Gamification, an innovative tool for interacting with consumers that can be seen as a new trend in marketing, could enhance customer behavior, such as greater loyalty. This paper investigates the relationship between gamification, attitude, and customer behavioral intention. Using the Starbucks branded app as the tool, this study aims to identify the influencing factors of the app from a gamification perspective (achievement, challenge, rewards) on customer engagement, perceived playfulness, attitude, and behavior. The Technology Acceptance Model and Mechanics Dynamics Emotions were employed, using perceived playfulness as an intrinsic motivation of the Technology Acceptance Model. The subjects of this study were 581 customers in Taiwan who have used the Starbucks branded app. The primary data were gathered to test the hypothesis and propose a model. The findings showed that game elements have a positive influence on customer engagement and perceived playfulness. Gamification positively enhances customer engagement on the Starbucks branded app and creates joyful emotion and sustainable consumption. Thus, the game element positively affects subsequent behaviors, such as attitude and behavioral intention.

Posting articles on the social platform is the favorite activity of young people. With the potential of digital movie and tv series industry, developing an automatic movie recommendation engine becomes a popular issue. Traditionally movie recommendation is based on structured information like director, players, rough class, etc. Recently, there are more and more researches trying to make a recommendation based on context information like music recommendation based on lyrics with the word vector representation. However, in the long text scenario, the recommendation based on all context vector makes the inference very imprecise.In this paper, we propose effective features types, relationships, and scenarios, to extract important information then improve the recommendation. Furthermore, comparing different pre-training model, we try to maximize the effectiveness of semantic understanding and make the recommendation be able to reflect meticulous perception on the relationship between social media articles and movie plot.

It is convenient to have advances in science and technology so that people obtain information without going out. We explore the intention of the use of housing apps based on the unified theory of acceptance and the use of technology. A total of 365 questionnaires were collected with 8 incomplete answers discarded. The snowball sampling method was used for confirmatory factor analysis and SEM structural equation model analysis. The research results show the following. (1) Housing app users can quickly obtain knowledge and information about houses, and it is more convenient. (2) Both effort expectancy and social influence have a direct and positive effect on behavior intention when using the housing app. (3) There is no significant impact after adding moderator variables of gender, age, and income in Unified Theory of Acceptance and Use of Technology, (UTAUT). It is convenient and helpful to use the housing app. Therefore, the use of the housing app will be an indispensable trend.