Participating Asper faculty

Lukas Neville
Department of Business Administration

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In an early pair of studies, I have found that interpersonal forgiveness can — in certain circumstances — be interpreted by workplace coworkers as a signal of trustworthiness. With a summer student, I am interested in designing and conducting a third study to better understand why and when forgiving employees are more likely to be trusted by their colleagues. In particular, I am interested in testing the role played by perceived self-control. For this project, I would be pleased to work with an undergraduate student in psychology, management, or any related field, with a preference for students who have some prior training or experience in survey and/or experimental design.

Yumin Wang
Warren Centre for Actuarial Studies and Research

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Registered index-linked annuities (RILAs) are increasingly popular equity-linked retirement savings products. Combining features of fixed-index annuities and traditional variable annuities, they offer investors equity exposure with downside protection. In this project, I will provide theoretical justification to the popularity of RILAs. Under a stochastic optimal stopping framework, I will compare an investor’s utility of holding RILAs to that of holding traditional variable annuities. By the comparison, I expect to demonstrate that RILAs are preferable to traditional variable annuities, which explains their increasing popularity. Contract design suggestions for RILAs will also be discussed.
Students involved in this project will conduct numerical analysis, e.g., applying finite difference method and Monte Carlo method to solve a stochastic optimal stopping problem. Candidates with strong backgrounds in statistics, actuarial science, and financial mathematics are encouraged to apply. The student involved will have the opportunity to learn some cutting-edge modelling methods and useful numerical approaches.

Yifan Wei
Department of Business Administration

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Since the 1980s, the world has been characterized by a wave of economic globalization, which is defined as the process of increasing economic interdependence among nations, led by multinational enterprises (MNEs) (Guillén, 2001; Rugman & Verbeke,2004). Yet, in recent years, growing evidence suggests the initiation of an economic de-globalization process: global trade and foreign direct investment (FDI) seem to have peaked in the early 2010s and declined afterwards (Witt, 2019b). This is mainly because of the collective shift of major countries’ (e.g., U.S., U.K.) national foreign economic policies to emphasize economic independence and decoupling, given the rise of domestic populism and anti-globalization sentiments (Korbin, 2017; Meyer, 2017). This de-globalization process was manifested most explicitly by the intensified U.S.-China rivalry under the Trump administration (Teece, 2020) and heightened by the COVID-19 pandemic (Fligstein, 2020) and the Ukraine-Russia conflict, eventually shocking MNEs’ global supply chains and global economic growth. 
My research project responds to this grand challenge to the globalized economy by investigating the impacts of MNEs’ home-country economic foreign policies on their global supply chains, mainly by leveraging the context of Trump’s shift to a decoupling policy. There is an urgency to this timely project, as global supply chains become more fragile amid increasingly antagonistic relationships between major economies. Additionally, without our scholarly inquiry into the role of national foreign economic policy, it is impossible for MNEs and their home-country governments to assess the true consequences for both their own economies and the global economy, and to maintain amore sustainable global economy. Specifically, I will:

  1. Assess whether and how the U.S.’ increasingly protectionist economic policy affects their MNEs’ suppliers in foreign countries, particularly those with established supply bases;
  2. Explore how such effects vary under different conditions.

I have a keen interest in working with our bright and competitive undergraduates at the University of Manitoba, and I am willing to involve them in this research to help collect and analyze data. Candidates with a strong academic background in statistics, actuarial science, business analytics, and computer science and engineering are strongly encouraged to apply. Computer programming skills (with SAS, R, Stata, Python, etc.) is a plus.

Ying Zhang
Department of Accounting and Finance

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Previous research has long recognized the impact of migration on the transformation of political landscape, but little research has focused on the effect of political party partisanship on migration. Throughout the pandemic, states have rolled out a patchwork of restrictions on social distancing, masking, and stay-at-home orders. However, orders vary by state which motivated people to move from more restrictive states to states with less or no restrictions, which further led to change in demand in the housing market in certain parts of the country. Since 2020, the housing market has been on a wild and crazy “ride”, for both home buyers’ and renters’ markets. However, the “ride” is not uniform across America because people moved from large cities to small and medium-sized cities in the south and west part of the country. This study proposes to study the potential linkage between political party partisanship and the motivation of migration. More specifically, this study aims at finding evidence of 

  1. the migration trend in the United States during the pandemic; 
  2. the political motivation of the migration; 
  3. if migration has driven up the housing market price in the local housing market after controlling for other factors such as mortgage rate, inflation, pandemic, and age groups of population, etc. 

The student is expected to collect the following data: State-level pandemic restrictions and policies; Historical state-level migration data from IRS; State-level housing price index; State-level economics and demographic data; State-level and county-level political party data.

Rong (Ratchel) Zeng 
Department of Business Administration

More about Rong (Ratchel) Zeng

More and more companies are taking corporate social responsibility (CSR) seriously, with some introducing a new Chief Sustainability Officer position to their leadership teams. However, many firms that have invested heavily in CSR have also been flagged for corporate social irresponsibility (CSiR). For instance, BP received several honors for good CSR practices, but its Deepwater Horizon oil spill in 2010 triggered an industrial disaster that was perceived as a major CSiR incident. CSiR tends to invoke a strong public reaction and attract negative media attention, creating unfavourable consequences for firms. However, we lack a comprehensive understanding of what factors contribute to and what consequences result from CSiR, as well as the co-existence of CSR and CSiR, as in the BP example. The proposed project utilizes the benefits of advanced meta-analytic techniques to analyze the data from different quantitative studies that treat CSiR as a construct distinct from CSR. The project will also develop a teaching case to unpack the interactions of identified factors. This set of studies will explore the relationship between CSiR and its antecedents and outcomes, with special attention to CSR-CSiR coexistence. Under my guidance, the Undergraduate Research Award recipient is expected to:

  1. Identify MNEs with CSiR incidents in other countries than their home countries and collect required materials for the teaching case as guided by the researcher.
  2. Search, collect, and download related literature and data. 
  3. Code and analyze them accordingly.

At the end of the project, the recipient is encouraged to display the work in the poster competition for undergraduate student researchers. The potential participants in the project need to pay attention to details, be proficient in Excel and have a basic knowledge of business and management (international business, in particular). Experience with EndNote or other reference management tools, and statistical analysis software tools such as SPSS, SAS, R, or STATA will be an asset.