PhD Studentship - University of Southampton, Marketing Research Group
PhD Studentship - University of Southampton, Marketing Research Group
The success of grocery retailers have often been linked to strategic choice of store location and store format corresponding to market opportunities in the chosen location. Prior research on the success of grocery retailers have mainly focused on the influence of market structure and competition on dominant positions. However, grocery retailers carry a wide assortment of products ranging from fast moving consumer goods, clothing to financial services. Drawing on the strategic networks literature, it can be argued that the structural design of network positions influence the extent of network opportunities available for product innovations. Specifically, a central and dense network position may favour affiliated benefits within the retailers' In contrast, multiple ties (structural holes) support non-redundant information and knowledge that the retailer is more likely to increase innovativeness through exploration. To carry out this project, a unique data set that includes store locations and network positions will be assembled. The data will be used to estimate the market structure model (extend to store locations to network positions) by using spatial analysis. Prior studies have estimated the store-level revenue model such as a two-stage estimation procedure similar to Mazzeo's Keywords: Retail store locations, Network positions, Spatial analysis, Exploitation and Exploration, Retail performance Supervisory team: Professor Teck Eng and Dr Ioannis Krasonikolakis For an informal discussion please contact Teck, mail to: t.y.eng@soton.ac.uk Primary research group: Marketing Research Group, Southampton Management School. This project is concerned with the significance of grocery store locations and their implications for exploiting and exploring network opportunities in the marketplace.
network with product innovation through exploitation.
(2002) approach building on the work of Heckman (1979). The data analysis will use statistical programming such R and S.