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2018年前沿理论与研究方法国际学术研讨会(二)会议通知

时间:2018-10-11点击数:打印

前沿理论与方法具有跨学科、多理论视角、应用广泛的特点,如何有效地整合和利用管理学不同领域的相关理论视角与研究方法,从而探索、发现并解决现代信息技术引发的一系列热点问题是众多学者关注的重中之重。

本次学术研讨会邀请了Patrick Chau教授,香港浸会大学工商管理学院研究生部主任、副教授Christy Cheung博士,中院数学与系统科学研究所预测科学研究中心总工程师、副研究员尚维博士做主题报告。他们将分别对当前各自领域的热点问题,以及相关理论与研究方法与我们进行交流研讨。同时,他们也将对我院部分研究生的学术成果汇报做分析点评。本次会议还特邀了我校杨晓光教授做点评专家。

欢迎有兴趣的教师与学生参加。

活动议程:

 

 

主要参加活动的专家介绍:

Patrick Y.K. CHAU is Padma and Hari Harilela Professor in Strategic Information Management and Associate Dean at the Faculty of Business and Economics of The University of Hong Kong. He received his PhD in business administration from the Ivey Business School, The University of Western Ontario in 1992. Dr. Chau is known for his research in IT adoption/implementation and electronic commerce. He has over 90 journal publications which are well cited by scholars in the academic community. Many of his papers published in various top-tier and highly reputed journals, including MIS Quarterly, Journal of Management Information Systems, European Journal of Information Systems, Journal of Association for Information Systems, Communications of the ACM, Decision Sciences, Decision Support Systems, Information & Management, and many others.  As of September 2018, the total number of citations of his papers in Google Scholar reaches over 17,000 with an H-index of 50.  He is currently the Editor-in- Chief of Information & Management and a Senior Editor of Journal of the Association for Information Systems. 报告简介(Abstract):Turning research to publication is a key step for an academic to advance in his/her academic career.  This is especially the case for those who are early in their academic career.  Thus, knowing the publishing game becomes a “necessary condition” in this career development process.  This talk aims to provide the audience with an experience sharing session from a scholar who has been an editor or on editorial board of more than a dozen ISI indexed journals in the Information Systems discipline. He will share his publication experiences from the perspectives of an editor, a reviewer and an author respectively.

杨晓光教授是中国科学院数学与系统科学研究所副所长、中国科学院管理决策与信息系统重点实验室主任,在金融风险管理、大数据背景下经济行为和社会行为分析、及数学优化和博弈论等领域有丰富的研究经验和研究成果。

Christy M.K. Cheung is an Associate Professor at Hong Kong Baptist University. She earned a Ph.D. in Information Systems from the College of Business at City University of Hong Kong. Her research interests include Technology Use and Well-Being, IT Adoption and Use, Societal Implications of IT Use, and Social Media. She has published over one hundred refereed articles in international journals, and conference proceedings, including Decision Support Systems, Information & Management, Journal of Information Technology, Journal of Management Information Systems, Journal of the Association for Information Science and Technology, MIS Quarterly and among others. Dr. Cheung is currently President of the Association for Information Systems (AIS-Hong Kong Chapter). She also serves as Editor-in-Chief of Internet Research. 报告简介(Abstract: Online harassment, a type of cyberbullying behavior, poses serious risks to users of social networking sites (SNSs) and challenges to platform providers.  In recent years, many SNS providers have implemented built-in reporting functions to combat such aversive online behavior.  However, the effectiveness of these reporting tools in encouraging proactive intervention remains relatively unknown.  To address this gap, this study answers a recent call for understanding of the societal impact of the use of information technology and aims to identify the underlying mechanisms driving bystanders’ decision to use these built-in functions to report online harassment on SNSs.  Drawing on theory of cognitive appraisal, we develop a research model that explains how a set of appraisal factors shape bystanders’ willingness to use the built-in reporting function on SNSs.  We empirically tested the research model with active Facebook users.  The data analysis shows support for most of our hypotheses. Specifically, our results show that bystanders’ perceived personal responsibility for addressing the incident, perceived effectiveness of the reporting function in curbing online harassment, social norms are pivotal appraisal factors explaining bystanders’ willingness to use the built-in function to report.  Shedding light on how to effectively mitigate the negative consequences of online harassment, this study yields valuable insights that guide the development of a brighter and safer digital society.

尚维博士是中国科学院数学与系统科学研究所预测科学研究中心总工程师、副研究员。报告简介(Abstract ): This study aimed to propose a new, novel crude oil price forecasting method based on online media text mining to capture more immediate market antecedents of price fluctuations. Specifically, this is an early attempt to apply deep learning techniques to crude oil forecasting, and to extract hidden patterns within online news media using convolutional neural network (CNN). While the news text sentiment features and CNN model extracted features reveal significant relationship with the price change, they need to be grouped according to their topics in the price forecasting to obtain a preferable forecasting accuracy. This study further proposes a feature grouping method based on LDA topic model to distinguish effects from various online news topics. Optimized input variable combination is constructed using lag order selection and feature selection methods. Empirical results suggest that the proposed topic-sentiment synthesis forecasting models perform better compared with older benchmark models. In addition, text features and financial features are proved to be complementary in forecasting more accurate crude oil price.