As increasing competitiveness in a local broadband access market, stimulated by the explosive growing of the Competitive Local Exchange Carriers (CLECs) and the advances in technology in recent years, strategic location planning is important for a firm to increase the market share by expanding geographic coverage. Most previous competitive location studies have paid little attention to the broadband access market, and therefore those studies may not represent adequately the actual broadband market situations. Moreover, significant components and methodologies in competitive location modeling have not been addressed in an integrated view.
With an emphasis on the characterizing features of the broadband market and competitive structure, this thesis seeks to address various spatial and non-spatial issues in competitive location modeling and provide an outline of methodological development in a single research framework. This research utilizes a wide variety of concepts and methods in many academic fields, such as customer behavioral theory, spatial economics, and computational geometry, as well as location theory and Geographic Information System (GIS). In particular, different customer choice rules indicative of behavioral complexity are mathematically incorporated and compared for capturing, spatial configuration, and computational difficulty. Also, strategically stable location pairs among firms, known as spatial equilibria, are explored in various market situations such as co-location, customer inertia, and different initial market share in a hypothetical environment. GIS and spatial optimization are used in a broadly coupled manner for implementation of the suggested models throughout the entire thesis. The geometric concepts and techniques supported by GIS functions are also utilized to enhance solution procedures. A hybrid approach combining exact and heuristic ways is also introduced for identifying spatial equilibria.
Results empirically confirm the significance of the choice rule in estimating the capture by new entries, the positive relationship between behavioral complexity in a model and computational effort, and the spatial distribution of new entries, which follows density of economy in general and stresses the spatial niches among existing systems. Regarding spatial equilibria, the equilibrium points are significantly influenced by the firm’s entrance type, as well as by customer loyalty and the market presence initially defined.