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
Ruay-Shiung Chang (張瑞雄) received his B.S.E.E. degree from National Taiwan University in 1980 and his Ph.D. degree in Institute of Decision and Computer Science from National Tsing Hua University in 1988. After graduation, he had worked for Chung Shan Institute of Science and Technology, National Taiwan University of Science and Technology, National Dong Hwa University, and Taiwan Hospitality and Tourism College. Right now, he is the President of National Taipei University of Business. His research interests include Internet, wireless networks, and cloud computing. NTUB is a traditional and the oldest business university in Taiwan. Dr. Chang hopes to bring modern Information and Communication Technology into the teaching and research of NTUB.
Dr. Chang is the President of Taiwan Institute of Information and Computing Machinery. Dr. Chang also served on the advisory council for the Public Interest Registry (www.pir.org) from 2004/5 to 2007/4. In 2009, Dr. Chang received the Outstanding Information Technology Elite Award from the ROC Information Month Committee.
Blockchain and Its Applications
Abstract: Blockchain is currently one of the hottest technologies that is said to change the future ways of doing business. Originally used in the digital currency called Bitcoin, Blockchain is actually a data structure with algorithms to manipulate the data structure. In this talk, we introduce what is Blockchain and how to use it. Various applications of Blockchain are also discussed
Keynote Speaker IV
Prof. Lichung Jen
National Taiwan University, Taiwan
Professor Lichung Jen, a citizen of Taipei, Taiwan, currently serves as the Director of Global Branding and Marketing Research Center and also a Marketing Professor in the Department of International Business at National Taiwan University. He is also Chief Secretary of Taiwan Institute of Marketing Science (TIMS), Chairmen of Chinese Applied statistics Association (CASA), Chairmen of Chinese Applied statistics Association (CASA), Chairman of Taiwan Institute of International Business Studies (TIIBS), and also the Head of Editor of Taiwan Journal of Marketing Science (TJMS).
Professor Jen has been involved in research projects and lectures for more than 30 well-known enterprises including Chunghwa Telecom in Taiwan, IBM, Cathay Bank, Ford Motor, China Petroleum, Panasonic and many more.
In the western countries, a lot of well-known journals have published his researches and thesis, such as Journal of Marketing Research, Journal of American Statistics Association, Journal of Business & Economic Statistics, Marketing Letters, and Industrial Marketing Management, allowing him to be nominated as an awardee of the Best Thesis Award by Journal of American Statistics Association in 1999. He has also gotten grants from Taiwan National Science and Technology Council and published 7 books. Over the years, he advised more than 200 MBA theses and 10 Ph.D. dissertations.
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.
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.
Assoc. Prof. David Pendery
National Taipei University of Business, Taiwan
David Pendery was born in Cincinnati, Ohio, and grew up in Albuquerque, New Mexico. He moved to San Francisco when he was 24, where he lived for ten years. He was an electrician at that time. He received his B.A. in International Relations for San Francisco State University. He moved to Boston in 1996, and received his M.S. in Journalism from Boston University. He moved back to San Francisco where he worked as a journalist, before moving to New England where he was a technical writer. He relocated to Taipei, Taiwan in 2000, and has worked here as teacher, English consultant and editor. He is current Associate Professor at National Taipei University of Business. He is married with one daughter.
The Next Wave in Sales and Purchasing: Bricks and Mortar are Not
Abstract: The presentation is entitled “The Next Wave in Sales and Purchasing: Bricks and Mortar are Not Dead!.” The topic covers new developments and technologies that are being used in regular, offline stores, and how that is reinventing this type of sales. Main ideas include:
1. The New Model in offline stores in which retailers are transforming from order fulfillment centers into experience-dominant centers;
2. “Supercharging,” in which customers are served in small-footprint locations that contain no inventory;
3. The combined “head office/showroom” in which combined functions give customers a “feel” for the brand;
4. Smaller footprint, tech-enabled, high-touch, creative spaces are proving effective for retailers now built with “bricks and bytes.”