Jiye Hu

China university of political sciences and law

Research Area：Economics; Financial supervision; Digital finance; Risk assessment

Speech Title: Supervision and Legislation of Cryptocurrency in China

Abstract:

The essence of blockchain is distributed ledger technology with the characteristics of disintermediation, unchangeable and traceability. As the application of blockchain technology, cryptocurrency will bring the risk of impact on the current financial legal relationship, and its supervision is becoming increasingly important. At present, the financial stability board (FSB), the bank for international settlements, Commission of payment and settlement systems (CPSS) committee and the international organization of security Commission  (IOSCO) and other international organizations, as well as the United States, Germany, Japan and other countries have taken the law and regulation of technical method of cryptocurrency carries on the preliminary exploration and obtained a certain result, can be the guide. The supervision of cryptocurrency has some problems, such as consumer protection, the opposition between the global asset flow and the supervision of a single sovereign state, and the difficulty in determining the subject of legal responsibility. To seek the solutions for these problems, first of all, it is necessary to define the legal attribute of cryptocurrency, to balance blockchain innovation and financial risk. At the same time, the regulatory sand-box can be used to regulate blockchain based cryptocurrency. The core regulatory points are to establish the technical standard access system, financing audit registration system and investor suitability management system of blockchain financial enterprises.

Zheng Li

Xi’an Jiaotong University

Research Area：Behavioural economics, transport/logistics management and risk/uncertainty analysis

Speech Title: Do Structural Changes in the Economy Play a Role in Machine Learning-based Forecasting?

Abstract:

We use a variant of machine learning (ML) to forecast energy demand within an autoregressive and structural model. By comparing the outputs of various model specifications, we find that training set selection plays an important role in forecasting accuracy. More specifically, however, the performance of training sets starting within identified systematic patterns is relatively worse, and the impact on forecast errors is substantial. We explain these systematic variations in machine learning performance, and explore the intuition behind the ‘black-box’ with the support of economic theory. An important finding is that these time points coincide with structural changes in the economy. By examining the out-of-sample forecasts, the model’s external validity can be demonstrated under normal situations.

Raymond Young                                 

Xi'an Jiaotong Liverpool University

Research Area：Top Management Support, Project Governance, Project Success/Failure

Speech Title: The need for ‘relevant’ research in management

Abstract:

Benbasat and Zmud (1999) quote a business school professor who said “As much as 80% of management research may be irrelevant”. This presentation will explore why this is the case and present examples of how to overcome the problem and do high impact, rigorous AND relevant research.

The presentation will start by showing the problem of relevance in computer science, management science, organizational science, economics and informations systems. It will then use projects and project management as the context to show how relevant research was conducted to produce publications and output that stimulated critical thought and was implementable in the business world. It will finish by showing a website that was created to help practitioners, to disseminate research and to maintain a dialogue between the academic and practitioner community.

Min Hou

Zhejiang Gongshang University

Research Area：Advertising; Bilateral markets;, Internet finance, Consumer behavior

Speech Title:The Impact of Visual Information on Donation Behavior: An Empirical Study Based on KIVA

Abstract:

In the field of charitable giving, digital photos (hereinafter referred to as digital) are an important medium of information communication and dissemination. Previous studies have focused on the characteristics of the recipient and their impact on individual donation decisions, ignoring the color characteristics of the images and the display medium itself. This study empirically analyzes the impact of colors on individuals’charitable donation behavior. We collected data from Kiva—a United States-based not-for-profit—and measured image information using the Query by Image Content (QBIC) system. Our results found that (1) both hue and value (brightness) have a significant positive impact on individuals’ donation behavior, and (2) the significance of Palmer and Gardener’s (2008) theory of center bias is verified. Theoretically, this study provides an explanation for the impact of image information on individual donation behavior. Practically, it has implications for not-for-profit marketers, and enhances individual donors’prosocial behavior.