Degree Type


Date of Award


Degree Name

Doctor of Philosophy


Apparel, Events and Hospitality Management

First Advisor

Tianshu Zheng


Mergers and acquisitions (M&A) activity has been growing in the restaurant industry over the past three decades. Recognizing that the importance of M&A has increased as a result of this growth, this study used simulation technique to investigate whether restaurant M&A deals occur in waves. Results indicated that the restaurant industry had three M&A waves between 1981 and 2010.

After confirming the existence of restaurant M&A waves, this study then investigated the macroeconomic determinants of the restaurant waves employing two econometric methods: a distributed lag (DL) model and error correction model (ECM). The results of DL estimation showed that cost of debt negatively affected deal frequency in the long term and inflation had a negative lagged effect on deal frequency. On the other hand, current activity and economic outlook had a significantly positive effect on both deal frequency and deal value. The effect of current activity was lagged while that of economic outlook was lagged and long-term. The results of ECM estimation showed that cost of debt had a negative effect on deal frequency in the short and long term while economic outlook had a significantly positive effect on deal frequency in the long term.

This study contributes to the restaurant industry and its scholarship in several ways. Theoretically, this study extends the restaurant literature by proving the existence of restaurant M&A waves and exploring the relationship between macroeconomic conditions and the restaurant waves. It also examines the applicability of the main theoretical frameworks for general M&A waves in all industries to industry-level waves. Practically, this study can help restaurant firms increase synergistic gains from their M&A deals by identifying important economic conditions that restaurant firms should take into account when considering M&A deals. Moreover, restaurant firms can use such conditions to predict an appropriate time for their M&A deals.


Copyright Owner

Jewoo Kim



File Format


File Size

134 pages