Prof. Qiang Mai
School of Economic and Management, Harbin Institute of Technology
Research Area：Public Management
Speech Title:Natural Disaster Emergency Collaborative Response: A Network Analysis from the Perspective of the Establishment of the Deliberation and Coordination Agencies
Abstract：Effective coordination among emergency management functions was an important foundation for the country to respond to natural disasters. The establishment of a network-based organizational model among emergency management functions and the formation of differentiated collaborative networks have become a common phenomenon. This paper started from the top-level design of inter-facial coordination at the national level with the establishment of a deliberative coordination agency as a research perspective. A natural disaster emergency coordination network was construested by using social network analysis methods. By dividing the time stage and introducing“the relative network density-network cohesion" analysis framework，the structural characteristics of China's natural disaster emergency coordination network at different stages were investigated. The evolution model of the emergency coordination network was clarified. The network structure was considered to follow the“coordinated dense network一balanced loose network一core edge network" evolution path. At the same time，the characteristics of the horizontal synergies between agencies in response to natural disaster in China was analyzed. In the future，it should be worked from the direction of perfecting the coordination mechanism promoting the depth of coordination in order to promote the modernization of country's emergency management system and capabilities.
Experience: Engaged in research on system engineering, policy analysis and emergency management, and put forward the integration principle and complexity degradation principle of Megaproject. He presided over 5 national projects such as general projects of National Natural Science Foundation of China, and won 7 provincial and ministerial awards. Relevant achievements have been successfully applied in national major projects such as lunar exploration project, manned spaceflight and Hong Kong Zhuhai Macao Bridge, and policy suggestions have been adopted by many provincial and ministerial departments. He has published more than 30 papers in management world, Journal of management science and other journals.
Prof. Robin Qiu
The Pennsylvania State University/Dept. of Information Science, USA
Research Area：Data and Computational Sciences, Business Analytics, Healthcare Analytics, Smart Service Systems (Healthcare, City Mobility, Energy Efficiency, IoT, etc.), Big Data, Blockchain and Cyber Security Analytics, Information Systems and Integration, Supply Chain Management, and Industrial Systems and Analytics
Speech Title: Leveraging Rich Data and Machine Learning to Facilitate Policymaking on Public Health Interventions in Fighting to Contain the COVID-19 Pandemic
Abstract: This talk presents of a study that can be further enhanced and used to facilitate policymaking on the timing and restrictive levels of intervention measures, types and lifting or hardening, needed for a community, at the state, region, or country level as time goes. Rich data and machine learning work well in reducing discrepancies. Because of knowing all truth that is highly context-dependent, promisingly and confidently, we can win this pandemic “war” and be well prepared for the future.
Experience: Prof. Qiu have successfully secured over 40 funded research projects and had over 160 refereed publications, covering areas from Data and Computational Sciences, Business Analytics, Healthcare Analytics, Smart Service Systems (Healthcare, City Mobility, Energy Efficiency, IoT, etc.), Big Data, Blockchain and Cyber Security Analytics, Information Systems and Integration, Supply Chain Management, and Industrial Systems and Analytics. More importantly, he has been enjoying in collaborating with scholars and practitioners around the world. As a result, he has established collaborative networks within the academia and across the industry around the world.
Prof. Luning Liu
School of Economic and Management, Harbin Institute of Technology
Research Area：Big Data and E-government; Smart City; E-commerce; Information Systems
Speech Title: Effects of Voice-Based AI in Public Service: Evidence from a Natural Field Experiment
Abstract: Voice-based artificial intelligence (AI) systems have been deployed gradually to replace traditional interactive voice response (IVR) systems in public service call center, but little evidence exists on how the implementation of AI systems impacts user behavior, as well as AI systems’ effects on call center service performance. Leveraging the proprietary data from a natural field experiment, we examine how the introduction of voice-based AI affects call length, users’ demand for human service, and user complaints in a public service call center. We find that the implementation of the AI system significantly increases call length and decreases user complaints. Although the AI-based service system presumably reduces users’ efforts to transfer to human agents, we do not find any significant increase in users’ demand for human service. Furthermore, our results show interesting heterogeneity in the effectiveness of the AI-based service system. For simple service requests, the AI-based service system reduces user complaints for both experienced and inexperienced users. For relatively complex quests, users learn from prior experience of interacting with the AI system, and this learning effect leads to fewer complaints. Moreover, the AI-based system exerts a significantly larger effect on reducing user complaints for older and female users, as well as for users who are experienced in using the IVR system. Finally, in examining details in user-AI conversations, we find that speech-recognition failures in user-AI interactions result in an increase in users’ demand for human service and user complaints.
Experience: Luning Liu is a Professor and Department Chair in the Department of Public Administration in the School of Management at Harbin Institute of Technology (HIT), China. He received his B.S., M.S. and PH.D. in Information Systems from HIT. His research primarily focuses on big data analytics, e-government, and e-commerce. His work has been published in European Journal of Information Systems, Information and Management, Government Information Quarterly, International Journal of Information Management, Information Systems Frontiers, Computers in Human Behavior, Information Technology for Development, Industrial Management & Data Systems, Telecommunications Policy, and conferences including ICIS, HICSS, ECIS, AMCIS, and PACIS.