This study focuses on cyclical behavior in the restaurant industry, types of strategy choices made by the casual dining industry, and the use of the industry cycle to make a timing decision of strategy choice. The main idea of this study is that the phases of the industry cycle differently support a firm's strategy choice, so the use of the cycle allows firms to find the right time for a particular strategy choice. This is done by developing and understanding of the restaurant industry cycle and determining the phase of the cycle that possesses different opportunities and threats. This is followed by identifying strategy choices adopted by casual dining firms through a content analysis. Next, a casual dining firm's responses to phases of the industry cycle are investigated. Using an individual firm's data regarding performance and the emphasis of strategy choice over the industry cycle, this study undertakes an investigation into whether the effect of a strategy choice adopted by a firm varies according to the phase of the restaurant industry cycle. The results of the study revealed that the movements of the restaurant industry cycle have unique timing, duration, and amplitude, and that casual dining firms adopt thirteen distinct types of strategy choices. Firms change strategy choices to respond to change in the industry cycle phase. Summarizing these findings, the study found that the effects of strategy choices on firm performance differed according to the cyclical change of the industry environment so adjusting strategy choices over the industry cycle is critical to outperform competitors This study aims at providing a relevant framework for using the industry cycle as a tool for well-timed strategy choices in the casual theme restaurant industry. In practice, by utilizing the industry cycle, executives would be better able to assess possible success or failure of a particular strategy at different phase of the industry cycle, and to determine the timing relevance as it relates to new investments or asset allocation. Managing the industry cycle allows firms to have an appropriate strategic portfolio to maximize their outcomes and sustain competitive advantage over long periods of time. / Ph. D.

In markets with cyclical fluctuations, firms may have different dynamic decision rules facing upturns and downturns of industry cycles. This paper extends the dynamic factor demand model to consider industry cycles. Because investment behavior could be endogenous uncertainty involved on industry dynamics, the current industry dynamic models with state-of-the-art would not appropriately interpret industry dynamics. In order to solve the uncertain problem, we utilize the idea of transfer probability in Markov switching model to catch the industry cyclical behavior. Explicitly incorporating the Markov regime switching mechanism based on Nelson and Kim (2000), this paper measures the firm¡¦s dynamic adjustments when facing upturns and downturns of industry cycles. The empirical work is based on firm level data of Taiwan high-technology industries. The empirical results show that the expansionary strategy in labor and capital usage may not have positive impacts on output when considering uncertainty that may be casued by business cycles. To have correct prediction in cyclical fluctuation becomes important task for high-technology firms. However, the positive contribution of exogenous technology to output growth is so significant. This proves why every industry tries to impel technology in recent years. The industry dynamic model integrated with cyclical fluctuation and demand uncertainty allows us to examine how sharp changes in financial factors might affect investment behavior, technological nature and adjustment effects for industries in facing demand and investment shocks.