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Introduction

The following PAR Group study looks into the impact of e-commerce shopping on large shopping centres.  A more detailed explanation of this work follows of from this. The study was undertaken by Anthony De Francesco of Real Investment Analytics, Rob Ellis of the Data App and Damian Stone of Y Research the PAR Group; an independent commercial property research collective. 

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Record growth in online spending, brought on by the COVID 19 pandemic, could see 20% of current sales in Australia’s largest 31 shopping centres move online. As a result, asset values could potentially fall in the order of 30%, according to a new study by the PAR Group.

Online shopping, which had been growing slowly in recent decades, exploded in 2020 due to the impacts of the COVID 19 pandemic. The NAB Online Retail Sales Index from September 2020, showed online spending had grown 62.7% across Australia compared to 2019.  This is based on Australians spending $40.9 billion on online retail, which represents around 12.0% of total retail spending.

Retailers as diverse as Woolworths, Harvey Norman, Officeworks and Bunnings have recorded record online sales. This highlights the breadth of products which consumers are now willing to purchase online. Australia Post reported that over 8.1 million households shopped online between March and August this year — 900,000 of them for the first time.

What are the longer-term risks to brick and mortar centres based on the accelerated rate of consumer spending moving online?

The PAR Group study sought to answer this question by reviewing just under 10,000 retail tenancies which occupy Australia’s 31 largest shopping centres to develop occupancy mix benchmarks across 11 categories (Major, Fashion, Food and Beverage, Health and Beauty, Services, Home and Lifestyle, Hobbies, Gifts and Stationery, Discount and Variety, Entertainment, Sport and Leisure and Electronics).  

For each category, using consensus forecasts, current and future e-commerce penetration was developed. Based on these penetration rates and occupancy benchmarks, each centre was reviewed to determine its vulnerability to increased online shopping.

Based on this assessment, the potential impact of sales leakages, based on Moving Annual Turnover, and capital values, based on price per square metre (sqm), were estimated.

It was determined that centres with relative high exposure to fashion brands, typically 30% of each centre’s occupancy, and food and beverage, typically 20% of each centre’s occupancy, retailers were most likely to experience online sales leakages due to e-commerce platforms such as Uber Eats and Amazon but, increasingly, the e-commerce capability of most major retail chains. In contrast, centres with relatively higher exposure to services-based retailers such as medical, beauty treatments and the post office, were likely to be less effected by online sales as these services could not be replicated online.

The longer-term take-up of online shopping by consumers, with the proportion of online sales tipped to reach 20% of total retail spending by 2025, has the potential to significantly erode in-person sales and the underlying values of Australia’s major retail assets.

Based on the typical occupancy mix and average moving annual turnover for super regional and major regional centres, increased online spending could see an average 20% drop in Moving Annual Turnover resulting in and decline in asset values on a price per sqm basis to around 30%.

The following comments can be attributed to PAR Group researchers, Anthony, Rob and Damian.

The impact of COVID 19 represents a paradigm shift for the commercial property market in Australia. The way we live, work and shop will be different in the months and years ahead.

Retail assets have been at the forefront of these changes. E-Commerce, which has been gradually eroding in person sales, has boomed due to COVID shutdowns, hoarding of groceries, increasing numbers working from home, fear of large public gatherings and, importantly, price differentials compared to in store shopping.

While future growth of online shopping is likely to moderate from 2020 levels once a vaccine is available, the investment by retailers in their e-commerce capability, the rise of platforms such as Amazon/Uber Eats/Catch and quicker supply chains by delivery partners such as Australia Post, is likely to result in e-commerce approach 20% of total retail sales in Australia within 5 years.

The direct impact of online leakages could push down underlying asset values by a third in trophy assets across the country. This is before you consider the impacts of the potential handback of space from major retailers such as Myer, David Jones, Target and Big W, store consolidation by retailers such as Mosaic Brands and further retailers, such as Collette, Riot Arts and Crafts and Jeanswest, entering administration.

However, this is likely to be partly offset in years ahead by a remixing of tenancies across centres. Shopping centres are likely to evolve with a higher mix of services-based retailers, such as medical and child care centres, gyms will become a standard feature, with supporting wellness related retailers a focus and entertainment-based retailers, from bowling alleys, mini golf, laser tag to help attract people to the physical centre.

For centre owners and retailers, as Dennis Denuto observed in the Australian movie The Castle, “the vibe” of shopping in person will be key focus. This includes the atmosphere, facilitating click and collect in person, customer service, stores allowing people to test items such as sporting equipment and pop ups. If not add to cart will increasingly surpass trying to find a park.”

Want To Know More?

PAR Group’s review of Australia’s Super/Major Regional Shopping Centres has developed extensive benchmarking of the tenancy mix in these centres. Nearly 10,000 tenants across these centres were reviewed. Each centres comparative tenancy strengths across 11 retailer classifications is outlined. If you would like to know more, custom reports are available. Contact Anthony, Rob or Damian to discuss your specific requirement.

Anthony De Francesco, Managing Director of Real Investment Analytics. Mob: 0438 506 284 or email: anthony.defrancesco@rianalytics.com.au

Rob Ellis, Director of the Data App. Mob: 0417 195 352 or email: rob@thedataapp.com

Damian Stone, Principal and Chief Problem Solver of Y Research. Mob: 0433 525 414 or email: damian.stone@yresearch.com.au

Disclaimer

The information contained in this article has been prepared with care by PAR Group and may include information from apparently reliable secondary data sources on which the authors may have relied for completeness and accuracy. However, PAR Group offers no warranty that the information it contains is accurate and disclaims all liability for any losses, damages, costs or expenses suffered by any person as a result of any reliance on this information.

Accordingly, all interested parties should make their own enquiries to verify the information and it is the responsibility of interested parties to satisfy themselves in all respects. No part of this article should be construed as investment advice, either in relation to the real estate sector or a particular transaction. Opinions and estimates constitute judgements, which change when circumstances change, if not before.

© Copyright 2020 PAR Group

RESEARCH REPORT

ONLINE RETAIL ANALYSIS FOR SUPER & MAJOR REGIONAL SHOPPING CENTRES

by Property Advisory Research (PAR) Group

1. EXECUTIVE SUMMARY

  • The PAR Group has developed the online penetration ratio (OPR) to assess a shopping centre’s vulnerability to increased online shopping.
  • This study involved a detailed review of OPRs across tenants that reside in Australia’s 31 largest retail shopping centres.  
  • While the onset of the COVID-19 pandemic has seen the growth in online spending soar to new levels, this ongoing trend is likely to impact around 20% of future moving annual turnover (MAT) across Australia’s largest 31 shopping centres.
  • Based on econometric modelling, the direct impact of a 20% leakage of MAT sales to online shopping could see asset values fall in the order of 30%.

2. BACKGROUND

Investment in retail shopping centres represents a major sector within the commercial property asset class.  Historically, the sector has performed well against other property sectors such as office and industrial; delivering solid total returns and favourable risk-adjusted returns. However, over recent years, the sector has confronted some key headwinds which place at risk the demand for retail space; namely, moderating growth in consumer demand and ongoing growth in online sales.      

Online shopping, which had been growing slowly in recent decades, exploded in 2020 due to the impacts of the COVID-19 pandemic. Indeed, retail sales data from the ABS shows the growth in online sales increased rapidly and is reflected in a rising penetration ratio, currently around 10%, as shown in the Figure below. Furthermore, the NAB Online Retail Sales Index for September 2020, shows online spending had grown by 62.7% across Australia compared to 2019. This is based on Australians spending $40.9 billion on online retail; around 12.0% of total retail spending. It would appear the impact of online is more significant in discretionary type commodities.

Retailers as diverse as Woolworths, Harvey Norman, Officeworks and Bunnings have recently posted record online sales, highlighting the breadth of products which consumers are now willing to purchase online. Australia Post reported over 8.1 million households shopped online between March and August this year; 900,000 of them for the first time.

With the retail property sector being a significant commercial investment sector, the impact of online shopping poses real and significant risks, both in terms of demand for space and ultimately asset pricing. So, what are the medium-term risks to bricks and mortar centres, based on the lift in consumer spending moving online? And what commodity groups and centres, based on their current occupancy, are most at risk to the shift to online?

The PAR Group study seeks to answer these questions by reviewing just under 10,000 retail tenancies which occupy Australia’s 31 largest shopping centres to develop occupancy mix benchmarks across 11 commodity categories.  

This report is structured as follows. Section 3 presents the analytical framework used in assessing the impact of online shopping. Section 4 briefly discusses the datasets used. Section 5 presents key findings. .

3. ANALYTICAL APPROACH

The analytical approach in this study occurs in two stages. Stage one focuses on estimating sub-sector online penetration ratios (OPRs) while stage two focuses on estimating the ‘value’ impact across shopping centres.

Stage one: estimating sub-sector online penetration ratios

Stage one involves estimating online penetration ratios across shopping centres and across the retail sub-sector sample. The sub-sector refers to Super and Major Regional shopping centres. 

The online penetration ratio for each shopping centre asset was estimated based on the following expression;

where n=number of commodity groups (which is 11), ω is the weight assigned to commodity group i and OPRt refers to the online penetration ratio for commodity group i. This was estimated, based on reviewing consensus forecasts and current and future e-commerce penetration ratio trends.

OPRA is a measure to assess a shopping centre’s vulnerability to increased online shopping. A higher OPRA value suggests the shopping centre has greater risk to e-commerce and vice-versa for a lower value.

To keep the analysis simple, the weights (ω) are based on the share of the number of stores (tenants) for a given commodity group to the total number of stores for a given shopping centre. This exercise involved reviewing just under 10,000 tenancies across 11 commodity groups and across Australia’s 31 largest shopping centres.  

Modifications to the model can be made by using variable weights, conditional on value parameters such as MAT or a size parameter, gross lettable area (GLA). While this extension of the analysis is not reported here, it remains a key aspect of future analysis.   

In a similar fashion, the online penetration ratio for the retail sub-sector is estimated using the following expression;

where k=number of shopping centres (which is 31 in this sample), w is the weight assigned to shopping centre j. The weight is determined using MAT values across shopping centres.

Stage two: estimating value impact

Having estimated OPRs, a cross-sectional analysis by shopping centre was conducted to examine the impact of these OPRs on shopping centre value. This was done using a simple econometric model which translates MAT sales to value. Namely;

Note that both asset value and MAT sales are deflated by square metres (sqm) to make interpretation meaningful across shopping centre assets.

Furthermore, it is then possible to evaluate the ‘value’ impact for a given asset by comparing the difference in estimated values based on current MAT sales and adjusted MAT sales for anticipated OPRs.

While the model above is a simple way to gauge the ‘vale’ impact, it essentially only captures direct effects. The modelling does not capture indirect effects such as asset mitigation and adaptation strategies to higher influence of e-commerce. 

 4.DATA SET

The data used in the analysis comprises two main types:

  1. online penetration ratio across a range of commodity groups; and
  2. descriptive and performance metrics across 31 individual shopping centre assets.

Online Penetration Ratios (OPR)

The online penetration ratios reflect saturation values, taking into consideration the current online ratios, anticipated market trends and stabilisation levels over the next five-year time horizon.  Notably, commodities with high discretionary spending were assigned high OPRs.

Asset level shopping centre data

The asset level data was based on the largest 31 shopping centres deemed to be Super and Major Regionals, under the property sector classification according to the Property Council of Australia.

The sample set of shopping centres was selected by reviewing annual MAT sales over the period 2019 and 2020. The ownership of the shopping centres is diverse, covering 11 property companies / property fund managers.

The geographical profile of the sample across states, outlined in the table below, shows the domination of NSW both in terms of asset count and GLA.  

Apart from descriptive measures, various performance measures were also examined, including MAT per sqm, asset value and asset value per sqm.

All asset level data used in the study was obtained from public platforms and sources. Even so, only aggregated results are reported.

5.KEY FINDINGS

Tenancy composition across shopping centres. The chart below depicts the tenancy composition aggregated across the 31 shopping centres.  It shows the largest commodity groups are fashion (32%), food & beverage (22%), health & beauty (15%) and services-based retailers (15%).   

Centres with relative high exposure to fashion brands, typically 30% of each centre’s occupancy, and food and beverage, typically 20% of each centre’s occupancy, are most likely to experience the largest online sales leakages due to e-commerce platforms such as Uber Eats and Amazon but, increasingly, the e-commerce capability of most major retail chains.

In contrast, centres with relatively higher exposure to services-based retailers such as medical, beauty treatments and the post office, were likely to be less effected by online sales as these services could not be replicated online.

Online penetration ratios. The table below reports estimated penetration ratios that are likely to prevail over the medium term. These estimates were formulated based on benchmarks from international markets, primarily the USA and UK, publicly available information from retailers and shopping centre owners and agents. These estimates are viewed as a base case scenario and alternative estimated could be considered when undertaking scenario analysis.

Commodity groups with the highest OPRs included: hobbies, gifts & stationery and fashion, electronics. In contrast, commodity groups with low OPRs included: entertainment, discount & variety stores, retail services and sports & leisure.   

Impact on shopping centre retail sales. With the ongoing trend towards online shopping and using the estimated OPRs, our modelling suggests that around 20% of future MAT across Australia’s largest 31 shopping centres is likely to be adversely affected.      

The medium-term take-up of online shopping by consumers, with the proportion of online sales tipped to reach 20% of total retail spending by 2025, has the potential to significantly erode in-person sales and the underlying asset values of Australia’s major retail assets.

Impact on shopping centre asset values. Using estimated asset values from econometric modelling, it was found a dilution of MAT sales, averaging 20% across shopping centres, will result in a decline in asset values on a price per sqm basis by around 30%.     

Such a significant impact on sales and asset values not only reaffirms online shopping as a key risk factor to retail demand for these shopping centres but also raises the issue of risk mitigation measures. One such strategy would be to tilt the shopping centre towards those exposed to low OPRs, which some retail asset owners and operators are exploring.

THE AUTHORS AND PAR GROUP

Anthony De Francesco, Managing Director of Real Investment Analytics. M: 0438 506 284 or email: anthony.defrancesco@rianalytics.com.au

Rob Ellis, Director of the Data App. M: 0417 195 352 or email: rob@thedataapp.com

Damian Stone, Principal and Chief Problem Solver of Y Research. M: 0433 525 414 or email: damian.stone@yresearch.com.au

Real Investment Analytics (RIA), The Data App (TDA) and Y Research are partners in PAR Group (http://par.group/) an independent research collective offering a comprehensive range of property research and analytical services. The team is experienced in economics, property research, transactional and corporate strategy; all with extensive industry involvement in both the property and finance sectors.