William Thackway
Biographic Data
| ID | 5234212 |
|---|---|
| NAME | William Thackway |
| GIVEN NAMES | William |
| FAMILY NAME | Thackway |
| SIGNATURE | THACKWAY W |
| AFFILIATIONS | UNSW Sydney |
| ORCID | 0000-0003-1847-5963 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 7 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Transforming urban planning through machine learning
Planning for sustainable urban growth is a pressing challenge facing many cities. Investigating proposed changes to the built environment can provide planners and policymakers information to understand future urban development trends and related infrastructure requirements. It is in this context we have developed a novel urban analytics approach that utilises planning applications (PAs) data and Natural Language Processing (NLP) techniques to for…
Bondi to Byron
In this paper, we look to compare the differential responses of metropolitan and regional rental markets in the first 12 months post-pandemic in New South Wales, Australia's most populous state.We employ descriptive statistics to analyse broad trends in both rental prices and transfers in and out of long-term rental supply through the short-term letting and property buyer markets.Moreover, we examine how these dynamics have played out at the loca…
Implementing a deep-learning model using Google street view to combine social and physical indicators of gentrification
Building a predictive machine learning model of gentrification in Sydney
Spatial Variability of the ‘Airbnb Effect’
Over the last decade, the emergence and significant growth of home-sharing platforms, such as Airbnb, has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney—one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increa…
Building a predictive machine learning model of gentrification in Sydney
Bondi to Byron
In this paper, we look to compare the differential responses of metropolitan and regional rental markets in the first 12 months post-pandemic in New South Wales, Australia's most populous state.We employ descriptive statistics to analyse broad trends in both rental prices and transfers in and out of long-term rental supply through the short-term letting and property buyer markets.Moreover, we examine how these dynamics have played out at the loca…
Spatial Variability of the ‘Airbnb Effect’
Over the last decade, the emergence and significant growth of home-sharing platforms, such as Airbnb, has coincided with rising housing unaffordability in many global cities. It is in this context that we look to empirically assess the impact of Airbnb on housing prices in Sydney—one of the least affordable cities in the world. Employing a hedonic property valuation model, our results indicate that Airbnb’s overall effect is positive. A 1% increa…
Implementing a deep-learning model using Google street view to combine social and physical indicators of gentrification
Building a predictive machine learning model of gentrification in Sydney
Bondi to Byron
In this paper, we look to compare the differential responses of metropolitan and regional rental markets in the first 12 months post-pandemic in New South Wales, Australia's most populous state.We employ descriptive statistics to analyse broad trends in both rental prices and transfers in and out of long-term rental supply through the short-term letting and property buyer markets.Moreover, we examine how these dynamics have played out at the loca…
Transforming urban planning through machine learning
Planning for sustainable urban growth is a pressing challenge facing many cities. Investigating proposed changes to the built environment can provide planners and policymakers information to understand future urban development trends and related infrastructure requirements. It is in this context we have developed a novel urban analytics approach that utilises planning applications (PAs) data and Natural Language Processing (NLP) techniques to for…
Geography (5 works) · Computer Science (3 works) · Economic geography (3 works) · Economics (3 works) · Housing Market and Economics (3 works) · Artificial Intelligence (2 works) · Gentrification (2 works) · Land Use and Ecosystem Services (2 works) · Political science (2 works) · Sharing Economy and Platforms (2 works)