Over the course of 2020, individuals and organizations were thrown various unprecedented obstacles that necessitated flexibility, empathy, and understanding. Many organizations were forced to reevaluate their financial status, their purpose, and how they could provide for their employees. The COVID-19 pandemic meant that most companies had to introduce a ‘work from home’ policy, drastically decreasing the face-to-face contact that employees had with each other and leadership. The virus, coupled with the social and political unrest in the U.S. in the wake of the Black Lives Matter movement and the 2020 presidential election, inspired many companies to reframe their organization and redefine their goals.<br/> The B2B (business-to-business) Marketing Agency, The Mx Group, is preparing for a change in leadership, with the current Chief Executive Officer and Founder stepping down, being replaced by the President of the company. The company plans to execute the transition in the spring of 2022, allowing them the rest of 2021 to plan for the change, catering to employees’ individual and the company’s collective needs. It was also prompted by factors such as the COVID-19 pandemic to reevaluate the values that it upholds as an organization, coinciding with the change in leadership. Leaders of the company are actively encouraging employees to engage with these values by recognizing when a colleague performs in alignment with a value.<br/> In reframing their organization, The Mx Group has a significant opportunity to uniquely position itself in the industry. Lee G. Bolman and Terrence E. Deal (2017) introduced four frames: human resources, symbolic, structural, and political, as a way to guide a transformative application of leadership and management in business. Analyzed from these perspectives, The Mx Group can utilize contemporary ideas to efficiently and effectively seize its opportunity of embedding new values and a change in leadership.
Ultimate Frisbee or "Ultimate," is a fast growing field sport that is being played competitively at universities across the country. Many mid-tier college teams have the goal of winning as many games as possible, however they also need to grow their program by training and retaining new players. The purpose of this project was to create a prototype statistical tool that maximizes a player line-up's probability of scoring the next point, while having as equal playing time across all experienced and novice players as possible. Game, player, and team data was collected for 25 different games played over the course of 4 tournaments during Fall 2017 and early Spring 2018 using the UltiAnalytics iPad application. "Amount of Top 1/3 Players" was the measure of equal playing time, and "Line Efficiency" and "Line Interaction" represented a line's probability of scoring. After running a logistic regression, Line Efficiency was found to be the more accurate predictor of scoring outcome than Line Interaction. An "Equal PT Measure vs. Line Efficiency" graph was then created and the plot showed what the optimal lines were depending on what the user's preferences were at that point in time. Possible next steps include testing the model and refining it as needed.
Virtual Reality is being widely adapted for use in the consumer market. There are adaptations of the technology for every purpose, from education, to gaming, and even medical. There are businesses being formed worldwide that incorporate the gaming utility in an arcade/internet café style. However, there are other plausible business models. There is the preexisting model that companies are currently using, another option is to add this technology to preexisting physical arcades, and to create a new business with practices decided by consumer statistics. These three models were tested in this study to determine the profitability, feasibility, and best practices for each. Each business model appears to be incredibly profitable based on the assumptions used for this study.
The first module of this thesis will create a statistically accurate representation of customers arriving at ticket purchasing channels. Each customer's attributes are: arrival time, origin and destination, number of destined tickets, and willingness to pay. Each attribute can be generated using a specific distribution.
The created customers will then be used to simulate the purchase of tickets and overall revenue for a flight network. With a valid simulation, airlines will be able to compare the performance of different RM engines under various circumstances.