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.
This thesis proposes a departmental and functional integration of various activities to arrive at an integrated revenue management approach that is viewed as the necessary reaction to changing market environment conditions.
Furthermore, revenue management and pricing programs have commonly been praised to have the potential to increase revenues by 3 to 8 % which can in turn result in 50 to 100 % profit improvements (Skugge, 2007).
As a result, companies have to optimize their revenue management procedures and processes within the company, and it is proposed that this can be achieved by taking a holistic view and integrating various disciplines to come to total profit optimization.
According to Skugge (2007), future improvements of profitability for companies will be by filling gaps and optimizing current revenue management programs rather than investing in new more elaborate computer systems.
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.