The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information. Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content. This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. Terms &

No abstract

The lodging industry is very competitive and hotels have to search for new methods to attract clients. Some firms are applying social and environmentally friendly behaviour beyond what is required by law. The tourism industry is one of the most important sectors in the world's economy and the social and environmental responsibility is vital for this industry. This paper is an empirical work showing the motivation that hotel stakeholders located in islands have to adopt corporate social responsibility (CSR) strategies. To prove the motivation, an index containing seven important social and environmental factors was created using three different approaches. The results show significant influence in some of the variables while no positive relations were found in other variables.

No abstract

Protected areas play an important role in biodiversity conservation and tourism. Significant efforts have been made to increase the amount of protected lands. A problem of increasing the amount of public protected areas is that governments and other institutions face difficulties in providing the necessary resources for effective management. Accordingly, managers must be as efficient as possible but the lack of comparative methods makes the evaluation of efficiency difficult. Using Data Envelopment Analysis, a non-stochastic and non-parametric approach, information from 29 protected areas in 5 countries was analyzed to compare management efficiency amongst them. The first result found is the level of management efficiency that each park has in comparison with the others parks. The other important result is a prediction of the changes in the outputs if there is a hypothetical budget change. These results allow the generation of information for decision making.