COMPETITION AMONG MULTIPLE RETAILERS WITHIN A SMALL AND FAST DEVELOPING ECONOMY

In the intensely competitive retailing sector of the new EU accession countries, retailers often compete on the basis of diversification or high growth. With high growth, discount pricing is the key. As new member countries often have households with a low purchasing power, price-based competition is widespread. However, as these economies grow, retailers will need to diversify away from simply a low price strategy. Using the case of Lithuania, a sample of mUltiple retailers is examined from the consumer perspective. Consumer loyalty. a multiple retailer'S image. differentiation and the idea of a purchasing occasion appear to be where retailers should focus as they move away from a narrow low price strategy.


Introduction
Economies of new EU member-states differ from economies of elder ones in a number of characteristics. The most obvious ones include GDP per capita (lagging behind 2-4 times) and the rate of economic growth, which significantly exceeds the growth of the old EU members. The two characteristics are interrelated, and countries with lowest GDP levels typically show fastest growth rates.
Economies of new EU member states differ from those of the elder EU member states in a number of ways. The most obvious difference is per capita GDP, which can be 2-4 times lower. The poorer new members also have higher growth rates of per capita GDP, often found around the world when comparing poor and rich economies.
While the EU market is quite open, the industrial structure of many new members reflects local conditions, geography and culture. Retailing is no exception. Low household incomes and per capita GDP suggest that retailing may be constrained by the overall economy. However, high economic growth suggests that important new directions are possible as well. Though retailing was historically underdeveloped, new retail chains have rapidly grown, and now intensely compete with each other. Understanding consumer behaviour and management of the chains is now critical to understanding where retailing is going. Though overview and methodology type publications exist (Kielyte, 2002, Pajuodis, 2005, retailing of new EU member states is understudied in the literature. As an important sector, retailing is attracting the attention of researchers. During the last decade, retailing companies increased their role in distribution channels (Bell, 2002). Some authors conclude that the overall growth of retail power has been specifically driven by the growth of the multiple retailers, which are increasingly absorbing some wholesale functions (McGoldrick, 2002). Development and successful management of private brands also increase the significance of multiple retailers, since through this they take part in manufacturing process (Dekimpe, 2002). Multiple retailers are also performing the role of gatekeepers within the channel of distribution (Gilbert, 2003).
Major retail market features include intense competi tion and slow growth (Kristensen et aI.,200 I). Some authors have even called the competition "dramatic" (Popkowski et aI., 2000). This suggests a need for analysis of consumers' attitudes towards competition if a retailer is to remain competitive. Analytical methods here can vary from a traditional market analysis to a customer-based approach of using perceivedrisk theory in analyzing store perceptions and store risks in this context (Mitchell. Kiral, 1999).

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Competition among retailers has also recently been studied. Studies range from analysis of the overall power of retailers (Ailawadi,200 I) to more specific issues such as market segmentation in retailing (Shaw, Cresswel, 2002;Steenkamp, Wedel, 2001;Daneels, 1996, etc.), retail consumers' behaviour, and satisfaction and loyalty issues (Murray, 2005;Kristensen, Juhl, Ostergaard, 200 I, Popkowski Leszczyc, Sinha, Timmermans, 2000, etc.). Almost all these issues are in some ways related with interaction between retailers and their customers, directly or indirectly integrating the aspect of competition among retailers (Magi, 2003;GonzaIelez-Benito, Muiioz-Gallego, Kopalle, 2005). However, much of the discussion about retailers' competitive strategies remains rather similar to the decadesold discussion of price versus non-price based competition among retailers (Morelli, 1998;Mazumdar, Raj, Sinha, 2005). With new EU members, there are some more general studies (Pajuodis, 2005), and some initial ideas are suggested by the authors of this article (Urbonavicius, Ivanauskas, 2005). Since there is an obvious lack of studies on competitive strategies of retailers in new EU member countries, authors of this paper aim, at least partially, to fill this gap. We choose the option to analyze competitors' strategies from the consumer perspective. Insights into consumer (buyer) loyalty, multiple retailer's image attributes, and specific purchasing occasions allow us to see the current starus of competition among retailers as well as to propose some ideas for strategy development.
The objective of this paper is to focus on consumer opinion as we analyze retail competition in Lithuania.
Authors believe that the customer-based methodology of competition analysis is rather universal, and thus can be successfully applied in the retailing sector. Therefore customer choices and associations were used for analysis of retailing clients' preferences, loyalty and associations of multiple retailers with certain buying occasions. These issues are analyzed in separate paragraphs, which follow a brief review of Lithuania's retail market and the methodological parts of this paper.

Scope of the research and methodology
Among the new EU member-states, Lithuania represents a good case of controversial influences of the economy on development of retailing strategies. Lithuania is the 19th among the EU countries in tenns of population with 0.7% of the total EU population residing in Lithuania. The Lithuanian economy is also among the smallest in tenns of total GDP which in 2004 was 18100 million EUR. The 2004 gross domestic product in purchasing power standards (PPS) was less than half of average EU (EU-25 = 100) GDP, but ahead of Poland and Latvia. At the same time, 2004 prices in Lithuania were among the lowest among all countries (48.6% of the EU average, measured in comparative price level indices at GDP levels, including indirect taxes)'.
Naturally, low levels of GDP and PPS can be evaluated as very unfavourable indicators for development of retailing. The low price level also hampers retailing growth, but this indicator can be considered both as a cause and effect in that it can cause a slowdown of the development of retailing companies and increase price competition, but also by itself can be a result of aggressive discounting, used as the main tool in competition among retailers. In tenns of GDP growth, as Lithuania is repeatedly one of the fastest growing EU economies (6.7 in 2004, 7.0 in 2005)', retailing has a great promise.
Another unique feature is found within Lithuanian retailing sector. Retailing sales in terms of both food and non-food items are growing by more than 10% annually. In 2002 and 2003, Lithuania's retail turnover growth rate significantly exceeded the average retail sales growth rate of the EU-25 as well as Latvia and Estonia'. In 2004, sales volume of Lithuanian food retailers was 2085 million EUR. This growth was correlated with an increase of average selling space per retailing outlet from 91.1 m' in 2000 to 122.2 m' in 2004. With a declining population, this resulted in retail trade space per thousand inhabitants increasing by 45%.
While the total number of retailing outlets decreases, the overall selling area of existing retailing outlets constantly increases. This is because Lithuanian food retailing is dominated by strong and constantly growing multiple retailers mainly developing supennarket fonnat stores. The share of product sales in supermarketlhypennarket format outlets in 2004 exceeded 50%, reflecting a high the speed growth (share of sales in these outlets grew by 10% during less than 4 years). Multiple retailers basically belong to four ownership groups, out of which only one is not developed domestically. Four multiple retailers play the major role in food retailing: VP Market, Palink, Norfos mazmena and Rimi Lietuva. In 2004, consolidated turnover of those four retailers was I 680 million EUR accounting for 45% of retail turnover (excluding from the total sales motor vehicles and motor fuel). The four companies employed 20% of retail sector employees. All four largest multiple retailers are among the 30 largest Lithuanian employers and among the 30 largest companies in terms of sales." This shows the importance of the largest multiple retailers not only in the Lithuania's retail sector, but also for the whole economy.
All major retailers are operating/developing operations both in Lithuania and in markets of other (not only neighbouring) countries. In many instances, management of these multiple retailers is based on fast learning and overall business skills rather than on formal specialised education or rich industry experience. Therefore competitive strategies typically are rather flexible, not always well defined, and often dominated by pricing arguments.
In these conditions, comparison of strategies of multiple retailers seems to suggest analysis from the standpoint of consumer perspectives rather than components of strategies themselves. This seems to be more applicable than applying well-known general models that look at competitive forces as a whole (Porter, 1985), the strategic aspect of competition, overall classification of types of competition (Henderson, 1980;Kotler, 2003), OR definition between the current and potential competitors (Kotler, Keller, 2006), etc. Applying the market concept of competition allows analysis of distinct competitors (Best, 2004). Based on it, two approaches are typically used for identification of specific competitors and evaluating how close they are (Aaker,200 I): • Strategic groups approach.
Strategic groups approach can be described as looking into a competitive situation from the standpoint of a company (one of the competitors). Expert opinions are used to group similar competitors into consistent groups, which later " Bused on infromotion of the Lithuanian Statistics Department. hllp'!lwww std !lIen 86 on can be analyzed across various dimensions (Mockus, 2003). Though this method allows disclosing specific characteristics of every group, analyzing their competitive advantages, strategies, assets and competencies, it just partially reflects the attitudes and possible reactions of direct retail customers.
The customer-based approach suggests evaluating competition from the standpoint of customers, concentrating on their behaviour patterns and choices. This approach allows identifying distant and indirect competitors, discovering new priorities and attitudes of customers towards specific aspects of competing offerings. The customer-based approach allows also tracking customer choices of different brands, companies or product types. It can also be directed towards analysis of product-use associations for identifying and understanding product use occasions or applications. In some way, multiple retailers and their complex services themselves represent brands that are comparable with brands of individual products. Though some authors questioned this issue, Jary and Wileman (1998) concluded that retail brands are "The Real Thing", although differing from product brands "not least because of the di ffi-cUlty of managing the multiplicity of attributes of a retail brand". In other words, customer attitudes and preferences towards multiple retailers' offerings can be analyzed in a similar way as in other cases, though retailers' offerings are more complex and harder to manage.
In this paper, we analyze competition among multiple retailers based on two aspects: I. Competition among differently named chain stores -this aspect corresponds with customers' choices among different brands. 2. Competition among multiple retailers in different shopping occasions -this aspect corresponds with analysis of product or service use associations.
This type of analysis is rather new for Lithuanian retailing, because no literature has yet applied such a "double" evaluation technique before.
Competition among multiple retailers was analyzed using a sample of multiple retailers operating in Lithuania, selling food products plus various non-food items (hereafter called "multiple retailers" or "chain stores"). This sample was used because: • multiple retailers were rapidly developing their activities during several past years in Lithuania and play an important role in the economy; • competition among multiple retailers is more intensive compared to chain stores operating in other retail sectors in Lithuania; • since the majority of Lithuanians frequently buy from multiple retailers. most people can respond to questions about these firms.
The empirical research was designed to test three major hypotheses: HI: Customers are loyal to only one store or a single chain of stores. H2: Multiple retailers have distinctive differences among themselves, and these differences predetermine their competitive advantages. H3: Similar multiple retailers compete in a distinct shopping occasion.
Empirical evidence was collected using two surveys. The first one (qualitative) included sets of in-depth interviews with customers. The second survey was a quantitative survey of the Lithuanian population. The series of in-depth interviews were used as a pilot survey for development of a detailed questionnaire. At the same time, information from the in-depth interviews was used for qualitative interpretations of some quantitative findings.
The in-depth interviews with multiple retailers' clients were performed during July-August of2004, and included seventeen respondents. Those re-spondents varied in terms of their demographic characteristics, had different income, and were buying larger part of food and non-food products for their families or households. Respondents for the in-depth interviews were selected from three largest cities of Lithuania (Vilnius, Kaunas and Klaipeda). The quantitative survey was performed in August 2004. It was part of the National Omnibus survey, which was performed by the public opinion and market research company Ba/tijos tyrimai. The survey included 1014 respondents aged between 15 and 74 years. The research company ensured that the structure of the sample matched the main socio-demographic characteristics of Lithuania's population as a whole. Data were analyzed only for descriptive statistics and development of image profiles, which was sufficient for testing our hypotheses.

Competition among chain stores
In-depth interviews indicated that most customers of mUltiple retailers usually have a set of several stores they shop at. Analysis of the data revealed that the majority of multiple retailers' clients (almost 63 percent) are not loyal to any single store and prefer buying in several of them. Only about 15 percent of clients can be treated as loyal to a single favourite store. For 12 percent of clients, there is no difference where to buy, therefore they do not have any favourite stores. Ten percent of respondents had no opinion or did not answer this question. In depth interview data suggest that customers are not loyal to one favourite store, because they select one or another store from a set of their favourite stores according to their needs and desires in a specific situation. Therefore the first hypothesis saying that "customers are loyal to only one store or a single chain of stores" should be rejected.
Analysis of survey data showed which mul- Table 1. Chains of store., where customers shop most tiple food retailers are the most popular among frequendy Lithuanian customers. These include Saulute. No/fa. Iki and Maxima chains of stores (see Table I).
These findings also reveal that a large number of stores in a particular chain are not associated with a greater popularity. For example, the percentage of customers who are most frequently buying in the Norfa and Iki chains don't differ much (2 percent), while the number of Norfa stores is larger than the number of Iki stores by almost 30 percent (at the end of December 2004 the Norfa chain had 87 stores (Elta, 2004) and the Iki chain 67 stores (Delfi, Elta, 2005». Another example: the Pigiau grybo chain has two times more stores than the Maxima chain (at the end of December 2004 the Pigiau grybo chain had 51 stores (Delfi, Elta, 2005), while the Maxima chain had 25 stores (Elta, 2004», but the percentage of customers most frequently buying in the Pigiau grybo chain is considerably less than the number of customers who prefer Maxima. Therefore we show that the popularity of a chain store among customers does not directly depend on the number of stores in a particular chain, but rather is influenced by numerous other factors. Based on in-depth interviews, we find these factors to include customers' opinion about a particular chain store, customers' perceived quality of retail services provided in a particular chain store, or customers' impression about how well their needs are satisfied in a particular chain store. Since buyers typically have one more or less preferred retail chain (where they shop most often), the set of its closest competitors includes stores where the same person buys relatively often. These alternative shopping places can be seen as closest possible substitutes for the place of the most frequent shopping. Therefore further analysis is based on the linkage between 88

Pigiau grybo'
3.3% the list of preferred multiple retailers (where customers buy most frequently) and the list of other visited multiple retailers (where the same customers also buy relatively frequently). Results of this comparison are shown in Table 2.
In the top-horizontal line of Table 2 we can see a list of chain stores where the customers shop most frequently. The left column lists chain stores which the same customers also visit often (respondents could indicate as many of the chain stores as they wanted). Percentages in every column show the number of buyers who are frequently shopping in other specific chains. In other words, it shows which chains are competing for the same customer. For example, almost one third of customers who most frequently shop in Saulute also frequently shop in Iki and Norfa chain stores. About one-sixth of Saulllte customers also frequently shop in Maxima and Pigiau grybo chain stores. Based on this, we can make a conclusion that Saulute mainly competes with the lki. NO/fa. Maxima and Pigiau grybo chain stores (named in the order of decreasing importance).
Results of this analysis of competition among multiple retailers show that competition for the same buyer is going on not just among retailers of the same format, but also among retailers S Currently operates under (he logo Leader Prke.  Table 2 we can see that the three chain stores compete for the same clients, i.e. there is some degree of cannibalization". Besides that, the results in Table 2 show that the concept of customer share is important in competition among the mUltiple retailers, because several mUltiple retailers are dividing among themselves expenditures for similar products of the same customers. As in other countries, these results confirm findings of previous research showing that consumers divide their purchases  across different outlets (Magi, 2003). These general findings allow moving further and assessing more specific characteristics that make retailers similar or different in customers' evaluations. These differences could serve as a basis for competitive advantage of particular retailers.

Competitive advantages of multiple retailers
In-depth interview data show that the customer's decision where to shop is based on evaluation from two to eight image attributes of stores. Survey data allowed evaluating which specific image attributes are the most important for customers when they select a store for shopping. The most important image dimensions for clients of multiple retailers are shown in Table 3. During the survey, respondents were asked to evaluate the image of their favourite store on each of the image attributes on a seven-point semantic differential scale. Based on respondents' answers, we developed and analyzed image profiles for each of the four most popular chain stores on the six most important image attributes (see Fig. I). This helped evaluating competitive advantages of the most popular multiple retailers.
The first immediate conclusion that comes from the analysis of image profiles is that the four most popular multiple retailers are very similar. In other words, they lack any clearer differentiation in terms of the six major attributes. This is possibly a consequence of implementing a low price strategy. Second, customers' evaluation of all six image dimensions is above average, which means that customers' opinion about the 7,0 most popular multiple retailers is quite positive. Third, none of multiple retailers have absolute competitive advantage over rivals in all six image attributes. the Sau/ute and Norfa chains have a competitive advantage in terms of prices. The Maxima and Iki chains have a little competitive advantage on product quality. The Maxima chain is a leader in assortment variety. The Maxima and Iki chains are a little better than the others on store location. Again, the Maxima and Iki chains have a competitive advantage in the quality of services. And finally, the Maxima chain has a competitive advantage on price discounts and special ofTers. According to these results, the second proposition stating that "multiple retailers have distinct differences among themselves, and these differences predetermine their competitive advantages" is wrong.
We can come to a conclusion that while none of the most popular multiple retailers has absolute competitive advantages over rivals on the six most important image attributes, the Maxima chain of stores seems to have the best overall competitive position. This chain was evaluated by customers better than the competing chains on all image attributes except product prices. The lki chain of stores would be in the second place, and its com- However, since the differences among retailers are relatively small, the above analysis does not allow indicating the key factors that predetermine success in competition. Therefore we proceeded to evaluation of competition among multiple retailers, using the aspect ofretail services use associations, making one more effort to find the answer to the

Competition of multiple retailers in different shopping occasions
Results of in-depth interviews with customers of the mUltiple retailers have shown that there are several shopping occasions when customers' behaviour is significantly different. Those shopping occasions disclose different needs, preferences and habits of customers. Customers have also noticed that their shopping behaviour and habits usually can be linked to several shopping occasions in parallel. Survey data analysis showed that a large part of buyers agree that their behaviour reflects a certain buying occasion (Table 4).
These results tell a lot about customers' shopping behaviour and habits. A large number of customers prefer buying food products in small quantities, but often. Those customers value the quality and freshness of food products. Almost one-third of customers prefer saving time and having possibility to select products from a large variety. Therefore they buy large quantities of food products, but once a week or once per several weeks. Surprisingly, quite a big part of customers buy the highest quality food products and precooked foods. Those customers are saving time for food preparation at home and have exclusive needs for food products and their quality. One-fifth of people buy clothes and footwear together with food products. Those customers often are price-sensitive and not requiring high quality of clothes and footwear. This allows stating that multiple retailers also compete with specialized apparel and footwear retailers, and even with catering service providers.
During the survey, customers also indicated chains of stores which in their opinion were the most suitable for each of a shopping occasion (Table 5).
It is noticeable that several types of chain stores compete for attention of clients when they buy everyday food products. Competition in this case involves supermarkets, convenience stores and discount stores. All those chain stores have one common feature -they are small or medium-sized. Supermarkets and hypermarkets, (i. e. larger stores) compete in buying larger quantities of food products and necessary non-food items. Only the largest stores -hypermarkets Hyper Maxima, Maxima, Hype/' Rimi, together with Iki supermarkets -can be suitable for buying precooked foods and luxury food products. And finally, only the largest stores are considered suitable for buying clothes and footwear.
These results also provide the background for a possible evaluation of how expenditures of products HyperRimi the same customer are divided among different chain stores. For example, if the same customer every week does several small-scale shoppings in a convenient store and once per two weeks he (or she) does large-scale shopping in a hypermarket, we can guess that the major part ofhislher expenditure for food products and various nonfood items will be left in a hypermarket.
In general, we can conclude that the same customer sees different sets of potential shopping possibilities depending on a specific buying occasion. On the other side, various multiple retailers and store formats are di fferently evaluated in terms how suitable they are for different buying occasions. Therefore we can state that multiple retailers not only compete for particular customers, but also for customers on particular shopping occasions. In this case, lhe third proposition that similar multiple retailers compete on distinct shopping occasions seems to be right.

Conclusions and implications for further research
The major purpose of the paper was to analyze competition among multiple retailers in a small but rapidly growing economy of the new EU member-country group, and to develop propositions about the competitive strategies of retailers that are influenced by specific economic conditions. Because of the scope and methodology, the research findings are of exploratory nature.
Based on the analysis, the authors hypothesize thal in a small and fast developing economy buyers (customers of multiple retailers) are not loyal to a single store or single retailer. Instead, they typically have several preferences, and only a relative loyalty to a few retailers at once can be defined. In this case, certain retailers can attempt increasing their share of a customer's shopping rather than develop loyalty in a classical understanding of the term.
The most popular multiple retailers in Lithuania are Sau/ute. NOlfa. Ik; and Maxima. The popularity of these chain stores does not depend on the number of stores in a chain, but rather on favourable customers' opinions and their positive impression about the high quality of retail services and good satisfaction of their needs.
Multiple retailers of the same format and multiple retailers of different formats compete for the same clients and share of their expenditures. Moreover, even differently named chains that are operated by the same retail company compete for the same customers thus producing cannibalization effects. This observation is related with the unclear differentiation of retailing chains. This also suggests that needs and requirements of customers are not homogeneous or vary depending on the purchasing occasion.
Another important observation is that multiple retailers in Lithuania are not really differ-entiated. From the customers' perspective, none of them have specific differences of clearly identifiable advantages over the others. The Maxima chain seems to have the strongest competitive position, but the Iki chain store is not far behind.
We conclude that under conditions of a small and price-sensitive market, retailers cannot afford a strict market targeting and differentiation on the basis of different groups of buyers. Instead, they need to attract the same clients. One way of doing this is specializing in being advantageous in certain purchasing occasions (buying for a daily consumption, buying for whole week, etc.). The research showed that buyers can well define different shopping occasions and describe their specific needs and requirements in every one of them. This opens opportunities to specialize on this basis in addition to traditional ways of differentiation.
There are also some implications for further research. Analysis of shopping behavior on different shopping occasions has just been started and needs to be developed further. We believe that future research would be helpful for a better understanding of customers' behaviour and increasing their satisfaction and loyalty. Another research direction is competition analysis based on customer attitudes in other retail sectors. This could help evaluating competition in other retail sectors and comparing the possible differences of competition in different retail sectors.