College of Business

Theft and fraud within family firms can have a significant impact on local, national, and international economies, given that most businesses operating throughout the world are family firms. According to familybusiness.com, 62% of the US workforce is employed by family businesses. Yet, we do not know much about how family firms respond to theft and fraud committed within their firms or the factors that influence their responses. The goal of this dissertation is to better understand a family firm owner’s decision to report theft and fraud committed by family and non-family employees, and whether kinship strength and race/ethnicity have any discernable effects on these reporting intentions. To achieve that goal, this study integrates insights from family firm, sociology, and psychology literatures. It presents a conceptual model and three sets of hypotheses that were tested in this empirical study. The results extend previous literature by providing support that kinship not only influences family employee theft intentions, but family owner reporting intentions as well. In addition, egalitarianism, or race avoidance, was shown to interact with kinship to influence owner reporting intentions.

The purpose of this study is to look at the effects that industry concentration has on the growth of local areas. People will go where the jobs are so by evaluating employment data one can also evaluate the growth of an area. Common economic basis calculations and indices were used to provide useful information about characteristics of growth, competitiveness, and concentrations of local industries compared to the national level. The key results show the complex nature of urban and regional development exemplified by changes in employment and that access to more and complex data will be necessary to gain a greater understanding of urban growth.

This study utilized environmental, social, and governance (ESG) data to analyze how institutional investors' strategies relate to the approaches of the private equity (PE) funds they invest in. Using limited partner (LP) investor and general partner (GP) PE fund data from Preqin, I created ESG scores for both LP and PE funds. Ordinary least-squares regression showed a significant, positive relationship between LP/GP ESG strategies. However, the relationship became negative and significant when firm-, fund-, and country-level controls were added. This misalignment between statements and action, often called greenwashing, suggests that firms are driven to ESG reporting due to external factors and do not feel accountable for investment decisions that follow strategic disclosures. Investor environmental (E), social (S), and governance (G) strategies had different relationships with GP ESG approaches. Public institutional investors, fund size, and the presence of a civil law system were positive contributing factors to the LP/GP ESG relationship. Fund performance was negatively associated with the relationship. There was also a significant difference in the LP/GP ESG approach between European PE funds versus those in North America. These findings show that E, S, and G factors may be more accurately analyzed separately than as one combined cluster. The findings also show that local conditions influence ESG strategic alignment between LPs and GPs. They suggest policymakers consider unique country-level attributes and differences in fund-level characteristics when attempting to influence ESG disclosure. ESG rating services could consider including factors that measure alignment between investors’ strategic statements and their investment decisions. The results provide valuable information on corporate social responsibility (CSR) in private markets, which has yet to be broadly studied compared to the extensive CSR literature available on public companies.

This empirical study examines the impact of a homeowners association (HOA) mandatory membership fee on residential real estate prices, a topic that has not been empirically addressed in the real estate literature. A mandatory membership fee is defined as an initiation fee charged by HOAs that grants homeowners country club access. Many studies have examined the impact of the presence of homeowners associations on price but only a few studies have examined the impact of homeowners associations on price by estimating the impact of homeowners association fees. This research expands the HOA literature by examining the specific HOA fee characteristics of a mandatory membership fee. In this analysis, hedonic price models (HPM) are used to estimate the impact of mandatory membership fee on price by analyzing 31,704 observations of single family home sales between 2018 and 2019 in Palm Beach County, Florida using data from a local multiple listing service. Specifically, Ordinary Least Squares (OLS) models using two dependent variables, sold price and natural log of sold price, with mandatory membership fee as the independent variable of interest are used to estimate the relationship between mandatory membership fee and sales price. By controlling for property, neighborhood, and market characteristics, the hypothesis I investigate states that the impact of the presence of a mandatory membership fee on sales price is negative.

This research investigates the impact of prior entrepreneurial exposure on an entrepreneur’s intention to persist. The objective of this study was to employ the Theory of Planned Behavior based logic to investigate its mediating effect of prior entrepreneurial exposure on entrepreneurial persistence intention among entrepreneurs, and whether their perception of the quality of that exposure or experience influences entrepreneurs’ intention to persist. Specifically, this study explores five exogenous influences on persistence intention. This study examines a final sample of 231 entrepreneurs from three data sources. The findings of this study indicate that subjective norms play a mediating role in the relationship between prior founding experience and persistence intention. The relationship between the perceived quality of prior entrepreneurial exposure and persistence intention behavior is also explained by subjective norms. Overall, it is not the exposure that leads to persistence intention, but the quality of the exposure that influences entrepreneur’s intention to remain in business. This study extends entrepreneurship literature on how exogenous variables impact entrepreneurial persistence intention through attitudinal factors.

This study examines whether emerging growth company (EGC) investors respond to the annual required internal control disclosures over financial reporting (ICFR). I develop three hypotheses to test across the EGC lifecycle. Specifically, I investigate whether the first year ICFR disclosure, the remediation of a previously reported material weakness ICFR disclosure and the EGC exit are associated with the firm’s cumulative abnormal return over a three-day event window. Prior literature has observed that ICFR disclosures by management and the ICFR audit opinion can be shown to be informative to investors. However, I am not aware of any study investigating whether the EGC investors respond to this type of information. I find that the reported ICFR disclosures are not associated with cumulative abnormal returns during their initial ICFR report disclosure or upon exit as informative but do respond to the reporting of material weakness remediation.

In Essay 1, I investigate the Equity Duration Hypothesis, which adapts Macaulay’s fixed income analysis to equity securities, finding evidence that dividend payers are less volatile than nonpayers and that dividend yield is negatively associated with volatility for the all-firms sample. Within the payer sample, however, I find unexpected evidence of a positive association when yield includes all dividends but a conflicting negative association when yield includes only quarterly dividends. This ambiguous evidence is corroborated by a one-year portfolio approach, as a previously strengthening negative relationship has transitioned to a strengthening positive one, with results demonstrably trending against the EDH in recent decades. I further find that high-yield stocks that have experienced negative price shocks are highly volatile and strong support for the EDH using firm-level earnings and cash flows as a proxy for dividends, allowing extension of the analysis to nonpaying firms. Unfortunately, I find abundant evidence supporting the assertions of many researchers who suggest that ED is not a unique asset pricing factor, but rather represents a composite of a firm’s characteristics and is redundant with other factors known to be associated with volatility.

I examine the importance of corporate scientific research. It is crucial to understand the role of corporate scientific research because such a knowledge could form an appropriate response to the current decline of corporate scientific research amidst the evolving innovation ecosystem featured with growing university research and tech companies’ research. R&D is often treated as a single construct in accounting and finance research for firm innovation. However, corporate scientific research (“R”) has different implications for firm innovations, “R” creates new knowledge, and reduced investment in "R" may lead to a loss of internal research capability, disrupting the speed and quality of innovation. As such, it is necessary and meaningful to examine "R" separately from "R&D."
Historically, corporate scientific research has played an important role in driving breakthrough innovations. Beginning in the 1980s, there has been a decline in corporate scientific research in favor of university research and tech companies’ research. Consequently, this raises a question: if corporate scientific research was important, is it still important? This is a fundamental question because if corporate scientific research is still important, declining or even stagnant corporate scientific research would present an issue of concern for firms and the economy.

Supply chain challenges have been significantly affected by both demand and supply on a global level. The selection of manufacturing countries has become critical to firms and their boards, even more so coming out of the COVID-19 global pandemic. The present study focuses on how firms select countries and regions to de-risk future global apparel sourcing, as countries that have been dependable in the past may not be in the future based on frequent environmental jolts, legacy supply chain failures, shifting government policy, and extreme volatility. The result of this study is a decision model for manufacturing country selection. This research was focused on the apparel industry; however, further research may indicate that it is applicable to other industries. A group of criteria was selected, the relative significance of these criterion was determined using the Analytical Hierarchy Process (AHP). The AHP methodology was applied in a case study as a decision-making tool to enable decision-makers to assess the most suitable countries for manufacturing country selection. The result of this study is a decision model for manufacturing country selection based on multiple criteria weighted by industry experts using Analytical Hierarchy Process (AHP). In developing the model we utilize data from 61 countries representing over 95% of all the global apparel exports, with criteria utilized originating from 10 indices.

The world is ever-changing with technological advancement. National economies and private organizations are shifting their infrastructure to adapt to innovation and technology. We are seeing a major shift in our transportation ecosystem as well. Automotive manufacturers are launching fully electric semi-truck (EST) on the road for freight transportation. Electric trucks will have a long-term effect on many industries and the national economy in the United States. Compared to conventional automobiles, the limited range of electric vehicles is a major obstacle. To adapt electric vehicles (EVs) to our transportation system, the U.S. needs a proper charging infrastructure in our grid. Though we have been adapting the passenger EVs, the EST needs larger charging infrastructure capabilities to charge the large batteries of these trucks to complete the journey. The most important aspect is the geographical locations of these mega charging stations along U.S. highways. To analyze the optimal locations of these charging infrastructures, we use the framework from Csiszár et al. (2020), an origin-destination (O-D) data model. OD is classified as the original location of the freight to the end destination. We also use the flow-refueling location model (FRLM) from He et al. (2019). This framework showcases the optimal locations in each route in order to complete the OD pairs. We use data from the U.S. department of energy for the locations of charging stations. Furthermore, we use U.S. department of transportation highway & transportation data to procure the major O-Ds of freight transportation.