Prof. Shaofeng Liu
Plymouth University, UK

Shaofeng Liu is Professor of Operations Management and Decision Making at University of Plymouth, UK. She is the Research Director for the Product and Service Value Chain Group, specializing in digital business, knowledge management, decision making, and value chain innovation. She obtained her PhD degree from Loughborough University, UK. She sits on the Management Board for Euro Working Group on Decision Support Systems. She is currently a Senior Editor for Cogent Business and Management, and on Editorial Boards for a number of international journals. She has undertaken a number of influential research projects funded by UK research councils and the European Commission with a total value over €40M. She is currently principal investigator and co-investigator for 4 EU projects (3 of which are funded by Horizon 2020 and one by Erasmus Plus) and 1 project funded by UK research council - Innovate UK. She has published over 150 peer-reviewed research papers.

Speech Title: A Holistic Framework for E-government to Transform Business Services
Abstract: Along with business globalisation, it was estimated that over 40 percent of a business’s expenditure has been invested in IT technologies to digitise it operations, such as through e-procurement, e-distribution, e-marketing and e-transactions. In parallel, public organisations such as government agencies have been taking advantage of the IT technologies to provide first class services to their businesses and citizens. E-government revolution has played a key role in respective local, regional and national economies in the last few decades. The need for alignment between business and digital technology domains has been identified by many researchers and practitioners as an important topic in e-government today. As a result, there have been a significant number of studies that have been undertaken to discuss various types of decisions on the alignment. In the meantime, various decision models and frameworks have been proposed which have helped e-governments to achieve various levels of performance.
  This keynote speech critically analyses work on Business and Information System Alignment (BISA) decisions, from both horizontal and vertical perspectives. The horizontal perspective looks at the whole breadth of the alignment, including strategic, functional, structural, cultural and social dimensions. The vertical perspective involves all stages of the alignment lifecycle, involving modelling, evaluation and improvement. As a result, a holistic framework is developed to integrate the two perspectives. The key contributions of the critical analysis are two folds: to highlight the key issues and challenges faced by the BISA in e-governments’ business management, and to identify opportunities for future research. Both academic researchers and management practitioners should be able to refer to the holistic framework when endeavouring BISA to avoid unnecessary pitfalls (misalignment) and better explore potential alignment opportunities.


 Prof. Yixun Shi
Bloomsburg University of Pennsylvania Bloomsburg, USA

Yixun Shi, Professor of Mathematical and Digital Sciences at the Bloomsburg University of Pennsylvania, USA. He earned his Ph.D. from the University of Iowa in USA, and has been a faculty at Bloomsburg University of Pennsylvania since 1992. His research areas include mathematical modeling and applications in finance and management, numerical optimization, applied statistics, and mathematical education. He is also serving as the editor-in-chief of two mathematics journals and one education journal.

Speech Title: Mathematical Models for the Demand of Luxury Goods in China
Abstract: Since China opened up its economy about 30 years ago, the nation has been growing amazingly rapidly in terms of gross domestic product (GDP) as well as in terms of consumption market demand. While almost all sections of China’s domestic demand are growing, the growth of the demand for luxury goods is much faster than all others. In this talk, we introduce a few mathematical models for studying the market demand for luxury goods in China. We apply a Markov chain model with changing transition matrices to analyze consumer behaviors in China’s luxury goods market, we suggest a linear regression model to explore the interactions among the luxury goods demand and various other factors in economics and social values, and we use a dynamical system model to estimate the long term trend of the market demand for luxury goods in China.

Prof. Donald Chang
Metropolitan State University of Denver, USA

Dr. Chang received his MBA and Ph.D. in marketing from University of Missouri-Columbia, BBA from National Chengchi University, Taiwan. His main teaching interests include international marketing, marketing research, and marketing strategy. Dr. Chang’s main research interests include strategic marketing, international marketing, crosscultural research, international leadership behavior, market orientation, service quality management, market research, innovation management, tourism and destination marketing, pricing strategy, among others. He has been a marketing educator since 1980s at a number of universities in the States and in Taiwan, including University of Missouri, University of Wisconsin, National Chengchi University (Taiwan), Tunghai University, Loyola University, and currently a senior professor at the Metropolitan State University of Denver.

Speech Title: Finding the Green Consumer
There are many obstacles facing firms that are interested in developing and promoting products that are friendlier to the natural environment, e.g., the uncertainty in determining the proper target market and the demand for such products, the difficulty in measuring the consumer’s readiness for such products, among others. To overcome some of such obstacles, it is essential to have an adequate measurement method to predict the consumer’s actual purchase behavior for green goods. A logit regression model is used to show how the consumer’s adoption of green products can be predicted from green related constructs. The proposed model can be applied to various product categories with minor adaptions. It could help firms in determining whether it economically feasible to promote related green products and how to choose proper target markets.


Prof. Alessio Ishizaka
Portsmouth Business School, University of Portsmouth, UK

Alessio Ishizaka is Full Professor in Decision Analysis, research lead and Deputy Director of the Centre of Operations Research and Logistics (CORL) at the Portsmouth Business School of the University of Portsmouth. He received his PhD from the University of Basel (Switzerland). He worked successively for the University of Exeter (UK), University of York (UK) and Audencia Grande Ecole de Management Nantes (France). He has been visiting professor at the Università del Sannio, Politecnico di Torino, Università degli Studi di Trento, INSA Strasbourg, Université de Lorraine, Universität Mannheim, Università degli Studi di Modena e Reggio Emilia, Universität der Bundeswehr Hamburg, Université d’Aix-Marseille, Università degli Studi di Torino, Università degli Studi della Tuscia and Università degli Studi di Padova. His research is in the area of decision analysis, where he has published more than 50 papers. He is regularly involved in large European funded projects. He has been the chair, co-organiser and guest speaker of several conferences on this topic. Alongside his academic activities, he acts as a consultant for companies in helping them to take better decisions. He has written the key textbook Multicriteria Decision Analysis: methods and software.

Speech Title: Multi-criteria sorting methods for AHP
Abstract: Six problem formulations exist in multi-criteria decision analysis (MCDA): choice, sorting, ranking, description, elimination and design problems. The Analytic Hierachy Process (AHP) is a useful and widespread method for solving choice and ranking problems. However, it is not adapted for sorting problems. Moreover, another practical limitation of AHP is that a high number of alternatives imply a large number of comparisons.

  The first part of the talk presents AHPSort I, a new variant of the AHP, used for the sorting of alternatives into predefined ordered categories. Furthermore, AHPSort I requires far less comparisons than AHP, which facilitates decision making within large scale problems. In the second part of the talk, AHPSort II will be introduced, which requires far less comparisons. Moreover the number of pairwise comparisons does not depend on the number of alternatives, therefore it is suitable for very large problems.
  AHPSort I will be illustrated with a supplier selection problem. AHPSort II will be illustrated with a risk assessment problem.


Dr. Arshad Jamal
Northumbria University London Campus, UK
Associate Dean, Northumbria University London Campus

Dr. Arshad Jamal is an accomplished academic and researcher with exceptional teaching, research and scholarship abilities. As an active researcher, He has published research in peer reviewed journals and conferences. He has extensive programme management experience in higher education with excellent track record of managing successful academic programmes and professional projects. In his teaching, he likes to apply technology enhanced and research rich teaching strategies. He has over twenty years of experience in teaching, research and practice and have delivered range of courses in the disciplines of IT and Business at undergraduate and postgraduate levels. Over the years, he has demonstrated knowledge and skills of programme design, session planning, effective assessment, awareness of diversity, working effectively with students, and application of professional value base in relation to teaching in higher education. A good team player with excellent networking, analytical and communication skills.