Retail analysis for major housingestablishments

Sammanfattning: The aim of the thesis was to develop a model for JM that can be used in the establishment of large housing projects. The model must be able to provide answers to what is economically possible to deliver the projects in form of retail and service. Using reference projects, which are built under other circumstances, may give a poor result and lead to large vacancies in the finished development. To develop this model, we have built upon a proven and tested model of Appraisal Institute, Buying Power segmentation method. Two case studies were done in order to apply it to the Swedish market. The model has been followed step by step but was also complemented with additional analyzes that were considered necessary for JM’s purposes. The case studies that took place were done in two new districts that JM has been involved in, Frösunda in Solna and Liljeholmskajen in Liljeholmen. In Frösunda Frösunda Torg was examined while in Liljeholmen it was Liljeholmskajens retail area. These two areas are of different characters, which is also what the results showed. In Liljeholmskajen there is a better retail structure and it is considered to be more lively area than Frösunda. Based on today's retail space Frösunda has a leakage of 70 % in their primary area and 85 % in their secondary area to their competitors. In Liljeholmen these were 50 % and 80 % respectively. One reason for these large leakages is the nature of the competitors, major shopping centers in Solna and Liljeholmstorget. Frösunda Torg and Liljeholmskajens retail area can therefore not compete against them in the same way since they are not shopping malls. Analyzes that completed the model were shop distribution in both housing areas. They have been analyzed using statistics from SCB and HUI. The statistics show Sweden’s and Stockholm’s store allocation for daily goods, seldom goods and restaurants. The analysis shows that the retail distribution in Liljeholmen was much better and closer to the statistics than of Frösunda. Frösunda was further analyzed in a scenario analysis where Liljeholmen’s input of sales retention was used as a reference. The result of this was that Frösunda could have had considerably larger retail area, particularly within seldom goods category. The statistics from SCB and HUI remains debatable as it is general and based on the entire country or Stockholm. Afterwards there has been a further analysis where the existing households were analyzed with data from SCB and Conzoom. It turned out that Frösunda and Liljeholmen consisted more or less out of the same type of customers, Lyxlirarna as Conzoom call them. The household preferences and preferred stores are now known with Conzooms mapping of customer profiles. This can be of great use in order to meet the residential area’s requirement for retail and service. Housing companies have a large social responsibility when developing new areas. The model which calculates the demand in the area was proved to be a good start. The analysis has shown that it is important to create added values for residents by choosing the right kind of shops, services, meeting places and green spaces. It is important to create an attractive area that appeals to individuals and companies to run their business there.