Lockout, lockdown and land-use.

Exploring the spatio-temporal evolution patterns of licenced venues in Sydney in the context of NSW public policy: 2012-20 21.

Abstract

This study has sought to explore the spatial implications of the NSW lockout laws, COVID-19 lockdowns and land-use planning regulations on the hospitality industry in inner-Sydney, between the period of 2012 to 2021.

Methods based in Geographical Information Science (GIS) were applied to a database of over 40,000 licenced venues. The analysis was divided into two sections. The first focussed on venues as they were in 2021, utilising the methods of point pattern analysis to present and understand the data and spatial autocorrelation analysis to identify spatially significant venue clusters, as relating to Local Government Area (LGA) and land-zone. The second used methods of spatio-temporal analysis including space-time cube and emerging hot spot analysis to explore and visualise significant venue clusters over the time period.

Results indicate that most venues are located in the Sydney LGA, with the majority of these located in business zoned land. Venues were shown to have a high degree of spatial clustering. Spatio-temporal analysis showed that this pattern of clustering was generally consistent over time. However, there exists significant variation in spatio-temporal trends depending on venue type, particularly for areas outside of the CBD. Results showed that there may have been an impact associated with the lockout laws, with there being a drop in venues across the study area following their introduction. Kings Cross in particular has not shown significant recovery following this drop. In the period following the introduction of lockdowns in response to the COVID-19 pandemic, there was no discernible change in the number of venues across the study area. However, some venues were identified as temporarily ceased trading, a disproportionate number of which were clustered in the CBD and Kings Cross precincts and surrounding inner-city areas.

Cauliflower Hotel, Waterloo (Source: Author)

This is the first study to use GIS methods to investigate the spatio-temporal patterns of licenced venues in Sydney, in the context of the policies addressed above. The findings of this study may assist policymakers, government regulators and industry bodies in better understanding the spatial implications of policies targeting the hospitality sector. Furthermore, they may assist the government in providing targeted stimulus to businesses recovering from the COVID-19 pandemic. Further research utilising methods of multi-variate analysis would provide greater assurance to these results. 

Introduction

The hospitality industry in Sydney, Australia has a long and complicated history with policy and regulation. From the rum rebellion to the six o'clock swill (Hughes 1987, Allen 2016), politicians and policymakers alike have struggled to balance Australia's drinking culture with the need to protect public health and safety . The industry itself plays a crucial role in supporting business and employment, contributing upwards of 6% to the NSW economy in 2019 (Profile id, 2021). 

In the context of the previous decade, three policies targeted at regulating the hospitality industry have stood out for their media attention and perceived impact on the industry. these include:

  • The lockout laws;
  • COVID-19 lockdowns;
  • Local Government regulations and land-use planning.

Research has explored the effectiveness of these policies and sought to understand their overall impact. However, no study has been undertaken using methods of spatial analysis to explore how these policies relate to and have impacted the spatial distribution of licenced venues across Sydney. 

The aim of this study is to fill this gap, through exploring the spatial implications of these policies on the hospitality industry in inner-Sydney between the period of 2012 to 2021. The investigation has sought to answer the following questions:

1.     What is the spatial distribution of licensed venues in inner-Sydney? How does this relate to Local Government Areas (LGAs) and land zones?

2.     How have these spatial patterns changed between 2012 and 2021?

3.     Do these changes correspond with the introduction of the lockout laws and COVID-19 lockdowns?

King Street, Newtown (Source: Author).

Research Context

Lockout Laws

During the period from 2014-2021, inner-Sydney was subject to a policy referred to as the lockout laws. The legislation, implemented by the NSW Government, sought to restrict the time of night patrons could enter licenced venues and how late alcoholic drinks could be served, along with various other licence restrictions (Government 2014). These regulations were applicable to venues within the Sydney CBD and Kings Cross precincts.

'Coca-Cola Sign', Kings Cross (Source: Author).

The intention behind the policy was to reduce alcohol related crime in the area and was enacted in response to pressure to improve public safety, following a number of alcohol related attacks in the Kings Cross and inner-City areas resulting in the death of two young men (Quilter 2015). Alongside the policy included expanding a temporary freeze on the issuing of liquor licences, previously only applying to Kings Cross precinct, to also include the CBD precinct (Government 2009, Liquor & Gaming 2021).The policy attracted significant media and public attention and was the subject of widespread scrutiny focussing on the perceived negative effect the laws were having on the hospitality and entertainment industries (Taylor 2018, Homan 2019, Williams 2019).

Much research has been undertaken with respect to the lockout laws, including how they have acted to reduce alcohol related violence in the CBD and Kings Cross precincts (Nepal, Kypri et al. 2018, Kypri and Livingston 2020), have altered house prices in the vicinity of the precincts (Perks and Maruyama 2017) and have impacted the hospitality and entertainment industries (Homan 2019). Media reports have also suggested the laws have resulted in a change to the cultural make-up of the area in which they were active (Ervine 2016, Smith 2021), with some suggesting the Kings Cross precinct in particular has lost its identity (Sydney 2021). 

COVID-19 Lockdowns

More recently, in the period from late March 2020 to the date of writing, lockdowns and capacity restrictions on hospitality venues have been enacted by the NSW Government to help reduce the spread of the COVID-19 disease by way of limiting the amount of people interacting with one another at any given time (Government 2020). Whilst not directly targeted at the hospitality industry, these lockdowns and restrictions have been similarly scrutinised by the media and public as having a negative effect on the industry, with data and reports suggesting the lockdowns are resulting in loss of business (ABS 2021) and the shutdown of venues (Brown 2020).

Sydney CBD in the midst of lockdown, 2020 (Source: Magin 2020).

Research has sought to understand how the COVID-19 pandemic and associated lockdowns are further impacting the industry globally (Dube, Nhamo et al. 2020) and in Australia (O’Sullivan, Rahamathulla et al. 2020). Results suggest that further lockdowns and the ongoing impact of the disease on consumer confidence may compromise the viability of businesses.

In Sydney, it is noted that such impacts on hospitality businesses have not been felt evenly across geographies. Whilst not yet the subject of published research, anecdotal evidence in the media and data taken from Google Trends indicates that there was a dramatic drop in pedestrian mobility within the Sydney CBD area in the months during and following lockdowns (Magin 2020, Google 2021), with the number of people visiting the CBD still well below baseline amounts. This was in comparison to suburban areas which experienced a strong bounce-back of visitors following easing of lockdowns according to the data. This reduction in people visiting the CBD has contributed to a drop in revenue for businesses in the area, many of which are struggling to stay afloat (Patrick 2021, Young 2021).

Land-use Planning

In the context of the two policies discussed above, differing ideological approaches between local Councils and the NSW Government with respect to land-use planning and the night-time economy have further impacted how the hospitality industry operates (Wolifson 2018). Some media reports suggest conflicts have occurred between areas zoned for residential and historic hospitality venues within their vicinity (Langford 2019).

Reforms at both the state and local government levels have sought to better integrate planning and land-use controls with the hospitality industry, with the goal of re-invigorating the night-time economy and avoiding such conflicts (Government 2020, Department of Planning Industry and Environment 2021, Sydney 2021).

Venue Location Analysis

Whilst no research has been undertaken focussing on the spatial distribution of licenced venues in Sydney in the context of policies discussed above, there exists an extensive body of work examining such patterns in other areas.

Research has included exploring the spatiality of karaoke bars in Nanjing, China (Cui et al., 2016); 'leisure venues' in Wuhan, China (Jing et al., 2018); hotels in Extremadura, Spain (Sánchez-Martín, Rengifo-Gallego et al. 2019) and hospitality and tourism employment clusters in Melbourne, Australia (Chhetri, Chhetri et al. 2017).

Further research has sought to explore the spatio-temporal aspects of these patterns, including restaurant failure rates in Denver, United States between 2007-2013 (Parsa, Kreeger et al. 2021); hotel locations across a 30 year time period in the United States (Kim, Kim et al. 2018); and across a 40 year time period in China (Qin, Qin et al. 2021); and the distribution of live music venues and electronic gaming machines in Sydney between the late-1980s and mid-2000s (Taylor, 2018).

Summary

This study builds upon the body of research surrounding the spatial distribution patterns of venues, utilising well established methods based on previous literature discussed above. The research has been undertaken with particular focus on how the results of above analysis relate to public policy decisions, namely the lockout laws, COVID-19 lockdowns and land-use planning. 

Data

The primary source of data that underpins the study is a list of every licenced premises in NSW (17,000+), updated monthly. The data was obtained from  Liquor and Gaming NSW  (Liquor and Gaming NSW, 2021).

The data was reduced to only show venues within the study area, with one list per year being used. For the purposes of this study, analysis was undertaken only on the following five licence types:

Club Licence

  • Allows registered clubs to sell alcohol to members and their guests for consumption on and off the premises.

Hotel Licence

  • Has broad permissions including the sale and consumption of alcohol on the premises, gaming, take-away alcohol, opportunities to host functions and more.

On-premises Licence

  • Allows the sale of alcohol at establishments where another product or service is the primary purpose of the business (such as dining).

Limited Licence

  • Allows for the sale of alcohol at infrequent events, trade fairs, exhibitions, one-off events and at sporting events by not-for profit sports clubs.

Small bar Licence

  • Allows for the sale and consumption of alcohol on a premises that holds up to 120 patrons without gaming machines or takeaway.

The reason for limiting the study to these venue types is outlined below:

  • Previous literature and media speculation indicates that these venue types were likely to be most impacted by the policies this study seeks to critique.

In addition to licenced venue data, polygon boundaries of the CBD precinct and Kings Cross precinct were obtained to allow analysis on the precinct specific level. 

Additional spatial data has been taken from several sources to assist with analysis and visualisation, including  LGA Boundaries  (Department of Customer Service, 2021),  ABS SA1 Data  (Australian Bureau of Statistics, 2016) and  NSW Land-zoning Data  (Department of Planning, 2021).

Method

This project has sought to explore the research questions using methods based in Geographical Information Science (GIS). The analysis was divided into two sections, with the first focussing on venues as they are in 2021, and the second focussing on how they have changed between 2012 and 2021. The methods have been outlined in detail in the following sections.

1) Point Pattern Analysis & Spatial Autocorellation

Initial analysis focussed on summarising and counting the data, with an emphasis on location relative to the variables of land-use zone and Local Government Area (LGA) in 2021. Further analysis utilised the Optimised Hotspot method which is based on the Getis Ord Gi* method and explores spatial-autocorrelation and statistically significant clusters within the dataset (Getis 1992, Anselin, 1995). The method works by calculating the sum of weighted points (in this case, venues) within a defined area (referred to as a ‘neighbourhood’) minus the mean for the entire study area, normalised by the standard deviation and corrected for neighbourhood weights.

This is summarised by the below formula:

Source: (Getis 1992, Anselin, 1995)

Where xj is the attribute value for feature j, wi,j is the spatial weight between feature i and j, and n is equal to the total number of features and:

Source: (Getis 1992, Anselin, 1995)

Source: (Getis 1992, Anselin, 1995)

2) Spatio-temporal Analysis

The methods of Emerging Hot Spot Analysis and Space-Time Cube visualisation were used to capture spatio-temporal patterns associated with the licenced venues. The tool works by summarising a set of points (in this case, venues) into a Network Common Data Form (net-CDF) structure by aggregating them into ‘space-time bins’ arranged both horizontally and vertically (as seen in figure 3 below) (Esri, 2021). In this instance there were 10 ‘bins’ making up the vertical axis, one for each year starting at 2012 and going until 2021. Within each bin, the venues were counted and the trend for bin values across time at each location is measured using the Mann-Kendall test (Mann 1945, Kendall 1990). The Mann–Kendall test uses the following statistic:

Source: (Mann 1945, Kendall 1990)

The variance of S is given by:

Source: (Mann 1945, Kendall 1990)

Figure 3. Space-time Cube (Source: Esri, 2021)

The statistic works by comparing the bin value for the first time period with the bin value for the second and so on up until the final bin. If the first is smaller than the second, the result is +1. If the first is larger than the second, the result is -1. If the two values are equal, the result is zero. Based on these trends an expected value is calculated for all bins, with differing results indicating statistically significant trends. Ultimately, if S > 0, then later observations in the time series tend to be larger than those that appear earlier in the time series, while the reverse is true if S < 0. This ultimately categorises the cells into hotspots and coldspots (see figure 4). A ‘hexgon grid’ was used to agglomerate the points on the map, with a width of 400m per cell.

Figure 4. Emerging Hotspot Analysis (Source: Esri, 2021)

The methods described above were undertaken using the ArcGIS Pro desktop platform (Esri 2021), which includes specialised tools for spatio-temporal analysis including the Emerging Hot Spot Analysis and Space-Time Cube techniques. It is noted that most of the methods utilised in this study reflect broader, well established principles of spatial analysis and as such could be replicated across other ‘open-source’ GIS platforms.

Venues Temporarily Ceased Trading 2021

It is noted however that the presence of a liquor licence does not necessarily indicate that a venue is actively trading. Whilst not available in previous lists, in June of 2020 a new column was added to the dataset showing the ‘trading status’ of a venue. This refers to whether a venue is operating or is temporarily closed.

Noting this additional data, a separate analysis was undertaken looking at the number and spatial distribution of licenced venues listed as ‘temporarily ceased trading’ in 2021, however was not incorporated into the core analysis. This was done to better determine the spatial impact that COVID-19 lockdowns may be having on licenced venues at the time of the study, something which may have gone unnoticed given the dataset was limited to only recording whether a licence existed and not whether it was actively in use. The Getis Ord Gi* technique was applied to the data following the same steps as used in the sections above.

Method Diagram

Figure 5 below outlines the methodology used in the study.

Figure 5. Method diagram.

Venues by Numbers: 2012-2021

Figure 28. Number of venues by type 2012-2021.

  • A large jump in the number of licenced venues was recorded between 2013 and 2014, led by a strong increase in the number of on-premises licences being issued.
  • Following this, there was a large drop in the number of on-premises licenced venues between 2015 and 2016, with a less pronounced drop in club and hotel numbers in the same period. It is not abundantly clear why this drop occurred; however, it is noted that it happened 2 years after the introduction of the lockout laws.
  • Following this drop there is observed to be a steady increase in on-premises and small bar licences.
  • There has been no discernible drop in venue numbers following the introduction of COVID-19 lockdowns.
  • Growth in small bar numbers which have grown consistently since their introduction in 2014.
  • There has been a small reduction in the number of licenced clubs and hotels across the study period.

Figure 29. Number of venues by type 2012-2021 in CBD precinct.

  • A similar pattern is followed by venues in the CBD precinct, showing a significant drop in venues followed by a steady increase following 2016.

Figure 30. Number of venues by type 2012-2021 in Kings Cross precinct.

  • Venues in the Kings Cross precinct observed a similar drop, however have not recovered since, with numbers staying relatively stagnant between 2016 and 2021. 

Discussion

When considering the results of this study, it is necessary to address the three questions posed at the beginning of this report.

Question 1 sought to explore the spatial distribution of licenced venues as they related to LGA and land-zone. The study found that, in 2021, Sydney LGA contained the largest number of licenced venues, with most venues located in business-zoned land.

Question 2 sought to understand how such patterns have changed between 2012-2021. Results indicated that venues were spatially clustered, with most significant clustering occurring in the inner-city CBD area. Spatio-temporal analysis showed that this pattern of clustering was generally consistent over time. However, there exists significant variation in spatio-temporal trends depending on venue type, particularly for areas outside of the CBD.

Question 3 sought to identify whether these changes corresponded with the introduction of the lockout laws and COVID-19 lockdowns. Results showed that, in the two years following introduction of the lockout laws, an overall drop in the number of venues across the study area was observed. However, this was not specific to the areas which the laws targeted, as confirmed by the results of the spatio-temporal analysis. Following this, growth in venue numbers was seen across the study area and in the CBD precinct. However, Kings Cross precinct experienced no growth in venue numbers, indicating that the lockdowns may have had a lasting effect on the precinct. This is consistent with the literature suggesting the identity of Kings Cross has changed following the introduction of the laws (Taylor 2018, Homan 2019, Williams 2019).

Furthermore, in the period following the introduction of lockdowns in response to the COVID-19 pandemic, there was no discernible change in the number of venues across the study area. However, some venues were identified as temporarily ceased trading, a disproportionate number of which were clustered in the CBD and Kings Cross precincts and surrounding inner-city areas. Whilst not definitive, these results provide some indication that the lockdowns might be having an impact on venues in the inner-city. 

Conclusion

The results of this study build upon those discussed in the literature and assist in answering some of the previously underexplored aspects of venue distribution in inner-Sydney. Further research looking at additional variables including alcohol expenditure and pedestrian mobility would help to confirm the results of this study. Qualitative research methods such as interviews with relevant stakeholders would also provide additional assurance to research results.

The cross-disciplinary approach to this study has meant the results have a broad application across social policy settings, along with GIS-based research focussing on the hospitality industry. The findings of this study will assist policymakers, government regulators and industry bodies in better understanding the spatial implications of policies targeting the hospitality sector. Furthermore, they may assist the government in providing targeted stimulus to businesses recovering from the COVID-19 pandemic.  

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Cauliflower Hotel, Waterloo (Source: Author)

King Street, Newtown (Source: Author).

'Coca-Cola Sign', Kings Cross (Source: Author).

Sydney CBD in the midst of lockdown, 2020 (Source: Magin 2020).

Source: (Getis 1992, Anselin, 1995)

Source: (Getis 1992, Anselin, 1995)

Source: (Getis 1992, Anselin, 1995)

Source: (Mann 1945, Kendall 1990)

Source: (Mann 1945, Kendall 1990)

Figure 3. Space-time Cube (Source: Esri, 2021)

Figure 4. Emerging Hotspot Analysis (Source: Esri, 2021)

Figure 5. Method diagram.

Figure 28. Number of venues by type 2012-2021.

Figure 29. Number of venues by type 2012-2021 in CBD precinct.

Figure 30. Number of venues by type 2012-2021 in Kings Cross precinct.