Exploring the Multiple Drivers and Operational Innovations of Pet Exhibition Services: Evidence from fsQCA and Interviews

Author : Tsai-Yu Lai, Li-Shiue Gau

Abstract :This study contributes to employ quantitative analysis and qualitative interviews to explore the evolution of smart technology and optimize smart products at pet exhibitions. The quantitative analysis focuses on investigating sufficient conditions for pet owners attending pet exhibitions and the application of AI smart products. The qualitative interviews explores operational innovations in pet exhibitions through business model analysis. The research uses a questionnaire survey method, collecting quantitative data from pet owners who have participated in pet exhibitions via Google Forms. Additionally, interviews has be conducted with key stakeholders, including pet exhibition organizers, exhibitors, and consumers who have attended these exhibitions, to gather qualitative data. Multivariate analysis emphasizes descriptive statistical analysis and fsQCA. Results of fsQCA represent that there are 14 and 13 sufficient conditions for both pet owners attending pet exhibitions and the application of AI smart products, respectively. Furthermore, results of qualitative analysis identify business model innovations in pet exhibitions from perspectives including enterprise, value, customer, and financial dimensions.

Keywords :AI Smart Technology, Pet Exhibitions, fsQCA.

Conference Name :International Conference on Business, Economics, Marketing and Management (ICBEMM-24)

Conference Place London, UK

Conference Date 19th Nov 2024