Conference Agenda

Over the past decade, the convergence of technology and entertainment has opened new avenues for improving the experiences of film enthusiasts and tourists alike. Focusing on merging reality and reel to enhance memorable tourist experiences, this paper introduces a comprehensive design model for developing smart film tourism applications. A qualitative approach was employed to explore the expectations and potential issues faced by film tourists throughout their journeys. Subsequently, insights are generated and translated into four key design aspects and corresponding features, integrating augmented reality technology. The convergence of elements within the model aims to facilitate a deeper connection between tourists and film-based destinations, fostering increased interactivity and immersion. Furthermore, a utility test was conducted on a prototype application, and the positive results validate the model’s potential for designing memorable film tourism experiences, offering a reference path for experience design in the tourism industry.

This study explores the design challenges of connecting passive NFC wearables such as fobs, rings, and bracelets, to online services such as payment and access. Through field studies, co-design workshops, and auto-ethnographic design work, we investigate how physical action and online media could be coupled, allowing for more considerate onboarding experiences. Our main contribution is four de-sign concepts specific to this domain: using media to link experience to new concepts, supporting physical practice, giving feedback on physical success, and providing interactive function through physical form. In sum, the work highlights media content as a fundamental element in the design of passive tangibles, to support embodied understanding of the manipulations involved.

Electronic commerce has significantly transformed the modern economy, efficiently connecting production and consumption while altering people's consumption patterns. While artificial intelligence has found extensive application in creative production, its application in creating innovative content for e-commerce is still in its early stages. The progressively refined e-commerce industry demands a significant amount of creative content to attract consumers, thus increasing the demand for designers and further elevating the operational costs for businesses. This paper focuses on creating creative content for products in an e-commerce context. It proposes a design paradigm integrating speech recognition and image generation technology, supplementing existing design theories and methods. Additionally, systematic design and empirical research are conducted in e-commerce, effectively addressing real-world issues such as a shortage of designers and a lack of creativity in the e-commerce industry.

Artificial intelligence (AI) is widely employed to empower creative industries. Many enterprises have adopted AI to design creative products (CPs). This study investigates the determinants of purchase behavior and consumer attitudes towards AI-design CPs. Two studies were conducted. Study 1, with 764 participants, aims to determine if consumers have a positive view of AI design. Results indicate recognition of AI's creative abilities, with the designer's identity significantly affecting creativity evaluation. Study 2, based on 328 surveys, explores consumer evaluations of AI-designed products, purchase intentions, and attitudes. The result indicates that the impact of social relationship value on consumer purchase intention is the highest. These findings suggest practitioners should highlight the advanced nature of AI-generated design, enhance the cultural significance of the product, and emphasize its social value. Addressing consumer aesthetic preferences and leveraging technology, such as AI-customized services, is crucial for enhancing emotional value and the overall consumer experience.

A critical goal when designing commercial services is the discovery of customer insights. In the digital transformation era, customer discussions of brands on social media have become indispensable for brands to explore service insights. The use of data-driven approaches for exploring service insights from the vast range of customer online data merits research. This study proposes a data-driven user analysis process to help brands explore service insights from massive amounts of data using data-mining techniques based on the social media platform Instagram. Using the proposed data-driven user analysis process, service designers can gain brand service insights from a large amount of customer social media data, thereby providing a reference for data-driven service design in terms of methodology and case practices.