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ASAC 2018 Professional Development Workshops
May 26, 2018, 9:30 a.m. - 3:30 p.m.
Ted Rogers School of Management, Ryerson University
55 Dundas Street West, Toronto, ON M5G 2C3
Room 2-119

Workshop Chair: Horatio M. Morgan, Ryerson University
Phone: 416-979-5000 x 2526 email:

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Which session would you like to attend? (Session descriptions below) Check all that apply *
Workshop agenda and description
9:30 – 9:45 a.m.
Chair: Welcome & Opening Remarks

9:45 – 11:00 a.m.
Session 1: Interrupted Time Series Analysis (ITSA) for Management Research

Lead: Murtaza Haider, Ryerson University

Please bring your own laptop/tablet. ITSA can be conducted with Microsoft Excel since it uses Ordinary Least Squares Regression. However, for advanced features, such as Newey-West Standard Errors, you will need to have Stata, R, SPSS, or SAS running on your machine. The minimum pre-requisite therefore is to have Microsoft Excel running on your computing device.

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.

11:00 – 11:15 a.m.

11:15 a.m. – 12:30 p.m.
Session 2: Building and Refining Theories in Entrepreneurship: Using a Mathematical/Computational Angle

Lead: Moren Lévesque, York University

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.

12:30 – 1:30 p.m.

1:30 – 2:45 p.m.

Session 3: Introduction to Social Network Analysis

Lead: Anatoliy Gruzd, Ryerson University

Bring your own device Please install Gephi on your laptop:

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.

2:45 – 3:00 p.m.
Chair: Closing Remarks

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