关键词: 生态旅游者, 识别, 细分, 百花山

Abstract: Ecotourist study is one of the most important parts in ectourism research, which must be based on enough ecotourist samples. Using the foreign experience for reference, the paper proposed an integrated classification technique comprising K-Nearest Neighbor (KNN) and BackPropagation (BP) Networks to identify the ectourists. A questionnaire was designed to collect data through "internet" and "face to face" interviews during the National Day holiday in 2003 in Beijing Baihuashan Nature Reserve. 423 persons answered the questionnaires and 139 out of them were identified as ecotourists. The result of classification is proved to be effective by prediction validity test, content validity test, theory validity test and convergence validity test.In addition, the ecotourists were classified as hard ecotourists, frequent ecotourists and occasional ecotourists farther according to the times they traveled to nature-based destinations every year and their New Ecological Paradigm (NEP) grade which is used to evaluate the visitors' attitude to environment. Frequent ecotourists and occasional ecotourists both fall category of soft ecotourists, so the "hard-soft" classification system is founded, which will help propel ecotourist studies in China to develop towards the current international mainstream of the field. Finally, the paper clarified the concept of hard ecotourists, frequent ecotourists and experienced ecotourists ever used in others's research. Hard ecotourists and frequent ecotourists both belong to experienced ecotourists, but the hard ecotourists evidently have better environmental attitudes than the frequent ecotourists.

Key words: ecotourist, identification, segmentation, Baihuashan