This study carried out a scenario experiment in Guangxi, China, and used a questionnaire to obtain the research data of the subjects to explore the service recovery effect of local online travel agencies (OTAs) from the perspective of consumer psychology. The empirical results show that consumer confusion will significantly worsen negative word-of-mouth, and negative word-of-mouth will reduce their repurchase intention. In the above empirical impact relationship research, it shows that negative word-of-mouth and consumer forgiveness play a mediating effect and a moderating effect respectively. Because this study is conducive to responding to and solving the new scenario and problems in the practice of OTA services. It will help to improve the risk resistance of OTA enterprises by providing effective service recovery strategies for these enterprises.
China is a multi-ethnic nation with rich and diverse culture traditions. State-wide standardized textbooks, however, take little into account the local ethnic minority cultures; thus limiting the opportunities of preserving the unique ethnic traditions through education. On the other hand, property of information technology requires information technology teaching to combine knowledge with local culture. Curriculum resource can bridge the gap between textbook knowledge and ethnic minority cultures. In this paper, we discuss the relation between ethnic minority cultures and education of information technology in China. In particular, we propose ideas on development of effective curriculum resources website based on ethnic minority cultures for use by teachers, and on reform of classroom teaching in order to incorporate ethnic minority cultures into education of information technology. Index Terms-ethnic minority cultures, information technology teaching, curriculum resource
Online big data provides large amounts of decision information to decision makers, but supporting and opposing information are present simultaneously. Dual hesitant fuzzy sets (DHFSs) are useful models for exactly expressing the membership degree of both supporting and opposing information in decision making. However, the application of DHFSs requires an improved distance measure. This paper aims to improve distance measure models for DHFSs and apply the new distance models to generate a technique for order preference by similarity to an ideal solution (TOPSIS) method for multiple attribute decision making (MADM).
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