Retail agglomeration formats and outshopping in Thai grocery market

Thailand has been one of the emerging markets in Asia in recent decades. The pattern of consumers has dramatically changed due to the arrival of various modern retail trade formats. Thai consumers have been shifting from traditional retail formats to modern retail formats and frequently do ‘outshopping’, particularly from rural areas to town centres. This has led to the decline of rural retailers. To improve this situation, the concept of developing retailers in market towns has been adopted. However, it is unclear what form (i.e. store format) this takes and on which factors (store image attributes and customer characteristics) the role depends. This thesis examines the effect of store image attributes and customer characteristics on retail agglomeration format choice for a regular grocery outshopping trip. The conceptual framework is constructed following the stimulus-organism-response (S-O-R) model. The concept of store image is applied as the stimulus, and the customer characteristics are proxy variables representing the organism, which lead to the choice decision as the response. The discrete choice model is applied using the mixed logit modelling approach. The choice set includes (1) a traditional agglomeration retail format (TAF), (2) a modern agglomeration retail format (MAF) and (3) a non-agglomeration retail format (NAF). The unit of analysis is a household in a regional city that does grocery shopping regularly. The stratified random sampling divided the population into an urban area and a rural area. Then, a random sample was drawn within each stratum by a simple random sampling − a store format. A systematic random sampling was applied by intercepting each household representative in order to maintain randomness. The chosen area is Nakhon Ratchasima province which is one of the regional cities in north-eastern Thailand. It consists of 2,600,000 people (around 830,000 households) and about 75% of the total population live in a rural area. The total sample consists of 1,521 households. The choice experiment is adopted by a computer-assisted personal interviewing (CAPI) survey. The parameters are estimated using the simulated maximum likelihood approach. The models are built, and then marginal effects are used to examine the effects of store image attributes and customer characteristics to the retail agglomeration format choice. Reliability and validity are tested. The results from the chosen model reveal that increases in seven store image attributes: product quality, customer service, price, travel time, atmosphere, accessibility, and range of products, affect the probability to shop at TAF and MAF with the same degree, while in store attributes have less effect on the probability to shop at NAF. The product quality, customer service level, and price are the most important attributes affecting the retail agglomeration format choice, following by atmosphere, accessibility, and range of products, respectively. The results indicate that consumers in rural areas are likely to shop at TAF and NAF than consumers in urban areas. Older rather than younger customers tend to shop at NAF. Finally, the higher income households have more opportunity to shop at MAF than the lower income households. This study employs the theory of cumulative attraction as theoretical lens of the study. However, this study contributes to the theory by examining further dimensions. The first contribution is to the theory of cumulative attraction by considering a location dimension. It investigates the role of retail agglomeration formats in market towns. The second dimension contributes to retail management by focusing on retail management style as traditional and modern retail formats. Another contribution of this study is the taxonomy of retail agglomeration formats. It indicates how retailers are planned and constructed, to what extent they are managed and marketed, and what their management styles are. This classification system can categorise existing retail formats, e.g. weekend markets, periodic markets, night markets, tourist attraction retail sites, and exhibition retail outlets which cannot be classified by the previous studies. The application of this taxonomy is applied as retail agglomeration formats in this study.