Determinants of environmental preference by housing consumers in Guangzhou, China, using analytic hierarchy process

Wu, Fan; 吴凡,

doi:10.5353/th_b4729986

Cited by 9 publications

(18 citation statements)

References 87 publications

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“…Çok kriterli karar verme tekniklerinden biri olan AHS, Thomas L. Saaty tarafından 1970'li yılların başlarında geliştirilmiş olup karar alma süreçlerinde kullanılan farklı ölçütleri de dikkate alan bir modeldir [44]. AHS, grup veya bireylerin karar alma sürecindeki önceliklerine dikkate alarak gerek niceliksel gerekse niteliksel kriterleri kriterleri belirlemeye, kriterlerin ağırlıklarını hesaplamaya ve nihai karara ulaşılmasının amaçlandığı matematiksel bir tekniktir [45].…”

Section: Anali̇ti̇k Hi̇yerarşi̇ Süreci̇ Yaklaşimi (Analytical Hierarchy Process Approach)unclassified

Türkiye'de Kişisel Verilerin Korunması ve Vatandaş Algısının Ölçülmesi

Uzun

2021

Bilişim Teknolojileri Dergisi

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Kişisel veri kavramı ve kişisel verilerin korunması konusu ülkemizde son yıllarda oldukça gelişim göstermiştir. Dünya genelinde meydana gelen ilerlemeler ve tartışmalar doğrudan ülkemizdeki gündemi etkilemektedir. Analitik Hiyerarşi Süreci modeli ayrıştırma, yargıların karşılaştırılması ve önceliklerin sentezi şeklinde üç ana ilke üzerine kurulmuştur. Model kriterlerin önem derecelerinin hesaplanmasını ve alternatifler arasından seçim yapılmasını kolaylaştırmaktadır. Bu çalışmanın amacı, ülkemizde kişisel verilerin işlenmesi ve korunmasına yönelik kavramsal bilgi vermek, konu ile ilgili dünyada ve ülkemizdeki gelişimi hakkında genel bir çerçeve çizmek, son yıllarda gündem olan big data (büyük veri) kavram ve uygulamalarıyla kişisel verilerin korunması ilişkisini incelemek ve son olarak kişisel verilerin işlenmesi ve korunması konusunda vatandaş algısının ölçülerek uygulanması gereken politika hakkında öneriler sunmaktadır. Bu amaçlardan yola çıkarak kişisel verilerin işlenmesi ve korunması konusunda vatandaş algısını ölçmek için beş ana kriter, yirmi alt kriter belirlenmiş ve hiyerarşik yapı oluşturulmuştur. Çalışmanın sonunda kişisel verilerin işlenmesi ve korunması konusunda en önemli kriterin gereklilik olduğu ve güvenilirlik yoğun politikanın seçilmesinin uygun olacağı değerlendirilmektedir.Anahtar kelimeler-Kişisel veri, kişisel verilerin korunması, vatandaş algısı, analitik hiyerarşi süreci.

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Section: Anali̇ti̇k Hi̇yerarşi̇ Süreci̇ Yaklaşimi (Analytical Hierarchy Process Approach)unclassified

Türkiye'de Kişisel Verilerin Korunması ve Vatandaş Algısının Ölçülmesi

Uzun

2021

Bilişim Teknolojileri Dergisi

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“…Thus, either owning a house or renting a house has positive and negative aspects. Therefore, the decision to own or rent a house is complex and multidimensional, involving a variety of factors such as preferences for home attributes, location and environment, and occupancy (Opoku & Abdul-Muhmin, 2010;Wang and Li, 2016;Wu, 2010;Jim and Chen, 2007;Gupta and Malhotra, 2016). Not only that, households that want to find a solution to decisions related to homeownership immediately are also limited by at least three constraints, namely the availability of houses (purchase or rent, flow of housing vacancies); regulations from the homeowners regarding the access to housing vacancies (for example, rules related to criteria for buying or renting a house; type of payment); and the economic limitations of prospective buyers or tenants (Cirman, 2004).…”

Section: Introductionmentioning

confidence: 99%

“…As a commodity, a house is generally described through its characteristics (Arnott, 1987). This is common in the housing market, where each housing agency will provide information such as a list of locations, the number of rooms, distance from the city center, and distance to public facilities (Opoku & Abdul-Muhmin, 2010;Wang and Li, 2016;Wu, 2010). Due to these characteristics, efforts in modeling the housing market are usually made through one or several characteristics of the house to define the house.…”

Section: Introductionmentioning

confidence: 99%

“…The main priority for low-income people is to get a house that is close to the work location. Next, the aspects of home quality and occupancy status considerations are considered (Panudju, 1999;Wang and Li, 2016;Wu, 2010). Besides, lowincome people generally do not pay much to the quality of the physical aspects of the house occupied if their homes can ensure their survival (Santoso, Iskandar, & Parwoto 2002).…”

Section: Introductionmentioning

confidence: 99%

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Housing Tenure Choice of Low-Income Household in Jabodetabek

Hartono

Budiman²,

Hastuti³

2020

EDAJ

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This study aims to identify the preferences of low-income people in making housing tenure choices within the next 5 years. Each person has the right to have a place to live in. However, the options available for low-income people to own a home are limited. Therefore, information on the preferences of low-income people in purchasing houses needs to be identified so that the government can formulate effective and efficient intervention policies. A sample of 1030 samples was obtained using the stratification sampling method, of which 638 are households had rental status (taking households with the lowest level of welfare between 10-40%) in the Regency and City. Discrete choice models were used to determine the preferences in owning a home. The study revealed that demographic variables and household characteristics variables (household size and length of stay) had consistent negative relationships with preferences for buying a house in the future. Also, the government needs to take action so that the socialization of housing policy becomes more optimal, effective and targeted. The goal of the policy socialization should be directed to newly married couples.

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“…Here, the accessibility included two factors: 1) the distance from public transportation, private traffic networks, downtown, shopping malls, parks and educational institutes, and 2) the ambient environment including the landscape (view), noise and whether any pollution facilities are nearby. More recently, Wu (2010) classified the factors into traffic and accessibility, ambient environment, safety and community environment, and used the AHP method for preference surveys.…”

Section: Introductionmentioning

confidence: 99%

A Feasible Sales Price Decision Model of Apartment Housing Units Considering the Market Price and Buying Power

Park

Lee

Kim

2016

Journal of Asian Architecture and Building Engineering

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Sales price closely correlates with the market price of neighboring apartment-housing units, which reflects the real transaction price. In addition, sales price is dependent on goods including the apartment's location, environment, traffic, residential conditions and housing characteristics. Studies on the sales price of apartment housing units mostly estimate the price in regard to the market price, the cost to build the apartments or a combination of both. Currently, there are studies in progress analyzing the factors that impact the sales price and the importance of purchase decision factors of consumers. However, the purchase decision factors of consumers and their importance are always changing. Thus, a sales price decision model that can account for the dynamic nature of purchase decision factors and market price is needed. In this regard, the purpose of this paper is to develop a feasible sales price decision model of apartment housing units considering market price and buying power. This model can be used as a decision-making tool in the initial phases of a project to help contractors' achieve a reasonable sales price and improve their successes with apartment housing projects.

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Determinants of environmental preference by housing consumers in Guangzhou, China, using analytic hierarchy process

Cited by 9 publications

References 87 publications

Türkiye'de Kişisel Verilerin Korunması ve Vatandaş Algısının Ölçülmesi

Türkiye'de Kişisel Verilerin Korunması ve Vatandaş Algısının Ölçülmesi

Housing Tenure Choice of Low-Income Household in Jabodetabek

A Feasible Sales Price Decision Model of Apartment Housing Units Considering the Market Price and Buying Power

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