Matching Items (17)
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- All Subjects: Internet of Things
- Creators: Department of Finance
Description
Social entrepreneurship has received a great deal of attention in recent years. Scholars constantly debate of the meaning of the term and the direction of the field. This paper explores literature written between the years 2010 \u2014 2015 in an effort to understand the current state of social entrepreneurship and gain insight as to the direction it is headed. This paper looks at definitions, characteristics, geographical differences, legal designations, and major themes such as social enterprise, social innovation, & social value as well as the implications for performance measures in an attempt to understand the broad concept that is social entrepreneurship.
ContributorsTalarico, Anthony (Author) / Shockley, Gordon (Thesis director) / Hayter, Christopher (Committee member) / Department of Management (Contributor) / School of Public Affairs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
For our collaborative thesis we explored the US electric utility market and how the Internet of Things technology movement could capture a possible advancement of the current existing grid. Our objective of this project was to successfully understand the market trends in the utility space and identify where a semiconductor manufacturing company, with a focus on IoT technology, could penetrate the market using their products. The methodology used for our research was to conduct industry interviews to formulate common trends in the utility and industrial hardware manufacturer industries. From there, we composed various strategies that The Company should explore. These strategies were backed up using qualitative reasoning and forecasted discounted cash flow and net present value analysis. We confirmed that The Company should use specific silicon microprocessors and microcontrollers that pertained to each of the four devices analytics demand. Along with a silicon strategy, our group believes that there is a strong argument for a data analytics software package by forming strategic partnerships in this space.
ContributorsLlazani, Loris (Co-author) / Ruland, Matthew (Co-author) / Medl, Jordan (Co-author) / Crowe, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Department of Economics (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Department of Information Systems (Contributor) / Hugh Downs School of Human Communication (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
As the IoT (Internet of Things) market continues to grow, Company X needs to find a way to penetrate the market and establish larger market share. The problem with Company X's current strategy and cost structure lies in the fact that the fastest growing portion of the IoT market is microcontrollers (MCUs). As Company X currently holds its focus in manufacturing microprocessors (MPUs), the current manufacturing strategy is not optimal for entering competitively into the MCU space. Within the MCU space, the companies that are competing the best do not utilize such high level manufacturing processes because these low cost products do not demand them. Given that the MCU market is largely untested by Company X and its products would need to be manufactured at increasingly lower costs, it runs the risk of over producing and holding obsolete inventory that is either scrapped or sold at or below cost. In order to eliminate that risk, we will explore alternative manufacturing strategies for Company X's MCU products specifically, which will allow for a more optimal cost structure and ultimately a more profitable Internet of Things Group (IoTG). The IoT MCU ecosystem does not require the high powered technology Company X is currently manufacturing and therefore, Company X loses large margins due to its unnecessary leading technology. Since cash is king, pursuing a fully external model for MCU design and manufacturing processes will generate the highest NPV for Company X. It also will increase Company X's market share, which is extremely important given that every tech company in the world is trying to get its hands into the IoT market. It is possible that in ten to thirty years down the road, Company X can manufacture enough units to keep its products in-house, but this is not feasible in the foreseeable future. For now, Company X should focus on the cost market of MCUs by driving its prices down while maintaining low costs due to the variables of COGS and R&D given in our fully external strategy.
ContributorsKadi, Bengimen (Co-author) / Peterson, Tyler (Co-author) / Langmack, Haley (Co-author) / Quintana, Vince (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Supply Chain Management (Contributor) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / Department of Marketing (Contributor) / School of Accountancy (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The purpose of this thesis was to design a market entrance strategy for Company X to enter the microcontroller (MCU) market within the Internet of Things (IoT). The five IoT segments are automotive; medical; retail; industrial; and military, aerospace, and government. To reach a final decision, we will research the markets, analyze make versus buy scenarios, and deliver a financial analysis on the chosen strategy. Based on the potential financial benefits and compatibility with Company X's current business model, we recommend that Company X enter the automotive segment through mergers & acquisitions (M&A). After analyzing the supply chain structure of the automotive IoT, we advise Company X to acquire Freescale Semiconductor for $46.98 per share.
ContributorsBradley, Rachel (Co-author) / Fankhauser, Elisa (Co-author) / McCoach, Robert (Co-author) / Zheng, Weilin (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Mike (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of International Letters and Cultures (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05
Description
Investment real estate is unique among similar financial instruments by nature of each property's internal complexities and interaction with the external economy. Where a majority of tradable assets are static goods within a dynamic market, real estate investments are dynamic goods within a dynamic market. Furthermore, investment real estate, particularly commercial properties, not only interacts with the surrounding economy, it reflects it. Alive with tenancy, each and every commercial investment property provides a microeconomic view of businesses that make up the local economy. Management of commercial investment real estate captures this economic snapshot in a unique abundance of untapped statistical data. While analysis of such data is undeniably valuable, the efforts involved with this process are time consuming. Given this unutilized potential our team has develop proprietary software to analyze this data and communicate the results automatically though and easy to use interface. We have worked with a local real estate property management and ownership firm, Reliance Management, to develop this system through the use of their current, historical, and future data. Our team has also built a relationship with the executives of Reliance Management to review functionality and pertinence of the system we have dubbed, Reliance Dashboard.
ContributorsBurton, Daryl (Co-author) / Workman, Jack (Co-author) / LePine, Marcie (Thesis director) / Atkinson, Robert (Committee member) / Barrett, The Honors College (Contributor) / Department of Finance (Contributor) / Department of Management (Contributor) / Computer Science and Engineering Program (Contributor)
Created2015-05
Description
The beautiful game is unpredictable. Arguably half of soccer is entirely out of our control, instead being determined by a simple concept: luck. But what of the other 50%? Ultimately, the goal of the rapidly-advancing technologies and analytics in on-field sports performance is to maximize the elements that we \u2014 the coaches, players, decision-makers, and analysts \u2014 truly control. Once perceived as too mathematical and systemized, contradicting coaches' intuitions, sports sciences are burgeoning in the sports arena both in applied and mainstream popularity. While the industry has its critics and is far shy of its pinnacle, its advancements and successes cannot be ignored. From the training ground to match day decision-making, analytics are embedded in soccer and sport. Technology and analytics are vastly utilized throughout sporting organizations across a myriad of sports and purposes: scouting and drafting, fan experience, ticketing, etc. However, while these areas must be addressed in discussing the success of analytics in assessing situations and reducing uncertainty, my central thesis relates to the technological capabilities and corresponding analytical tools utilized to identify, assess, and improve on-field soccer performance: match analysis. This paper's core focuses on optimizing performance in soccer players in three specific areas of performance: technical abilities and tactics, physiology, and neuroscience.
ContributorsHeckendorn, Jason Farrell (Author) / Eaton, John (Thesis director) / Ostrom, Amy (Committee member) / Barrett, The Honors College (Contributor) / Department of Marketing (Contributor) / W. P. Carey School of Business (Contributor) / Department of Management (Contributor)
Created2014-05
Description
The basis of this project was to analyze the potential cost savings derived from the implementation of an ultrasonic flaw detector for gas pipes in factories. The group began by researching the market of the Industrial Internet of Things. IIoT is a very attractive market for investment, as connected technologies are become both more advanced and more affordable. Factory automation also saves costs of human capital, maintenance, and bad product cost as well as safety. After doing this preliminary research, the group continued by identifying potential solutions to current shortcomings of the manufacturing status quo. After narrowing down the options, the ultrasonic flaw detector appeared to have the highest potential for success in Company X's factories. The group began doing research on what physical components would go into this solution. They found pricing for all of the various parts of such a device as well as estimated labor, maintenance, and implementation costs. After estimating these costs, the team began the construction of a detailed financial model to generate the hypothetical net present value of such a tool. After presenting two times to a panel of Company X employees, the group decided to focus only on cost savings for Company X, and not the potential revenues of selling the whole solution. They ran a sensitivity analysis on all of the factors that contributed to the NPV of the project, and discovered that the estimated percentage of scrapped product resulting from gas leaks and the percentage of gas lost to leaks contributed the most to the NPV.
ContributorsFlick, Jacob (Co-author) / Alam, Mustafa (Co-author) / Nguyen, Mong (Co-author) / Zhang, Zihan (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Information Systems (Contributor) / WPC Graduate Programs (Contributor) / School of International Letters and Culture (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
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 purpose and goal of this project is to pinpoint a potential use case for Company X to invest in to sell their 5G modems. As 5G technology is growing to be a dominant force in global markets, Company X is looking to capitalize on the emerging technology by selling their 5G modems for Internet of Things applications. Research and gathering of information involved understanding cellular connectivity, modem operations and applications, companies in related industries, the history of the wireless spectrum, the pillars of 5G technology, and the plethora of use cases enabled by 5G. Looking at smart street lights as a potential use case for Company X, analyses were conducted to recommend whether Company X should invest in smart street lights. These analyses ranged from researching Company X’s competitors to performing a pro forma financial analysis to see if it is financially viable for Company X to enter the smart street light industry. The final recommendation is for Company X to not invest in smart street lighting.
ContributorsPannala, Ishan R (Co-author) / Alcaron, Sandra (Co-author) / Nilles, Robert (Co-author) / Wells, Dwight (Co-author) / Simonson, Mark (Thesis director) / Reber, Kevin (Committee member) / Department of Finance (Contributor) / Department of Supply Chain Management (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Our research encompassed the prospect draft in baseball and looked at what type of player teams drafted to maximize value. We wanted to know which position returned the best value to the team that drafted them, and which level is safer to draft players from, college or high school. We decided to look at draft data from 2006-2010 for the first ten rounds of players selected. Because there is only a monetary cap on players drafted in the first ten rounds we restricted our data to these players. Once we set up the parameters we compiled a spreadsheet of these players with both their signing bonuses and their wins above replacement (WAR). This allowed us to see how much a team was spending per win at the major league level. After the data was compiled we made pivot tables and graphs to visually represent our data and better understand the numbers. We found that the worst position that MLB teams could draft would be high school second baseman. They returned the lowest WAR of any player that we looked at. In general though high school players were more costly to sign and had lower WARs than their college counterparts making them, on average, a worse pick value wise. The best position you could pick was college shortstops. They had the trifecta of the best signability of all players, along with one of the highest WARs and lowest signing bonuses. These were three of the main factors that you want with your draft pick and they ranked near the top in all three categories. This research can help give guidelines to Major League teams as they go to select players in the draft. While there are always going to be exceptions to trends, by following the enclosed research teams can minimize risk in the draft.
ContributorsValentine, Robert (Co-author) / Johnson, Ben (Co-author) / Eaton, John (Thesis director) / Goegan, Brian (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / School of Accountancy (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05