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The theory of competitiveness of cities is based on Porter’s Diamond Theory. There is a relation between housing and urban competitiveness. The adequacy of land supply and allocation of land for new housing development is integral. This paper aims to estimate the required number of housing units to secure housing needs in Tehran for the next four years in 1400 H.Sh (2021 A.D.). The research methodology is carried out using qualitative and quantitative approaches based on the given data. First, the population of Tehran in 1400 H.Sh was predicted using nonlinear quadratic polynomial, Gompertz and logistic models. Then, a Logistic model is proposed to estimate the number of housing units in Tehran. The calculations of residential units related to the population obtained from the Gompertz model equivalent to 663141 is suggested as a criterion for local authority to future decision making and planning for urban development.

The present research is an applied research in terms of the purpose a descriptive research in terms of the nature and methodology and a descriptive-analytical research in terms of attitude and approach toward the research problem (Hafeznia, 2013, 58, 63 and 71). To provide the required information for the analytical stage, a documentary method, related to the use of internal and external books and papers, has been applied. First, the population of Tehran in 1400 H.Sh is estimated using three nonlinear models of quadratic polynomials, Gompertz and logistic. Then, among them, the options that were more consistent with the estimation of the new comprehensive plan of Tehran (1386 H.Sh), which is the most important plan of this city, were chosen. After that, by using the logistic model, which is an appropriate expression of saturable phenomena and a suitable method of estimating the number of residential units in a city and based on the past trend, the future of housing is predicted, and the number of required residential units is determined.

Any city for competitiveness must seek the search and development of a set of unique strategies and practices that will shape its status from other cities. No single action for all cities is feasible. In fact, the most important challenge is to propose a unique value proposition and to formulate a strategy that distinguishes that city from the rest. Among the measures taken around the world is attention to infrastructure. From the point of view of competitiveness, different types of investment in infrastructure are important for different types of cities and in different stages of development of a city. Large cities need targeted investments in housing issues to overcome the segments associated with the poorer neighborhoods. Without investment in desirable housing, there will be holes in competitive advantage. In this paper, the number of residential units in Tehran was projected for 2021. The city’s population was originally estimated for 2021. In addition to the models used to predict and estimate necessary, it is necessary to consider the area, land use map, future development lines and […] city. To this end, the city can continue to meet the needs of residents’ diversification and the city’s needs. We cannot accept any predictions about the population and, consequently, the number of residential units. Providing predictions can provide the most predictive, or more prudent, and different scenarios that can emerge, which will lead to flexibility in the presentation of plans and programs. Among the models that were used to predict the population, the result obtained from second-order polynomial and Gompartz models was found to be appropriate for the estimation of the new comprehensive design of Tehran (2007). But the prediction of the population of the logistic model was beyond the prediction of the new comprehensive plan of Tehran (2007) and thus was not considered appropriate. The number of residential units required according to the predicted population of the second order polynomial models, Gompartz and the population considered in the new comprehensive plan of Tehran (2007). After the finalization of the proposed population, using the logistic model, the number of residential units needed in Tehran was projected for 2021. Since these three estimates are somewhat close to each other, it is suggested that Gompertz model calculations, equivalent to 663,141 residential units, are proposed, and according to that, local authorities are planning to supply land to achieve economic competitiveness (urban). As it is shown in the conceptual model of the paper in Figure 1, after determining the need for housing, it is necessary to ask whether the adequacy of the supply and allocation of land, as well as the importance of maintaining it for the development of housing by local authorities, is clear. Also, is there any suitable planning for that? Despite the severe shortage of ready-made land for the city of Tehran, a large volume of land is a large area owned by natural and legal persons, and, in particular, state-owned enterprises of semipublic and public institutions, which have been abandoned in cities for years without use and in the form of barren. According to municipal management laws, municipalities can receive land, taxes and fees that are included in the annual budget of the Tehran Municipality. According to the figure obtained from this study, which states that 663,141 residential units are needed for Tehran in 2021, large landowners in Tehran need to supply their land to the market. According to the Population and Housing Census in Tehran in 2011, there are 245,769 inhabited vacancies in Tehran; hence there are two scenarios for the provision of residential units in the city of Tehran in 2021, assuming that these units in the housing market require 417,372 units Another residence will be for Tehran, otherwise 663141 residential units will be needed for Tehran in 2021. Other possibl

Tehran is the largest city and the capital of Iran, and it is also the capital of the province Tehran. In the southern foothills of the Alborz Mountains within a longitude of 51 degrees and 2 minutes East to 51 degrees and 36 minutes East, with an approximate length of 50 kilometers and latitude 35 degrees and 34 minutes North to 35 degrees and 50 minutes North with an approximate width of 30 kilometers. The area of this city is 730 km². This is one of the largest cities in West Asia, the 25th the most populous city, and the 27th greatest city to the world. The administrative structure of Iran has been concentrated in this city. The city has been divided into 22 zones, 134 areas (including Rey and Tajrish), and 370 districts (Wikipedia). The problem of housing in the city of Tehran has always been one of the important issues that less has been planned for it. The result is housing shortage, high housing prices and so on, due to the excessive expansion of the city, its population increase and so on.

Appropriate logistic planning for the pharmaceutical supply chain can significantly improve many financial and performance aspects. To this aim, a multi-objective optimization model is proposed in this paper that considers different types of pharmaceuticals, different vehicles with determining capacities and multi-period logistic planning. This model can be updated based on new information about resources and newly identified requests.

The main objective function of the proposed model in this paper is minimizing the unsatisfied prioritized requests for pharmaceuticals in the network. Besides, the total transportation activities of different types of vehicles and related costs are considered as other objectives. Therefore, these objectives are optimized hierarchically in the proposed model using the Lexicographic method. This method finds the best value for the first objective function. Then, it tries to optimize the second objective function while maintaining the optimality of the first objective function. The third objective function is optimized based on the optimality of other objective functions, as well. A non-dominated sorting genetic algorithm II-multi-objective particle swarm optimization heuristic method is designed for this aim.

The performances of the proposed model were analyzed in different cases and its results for different problems were shown within the framework of a case study. Besides, the sensitivity analysis of results shows the logical behavior of the proposed model against various factors.

The proposed methodology can be applied to find the best logistic plan in real situations.

In this paper, the authors have tried to use a multi-objective optimization model to guide and correct the pharmaceutical supply chain to deal with the related requests. This is important because it can help managers to improve their plans.

The purpose of this research is to describe how total cost concept with logistical based costing (LBC) is developed in detail and then used to build logistical models on the Microsoft Excel™ platform that are integrated from the customer's factory to the supplier's door.

The models developed in this project are deterministic, event‐based algorithms to compare logistical conduits for bulk and containerized commodities. The demand chain approach is used to derive the pathways in reverse order from the customer to the supplier. The methodology is necessary to find all possible conduits from origin to destination, including points where product may cross over between various logistics systems. The approach is applied to the bulk and container system with disconnects (elevators, ports) serving as the demarcation points. The pathways from supplier to end‐user must be identified prior to application of classification and costing techniques. A goal of this research was to compare the per unit cost of two different logistical systems – bulk versus container – in two case studies. The first case study was for a miller in Northern China and the second was for a mill in Helsinki, Finland.

The spreadsheet models produced results that were within 3 percent of real world costs. Each demand chain was shown to be unique and required customized cost functions to properly configure algorithms.

The paper suggests that, while a core algorithm may exist for all supply/demand chains, no one particular algorithm configuration suffices. Each supply/demand chain is unique, in terms of both costs and performance. The use of modular cost functions provides the customization necessary to address this issue.

This project verifies that successful implementation of a model is dependent on following a set of procedures that begins with a clear statement of what the model is to measure, along with what is to be included and what are the constraints imposed on the algorithm. Mapping the flow of the goods through logistical systems provides visibility as to where costs are incurred and how they are to be assigned to the supplier or customer. An improperly assigned variable in the early stages of a supply/demand chain reduces accuracy of subsequent calculations. LBC increases the precision of models by properly establishing the configuration of cost drivers for each stage of the supply/demand chain by avoiding the use of the cost averaging used in statistical analysis.

This paper provides a standardized approach for mapping, costing and building global supply/demand chain models. The ultimate customer, once thought of as the “end of the line”, now dictates the cost and performance requirements of logistical conduits. While this paper encapsulates methods for building total cost models from the customer's perspective, other configurations can be readily constructed to examine physical and performance characteristics.

This chapter shows how to identify the characteristics of borrowers that are part of a credit scoring model. The credit risk scoring model is an important tool for evaluating credit risk associated with customer characteristics that affect defaults. This research was conducted at a financial institution, a subsidiary of a commercial bank in Indonesia, to answer the challenge of determining the feasibility of providing financing quickly and accurately. This model uses a logistic regression method based on customer data with indicators of demographic characteristics, assets, occupations, and financing payments. This study identifies nine variables that meet the goodness of fit criteria, which consist of WOE, IV, and p-value. The nine variables can be used as predictors of default probability: type of work, work experience, net finance value, tenor, car brand, asset price, percentage of down payment (DP), interest, and income. The results of the study form a risk assessment model to identify variables that have a significant effect on the probability of default.

This paper aims to build a predictive model for the investment yield of British banking-halls.

Empirical data of similar lots sold at previous auctions are subjected to statistical analyses utilizing a cross-sectional research design. The independent variables analysed are taken from a previous study using the same cases. Models are built using logistic regression and ANCOVA.

Logistic regression generally generates better models than ANCOVA. A division of Britain on a north/south divide produces the best results. Rent is as good as lot size and price in modelling, but has greater utility, because it is known prior to auctions.

Cases analysed were restricted to lots let entirely as banking-halls. Other lots comprising premises only partially used as banking-halls might produce different results. Freehold was the only tenure tested.

The study provides a form of predictive modelling for investors and their advisors using rent which is known in advance of any sale.

The study makes an original contribution to the field, because it builds a predictive model for investment yields for this class of property. Further research may indicate if similar predictive models can be built for other classes of investment property.

Based on the concept of blown‐ups of evolution, introduced by OuYang in 1995, for nonlinear models, the logistic model and its modification of population evolutions are analyzed analytically and numerically. Presents results that imply: (1) There does not exist successive whole evolution of time in both the logistic model and its modifications. (2) The increase or decrease of the population size, caused by unsuccessive evolution, is limited. (3) The discontinuity characteristic realizes the philosophy that “things will develop in the opposite direction when they have reached extremes”. (4) The exponential increase of the population size is a special case, where it is shown that the modified logistic model agrees more with the reality than the original model. At the end, it points out that it is necessary to reconsider the method of reducing the original model into an algebraic equation by changing Δt to a non‐dimensional nonvariable by using difference scheme.

Facing the aging workforce but older workers’ vulnerability in the labor market, this chapter empirically explores factors and policy implications to enhance older workers’ entered employment rates (EER) after exiting the national workforce program. After reviewing older workers’ attributes and the unique methods to train them, the chapter examines demographic, socioeconomic, and program attributions to older workers’ EER, controlling for cyclical changes in the labor market. The chapter relies on three sets of models including logistic regression, multi-level mixed-effect regression, and multilevel mixed effect logistic regression models, as well as longitudinal Workforce Investment Act Standardized Record Data and Bureau of Labor Statistics unemployment data. Older dislocated workers and older adults are examined separately. Some Workforce Innovation and Opportunity Act training and related service combinations are identified to contribute to older adults and older dislocated workers’ EER and to inform strategic decision-making about future allocations of funds and policy efforts to serve older workers.

Purpose: This chapter aims: (a) to extend biased net models of homophily to complete networks; (b) to extend the scope of application of these models to processes of social exchange in a small-group laboratory setting; and (c) to link the theoretical model of attraction and repulsion with a standard statistical model of logistic regression as a way of estimating and evaluating the model.

Methods: We discuss the logic of biased net theory and show how it leads to formal mathematical models of tie formation and tie renewal under mechanisms of attraction and repulsion. We then estimate key theoretical parameters in the models by means of logistic regression.

Findings: The estimated effects of homophily in our models are moderate in strength, weaker than corresponding reciprocity effect, and processes of tie formation and tie renewal are driven more by considerations of direct reciprocity than group membership. Under attraction, homophily effects are stronger for tie renewal than tie formation. Under repulsion, the opposite holds.

Limitations: Participants in our study are divided into two groups based on a criterion that is likely to have been too weak to induce strong group identity. Measures that enhance the sense of group identity need to be introduced in future studies.

This paper aims to examine the effect of domain knowledge on eye-tracking measures and predict readers’ domain knowledge from these measures in a navigational table of contents (N-TOC) system.

A controlled experiment of three reading tasks was conducted in an N-TOC system for 24 postgraduates of Wuhan University. Data including fixation duration, fixation count and inter-scanning transitions were collected and calculated. Participants’ domain knowledge was measured by pre-experiment questionnaires. Logistic regression analysis was leveraged to build the prediction model and the model’s performance was evaluated based on baseline model.

The results showed that novices spent significantly more time in fixating on text area than experts, because of the difficulty of understanding the information of text area. Total fixation duration on text area (TFD_T) was a significantly negative predictor of domain knowledge. The prediction performance of logistic regression model using eye-tracking measures was better than baseline model, with the accuracy, precision and F(β = 1) scores to be 0.71, 0.86, 0.79.

Little research has been reported in literature on investigation of domain knowledge effect on eye-tracking measures during reading and prediction of domain knowledge based on eye-tracking measures. Most studies focus on multimedia learning. With respect to the prediction of domain knowledge, only some studies are found in the field of information search. This paper makes a good contribution to the literature on the effect of domain knowledge on eye-tracking measures during N-TOC reading and predicting domain knowledge.

This paper aims at developing an early warning signal model for predicting corporate default in emerging market economy like India. At the same time, it also aims to present methods for directly estimating corporate probability of default (PD) using financial as well as non‐financial variables.

Multiple Discriminate Analysis (MAD) is used for developing Z‐score models for predicting corporate bond default in India. Logistic regression model is employed to directly estimate the probability of default.

The new Z‐score model developed in this paper depicted not only a high classification power on the estimated sample, but also exhibited a high predictive power in terms of its ability to detect bad firms in the holdout sample. The model clearly outperforms the other two contesting models comprising of Altman's original and emerging market set of ratios respectively in the Indian context. In the logit analysis, the empirical results reveal that inclusion of financial and non‐financial parameters would be useful in more accurately describing default risk.

Using the new Z‐score model of this paper, banks, as well as investors in emerging market like India can get early warning signals about the firm's solvency status and might reassess the magnitude of the default premium they require on low‐grade securities. The default probability estimate (PD) from the logistic analysis would help banks for estimation of credit risk capital (CRC) and setting corporate pricing on a risk adjusted return basis.