Matching Items (2)
Description
Artificial intelligence (AI) and machine learning (ML) is rapidly evolving with enormous impact on a wide range of individual and societal matters including in health care, now and in the future. The goal of this research project is to assess the current knowledge level of AI and ML in health care among healthcare professionals and the lay public. Results from this research will identify knowledge gaps and educational opportunities to improve future use and applications of AI and ML in health care.
ContributorsShen, Maria (Author) / Martin, Thomas (Thesis director) / Wheatley-Guy, Courtney (Committee member) / Barrett, The Honors College (Contributor) / College of Health Solutions (Contributor)
Created2022-05
Description
Financing lease has bloomed as a new financing tool in China for the last several years. In this thesis I investigate the factors that influence China’s automobile financial leasing decisions by both lessors and lessees through market surveys. Based on Probit regression analysis of the data collected from 250 companies and 300 individuals, I find that a firm is more likely to use automobile financial leasing when its corporate tax rate is lower, growth potential is more stabilized, and profit is higher. It is also more likely to happen when a firm's long-term debt ratio and its degree of internationalization are higher. At the individual level, I find that the likelihood of individuals’ leasing decision is influenced by their risk preference, income level, and car price. Individuals’ gender, age and education level show no effect.
Using the analytic hierarchy process (AHP) analysis, I further find that financing costs, service value-added, and products diversity are the three most important competitive factors for the auto financial leasing service providers. This is the case for both the corporate and individual customers in the sample. By contrast, the factors of sales channel and government relationship are found to be much less important. Finally, through an in-depth case study of the leasing company Shanghai Auto Financial Leasing, I find that the key factors determining the customers’ credit default risk are interest rate and automobile type. I also investigate factors that influence business risk during the automobile procurement stage, at the selling stage, and toward the disposition stage. The managerial implications of the above results are discussed throughout the thesis.
Using the analytic hierarchy process (AHP) analysis, I further find that financing costs, service value-added, and products diversity are the three most important competitive factors for the auto financial leasing service providers. This is the case for both the corporate and individual customers in the sample. By contrast, the factors of sales channel and government relationship are found to be much less important. Finally, through an in-depth case study of the leasing company Shanghai Auto Financial Leasing, I find that the key factors determining the customers’ credit default risk are interest rate and automobile type. I also investigate factors that influence business risk during the automobile procurement stage, at the selling stage, and toward the disposition stage. The managerial implications of the above results are discussed throughout the thesis.
ContributorsLin, Zhen, Ph.D (Author) / Zhang, Anming (Thesis advisor) / Pei, Ker-Wei (Thesis advisor) / Chen, Hong (Committee member) / Arizona State University (Publisher)
Created2015