Have Discount Retailers gone upmarket in the UK?

Preliminary Information

Working Title of Dissertation: Have Discount Retailers gone upmarket in the UK? If so, how and why?

Research Question and aim:

• To investigate location of Aldi and Lidl stores in relation to income/social class of catchment area(compare 1991, 2001 and 2011 census data) to understand store strategy.
• Why would more affluent household shop at hard discounters?
• Understand hard discounters non-locational strategy.

Introduction

The review aims to look at theoretical explanations of retailer’s change such as the Wheel of Retailing and the Conflict Theory. It then focuses on research studies which try to understand consumers store choice decision and factors influencing it. Finally, it will briefly look at methods which are used to understand retailers’ store decisions. All the sources are either books or peer-reviewed journal articles. Understanding the current literature available is important as it would help support my research findings and improve my research methods based on other academics’ research.

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The most widely used model in explaining retail growth is the Wheel of Retailing created by McNair in 1958. The details of his work are mostly described in Hollander (1960) work. The model describes most retailer start as a low margin or focuses on low prices such as the discount grocery retailers. Investment in facilities and services increases, therefore, leads to increasing cost and price with its emphasis on service which allows a higher profit margin. This leaves a gap for lower margin retailers to enter the market which will make traditional retailers vulnerable to competition.  Hollander also identified the factors causing the changes which are Management Deterioration, price competition and excess capacity in factories. The Retail life cycle is a similar theory propose by Davidson et al (1976) cited in Levy et al (2005). It describes 4 stages of a retailer: Introduction, Growth, Maturity and decline. The focus is the profit level and the market share whereas the Wheel of Retailing focuses on the price-quality continuum. Sparks (1990) case study on Kwik Save provides an excellent case study on how it has progressed through the cycle with the name ‘discount’ removed from their store in 1986 suggesting a move to the maturing stage. These cyclical theories are simple to understand and supportive examples can be found, however, Roth and Klein (1993) found that it is very difficult to test it with limited expense data and Brown (1991) criticise that it only considers price and quality and ignores other factors such as assortments and store size. Also, it assumes that there is only one path to retail growth, therefore alternative theories such as the Big Middle (Levy et al, 2005) was developed. It considers another path of development through innovation targeting at a higher income market which then moves into the Big Middle to benefit from economies of scale and where there is the highest demand focusing on services.

There are also non- cyclical theories. The conflict theory suggests competition is the main reason for changes in retailing. Stores can be classified as thesis which has higher margins and antithesis which have a lower margin (such as discounters). Over time, a merger could occur which will lead to synthesis to reduce competition or increased price competition through introduction of value private labels (Burt and Sparks, 1994). Changes in the environment also encourage retail changes. Levy et al (2005) mentioned Dresseman ‘s(1968) work which uses Darwin’s natural selection theory as an analogy for retail changes where only the ‘fittest’ store will survive. Roth and Klein (1993) also identifies environmental factors such as demographics, regulation and demand encourage retailers to adapt otherwise they would be outcompeted.

Overall, the theories suggest that retailer change due to a changing environment and try to avoid competition, especially price which is the focus of retailers who just joined the market.

Consumer’s store choice

Understanding consumers shopping behaviour is important as it allows retailers to strategically plan their store location, format and the assortments. Therefore, this is an area which is widely researched. Fox and Sethuraman (2010) and Leszczyc et al (2004) provides a summary of consumers store choice and segmentation. There are three types of consumers: price, service seekers and cheery-pickers. Price seekers are usually from lower income households who are more price conscious (Katsaras et al., 2001) and would travel to an everyday low pricing (EDLP) stores which are usually cheaper, larger stores to do their main shopping. This includes the deep-discounters. For service seekers who usually are single household who have a higher income and time-deprived due to work commitments, they therefore value convenience store more which provides better services such as Tesco Express Shops. They are known as High/Low Price Store (Hilo) who offers discount by promotion. When doing a Multi-Purpose Trips, both groups will visit stores near shopping centres and would visit both types of stores. The final type of shopper is the cherry-pickers who go to different stores to look for the best deals, hence they would visit both types of stores and have a lot of time to do shopping but also has the lowest loyalty to a brand or store.

Apart from price and convenience, assortment is another factor affecting store choice. Briesch et al (2009) found that it is the 3^rd most important factor and it is measured in Store Keeping Units (SKU). Generally, store size is used as a proxy for assortments hence EDLP stores usually has higher SKUs and are more attractive to customers who want choice. However, Broniarczyk et al (1998) study found that retailers could make significant reduction in SKUs and customer’s perception will remain the same. Briesch et al (2009) also concluded that only the number of brands and availability of favourite brands would affect store choice suggesting assortment could be less important than brands in consumer’s store choice decision.

Brands can be separated into private labels and National brand. The UK is a unique market that the private labels are stronger than in continental Europe. For example, Tesco own private label has three grades: Value, Finest, Normal (Krafft and Mantrala, 2010) which is different from other countries where private labels are seen as low cost and quality(Burt, 2000) hence able to directly compete with National Brand. In the same paper, he mentioned previous studies in the USA by Myers, 1967 found that there is no socio-economic difference in choosing National or private brands but Liversey and Lennin (1978) found that more affluent and young people are more likely to take risks to buy new national brands than lower income people. Hence there is no clear consensus whether private and national brands are targeting different groups.

During economic recession, people become more price orientated hence Hard-Discounters would be popular during the period as their price are 15-40% cheaper than traditional retailer (Lamey, 2014). According to Colla (1994) study, he found that 1/3 of people in the sample thinks that the quality in discounters is high due to the basic display hence shop from them. This means traditional retailer are not only competing with hard discounter on price but also on its quality which means after recession, these customers are very likely to be retained. Also, this shows different customer has different view on factors such as quality, therefore different literature provides a different view and there is no consensus on the most important factor.

It is now becoming common for retailers to use models to help decide where stores should be located. The three methods that will be discussed are Regression, GIS and Spatial Interaction Model. Regression can be used to accurately predict how one factor affects another with known values. This allows understanding of the relative importance of each factor. Leszczyc and Timmermans (1997) work used regression to analyse variables such as income with repeated trips, store loyalty etc. using data collected from consumer.

GIS can be used to help to understand store location decision by doing simple catchment area analysis. This involves drawing a buffer of a certain travel time or distance on the program to show how far people would travel to a store (Benoit and Clarke, 1997). Neighbourhood data could also be incorporated which will help to identify potential new site and analyse current store strategy of a retailer. However, this paper and Birkin et al (2002) raises issues of using the method. How should the buffer be defined and when the buffers overlap, how can we allocate the number of consumers or revenue to each store? The second problem could be solved by using a spatial interaction model which according to Brown (1993), it considers the “Trade-off between distance and attractiveness of alternative of shopping area.” Hence revenue can be allocated according to the attractiveness (e.g. Floorspace) and its accessibility relative to another. This will improve the accuracy of the analysis.

The literature review showed that a wide range of theories have been constructed to understand changes in retail and through research has been done on consumer’s behaviour and how they are analysed. However, more research is still needed in understanding customer’s perception of different store types as results still vary a lot. The review of the methods helped me to consider other methods to analyse the relationship between discount retailers and income and the store choice review would help me with the questionnaire design to understand consumer behaviour for discount retailers. Finally, the theory review would help explain the findings in GIS analysis.

References

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Briesch, R.A., Chintagunta, P.K. and Fox, E.J. 2009. How does assortment affect grocery store choice? Journal of Marketing Research. 46(2), pp.176-189.

Broniarczyk, S.M., Hoyer, W.D. and McAlister, L. 1998. Consumers’ perceptions of the assortment offered in a grocery category: The impact of item reduction. Journal of Marketing Research. pp.166-176.

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