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The purpose of this study was to make a mid- and long-term development plan on the business incubator center after interviewing five startups that currently being occupied in or already left the center and reviewing benchmark on business incubator centers in developed countries such as USA, Sweden, and Israel. For the interview, the three startups currently being occupied in the center and the two companies already left the center were participated. The main strengths of the center from all of these five companies were easy accessibility to the equipment and space and at the same time trustworthy from the outside vendors and/or government, etc. USA is a leading country who has long history for the startups but mostly the private companies/organizations/individuals have supported the startups in terms of funding or consulting. Also, there are countless local governments nationwide who provide funding, education, and/or space for the small businesses. Mainly based on the interview and the benchmarking, the mid- and long-term development plan for the business incubator center was made. All six themes such as consortium for investment or a local network plan were derived for the development plan which was described in this study.

This paper proposes a method of integrating ChatGPT with traditional chatbot systems to enhance conversational artificial intelligence(AI) and create more efficient conversational systems. Traditional chatbot systems are primarily based on classification models and are limited to intent classification and simple response generation. In contrast, ChatGPT is a state-of-the-art AI technology for natural language generation, which can generate more natural and fluent conversations. In this paper, we analyze the business service areas that can be integrated with ChatGPT and traditional chatbots, and present methods for conducting conversational scenarios through case studies of service types. Additionally, we suggest ways to integrate ChatGPT with traditional chatbot systems for intent recognition, conversation flow control, and response generation. We provide a practical implementation example of how to integrate ChatGPT with traditional chatbots, making it easier to understand and build integration methods and actively utilize ChatGPT with existing chatbots.

A single-learner model which integrates the user's positive and negative perceptions is proposed by augmenting counterfactual data to the interaction data between users and items, which are mainly used in collaborative filtering in this study. The proposed CausRec showed superior performance compared to the existing NCF model in terms of F1 value and AUC in experiments using three published datasets: MovieLens 100K, Amazon Gift Card, and Amazon Magazine. Compared to the existing NCF model, the F1 and AUC values of CausRec showed 1.2% and 2.6% performance improvement in MovieLens 100K data, and 2.2% and 10% improvement in Amazon Gift Card data, respectively. In particular, in experiments using Amazon Magazine data, F1 and AUC values were improved by 11.7% and 21.9%, respectively, showing a significant performance improvement effect. The performance of CausRec is improved because both positive and negative perceptions of the item were reflected in the recommendation at the same time. It is judged that the proposed method was able to improve the performance of the collaborative filtering because it can simultaneously alleviate the sparsity and imbalance problems of the interaction data.

The recent expansion of large cities for economic benefits has worsened cultural inequalities within urban areas, eroding unique cultural identities and social values and deepening mistrust between regions. To tackle this, the idea of creating cultural cities is gaining traction, involving urban branding and cultural elements to foster balanced local cultural development. Current research primarily concentrates on case analysis in cultural cities, lacking sufficient studies examining the interplay of factors through empirical analysis, This study investigated whether Cultural City Formation Factors, which are resources of a cultural city, have a positive effect on City Brand Equity, City Innovativeness, Brand Personality, and Behavior Intention. For this study, questionnaires were collected from 310 people who continuously experience culture and arts in Seoul, and empirical analysis was conducted on 292 copies of them. Consequently, a significant impact was observed among the factors influencing cultural city formation, city brand equity, city innovativeness, brand personality, and behavioral intention. Moreover, it was verified that city brand equity, city innovativeness, and brand personality positively contributed to mediating effects as well as sequential mediating effects. It is expected that the results of this study will be used to establish the foundation for effective urban management and the development of strategies for creating cultural cities.

On social media, companies create brand experiences while customers actively seek, consume, and generate brand-related content. Customer engagement plays a vital role in the marketing performance of social media-driven brands. This study explores the positive relationship between brand authenticity, aligning brand identity with image, and self-brand connection, aligning brand identity with consumers' self-concepts, on customer engagement and its subsequent impact on brand loyalty. The study surveyed 243 consumers engaged with brand-related social media content, validating hypotheses using structural equation modeling. Results confirmed that brand authenticity and self-brand connection positively affect customer engagement, which, in turn, boosts brand loyalty. These findings highlight the importance of companies enhancing brand authenticity and self-brand connection to drive customer engagement, with theoretical and practical implications provided.

This study conducted sentiment analysis on Hong Kong cinema from two distinct eras, pre-2000 and post-2000, examining audience preferences by comparing keywords from movie reviews. Before 2000, positive keywords like ‘actors,’ ‘performance,’ and ‘atmosphere’ revealed the importance of actors' popularity and their performances, while negative keywords such as ‘forced’ and ‘violence’ pointed out narrative issues. In contrast, post-2000 cinema emphasized keywords like ‘scale,’ ‘drama,’ and ‘Yang Yang,’ highlighting production scale and engaging narratives as key factors. Negative keywords included ‘story,’ ‘cheesy,’ ‘acting,’ and ‘budget,’ indicating challenges in storytelling and content quality. Word2Vec analysis further highlighted differences in acting quality and emotional engagement. Pre-2000 cinema focused on ‘elegance’ and ‘excellence’ in acting, while post-2000 cinema leaned towards ‘tediousness’ and ‘awkwardness.’ In summary, this research underscores the importance of actors, storytelling, and audience empathy in Hong Kong cinema's success. The industry has evolved, with a shift from actors to production quality. These findings have implications for the broader Chinese film industry, emphasizing the need for engaging narratives and quality acting to thrive in evolving cinematic landscapes.