Search results for: housing sale price

Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut

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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.

Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems

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Authors: Victoria Masi Haruna Karatu, Nik Kamariah Nikmat

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In recent times awareness about the environment and green purchase has been on the increase across nations due to global warming. Previous researchers have attempted to determine what actually influences the purchase intention of consumers in this environmentally conscious epoch. The consumers too have become conscious of what to buy and who to buy from in their purchasing decisions as this action will reflect their concern about the environment and their personal well-being. This trend is a widespread phenomenon in most developed countries of the world. On the contrary evidence revealed that only 5% of the populations of Nigeria involve in green purchase activities thus making the country lag behind its counterparts in green practices. This is not a surprise as Nigeria is facing problems of inadequate green knowledge, non-enforcement of environmental regulations, sensitivity to the price of green products when compared with the conventional ones and distrust towards green products which has been deduced from prior studies of other regions. The main objectives of this study is to examine the direct antecedents of green purchase intention (green availability, government regulations, perceived green knowledge, perceived value and green price sensitivity) in Nigeria and secondly to establish the mediating role of perceived behavioral control on the relationship between these antecedents and green purchase intention. The study adopts quantitative method whereby 700 questionnaires were administered to lecturers in three Nigerian universities. 502 datasets were collected which represents 72 percent response rate. After screening the data only 440 were usable and analyzed using structural equation modeling (SEM) and bootstrapping. From the findings, three antecedents have significant direct relationships with green purchase intention (perceived green knowledge, perceived behavioral control, and green availability) while two antecedents have positive and significant direct relationship with perceived behavioral control (perceived value and green price sensitivity). On the other hand, PBC does not mediate any of the paths from the predictors to criterion variable. This result is discussed in the Nigerian context.

Keywords: Green Availability, Green Price Sensitivity, Green Purchase Intention, Perceived Green Knowledge, Perceived Value

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Authors: Sudikshya Bhandari, Jonathan K. London

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Barpak in northern Nepal represents a unique identity expressed through the local rituals, values, lifeways and the styles of vernacular architecture. The traditional residential buildings and construction practices adopted by the dominant ethnic groups: Ghales and Gurungs, reflect environmental, social, cultural and economic concerns. However, most of these buildings did not survive the Gorkha earthquake in 2015 that made many residents skeptical about their strength to resist future disasters. This led Barpak residents to prefer modern housing designs primarily for the strength but additionally for convenience and access to earthquake relief funds. Post-earthquake reconstruction has transformed the cohesive community, developed over hundreds of years into a haphazard settlement with the imposition of externally-driven building models. Housing guidelines provided for the community reconstruction and earthquake resilience have been used as a singular template, similar to other communities on different geographical locations. The design and construction of these buildings do not take into account the local, historical, environmental, social, cultural and economic context of Barpak. In addition to the physical transformation of houses and the settlement, the consequences continue to develop challenges to sustainability. This paper identifies the major challenges for environmental sustainability with the construction of new houses in post-earthquake Barpak. Mixed methods such as interviews, focus groups, site observation, and documentation, and analysis of housing and neighborhood design have been used for data collection. The discernible changing situation of this settlement due to the new housing has included reduced climatic adaptation and thermal comfort, increased consumption of agricultural land and water, minimized use of local building materials, and an increase in energy demand. The research has identified that reconstruction housing practices happening in Barpak, while responding to crucial needs for disaster recovery and resilience, are also leading this community towards an unsustainable future. This study has also integrated environmental, social, cultural and economic parameters into an assessment framework that could be used to develop place-based design guidelines in the context of other post-earthquake reconstruction efforts. This framework seeks to minimize the unintended repercussions of unsustainable reconstruction interventions, support the vitality of vernacular architecture and traditional lifeways and respond to context-based needs in coordination with residents.

Keywords: earthquake, environment, reconstruction, sustainability

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Authors: Esra Yaldız, Tugba Bulbul Bahtiyar, Dicle Aydın

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Humans meet their need for shelter via housing which they structure in line with habits and necessities. In housing culture, traditional dwelling has an important role as a social and cultural transmitter. It provides concrete data by being planned in parallel with users’ life style and habits, having their own dynamics and components as well as their designs in harmony with nature, environment and the context they exist. Textures of traditional dwelling create a healthy and cozy living environment by means of adaptation to natural conditions, topography, climate, and context; utilization of construction materials found nearby and usage of traditional techniques and forms; and natural isolation of construction materials used. One of the examples of traditional settlements in Anatolia is Kilistra (Gökyurt) settlement of Konya province. Being among the important centers of Christianity in the past, besides having distinctive architecture, culture, natural features, and geographical differences (climate, geological structure, material), Kilistra can also be identified as a traditional settlement consisting of family, religious and economic structures as well as cultural interaction. The foundation of this study is the traditional residential texture of Kilistra with its unique features. The objective of this study is to assess the conformity of traditional residential texture of Kilistra with present topography, climatic data, and geographical values within the context of human scale construction, usage of green space, indigenous construction materials, construction form, building envelope, and space organization in housing.

Keywords: traditional residential architecture, Kilistra, Anatolia, Konya

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Authors: Marlen Acosta Alamo, Lisa Manne, Richard Veit

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Habitat loss due to land use change is one of the leading causes of biodiversity loss worldwide. This form of habitat loss is a non-random phenomenon since the same environmental factors that make an area suitable for supporting high local biodiversity overlap with those that make it attractive for urban development. We aimed to compare the effect of two non-random habitat loss predictors on the richness, abundance, and rarity of nature-affiliated and human-affiliated North American breeding birds. For each group of birds, we simulated the non-random habitat loss using two predictors: the House Price Index as a measure of the attractiveness of an area for humans and the Normalized Difference Vegetation Index as a proxy for primary productivity. We compared the results of the two non-random simulation sets and one set of random habitat loss simulations using an analysis of variance and followed up with a Tukey-Kramer test when appropriate. The attractiveness of an area for humans predicted estimates of richness loss and increase of rarity higher than primary productivity and random habitat loss for nature-affiliated and human-affiliated birds. For example, at 50% of habitat loss, the attractiveness of an area for humans produced estimates of richness at least 5% lower and of a rarity at least 40% higher than primary productivity and random habitat loss for both groups of birds. Only for the species abundance of nature-affiliated birds, the attractiveness of an area for humans did not outperform primary productivity as a predictor of biodiversity following habitat loss. We demonstrated the value of the House Price Index, which can be used in conservation assessments as an index of the risks of habitat loss for natural communities. Thus, our results have relevant implications for sustainable urban land-use planning practices and can guide stakeholders and developers in their efforts to conserve local biodiversity.

Keywords: biodiversity loss, bird biodiversity, house price index, non-random habitat loss

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Authors: Ivelise M. Strozberg, Juliana Sales Frota, Lucas de Oliveira Vale

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The state of Ceara, located in the northeast region of Brazil, is abundant in lateritic soil which has been usually discarded due to its lack of agricultural potential while materials of similar nature have been used as constituents of housing constructive elements in many parts of the world, such as India and Portugal, for decades. Since many of the semi-arid housing conditions in the state of Ceara fail to meet the minimum criteria regarding comfort and safety requirements, this research proposed to study the Ceara lateritic soil and the possibility of its use as a sustainable building block constituent for social housings, collaborating to the improvement of the region living conditions. In order to achieve this objective, soil samples were collected from five different locations within the specific region, three of which presented lateritic nature, being characterized according to the Unified Soil Classification System and the MCT methodology, which is a Brazilian methodology developed during the 80’s that aimed to better describe and approach tropical soils, its characterization and behavior. Two of these samples were used to build two different miniature block prototypes, which were manually molded, heated at low temperatures -( < 300 ºC) in order to save energy and lessen the CO₂ high emission rate common in traditional burning methods- and then submitted to load tests. Among the soils tested, the one with the highest degree of laterization and greater presence of fines constituted the block with the best performance in terms of flexural strength tensions, presenting resistance gains when heated at increasing temperatures, which can indicate that this type of soil has potential towards being used as constructing material.

Keywords: constructive blocks, lateritic soil, MCT methodology, sustainability

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Authors: Mehrab Gholami Zangalani, Siavash Rajabpour

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In compliance with the Statistical Centre of Iran (SCI)’s results, construction and housing section in Iran is consuming 40% of energy, which is 5 times more than the world average consumption. By considering the climate in Iran, the solutions in terms of design, construction and exploitation of the buildings by utilizing the LEED rating system (LRS) is presented, regarding to the reasons for the high levels of energy consumption during construction and housing in Iran. As a solution, innovative Work Break Structure (WBS) in accordance with LRS and Iranian construction’s methods is unveiled in this research. Also, by amending laws pertaining to the construction in Iran, the huge amount of energy and cost can be saved. Furthermore, with a scale-up of these results to the scale of big cities such as Tehran (one of the largest metropolitan areas in the middle east) in which the license to build more than two hundred and fifty units each day is issued, the amount of energy and cost that can be saved is estimated.

Keywords: costs reduction, energy statistics, leed rating system (LRS), work brake structure (WBS)

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Authors: Rahmatollah Amirjani

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By the emergence of the debate over the failure of Regionalism in the late 1970s, Critical Regional­ism was introduced as a different way to respond to the state of architecture in the post-war era. Critical Regionalism is most often understood as a discourse that not only mediates the language of modern architecture with the local cultures but also revives the relation between architecture and spectator as indexed by capitalism. Since the inception of Critical Regionalism, a large number of architectural practices have emerged around the globe; however, the work of the well-known Portuguese architect, Álvaro Siza, is considered as a unique case amongst works associated with the discourse of Critical Regionalism. This paper intends to respond to a number of questions, including; what are the origins of Critical Regionalism? How does Siza’s design strategy correspond to the thematic of Critical Regionalism? How does Siza recover the relation between object and subject in most of his projects? Using Siza’s housing project for the Malagueira district in Évora, Portugal, this article will attempt to answer these questions, and highlight Alvaro Siza’s design procedure which goes beyond the existing discourse of Critical Regionalism and contributes to our understanding of this practice.

Keywords: Alvaro Siza, critical regionalism, Malagueira housing, placelessness

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Authors: Deniz Peksen

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This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

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Authors: Scott Kelting, Lucas Nozick

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The perpetually growing population and economy within the United States necessitates building construction of all types. Increased building generates environmental concerns, and rightfully so. This industry accounts for approximately 4% of the total GDP in the United States while creating around two-thirds of the material waste annually. The green building movement is certainly gaining popularity in both application and recognition through entities such as the United States Green Building Council (USGBC) and their LEED program; however, builders are also producing their ideas. Alternative housing solutions that include pre-fabricated building components and shipping container homes are making great strides in the residential construction industry, and will certainly play an important role in the future. This paper will compare the cost and schedule of modular, panelized and shipping container homes to traditional stick frame home construction in the Greater Los Angeles Metropolitan Area and recommend the best application for each option.

Keywords: cost, prefabricated, schedule, shipping container, stick framed

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Authors: Sahar Navabakhsh, Rokia Raslan, Yair Schwartz

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Decision-making on regeneration of housing estates, whether to refurbish or re-build, has been mostly triggered by economic factors. To enable sustainable growth, it is vital that environmental and social impacts of different scenarios are also taken into account. The methodology used to include all the three sustainable development pillars is called Life Cycle Sustainability Assessment (LCSA), which comprises of Life Cycle Assessment (LCA) for the assessment of environmental impacts of buildings. Current practice of LCA is regularly conducted post design stage and by sustainability experts. Not only is undertaking an LCA at this stage less effective, but issues such as the limited scope for the definition and assessment of environmental impacts, the implication of changes in the system boundary and the alteration of each of the variable metrics, employment of different Life Cycle Impact Assessment Methods and use of various inventory data for Life Cycle Inventory Analysis can result in considerably contrasting results. Given the niche nature and scarce specialist domain of LCA of buildings, the majority of the stakeholders do not contribute to the generation or interpretation of the impact assessment, and the results can be generated and interpreted subjectively due to the mentioned uncertainties. For an effective and democratic assessment of environmental impacts, different stakeholders, and in particular the community and design team should collaborate in the process of data collection, assessment and analysis. This paper examines and evaluates a participatory approach to LCSA through the analysis of a case study of a housing estate in South West London. The study has been conducted throughout tier-based collaborative methods to collect and share data through surveys and co-design workshops with the community members and the design team as the main stakeholders. The assessment of lifecycle impacts is conducted throughout the process and has influenced the decision-making on the design of the Community Plan. The evaluation concludes better assessment transparency and outcome, alongside other socio-economic benefits of identifying and engaging the most contributive stakeholders in the process of conducting LCSA.

Keywords: life cycle assessment, participatory LCA, life cycle sustainability assessment, participatory processes, decision-making, housing estate regeneration

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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: Krishang Surapaneni

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The goal of this project is to determine how to predict important aspects of options, including the ask price. We want to compare different machine learning models to learn the best model and the best hyperparameters for that model for this purpose and data set. Option pricing is a relatively new field, and it can be very complicated and intimidating, especially to inexperienced people, so we want to create a machine learning model that can predict important aspects of an option stock, which can aid in future research. We tested multiple different models and experimented with hyperparameter tuning, trying to find some of the best parameters for a machine-learning model. We tested three different models: a Random Forest Regressor, a linear regressor, and an MLP (multi-layer perceptron) regressor. The most important feature in this experiment is the ask price; this is what we were trying to predict. In the field of stock pricing prediction, there is a large potential for error, so we are unable to determine the accuracy of the models based on if they predict the pricing perfectly. Due to this factor, we determined the accuracy of the model by finding the average percentage difference between the predicted and actual values. We tested the accuracy of the machine learning models by comparing the actual results in the testing data and the predictions made by the models. The linear regression model performed worst, with an average percentage error of 17.46%. The MLP regressor had an average percentage error of 11.45%, and the random forest regressor had an average percentage error of 7.42%

Keywords: finance, linear regression model, machine learning model, neural network, stock price

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Authors: Siphat Lim

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This study used Autoregressive Distributed Lag (ARDL) approach to cointegration. In the long-run the general price level and exchange rate have a positively significant effect on domestic output. The estimated result further revealed that fiscal stimulus help stimulate domestic output in the long-run, but not in the short-run, while monetary expansion help to stimulate output in both short-run and long-run. The result is complied with the theory which is the macroeconomic policies, fiscal and monetary policy; help to stimulate domestic output in the long-run. The estimated result of the Vector Error Correction Model (VECM) has indicated more clearly that the consumer price index has a positive effect on output with highly statistically significant. Increasing in the general price level would increase the competitiveness among producers than increase in the output. However, the exchange rate also has a positive effect and highly significant on the gross domestic product. The exchange rate depreciation might increase export since the purchasing power of foreigners has increased. More importantly, fiscal stimulus would help stimulate the domestic output in the long-run since the coefficient of government expenditure is positive. In addition, monetary expansion would also help stimulate the output and the result is highly significant. Thus, fiscal stimulus and monetary expansionary would help stimulate the domestic output in the long-run in Cambodia.

Keywords: fiscal policy, monetary policy, ARDL, VECM

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Authors: Jorge Eliseo Muñiz-Gutierrez, Daniel Olvera-García, Cristina Sotelo-Salas

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The objective of this research is to allow the understanding of the hybridization process shown in culture through the architecture of mass production for the purpose of consumption, taking as a case study the mass-built housing of the city of Mexicali, Mexico. The methodology is born from the hermeneutical study of the meta-modified architectural object, which guided the research with a qualitative focus to be carried out in two stages, the first is based on the literature review regarding cultural hybridization, and the second stage is carried out in through an ethnographic study of the cultural exploration of the contextual landscape produced by the houses located in popular neighborhoods of the city of Mexicali, Mexico. The research shows that there is an unconscious hybridization process, the birth of a mixture of impositions guided by the popular and the personal aspirations of the inhabitant. The study presents the possibilities of a home and the relationship with its inhabitant and, in turn, its effects on the context and its contribution to culture through hybridization.

Keywords: hybridization, architectural landscape, architecture, mass housing

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Authors: S. Sakthivel

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Currently, the global economy is based on the hydrocarbon economy, which is referencing the global hydrocarbon industry. Problems of using these fossil fuels (like oil, NG, coal) are emitting greenhouse gases (GHGs) and price fluctuation, supply/distribution, etc. These challenges can be overcome by using clean energy as hydrogen. The hydrogen economy is the use of hydrogen as a low carbon fuel, particularly for hydrogen vehicles, alternative industrial feedstock, power generation, and energy storage, etc. Engineering consulting firms have a significant role in this ambition and green hydrogen value chain (i.e., integration of renewables, production, storage, and distribution to end-users). Typically, the cost of green hydrogen is a function of the price of electricity needed, the cost of the electrolyser, and the operating cost to run the system. This article focuses on economic viability and explores the alluring business scenarios globally. Break-even analysis was carried out for green hydrogen production and in order to evaluate and compare the impact of the electricity price on the production costs of green hydrogen and relate it to fossil fuel-based brown/grey/blue hydrogen costs. It indicates that the cost of green hydrogen production will fall drastically due to the declining costs of renewable electricity prices and along with the improvement and scaling up of electrolyser manufacturing. For instance, in a scenario where electricity prices are below US$ 40/MWh, green hydrogen cost is expected to reach cost competitiveness.

Keywords: green hydrogen, cost analysis, break-even analysis, renewables, electrolyzer

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Authors: Gamalath M. B. P. Abeysekara

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Primary objective of any organization is to enhance the bottom line profit. Strategic procurement is one of the prominent aspects in view of receiving this ultimate objective. Strategic procurement is an activity used in each and every organization in their operations. Pharmaceutical procurement is an especially significant task for any organizations, particularly state sector concerned. The whole pharmaceutical procurement requirement of the country is procured through the State Pharmaceutical Corporation (SPC) of Sri Lanka. They follow Pharmaceutical Procurement Guideline of 2006 as the procurement principle. The main objective of this project is to identify the importance of State Pharmaceutical Corporation supplier selection criteria and critical analysis of pharmaceutical procurement procedure. State Pharmaceutical Corporations applied net price, product quality, past performance, and delivery of suppliers’ as main criteria for the selection suppliers. Data collection for this study was taken place through a questionnaire, given to fifty doctors within the Colombo district attached to five main state hospitals. Data analysis is carried out with mean and standard deviation functions. The ultimate outcomes indicated product quality, net price, and delivery of suppliers’ are the most important criteria behind the selection of suppliers. Critical analysis proved State Pharmaceutical Corporation should focus on net price reduction, improving laboratory testing facilities and effective communication between up and down stream of supply chain.

Keywords: government procurement procedure, pharmaceutical procurement supplier selection criteria, importance of SPC supplier selection criteria

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Authors: Flavia Magliacani

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The urbanization of the last decades and its resulting urban growth entail problems both for environmental and economic sustainability. From this perspective, sustainable settlement development requires a horizontal decrease in the existing urban structure in order to enhance its greater concentration. Hence, new stratifications of the city fabric and architectural strategies ensuring high-density settlement models are possible solutions. However, although increasing housing density is necessary, it is not sufficient. Guaranteeing the quality of living is, indeed, equally essential. In order to meet this objective, many other factors come to light, namely the relationship between private and public spaces, the proximity to services, the accessibility of public transport, the local lifestyle habits, and the social needs. Therefore, how to safeguard both quality and density in human habitats? The present paper attempts to answer the previous main research question by addressing several sub-questions: Which architectural types meet the dual need for urban density and housing quality? Which project criteria should be taken into consideration by good design practices? What principles are desirable for future planning? The research will analyse different architectural responses adopted in four European cities: Paris, Lion, Rotterdam, and Amsterdam. In particular, it will develop a qualitative and comparative study of two specific architectural solutions which integrate housing density and quality living. On the one hand, the so-called 'self-contained city' model, on the other hand, the French 'Habitat Dense Individualisé' one. The structure of the paper will be as follows: the first part will develop a qualitative evaluation of some case studies, emblematic examples of the two above said architectural models. The second part will focus on the comparison among the chosen case studies. Finally, some conclusions will be drawn. The methodological approach, therefore, combines qualitative and comparative research. Parameters will be defined in order to highlight potential and criticality of each model in light of an interdisciplinary view. In conclusion, the present paper aims at shading light on design approaches which ensure a right balance between density and quality of the urban living in contemporary European cities.

Keywords: density, future design, housing quality, human habitat

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Authors: Oliver Takawira, Thembi Hope

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This study will analyse the relationship between Bitcoin price movements and the Johannesburg stock exchange (JSE). The aim is to determine whether Bitcoin price movements affect the stock market performance. As crypto currencies continue to gain prominence as a safe asset during periods of economic distress, this raises the question of whether Bitcoin’s prosperity could affect investment in the stock market. To identify the existence of a short run and long run linear relationship, the study will apply the Autoregressive Distributed Lag Model (ARDL) bounds test and a Vector Error Correction Model (VECM) after testing the data for unit roots and cointegration using the Augmented Dicker Fuller (ADF) and Phillips-Perron (PP). The Non-Linear Auto Regressive Distributed Lag (NARDL) will then be used to check if there is a non-linear relationship between bitcoin prices and stock market prices.

Keywords: bitcoin, stock market, interest rates, ARDL

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Authors: Marcelo T. Okano, Oduvaldo Vendrametto, Osmildo S. Santos, Marcelo E. Fernandes, Heide Landi

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The literature on the interorganizational relationship between companies and organizations has increased in recent years, but there are still doubts about the various settings. The interorganizational networks are important in economic life, the fact facilitate the complex interdependence between transactional and cooperative organizations. A need identified in the literature is the lack of indicators to measure and identify the types of existing networks. The objective of this research is to examine the interorganizational relationships of two milk chains through indicators proposed by the theories of the four authors, characterizing them as network or not and what the benefits obtained by the chain organization. To achieve the objective of this work was carried out a survey of milk producers in two regions of the state of São Paulo. To collect the information needed for the analysis, exploratory research, qualitative nature was used. The research instrument of this work consists of a roadmap of semistructured interviews with open questions. Some of the answers were directed by the interviewer in the form of performance notes aimed at detecting the degree of importance, according to the perception of intensity to that regard. The results showed that interorganizational relationships are small and largely limited to the sale of milk or dairy cooperatives. These relationships relate only to trade relations between the owner and purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships and increase benefits for all participants in the network. The various visits and interviews in several dairy farms in the regions of São Pau-lo (indicated that the inter-relationships are small and largely limited to the sale of milk to cooperatives or dairy. These relationships refer only to trade relations between the owner and the purchaser of milk. But when the producers are organized in associations or networks, interorganizational relationships increase and bring benefits to all participants in the network.

Keywords: interorganizational networks, dairy chain, interorganizational system, São Pau-lo

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Authors: Antoni Wibowo, Harry Pujianto, Dewi Retno Sari Saputro

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The stock market can provide huge profits in a relatively short time in financial sector; however, it also has a high risk for investors and traders if they are not careful to look the factors that affect the stock market. Therefore, they should give attention to the dynamic fluctuations and movements of the stock market to optimize profits from their investment. In this paper, we present a nonlinear autoregressive exogenous model (NARX) to predict the movements of stock market; especially, the movements of the closing price index. As case study, we consider to predict the movement of the closing price in Indonesia composite index (IHSG) and choose the best structures of NARX for IHSG’s prediction.

Keywords: NARX (Nonlinear Autoregressive Exogenous Model), prediction, stock market, time series

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Authors: Rui Pedro de Sousa Guimarães Ferreira, Carlos Alberto Maia Domínguez

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Despite the ambitions to achieve climate neutrality by 2050, to fulfill the Paris Agreement's goals, the building and construction sector remains one of the most resource-intensive and greenhouse gas-emitting industries in the world, accounting for 40% of worldwide CO ₂ emissions. Over the past few decades, globalization and population growth have led to an exponential rise in demand in the housing market and, by extension, in the building industry. Considering this housing crisis, it is obvious that we will not stop building in the near future. However, the transition, which has already started, is challenging and complex because it calls for the worldwide participation of numerous organizations in altering how building systems, which have been a part of our everyday existence for over a century, are used. Wood is one of the alternatives that is most frequently used nowadays (under responsible forestry conditions) because of its physical qualities and, most importantly, because it produces fewer carbon emissions during manufacturing than steel or concrete. Furthermore, as wood retains its capacity to store CO ₂ after application and throughout the life of the building, working as a natural carbon filter, it helps to reduce greenhouse gas emissions. After a century-long focus on other materials, in the last few decades, technological advancements have made it possible to innovate systems centered around the use of wood. However, there are still some questions that require further exploration. It is necessary to standardize production and manufacturing processes based on prefabrication and modularization principles to achieve greater precision and optimization of the solutions, decreasing building time, prices, and waste from raw materials. In addition, this approach will make it possible to develop new architectural solutions to solve the rigidity and irreversibility of buildings, two of the most important issues facing housing today. Most current models are still created as inflexible, fixed, monofunctional structures that discourage any kind of regeneration, based on matrices that sustain the conventional family's traditional model and are founded on rigid, impenetrable compartmentalization. Adaptability and flexibility in housing are, and always have been, necessities and key components of architecture. People today need to constantly adapt to their surroundings and themselves because of the fast-paced, disposable, and quickly obsolescent nature of modern items. Migrations on a global scale, different kinds of co-housing, or even personal changes are some of the new questions that buildings have to answer. Designing with the reversibility of construction systems and materials in mind not only allows for the concept of "looping" in construction, with environmental advantages that enable the development of a circular economy in the sector but also unleashes multiple social benefits. In this sense, it is imperative to develop prefabricated and modular construction systems able to address the formalization of a reversible proposition that adjusts to the scale of time and its multiple reformulations, many of which are unpredictable. We must allow buildings to change, grow, or shrink over their lifetime, respecting their nature and, finally, the nature of the people living in them. It´s the ability to anticipate the unexpected, adapt to social factors, and take account of demographic shifts in society to stabilize communities, the foundation of real innovative sustainability.

Keywords: modular, timber, flexibility, housing

Procedia PDF Downloads 34

Authors: Siti Rodliyah, Andrik Purwasito, Bani Sudardi, Abdullah Wakit

Abstract:

This study employs sociological-ethnographic basic method and the cultural studies paradigm as the approach in understanding the habitus within the customary marriage of the East Nusa Tenggara society who require belis as a bride-price. The conceptual basis underlying the application of habitus theory and symbolic power in East Nusa Tenggara (NTT) society refers to the Bourdieu’s framework. This study is a result of participatory observation on habitus of a marital system using belis observed by the NTT society as a cognitive structure which connects individuals to the social activities of the customary marriage and makes it unquestionable habits. Knowledge of the social world under the pretext of prosperity for the recipients (family) of a bride-price can be a political instrument for the sustainability of power relations. The ritual-mythical system in the society has never been fully present as a neutral habit. The habitus reflected in the marital relationship among the NTT society enables the men to obtain and exercise their power relations. The sustainability of power relations can be seen from the representation of the social status of a girl and the properties attached to her. This is what gave birth to a symbolic rule, in which the social rules about bride-price or belis eventually will serve the interests of those who occupy a dominant position in the social structure, namely the rich men.

Keywords: belis, habitus, East Nusa Tenggara, marital system, power, symbolic

Procedia PDF Downloads 221

Authors: Maryam Ghoreishi, Christian Larsen

Abstract:

In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

Procedia PDF Downloads 300

Authors: Rosie S. Abalos, John Patrick M. Dizon

Abstract:

The operation of fish cages in mariculture parks for milkfish production remains a lucrative business for aquaculture operators. Three areas in the Philippines where mariculture parks are still in active operation were identified as study sites for this research. Financial analysis was used to estimate profitability of mariculture operations in the selected study sites. Based on the result of this research, milkfish production in mariculture parks remains profitable both in terms of net profit generation and the return on investment. To improve the profitability of aquaculture operations in mariculture parks, the relatively high price of operational inputs should be managed. As a recommendation, further studies should be conducted on the profitability of aquaculture operations in mariculture parks in the country to include other factors which may cause losses on the part of the operator and factors that may affect price of produce upon harvest.

Keywords: mariculture parks, milkfish production, aquaculture, profitability

Procedia PDF Downloads 124

Authors: Ketsada Sutthiumporn, Sittichot Thongkaw, Malee Santikunaporn

Abstract:

In Thailand, biodiesel has been utilized as an attractive substitute of petroleum diesel and the government imposes a mandatory biodiesel blending requirement in transport sector to improve energy security, support agricultural sector and reduce emissions. Though biodiesel blend has many advantages over diesel fuel such as improved lubricity, low sulfur content and higher flash point, there are still some technical problems such as oxidative stability, poor cold- flow properties and impurity. Such problems were related to the fatty acid composition in feedstock. Moreover, Thailand has announced the use of low sulfur diesel as a base diesel and will be continually upgrading to EURO 5 in 2023. With ultra low sulfur content, it may affect the diesel fuel properties especially lubricity as well. Therefore, in this study, the physical and chemical properties of palm oil-based biodiesel in low sulfur diesel blends from different producers will be investigated by standard methods per ASTM and EN. Also, its economic benefits based on diesel price structure in Thailand will be highlighted. The appropriate biodiesel blend ratio can affect the physico-chemical properties and reasonable price in the country. Properties of biodiesel, including specific gravity, kinematic viscosity, FAME composition, flash point, sulfur, water, oxidation stability and lubricity were measured by standard methods of ASTM and EN. The results show that the FAME composition of biodiesel has the fatty acid of C12:0 to C20:1, mostly in C16:0, C18:0, C18:1, and C18:2, which were main characteristic compositions of palm biodiesel. The physical and chemical properties of biodiesel blended diesel was found to be increases with an increasing amount of biodiesel such as specific gravity, flash point and kinematic viscosity while sulfur value was decreased. Moreover, in this study, the various properties of each biodiesel blends were plotted to determine the appropriate proportional range of biodiesel-blended diesel with an optimum fuel price.It can be seen that the amount of B100 can be filled from 1% up to 7% in which the quality was in accordance with Notification of the department of Energy business.The understanding of relation between physico-chemical properties of palm oil-based biodiesel and pricing is beneficial to guide the better development of desired feedstock in Thailand and to implement biodiesel blends with comparative price and diesel engine performance.

Keywords: fatty acid methyl ester, biodiesel, fuel price structure, palm oil in Thailand

Procedia PDF Downloads 87

Authors: O. Benabdeljelil, A. Karioun, S. Amami, R. Rouger, M. Hamidine

Abstract:

A model for preventing the risks related to climate conditions in the agricultural sector is presented. It will determine the yearly optimum premium to be paid by a producer in order to reach his required turnover. The model is based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, the main ones of which are daily average sunlight, rainfall and temperature. By simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is determined from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. The model also requires accurate pricing of commodity at N+1. Therefore, a pricing model is developed using 3 state variables, namely the spot price, the difference between the mean-term and the long-term forward price, and the long-term structure of the model. The use of historical data enables to calibrate the parameters of state variables, and allows the pricing of commodity. Application to beet sugar underlines pricer precision. Indeed, the percentage of accuracy between computed result and real world is 99,5%. Optimal premium is then deduced and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect its harvest. The application to beet production in French Oise department illustrates the reliability of present model with as low as 6% difference between predicted and real data. The model can be adapted to almost any agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, production model, optimal price, meteorological factors, 3-factor model, parameter calibration, forward price

Procedia PDF Downloads 350

Authors: Mawardati Mawardati

Abstract:

This research was carried out on the traditional milkfish and shrimp culture cultivation from March to May 2018 in East Aceh District. This study aims to to analyze the differences between traditional milkfish cultivation and shrimp farming in East Aceh District, Aceh Province. The analytical method used is acquisition analysis and Independent Sample T test analysis. The results showed a significant difference between milkfish farming and shrimp farming in East Aceh District, Aceh Province. Based on the results of the analysis, the average profit from shrimp farming is higher than that of milkfish farming. This demand exceeds market demand for exports. Thus the price of shrimp is still far higher than the price of milk fish.

Keywords: comparative, profit, shrimp, milkfish

Procedia PDF Downloads 129

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

Abstract:

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

Procedia PDF Downloads 334

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

Procedia PDF Downloads 364