hong Kong and the social sustainability factors affecting residents' mental and physical health. To address this gap, our study employs a mixed-methods approach combining survey questionnaires and interviews to gather both quantitative and qualitative data. This methodology will provide comprehensive insights into residents' experiences and perceptions. Our research's main contribution is identifying key social sustainability factors in transitional housing and their impact on residents' well-being, informing policy-making and the creation of inclusive, healthy living environments. By addressing this research gap, we aim to provide valuable insights for future housing projects, ultimately promoting the development of socially sustainable transitional communities.

Keywords: social sustainablity, affordable housing, transitional housing, high density housing

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Authors: Jubril Olatunbosun Akinde

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Unplanned population growth are mostly attributed to a lack of infrastructural facilities and poor economic condition in the rural dwellings and the incidence of rural-urban migration, which has resulted in severe housing deficiency in the urban centre, with a resultant pressure on housing delivery in the cities. Affordable housing does not only encompass environmental factors that make living acceptable and comfortable, which include good access routes, ventilation, sanitation and access to other basic human needs, which include water and safety. The research assessed the housing affordability and safety measures in the varied residential area of lagos by examining the demographic and socioeconomic attributes of residents; examining the existing residential safety measures; by examining the residential quality in terms of safety; the researcher therefore examined if relationship between housing affordability and safety in the varied residential areas. The research adopted the bartlett, kotrlik and higgins (2001) method of t-test to determine the sample size which specifies different populations at different levels of significance (α). The researcher adopted primary data which was sourced from a field survey where the sample population was simply randomly selected to give a member of the population an equal chance of being selected, therefore, the sample size for the field survey was two hundred (200) respondents, and subjected to necessary testing. The research come to conclusion that housing safety and security is the responsibility of every resident, the landlords/landladies possess a better sense of security in their neighbourhood than renters in the community, therefore they need to be aware of their responsibility of ensuring the safety of lives and property.

Keywords: housing, housing affordability, housing security, residential, residential quality

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Authors: Helida Thays Gomes Soares, Conceicao De Maria Pinheiro Correia, Fabiano Maciel Soares, Kleymer Silva

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There is great discussion around populational increase in urban areas of the global south, and, consequently, the growth of inappropriate housing and the different ways humans have found to solve housing problems around the world. Sao Luís, the capital of the state of Maranhao is a good example. The 1.6 million inhabitant metropole is a colonial tropical city that shelters 22% of the population of Maranhão, brazilian state that still carries the scars of slavery in past centuries. In 2016, Brazilian Institute of Geography and Statistic found that 20% of Maranhão’s inhabitants were living in houses with external walls made of non-durable materials, like recycled wood, cardboard or soil. Out of this problematic, this study aims to propose interventions not only in the physical structure of irregular housing, but also to serve as a guide to intervene in the way eco-friendly, communitarian housing is seen by extreme poor zones inside metropolitan regions around big cities in the global south. The adaptation and reuse of industrial containers from the Harbor of Itaqui for housing is also an aim of the project. The great volume of discarded industrial containers may be an opportunity to solve housing deficit in the city. That way, through field research in São Luís’ neighborhoods mostly occupied by inappropriate housing, the study intends to raise ethnographical and physical values that help to shape new uses of industrial containers and recycled building materials, bringing the community into the process of shaping new-housing for local housing programs, changing the mindset of a concrete/brick model of building. The study used a general feasibility analysis of local engineers regarding strength of the locally used container for construction purposes, and also researched in-loco the current impressions of risky areas inhabitants of housing, traditional housing and the role they played as city shapers, evaluating their perceptions of what means to live and how their houses represent their personality.

Keywords: container housing, civil construction, housing deficit, participatory design, sustainability

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Authors: Mohammed F. Haddad, Mohammad A. Albenayyan

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Realistically, 3-D printing as a technology has not yet reached the required maturity level to handle construction housing projects for citizens on a country scale. However, potentially, it has all of the required elements for addressing this issue. There are two main high-level elements of this technology that need to be capitalized on in order for the technology to reach its full potential, technical and logistical. This paper aims to cover how 3-D printing can be a viable technical solution for housing projects and describe the impact of 3-D printing technical features on the logistical aspects of completing a housing project. Additionally, a perspective about 3-D printing in Saudi Arabia will be presented in order to give the reader an idea of where the kingdom stands in the deployment of this technology. Finally, a glimpse will be given regarding the potential utilization of this technology for space applications.

Keywords: large-scale 3-D printing, additive manufacturing, D- shape, contour crafting

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Authors: Sisi Xia, Dezhuan Tao, Junyan Yang, Weiting Xiong

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Under the background of Chinese urbanization changing from incremental development to stock development, the completion of urban public service facilities is essential to urban spatial quality. As public services facilities is a huge and complicated system, clarifying the various types of internal rules associated with the land market price is key to optimizing spatial layout. This paper takes Wuxi City as a representative sample location and establishes the digital analysis platform using urban price and several high-precision big data acquisition methods. On this basis, it analyzes the coupling relationship between different public service categories and land price, summarizing the coupling patterns of urban public facilities distribution and urban land price fluctuations. Finally, the internal mechanism within each of the two elements is explored, providing the reference of the optimum layout of urban planning and public service facilities.

Keywords: public service facilities, land price, urban spatial morphology, big data

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Authors: Fathi Abid, Bilel Kaffel

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The olive tree, the olive harvest during winter season and the production of olive oil better known by professionals under the name of the crushing operation have interested institutional traders such as olive-oil offices and private companies such as food industry refining and extracting pomace olive oil as well as export-import public and private companies specializing in olive oil. The major problem facing producers of olive oil each winter campaign, contrary to what is expected, it is not whether the harvest will be good or not but whether the sale price will allow them to cover production costs and achieve a reasonable margin of profit or not. These questions are entirely legitimate if we judge by the importance of the issue and the heavy complexity of the uncertainty and competition made tougher by a high level of indebtedness and the experience and expertise of speculators and producers whose objectives are sometimes conflicting. The aim of this paper is to study the formation mechanism of olive oil prices in order to learn about speculators’ behavior and expectations in the market, how they contribute by their industry knowledge and their financial alliances and the size the financial challenge that may be involved for them to build private information hoses globally to take advantage. The methodology used in this paper is based on two stages, in the first stage we study econometrically the formation mechanisms of olive oil price in order to understand the market participant behavior by implementing ARMA, SARMA, GARCH and stochastic diffusion processes models, the second stage is devoted to prediction purposes, we use a combined wavelet- ANN approach. Our main findings indicate that olive oil market participants interact with each other in a way that they promote stylized facts formation. The unstable participant’s behaviors create the volatility clustering, non-linearity dependent and cyclicity phenomena. By imitating each other in some periods of the campaign, different participants contribute to the fat tails observed in the olive oil price distribution. The best prediction model for the olive oil price is based on a back propagation artificial neural network approach with input information based on wavelet decomposition and recent past history.

Keywords: olive oil price, stylized facts, ARMA model, SARMA model, GARCH model, combined wavelet-artificial neural network, continuous-time stochastic volatility mode

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Authors: Fauzia Dianawati, Riska W. Purnomo

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Food and agricultural sector become the biggest sector contributing to inflation in Indonesia. Especially in Wonogiri district, red cayenne pepper was the biggest sector contributing to inflation on 2016. A national statistic proved that in recent five years red cayenne pepper has the highest average level of fluctuation among all commodities. Some factors, like supply chain, price disparity, production quantity, crop failure, and oil price become the possible factor causes high volatility level in red cayenne pepper price. Therefore, this research tries to find the key factor causing fluctuation on red cayenne pepper by using ARCH/GARCH method. The method could accommodate the presence of heteroscedasticity in time series data. At the end of the research, it is statistically found that the second level of supply chain becomes the biggest part contributing to inflation with 3,35 of coefficient in fluctuation forecasting model of red cayenne pepper price. This model could become a reference to the government to determine the appropriate policy in maintaining the price stability of red cayenne pepper.

Keywords: ARCH/GARCH, forecasting, red cayenne pepper, volatility, supply chain

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Authors: Simone Tedeschi, Francesco Crespi, Paolo Liberati, Massimo Paradiso, Antonio Sciala

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This paper aims at contributing to the understanding of smokers’ responses to cigarette prices increases with a focus on heterogeneity, both across individuals and price levels. To do this, a stated preference quasi-experimental design grounded in a random utility framework is proposed to evaluate the effect on smokers’ utility of the price level and variation, along with social conditioning and health impact perception. The analysis is based on individual-level data drawn from a unique survey gathering very detailed information on Italian smokers’ habits. In particular, qualitative information on the individual reactions triggered by changes in prices of different magnitude and composition are exploited. The main findings stemming from the analysis are the following; the average price elasticity of cigarette consumption is comparable with previous estimates for advanced economies (-.32). However, the decomposition of this result across five latent-classes of smokers, reveals extreme heterogeneity in terms of price responsiveness, implying a potential price elasticity that ranges between 0.05 to almost 1. Such heterogeneity is in part explained by observable characteristics such as age, income, gender, education as well as (current and lagged) smoking intensity. Moreover, price responsiveness is far from being independent from the size of the prospected price increase. Finally, by comparing even and uneven price variations, it is shown that uniform across-brand price increases are able to limit the scope of product substitutions and downgrade. Estimated price-response heterogeneity has significant implications for tax policy. Among them, first, it provides evidence and a rationale for why the aggregate price elasticity is likely to follow a strictly increasing pattern as a function of the experienced price variation. This information is crucial for forecasting the effect of a given tax-driven price change on tax revenue. Second, it provides some guidance on how to design excise tax reforms to balance public health and revenue goals.

Keywords: smoking behaviour, preference heterogeneity, price responsiveness, cigarette taxation, random utility models

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Authors: Tony Rizk

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Recent material advances and cost efficiencies are transforming the housing industry away from traditional lumber and gypsum material to alternate fiberboard material that is workable and resistant to fire, mold, and pest infestation. The use of these materials may add to the initial cost of construction. However, the life cycle (cradle to grave) cost of houses using these construction materials and methods are lower than the life cycle costs using traditional housing construction materials and methods. This paper will present four (4) case studies of sustainable house projects. Each project was designed and constructed using earthen-based, sustainable fiberboard material that is resistant to fire, mold, and infestation and fabricated at a very low material calorific value. These house projects have a living space ranging from 625 sq. ft. for an accessory dwelling unit and up to 3,200 sq. ft. 1-story and 2-story homes. For each case study, we will present the house engineering design and construction method, the initial construction costs, a summary of the life cycle costs, and a comparison to the life cycle cost of traditional housing available in the literature.

Keywords: residential housing, sustainable housing, life cycle cost, fire resistance, mold, infestation resistance

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Authors: Micah Amor P. Yares

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Aside from the provision of adequate housing, the Philippine government faces the challenge of ensuring that the housing units provided conform to the Filipino’s ambition to self as manifested by owning a small house on a big lot. The study aimed to explore the levels of satisfaction of end-users and the public perception towards socialized housing in Davao City, Philippines. The residential satisfaction survey includes three types of respondents, which are end-users of single-detached, duplex and rowhouse socialized housing units. Respondents were asked to rate their level of satisfaction and perception to the following housing components: Dwelling Unit; Public Facilities; Social Environment; Neighborhood Facilities; Management Systems; and Acquisition and Financing. The data were subjected to Exploratory Factor Analysis to determine if variables can be grouped together, and Confirmatory Factor Analysis to measure if the model fits the construct. In determining which component affects the level of perception and satisfaction, a Multiple Linear Regression Analysis was employed. Lastly, an Individual Samples T-Test was performed to compare the levels of satisfaction and perception among respondents. Results revealed that residents of socialized housing were highly satisfied with their living conditions despite concerns on management systems, public and neighborhood facilities. Residents' satisfaction is primarily influenced by the Social Environment, Acquisition and Financing, and the Dwelling Unit. However, a significant difference in residential satisfaction level was observed among different types of housing with rowhouse residents recording the lowest satisfaction level compared to single-detached and duplex units. Moreover, the general public perceived Socialized housing as moderately satisfactory having the same determinant as the end-users aside from the Public Facilities. This study recommends revisiting the current Socialized Housing policies by considering the feedback from the end-users based on their lived experience and the public according to their perception.

Keywords: public perception, residential satisfaction, rowhouse, socialized housing

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Authors: Cheng-yu Hsieh, Bo Zhang, Ahmed Hambaba

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Stock market prediction has long been an area of interest for both expert analysts and investors, driven by its complexity and the noisy, volatile conditions it operates under. This research examines the efficacy of combining the Patch Time Series Transformer (PatchTST) with wavelet transforms, specifically focusing on Haar and Daubechies wavelets, in forecasting the adjusted closing price of the S&P 500 index for the following day. By comparing the performance of the augmented PatchTST models with traditional predictive models such as Recurrent Neural Networks (RNNs), Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Transformers, this study highlights significant enhancements in prediction accuracy. The integration of the Daubechies wavelet with PatchTST notably excels, surpassing other configurations and conventional models in terms of Mean Absolute Error (MAE) and Mean Squared Error (MSE). The success of the PatchTST model paired with Daubechies wavelet is attributed to its superior capability in extracting detailed signal information and eliminating irrelevant noise, thus proving to be an effective approach for financial time series forecasting.

Keywords: deep learning, financial forecasting, stock market prediction, patch time series transformer, wavelet transform

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: Faisal Algosair

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We examine the role of monetary policy in the presence of commodity price shocks using a Dynamic stochastic general equilibrium (DSGE) model with price and wage rigidities. The model characterizes a commodity exporter by its degree of export diversification, and explores the following monetary regimes: flexible domestic inflation targeting; flexible Consumer Price Index inflation targeting; exchange rate peg; and optimal rule. An increase in the degree of diversification is found to mitigate responses to commodity shocks. The welfare comparison suggests that a flexible exchange rate regime under the optimal rule is preferred to an exchange rate peg. However, monetary policy provides limited stabilization effects in an economy with low degree of export diversification.

Keywords: business cycle, commodity price, exchange rate, global financial cycle

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Authors: Gert Van Schalkwyk, Chris Cloete

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South Africa is experiencing a massive housing backlog in urban low-cost housing. A backlog in the transfer of low-cost housing units is exacerbated by various impediments and delays that exist in the current legal framework. Structured interviews were conducted with forty-five practicing conveyancers and fifteen deeds office examiners at the Deeds Office in Pretoria, South Africa. One of the largest, the Deeds Office in Pretoria implements a uniform registration process and can be regarded as representative of other deeds offices in South Africa. It was established that a low percentage of low-cost properties are freely transferable. The main economic impediments are the absence of financing and the affordability or payment of rates and taxes to local government. Encroachment of buildings on neighboring stands caused by the enlargement of existing small units on small stands also causes long-term unresolved legal disputes. In addition, as the transfer of properties is dependent on the proper functioning of administrative functions of various government departments, the adverse service delivery of government departments hampers transfer. Addressing the identified problems will contribute to a more sustainable process for the transfer of low-cost housing units in South Africa.

Keywords: conveyancing, low-cost housing, South Africa, tenure, titling, transfer

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Authors: Shayla He

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Background and Purpose: According to Chamie (2017), it’s estimated that no less than 150 million people, or about 2 percent of the world’s population, are homeless. The homeless population in the United States has grown rapidly in the past four decades. In New York City, the sheltered homeless population has increased from 12,830 in 1983 to 62,679 in 2020. Knowing the trend on the homeless population is crucial at helping the states and the cities make affordable housing plans, and other community service plans ahead of time to better prepare for the situation. This study utilized the data from New York City, examined the key factors associated with the homelessness, and developed systematic modeling to predict homeless populations of the future. Using the best model developed, named HP-RNN, an analysis on the homeless population change during the months of 2020 and 2021, which were impacted by the COVID-19 pandemic, was conducted. Moreover, HP-RNN was tested on the data from Seattle. Methods: The methodology involves four phases in developing robust prediction methods. Phase 1 gathered and analyzed raw data of homeless population and demographic conditions from five urban centers. Phase 2 identified the key factors that contribute to the rate of homelessness. In Phase 3, three models were built using Linear Regression, Random Forest, and Recurrent Neural Network (RNN), respectively, to predict the future trend of society's homeless population. Each model was trained and tuned based on the dataset from New York City for its accuracy measured by Mean Squared Error (MSE). In Phase 4, the final phase, the best model from Phase 3 was evaluated using the data from Seattle that was not part of the model training and tuning process in Phase 3. Results: Compared to the Linear Regression based model used by HUD et al (2019), HP-RNN significantly improved the prediction metrics of Coefficient of Determination (R2) from -11.73 to 0.88 and MSE by 99%. HP-RNN was then validated on the data from Seattle, WA, which showed a peak %error of 14.5% between the actual and the predicted count. Finally, the modeling results were collected to predict the trend during the COVID-19 pandemic. It shows a good correlation between the actual and the predicted homeless population, with the peak %error less than 8.6%. Conclusions and Implications: This work is the first work to apply RNN to model the time series of the homeless related data. The Model shows a close correlation between the actual and the predicted homeless population. There are two major implications of this result. First, the model can be used to predict the homeless population for the next several years, and the prediction can help the states and the cities plan ahead on affordable housing allocation and other community service to better prepare for the future. Moreover, this prediction can serve as a reference to policy makers and legislators as they seek to make changes that may impact the factors closely associated with the future homeless population trend.

Keywords: homeless, prediction, model, RNN

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Authors: Aisha Abdulkarim Aliyu, Alice Sabrina Ismail, Fadhlina Binti Ahmad

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The study's main goal is to improve Afrocentric cultural approaches in Nigerian residential environments (Kano) in terms of physical, aesthetical, and socio-cultural factors. Kano's fast-changing residential settings and city image have been subjected to a significant neoliberal restructuring process in recent decades. Architects have evolved in lockstep with the society they serve, first as an art form, then as a science, and finally as a business that designs structures. Design values have always emphasized a certain building style throughout history. Architects and architectural critics have a different perspective on them than the general public. In fact, a popular style among the general public was taken into consideration. When it comes to the current design, this study examines the values and viewpoints of architects on the usage of an Afrocentric cultural approach to housing. The qualitative data analysis of surveys conducted with Kano housing and planning professionals is used to determine the criteria for using an Afrocentric cultural approach in housing development in order to preserve and restore our cultural heritage, as well as to rank these criteria according to their importance. The professional lens on this subject differs insignificantly across Nigeria, although they do vary to some amount based on the sector of the housing industry, according to the study.

Keywords: architects lens, Afrocentric culture, housing, northern Nigeria

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Authors: H. C. Chinwenyi, H. D. Ibrahim, F. A. Ahmed

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In modern financial mathematics, valuing derivatives such as options is often a tedious task. This is simply because their fair and correct prices in the future are often probabilistic. This paper examines three different Stochastic Differential Equation (SDE) models in finance; the Constant Elasticity of Variance (CEV) model, the Balck-Karasinski model, and the Heston model. The various Martingales option price valuation formulas for these three models were obtained using the replicating portfolio method. Also, the numerical solution of the derived Martingales options price valuation equations for the SDEs models was carried out using the Monte Carlo method which was implemented using MATLAB. Furthermore, results from the numerical examples using published data from the Nigeria Stock Exchange (NSE), all share index data show the effect of increase in the underlying asset value (stock price) on the value of the European Put Option for these models. From the results obtained, we see that an increase in the stock price yields a decrease in the value of the European put option price. Hence, this guides the option holder in making a quality decision by not exercising his right on the option.

Keywords: equivalent martingale measure, European put option, girsanov theorem, martingales, monte carlo method, option price valuation formula

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Saleh Alzahrani, Halim Boussabaine

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The majority of Public Private Partnership (PPP) are developed based on the rationale that the design, construction, operation, and financing of a public project is to be awarded to a private party within a single contractual framework. PPP project risks normally include the development and construction of a new asset as well as its operation for decades. Undoubtedly the most serious consequences of risks during the construction period are price and time overruns. These events are amongst the most broadly used scenarios in value for money analysis risks. The sources of risk change over the life cycle of a PPP project. In traditional procurement, the public sector normally has to cover all price distress from these risks. At least there is plenty evidence to suggest that price distress is a norm in some of the projects that are delivered under traditional procurement. This paper will find the impact of construction risk factors into actual construction price into PPP projects. The paper will present a brief literature review on PPP risk pricing strategies, and then using system dynamics (SD) to analyses of the risks associated with the estimated project price. Based on the finding from these analyses a risk pricing association model is presented and discussed. The paper concludes with thoughts for future research.

Keywords: Public Private Partnership (PPP), Risk, Risk Pricing, System Dynamics (SD), construction price

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Authors: Saif Ul Haq

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The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.

Keywords: construction industry, quality considerations, quality function deployment, safety considerations

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Authors: Han Bing, Yin Zhenjie

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In order to analyze the status of a diesel engine, as well as conduct fault prediction, a new prediction model based on a gray system is proposed in this paper, which takes advantage of the neural network and the genetic algorithm. The proposed GBPGA prediction model builds on the GM (1.5) model and uses a neural network, which is optimized by a genetic algorithm to construct the error compensator. We verify our proposed model on the diesel faulty simulation data and the experimental results show that GBPGA has the potential to employ fault prediction on diesel.

Keywords: fault prediction, neural network, GM(1, 5) genetic algorithm, GBPGA

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Authors: Madifedile Thasi, Azola Mayeza

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In South Africa, provision of housing to the growing population has been described as one of the greatest challenges facing the government. Between 1994 to 2015, more than 2.5 million housing units were provided by the government for the poorest households and the low-income earners under the Reconstruction and Development Programme (RDP). Yet, the latest census figure revealed that about 2.1 million households still live in shacks and informal dwellings. Human settlements patterns remain dysfunctional across in South Africa because of rapid urbanisation. The housing backlog is growing at a rate of 178 000 units a year. The aforementioned predicament calls the need for innovative approaches to address the issue in a sustainable way and this need not be overemphasized. Aside from the issue of cost, the delivery of more housing units comes with environmental and sustainability issues. The prefabrication building technology has resulted into accelerated housing delivery to a satisfactory level in some countries such as Nigeria and Malaysia that are facing similar issue. It is therefore expected to be a foremost option to address the social housing backlog in South Africa and within the country housing sustainability agenda. This paper appraises the factors responsible for the limited implementation of prefabrication technology in South African housing projects. The objective is to recommend the method and materials that can be best sustained in the country in terms of local availability, cost effectiveness and environmental friendliness. It presents empirical data to support the hypothesis that a wider implementation of prefabrication technology in the social housing projects will be of significant benefit, by providing fast turnaround, cost-effective and sustainable solution that will dent the housing backlog, as well as improving the quality of the social housings. It was found that only 17 000 units of the RDP housings provided were constructed using alternative building technologies. Furthermore, there are variety of prefabricated technologies in the market but mostly have limited production capacity, minimal manufacturing capacity and most materials are imported, which leads to unavailability of the technology for large scale delivery and utilization despite its obvious advantages.

Keywords: prefabrication technology, sustainable social housings, South Africa, housing delivery

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Authors: Claudia Aguilar, Amen Farooq

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Among other cities in the United States, the city of Atlanta is experiencing levels of growth that surpass anything we have witnessed in the last century. With the surge of population influx, the available housing is practically bursting at the seams. Supply is low, and demand is high. In effect, the average one-bedroom apartment runs for 1,800 dollars per month. The city is desperately seeking new opportunities to provide affordable housing at an expeditious rate. This has been made evident by the recent updates to the city’s zoning. With the recent influx in the housing market, young professionals, in particular millennials, are desperately looking for alternatives to stay within the city. To remedy Atlanta’s affordable housing crisis, the city of Atlanta is planning to introduce 40 thousand of new affordable housing units by 2026. To achieve the urgent need for more affordable housing, the architectural response needs to adapt to overcome this goal. A method that has proven successful in modern housing is to practice modular means of development. A method that has been constrained to the dimensions of the max load for an eighteen-wheeler. This approach has diluted the architect’s ability to produce site-specific, informed design and rather contributes to the “cookie cutter” stigma that the method has been labeled with. This thesis explores the design methodology for modular housing by revisiting its constructability and adaptability. This research focuses on a modular housing type that could break away from the constraints of transport and deliver adaptive reconfigurable assemblies. The adaptive assemblies represent an integrated design strategy for assembling the future of affordable dwelling units. The goal is to take advantage of a component-based system and explore a scalable solution to modular housing. This proposal aims specifically to design a kit of parts that are made to be easily transported and assembled but also gives the ability to customize the use of components to benefit all unique conditions. The benefits of this concept could include decreased construction time, cost, on-site labor, and disruption while providing quality housing with affordable and flexible options.

Keywords: adaptive assemblies, modular architecture, adaptability, constructibility, kit of parts

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Authors: Asiye Aydilek, Harun Aydilek

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We investigate the costs of various suboptimal allocations in housing, consumption, bond and stock holdings of a retiree in a setting with recursive utility, considering the extensive empirical evidence that investors make suboptimal decisions in different ways. We find that suboptimal stock holdings impose only modest costs on the retiree. This may have a merit in explaining the limited stock investment in the data. The cost of suboptimal bond holdings is higher than that of stocks, but still small. This may partially explain why many more people hold bonds compared to stocks. We find that positive deviations from the optimal level are less costly relative to the negative ones in suboptimal housing allocations. This may help us to clarify why the elderly are over consuming housing, as seen in the housing data. The cost of suboptimal consumption is quite high and the highest of all. Our paper suggests that, in terms of welfare, the decisions of how much of liquid wealth to use for consumption and for saving are more important than the decision about the composition of liquid savings. Suboptimal stock holdings are twice more costly in power utility and suboptimal bond holdings are twenty times more costly in recursive utility. Recursive utility is superior to power utility in terms of rationalizing many people's preference for bonds instead of stocks in investment.

Keywords: housing, recursive utility, retirement, suboptimal decisions, welfare cost

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Zhaojun Wang, Zongdi Sun, Zhiyuan Liu

Abstract:

First of all, the carbon trading price and trading volume in Shanghai are transformed by Fourier transform, and the frequency response diagram is obtained. Then, the frequency response diagram is analyzed and the Blackman filter is designed. The Blackman filter is used to filter, and the carbon trading time domain and frequency response diagram are obtained. After wavelet analysis, the carbon trading data were processed; respectively, we got the average value for each 5 days, 10 days, 20 days, 30 days, and 60 days. Finally, the data are used as input of the Back Propagation Neural Network model for prediction.

Keywords: Shanghai carbon trading, carbon trading price, carbon trading volume, wavelet analysis, BP neural network model

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Authors: Poorva Kulkarni

Abstract:

Developing countries are having significant additions to existing population of urban areas with loads of migrants from rural areas. There is a tremendous need to provide accommodation facility to cater to rapidly growing urban population. This leads to unprecedented growth in urban areas since the temporary shelters are constructed with any available material. Architecture in a broader sense serves to humanity in terms of making life of people happy and comfortable by providing comfortable shelters. It is also the need of the time for an architect to be extremely sensitive towards nature by providing design solution of human shelters with minimum impact on the environment. The sensitive approach towards designing of housing units and provision of comfortable and affordable housing units should go hand in hand for future growth of developing countries. Steel has proved itself a versatile material in terms of strength, uniformity and ease of operation and many such other advantages. Steel can be used as the most promising material for modern construction practices. The current research paper focuses on how effectively steel can be used probably in combination with other construction material to achieve the mentioned objectives for sustainable housing. The research available on sustainable housing in steel is studied along with few case studies of buildings with the efficient use of steel providing a solution with affordability and minimum harm to the environment. The research will conclude the effective solutions exploring possibilities of use of steel for sustainable housing units. The researcher shows how the use of steel in combination with other materials for human shelters can promote sustainable housing for community living which is the need of the time.

Keywords: community living, steel, sustainable housing, urban area

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Authors: Tatenda Manomano

Abstract:

The chronic challenges presented by HIV/AIDS globally have come with extreme negative effects on individuals, families and communities as well as governments. Sub-Saharan Africa remains strongly challenged with South Africa bearing a huge brunt of these. The paper examines the extent to which the effects of HIV/AIDS are addressed in low cost housing projects in South Africa with a case of the RDP Golf Course Housing Project in Alice Town. The study used a triangulation of both qualitative and quantitative methods with the qualitative as the dominant method while the quantitative was less dominant. Findings revealed that infection rate was high; prostitution was high; alcohol abuse was also high; and rape and sexual abuse was also high and there was also lack of hospitals and social workers around the location. These findings prompted this researcher to recommend for proactive policy making that can bolster the challenges faced by these low cost housing projects in accessing health and social services as well as massive campaigns that can promote behavior modification among other things. It is hoped that this paper will be a platform to ring a bell to both government and non-government to augment the campaign against HIV/AIDS in South Africa.

Keywords: HIV/AIDS, RDP houses, low cost housing projects, campaigns

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Authors: Ruhizal Roosli, Julaihi Wahid, Abu Hassan Abu Bakar, Faizal Baharum

Abstract:

This paper reports on the progress of a study on the reconstruction project after the ‘Yellow Flood’ disaster in Kelantan, Malaysia. Malaysia still does not have guidelines to build housing after a disaster especially in disaster-prone areas. At the international level, many guidelines have been prepared that is found suitable for post-disaster housing. Which guidelines can be adapted that best describes the situation in Malaysia? It was reported that the houses should be built on stilts, which can withstand certain level of impact during flooding. Unfortunately, until today no specific guideline was available to assist homeowners to rebuild their homes after disaster. In addition, there is also no clear operational procedure to monitor the progress of this construction work. This research is an effort to promoting resilient housing; safety and security; and secure tenure in a prone area. At the end of this study, key lessons will be emerged from the review process and data analysis. These inputs will then have influenced to the content that will be developed and presented as guidelines. An overall objective is to support humanitarian responses to disaster and conflicts for resilience house construction to flood prone area. Interviews with the field based staff were from recent post-disaster housing workforce (disaster management mechanism in Malaysia especially in Kelantan). The respondents were selected based on their experiences in disaster response particularly related to housing provision. These key lessons are perhaps the best practical (operational and technical) guidelines comparing to other International cases to be adapted to the national situations.

Keywords: disaster, guideline, housing, Malaysia, reconstruction

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Authors: Ghazaleh Monazami Tehrani, Zhamak Monazami Tehrani, Raziyeh Hadavand

Abstract:

Optimal site selection for temporary housing is one of the most important issues in crisis management. In this research, district six of Tehran city with high frequency and geographical distribution of earthquakes has been selected as a case study for positioning temporary housing after a probable earthquake. For achieving this goal this study tries to identify and evaluate distribution of location according to some standards such as compatible and incompatible urban land uses with utility of GIS and AHP. The results of this study show the most susceptible parts of this region in the center. According to the maps, north eastern part of Kordestan, Shaheed Gomnam intersection possesses the highest pixels value in terms of areal extent, therefore these places are recommended as an optimum site location for construction of emergency evacuation base.

Keywords: optimal site selection, temporary housing , crisis management, AHP, GIS

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