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A multivariate regression is necessary to account for additional control variables that may have an impact on the profitability than Revenue Management Integration alone. Regression analysis is commonly used to determine the relationship between a dependent and one or many predicting variables (Burrill, 1992). A cross-sectional design is chosen to determine the relationship between financial performance and Revenue Management Integration (RMI) of hotel chains.
The statistical research method that is used to assess the relationship between financial performance and Revenue Management Integration (RMI) is the multivariate regression analysis.
However, since the interviews took place with revenue managers in hotels, which are certainly available by phone and can be identified as the correct interviewee by their organizational title, the disadvantages may for the most part be neglected.
Customer Segmentation and Differential Pricing 5.4. Revenue Management Integration (RMI) in hotels is positively related to financial performance. Revenue Management Integration stands in positive relation to Revenue per Available Room (Rev PAR). Revenue Management Integration stands in positive relation to Return on Equity (ROE). Revenue Management Integration stands in positive relation to Operating Profit Margin (OPM).
The following working hypotheses are derived for the thesis: 1.
On the other hand disadvantages of telephone interviews are that persons without telephone are not able to participate, the interviewer cannot observe and is not sure to interview the right person, and also no visual aids can be used (Bryman & Bell, 2003).
As Owens (2002) found, telephone interviews have the advantages of having relatively low costs, short data collection period, good response rates, and less influence of interviewer on responses.
Impact of the Modern Tourism Value Net on Tourism Industry Structure 2.1. Industry Analysis along the Five Competitive Forces 3. Integrated Revenue Management as a Competitive Advantage 3.2. In cross-sectional design it is crucial to have a standardized procedure based on quantitative data to measure the variation between cases, which also results in a study of high replicability (Bryman & Bell, 2003).
According to Bryman and Bell (2003), cross-sectional design is suited when the research is looking for variation between many cases and for that purpose, from each case observations on several variables are made. George (2004) emphasized that the cross-sectional study design takes the observations at a single point in time, thus change in observations cannot be measured.
According to Bryman and Bell (2003), structured interviews are standardized whereby each interviewee receives the same questions in the same order, and the same way.
The questionnaire derived from the literature review was filled out by conducting structured telephone interviews, which were identified as being most suited for the cross- sectional research design used.