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Sara Wilkinson & Richard Reed Faculty of Business & Law Deakin University Melbourne Australia

Alterations and extensions to commercial buildings in the Melbourne CBD: The relationship between adaptation and building attributes. Sara Wilkinson & Richard Reed Faculty of Business & Law Deakin University Melbourne Australia. overview. Introduction Rationale for the research

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Sara Wilkinson & Richard Reed Faculty of Business & Law Deakin University Melbourne Australia

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  1. Alterations and extensions to commercial buildings in the Melbourne CBD: The relationship between adaptation and building attributes Sara Wilkinson & Richard Reed Faculty of Business & Law Deakin University Melbourne Australia

  2. overview • Introduction • Rationale for the research • Factors influencing building adaptation • Research Method • Principal Components Analysis • Results and discussion • Conclusions

  3. Introduction • Significance of buildings to greenhouse gas emissions • 1200 buildings program / carbon neutral 2020 • 1-2% added to total stock per annum • We need to adapt existing buildings • what is the relationship between building adaptation event, classified as ‘alterations and extensions’ in the CBD and building attributes?

  4. Factors influencing building adaptation • Definitions • Previous research grouped factors into; • Economic • Social • Environmental • Technological • Legal • Physical

  5. Research Methodology • Case study approach favoured • Stage 1 - factors identified from previous studies • Stage 2 – analysed relationship between adaptation criteria and building adaptation events • Building Attribute Database • Building Adaptation Event Database – levels of adaptations identified • 13,222 events 1998 to 2008 • Geographical area defined

  6. Principal Component Analysis (PCA). • What PCA does - uncover, disentangles and summarises patterns of correlation within a data set • How - condenses information contained in a number of original variables into a smaller set of new composite factors with a minimum loss of information • Series of steps • Step 1 – enter all variables into PCA • Step 2 – number of factors to retain • Based on Kaiser criterion, only Eigenvalues exceeding 1 are retained, • Interpret factor loadings • 5290 events categorised as ‘alterations and extensions’

  7. Factor 1 – physical / size • No. of storeys, GFA, PCA Grade, site boundaries. typical floor area and site access are strongly to very strongly loaded on factor one. • Six attributes explain 44.86% of the original variance. • Three relate to the physical dimensions/size of the property in terms of floor area and height (i.e. physical attributes). • Two relate to site boundaries; (degree of attachment to other buildings) and site access (number of access/entry/exit points) • These attributes are ‘physical - size’ related. • The final variable ‘PCA Grade’ is strongly and negatively loaded and relates to building quality. • With a loading of .427 Parking is too weak to be included in the final interpretation

  8. Factor 2 – land • three variables loaded very strongly to strongly on factor 2 are street frontage, vertical services location and location • explain 19.78% of the variance. • may be described as influenced by land/design factors. • street frontage or width of the land parcel and the location of the property relate to land attributes. • vertical services location - a design attribute that influencing flexibility of the space plan to adapt to different configurations of the floor plate.

  9. Factor 3 – social • historic listing and age are very strongly and moderately loaded on factor 3 • explain 9.33% of the variance • age is negatively loaded - as buildings age they are more likely to be adapted. • can be described as social attributes. • aesthetics is weakly loaded, relates to building appearance (buildings having a poor appearance; outmoded or outdated are less likely to be adapted). • aesthetics is the related to age and historic listing.

  10. Conclusions • Two primary findings from the PCA. • Three defined and readily interpreted factors (table 4). • The PCA has correlated variables that previous studies identified as being separate and distinct (Blakstad 2001; Kucik 2004; Arge 2005) which indicates that the relationship between building adaptation and building attributes is more complex than previously considered.

  11. Final comments • No research has investigated such a large number of events • The research questions have been answered • The importance of a small number of building attributes is found to influence adaptation to a high degree (73.98% of adaptation is explained by 12 attributes). • These findings begin to place important parts of the adaptation jigsaw in place. • Through the enhanced understanding of the patterns of commercial building adaptation, it is possible to strategically plan and target policy making to optimise efforts to deliver the 38% reductions in building related greenhouse gas emissions and the objectives of the 1200 buildings program.

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