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- Creators: Department of Finance
- Creators: Industrial, Systems
Description
Billions of people around the world deal with the struggles of poverty every day. Consequently, a number of others have committed themselves to help alleviate poverty. Many various methods are used, and a current consensus on the best method to alleviate poverty is lacking. Generally the methods used or researched exist somewhere on the spectrum between top-down and bottom-up approaches to fighting poverty. This paper analyzes a specific method proposed by C.K. Prahalad known as the Bottom of the Pyramid solution. The premise of the method is that large multinational corporations should utilize the large conglomerate of money that exists amongst poor people \u2014 created due to the sheer number of poor people \u2014 for business ventures. Concurrently, the poor people can benefit from the company's entrance. This method has received acclaim theoretically, but still needs empirical evidence to prove its practicality. This paper compares this approach with other approaches, considers international development data trends, and analyzes case studies of actual attempts that provide insight into the approach's potential for success. The market of poor people at the bottom of the pyramid is extremely segmented which makes it very difficult for large companies to financially prosper. It is even harder to establish mutual benefit between the large corporation and the poor. It has been found that although aspects of the bottom of the pyramid method hold merit, higher potential for alleviating poverty exists when small companies venture into this space rather than large multinational corporations. Small companies can conform to a single community and niche economy to prosper \u2014 a flexibility that large companies lack. Moving forward, analyzing the actual attempts provides the best and only empirical insights; hence, it will be important to consider more approaches into developing economies as they materialize.
ContributorsSanchez, Derek Javier (Author) / Henderson, Mark (Thesis director) / Shunk, Dan (Committee member) / Industrial, Systems (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Exchange traded funds (ETFs) in many ways are similar to more traditional closed-end mutual
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to minimize the deviations that occur
between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However
while this does cause ETF deviations to be generally lower than their mutual fund counterparts,
as our paper explores this process does not eliminate these deviations completely. This article
builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of
premiums (discounts) of ETFs from their fair market value. And looks to see if these premia
have changed in the last 10 years. Our paper then diverges from the original and takes a deeper
look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be
explained through a linear combination consisting of two variables: a categorical (Domestic[US],
Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds
that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market
indicators such as the economic freedom index and investment freedom index are insignificant
predictors of an ETFs standard deviation of premia. These findings differ somewhat from
existing literature which indicate that these factors should have a significant impact on the
predictive ability of an ETFs standard deviation of premia.
funds, although thee differ in a crucial way. ETFs rely on a creation and redemption feature to
achieve their functionality and this mechanism is designed to minimize the deviations that occur
between the ETF’s listed price and the net asset value of the ETF’s underlying assets. However
while this does cause ETF deviations to be generally lower than their mutual fund counterparts,
as our paper explores this process does not eliminate these deviations completely. This article
builds off an earlier paper by Engle and Sarkar (2006) that investigates these properties of
premiums (discounts) of ETFs from their fair market value. And looks to see if these premia
have changed in the last 10 years. Our paper then diverges from the original and takes a deeper
look into the standard deviations of these premia specifically.
Our findings show that over 70% of an ETFs standard deviation of premia can be
explained through a linear combination consisting of two variables: a categorical (Domestic[US],
Developed, Emerging) and a discrete variable (time-difference from US). This paper also finds
that more traditional metrics such as market cap, ETF price volatility, and even 3rd party market
indicators such as the economic freedom index and investment freedom index are insignificant
predictors of an ETFs standard deviation of premia. These findings differ somewhat from
existing literature which indicate that these factors should have a significant impact on the
predictive ability of an ETFs standard deviation of premia.
ContributorsHenning, Thomas Louis (Co-author) / Zhang, Jingbo (Co-author) / Simonson, Mark (Thesis director) / Wendell, Licon (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation study. This research seeks to determine the acquisition processes that contribute significantly to total simulated program time in the acquisition system for all programs reaching Milestone C. Specifically, this research examines the effect of increased scope management, technology maturity, and decreased variation and mean process times in post-Design Readiness Review contractor activities by performing additional simulation analyses. Potential policies are formulated from the results to further improve program acquisition completion time.
ContributorsWorger, Danielle Marie (Author) / Wu, Teresa (Thesis director) / Shunk, Dan (Committee member) / Wirthlin, J. Robert (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
This paper attempts to introduce analytics and regression techniques into the National Hockey League. Hockey as a sport has been a slow adapter of analytics, and this can be attributed to poor data collection methods. Using data collected for hockeyreference.com, and R statistical software, the number of wins a team experiences will be predicted using Goals For and Goals Against statistics from 2005-2017. The model showed statistical significance and strong normality throughout the data. The number of wins each team was expected to experience in 2016-2017 was predicted using the model and then compared to the actual number of games each team won. To further analyze the validity of the model, the expected playoff outcome for 2016-2017 was compared to the observed playoff outcome. The discussion focused on team's that did not fit the model or traditional analytics and expected forecasts. The possible discrepancies were analyzed using the Las Vegas Golden Knights as a case study. Possible next steps for data analysis are presented and the role of future technology and innovation in hockey analytics is discussed and predicted.
ContributorsVermeer, Brandon Elliot (Author) / Goegan, Brian (Thesis director) / Eaton, John (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
The widespread use of statistical analysis in sports-particularly Baseball- has made it increasingly necessary for small and mid-market teams to find ways to maintain their analytical advantages over large market clubs. In baseball, an opportunity for exists for teams with limited financial resources to sign players under team control to long-term contracts before other teams can bid for their services in free agency. If small and mid-market clubs can successfully identify talented players early, clubs can save money, achieve cost certainty and remain competitive for longer periods of time. These deals are also advantageous to players since they receive job security and greater financial dividends earlier in their career. The objective of this paper is to develop a regression-based predictive model that teams can use to forecast the performance of young baseball players with limited Major League experience. There were several tasks conducted to achieve this goal: (1) Data was obtained from Major League Baseball and Lahman's Baseball Database and sorted using Excel macros for easier analysis. (2) Players were separated into three positional groups depending on similar fielding requirements and offensive profiles: Group I was comprised of first and third basemen, Group II contains second basemen, shortstops, and center fielders and Group III contains left and right fielders. (3) Based on the context of baseball and the nature of offensive performance metrics, only players who achieve greater than 200 plate appearances within the first two years of their major league debut are included in this analysis. (4) The statistical software package JMP was used to create regression models of each group and analyze the residuals for any irregularities or normality violations. Once the models were developed, slight adjustments were made to improve the accuracy of the forecasts and identify opportunities for future work. It was discovered that Group I and Group III were the easiest player groupings to forecast while Group II required several attempts to improve the model.
ContributorsJack, Nathan Scott (Author) / Shunk, Dan (Thesis director) / Montgomery, Douglas (Committee member) / Borror, Connie (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
In 2010, for the first time in human history, more than half of the world's total population lived in cities; this number is expected to increase to 60% or more by 2050. The goal of this research effort is to create a comprehensive model and modelling framework for megacities, middleweight cities, and urban agglomerations, collectively referred to as dense urban areas. The motivation for this project comes from the United States Army's desire for readiness in all operating environments including dense urban areas. Though there is valuable insight in research to support Army operational behaviors, megacities are of unique interest to nearly every societal sector imaginable. A novel application for determining both main effects and interactive effects between factors within a dense urban area is a Design of Experiments- providing insight on factor causations. Regression Modelling can also be employed for analysis of dense urban areas, providing wide ranging insights into correlations between factors and their interactions. Past studies involving megacities concern themselves with general trend of cities and their operation. This study is unique in its efforts to model a singular megacity to enable decision support for military operational planning, as well as potential decision support to city planners to increase the sustainability of these dense urban areas and megacities.
ContributorsMathesen, Logan Michael (Author) / Zenzen, Frances (Thesis director) / Jennings, Cheryl (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Africa has some of the "fastest growing economies," yet there is a lack of a middle class (Economist). Natural resources have attracted foreign investments, however, most of the revenue exit these economies. What remains a consistent, permanent advantage is culture; it has been the most integrated core value before and after colonialism. The concept of culture has become a part of the identity of Africa and it has not been leveraged to its full potential. The 2013 Creative Economy Report states, "Culture is a way to create jobs and improve people's lives. It empowers people. It works for development" (UNESCO/UNDP). Cultural industries create local sustainable jobs that are less susceptible to the fluctuation of the global economy compared to jobs in factories and multinational companies. They are based on "local tacit know how" that is not accessible globally as they are people intensive rather than capital intensive (Scott A.J, 1999). Activ8 seeks to tap into this opportunity by maximizing the economic potential of developing economies by investing in their cultural industries. Activ8 aspires to accomplish this by targeting two sets of customers: creators, who are the activators, and investors. Our activators consist of two target segments: one living and working in these industries in a developing country, and the other being refugee clients who may have been exposed to a cultural industry and may want to pursue developing cultural products in their new country of asylum. Our investors are globally minded individuals who want to be culturally aware, have an appreciation for authentic cultural products, or seek to invest in entrepreneurial pursuits in Africa. During our first phase we will focus on the cultural industries in Ghana, West Africa. This will range from products in the textiles industry to sculptures and traditional instruments. We plan to pilot the first phase in Ghana and in the second phase, form a partnership with the International Rescue Committee, a refugee settlement agency, in Arizona. Our goals are to provide education and mentoring, market accessibility, product development, and financing to encourage and empower activators to be self-sufficient and successful cultural entrepreneurs, whiles improving economic development in their communities. Our online store will feature our activators' authentic products, their stories, and the cultural importance of each product. There will also be a platform for entrepreneurs in other industries in Africa to connect with venture capitalists or angel investors around the world. The educational component will be infused with product development and entrepreneurship training derived from the "From AHA!! to EXIT" strategy coined by Aram Chavez from the College of Technology and Innovation at ASU. In order for Activ8 to successfully execute its mission, Activ8 will need to be able to give our team and our activators access to technology, mentorship, and financial resources to operate an online store and rum Activ8's educational program. We also envision creating partnerships with boutiques and retail corporations to adapt these cultural products. Our long-term goal is formulate the conditions conducive for economic growth and sustainable development to ensure Africans become the main agents of development.
ContributorsAdusei, Esther (Author) / Chavez, Aram (Thesis director) / Schoellman, Todd (Committee member) / Department of Supply Chain Management (Contributor) / School of International Letters and Cultures (Contributor) / W. P. Carey School of Business (Contributor) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
The growth of fintech companies in developing countries has led to increased levels of economic development and financial inclusion. This thesis explores the reasons for the success of these companies, with a focus on the impact they have on the local economy and their ability to provide financial services to underserved populations. The intent of this thesis is to educate the reader on the overall landscape of financial technology companies in developing countries. The writing will examine the specific types of services offered by these fintech companies that operate in developing countries and the catalysts that make them successful. It will also cover the impact that these companies have on the nations they operate in by looking at contributions to overall economic development and financial inclusion. The results of this literature will have implications for business leaders, policymakers, and investors interested in promoting financial inclusion and economic development through fintech.
ContributorsLee, Kawika (Author) / Licon, Wendell (Thesis director) / Garrett, James (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Economics Program in CLAS (Contributor)
Created2023-05