Why Do Consumers Review Doctors Online? Topic Modeling Analysis of Positive and Negative Reviews on an Online Health Community in China

Consumers often learn from others through a social learning process (e.g. electronic word of mouth) before making decisions. From the e-business perspective, online reviews have changed how people select products and services, and no doubt it is the same in the e-health sector. In this study, we examine online reviews of patients and health consumers for their doctors in an online health consultation platform in China. We combine machine learning and qualitative techniques to derive the themes of online reviews and the factors leading to positive and negative reviews. Our analysis demonstrates that service levels of hospitals, doctors’ communication skills and their professional skills influence the sentiment of reviews. Our findings offer important insights into theories and practice for studying online reviews in the healthcare context

Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature

The booming adoption of Artificial Intelligence (AI) likewise poses benefits and challenges. In this paper, we particularly focus on the bright side of AI and its promising potential to face our society’s grand challenges. Given this potential, different studies have already conducted valuable work by conceptualizing specific facets of AI and sustainability, including reviews on AI and Information Systems (IS) research or AI and business values. Nonetheless, there is still little holistic knowledge at the intersection of IS, AI, and sustainability. This is problematic because the IS discipline, with its socio-technical nature, has the ability to integrate perspectives beyond the currently dominant technological one as well as can advance both theory and the development of purposeful artifacts. To bridge this gap, we disclose how IS research currently makes use of AI to boost sustainable development. Based on a systematically collected corpus of 95 articles, we examine sustainability goals, data inputs, technologies and algorithms, and evaluation approaches that coin the current state of the art within the IS discipline. This comprehensive overview enables us to make more informed investments (e.g., policy and practice) as well as to discuss blind spots and possible directions for future research