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In the third chapter we further enhance the literature on the location choices, this time incorporating strategic interactions among establishments. We shed light on strategic interactions, fundamental in establishments’ location choices, yet largely unheeded in the empirical literature. If establishments acted in isolation, it would be a relatively simple task to adapt existing discrete-choice models. Yet, being non-strategic means that an establishment ignores other players’ decisions. Less is known about how to correctly adapt location choice models to study establishments’ discrete choices when they are interrelated. In very sparse empirical applications, when locational choice models are developed for several activity sectors, each of the model is typically run independently.  What makes these discrete choices particularly interesting and challenging to analyze is that decisions of a particular establishment are interrelated with choices of the others because an establishment accounts for the actions of other agents when making its own decisions (Draganska et al., 2008). These thorny problems posed by the interdependence of decisions generally cannot be assumed away, without altering the realism of the model of establishment decision making (Berry and Reiss, 2007). The conventional approaches to location selection, i.e., traditional theory and methods, fail (Thill, 1997) by providing only a set of systematic steps for problem-solving without considering strategic interactions between the establishments in the market.Being non-strategic would mean that an establishment ignores other players’ decisions (Toivanen and Waterson, 2005).  A appropriately specified model of simultaneous entry or location decisions needs to recognize this interdependence of profits (Berry and Reiss, 2007).  There is a need for more realistic studies of complex establishment’s decision-making processes. Even though the computational burden imposed by these models considering strategic interactions is relatively high, it seems that the costs imposed are more than offset by the benefits that accumulate/accrue (Draganska et al., 2008). 
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Literature   Chapter I introduces the reader to the location choice models. The list of the key factors that potentially influence the locational decisions has been created baseed based  on the research of Maoh (2005), Strotmann (2007), Liviano-Solis and Arauzo-Carod (2011), Rocha (2008), Maoh and Kanaroglou (2005, 2007), Bondomi and Greenbaum (2007), Bodenmann (2011), Duvereux et al. (2007), Neumark and Kolko (2010), De Bok (2004), Bodenmann and Axhausen (2012, 2010), and the review of Arauzo-Carod et al. (2010). Chapter I provides also a discussion on the first attempts to incorporate spatial effects into location choice models starting with Bhat and Guo (2004) on modeling spatial dependence in residential locations using a mixed logit. Sener et al. (2011) propose the generalized spatially correlated logit and Miyamoto et al. (2004) the mixed logit with the error autocorrelation and an autocorrelated deterministic component of utility to model the residential behavior. Garrido and Mahmassani (2000) discusses a multinomial probit with spatially and temporally correlated error structure to analyze and forecast the distribution of freight flows. Nguyen et al. (2012) discusses a tree-stage firm relocation model wherein spatial correlation between zones has been implemented in the error term and spatial interactions among firms in the deterministic part. Klier and McMillen (2008) provide a description of the generalized method of moments spatial logit to model the clustering of the auto supplier establishments.