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The retail industry is considered to be a very competitive industry in the United States since there are so many players in the almost saturated retail markets that provide similar products and services at similar price levels to customers. Market selection has been identified as an important strategy to differentiate a retailer in this competitive market. Therefore in this thesis, we describe a conceptual framework to evaluate retailers investment opportunities in dynamic, competitive retail markets. The objective is to describe a conceptual investment analysis framework to address the strategic aspects of a retailer s investment opportunity as well as the dynamic uncertainty of a retail market in a single framework. This conceptual framework outlines a strategic view towards retail stores as flexible assets of a retail enterprise. This conceptual framework is general and can be adjusted and applied to investments options in other services. In addition, we develop an integrated investment analysis approach based on dynamic programming to explore retailers investment behaviors in dynamic markets. The objective is to determine retailers optimal investment thresholds in noncompetitive and competitive markets. We consider two retailers to illustrate our approach and use a simple game theory treatment to address competition in retail markets. We use our integrated investment analysis model based on a real options methodology to evaluate the apparent tendency for the small discount retailer invests earlier in a new developing market due to the competition effect from the large discount retailer. This early entry gives the small retail a first-mover advantage and delays the big retailer s entry into the competitive market. In addition, we conduct sensitivity analysis to characterize how significantly the values of our model parameters impact the retailers investment decisions. We also develop an integrated investment analysis approach based on contingent claims analysis to explore retailers investment behaviors in dynamic markets. The objective is to determine retailers optimal investment thresholds in noncompetitive and competitive markets. The equivalent risk neutral evaluation approach is presented in this thesis as an extended version of the contingent claims analysis approach, which facilitates the market-oriented valuation of the retailer s investment option in dynamic markets. Sensitivity analysis is conducted to study how retailers optimal investment thresholds change as the values of parameters in this equivalent risk neutral evaluation approach change. The relationship between the dynamic programming and the equivalent risk neutral evaluation approach is also summarized in this thesis to identify the similarities and the differences between these two investment analysis approaches. One of the most important objectives of this comparison is to determine in what market conditions the choice of investment analysis approach is critical and dramatically changes the retailer s optimal investment threshold. Finally, we empirically examine an important aspect of our theoretical work that the big retailer invests and opens a store relatively later in markets with a small retailer compared to markets without a small retailer. In addition, the big retailer opens a store at relatively higher retail market potential in markets with a small retailer compared to markets without a small retailer. In this thesis, we discuss some empirical evidence to support these theoretical results. We chose Wal-Mart and Dollar General as the big and small retailers, respectively, in our empirical study. Our empirical results do not validate the theory and just provide supporting evidence for our theoretical works.