2019 INFORMS Conference on Service Science

Smart Service Systems, Operations Management, and Analytics

June 27th-29th, 2019

Nanjing, Jiangsu, China

Sponsored By: INFORMS Service Science Hosted By：Nanjing University of Aeronautics and Astronautics (NUAA)

College of Economics and Management (CEM) Supported By: East China University of Science and Technology

Contents

ICSS2019 Committees ...................................................................................- 1 -

Keynote Speakers ..........................................................................................- 6 -

Plenary Speakers ..........................................................................................- 10 -

Program Overview .......................................................................................- 21 -

Parallel Sessions ..........................................................................................- 23 -

Key Contacts ................................................................................................- 30 -

Map ..............................................................................................................- 35 -

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ICSS2019 Committees

Conference Chairs: Hong Nie, Dequn Zhou, Robin Qiu, Hui Yang

Professor Hong Nie President, Nanjing University of Aeronautics and Astronautics, China

Prof. Hong Nie is the President of Nanjing University of Aeronautics and

Astronautics. He has long been engaged in the research of aircraft structural

dynamics and structural fatigue life prediction. He has been responsible for a

variety of funds, such as the German "Humboldt" Research Fund, the Korea

Science and Engineering Fund, the National Natural Science Foundation, the

National 863 Program, the National 921 Project, and the National Major Science and Technology

Project. He has worked on a number of research projects, presided over the preparation of 1

monograph, participated in the compilation of review manuals and 4 books, and published more

than 150 articles in SCI and EI. He won the second prize of the National Science and Technology

Progress Award, and the first prize for scientific research achievements of the provincial and

ministerial level (for three times). He is currently the convener of the 7th Academic Assessment

Committee of the State Council Academic Accreditation Group, Aerospace Aeronautical Science

and Technology Group, Vice Chairman of the Chinese Aviation Academy, and Deputy Director of

the Edit

Professor Dequn Zhou Dean, College of Economics and Management, Nanjing University of

Aeronautics and Astronautics, China

Prof. Dequn Zhou is the Dean of Economics and Management, director of

"Energy Soft Science Research Center". He has long been engaged in

teaching and research in areas such as energy soft science, management

science and engineering, and systems engineering. He is the chief expert of

the National Philosophy and Social Science Fund Project entitled "Strategic Research on the

Sustainable Development of China's Energy Development, Utilization, and Reserves under

Uncertain Conditions". He carried out several research projects granted by the National Natural

Science Foundation of China in energy strategy, mining cities, and energy efficiency. Besides, he

has taken part in more than 20 key projects, such as the National Soft Science Fund Project, the

Humanities and Social Science Fund Project of the Ministry of Education, and the Doctoral Fund

Project of the Ministry of Education.

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Professor Robin Qiu

The Pennsylvania State University

Dr. Qiu is a tenured full Professor at School of Information Science, The

Pennsylvania State University. He holds a Ph.D. in Industrial Engineering

and a Ph.D. (minor) in Computer Science both from The Pennsylvania

State University. Dr. Qiu’s research interests include Big Data, Data Analytics, Smart Service

Systems, Service Science, Service Operations and Management, Information Systems, and

Manufacturing and Supply Chain Management. Dr. Qiu is the past Editor-in-Chief of INFORMS

Service Science, and Advisory Editor for International Journal of Services Operations and

Informatics, and an Associate Editor for IEEE Transactions on System, Man and Cybernetics and

IEEE Transactions on Industrial Informatics. He also serves on Editorial Boards of many other

international journals. Dr. Qiu is the founding Chair of the INFORMS Service Science Section

and the founder of INFORMS Service Science.

Prof. Hui Yang

The Pennsylvania State University

Dr. Hui Yang is the Harold and Inge Marcus Career Associate Professor in

the Harold and Inge Marcus Department of Industrial and Manufacturing

Engineering at The Pennsylvania State University, University Park, PA. Dr.

Yang's research interests focus on sensor-based modeling and analysis of

complex systems for process monitoring, process control, system diagnostics, condition

prognostics, quality improvement, and performance optimization. His research program is

supported by National Science Foundation (including the prestigious NSF CAREER award),

Lockheed Martin, NSF center for e-Design, Susan Koman Cancer Foundation, NSF Center for

Healthcare Organization Transformation, Institute of Cyberscience, James A. Harley Veterans

Hospital, and Florida James and Esther King Biomedical research program. His research group

received several best paper awards and best poster awards from IISE Annual Conference, IEEE

EMBC, IEEE CASE, and INFORMS.

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Program Co-chairs: Jing Ma, Weiwei Chen

Professor Jing Ma

Nanjing University of Aeronautics and Astronautics, China

Dr. Jing Ma is Professor of the College of Economics and Management,

Nanjing University of Aeronautics and Astronautics, China. She received

her Ph.D. from the Nanjing University of Aeronautics and Astronautics in

China. Her research interests include natural language processing, complex

system control, and management information systems. She has been

responsible for various research funds, such as the Chinese National Natural Foundations and

National Defense Technology Foundation. Her research articles have appeared in top-ranking

journals such as Scientific Reports, International Journal of Nonlinear Science, International Journal

of Engineering Research and Applications, Information Systems Frontiers,

Prof. Weiwei Chen

The State University of New Jersey, USA

Dr. Chen received his Ph.D. degree from University of Wisconsin-Madison,

and the M.S. and B.S. degree from Tsinghua University, Beijing, China. Prior

to joining Rutgers Business School, he was a Scientist at GE Global Research,

NY, solving various problems from GE Energy, GE Aviation, Lockheed Martin

and electric utility companies. Dr. Chen’s research interest lies in operations

and finance interface, as well as supply chain operations planning and scheduling. He also works on

simulation and randomized global optimization methodologies. He has extensive experience

working with businesses and public sectors, especially in energy and healthcare, to improve

strategic decisions and operational efficiencies using data analytics. His work has appeared in

Operations Research, Manufacturing & Service Operations Management, Interfaces, Automatica,

IEEE Transactions on Automatic Control, IEEE Transactions on Smart Grid, etc.

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Program Committee Name Institution

Ozgur Araz Nebraska-Lincoln, USA Ralph Badinelli Virginia Tech, USA Youakim Badr INSA, France Rahul Basole Georgia Institute of Technology, USA George Cai Santa Clara University, USA Mukun Cao Xiamen University, China Victor Chan Tsinghua University, China Xiangyun Chang East China University of Science and Technology, China Guoqin Chen Tsinghua University, China Jenny Chen Dalhousie University, Canada Jian Chen Tsinghua University, China Weiwei Chen Rutgers University, USA Zhixiang Chen Sun Yat-sen University, China Qiang Duan Penn State, USA Tijun Fan East China University of Science and Technology, China Siyang Gao City University of Hong Kong, Hong Kong Ziyou Gao Beijing Jiaotong University, China Na Geng Shanghai Jiaotong University, China Christoph Heitz ZHAW School of Engineering, Switzerland Lihua Huang Fudan University, China Ming-Hui Huang National Taiwan University, Taiwan Zuqing Huang Guangzhou University, China Kwang-Jae Kim POSTECH, Korea Zhibin Jiang Shanghai Jiaotong University, China Wei Jiang Shanghai Jiaotong University, China Haitao Li University of Missouri - St. Louis, USA Weian Li Tianjin, China Yijun Li Harbin Instiutte of Technology, China Chiehyeon Lim UNIST, Korea Ching-Torng Lin Dy-Yeh University, Taiwan Bin Liu Shanghai Maritime University, China Xiao Liu University of Arkansas, USA Xiao Lu Stevens Institute of Technology, USA Yingdong Lu IBM, USA Kelly Lyons University of Toronto, Canada Juan Ma Turner Broadcasting System, USA Tieju Ma East China University of Science and Technology, China Rym M'Hallah Kuwait University, Kuwait Paul Maglio UC Merced, USA Aly Megahed IBM, USA Paul Messinger U Alberta, Canada Chuanmin Mi Nanjing University of Aeronautics and Astronautics, China Ran Mo Central China Normal University, China Ashkan Negahban Penn State, USA Kai Pan The Hong Kong Polytechnic University, Hong Kong

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Michael Pinedo NYU, USA Francesco Polese UniversitàdegliStudi di Salerno, Italy Gang Qian Nanjing Audit University, China Patrick Qiang Penn State, USA Robin Qiu Penn State, USA Changrui Ren IBM Beijing, China Huizhang Shen Shanghai Jiaotong University, China Xinning Su Nanjing University, China Tuure Tuunanen University of Jyväskylä, Finland Huimin Wang Hohai University, China Tina Wang Oxford University, UK Wenping Wang Southeast University, China Xiaolei Xie Tsinghua University, China Qi Xu Donghua, China Yuqian Xu University of Illinois at Urbana-Champaign, USA Zeshui Xu PLA University of Science and Technology, China Hui Yang Penn State, USA Shanlin Yang Hefei Univrsity of Technology, China Ming Yu Tsinghua University, China Limin Zeng Technische Universität Dresden, Germany Hui Zhang Lakehead University, Canada Runtong Zhang Beijing Jiaotong University, China Weixing Zhou East China University of Science and Technology, China

Conference Organizing Committee

Conference Co-chairs Dequn Zhou, Robin Qiu, and Hui Yang Program Co-chairs Jing Ma; Weiwei Chen Publication Chair Hui Yang Publicity Chair Shan Li Invited/Special Session Co-chairs Xiao Liu; Qiang Duan Local Conference/Registration Co-chairs

Chuanmin Mi; Lingfei Qian

Local Organizing Committee Members General Directors Dequn Zhou and Hongtu Jiao General Coordinators Zhihong Tu and Jing Ma Supervisors Haiyan Xu Coordination Team Shan Li and Chuanmin Mi, Operations & Logistics Team Ci Ren, Mingbao Zhang, Jian Chen, and Zhengjun Luo Publicity Team Lianlian Song and Xiaofeng Li Volunteer Team Lin Xiao, Zhiping Zhou, Jianling Wang, Yun Shi, and Yida

Pang Financial Team Lingfei Qian and Lili Liu

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Keynote Speakers 1. Professor Michael Pinedo, New York University Leonard N. Stern School of Business, USA

SCHEDULING IN THE SERVICE INDUSTRIES: Theory and Applications

Abstract: This talk focuses on current research directions in scheduling in the service industries. The scheduling models in services as well as the solution methodologies tend to be different from those used in manufacturing environments. We describe five classes of models and their current status quo. The first class consists of transportation models (tanker scheduling, aircraft routing and scheduling and train timetabling). The second class deals with scheduling models in health care, e.g., appointment scheduling. The third class consists of workforce scheduling models, e.g., operators in a call center. The fourth class involves timetabling and tournament scheduling. The fifth class considered includes interval scheduling models and reservation systems. We conclude with a summary of the similarities and the differences between the model formulations and the solution techniques that are used in these various different areas.

Biography: Michael Pinedo is the Julius Schlesinger Professor of Operations Management at New York University's Stern School of Business. He received an Ir. degree in Mechanical Engineering from Delft University of Technology (in the Netherlands) in 1973 and a Ph.D. in Operations Research from the University of California at Berkeley in 1978. He has taught at Columbia University from 1982 till 1997 and at New York University since 1997. His research focuses on the modeling of service systems, and in the development of

planning and scheduling systems, as well as systems for measuring operational risk. Over the last decade his research has focused on operational risk in financial services. He is co-editor of Creating Value in Financial Services: Strategies, Operations, and Technologies (Kluwer), and co-editor of Global Asset Management: Strategies, Risks, Processes, and Technologies (Palgrave/McMillan). He has co-authored the book Operations in Financial Services - Processes, Technologies, and Risks (NOW Publishers) together with Yuqian Xu. Professor Pinedo has been actively involved in industrial system development. He supervised the development of systems at Goldman Sachs, Siemens, and at Merck. Professor Pinedo is Editor of the Journal of Scheduling (Springer), Associate Editor of the Journal of Operational Risk, Department Editor of Production and Operations Management and Associate Editor of Annals of Operations Research.

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2. Dr. Hong Huo, Department of Management Sciences (DMS) of National Natural Science

Foundation of China (NSFC)

Trends of research hotspots and projects funded by NSFC in the areas of service operation management NSFC in the past 20 years

Abstract: Service Science and Operations Management discipline mainly explores and develops management theories, methods and technologies for economic and social activities with service dominant logic, cultivates innovative talents for modern service industries. Service Science and Operations Management takes service systems composed of interconnected people and various service resources as research objects, to reveal the law of value co-creation with the application of interpersonal interaction, network technology, organization and information under various conditions. The aim is to promote service innovation, improve service experience and increase service efficiency. This talk describes the concept of service science and summarizes the research hotspots and projects funded by NSFC in the areas of Service Science and Operations Management in the past 20 years. Future research directions in Service Science and Operations Management will also be introduced.

Biography: Dr. Hong Huo works at the Department of Management Sciences (DMS) of National Natural Science Foundation of China (NSFC). Dr. Huo got her Ph.D. degree in Environmental Science and Engineering from Tsinghua University in 2005 and worked as a postdoctoral research associate at Argonne National Laboratory during 2005 and 2009. She joined in the Institute of Energy, Environment, and Economy of Tsinghua University as an associate professor in 2009, and her research areas were focused on air pollution modeling and policy

evaluation in China. Dr. Huo has published more than 50 articles in various journals including Nature, PNAS, Environmental Science & Technology, etc. Since 2018, Dr. Huo has worked in DMS of NSFC, as a program director in the disciplines of Economic Sciences and Management Science and Engineering, successively. Her main work at NSFC includes organization of peer reviews and evaluation panel meetings for proposals submitted to NSFC, routine management of funded proposals, and planning discipline development and funding strategies.

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3. Professor Prof. Zhongsheng Hua, Zhejiang University, China

Some Key Issues in Service Science Research

Abstract: With the development of information and communication technology (ICT), new service products and models are continuously emerging, and traditional industries are being fused or reformed as new service patterns with the help of ICT. Service science is the science of studying all human behaviors and activities with service essence and value creation. This talk describes the concept of service science, summarizes current situation and future trend of modern service industry, and proposes some key issues in service science research to support the development of modern service industries. These key issues focus on principles and methods of forming data foundation for service measurement and experience perception; the description, nature and formation of service relationship among professional service providers and clients; principles and methods of service design and innovation. Example problems on these issues are presented, importance of these issues are discussed, and primary idea for dealing with these issues are outlined.

Biography: Prof. Zhongsheng Hua is a Qiushi Chair Professor of Zhejiang University, a Changjiang Sochlars Distinguished Professor of the Chinese Ministry of Education. He is the Vice Director of the Research Center of E-Service Technology for the Modern Service Industry at Zhejiang Province, the Director of Research Center of Service Sciences of Zhejiang University. He takes the positions as a vice President of the Society of Management Science and Engineering of China, a President-Elect of the Production and Operations

Management Society-China Chapter, IEEE Senior Member. He is the associate editor of the International Journal of Society Systems Science, an editorial board member of the Frontiers of Engineering Management and the International Journal of Services and Operation Management, respectively. He also serves as editorial board members of the Chinese Journals, e.g., the Chinese Journal of Management Science, the Journal of Industrial Engineering and Engineering Management, Forecasting, and Information and Management Research.

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4. Professor Xinggang Luo, Hangzhou Dianzi University, China

From Product Design to Service Design: Research Challenges and Opportunities

Abstract: Product/service design problem is one of vital importance to the success of a firm, which aims at determine the attributes of the product or service so as to maximize the revenue or minimize the cost. In this talk, we review the related optimization models and algorithms on product design problem, analyze the characteristics of service design, and point out some key research challenges and opportunities on this topic.

Biography: Xinggang Luo received the M.Sc. degree in mechanical design and manufacturing and the Ph.D. degree in system engineering, both from the Northeastern University, Shenyang, China. He was a professor at the department of system engineering, Northeastern University, Shenyang, China, from 2011 to 2017. He is currently a distinguished professor at the school of management, Hangzhou Dianzi University, Hangzhou, China. He has won several research grants from Nation Natural Science Foundation of China. His research interests include product/service design, service operations, optimization algorithms and

quality management. He is the author or coauthor of over 50 research papers published in refereed international journals including DSS, IJPR, OMEGA, EJOR, IJPE, IEEE EM, IEEE SMC, C&IE, IS, CII, JED, RED, etc. His research interests include product/service planning, service operations, optimization algorithms and quality management.

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Plenary Speakers 1. Professor Saif Benjaafar, University of Minnesota, U.S.

Operations Management in the Age of the Sharing Economy: What Is Old and What Is New?

Abstract: The sharing economy, a term we use to refer to business models built around on-demand access to products and services mediated by online platforms that match many small suppliers or service providers to many small buyers, has emerged as an important area of study in operations management. We first describe three "canonical" applications that have garnered much attention from the operations management community: (1) peer-to-peer resource sharing, (2) on-demand service platforms, and (3) on-demand rental networks. We use these applications to highlight distinguishing features of sharing economy business models and to point out research questions that are new. For each application, we describe our attempt at addressing some of these questions. We conclude by drawing connections between classical operations management theory/models and theory/models that have been used to study sharing economy applications.

Biography: Saif Benjaafar is Distinguished McKnight University Professor at the University of Minnesota. He is Head of the Department of Industrial & Systems Engineering at the University of Minnesota, where he also directs the Initiative on the Sharing Economy. He is a founding member of the Singapore University of Technology and Design where he served as Head of Engineering Systems and Design. He is the Editor in Chief of the INFORMS journal Service Science. He serves on the board of directors of Hourcar, a social car

sharing organization. His research is in the area of operations management broadly defined, with a current focus on sustainable operations and innovation in business models, including sharing economy, on-demand services, and digital marketplaces. The work described in this talk has been funded by grants from the US National Science Foundation, the Bill and Melinda Gates Foundation, and the Singapore Ministry of Education.

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2. Professor Kwang-Jae Kim, Department of Industrial and Management Engineering, Pohang

University of Science and Technology (POSTECH), Korea

Data-Driven Approach to Developing New Services: Recent Cases and Research Issues

Abstract: Various types and massive amounts of data are being collected in multiple industries. Such a big data proliferation has provided ample opportunities to develop more and better services, especially in manufacturing industries. For example, heavy equipment manufacturers monitor, diagnose, and predict product health through prognostics and health management services using the data collected from their equipment. Consequently, equipment managers can cope with potential product breakdowns and maximize product availability for clients. Numerous companies in manufacturing industries have “servitized” their value propositions to address issues on product commoditization and sustainability. A key component of servitization is informatics, which transforms system data into useful information for the system stakeholders. This talk proposes a conceptual framework of new service development based on the analysis of data collected from a system in question. The framework is introduced using recent case studies in automobile, vessel, energy, and healthcare industries. Observations and findings from the case studies would contribute to promoting and inspiring research on the development of smart services in various industries.

Biography: Kwang-Jae Kim is Professor in the Department of Industrial and Management Engineering and a Vice President at Pohang University of Science and Technology (POSTECH), Korea. His current research interests include quality assurance in product and service design, product-service systems, and smart service systems. His work has been applied in various areas including semiconductor manufacturing, steel manufacturing, automobile design and manufacturing, healthcare and wellness, smart energy, telematics,

and ICT services. His research has been supported by National Research Foundation, Ministry of Science and Technology, Ministry of Knowledge Economy, Ministry of Health and Welfare, Ministry of Trade, Industry and Energy, Ministry of ICT of Korea, and various industrial companies including Samsung, LG, POSCO, Hyundai, IBM, and Microsoft. He is a member of the National Academy of Engineering of Korea, a fellow of Asia Pacific Industrial Engineering and Management Systems (APIEMS), and an advisory board member of INFORMS QSR. More details can be found at http://quality.postech.ac.kr/.

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3. Professor Grace Lin, Vice President at Asia University

Realizing Inclusive Finance through Supply Chain and Blockchain innovation

Abstract: High interest rate and low coverage are the current status of SME financing market due to hard-to-access credit information. The objective is to fill in SME financing gap by leveraging smart analytics and innovative business model in order to enable quality SMEs easier, faster and better financing services., and to empower reliable e2e supply chain with greater competitive power and healthier finances. Our approach: Cooperate with dominant companies to gain information access of the supply chain. Develop intelligent supply-chain based credit rating to lower default rate. Build transparency and trust through blockchain technology. Design and develop a blockchain-based 3rd party supply chain and crowdfunding platform to provide alternative financial services. Designed a SC-based stochastic credit rating methodology coupling with blockchain technology to build a SC Financing and crowd funding system for inclusive financing.

Biography: Grace Lin is an INFORS Fellow and Vice President at Asia University and Director General for the Big Data Research Center and the FinTech and Blockchain Research Center. She is also a Chair Professor at Asia University, Chinese Medical University, and Soochow University (Adjunct) in Taiwan. Dr. Lin’s experience includes five years as a VP at Taiwan’s Institute for Information Industry (III), leading the development of Big Data Analytics and Advanced Technology, Adjunct Full Professor at the Department of

Industrial Engineering and Operations Research at Columbia University, New York, as well as more than 16 years at IBM US. While at IBM, she served for more than six years as the Global Sense-and-Respond Value-Net Leader and CTO and Director for Innovation and Emerging Solutions at IBM Global Business Services, after serving as Manager, and Senior Manager at the IBM T.J. Watson Research Center. Dr. Lin was also an elected member of the IBM Academy of Technology and an IBM Distinguished Engineer. She has received a number of major awards including the INFORMS Franz Edelman Award, IBM Outstanding Technical Achievement Award, the IBM Corporate Logistics Award, the IBM Research Division Award, the IIE Doctoral Dissertation Award, and the Purdue Outstanding Industrial Engineer Award, and recently, Tsing Hua University, Distinguished Alumni Award from the School of Science, Tsing Hua University, Hsin-Hu, Taiwan. Dr. Lin received her Ph.D. in IE and M.S. in Applied Math from Purdue University, West Lafayette, US and an M.S. and B.S. in Math from Tsing-Hua University, Hsinchu, Taiwan

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4. Professor Christoph Heitz, ZHAW School of Engineering, ZHAW Zurich University of Applied

Sciences

Designing Value Co-creation for a Free-Floating E-Bike Sharing System

Abstract: In my talk, I will describe an interdisciplinary research approach for designing value co-creation in the context of the development of a new E-bike sharing system (BSS) in Zurich, Switzerland. This BSS is based on the idea that users of the BSS co-create value by adapting their usage behavior such that the overall service level is maximized, by dropping off their bike at locations where a future demand is expected. Incentives serve to influence users’ behavior for optimizing the system’s overall performance. The studied system is a typical scenario of value co-creation in services, as it is based on interlinking provider’s and clients’ activities with the aim to create value for both of them.

Our approach of designing such a system is based on operationalizing the concept of value and value generation for the different actors and linking this to design options: What exactly is the value that is to be created, and how can it be measured? By which activities is value created, and what are the options for stimulating these activities? Which design options maximize value creation? We found that this required combining two different research approaches: Empirical social research was necessary to understand user needs, value perception, motivational patterns in response to incentives, and communication needs. Operational research was necessary for assessing different options for the incentive system with respect to the value creation both for provider and users. By interlinking both research activities, we were able to design a dynamic incentive system that creates value for the provider by allowing a substantial reduction of the number of bikes without diminishing the service level, and creates value for the users in form of both incentives and social value.

Biography: Christoph Heitz received a PhD in theoretical physics in 1996 from the University of Freiburg i.Br., Germany. After few years in industry, he joined the Zurich University of Applied Sciences (ZHAW) in 2000 as professor for Operations Management at the Institute of Data Analysis and Process Design (IDP). He is founding member and part of the executive board of this institute, and head of its department “Business Engineering and Operations Management”. In the academic years 2007-08 and 2012-13 he was visiting

professor at the University of California, Santa Cruz, USA. In addition to his position at ZHAW, he is currently a fellow of the Digital Society Initiative of the University of Zurich.

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In 2017, he co-founded the Swiss Alliance for Data-Intensive Services (www.data-service-alliance.ch) and serves as its president since then. This Swiss national innovation network consists of more than 300 researchers and professionals from >40 companies and > 20 research institutions from all over Switzerland. Its goal is to foster innovation in the field of data-based value creation, by combining knowledge from different fields such as data science and technology, service science, and social sciences into marketable products and services.

During the last 15 years, Christoph Heitz has run more than 30 funded research projects with Swiss and international companies with budgets up to 1 MCHF. His publications include contributions in the fields of service science, digital ethics, operations management, physical asset management, high voltage engineering and signal analysis. He is inventor or co-inventor of 11 international patents, and (co-) founder of three companies.

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5. Professor Fiona Jamison, CEO of Spring International.

People Analytics in Practice: Connecting Employee, Customer and Operational Data to Create Evidence-Based Decision Making

Abstract: People analytics is a rapidly growing field and one that can be daunting for many HR professionals. The sophistication and capability of organizations varies considerably: Some organizations are just starting to get a handle on their data and improve its quality, while others are on the cutting edge of predictive analytics. This paper outlines an analytics maturity model and various case studies, sharing how organizations have moved from data to action. Examples will demonstrate how companies have embarked on a journey to connect data on employee attitudes, customer loyalty and satisfaction, operations and financial performance to make more informed, evidence-based business decisions.

Biography: Fiona brings 20 years of experience conducting research and providing solutions to both for-profit and non-profit organizations with specific expertise in employee engagement, employee relations, change management and human capital analytics. For the last 25 years, Spring International has provided custom research and analytics for Fortune 100 companies across the United States.

Born and raised in Britain, Fiona has provided research and consultancy services in the U.K., Europe, and North America. This international experience adds a unique perspective to understanding employee relations and organizational culture. In the U.K. Fiona worked mostly in the aerospace, energy and telecommunications industry. She is the author of numerous articles on human capital analytics, change management, effective downsizing and understanding the role of line managers during organizational change.

Fiona’s Ph.D. is in Human Resource Management from the University of Bristol, was an Honorary Research Fellow for the University of Wolverhampton (U.K.). In the USA, she has been an adjunct professor at Arcadia University and Temple University. She is actively involved with leading HR think tank organizations such as the Wharton Research Advisory Group, University of Pennsylvania and more recently the Philadelphia Society for People and Strategy Human Capital Analytics Group. She currently sits on the Senior HR Advisory Board for Fox Business School.

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6. Dr. Paul Messinger, Alberta School of Business, University of Alberta, Canada

Machine Learning Meets Service Dominant Logic: Directions for Service Research

Abstract: At the 2018 INFORMS annual meeting in Pheonix, a panel of experts from marketing and operations, academics and practitioners, discussed the past and future of the study of service research. The panelists included Mary Jo Bitner, Peter Frazier, Xin (Shane) Wang, Aly Megahed, and Paul Messinger. This talk sums up some of the ideas raised there.

Early in the field, it was necessary to make a case that service research was both interesting and different. Now, in the wake of early research breakthroughs, and partly due to the disproportionate growth in services as part of modern economic activity, service research is becoming ubiquitous. Some of this research began with services marketing, then successively branched out to service management, service design, service operations, service IT, service engineering, and service science. The field is still (a) open, progressive, inclusive, (b) global, (c) cross disciplinary, (d) multi-method and rigorous, (e) problem-based, (f) focused on topical challenges and issues, and (g) has seen growth in theory, methods, and practice.

Technology has been a key driver of modern service research. As service expands online, with disruption of many traditional industries, several issues come to the fore: (a) the tension between reliability and scalability, (b) concerns about human response, both as customers displaying strategic behavior and as workers, displaying heterogeneity in skills/workstyles, and even fear of obsolescence, and (c) consideration of different types of platforms and whether they should be regulated. New sensor technologies have been important for gathering data, and robotics will be increasingly deployed and enhanced in the future.

In parallel with diffusion of service delivery technology is the emergence of new methods of machine learning, deep learning, and artificial intelligence. Much of machine learning is prediction and categorization; it is used to improve on some performance metric (e.g., fraud, spam classification, customer churn, etc.) through experience (i.e., data). The most common software tools are free open-source systems or languages such as R and Python. There is an increasing trend towards studying unstructured data (e.g., text, images, and video), with the approach of processing the unstructured data so as transform it into a useable structured form. Early work was with human supervised methods, but applications increasingly use unsupervised learning. This work is growing in operations, marketing, MIS, and service science. For natural language processing, in particular, future applications may be suggested by considering the industry participants, who are sources of textual data, and important service operations and service marketing questions that potentially can leverage textual analysis from these sources.

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There is a difference in perspective that has to be bridged concerning the orientation of machine learning toward prediction with large datasets using many variables (with concern for out-of-sample prediction accuracy) versus the empirical orientation in the management sciences toward attempts to develop causal structural models with a preference for parsimony, simplicity, and statistical significance. Which is more suitable depends on the particular research objectives and taste (reflecting a scientific orientation toward “understanding” or an engineering orientation toward “doing”). And for those interested in underlying theory, either testing or development of new theory, different theories can be applied to different contexts. Two potentially important theories involve service-dominant logic and transactions cost economics.

Applications of Machine Learning with structured and unstructured data cover B2C and B2B sales, service operations, service marketing, and health services. We will summarize research examples from service science and related disciplines; suggest possible new areas, and identify a few emerging themes.

Biography: Paul R. Messinger is Chair of the Service Science Section of the Institute for Operations Research and the Management Sciences (INFORMS) and was Founding Director of the University of Alberta School of Retailing. Paul is an Associate Professor of Marketing and Marketing Group Ph.D. Coordinator at the University of Alberta School of Business, and Visiting Professor at the University of Northern British Columbia. Paul has served as Vice President Sections and Societies of INFORMS and as Principle

Investigator of the Research Alliance “Harnessing the Web-Interaction Cycle for Canadian Competitiveness” for the Social Science and Humanities Research Council of Canada. Paul has served on the Editorial Boards of Service Science (2016-present) and Marketing Science (1997-2015), as Guest Area Editor of Information Technology and Management (2015-present), and as guest editor for two special issues on eService for the Canadian Journal of Administrative Sciences. Paul’s research focuses on service science, emerging retail formats, consumer behavior and pricing, 3D mediated virtual worlds, e-commerce, and recommendation systems; his publication outlets include Marketing Science, Journal of Marketing, Journal of Retailing, Decision Support Systems, Journal of Economic Dynamics and Control, European Journal of Operations Research, Journal of Business Research, Information Systems and e-Business Management, Journal of Human Factors and Ergonomics in Manufacturing and Service Industries, Journal of Virtual Worlds Research, and Journal of Retailing and Consumer Services.

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7. Dr. Jin Dong, Director of Beijing Academy of Edge Computing (BAEC)

The Perspective of Next-gen AI Technology

Abstract: AI technology evolves rapidly with several milestones obtained in the recent years. With breakthroughs witnessed in fundamental technologies (e.g. voice recognition, vision analytics, NLP, reasoning etc.), industrial application innovations become viable in healthcare, environmental management, Industry 4.0, smart agriculture etc. To accelerate the development of enterprise AI application and next-gen industrial innovations, the adoption of smarter algorithms and the application of ubiquitous and trusted IoT devices is key to the bloom of commercial AI application in future.

In this presentation, Dr. Jin Dong will provide his perspective on the next-gen AI technology with the impact of algorithms, data, and hardware.

Biography: Dr. Jin Dong received his Ph.D. degree from the Faculty of Automation of Tsinghua University. Prior to joining IBM, he was a research assistant professor at the Department of Industrial Engineering at Arizona State University. Dr. Dong is dedicated to establish a world-class core technology research and development platform including IoT, Blockchain, AI and Edge Computing, benefiting to scientific breakthroughs and solving the real world problems. Before that, Dr. Jin Dong was the Associate Director of IBM

Research – China. The research team he led is mainly on the application of advanced technologies such as big data analytics, artificial intelligence and optimization, blockchain, quantum computing in various industries, including the environment, energy, weather, public health and food safety, winning hundreds of millions of dollars’ worth commercial projects for IBM. Dr. Jin Dong filed more than 30 US patents, authored or co-authored more than 50 academic papers published in academic journals and leading international conferences.

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8. Dr. Aly Megahed, IBM’s Almaden Research Center

Service Science Topics in the IT Services Industry

Abstract: IT service providers compete in a tender kind of process to win complex IT service contracts worth multi-million dollars each. In response to clients’ request for proposals (RFPs) for IT services, IT service providers prepare and submit solution proposals to the clients. Clients short list a number of providers and engage with them through due diligence and intense negotiations (that could last up to a year) to select a final winner for the bid. Given the business value at stake, the conventional approach to prepare a proposal and negotiate it involves resource-intensive complex activities and decision making. This calls for a strong demand to bring in data-driven service science, analytics, and operations research (OR) techniques.

In this talk, we will discuss recent advances in this area including RFP textual analytics, costing analytics, price optimization, and win prediction of prospective deals using structured and unstructured data. This body of work resulted in 19 publications and over a dozen patents. Our approaches were deployed in production resulting in a verifiable $350M business impact and a significant improvement in the production/win rates and efficiencies. The work was also a finalist at the prestigious Edelman award in 2019.

Biography: Dr. Aly Megahed is a research staff member at IBM’s Almaden Research Center in San Jose, CA. In his current job, he develops and advances research in analytics, statistics, machine learning, and operations research to address different service science, cloud computing, Internet of Things (IoT), and blockchain technology problems. Dr. Megahed got his Ph.D. in Industrial Engineering from Georgia Tech. He has two master’s degrees in Industrial and Production Engineering from Georgia Tech and Alexandria University,

respectively, and a B.S. in Production Engineering from Alexandria University. He has done multiple analytical research/consultancy projects for over 6 companies in the past, has given both invited and submitted talks at several conferences, companies, and institutions/universities, and has his work published in several academic journals and conferences in addition to filing 30+ patent disclosures. He has taught university level courses at 7 different academic institutions. He is the current elected secretary of the INFORMS service science section. Dr. Megahed has also won several internal IBM awards and external ones, including the second place at the INFORMS Innovative Applications in Analytics Award, being a finalist for the Edelman award, and the first place at the Excellence in Service Innovation Award of ISSIP.

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9. Dr. Hui Yang, Harold and Inge Marcus Department of Industrial and Manufacturing

Engineering, The Pennsylvania State University

Internet of Things and Data-enabled Innovations for Smart Service Systems

Abstract: Modern industry is investing in new technologies such as the Internet of Things (IoT), big data analytics, cloud computing and cyber security to cope with system complexity, increase information visibility, improve system performance, and gain competitive advantage in the global market. These advances are rapidly enabling a new generation of smart service systems that “enable all information about the complex process to be available whenever it is needed, wherever it is needed, and in an easily comprehensible form across the enterprise and among interconnected enterprises”. Smart service systems depend on data-driven innovations to realize high levels of autonomy and optimization of interconnected enterprises. This talk will present the internet of things (IoT) and data-enabled innovations for smart service systems that will help (1) Understand the evolution of IoT technology and its applications in the areas of both manufacturing and healthcare services; (2) Develop the strategy to implement IoT technology for smart and interconnected service systems; (3) Understand the technology of cloud computing and fog computing for IoT data analytics; (4) Realize full potentials of big data through new analytical methods and tools for smarter service systems. Specifically, case studies in both advanced manufacturing and smart health will be demonstrated. In the end, future research directions will be discussed.

Biography: Dr. Hui Yang is the Harold and Inge Marcus Career Associate Professor in the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering at The Pennsylvania State University, University Park, PA. Dr. Yang's research interests focus on sensor-based modeling and analysis of complex systems for process monitoring, process control, system diagnostics, condition prognostics, quality improvement, and performance optimization. His research program is supported by National Science

Foundation (including the prestigious NSF CAREER award), Lockheed Martin, and many others public and private funding agencies.

Dr. Yang was the president (2017-2018) of IISE Data Analytics and Information Systems Society, the president (2015-2016) of INFORMS Quality, Statistics and Reliability (QSR) society, and the program chair of IISE Annual Conference 2016. He serves on many journal editorial boards and conference organizing committees. He is a professional member of IEEE, IEEE EMBS, INFORMS, IIE, ASEE and American Heart Association (AHA).

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Program Overview CEM：College of Economics and Management building NUAA：Nanjing University of Aeronautics and Astronautics (Jiangning Campus)

DATE TIME EVENT VENUE

June 26 08:00-22:00 Registration Lobby, Crowne Plaza

June 27

07:50-08:00 Shuttle Bus Transportation In Front of Crowne Plaza

08:00-18:00 Registration Lobby, CEM, NUAA

08:30-9:00

Opening Ceremony Speaker I: Hong Nie, President of NUAA

Speaker II: Paul Messinger, Chair of INFORMS Service Science

Speaker III: Zuoyi Liu, Deputy Head of Management Science Department, NSFC

Chair: Robin Qiu A305, CEM, NUAA

09:00-09:50 Keynote Speech Speaker: Prof. Michael Pinedo

09:50-10:15 Group Photo In front of CEM, NUAA

10:15-10:30 Coffee/Tea Break Atrium of Level 3, CEM, NUAA

10:30-11:10 Keynote Speech Speaker: Prof. Hong Huo

Chair: Paul Messinger A305, CEM, NUAA 11:10-11:50 Plenary Session

Speaker: Prof. Saif Benjaafar

11:50-12:30 Plenary Session Speaker: Prof. Grace Lin

12:30-14:00 Lunch W&M Cafe house, First Floor of CEM, NUAA

14:00-15:40 Parallel Sessions CEM, NUAA

Session 5A(A302) Session 5B (A304) Session 5C (A402) Session 5D (A404) Session 5E (A405)

Chair: Robin Qiu Paper IDs: 135, 115,

110, 21, 91

Chair: Chuanmin Mi Paper IDs: 19, 40, 10,

27, 53

Chair: Qiang Duan Paper IDs: 66, 89,

108, 100, 124

Chair: Jian Chen Paper IDs: 20, 92,

131, 99, 4

Chair: Qiansheng Deng Paper IDs: 14, 32, 129,

114, 60

15:40-16:00 Coffee/Tea Break Atrium of Level 3 and Level 4, CEM,NUAA

16:00-17:40 Parallel Sessions CEM, NUAA

Session 6A (A302) Session 6B (A304) Session 6C (A402) Session 6D (A404) Session 6E (A405)

Chair: Robin Qiu Paper IDs: 12, 78,

120, 118, 103

Chair: Yu Wang Paper IDs: 5, 33, 36,

13, 54

Chair: Tijun Fan Paper IDs: 26, 44, 45,

105, 41

Chair: Jing Chen Paper IDs: 79, 85,

128, 86

Chair: Yan Li Paper IDs: 119, 138,

42, 69

18:30-20:00 Dinner (Buffet) Cuipingyuan Restaurant, NUAA

20:00 Shuttle Bus Transportation In Front of Cuiping Yuan Restaurant, NUAA

June 28

07:50-08:00 Shuttle Bus Transportation In Front of Crowne Plaza

08:00-18:00 Registration Lobby, CEM, NUAA

08:30-09:20 Keynote Speech Speaker: Prof. Zhongsheng Hua Chair:

Hui Yang A305, CEM, NUAA 09:20-10:00 Plenary Session

Speaker: Prof. Christoph Heitz

- 22 -

10:00-10:20 Coffee/Tea Break Atrium of Level 3, CEM, NUAA

10:20-11:00 Plenary Session Speaker: Prof. Kwang-Jae Kim

Chair: Aly Megahed A305, CEM, NUAA 11:00-11:40 Plenary Session

Speaker: Dr. Fiona Jamison

11:40-12:20 Plenary Session Speaker: Prof. Paul Messinger

12:20-14:00 Lunch W&M Cafe house, First Floor of CEM, NUAA

14:00-15:40 Parallel Sessions CEM, NUAA

Session 12A (A302) Session 12B (A304) Session 12C (A402) Session 12D (A404) Session 12E (A405)

Chair:Jian-Jun Wang Paper IDs: 34, 48,

133, 9

Chair: Yifan Wu Paper IDs: 102, 106,

109, 117

Chair: Xin Jia Jiang Paper IDs: 50, 80,

113, 7

Chair: Beibei Dong Paper IDs: 15, 25,

101, 18, 46

Chair: Victor Chan Paper IDs: 1, 123, 68,

64,

15:40-16:00 Coffee/Tea Break Atrium of Level 3 and Level 4, CEM,NUAA

16:00-17:40 Parallel Sessions CEM, NUAA

Session 13A (A302) Session 13B (A304) Session 13C (A402) Session 13D (A404) Session 13E (A405)

Chair: Qiushi Chen Paper IDs: 23, 67, 84,

82

Chair: Guiping Hu Paper IDs: 29, 30, 31,

65

Chair: Ran Lun Paper IDs: 11, 62, 71,

49

Chair: Robin Qiu Paper IDs: 55, 74,

107, 97, 77

Chair: Houping Tian Paper IDs: 95, 136,

35, 75, 17

17:40-17:50 Shuttle Bus Transportation In Front of CEM, NUAA

18:30-21:00 Award Ceremony, Banquet Zijin A, Crowne Plaza 2F

June 29

07:50-08:00 Shuttle Bus Transportation In Front of Crowne Plaza

08:30-9:20 Keynote Speech Speaker: Xinggang Luo Chair:

Weiwei Chen A305, CEM, NUAA 9:20-10:00 Plenary Session

Speaker: Dr. Jin Dong

10:00-10:20 Coffee/Tea Break Atrium of Level 3, CEM, NUAA

10:20-11:00 Plenary Session Speaker: Dr. Aly Megahed Chair:

Robin Qiu A305, CEM, NUAA 11:00-11:40 Plenary Session

Speaker: Prof. Hui Yang

11:40-13:10 Lunch W&M Cafe house, First Floor of MBA Building, NUAA

13:10-14:50 Parallel Sessions CEM, NUAA

Session 18A (A302) Session 18B (A304)

Chair: Xiaofeng Li Paper IDs: 52, 76, 130, 57, 70

Chair: Lin Xiao Paper IDs: 87, 116, 122, 28, 61

14:50-15:10 Coffee/Tea Break Atrium of Level 3, CEM, NUAA

15:10-16:50 Parallel Sessions CEM, NUAA

Session 19A (A302) Session 19B (A304) Chair: Yong Wu

Paper IDs: 16, 93, 2, 90 Chair: Junwei Wang

Paper IDs: 127, 137, 139, 132, 6 17:30-19:00 Dinner (Buffet) Cuipingyuan Restaurant, NUAA

19:00 Shuttle Bus Transportation In Front of Cuipingyuan Restaurant, NUAA

- 23 -

Parallel Sessions Date Time Venue Stream Title Authors

June 27th 14:00-15:40

Parallel Session 5A

(A302), CEM, NUAA

Best Student Paper

Competition

Chair: Robin Qiu

135 Analyzing WeChat Diffusion

Cascade: Pattern Discovery and Prediction

Ruilin Lv, Chengxi Zang, Victor Chan and Wenwu Zhu

115 Capacitated Hub Location Problem of

Fresh Agricultural Products Under Uncertain Demand

Zhiying Liu, Shuxia Li, Liping Liu and Yiquan Wang

110 Research on Information Dissemination Model in

WeChat-Based Brand Community

Huijie Peng, Xingyuan Li, Yisong Zhang, Qifeng Tang and

Liwei Zheng

21

Analysis of Crude Oil Price Fluctuation and Transition

Characteristics at Different Time Scales Based on Complex Networks

Jiao Yan and Jing Ma

91 Two-Level Trip Selection and Price

Incentive Scheduling in Electric Vehicle Sharing System

Zihao Jiao, Lun Ran, Xin Liu and Yuli Zhang

Parallel Session 5B

(A304,CEM, NUAA)

Special Topic Session (I):

Internet Service, Power

Safety Management

and Operation

Chair: Chuanmin Mi

19

Research on the Evaluation of Electric Power Companies’ Safety Capabilities

Based on Grey Fixed Weight Clustering

Yijing Wang, Jie Xu, Chuanmin Mi and Zhipeng Zhou

40 Research on Electricity Falling

Accident Based on Improved Bode Accident Causation Model

Yuanyuan Qian, Jie Xu, Chuanmin Mi and Qiwei Peng.

10 The Impacts of Facilitating and

Inhibiting Factors on Usage Intention of Mobile Payment Services

Chien-Wen Chen, Ching-Torng Lin and Wan-Yun Chen

27 Factors Influencing Online Health Service Use: a Valence Framework Lin Xiao and Chuanmin Mi

53 Design of Power Grid Security Data Model Based on SG-CIM

Bao-Sheng Liu, Chao Liu, JinLv and Dong-Jun Tang

Parallel Session 5C

(A402,CEM, NUAA)

Special Topic Session (II):

Network/Internet-based Services

Chair:

Qiang Duan

66

Cloud-Based Life Sciences Manufacturing System: Integrated Experiment Management and Data

Analytics via Amazon Web Services

Pei Guo, Jianwu Wang, Raymond Peterson and Paul

Paukstelis

89 Spreading Path Prediction of

Information on a Topic-Oriented Relationship Strength Network

Xinyi Yang and Hengmin Zhu

108 Energy-Efficiency for Smartphones Using Interaction Link Prediction Zhongshun Sun and Junyun Xu

100 Service Performance Tests on the

Mobile Edge Computing Platform: Challenges and Opportunities

Ishtiaque Hussain, Tiffany Zhong and QiangDuan

124

An Investment Model of Crowdfunding Projects Based on

Multiple Regression and Entropy-Weighted TOPSIS

Xueqin Huang, Longchun Zou, Xiandong Li, Qinglong Meng

and Yeqing Guan

- 24 -

Parallel Session 5D

(A404, CEM, NUAA)

Contributed Session (I)

Chair:

Jian Chen

20

Risk Assessment of Closed-Loop Supply Chain for Electronic Products Recycling and Reuse Based on Fuzzy

BP Neural Network

Wei Shao, Zuqing Huang and Lianjie Jiang

92 Research on the Method of Identifying

Opinion Leaders Based on Online Word-of-Mouth

He Chenglin, Li Shan, Yao Yehui and Ding Yu

131 Over Confidence and Economic Risk—Evidence from China Hao Qingmin

99 Gleaning Inferences from Soldout Products

Xin Ge, Paul Messinger and Yuanfang Lin

4 The Logistics Performance and International Trade Youqin Pan

Parallel Session 5E

(A405, CEM, NUAA)

Contributed Session (II)

Chair:

Qiansheng Deng

14

Robust Design of a Strategic Network Planning for Photovoltaic Module Recycling Considering Reclaimed

Resource Price Uncertainty

Qiaofeng Li, Kanglin Liu and Zhi-Hai Zhang

32 Optimal Relief Order Quantity Under Stochastic Demand and Lead Time

Kanglin Liu, Zhi-Hai Zhang and Kamran Movahed

129 Study on the Control Measures of

MDRO Transmission in ICU Based on Markov Process

Zhu Min and QiangSu

114 A Data-Mining Algorithm for

Location Assignment of Outbound Containers

Qiansheng Deng and Canrong Zhang.

60 A Self-Learning Vehicle Routing Approach Using Inverse Optimization Sikun Xu and Lu Chen

16:00-17:40

Parallel Session 6A

(A302, MAB Building, NUAA)

Best Paper Competition

Chair:

Robin Qiu

12

Performance Analysis of a Security-Check System with Four Types of Inspection Channels for

High-Speed Rail Stations in China

Chia-Hung Wang and Xiaojing Wu

78

Developing a Production Structure Model Using Service Dominant Logic

- a Hypergraph-Based Modeling Approach

Mahei Manhai Li, Christoph Peters and Jan Marco Leimeister

120 The Value of Personalized Promotion: Field Experiment on O2O Platform

Hongyan Dai, Baile Lu, Yuqian Xu and Weihua Zhou

118 An Ontology Based Inference System for Group Activity Recognition Using

Multi-Layered HMMs Vinayak Elangovan

103 Dynamic Surveillance Strategies of Mobile Monitor to Map Precise Air

Pollution Distributions

Baoxian Liu, Yutao Ba, Dawei Zhang, Yunting Li, Xinxin An, Na Sun, Miao He and Guoxing

Wang

Parallel Session 6B

(A304, CEM

Healthcare Session (I)

5

Real-Time Scheduling of Emergency Patients by Considering Waiting Time

Targets

Jing Wen, Na Geng and XiaolanXie

- 25 -

,NUAA) Chair: Yu Wang 33

Integrated Scheduling for Elective Patients Under Surgery Duration

Uncertainty

Jian-Jun Wang, Hai-Guan Liu and Hong-Ru Miao

36 Scheduling and Sequencing of Unpunctual Patients Under a

Multi-Server Setting

Xingwei Pan, Na Geng and XiaolanXie

13 Mitigating Overtime Risk in Tactical Surgical Scheduling

Yu Wang, Jiafu Tang, Yu Zhang and Lim Andrew

54

What Factors Affect Doctors’ Willingness of Participation in

Telemedicine Service: QCA and Structural Equation Modeling

Analyses

Wan Mingshi

Parallel Session 6C

(A402, CEM, NUAA)

Sponsored Session (I)

Chair:

Tijun Fan

26 Dynamic Pricing and Replenishment Policy for Multi-Batch Fresh Products

Fan Tijun, Chang Xu and Feng Tao

44 Copyright Sharing and Compensation Contract Coordination in Streaming

Service Supply Chain Yifan Wu and ShiboJin

45 Effect of Partial Cross Holding

Between Competitors on Probabilistic Selling Strategy

Yifan Wu and Yaping Qu

105 Pricing and Inventory Decisions with

Multiple Types of Strategic Consumers

Tang Yuewu and Fan Tijun

41 Effect of Carbon Tax Policy on the

Development of Renewable Generation in the Coal-Power Industry

Gao Xiang Lou, Zhi Xuan Lai and Hai Yang Xia

Parallel Session 6D

(A404, CEM, NUAA)

Special Topic Session (III):

Managing Product Returns

Chair:

Jing Chen

79 Consumer Return Policies in Presence of a P2P Market Tingting Li

85 Coordination of a Decentralized

Supply Chain with Option Contracts in the Presence of Customer Returns

Chong Wang, Jiarong Luo and Lili Wang

128 Competing with Pricing and Customer Returns Policies Bintong Chen and Jing Chen

86 Supply Chain Coordination with

Customer Returns and Retailer'S Store Brand Product

Wei Li, Jing Chen and Bintong Chen

Parallel Session 6E

(A405, CEM, NUAA)

Contributed Session (III)

Chair: Yan Li

119 Teaching a Man to Fish: Teaching Cases of Business Analytics

Sung Hee Park, Soohoon Park and Linda Oldham

138 A Smart Institutional Research Decision Support System Grace Lin

42 Applications of Artificial Intelligence in Education Yan Li and Jing Ma

- 26 -

69 Research on the Influencing Factors of

Academic Innovation Based on Complex Networks

Lingfei Qian, Rong Wang and GuanglinWu

June 28 14:00-15:40

Parallel Session 12A (A302,CEM,

NUAA)

Healthcare Session (II)

Chair:

Jian-jun Wang

34 The Impact of Discriminative

Reimbursement Scheme on Healthcare Referral in a Two-Tier Service System

Zhong-Ping Li, Jian-Jun Wang and Xin-Mou Zhang

48 Data-Driven Teleconsultation

Appointment Scheduling Using Discrete-Event Simulation

Qiao Yan and Ran Lun

133 What Makes a Helpful Online Review for Healthcare Services? an Empirical

Analysis of Haodaifu Website Ya Gao and Ling Ma

9 Staffing Level Design Using

Multi-Fidelity Models for Outpatient Departments

Bowen Pang, XiaoleiXie, Yijie Peng and Bernd Heidergott

Parallel Session 12B (A304, MAB

Building, NUAA)

Sponsored Session (II)

Chair:

Yifan Wu

102 On the Uncertain Accuracy of

Seller-Provided Information in the Presence of Online Reviews

Tian Li and Zeting Chen

106 Route Planning for Vehicles with UAVs Based on Set-Covering Qiu Chen Gu and Ti Jun Fan

109 Improved Grey Forecasting Model

and Its Application in Shanghai Stock Market

Xingyuan Li, Yan Cheng and Huijie Peng

117

Impacts of Product Harm Crisis Response Strategies in Social Media: a Case Study of Samsung Galaxy Note

7

Qianyu Ma and Ying Li

Parallel Session 12C

(A402, CEM, NUAA)

Special Topic Session (IV):

Service Analytics and

Applications in Transportation

Chair:

Xin Jia Jiang

50

Evacuation in Urban Agglomeration via Multiple Transportation Modes: an Integrated Dynamic System Optimal

Model and Real-Life Case Study

Xin Yang

80 A Benders Decomposition Approach

for the Multi-Vehicle Production Routing Problem

Zhixing Luo

113 Solving the Intermodal Hub Location Problem with Fenchel Heuristic Canrong Zhang and Quan Zhu

7 Yard Crane Scheduling in a New Automated Container Terminal Design Xin Jia Jiang

Parallel Session 12D

(A404, CEM, NUAA)

Contributed Session (IV)

Chair:

Beibei Dong

15

The Correlative Factors Among Teenager Binge-Watching Behaviors,

Problematic Binge-Watching Behaviors, and Drama Transfer

Phenomenon in Taiwan

Fu-Yuan Hong and Der-Hsiang Huang

25 Understanding of Servicification

Trends in China Through Analysis of Inter-Industry Network Structure

Yunhan Liu and Dohoon Kim

101 Study on Argumentation-Based

Negotiation in Human-Computer Negotiation Service

Mukun Cao and Jing Gong

- 27 -

18 The Dual-Learning Process in

Customer Cocreation and Its Financial Impact

Beibei Dong and Jun Ye

46 Analysing Online Review Helpfulness

for Experience Goods with Review Content

He Chenglin, Li Shan and Ding Yu

Parallel Session 12E (A405,CEM,

NUAA)

Contributed Session (V)

Chair:

Victor Chan

1 Prototyping a Home-Based Early

Detection Toolkit for Persons with Possible Alzheimer’S Disease

Robin Qiu, Jason Qiu and Fengxue Zhang

123 Maintenance Architecture

Optimization of a Distributed CubeSat Network Based on Parametric Model

Honglan Fu, Hao Zhang and Yang Gao

68 Matching Anonymized Individuals with Errors for Service Systems Wai Kin Victor Chan

64 Distributed Demand Response Under Real Time Electricity Pricing Andrew Liu and Zibo Zhao

16:00-17:40

Parallel Session 13A

(A302, CEM, NUAA)

Healthcare Session (III)

Chair:

Qiushi Chen

23 Assortment Planning of Physician with Patient Choice

Hanqi Wen, Xin Pan and Jie Song

67 Overbooking for Specialty Clinics

with Patient No-Shows: a Queueing Approach

Zhenghao Fan, Xiaolei Xie, Reynerio Sanchez and Xiang

Zhong

84 Hospital Referral Operations Considering Revenue Sharing Yue Zhang and Na Li

82 Resource Allocation for Hepatitis C Elimination

Qiushi Chen, Turgay Ayer and Jagpreet Chhatwal

Parallel Session 13B (A304,CEM,

NUAA)

Special Topic Session (V):

Data Analytics and Artificial Intelligence in

Service

Chair: Guiping Hu

29 Machine Learning Methods for

Revenue Prediction in the Google Merchandise Store

Vahid Azizi and Guiping Hu

30 Predicting Metropolitan Crime Rates Using Machine Learning Techniques

Saba Moeinizade and Guiping Hu

31 Optimizing Machine Learning Bias and Variance with Ensembles Weights

Mohsen Shahhosseini, Guiping Hu and Hieu Pham

65 Crop Yield Prediction Using Deep Neural Networks

Lizhi Wang, FaezehAkhavizadegan and

Guiping Hu

Parallel Session 13C (A402, MAB

Building, NUAA)

Special Topic Session (VI):

Electric Vehicle

Industry

Chair: Ran Lun

11 Cleaning and Processing on Electric Vehicle Telematics Data

Shuai Sun, Jun Bi and Cong Ding

62 Energy-Storage Device Allocation and

Flexible Price in a Vehicle-to-Grid System

Ying Yin, Lun Ran, Zihao Jiao and Xin Liu

71

Research on Optimization Model and Algorithm of Electric Vehicle Routing

Problem Under Time-Dependent Network

Changshi Liu and Xiancheng Zhou

- 28 -

49 Shared Electric Cars: Several Topics in Operating Level Ruiyou Zhang

Parallel Session 13D

(A404, CEM, NUAA)

Contributed Session (VI)

Chair:

Robin Qiu

55

Missing Value Estimating Algorithm Based on Cloud Manufacturing Services QoS Time Series Data

Properties

Ying Yu and Jing Ma

74 Aviation Demand Forecast Based on Multivariate Time Series

Qi Li, Zengqiang Jiang, Mingcheng E and Xiangzhen Li

107

Identify Suspected Emission Events Applying to Air Pollution Control

Based on High Density IoT Monitoring Network

Baoxian Liu, Dawei Zhang, Feng Sun, Hongfei Hao, Kun

Han, Yutao Ba and Wenjun Yin

97 Multiple-Disease Risk Predictive

Modeling Based on Directed Disease Networks

Tingyan Wang, Robin Qiu and Ming Yu

77 A Fuzzy Detecting Method for ICP Flow Based on Recurrent Neural

Networks He Huang

Parallel Session 13E (A405,CEM,

NUAA)

Contributed Session (VII)

Chair:

Houping Tian

95 Eco-Labeling in Duopoly Market with Imperfectly Informed Consumers

Song Yang, Xia Haiyang and Fan Tijun

136

Study on the Relationship Between the Logistics Industry and

Macroeconomic Factors in China Based on the Grey Incidence

Guangxing Chu

35 How Do the Pricing Power and

Service Strategy Affect the Decisions of a Dual-Channel Supply Chain?

Houping Tian and Chaomei Wu

75

Strategies of Delay Delivery and Controllable Lead Time to Optimize

the Total Cost in Consignment Inventory

Chidurala Srinivas and A Ramnarsimha Reddy

17 Multi-Leadership in Closed Loop Supply Chain Based on Dual-Channel Xueqin Liu and Xu

June 29 13:10-14:50

Parallel Session 18A

(A302, CEM, NUAA)

Contributed Session (VIII)

Chair:

Xiaofeng Li

52

Machine Learning Based Cross-Border E-Commerce

Commodity Customs Product Name Recognition Algorithm

Jing Ma, Xiaofeng Li, Chi Li, Bo He and XiaoyuGuo

76 Using Service Science to Explicate the Relationship Between Innovation and

Revenue Growth

SeidaliKurtmollaiev, Anneline Solberg, Emilie Kaasin and Per

Egil Pedersen

130 The Empirical Research on Key

Factors of Manufacturing Companies Quality Management

Jian Hua Yang and Yanyan Jia

57

Value Co-Creation Model Based on Open Innovation in Planning

ICT-Based Tourism Innovation, Indonesia

Santi Novani, Citra Brilliane and AfinaVindiana

70

The Impact of Live Video Streaming Technical Environment on Purchase

Intention: a Social Support Perspective

Min Zhang and Fang Qin

- 29 -

Parallel Session 18B

(A304, CEM, NUAA)

Contributed Session (IX)

Chair:

Lin Xiao

87 Airworthiness Evaluation Model Based on Fuzzy Neural Network

JinJieru, Shen Yang and Zhang Kaixi

116 Structure Evolvement and Equilibrium

Analysis of International Credit Rating Market

Xuewei Huang, Jianling Wang and FengzhiLv

122 The Study of Fresh Products

Supplier’S Comprehensive Evaluation Based on Balanced Scorecard

Xinyu Ma and Qing Zhang

28 Offensive Strategic Innovation: a Service Perspective Chaoren Lu

61 Vehicle Routing Problem of Fresh Agricultural Products Considering

Decaying Factor

Shu-Xia Li, Hui-Min Fang, Li-Ping Liu and Zhen Chen

15:10-16:50

Parallel Session 19A (A302,CEM,

NUAA)

Contributed Session (X)

Chair:

Yong Wu

16 LSTM-Based Neural Network Model for Semantic Search

Xiaoyu Guo, Jing Ma and Xiaofeng Li

93 Multiple Yard Crane Scheduling with Variable Crane Handling Time Yong Wu

2 A Qualitative Study of TQM and Learning Orientation in Service Sector: the Role of Management

Yingying Liao and Ebrahim Soltani

90

Better to Deliver Tomorrow Morning than Later Today? Time of Day Effect

on Logistics Service Ratings: Evidence from Online Reputation

Systems

Heng Chen, Fei Song, Yuhang Xu and Kunpeng Zhang

Parallel Session 19B

(A304, CEM, NUAA)

Contributed Session (XI)

Chair:

Junwei Wang

127 Profit or Market Thickness? Order

Allocation Mechanisms with a Hybrid Workforce

Eryn Juan He and Joel Goh

137 Study of the Interactions Between Schemes with Capacity Theory Ling Zhang and Chenyu Li

139 Overview and Outlook of Studies on

Inter-Regional Collaborative Innovation

Hecheng Wu

132 Resilience Measurement of the Financial System Considering

Recovery Solutions J.W. Wang and Mingying Song

6 A Recommendation Approach for

Personalized Service Design Based on BPNN and LFM

XiuliGeng, Yongzheng Zhang and Yela Chen

- 30 -

Key Contacts

Medical Service 1 Medical Emergency: In case of a medical emergency, please call 120 immediately, and then

notify the conference staff. Campus Hospital of NUAA: Xiehe Liu Tel: +86-25-52119819

2 Hospital Contact Information： Nanjing Gulou Hospital Address: 321 Zhongshan Road, Gulou District, Nanjing Tel: +86-25-83106666

Staff Phone Email

Shan Li (Chief Coordinator) +86 13813834822 lishan@nuaa.edu.cn

Lili Liu (Chief Coordinator) +86 13913344261 Llily8587@gmail.com

Jing Ma (Chief Coordinator) +86 13915970725 Majing5525@126.com

Reception Group

Jian Chen (Accommodations, etc.) +86 15950526889 jchen@nuaa.edu.cn Zhengjun Luo (Lunch and dinner) +86 13951602104 andrewluo@nuaa.edu.cn Mingbao Zhang (Transportation) +86 13605196686 ZMB7381@126.com

Registration Group

Lili Liu (Registration, Cashier, Invoice) +86 13913344261 Llily8587@gmail.com Lin Xiao (Conference documents,etc ) +86 17372264202 xiaolin@nuaa.edu.cn

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Brief Travel Guides and Local Transportation Information

Shuttle Bus & Shuttle Bus Transportation

Shuttle Bus transfer passengers between Crowne Plaza and NUAA. It is 4kilometers (approximately ten minutes) between Crowne Plaza and NUAA.

Shuttle Bus Schedule

Date Departure Time Origin Destination Vehicle Plate

Numbers Number of

Buses

June 27 07:50 Crowne Plaza

College of Economics and Management (CEM),

NUAA 2

20:00 Cuiping Yuan Restaurant Crowne Plaza 2

June 28

07:50 Crowne Plaza College of Economics

and Management (CEM), NUAA

2

17:40 College of Economics

and Management, NUAA

Crowne Plaza 3

June 29 07:50 Crowne Plaza

College of Economics and Management (CEM),

NUAA 2

19:00 Cuiping Yuan Restaurant Crowne Plaza 2

Airport & Airport Transportation

Nanjing Lukou International Airport: http://www.njiairport.com/

It is 28 kilometers (approximately forty minutes) from Nanjing Lukou International Airport to Nanjing University of Aeronautics and Astronautics (Jiangjunlu campus) or area hotels.

Subway information:http://www.njmetro.com.cn/njdtweb/home/go-dtmain.do

From Lukou International Airport to Crowne Plaza Hotels & Resorts: Take Airport Line S1 at Lukou International Airport Station, transfer Line 1 at Nanjing South Railway Station and get off at Shengtailu Station

From Lukou International Airport to Nanjing University of Aeronautics and Astronautics: Take Airport line S1atLukou International Airport Station and get off at Cuipingshan Station

Airport taxi information: http://www.njiairport.com/traffic/60.html

Airport shuttle bus information: http://www.njiairport.com/traffic/59.html

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Railway & Railway Transportation

Official website to book railway tickets: https://www.12306.cn/index/

It is 16 kilometers (approximately one hour) from Nanjing Railway Station to Nanjing University of Aeronautics and Astronautics (Jiangjunlu campus) or area hotels.

It is 3 kilometers (approximately twenty minutes) from Nanjingnan Railway Station to Nanjing University of Aeronautics and Astronautics (Jiangjunlu campus) or area hotels.

Subway information: http://www.njmetro.com.cn/njdtweb/home/go-dtmain.do

From Nanjing Railway Station to Nanjing University of Aeronautics and Astronautics: Take Line 1 at Nanjing Railway Station, transfer Airport line S1 at Nanjing South Railway Station and get off at Cuipingshan Station

From Nanjing Railway Station to Crowne Plaza Hotels & Resorts: Take Line 1 at Nanjing Railway Station and get off at Shengtailu Station.

From Nanjingnan Railway Station to Nanjing University of Aeronautics and Astronautics: Take Airport line S1 at Nanjing South Railway Station and get off at Cuipingshan Station

From Nanjingnan Railway Station to Crowne Plaza Hotels & Resorts: TakeLine 1 at Nanjing South Railway Station and get off at Shengtailu Station

Please see Guidance Map6 for more information.

Traveling by Automobile or Rental

Guests who come by driving are suggested to enter through east gate of Nanjing University of Aeronautics and Astronautics, which is near theConference Center.

From Nanjing Lukou International Airport to East gate of Nanjing University of Aeronautics and Astronautics

1. Drive on Welcome Avenue for 1.1 kms to Ningxuan Expressway. 2. Drive on Ningxuan Expressway for 23.1 kms to Cuipingshan Service Area. 3. Drive on Cuipingshan Service Area for 840 meters and turn right to Tianyuan West Road. 4. Drive on Tianyuan West Road for 400 meters and turn left to Jinghuai Avenue. 5.Drive on Jinghuai Avenue for 1 km and East gate of Nanjing University of Aeronautics and Astronautics will be on your left.

From Nanjing Lukou International Airport to Crowne Plaza Hotels & Resorts

1. Drive on Welcome Avenue for 1.1 kms to Ningxuan Expressway.

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2. Drive on Ningxuan Expressway for 23.1 kms to Cuipingshan Service Area. 3. Drive on Cuipingshan Service Area for 400 meters to Tianyuan West Road 4. Turn right and drive on Tianyuan West Road for 1.1km meters to Liyuan Middle Road. 5. Turn left and drive on Liyuan Middle Road for 400 meters to Jiahu West Road. 6. Turn right and drive on Jiahu West Road for 600 meters to Bailongqiao Road. 7. Turn right and drive on Bailongqiao Road for 800 meters to JiahuEast Road. 8. Drive on Jiahu East Road for 800 meters to Crowne Plaza Hotels & Resorts.

From Nanjingnan Railway Station to East gate of Nanjing University of Aeronautics and Astronautics

1. Drive on Lvdu Avenue for 700 meters to Hongyun Avenue. 2. Turn left and drive on Hongyun Avenue for 1.3 kms. 3. Turn right and drive on Mingcheng Avenue for 1 kms to Liyuan North Road. 4. Drive on Liyuan North Road for 600 meters and turn right to Shengtai Road. 5. Drive on Shengtai Road for 1.5 kms and turn left to Jinghuai Avenue. 6. Drive on Jinghuai Avenue for 500 meters and East gate of Nanjing University of Aeronautics and Astronautics will be on your right.

From NanjingnanRailway Station to Crowne Plaza Hotels & Resorts

1. Drive on Lvdu Avenue for 700 meters to Hongyun Avenue. 2. Turn left and drive on Hongyun Avenue for 800meters to Mingcheng Avenue. 3. Turn right and drive on Mingcheng Avenue for 1.2 kms to Liyuan North Road. 4. Drive on the Liyuan North Road for 582meters to Shengtai Road. 5. Turn left and drive on Shengtai Road for 1000meters to Jiahu East Road. 6. Turn right and drive on Jiahu East Road for 300 meters to Crowne Plaza Hotels & Resorts.

From Nanjing Railway Station to East gate of Nanjing University of Aeronautics and Astronautics

1. Drive on Longpan road for 2.5 kms and turn right to Inner Ring East Line. 2. Drive on Inner Ring East Line for 7.4 kms. 3. Take the exit on the left toward Longpan South Road. 4. Continue onto Longpan South Road for 1.5kms and drive onto Weiba Road. 5. Turn left and drive onto Airport Road for 2 kms. 6. Keep right to continue toward Shengtai Road for 210 meters. 7. Keep left at the fork to continue toward Shengtai Road for 1.4 kms. 8. Continue toward Shengtai Road for 2 kms. 9. Turn right onto Shengtai Road and turn left at the 3rd cross street onto Xuefu Road. 10. Turn left onto Shengtai West Road and drive for 900 meters. 11. Turn right to Jinghuai Avenue for 500 meters and East gate of Nanjing University of Aeronautics and Astronautics will be on your right.

From Nanjing Railway Station to Crowne Plaza Hotels & Resorts

1. Drive on Longpan road for 2.5 kms and turn right to Inner Ring East Line. 2. FollowInner Ring East Line for 7.4 kms to Longpan South Road. 3. Continue onto Longpan South Road and take the exit toward Kazimen Avenue.

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4. Keep left at the fork and merge onto Kazimen Avenue. 5. Continue onto Shuanglong Avenue for 4.3 kms and slight right onto Shuanglong Avenue Side Road for 450 meters. 6. Turn right onto Hubin Road and drive for 220 meters. 7. Turn left and drive for 35 meters. 8. Turn right and Crowne Plaza Hotels & Resorts will be on your left.

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Map Guidance Map1: Nanjing University of Aeronautics and Astronautics,

Conference Center at Jiangjunlu Campus

Line form the Crowne Plaza to CEM

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Guidance Map2:Plan of CEM 3F

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Guidance Map3: Plan of CEM4F

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Guidance Map4: Cuipingyuan Restaurant, NUAA

Line from CEM to Cuipingyuan Restaurant

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Guidance Map5: Plan of Crowne Plaza

Registration, Crowne Plaza 1F

Banquet: Zijing A, Crowne Plaza 2F

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Guidance Map6: Plan of Nanjing University of Aeronautics and Astronautics, Jiangjunlu Campus

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Guidance Map7: Nanjing Railway Station, Nanjingnan Railway Station, NUAA, Crowne Plaza, Nanjing Lukou International Airport and related

subway stations

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Introduction to INFORMS Conference on Service Science 2019 INFORMS Conference on Service Science (ICSS2019) program committee is committed to organizing a quality program with diverse participants sharing their vision, knowledge and experience in Service Science Research, Education, and Applications. The conference theme is Smart Service Systems, Operations Management, and Analytics.

This conference presents excellent opportunities for you to present your Service Science related

research, education, and implementation work, to learn about the emerging technology and applications, and to network with international leaders of the profession in the field. We invite you to submit a paper/abstract. Accepted full papers will be published in a proceedings by Springer.

Introduction to NUAA The Nanjing University of Aeronautics and Astronautics (NUAA) is one of China’s premier learning and research institutions, now developing into a comprehensive university from its base in Aerospace Engineering. Ever since it was established in 1952, this venerable academic institution strived to be known for world-class research and education. During its 66-year history, NUAA has made remarkable progress in its many educational and research activities.

Academia and education at NUAA represent strong capacity among all the universities in China. It has acquired national status through the excellence of its research work, especially in the areas of Aerospace Engineering, Mechanics, Electromechanics, Economics and Management, etc.

Our university’s laboratories are a constant source of new ideas, especially in the fields of Aircraft Design, Dynamics, Mechanics, Manufacturing, Automation, Unconventional Machining, etc. Through the diverse research and teaching activities, we are striving to provide the highest quality of educational experience for students to meet the current needs of society, endowing them with a passport to the professional world and cultivating them into future pioneers in the fields of science and technology. NUAA will construct high-level research-oriented university featured with Aeronautics, Astronautics and Civil Aviation, with coordinated development of other disciplines including literature, law, philosophy, etc.; fostering highly-qualified citizens and innovative pioneers and spreading its academic wings to the nation as well as to the world.

Introduction to CEM The College of Economics and Management (CEM) traces its origin to the section of management sciences affiliated with NUAA since 1980, consisting of 3 departments: Management Science and Engineering, Business Administration, and Economics. Now CEM has three provincial research bases and a batch of scientific research institutions with great influence in the society. Management Science and Engineering has been ranked A+ among peer colleges in China, and classified as 1st-level key disciplines in Jiangsu Province. In 2012, Management Science and Engineering was ranked 14 out of 102 by the Ministry of Education in China (Tied for 6th). System engineering is listed as the key discipline of National Defensive Construction; Industrial Engineering is listed as a Key construction major of universities in Jiangsu. Industrial engineering, information management and information system have been named the strongest majors in the national professional ranking of colleges and universities. Industrial Engineering is listed as a brand major of Jiangsu province and of MIIT (Ministry of Industry and Information Technology of the People’s Republic of China). Business Management and Accounting have been named the featured major of Jiangsu province.

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Attractions Nanjing is the capital of Jiangsu Province in East China, running through the city are lower reaches of the Yangtze River whose estuary is not far away. Nanjing enjoys a civilization of over 6000 years and the city itself was founded 2500 years ago. As one of the Four Ancient Capitals, Nanjing is a vital cradle of Chinese civilization and over a long stretch of time, it has been the political and cultural pivot of South China, thus dubbed as the Capital of Ten Ancient Dynasties, rich in both cultural heritage and historical relics. Among the landmarks of Nanjing there are the Ming Xiaoling Mausoleum, Dr. Sun Yat-sen Mausoleum, Xuanwu Lake, Presidential Palace and Confucius Temple.