Graduation Year


Document Type




Degree Name

Master of Science (M.S.)

Degree Granting Department

Hospitality Management

Major Professor

Cihan Cobanoglu, Ph.D.

Committee Member

Katerina Berezina, Ph.D.

Committee Member

Serdar Ongan, Ph.D.


Back of house technologies, Front of house applications, Mobile POS, PCI DSS, Restaurant technology


The purpose of this study was to examine the utilization of Front of House and Back of House technology applications by U.S. restaurants across different types of restaurants along with their level of IT management style, and the importance of these technology applications to the restaurants' operations. This study used secondary data. The survey data collected from 500 randomly selected restaurant technology managers who are current subscribers of Hospitality Technology Magazine as of January 2013. Response rate was 27.2% and these sample groups represented 67,299 restaurant units. The data analysis was organized into 3 parts (descriptive, factor analysis and independent samples t-test). In the descriptive part of the data analysis, the information about respondents' job functions, company characteristics and companies' IT perspectives are evaluated. In the second part, factor analysis was used. Since the factor analysis is a data reduction technique, factor analysis is used to create correlated variable composites and to reduce variables for better interpretation. The third and final stage of the data analysis included testing hypotheses based on factor analysis outcomes by using an independent samples t-test. The main purpose of using an independent samples t-test is to determine whether position (IT versus Non-IT), types of restaurant (Chain versus Independent), business leadership and technology leadership (Innovator versus Follower) differ on the factor attributes.