Design considerations for environmental sustainability in high density development: a case study of Hong Kong

Abstract

This study has indicated that there is close relationship between development density and environmental quality; therefore, it is necessary to decide the form of development carefully beforehand. The form of development is shaped either by new development or urban renewal which is a major tactic nowadays adopted by the Hong Kong Government to improve the living condition of the citizens and the quality of the built environment. This study is limited to urban renewal and aims to find out the major urban design considerations for sustaining the environment. Through a questionnaire survey carried out in Hong Kong, the opinions of architects, planners, property development managers, and local citizens were sought and evaluated, and critical design factors for enhancing environmental sustainability of urban renewal projects are highlighted. The results derived from factor analysis indicated that certain design considerations should be incorporated for sustaining the urban environment. “Land Use Planning”, “Quality of Life”, “Conservation & Preservation”, “Integrated Design”, “Provision of Welfare Facilities”, and “Conservation of Existing Properties” were believed to be the significant underlying factors for achieving environmental sustainability of local urban renewal projects.

Appendix

Regarding the comments from the reviewer, more information about the terms “eigenvalues”, “eigenvectors” and “Cronbach’s alpha” is given in this appendix.

1.1 Eigenvalues

An eigenvalue (λ) in PAF represents the amount of common variance among the variables i.e., urban design considerations in this study that are explained by the particular common factor (Pett et al. 2003). Generally speaking, eigenvalues can be negative and positive but in factor analysis, all eigenvalues have to be greater than 0 as they represent the amount of explained variance in the variables associated with a given common factor (Pett et al. 2003). The eigenvalue associated with a given common factor is equal to the sum of the squared factor loadings for each variable on that factor that is presented in the following equation:

$$ \lambda _n {\text{ = }}\sum\nolimits_j {\left( {{\text{f}}_n } \right)} ^{\text{2}} $$

where

• λ _n  = Eigenvalue of factor n

• f _n  = Factor loading on factor n

• j = 30 urban design considerations

• n = 6 factors to be extracted from PAF

1.2 Eigenvectors

In order to obtain reliable results from the exploratory factor analysis, computation of a correlation matrix for the variables i.e., 30 urban design considerations is an important step to be carried out. An eigenvector of a correlation matrix is a column of weights and each of these weights is associated with a variable in the matrix (Pett et al. 2003). In this study, a 30 × 30 correlation matrix is formed and therefore, a total of 30 eigenvectors is generated.

1.3 Cronbach’s alpha

Cronbach’s alpha (α) is the most widely used measure of reliability (Aron and Aron 2002). Reliability is concerned with the degree to which the results can be replicated and reliability analysis is useful to measure the degree of stability or consistency of measurement scales and the variables that make them up. According to Aron and Aron (2002), α in value from 0 to 1 was used to measure the internal consistency of the data collected. The higher the value (i.e. α closer to 1) is, the more is the reliability of the data. They also specified that it should have a α of at least 0.7 and it was preferable to have a α closer to 0.9 (Aron and Aron 2002). In this study, reliability analyses were performed to evaluate the internal consistencies of the extracted factors.