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There is a large demand for and a large profit potential in the Chinese housing market. However, foreign investors still suffer high risk because they are unfamiliar with the complexities of this enormous market. This paper presents the issues associated with housing sales in the People's Republic of China and the applications of Fuzzy Logic and De...
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Citations
... The opaque relationship between economic growth from market forces and government programs make it difficult for research to clarify the contributions of housing investment to sustainable economic development ( Hongyu et al., 2002;Malpezzi, 1990). Nonetheless many emerging market governments have been persuaded about the investment potential of stateled housing construction as a means to create wealth for the country ( Perng et al., 2005). This soft focus overlooks the challenges associated with mass housing initiatives. ...
... Government-driven mass housing programs customarily encounter an assortment of problems related to unequal distribution of stock, lack of investment, inefficient management and poor maintenance ( Wang and Shao, 2014;Sambasivan and Soon, 2007;Gyourko and Saiz, 2006;Bugra, 1998). Implementation of mass housing programs is additionally compromised with various policy decisions related to building designs, construction plans, customer demand and location ( de Duren, 2018;Greene and Rojas, 2008;Perng et al., 2005;Pettang et al., 1997;Peer and Warszawski, 1972). Together these problems have led to quality issues with mass housing stock ( Tam et al., 2000;Ogunshakin and Olayiwola, 1992). ...
Purpose
Emerging states confront staggering shortages in adequate housing stock. In response, governments have sought various supply-based solutions to mitigate growing housing deficits. While many of these mass housing efforts have not produced the desired outcome, the Republic of Korea’s Two Million Housing Drive (TMHD) was a comparatively successful intervention with its implementation from 1988 to 1992. The five-year initiative exceeded its objective with the construction of over 2.1 million units – of which two-thirds were built by the private sector. The purpose of this study is to analyse Korea’s relatively effective supply-based affordable housing approach and then extrapolate best practices and lessons learned with applications for real estate markets in the developing world. Comparative understanding of the TMHD can help promote greater access to adequate housing in the developing world, especially for the many who continue to live in impoverished conditions.
Design/methodology/approach
The research uses content-based and quantitative methods to analyze the case of the TMHD in Korea toward informing improvements in corresponding supply-based housing policies and programs in developing states.
Findings
While there were challenges with the TMHD, the program repositioned Korea’s urban housing market with greater access to affordable housing in cities for the lower-income and vulnerable. The TMHD enabled the subsequent effectiveness of demand-based housing policies.
Research limitations/implications
There are research limitations in fully understanding the complex relationships between mass housing programs, economic growth and government policies. The abductive reasoning used in this case study enables in-depth analysis of the TMHD with generalizable inferences for middle-range theories with applications for emerging markets.
Practical implications
The experience of the TMHD can promote policy harmonization by helping optimize corresponding mass housing efforts in the developing world with the potential to similarly close quantitative housing deficits and expand access to adequate housing for lower-income and vulnerable households.
Social implications
Deeper understanding of the TMHD can lead to reforms of other mass housing initiatives in emerging markets to make adequate housing more accessible and economical for the benefit of underserved segments of society.
Originality/value
The Korean experience with the TMHD can inform the optimization of other similar large-scale policies and programs seeking to sustainably overcome shortfalls in adequate housing that have become all too common in the developing world.
... After the quantitative natural language membership functions are selected, the fuzzy sets and fuzzy scale set, the fuzzy logic inference system (FLIS) of "IF-THEN rules base," and the DFuzzy -DAHP model can function. the Fuzzy Logic Inference System (FLIS) into four major modeling procedures, such as determining evaluation factors; defining the fuzzy set of input evaluation factors and output values; defining Membership Functions; creating IF-THEN rules; defuzzification; and exporting quantized values (Perng et al., 2005). As shown in Fig. 3, this study first collected relevant literature and big data on improving air pollution in communities. ...
Information technology has advanced rapidly and has long been used in various fields and industries. The accumulated data are valuable in practical applications related to topics, such as scientific research, commercial development, and policy-making references. Recent global climate anomalies are due to the ongoing reclamation and extensive use of natural resources in the ongoing process of human evolution and development. Demand for industrial development and economic competition among countries have caused high CO2 emissions, which is becoming a severe problem. Through analyzing relevant big data, people can explore the causes of high CO2 emissions and propose effective solutions. Factors contributing to high CO2 emissions not only include the strong dependence on energy and its use in economic, industrial, and commercial development, but families and individuals also contribute to air pollution. To solve this problem, this study investigated topics on public policy issues involving big data, community education effectiveness, and low-interest loans. In addition, this study adopted the Delphi method, analytical hierarchy process, and fuzzy logic theory to establish a multicriteria decision-making model based on big data to evaluate the processes of reducing air pollution in urban areas. Because community education contributes to resolving public policy problems, the proposed MCDM model enables researchers to determine improvements in urban air quality and aids in discerning the effects of community education on the promotion of environmental protection policies. In addition, this study proposed methods involving grants and low-interest financing to enhance improvements.
... The success of any housing project development requires the development of consumer satisfaction as a top priority (Perng, Hsueh et al. 2005). In order to achieve sustainability in the housing sector, housing developers on the housing industry must organize to suit the needs of families and their desires by studying the factors influencing the urban environment and leading residential satisfaction or lack thereof. ...
Egypt suffers from the rapid growth of informal areas, as an expression of the population needs. New cities have not been able to attract the inhabitants of those areas, as a result of lack of responsiveness to the needs and priorities. An earlier study by the researcher using a fuzzy model of priorities showed that the independent results of each class of cooperative trinity was spaced, which made a model giving a double-headed decision. The aim of this research is to develop the former fuzzy model to make it able to choose a single ideal alternative to represent compatibility between cooperative trinity. The model used a neighborhood satisfaction index, the fuzzy logic and Delphi method. Results showed the efficiency of the developed model and the possibility of reaching through it to an ideal alternative to the indicator of urban development.
... This study combines Delphi's group decision-making technique (Murry Jr. and Hammons, 1995;Ziglio and Adler, 1996) with a fuzzy logic technique for processing quantitative values (Zadeh, 1983;Perng et al., 2005) as well as an AHP multicriteria decision-making technique (Saaty, 1980;Saaty and Takizawa, 1986) to develop a DFAHP (Delphi-Fuzzy-AHP) risk assessment model for redeveloping derelict public buildings. The DFAHP model has the implicit co-research characteristics of Delphi experts and can increase the reliability of the model. ...
Reusing abandoned public buildings is a positive strategy in sustainable urban development. An appropriate assessment method is needed to reduce the risks of redeveloping derelict public properties. The Delphi method is an optimal group decision-making technique; whereas the analytical hierarchy process (AHP) method is useful for solving multicriteria decision-making problems. In addition, fuzzy logic manages artificial uncertainty and ambiguity, where an explicit number or ratio can express the level of preference. This study uses the Delphi method, fuzzy logic, and AHP (DFAHP) as a risk assessment model to redevelop derelict public buildings. The DFAHP provides an objective reference for investment decisions and is beneficial in reducing the risk of the public sector investing in the reuse of abandoned public buildings, in aiding in reuse cases that revitalize urban economic development, and in appreciating the value of sustainable city development.
... The Delphi method was developed by the RAND Corporation in the US back in the 1950s. It is a method that assists management as a prediction tool, especially for collecting the opinions and judgments of individual members to form high quality decisions and has been widely used in complex societies [21,22]. The Delphi method is composed of the following steps: (a) select experts; (b) obtain initial assessment factors from previous studies; (c) design and distribute questionnaires; (d) recover and modify questionnaires; (e) if assessment factors do not reach a consensus, return to Step (d); (f) obtain the criteria required for this study [2]. ...
... The fuzzy theory was developed by Professor L. A. Zadeh of the University of California Berkeley in 1965 [21,22]. It is the best quantization tool for processing fuzzy phenomena and fuzzy meaning. ...
This study proposes the promotion of environmental protection education among communities as a solution to the serious problems of high energy consumption and carbon emissions around the world. Environmental protection education has direct and lasting influences on everyone in society; therefore, it is helpful in our fight against many serious problems caused by high energy consumption. In this study, the Delphi method and the fuzzy logic theory are used to develop a quantizing assessment model based on qualitative analysis. This model can be used to assess the results and influences of community residents' participation in environmental protection education on green community development. In addition, it can be used to provide references for governing authorities in their decision making of green community development policies.
... It is therefore necessary to integrate such qualification into model computations. The application of fuzzy theory in decision making in different real world issues has been well documented in different contexts (Perng et al., 2005, Bagnoli & Smith, 1998, Pagourtzi et al., 2003. Watada (1997) introduced the vague goals of expected return and risk in order to consider fuzzy portfolio selection problem. ...
In this paper, we examine advanced optimization approach for portfolio problem introduced by Black and Litterman to consider the shortcomings of Markowitz standard Mean-Variance optimization. Black and Litterman propose a new approach to estimate asset return. They present a way to incorporate the investor's views into asset pricing process. Since the investor's view about future asset return is always subjective and imprecise, we can represent it by using fuzzy numbers and the resulting model is multi-objective linear programming. Therefore, the proposed model is analyzed through fuzzy compromise programming approach using appropriate membership function. For this purpose, we introduce the fuzzy ideal solution concept based on investor preference and indifference relationships using canonical representation of proposed fuzzy numbers by means of their correspondingα-cuts. A real world numerical example is presented in which MSCI (Morgan Stanley Capital International Index) is chosen as the target index. The results are reported for a portfolio consisting of the six national indices. The performance of the proposed models is compared using several financial criteria.
... An effective decision evaluation model helps to reduce errors in decision making and lower the risk of investment. This research combines with the group decision-making technique from Delphi [9] [10] and Fuzzy quantified value processing techniques [11] [12] to build a multi-criteria evaluation model for -Lin Hsueh et al. / Procedia Engineering 29 (2012) 1755 – 1761 S-L Hsueh, K-H Hsu, C-Y Liua / Procedia Engineering 00 (2011) 000–000 3 developmental effectiveness in cultural and creative industries. Through a case study, the model is shown to be objective, adaptable, and reliable ...
Artificial intelligence is a scientific tool that is both supportive and has many applications and has been widely applied in different domains and industries. In the globalize competitive environment, raising firm competitiveness and reducing investment risk are serious issues that must be confronted by decision makers. Artificial intelligence helps enhance industrial development by providing the benefits of lending support to management, aiding in decision making, assisting in the design process, and helping in practical applications. In recent years, Taiwan has been actively promoting the implementation of the cultural and creative industries in developments from various sectors, and has established relevant subsidy policies. The goal is to improve Taiwan's influence in the knowledge economy. Selecting a set of proper tools to evaluate effectiveness in industrial development and policy promotion will help enhance overall execution efficiency and improve final results. This research uses the fuzzy logic theory in artificial intelligence to process the imprecise and vague linguistic meanings in decision making. By further combining the group decision-making technique from Delphi, we developed a multi-criteria evaluation model for developmental effectiveness in the cultural and creative industries. This model evaluates the developmental effectiveness of the inputs from each sector into the cultural and creative industries through first performing a quantified value transformation process by the fuzzy logic inference system. Decision making units may base the evaluation upon the quantified values. Lastly, this model is presented via a case study to illustrate the use of this model and to demonstrate the capability of the model. (C) 2011 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Harbin University of Science and Technology
... Although multiple types of membership functions exist, the membership functions commonly used include triangular functions and bell-shaped functions [60,61]. Therefore, triangular functions and bell-shaped functions were also adopted in this study for fuzzy set membership functions. ...
Industry and economy are developed to satisfy the needs and material desires of people. In addition to making high greenhouse gas emissions the responsibility of industry, individuals and families should also be held responsible for the production of greenhouse gas emissions. In this study, we applied the Delphi method, the analytical hierarchy process, utility theory, and fuzzy logic theory to establish an energy conservation assessment model for households. We also emphasize that subsidy policy makers should consider the social responsibility of households and individuals, as well as sustainability of energy conservation.
... To understand the change in continuous output, we adopted the Mamdani system. In addition, multiple types of membership functions existed; the membership functions commonly used include triangular functions and bell-shaped functions [80,81]. Therefore, triangular functions and bell-shaped functions were also adopted in this study for fuzzy set membership functions. ...
The construction industry is a high-pollution and high-energy-consumption industry. Energy-saving designs for residential buildings not only reduce the energy consumed during construction, but also reduce long-term energy consumption in completed residential buildings. Because building design affects investment costs, designs are often influenced by investors' decisions. A set of appropriate decision-support tools for residential buildings are required to examine how building design influences corporations externally and internally. From the perspective of energy savings and environmental protection, we combined three methods to develop a unique model for evaluating the energy-saving design of residential buildings. Among these methods, the Delphi group decision-making method provides a co-design feature, the analytical hierarchy process (AHP) includes multi-criteria decision-making techniques, and fuzzy logic theory can simplify complex internal and external factors into easy-to-understand numbers or ratios that facilitate decisions. The results of this study show that incorporating solar building materials, double-skin facades, and green roof designs can effectively provide high energy-saving building designs.
... We adopt the mamadani system in order to understand the continuous changes of output values. We divide the FLIS establishment process into steps including: the definit ion of fuzzy set of input evaluation factors/output values; IF-THEN ru le Logic gate model, the definition o f membership function and the defuzzification o f output values [13]. ...
Man consumes energy and community, the basic unit of urban development, is also an integrated energy -consuming unit. Sustainable community construction is a development model for local redevelopment which integrates culture and local features. Hence, incorporating a low-carbon concept into a sustainable community construction model will help reduce a community's carbon footprint. Community energy-saving polices can be effectively promoted by guidance, evaluation, feature development and sustainable management as well as heritage programs. This study applies Delphi method, analytic hierarchy process (AHP), and fuzzy logic in building a quantitative evaluation model for sustainable community construction low-carbon development effectiveness, to compare community low-carbon and energy saving development levels by calculating quantitative values as the basis for merits. In addition to testing the effectiveness of self-development of features, this study can also provide the government with a reference and criteria to evaluate the performance of low-carbon community construction projects.
