Keynote Speaker I

Prof. Luiz Moutinho
University of Suffolk, England

Professor Luiz Moutinho (BA, MA, PhD, FCIM) is Visiting Professor of Marketing at Suffolk Business School, Faculty of Arts, Business and Applied Social Science, University of Suffolk, Ipswich, England, Adjunct Professor of Marketing at Graduate School of Business, University of the South Pacific, Suva, Fiji, and Visiting Professor of Marketing at Universidade Europeia and the Marketing School, Portugal.

During 2015 - 2017 he was professor of BioMarketing and Futures Research at the DCU Business School, Dublin City University, Ireland. This was the first Chair in the world on both domains - BioMarketing and Futures Research. Previously, and for 20 years, he had been appointed as the Foundation Chair of Marketing at the Adam Smith Business School, University of Glasgow, Scotland. In 2017 Luiz Moutinho received a degree of Professor Honoris Causa from the University of Tourism and Management Skopje, FYR of Macedonia.

He completed his PhD at the University of Sheffield in 1982. He has been a Full Professor for 29 years and held posts at Cardiff Business School, University of Wales College of Cardiff, Cleveland State University, Ohio, USA, Northern Arizona University, USA and California State University, USA. He has held Visiting Professorship positions at numerous universities in China, Lithuania, Austria, New Zealand, Denmark, Slovenia, Portugal, Hungary, Taiwan, Brazil, Colombia and Cyprus.

Between 1987 and 1989 he was the Director of the Doctoral Programmes at the Confederation of Scottish Business Schools and at the Cardiff Business School between 1993 and 1996. He was Director of the Doctoral Programme in Management at the University of Glasgow between 1996 and 2004.

Professor Moutinho is the Founding Editor-in-Chief of the Journal of Modelling in Management (JM2) and co-editor of the Innovative Marketing Journal. He has another 4 Associate Editorships as well as being in the Editorial Boards of another 47 international academic journals.

His areas of research interest encompass bio-marketing, neuroscience in marketing, EmoWear - a wearable tech device that detects human emotions, evolutionary algorithms, human-computer interaction, the use of artificial neural networks in marketing, modelling consumer behaviour, futures research, marketing futurecast and tourism and marketing. Other primary areas of Professor Moutinho’s academic research are related to modelling processes of consumer behaviour. Currently, he is Program Designer and Faculty Member at Neuroscience Ltd. (Neuroscience - Academic and Business Solutions).

He has developed a number of conceptual models over the years in areas such as tourism destination decision processes, automated banking, supermarket patronage, among other areas. The testing of these research models has been based on the application of many different statistical, computer and mathematical modelling techniques ranging from multidimensional scaling, multinomial logit generalised linear models (GLMs) and linear structural relations to neural networks, ordered probit, simulated annealing, tabu search, genetic algorithms, memetic algorithms and fuzzy logic.

Professor Moutinho has over 150 articles published in refereed academic journals, 32 books and more than 10,800 academic citations, a h-index of 49 and an i10-index of 156 (by the end of 2017).

Speech Title: Trending THE FUTURE... from Amplified Senses, Sensing-as-a-Service, Sensing Enterprise, MiFi, Tele-Presence and Spectral Tech... to Thinking Spaces, Modular Smartphones, Humarithms, Androrithms and Augmented Humanity...

Abstract: The talk starts with emphasize of necessity to anticipate unknown future. Six new trends related to changes in the world of collaborative economy, with people coming in the focus, will be introduced. Although due to latest technologies almost everything can be digitalised and automated and technology is entering in all segments of peoples’ lives, the middle of humans’ interest is more and more occupied with issues like trust and sense... This presentation with encompass many different technological and human-related trends and topics from genomics, collaborative economy, a digitized world ,amplified senses, cloud-based machine intelligence, live social semantics, Web 4.0 - a Web of connected intelligences, humanizing technologies to sensing-as-a-service, little data, personal resource planning (PRP), holographic companies ,androrithms and the age of augmented humanity.

Keynote Speaker II

Prof. Ruay-Shiung Chang
National Taipei University of Business, Taiwan

Dr. Chang received his B.S. degree for the department of Electric Engineering, National Taiwan University in 1980. After 2 years’ military service, he joined the China Steel Corporation in 1982. In CSC, Dr. Chang was responsible for the management and maintenance of process control computer system of the hot strip mill. After one year of service, he went to the Institute of Computer Science in National Tsing Hua University for advanced studies, where he received his Ph.D. degree in 1988. From 1988 to 1992, Dr. Chang worked for the Chung Shan Institute of Science and Technology (CSIST), the major research body of the Ministry of Defense, Taiwan, as a research scientist. In his four years’ tenure at the CSIST, he developed the prototype for the C3I (Command, Control, Communication and Intelligence) system of Taiwan’s joint armed forces. The advanced version of this system is still in operation now.

After leaving CSIST, Dr. Chang joined the Department of Information Management, National Taiwan University of Science and Technology (NTUST) as an associate professor. In NTUST, Dr. Chang research focused on the design and development of network management system and on the Internet. At that time, the Internet was on the infant stage. But Dr. Chang saw its potential and wrote three articles to introduce the Internet status in Taiwan, China, and Japan, which were published in IEEE Internet Computing Magazine 1997.

Dr. Chang also served actively for many volunteer jobs in the academic field. He organized the 14th Workshop for Discrete Math and Computing Theory, held in NTUST. He also served as the program committee many times for the National Computer Symposium and the International Computer Symposium, the two most important annual conferences in Taiwan for the computing field. He published his first review article for ACM Computing Reviews in 1994. Since then, he has published more than 100 review articles in ACM Computing Reviews.

In 1998, Dr. Chang joined the Department of Computer Science and Information Engineering, National Dong Hwa University (NDHU) and served as the chairperson. In his three years’ tenure, he strengthened the research activities of the department, enriched the faculty lineup, and successfully established the Ph.D. program of the department.

Due to his excellent performance in the department chair, Dr. Chang was promoted and appointed as the Dean of Academic Affairs (Provost) of NDHU in February 2002. In this position, he successfully promoted the academic standards of the university. With a fine and detailed proposal, Dr. Chang also helped to acquire the Teaching Excellence Project for NDHU from the Ministry of Education, Taiwan. Out of a total of 76 Higher Education Universities, only 13 were granted this project. With this distinguished service, Dr. Chang was appointed as the Vice President of the University in February 2006.

Because of his excellent academic credentials and contributions, Dr. Chang was selected as the President of Taiwan Hospitality and Tourism College in August, 2012, a 4-year higher education institute specialized in Hospitality and Tourism. During his tenure, Dr. Chang promoted the reputation and quality of THTC profoundly.

Due to his excellence performance in THTC, Dr. Chang is selected as the new President of National Taipei University of Business from April, 2014 by a 15 member searching committee.

Besides academic career, Dr. Chang is also very active in serving the academics in particular and other fields in general. He is a founding and permanent member of the Institute of Information and Computing Machinery of Taiwan, a senior member of IEEE, and a professional member of ACM. From 2004 to 2007, he served on the advisory council of the Public Interest Registry (www.pir.org). From 2005, he serves as the vice chair of ACM Taipei Chapter. He is also on the IASTED technical committee on the web, the Internet, and multimedia and IASTED technical committee on Telecommunications. Furthermore, Dr. Chang serves on the technical program committee for many international conferences, including International Communication Conference, International Wireless Communications and Mobile Computing conference, Grid and Pervasive Computing conference, International conference on Pervasive Computing, and so on.

Dr. Chang supervises more than 50 master students and 10 Ph.D. students to graduation. He also publishes actively in many international journals and conferences. For his contribution, Dr. Chang received the Outstanding Information Technology Elite Award from the Taiwan's Information Month Committee in 2009.

Keynote Speaker IV

Prof. Lichung Jen
National Taiwan University, Taiwan

Speech Title: Comparing Apples and Oranges: Eliminating Individual and Product Heterogeneity in Teaching Evaluation
Abstract: In the age of information overload, the enormous quantity of information has compelled consumers to rely on customer ratings to quickly identify desired products or services from tens of thousands of products or services. However, research on customer ratings in e-commerce should not merely focus on consumers’ scale usage or their preferences and attitude toward various products; researchers should also consider the fact that product ratings are provided by various individuals who have varying standards. For example, apples and oranges are essentially different types of a product, and their overall satifaction ratings are not necessarily based on the same group of consumers or standards. This can result in a lack of objectivity when comparing varying product types, which can lead to wrong decisions. Therefore, this study aims develop a statistical model enables consumers to objectively make cross-products/services comparisons by controlling biases generated from (a) source of different evaluators, especially, when the sample size is small, (b) product characteristics, (c) respondents’ individual characteristics, and finally, (d) the bias of scale usage heterogeneity, in particular, when adopting multi-item scales on evaluating multiple products. The results suggest our model effectively and objectively evaluates the quality of products/services. Managerial implications and limitations are also discussed.

Keynote Speaker IV

Prof. Kun-Huang Huarng
Feng Chia University, Taiwan
 

Prof. KUN-HUANG HUARNG received Ph.D. in Texas A&M University, Texas, U.S.A. (1993). And he is now Professor of International Business, Feng Chia University, Taiwan; Dean in College of Business, Feng Chia University, Taiwan; Associate Editor in Journal of Innovation & Knowledge; Editor-in-Chief in International Journal of Business Economics; Associate Editor in Journal of Business Research; Founder Governor of Global Innovation and Knowledge Academy (GIKA). Also, he is Life Fellow of International Society of Management Engineers and received Outstanding Service Award in the Literati Network 2008 Awards for Excellence, Emerald (2008).
Speech Title: Qualitative analysis of housing demand by using Google Trends
Abstract: Housing accounts for 30% more of the consumer price index (CPI) which is also the largest of the constituting categories. On the other hand, housing takes a big part of consumer spending. Hence, housing demand modeling and forecasting is an interesting and important research topic. Housing demand is often treated as a time series problem. Mainly, housing demand modeling and forecasting relies on secondary data. In addition, seasonality is one of the key factors in the modeling. Hence, most studies use quantitative methods to tackle the problem. This study intends to tackle the same problem with very different approaches. First, this study uses qualitative method, instead of quantitative, to conduct the time series analysis. How can a qualitative method solve a time series problem? Second, ready-to-use open data, Google Trends, are used as the target. Can a relative index be used for forecasting? Third, in addition to in-sample modeling, this study also conducts out-of-sample forecasting. Fourth, can better forecasting performance be achieved? Fuzzy set/qualitative comparative analysis (fsQCA) is used as the analytic tool, a popular qualitative method. FsQCA is also suitable to solve the problems of small data sets, which fits the data of this study.

Plenary Speaker

Prof. Hsin-Hung Wu
National Changhua University of Education, Taiwan

Prof. Hsin-Hung Wu is University Distinguished Professor and Interim Chair Department of Business Administration, College of Management National Changhua University of Education, Changhua, Taiwan. He got Ph.D. in Industrial & Systems Engineering and Engineering Management, The University of Alabama in Huntsville, Huntsville, USA, 1998; M.S. in Industrial & Manufacturing Systems Engineering, The University of Texas at Arlington, Arlington, USA 1994 and B.S. in Industrial Engineering and Enterprise Information, Tunghai University, Taichung, Taiwan, 1993.
Speech Title: A Data Mining Approach to Analyze Outpatient Loyalty and Value from A Medical Center
Abstract: Data mining technique enables the hospital to identify loyal patients and potential patients’ needs from the database to assist hospital management to make decisions. Hospital management can deploy limited resources, develop effective strategies to provide needed medical services for patients, and then establish and maintain the hospital’s competitive advantage. A case study in a medical center is used to analyze customer value and consumer behavior of outpatients such that hospital can use the reference to deal with the related patient management issues. A combination of LRFM model, self-organizing maps, and K-means method is applied to cluster 321,908 outpatients into twelve groups and then further categorize outpatients into core customer groups, potential customer groups, new customer groups, lost customer groups, and resource-consuming customer groups. In doing so, the hospital can develop the optimal service strategies, provide the best care services, improve hospital’s performance, and reduce the cost so as to establish quality relationships with patients.