Have you ever tried to apply a multiple levels of analysis in tourism setting? What kind of tips would you give to a novice in this field? I am planning to look at tourism organizations and investigate their climate for creativity and innovation. Preliminary idea is to use one of the creative climate measurements as a dependent variable and some process variables as IVs. Could you recommend me some readings with regard to the design and analysis within this field? I am thankful for any comments ;-)
Well the first thing I notice here is that 'multiple levels of analysis' is not necescarilly multilevel analysis. Specifically, multilevel analysis uses the hierarchy in nested data to see if the variance in the data is explained not just at an individual level, but at a larger level as well.
A famous example of this (and often used) is that off students across europe. Lets say you're interested in how well students are at school. The first level would be the students. Each students' test GPA score can be used to determine how well Europe's kids are really doing. However, usually there are differences not just between students but between classes (because some teachers are simply better than others), between schools (private versus public) and between countries (Sweden usually is much stronger than i.e. Spain on education). All these can be put into different levels in your analysis so that you can say much more precise how much variance is explained at each level (that is how much error in your estimation you can reduce).
In your case, your dependent variable is 'creative climate of the tourism sector'. Independent variables will be proces variables. This fits in a regression (that is if you're going to use survey's to gather data). However, if you're planning to take countries into account you can add a second level: countries. In that case you're first level consists of tourism organizations over all your data. On your second level you split them into countries/regions to try and explain more variance.
As you probably noted by now: multilevel analysis requires nested data and that data has to be 'tangible' nested into eachother: students in a class in a school. This does not work (and I can't stress this enough) for intangible nesting (i.e. attitudes towards national politics nested in attitude towards international politics).
So is multilevel analysis for your study? Depends on your data and your research question.
Take a look at http://www.bristol.ac.uk/cmm/learning/multilevel-models/what-why.html
Multi-level analysis is preferred where you have mixed studies approach o your research design.
Thank you all for the given comments!
Could I ask you Napoleon Ono Imaah for more information concerning system and network approaches? I have read the paper you mentioned and I find it very interesting but at the same time I feel like I need to learn a bit more on this issue.
Dear Sander Spoelstra, your detailed info on multiple level analysis was very helpful for me. Especially the link to the University of Bristol - priceless.
After some weeks of intensive work I am able to give you all a bit more thorough description of my problem. Nowadays, tourism destinations in Norway are facing the time when the government does not want to support and subsidize them any longer (at least not to the same extent as some years ago). Political issues have made all the private players in the market to reorient/redesign their business plans to be more independent, competitive and effcient. As a result companies within various geographical regions decided to combine their efforts and cooperate with each other (I guess small and medium firms need it in order to survive in the highly competitive environment). Two main forms of collaboration emerged from this process. Some prefer a network structure of interdependence, while the others agreed on something similar to hierarchical/organizational form. The thing that makes this problem even more complex, is the fact that the whole process of restructuring has not ended yet. But in the end, my task boils down to the investigation of companies' potential (climate for creativity and innovation) for delivering highly competitive products, services, etc.. From the perspective of organizational psychology, these turbulent times trigger complext and dynamic social processes that I would like to take a closer look at.
If you have any further comments, please share them with me! Thank you in advance!
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