中文摘要：

除交易行为外,顾客的非交易性行为（即契合行为）也对企业有重要影响。顾客的非交易性行为被概括为＂顾客契合行为＂（customer engagement behavior）,作为一个较新的概念成为营销学界研究的热点,在营销实践中也成为企业关注的焦点,不少企业已经开始关注顾客契合行为,并且践行顾客契合营销策略。文章采用实证研究方法,探讨旅游虚拟社区成员的＂感知-认同-契合行为＂模式。数据分析结果表明,顾客感知的功能性价值、社交性价值和娱乐性价值都对成员的社区认同有显著的正向影响,且在三类价值中,社交性价值对社区认同的影响最大;社区认同对成员的社区参与、知识共享和口碑推荐都有显著的正向影响;社区参与对知识共享和口碑推荐有显著的正向影响,知识共享也正向影响口碑推荐。

英文摘要：

The engagement concept is not new to the arena of commercial activities and business relationships; however, there is little research on the concept until recent years. With the rapid development of the network society, customers can easily interact with companies, or with each other, through social networks and social media. Consequently, the non-transactional behavior of customers is increasingly important, and companies are focusing on this aspect. The customer engagement concept is now popular in the marketing field, with a corresponding output of relevant literature; however, the concept is not yet fully explored in academic and research literature. The emergence of the tourism virtual community means that consumers can rapidly （indeed, instantly） access tourist information while they are making their travel decisions. The virtual platform has revolutionized the access to tourist information, tourists can now get the latest tourism information anytime and anywhere. Moreover, they can communication with others anytime and anywhere. Such changes meant that the tourism enterprises have to transform their marketing modes, to adapt to the changes and to exploit the opporttmities that they offer. Based on a literature review, we propose a ＂perception-identity-engagement＂ behavior model, and empirically test the model in the tourism virtual community. We test the relationships among the three variables through an empirical study. The results of this study help to enrich the academic study of customer engagement. We propose some practical guidelines for companies to encourage customer engagement, and to improve customer loyalty. We measured the research model constructs with self- reported, multiple-item scales. All of the measures were adapted from previous studies. The items were measured using seven-point scales. We use Structural Equation Model （SEM） analysis, and a second- order factor analysis, to process the data. The results indicate that the customer＇s perceived value affects the community