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ASAC 2018 Conference

Professional Development Workshops


Interrupted Time Series Analysis (ITSA) for Management Research

Saturday May 26th, 9:45 am - 11:00 am

Lead by Dr. Murtaza Haider

Murtaza Haider is an associate professor of Real Estate Management at the Ted Rogers School of Management, Ryerson University, in Toronto. He is also the research director of the Urban Analytics Institute and an adjunct professor of engineering at McGill University in Montreal. Murtaza Haider holds a Masters in transport engineering and planning and a Ph.D. in Urban Systems Analysis (Civil Engineering) from the University of Toronto.

Professor Haider specializes in applying analytics and statistical models to find solutions for socio-economic challenges. His research interests include business analytics, data science, forecasting housing market dynamics, transport/ infrastructure/ urban planning, and human development in Canada and South Asia.

Murtaza Haider is the author of Getting Started with Data Science: Making Sense of Data with Analytics, which was published by Pearson/IBM Press in 2016. Dr. Haider is also a columnist with Canada’s leading financial newspaper, The Financial Post. He is also an avid blogger and writes for Dawn newspaper and Huffington Post. He has also written for The Globe and Mail, The Toronto Star, and The Montreal Gazette. Murtaza Haider is regularly interviewed by media including CBC, City TV, and Global.

Workshop description: this workshop explains the method of ITSA using the example of self defense laws being amended by the State of Florida in 2005. The intent of this change was to improve public safety and lower the incidence of violent crime, by providing individuals legal immunity if they were to use lethal force in self defense. Unfortunately, the reverse happened. After the law was enacted, “there was an abrupt and sustained increase in the monthly homicide rate … and in the rate of homicide by firearm.” The authors used ITSA to demonstrate the impact of a policy or strategy change where the underlying data set is a time series and not a cross section.

ITSA is a simple extension of ordinary regression models. It is straightforward to implement and interpret and has been used extensively in the health sector where control and treated groups are used. ITSA could be an extremely powerful tool to analyze the impact of changes in policy and strategy where time series data are available for the dependent variable before and after the change was implemented. ITSA can be readily extended to treated and control groups to determine a more “causal” notion of the difference in impacts between the control and treated groups.


Building and Refining Theories in Entrepreneurship: Using a Mathematical/Computational Angle

Saturday May 26th, 11:15 am - 12:30 pm

Lead by Dr. Moren Lévesque

Moren Lévesque is Professor and the CPA Ontario Chair in International Entrepreneurship at York University Schulich School of Business. Moren has been on the faculty at Université Laval, Carnegie Mellon University, Rensselaer Polytechnic Institute, Humboldt Universität, Case Western Reserve University, and the University of Waterloo as a Canada Research Chair in Innovation & Technical Entrepreneurship. Her research applies the methodologies of analytical and quantitative disciplines to the study of decision making in new business formation. Her work appears in Entrepreneurship Theory & Practice, European Journal of Operational Research, IEEE Transactions on Engineering Management, Journal of Business Venturing, Journal of Management Studies, Long Range Planning, Organization Science, Production and Operations Management, Strategic Entrepreneurship Journal and Strategic Management Journal, among other research outlets. Most recently, she has served the Academy of Management’s Entrepreneurship Division as Chair of its Membership Committee. She has also served for a 5-year term as an officer for the Institute for Operations Research & Management Science’s (INFORMS) Technology, Innovation Management and Entrepreneurship Section. Moren currently serves as Editor for Entrepreneurship Theory & Practice, Senior Editor for Production and Operations Management, and she served from 2013 to 2017 as Department Editor for IEEE Transactions on Engineering Management.

Workshop description: in this workshop, Moren will illustrate how the use of mathematical/computational modeling and its underlying logical arguments can build and refine theories in entrepreneurship. This theoretical lens is effective to study tradeoffs inherent in numerous decisions that await entrepreneurs, including ownership sharing, market entry timing, and funding/partner acquisition, to name a few. Today’s computational power enables mathematical modeling to account for dynamism, nonlinearity, path-dependency, interaction, disequilibrium and unawareness, which characterize most entrepreneurial contexts and related decisions. Formal modeling can help complement or rethink our current understanding of entrepreneurship, especially when a decision must consider the evolution of key factors (and their dynamic interplay) or take into account future events that can inform theory and practice today rather than solely relying on data to understand what has already happened. From her experience as researcher, author, reviewer or editor, and interest in technology/innovation management and entrepreneurship, Moren will also share practices for publishing work that is multi-disciplinary or multi-method by nature. The objective of this workshop is certainly not to learn mathematical/computational modeling, but to build an appreciation for using it and forming scholarly teams with the relevant skills to address a broader set of entrepreneurial phenomena.


Introduction to Social Network Analysis

Saturday May 26th, 1:30 pm - 2:45 pm

Lead by Dr. Anatoliy Gruzd

Dr. Anatoliy Gruzd is a Canada Research Chair in Social Media Data Stewardship, Associate Professor at the Ted Rogers School of Management at Ryerson University, and Director of Research at the Social Media Lab. Anatoliy is also a Member of the Royal Society of Canada’s College of New Scholars, Artists and Scientists; a co-editor of a multidisciplinary journal on Big Data and Society; and a founding co-chair of the International Conference on Social Media and Society. His research initiatives explore how social media platforms are changing the ways in which people and organizations communicate, collaborate and disseminate information and how these changes impact the norms and structures of modern society.

Workshop description: this workshop will introduce some of the main principles and techniques of Social Network Analysis (SNA). We will use examples from organizational and social media-based networks to understand concepts such as network density, diameter, centrality measures, community detection algorithms, etc. The session will also introduce Gephi, a popular program for SNA. Gephi is a free and open-source tool that is available for both Mac and PC computers. By the end of the session, you will develop a general understanding of what SNA is, what research questions it can help you answer, and how it can be applied to your own research. You will also learn how to use Gephi to visualize and examine networks using various layout and community detection algorithms.


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