Prof. Pengguo Wang
Business School, University of Exeter, UK
Research Area:Equity Risk Premium, Empirical Corporate Finance, Risk Factors, Firm Valuation Models, Option Pricing, Equity Trading Strategies.
Pengguo Wang is a professor of finance and accounting in the Department of Finance and Accounting at the University of Exeter. He was educated in China and the UK. He received his MPhi in Economics and PhD in Finance in the Business School at Strathclyde University. Prior to joining the University of Exeter, he was a faculty member at Imperial College London and Bristol University. He worked as an ESRC Research Fellow in a joint program in Lancaster Management School and Manchester Business School.
Pengguo has been invited to give talks to the City of London for investment, accounting and legal practitioners on valuation. The methodology he proposed has been applied by investment funds to develop equity-trading strategies. He has been involved with training through professional accounting associations such as the Institute of Chartered Accountants in England and Wales (ICAEW).
Pengguo has researched and published extensively in the areas of capital markets, financial reporting, derivative pricing and stock valuation. His research, teaching and consulting interests are at the interface of finance and accounting. His current research interests are focused on cost of capital, equity risk premium, market anomalies and fundamental valuation models and applications, with particular reference to the links between financial statement information, risk and equity returns. His research has financially sponsored by ESRC, KPMG, ACCA, and The Institute for Quantitative Investment Research (INQUIRE-UK) and other grants.
Title of Keynote Speech:
Big Data and Stock Valuation
Big data and machine learning (ML) are proved to be useful in portfolio allocation in asset management, corporate finance and financial risk management. This talk focuses on the roles of big data and ML in stock valuation. It covers the following aspects. (i) why does stock valuation need conventional structured data and new unstructured data? (ii) what do we mean by big data and machine learning? (iii) current applications of big data and ML in stock valuation; (iv) future research and practice of big data and ML in stock valuation.
Assoc. Prof. Minyue Jin
Chongqing University, China
Research Area: Supply chain management, sustainable operations, marketing‐manufacturing interface
Brief: Dr. Minyue Jin received her Ph.D. from University of Science and Technology of China, and had been a visiting postdoc at University of California, San Diego. In 2018, she joined Chongqing University under the “One-hundred Talents Program”. Her research interests include sustainable operations and supply chain management, consumer behavior and marketing strategies. Jin has been published in numerous journals, including Manufacturing & Service Operations Management (UTD 24), European Journal of Operational Research, Omega, International Journal of Production Research, and International Journal of Production Economics.
Title of Keynote Speech:
Choice of Electronic Waste Recycling Standard Under Recovery Channel Competition
We consider two competing electronic waste (e-waste) recovery channels, each of which consists of a collector and a recycler. Collectors obtain donated e-waste and sell the collected items to recyclers or in the secondary market, whereas recyclers process e-waste and sell the recycled material in the commodity market. Each recycler chooses for certification of one of two standards: e-Stewards or Responsible Recycling (R2). E-Stewards requires comparably more responsible handling, thus a higher processing cost, but attracts more e-waste from environmentally conscious donors. We find that competition between recovery channels is a key factor motivating e-Stewards adoption, whereas a recycler always chooses R2 in its absence. Interestingly, when competition exists both within and between recovery channels, recyclers with strong e-waste processing scale economies choose e-Stewards when incurring significantly higher processing costs than with R2. Furthermore, both the total environmental benefit and welfare might be higher when recyclers choose R2. Managerial implications: Policy makers who aim to encourage e-Stewards adoption should (1) lower entry barriers for new recyclers to induce competition, and (2) offer incentive programs to alleviate e-Stewards’ cost disadvantage, though only when recyclers have weak scale economies. Policy makers and nongovernmental organizations, however, should exercise caution in endorsing e-Stewards because R2 actually may generate a higher environmental benefit because of higher recycling volumes.
Assoc. Prof. Wanying Chen
Logistics Department, Zhejiang Gongshang University, China
Research Area:Automated warehouse, Queuing theory, Reinforcement Learning, Logistics
• 2007 to 2011, B.E. in Computer Science, Northwestern Polytechnical University
• 2011 to 2012, Master in Automation, INSA de Lyon, France
• Nov 2013 to Sept 2014, Research Assistant (Internship), Cirrelt, Ulaval, Canada
• 2012 to 2015, Ph.D. in Computer Science and Mathematica School, INSA Lyon, Logistics management
• Aug 2016 to Dec 2020, Assistant Professor, Zhejiang Gongshang University, China
• 2021 to now, Associate Professor, Zhejiang Gongshang University, China
Title of Keynote Speech:
How does the battery management impact the performance of the automated warehouse? Performance evaluation in a self-climbing robotic warehouse
Our research is motivated by the battery management in a new robotic warehouse, the compact self-climbing robotic (CSCR) system, which is different from previous compact warehouses and robotic warehouses. This system fully depends on the battery powered robots for the tote movement. Therefore, the battery management plays an important role and considerably impacts the system performance of the robotic warehouse. This paper optimizes the battery management in the CSCR system by establishing semi-open queuing networks (SOQNs). The analytical models are solved by the approximated mean value analysis and are validated by simulation models. We find several interesting managerial insights: (1) Although the fast charging can decrease the throughput time, with the increase of the charging cycles, the slow charging may outperform the fast charging. (2) The system is more sensitive to the battery charging policy (priority charging policy or the first-come-first-service charging policy) than the battery charging technologies (fast charging or slow charging). (3) Although the robot blocking is regarded as an important factor which may impact the system performance, the battery management has a stronger impact than the robot blocking, especially for the large size system. But the impact of the robot routing is larger than the robot battery management. Our models can help the decision makers to (i) choose the charging technology, fast charging or slow charging, to decrease the throughput time under different scenarios; (ii) decide the suitable charging policy for the system with different charging technologies; (iii) determine the optimal charging station number and the optimal robot number.
Assoc. Prof. Dr. Shafie Mohamed Zabri
Department of Business Management, Universiti Tun Hussein Onn Malaysia, Malaysia
Research Area:Small Business Financing, Behavioural Finance, Entrepreneurship, Financial Management, Capital Structure, Corporate Governance, Working Capital Management
Shafie is currently the Dean of the Faculty of Technology Management and Business at Tun Hussein University of Malaysia (UTHM).
Prior to this appointment, he was seconded to the Ministry of Higher Education Malaysia (MOHE) as the Director of Education Malaysia London for 4 years. He oversees the internalisation activities between higher education institutions in Malaysia with higher education institutions in United Kingdom, Ireland and the European region. Apart from that, Education Malaysia London also oversees the development and wellbeing of Malaysian students in UK, Ireland and Europe, as well as the management of Education Malaysia offices in London, Belfast and Dublin.
Shafie started his academic career with the Faculty of Finance and Banking, Universiti Utara Malaysia in 2003. Prior to his secondment to the MOHE in October 2018, Shafie was an Associate Professor in the Department of Business Management at Universiti Tun Hussein Onn Malaysia. He joined UTHM since 2007, during which he was appointed as the Head of Department, Deputy Dean (Academic and International) and Deputy Director of Innovation and Commercialisation Centre.
He earned his PhD in Business (with Management) from University of Plymouth, United Kingdom. He received a degree in Business Administration from Universiti Utara Malaysia (UUM) and a Master in Business Administration from the National University of Malaysia (UKM).
Title of Keynote Speech:
Development of Sustainable Financial Management Framework for Agile and Resilient Micro, Small and Medium Enterprises (Msmes)
In recent years, the incorporation of sustainability into financial management emerged as an essential element of business strategy and has garnered considerable attention. Micro, Small, and Medium-Sized Businesses (MSMEs) are of utmost importance to the global economy, as their financial sustainability is essential to their continued growth and survival. This study aims to provide a comprehensive analysis of the framework associated with sustainable financial management practices in the context of MSMEs. In order to maintain the long-term viability of small firms, it is imperative to establish a comprehensive framework comprising sustainable financial management practices. The five fundamental components of sustainable financial management practices are budgeting, financial reporting, cash flow management, risk management, and sustainability. Each of these factors is thoroughly assessed in light of the context and actual practices of MSMEs. In order to accurately represent the overall framework, a subsequent index of significance will be developed and then incorporated into the sustainable financial management index (SFMI). This index aims to provide a framework for evaluating the sustainable financial management practices of MSMEs. This is hoped to enable enhanced provision of financial assistance for MSME that aligned with their objective development and in turn increasing their agility and resilient. This is also helping the governments specifically in providing much needed financial support and assistance for MSMEs.
Keywords: Sustainability, Financial Management, MSMEs