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With the rise of cultural and creative industries, cultural creativity has gradually become an important factor to promote the value of design in the future, and it is also a trend to integrate "cultural elements" into the design of products. At present, the cultural and creative industries in Western countries and Taiwan are the mainstay of their economic development. We should actively absorb their successful experiences and, with the support of national policies, carry out effective and lasting development of them, as well as continuously improve the quality of cultural and creative products. In today's steady economic development, the emotionalization of cultural and creative consumption has gradually formed a new consumption trend. When cultural and creative consumers buy stationery, they will inevitably have three situations: purchasing instinct, purchasing behavior, and reflection. Therefore, this paper adopts the method based on machine learning to conduct in-depth research on the users of cultural and creative products of "Forbidden Day and Night Set Gift Box." Through the research on the cultural and creative consumption intention of "Forbidden Day and Night Set Gift Box," it can effectively promote the development of domestic cultural and creative enterprises, and then promote the customer satisfaction of cultural and creative enterprises. This paper makes a detailed analysis of it from the perspectives of data processing, feature engineering, classification prediction models, and future development directions. By studying the cultural and creative behavior of users, a deep learning model based on neural network is established. The feature extraction, feature preprocessing, feature selection, and asymmetric data collection in the process of data processing are discussed in depth. In order to further improve the prediction accuracy and conduct more in-depth research, this paper establishes a deep learning prediction model based on depth. This model is experimentally validated and it can be observed that the model is 10% more efficient than the traditional model, so the model can learn data better from the user's behavior in several aspects, and the proposed and practice of this model has good practical significance. [ABSTRACT FROM AUTHOR]

Following the outbreak of the COVID-19 pandemic, some hotels have introduced a new service model called contactless service. This paper unpacks this new hospitality landscape through a random sample of 510 valid responses collected at a smart hotel in Taiwan in June 2020 and discusses the emergent insights through Multiple Linear Regression (MLR). The findings revealed that (1) Sense experience (SE), feel experience (FE), and relate experience (RE) were all positively impacting information sharing (IS); (2) Sense experience (SE) and feel experience (FE) positively affected satisfaction (CS). The positive adjustment of the relationship between the sense experience (SE) and the related experience (RE) for information sharing (IS) is regulated by the outbreak event disruption (ED). Intelligence operation (IO) is a significant mediating effect among five-sense experiences, customer satisfaction, and information sharing. This paper analyzes empirical data and provides insights that illuminate the nuances of customer experiences with contactless hospitality service. [ABSTRACT FROM AUTHOR]

The concept of the smart city has been created in response to the increasing numbers of people living in cities. Just as the development of technology has evolved rapidly, smart life has also emerged. The goal of the smart city is one day to enable all affairs of daily life to be completed with the single touch of a finger through cutting-edge technology. New and innovative information must be applied effectively to the industry. With the industrial revolution, propelled by the Internet of Things (IoT), big data and the cloud platform have birthed the “smart city,” integrating the IoT and the cloud through mobile devices and applying technology to fields like logistics, finance, healthcare, recreation, surveillance, and traffic transportation, thus providing people with greater well-being and convenience. Following the era of the big data knowledge economy, the IoT has become an important pillar of national economic development. The IoT is expected to provide substantial support for continued and sustainable development of the smart city. Therefore, effective use of the IoT has become an important topic in smart city development. The purpose of this paper is to build a conceptual framework of service innovation, relying on the smart city case of Taiwan. Based on a literature review, in-depth interviews, and case interviews, the proposed conceptual framework of IoT is rooted in the market, policy, and technical aspects. It incorporates eight steps: composition of the project team, service idea generation, service idea screening, development concept selection, design and development, service testing, commercialization, and service quality, to generate new service value and thereby create customer satisfaction. In fact, the IoT is designed to support the smart city vision; thus, this paper describes the various innovation modes of the smart city. Furthermore, the paper presents and discusses the technical solutions and best-practice guidelines adopted in the Taiwan Smart City project. Finally, it discusses the meaning and future research direction of the smart city through the use of the IoT. With wave after wave of digital development civilizing the city's evolution and with the phenomenon of Internet access through mobile phones for each person, the smart city of human factors is clearly coming. [ABSTRACT FROM AUTHOR]