A Quantitative Spatial Exploratory Analysis on Fast Consumer Goods, Shopping Trips, and Discount Supermarket Revenues: The Case of Istanbul
Mete Başar Baypınar, Cem Beygo, Gökalp Köseoğlu, Elifsu Şahin, Burcu Aksoy SertbakanIn response to changing consumer behaviors, innovative retail chains have begun offering consumers higher value and a higher quality experience than competitors. For successful diffusion in a country, innovators must establish a competitive position by creating better value for consumers offering a more appropriate product and quality of service compared to competitors. Consumers adapt the structure, cost, and frequency of their shopping baskets and visits to the changing spatial conditions, cultural norms, and time costs in order to maintain their living standards. A better understanding of the temporal behavioral changes of spatially segregated consumer groups opens the way for econometric studies that can inform what strategic decisions will help the successful development and diffusion of innovative store formats. Spatial data exist in abundance, and examining new retail potentials and analyzing current performance have become easier. However, the literature has thoroughly criticized the insufficiency of existing business intelligence applications regarding their theoretical foundations and empirical findings, as well as their ignorance of the exceptional conditions of emerging market economies. Another limitation concerns data confidentiality. This article demonstrates how open-source secondary and primary data collected through surveys are helpful in generating new spatial and non-spatial variables for further use in econometric and statistical studies. Within this scope, the study analyzes the annual change in demand for fast-moving consumer goods in terms of middle- and lower-income groups originating from residential areas in Istanbul within shopping basins using geographic information systems. The study then identifies the changes in the number of planned and unplanned shopping visits and the local potential for discount markets. These comparisons using officially announced data reveal the method to be successful. The study’s findings have the potential to guide statistical and econometric business intelligence applications in developing innovative retail formats in Türkiye and similar countries.
İstanbul’da Hızlı Tüketim Malları Alışveriş Ziyaretleri Ve İndirim Market Cirolarındaki Değişime Dair Sayısal - Mekansal Keşfedici Bir İnceleme
Mete Başar Baypınar, Cem Beygo, Gökalp Köseoğlu, Elifsu Şahin, Burcu Aksoy SertbakanRakiplerine göre yenilikçi perakende zincirleri değişen tüketici davranışlarına uygun şekilde daha yüksek değer, dolayısıyla yaşam kalitesi sunabilen girişimlerdir. Bir ülkede yayılabilmek için öncelikle rekabetçi bir konuma yerleşmeli ve rakiplere göre ürün ve hizmet kalitesi ile tüketici açısından uygun maliyetler sunarak değer yaratmalıdırlar. Tüketiciler yaşam standartlarını korumak için alışveriş sepetleri ve ziyaretlerinin yapısı, maliyeti ve sıklıklarını değişen mekânsal koşullara, kültürel normlara ve zaman maliyetlerine göre uyarlamaktadırlar. Mekânsal olarak ayrışmış tüketici gruplarının zamansal davranış değişimlerinin iyi anlaşılması, yeni mağaza formatlarının başarıyla geliştirilmesi ve yaygınlaşmasına dair stratejik kararları besleyecek ekonometrik çalışmaların da önünü açmaktadır. Mekânsal verilerin bol olduğu günümüz koşullarında, yeni perakende potansiyellerini incelemek veya mevcut performansı analiz etmek daha kolay hale gelmiştir. Ancak mevcut iş zekası uygulamalarının teorik temelleri ve ampirik bulguları yeterince dikkate almamaları, yükselen piyasa ekonomilerinin özel koşullarını göz ardı etmeleri eleştirilmektedir. Bir diğer kısıt ise veri gizliliğinden kaynaklanmaktadır. Oysa gösterdiğimiz üzere, açık kaynaklı verilerin ve sahadan toplanacak verilerin çeşitli mekansal ya da mekansal olmayan yeni değişkenlerin üretilmesinde ya da bazı parametrelerin hesaplanmasında kullanılması mümkündür. Bu çerçevede İstanbul’daki konut alanları kaynaklı orta ve alt gelir gruplarına dair hızlı tüketim malları talebindeki yıllık değişim, mekansal ve mekansal olmayan veriler yoluyla alışveriş havzaları bütününde incelenmiş, planlı ve plansız alışveriş ziyaret sayılarındaki değişim deterministik bir şekilde hesaplanmıştır. Bu sayede indirim marketlere dair yerel potansiyeller ortaya konulmuştur. Gerçek veriler ile kıyaslandığında yöntemin başarılı olduğu görülmüştür. Çalışma bulgularının Türkiye ve benzer ülkelerde yenilikçi perakende formatları geliştirmeye yönelik yapılacak istatistiksel veya ekonometrik iş zekâsı uygulamalarına yön vermesi beklenmektedir.
For successful diffusion in a country, innovative retail chains must establish a competitive position by creating better value for consumers who adapt to changing social, economic, and technical conditions by adjusting their shopping trips and shopping baskets (Burt et al., 2003; Kim, 2008; Matusitz & Forrester, 2009; Matusitz & Leanza, 2009). Consumers adapt to maintain their living standards under changing conditions, and a better understanding of the temporal behavioral changes of spatially segregated consumer groups will open the way for econometric studies that can inform what strategic decisions would help successfully develop and diffuse innovative store formats (Hernández & Bennison, 2000).
Spatial data currently exist in abundance, and new computing systems have also become available that facilitate the dynamic examination of spatial retail potentials. Interest in such applications has also grown in Türkiye, where fast-moving consumer good (FMCG) expenditures take second place in household budget expenditures, mainly due to rising competition since 2010. However, the literature has thoroughly criticized the insufficiency of existing business intelligence applications regarding their theoretical foundations, as well as their relevance to empirical findings (Newing et al., 2013). Another limitation arises from data confidentiality, as retail chains do not reveal individual outlet revenues. As an emerging market economy, Türkiye also appears to have some special conditions that must be considered (Franz et al., 2013; Franz & Hassler, 2011; Hökelekli et al., 2017). A better understanding using exploratory spatial studies will open the way for econometric studies to provide better information about strategic decisions, thus allowing faster diffusion of innovative retail formats in emerging markets.
The potentials arising from socioeconomic status groups in particular locations also have particular interest. While the local real estate markets and transport infrastructure in these localities dictate the limits for consumer shopping trips and the size of shopping baskets on one hand, on the other, they also limit the available space innovative retail outlets can exploit. These particular situations must be empirically studied, as they may impose significant barriers against the successful diffusion of retail formats and consumer coping behaviors. This article demonstrates that specific demand pattens for discount markets in specific locations can be explored by utilizing parallel geographic information systems and computing platforms, as well as secondary quantitative data alongside primary qualitative data.
Within this scope, the study first determines the demand from middle- and lowerincome households for FMCGs originating from residential areas in Istanbul, using both Turkish Statistical Institute (TurkStat) household income statistics as well as derived spatial data regarding the precise location of certain socioeconomic status groups within district bazaar basins. The study then employs the Maptriks Geographic Information Systems (GIS) Engine, which allows 10 to 100 times faster calculation speeds with respect to traditional GIS algorithms by utilizing parallel hardware and parallel computing approaches, in order to identify the spatial borders of district bazaar shopping basins within 750 meters of walking distance through origin-destination matrices within the scope of a city with a population of 15 million people. This also allows how many discount markets are located within these basins to be identified. By making use of public company data regarding the annual change of average shopping baskets and primary qualitative data, this article establishes a structure for studying change in demand, deterministically calculating the average number of target households’ weekly planned and unplanned shopping trips with respect to expendable income on FMCGs. The study then calculates the potential demand in shopping basins per discount market. Using officially announced data, the comparisons reveal the method to have been successful. The study’s findings have the potential to guide and inform statistical and econometric business intelligence applications with regard to evaluating strategic development and diffusion innovative retail formats in Türkiye and other similar countries.