HEDONIC MODELING OF HOUSING PURCHASE/SALE DENSITY WITH URBAN CHANGE FACTORS

Due to the industrialization in the cities, land needs have appeared in the increasing urban population. These needs have created houses with the accumulate of collective living spaces in the city. It is necessary to determine the supply-demand relationship and value of these real estates with economic importance for smart urban management systems and decision support systems in the market. The value of real estate varies according to the country in which it is located, but in general, it is affected by many factors such as spatial attributes, demographic factors, building factors, economic conditions. Depending on these factors, values and purchase-sale densities of housing also change.In this study, for prediction of housing purchase-sale density, hedonic modeling was realized with 15 features from urban change factors. Urban change factors that affect the purchase/sale of housing such as land use, demographic factors, population density and structural factors have been examined through Geographic Information System (GIS). The hedonic regression method was used for predicting the density of housing purchase/sale. As a result of the modeling, it was found as R2 = 0,85.

Enterprise Restructuring Based on Modeling the Economic Responsibility of Its Divisions

Structure and function as two system-building factors that affect each other. Their mutual conformity is a guarantee of the system efficient functioning. At certain time this conformity can be broken and it will impact adversely the organization work. As a result it will be necessary either to revise the function (mission) of the enterprise or to restructure it. According to the theory of business systems, the contribution of each division to the system function realization can be estimated through modeling economic responsibility, which should, in theory, correspond to employees' remuneration. The given logic underlies COMPAS methodology, whose version was elaborated by the authors and used in the article. This methodology was tested at the Research Center of Pharmacotherapy. The findings of the research allowed the authors to put forward the current and strategic solution to the problem of unbalanced economic responsibility and personnel remuneration. In the short run in order to reduce the general manager's load it is possible to pass some of his/her tasks to subordinates and in the long run it is recommended to change the structure of enterprise management and revise the distribution of economic responsibility and remuneration in divisions.

Towards a Methodological Approach to Builder Specific, Preconstruction Airtightness Estimates for Light-Framed, Detached, Low-Rise Residential Buildings in Canada

Towards A Methodological Approach to Builder Specific, Preconstruction Airtightness Estimates for LightFramed, Detached, Low-Rise Residential Buildings in Canada Bomani Khemet, Doctor of Philosophy in Civil Engineering, Ryerson University, 2019 This research is an investigation into residential building airtightness. Its purpose is to establish a methodology to predict preconstruction airtightness in Canadian homes. The dissertation presented an analysis of a large, national blower door testing population, numbering over 900,000 low-rise detached homes. The relationship between airtightness and various building factors, such as; insulation levels, building size, and year of construction, is explored. Regressionbased models were found to be highly significant (p<<0.01) and explained up to 48% (R = 0.69, p<<0.01) of whole building airtightness. The national models’ scope was confined to predicting airtightness in existing homes with heterogeneous wall construction. In order to estimate preconstruction airtightness in conventionally constructed homes, a local blower door testing population of nearly 3000 homes was examined. Three builder-specific, geometricbased, temporally independent, multiple linear regression models were developed. Some of these builder-specific models were found to be strong, and explained over 58% (R = 0.79, p<<0.001) of whole building airtightness. A five variable, geometrically based model which controlled for handicraft was found to be very strong, explaining up to 73% (R = 0.87, p<<0.001) of the whole building airtightness. The regression-based analyses on the local population suggests that air leakage is prominent through two building details: the floor-to-wall details, and at the window-to-wall assemblies. An empirically based design of experiments was devised to quantify the impact of air leakage through a floor-to-wall detail. A very strong laboratory-based model explained up to 88% of the air leakage through the floor-to-wall joint (R = 0.95, p<<0.001). A builder-specific, temporally-independent model was combined with the empirically-based, floor-to-wall model to illustrate the applicability of the approach residential building designers. The synthesis of the two models resulted in a novel, whole building, preconstruction airtightness forecasting model. The dissertation demonstrated that airtightness in homes could be estimated with temporally independent, builder-specific, and geometrically-based preconstruction models. The estimation approach spurred models that were stronger in explanatory power, and industrial applicability as compared to previous airtightness models.

Towards a Methodological Approach to Builder Specific, Preconstruction Airtightness Estimates for Light-Framed, Detached, Low-Rise Residential Buildings in Canada

Towards A Methodological Approach to Builder Specific, Preconstruction Airtightness Estimates for LightFramed, Detached, Low-Rise Residential Buildings in Canada Bomani Khemet, Doctor of Philosophy in Civil Engineering, Ryerson University, 2019 This research is an investigation into residential building airtightness. Its purpose is to establish a methodology to predict preconstruction airtightness in Canadian homes. The dissertation presented an analysis of a large, national blower door testing population, numbering over 900,000 low-rise detached homes. The relationship between airtightness and various building factors, such as; insulation levels, building size, and year of construction, is explored. Regressionbased models were found to be highly significant (p<<0.01) and explained up to 48% (R = 0.69, p<<0.01) of whole building airtightness. The national models’ scope was confined to predicting airtightness in existing homes with heterogeneous wall construction. In order to estimate preconstruction airtightness in conventionally constructed homes, a local blower door testing population of nearly 3000 homes was examined. Three builder-specific, geometricbased, temporally independent, multiple linear regression models were developed. Some of these builder-specific models were found to be strong, and explained over 58% (R = 0.79, p<<0.001) of whole building airtightness. A five variable, geometrically based model which controlled for handicraft was found to be very strong, explaining up to 73% (R = 0.87, p<<0.001) of the whole building airtightness. The regression-based analyses on the local population suggests that air leakage is prominent through two building details: the floor-to-wall details, and at the window-to-wall assemblies. An empirically based design of experiments was devised to quantify the impact of air leakage through a floor-to-wall detail. A very strong laboratory-based model explained up to 88% of the air leakage through the floor-to-wall joint (R = 0.95, p<<0.001). A builder-specific, temporally-independent model was combined with the empirically-based, floor-to-wall model to illustrate the applicability of the approach residential building designers. The synthesis of the two models resulted in a novel, whole building, preconstruction airtightness forecasting model. The dissertation demonstrated that airtightness in homes could be estimated with temporally independent, builder-specific, and geometrically-based preconstruction models. The estimation approach spurred models that were stronger in explanatory power, and industrial applicability as compared to previous airtightness models.

Change Factors and the Adaptability of Buildings

The adaptability of buildings addresses the responses of buildings to the changing needs of owners/users and the demands of external factors, over their lifecycle. An understanding of these changes is therefore key to the creation of adaptable buildings. This paper reports research which was aimed at modelling building changes to better understand the challenges for their adaptability. An in-depth study of the changes in selected case studies was conducted to understand the nature, characteristics, and implications of these changes for buildings and their ability to adapt. The findings from these case studies were analyzed against theoretical models reported in the literature on change and adaptability. As a result, a model was developed that identified and categorized a wide spectrum of changes to the building fabric within the broad remit of adaptability that are triggered by many factors, which are sometimes external to the building or organization. In the cases investigated, it was found that the factors that lead to actual changes to buildings were not necessarily due to the ease of making those changes, but rather the organizational will and means to make the changes. Similarly, changes were made not because the building systems were obsolete, but because of non-building factors. The timings of changes therefore did not correspond to the assumed lifespan models of different building layers, suggesting that a new way of predicting and/or categorizing building changes is needed. Furthermore, the interrelationships and nature of the triggers for change suggest that the adaptability of buildings is not just about building systems, but also about non-building factors. Thus, the further exploration of non-building triggers and enablers for change using the developed model presented here, will further enhance the creation of more adaptable buildings.

A Joint Dynamic Pricing, Advertising, and Production Model with Inventory-Level-Dependent Goodwill

Inventory level has a significant impact on the goodwill of products to customers, which seldom becomes the focus of previous studies. In this paper, joint dynamic pricing, advertising, and production decision-making problem is investigated, where the demand rate depends on sales price and goodwill. The inventory and backlog as well as advertisement are considered as goodwill-building factors. The optimal dynamic pricing, advertising, and production policies are derived by using Pontryagin’s maximum principle. Numerical examples are provided to demonstrate the obtained results, and sensitivity analysis of main system parameters is carried out to obtain some managerial insights. We find that when the initial goodwill is relatively high, the firm’s profit first decreases and then increases with respect to the impact intensity of inventory on goodwill; otherwise, the firm always benefits from a higher impact intensity of inventory on goodwill. Furthermore, the optimal production and advertising policies are complementary caused by the feature of inventory-dependent goodwill.