The intersection between digital technologies and tourism emerges as a prominent area of research within the tourism industry. This is primarily driven by the immense complexity of digital tourism itself as a multifaceted social, economic, and cultural phenomenon. This paper reveals the future implications of tourism in the context of digital intelligence. To gain insights into the latest applications of digital tourism, this work reviews 278 studies spanning from 2012 to 2024. A systematic literature analysis method is proposed to identify the research hotspots and trends. Through value co-creation theory and Schumpeter’s innovation theory, five key trajectories are suggested, as follows: in-depth application of digital technologies in tourism, spawning new scenarios, new forms and new modes of digital tourism, and deep integration of digital economy and tourism real economy. This state-of-the-art review will help to reflect the efforts towards promoting the smart development of digital technologies in tourism.

With the development of e-commerce, an increasing number of online reviews can serve as a promising data source for enterprises to improve online products. This paper proposes a method for modelling consumer satisfaction based on online reviews using the improved Kano model from the perspective of risk attitude and aspiration. Firstly, the attributes concerned by consumers are extracted from online reviews, and sentiment analysis of the extracted attributes is carried out using Standford CoreNLP. Secondly, to identify the types of product attributes, an improved Kano model is proposed based on the effects of product attributes on consumer total utility. On this basis, different attribute types are illustrated from the perspective of risk attitude. Then, the consumer aspirations are mined based on the risk attitudes of different attributes and the attribute impact on consumer satisfaction. According to the risk attitudes and aspirations of different attributes, the quantified satisfaction functions are constructed to provide more objective and accurate improvement suggestions. Finally, the proposed method is applied to the hotel service improvement to illustrate the effectiveness.