Faculty Fellows

 

One-year Fellowships (July 2022 - June 2023)

 

Saied Samiedaluie

Hugh E. Pearson Fellowship

Project: Approximate Linear Programming for Network Revenue Management

NRM [network revenue management] are often formulated as dynamic programs, where the state of the system is described by the remaining level of resources. In the classical airline application of NRM, each resource corresponds to a flight leg. In practice, the airline NRM problems usually involve a large number of flight legs. Therefore, the dynamic programming formulation suffers from the well-known “curse of dimensionality.” Over the last two decades, majority of research in NRM has focused on developing approximations and heuristic control policies to deal with the curse of dimensionality.


One of the approximation method that has received significant attention is approximate linear programming, which is based on linear programming equivalent of the dynamic program. The approximate linear programming requires one to select a specific functional approximation form, which is used to evaluate the value of resources over time. So far, only a few approximation forms have been introduced and used in the NRM literature. The objective of this research is to develop new approximation architectures to take into account relevant properties specific to the NRM problems. Examples of these properties include existing correlations between resources or demand, which are completely ignored in the current literature.

 

Vikas Mehrotra

Canadian UtilitiesFaculty Fellowship

Project: Anatomy of Long-run Stock Returns in Japan

In this study we propose to document stock returns in post-war Japan at the monthly, annual, decadal and lifelong horizons. We propose to look at the universe of all listed firms in Japan (The Tokyo Stock Exchange, the Osaka Stock Exchange and JASDAQ). The motivation for such a study is a path-breaking publication by Bessembinder (2018) in the Journal of Financial Economics that documented a stark difference between individual stock returns and the wider market return in the CRSP era.

 

Noah Castelo

NOVA Management of Technology Endowment

Project: Exploring the effects of social chatbots 

The goal of this research is to explore consumers’ engagement with a new class of social chatbots that are positioned and marketed as replacements for human relationships. For example, 660 million Chinese consumers chat regularly with the Xiaoice chatbot, positioned as a virtual girlfriend or virtual boyfriend (Xu, 2021). In North America, the Replika chatbot has 7 million users and is positioned as a virtual friend (Metz, 2020). We plan to use large-scale, longitudinal experiments to test how engaging with these bots affects users’ mental health and their relationships with other humans.

 

Yonghua Ji

G.R.A. Rice Faculty Fellowship

Project: IoT Technology and e-Commerce Platform: Encroachment and Data Sharing

Internet of Things (IoT) refers to the technology of using sensors and other internet-enabled
devices to collect and share data. Smart devices, i.e., IoT-enabled devices, are becoming
more popular, and the number of such devices is estimated to increase fivefold in ten years
from 2015, reaching 75 billion worldwide by 2025 (Statistica Inc, 2016).

With more and more data being pushed to the cloud, IoT technology enables innovations in smart devices and applications such as location intelligence (Amazon Inc., 2020). By using data gathered through smart devices, supply chain members can interact with customers on an individual basis. For example, manufacturers can design devices such as smart refrigerators and smart fitness systems (Hyde, 2020, Griffith and Colon, 2019) that can adjust the settings in the home environment based on the owner’s preferences. In this
paper, we consider a setting where device manufacturer decides whether to encroach, i.e,
selling directly to consumers, in addition to selling on an e-commerce platform. Also, the
manufacturer can decide whether to share IoT data with the e-commerce platform. This proposal seeks to model an incentive system to motivate manufacturers to share IoT information. This proposal will be part of a program of research on IoT technology and
information sharing to be developed for a major NSERC/SSHRC proposal.

 

Ke Wang

The Edmonton Journal Fellowship

Project: Do Peer Firms Respond to Public Shaming of Corporate Tax Practices? A Strategic Disclosure Perspective

In recent years, corporate tax practices have received increasing scrutiny from the media, activist groups, and regulators. According to a report by PricewaterhouseCoopers (PwC 2014), whether corporations pay their “fair share” of tax has become a headline issue. A media article that accuses large corporations of “immoral” tax avoidance behavior may induce protests and boycotts, as illustrated in the Starbucks case publicized in October 2012 (Bergin 2012). More recently, tax activists accuse Silicon Valley giants of avoiding large amount of taxes over the last decade (Taylor 2019). In addition, US President Joe Biden wrote on Twitter to criticize large corporations for paying zero tax (Kaplan 2021).
Academic studies have also examined whether and how media coverage of corporate tax practices affects stock market reactions, consumer purchase behavior, and employee perceptions (e.g., Asay et al. 2021; Hanlon and Slemrod 2009; Lee et al. 2021). Due to information spillover, the impact of media coverage of one firm’s aggressive tax strategies can go beyond the target firm. The proposed research aims to investigate peer firms’ responses to negative media coverage of corporate tax practices and, particularly,
how they strategically disclose tax-related information in response to such news.

 

Timothy Hanningan

Xerox Canada Faculty Fellowship

Project: Building Markets out of Bits and Blocks: The Early Moments of NFT-based Blockchain Entrepreneurship

As the first major application of blockchain technology, cryptocurrencies have a murky provenance. With Bitcoin as an example, there are many accounts of a dark world with organized crime and drug rings as early adopters. However, we also see more recent accounts of applications that are less morally objectionable, such as people sending remittances from Canada to their extended families in developing countries. This phenomenon has become so prevalent that recently El Salvador has adopted Bitcoin as legal tender. Given the high costs in the remittance market imposed by oligopolist incumbents (such as Western Union), it is not surprising to see cryptocurrency being adopted by so many people transferring funds abroad. The legitimacy struggles of cryptocurrency also resemble historical analogs, where incumbents frame challengers (Ansari & Krop, 2013) as ‘pirates’ who in turn may be innovators reshaping the market (Vergne & Durand, 2013). Studying this has implications for organizational theory on centralized organizations and distributed trust (Vergne, 2020; Seidel, 2018), but also on market category emergence. 

 

Three-year Fellowships (July 2022 - June 2025)

 

Vishal Baloria

Roger S. Smith Professor of Business

(July 2022 - June 2025)

Project: Corporate Watchdogs and the Business Press 

Corporate watchdog groups play an increasingly important role in financial markets. They generate,  disseminate, and rebroadcast information on controversial corporate issues, including the extent to  which firms (1) pay their “fair share” of taxes, (2) engage in socially irresponsible behavior, (3) provide  executives with excessive compensation, (4) receive government subsidies, and (5) engage in corporate  fraud. Unlike the mainstream business press, which typically has to manage multiple priorities and therefore plays a generalist role, corporate watchdog groups specialize specifically in watchdog  journalism. We propose to examine the extent to which corporate watchdog groups have an influence on  the level and tone of business press coverage of U.S. firms. Our first prediction is that corporate  watchdog groups reduce the costs of information acquisition for the business press, thereby leading to an  increase in the level of business press coverage of firms actively followed by corporate watchdog  groups. Our second prediction is that corporate watchdog groups take a critical tone in their coverage of  firms, thereby leading to an increase in the negative sentiment of business press coverage of firms  actively followed by corporate watchdog groups. In further tests, we plan to examine specific topics and specific news outlets for which corporate watchdog groups have a particularly significant influence.

 

Naomi Rothenberg

Alex Hamilton Professor of Business

(July 2022 - June 2025)

Project: Voluntary Disclosure and Audit Quality

There are several issues that arise when considering a firm’s choice to voluntarily disclosure information in the context of mandated, audited financial reports. Specifically, we plan to work on two areas: (i) the effect of a voluntarily disclosed forecast on the manager’s motivation to manipulate the firm’s audited reports, and the auditor’s choice of audit quality; (ii) the effect of the timing of a voluntary disclosure in relation to the firm’s mandated disclosure of its financial reports on audit quality.

 

Armann Ingolsson

Francis Winspear Professor of Business

(July 2022 - June 2025)

Project: Service Operations Management

We will investigate methods to forecast EMS call volumes over time and space, the way in which load impacts the time that paramedics spend at the scene of an emergency and whether or not they transport the patient to a hospital, and methods to balance EMS load across the emergency departments in a city. At a more general level, we will formulate and analyze mathematical models of waiting lines that incorporate recent empirical findings: that customers and servers adapt their behaviour in response to changes in load—that is, behavioural queueing science (BQS).

 

Three-year Fellowships (july 2021-June 2024)

 

Vern Glaser
Eric Geddes Professor of Business 

Project: The Biography of an Algorithm: Performing Algorithmic Technologies in Organizations

Algorithms are ubiquitous in modern organizations. Existing research views algorithms as self-contained computational tools that either magnify organizational capabilities or generate unintended negative consequences. To overcome the limitations associated with focusing on the “recipe” of an algorithm, Glaser will develop a biographical perspective on algorithms that focuses on key biographical moments that explain how algorithms evolve as they move across contexts and over time. 

 

Karen Hughes
Alex Hamilton Professor of Business 

Project: Gender, Innovation, and Inclusive Entrepreneurial Ecosystems in Western Canada

How to create and sustain vibrant, inclusive, entrepreneurial ecosystems is a question of great interest not only to academics but to policy makers, practitioners, and service providers across Canada. This project will generate new academic and policy knowledge about gender-inclusive ecosystems, focusing on Western Canada. Leveraging nationally representative data from the Global Entrepreneurship Monitor (GEM) Canada survey, the project will examine three questions relevant to current debates over inclusive recovery in the COVID-19 and post-COVID-19 contexts: 1) How are gender gaps in entrepreneurial outcomes shaped by distinct provincial entrepreneurial ecosystems? 2) How can social and technological innovation mitigate gender gaps and enhance the viability of women-led businesses? 3) How can entrepreneurial ecosystems be made more gender-inclusive?  This project builds on ongoing collaborations with academic and policy researchers at the Haskayne School of Business, Diana International Research Institute at Babson College, GEM Canada, Western Economic Diversification Canada, and Global Affairs Canada.

 

Ilbin Lee
CN Western Economic Research Fellowship

Project: Data Analytics for Decision-making: Theory and Applications 

Wildfires pose significant threats to public safety and surrounding values, as demonstrated by the recent examples in the USA and Australia. The initial attack (IA) to a newly reported fire is critical for ensuring fires are limited to small sizes. Decisions about the timing, type, and quantity of suppression resources in the early stage of firefighting are expected to influence the likelihood of success. Also, high costs are incurred when scarce resources such as air tankers are dispatched. However, the impact of the IA decisions on the success has been largely unstudied. Using fire operations data of Alberta over the last 20 years, Lee’s team is estimating the causal effect of IA resources on the suppression success. Based on the results, he aims to build a machine learning model that can predict the success probability under different conditions and improve IA dispatching decisions.