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Optimize The Effectiveness Of Recruiting Campaigns, Ryan A. Talk, Lakshmi Bobbillapati, Marshall Coyle 2019 Southern Methodist University

Optimize The Effectiveness Of Recruiting Campaigns, Ryan A. Talk, Lakshmi Bobbillapati, Marshall Coyle

SMU Data Science Review

Abstract. Recruiting marketing plays an important role in the talent acquisition strategy today. To find the best candidates, companies make substantial investments through numerous recruiting agencies, job boards, and internal systems such as Indeed, LinkedIn, Monster, Talent Communities. In this paper we obtained a company’s LinkedIn Job Posting data to try to predict the number of visits they will receive for each job posting based on the time of the year it is posted. We compare AR(1), AR(2), AR(52), MA(1), and ARMA(1, 1) time series methods to a baseline of a persistence model. We ...


Demand Forecasting: An Open-Source Approach, Murtada Shubbar, Jared Smith 2019 Southern Methodist University

Demand Forecasting: An Open-Source Approach, Murtada Shubbar, Jared Smith

SMU Data Science Review

In this paper, we compare demand forecasting methods used by the supply chain department at Bilports to open-source forecasting methods. The design and implementation of the open-source forecasting system also attempts to use several external datasets such as consumer sentiment, housing permit starts, and weather to improve prediction quality. Additionally, the performance of the forecast is evaluated by the reduction of shipment lead times from China, the company’s primary vendor. The objective of our paper is to improve Bilports’s forecasting capabilities. The primary motivation of this paper is to increase forecasting accuracy and identify the weaknesses of the ...


Leveraging Reviews To Improve User Experience, Anthony Schams, Iram Bakhtiar, Cristina Stanley 2019 Southern Methodist University

Leveraging Reviews To Improve User Experience, Anthony Schams, Iram Bakhtiar, Cristina Stanley

SMU Data Science Review

In this paper, we will explore and present a method of finding characteristics of a restaurant using its reviews through machine learning algorithms. We begin by building models to predict the ratings of individual reviews using text and categorical features. This is to examine the efficacy of the algorithms to the task. Both XGBoost and logistic regression will be examined. With these models, our goal is then to identify key phrases in reviews that are correlated with positive and negative experience. Our analysis makes use of review data publicly made available by Yelp. Key bigrams extracted were non-specific to the ...


The Performance Of Military Defense Contracted Companies After September 11th, 2001: The Case Of Politically Connected Companies, Derek J. Larsen 2019 Utah State University

The Performance Of Military Defense Contracted Companies After September 11th, 2001: The Case Of Politically Connected Companies, Derek J. Larsen

All Graduate Plan B and other Reports

This paper examines the effect that the terrorist attacks on September 11th, 2001 had on the stock prices of companies within the military defense industry. In addition, this paper studies the effect of the defense firms’ political engagement (through lobbying activities) and how this affected the stock price response to the terrorist attacks. Our study finds that the cumulative abnormal returns of these companies are positively significant and that companies who lobbied experienced higher returns relative to those who did not lobby.


What Makes A Movie Successful : Using Analytics To Study Box Office Hits, Sarah E. Joseph 2019 University of Tennessee, Knoxville

What Makes A Movie Successful : Using Analytics To Study Box Office Hits, Sarah E. Joseph

Chancellor’s Honors Program Projects

No abstract provided.


The Relationship Between Capital Structure And Profitability Of United States Manufacturing Companies: An Empirical Analysis, Cuibing Wu 2019 Morehead State University

The Relationship Between Capital Structure And Profitability Of United States Manufacturing Companies: An Empirical Analysis, Cuibing Wu

Morehead State Theses and Dissertations

A thesis presented to the faculty of the Elmer R. Smith College of Business and Technology at Morehead State University in partial fulfillment of the requirements for the Degree Master of Science by Cuibing Wu on April 22, 2019.


Systemic Risk And The Ripple Effect In The Supply Chain, Kevin P. Scheibe, Jennifer Blackhurst 2019 Iowa State University

Systemic Risk And The Ripple Effect In The Supply Chain, Kevin P. Scheibe, Jennifer Blackhurst

Supply Chain and Information Systems Publications

Supply chains are highly complex systems, and disruptions may ripple through these systems in unexpected ways, but they may also start in unexpected ways. We investigate the causes of ripple effect through the lens of systemic risk. We derive supply chain systemic risk from the finance discipline where sources of risk are found in systemic risk-taking, contagion, and amplification mechanisms. In a supply chain context, we identify three dimensions that influence systemic risk, the nature of a disruption, the structure, and dependency of the supply chain, and the decision-making. Within these three dimensions, there are several factors including correlation of ...


Cyanotech: A Strategic Audit, Trent Hoppe 2019 University of Nebraska - Lincoln

Cyanotech: A Strategic Audit, Trent Hoppe

Honors Theses, University of Nebraska-Lincoln

Microalgae is a fascinating group of organisms that possess a diverse array of interesting traits and benefits relevant to food, medicine, and biofuel. Extensive research behind the viability of microalgae to disrupt the market has sparked an emergent microalgae industry. Founded in 1983, one of the top microalgae companies in the world today is Cyanotech. With a 90-acre algae farm in Kailua-Kona, Hawaii and two flagship microalgae products that are world leaders in their categories, Cyanotech is well- positioned be setting the course for the industry and revolutionizing the use microalgae commercially. Despite these favorable attributes, Cyanotech has been trapped ...


A Strategic Audit Of Nintendo Co., Ltd., Emily Wagner 2019 University of Nebraska - Lincoln

A Strategic Audit Of Nintendo Co., Ltd., Emily Wagner

Honors Theses, University of Nebraska-Lincoln

The astounding success of the Nintendo Switch since its launch in March 2017 has brought Nintendo back into the spotlight of the gaming industry. However, what strategies led to the Switch’s success, enabling Nintendo to come back from the complete and utter failure of the Wii U? Also, what does Nintendo need to do to maintain its success over the lifetime of the Switch and beyond? This paper offers a strategic analysis of Nintendo, examining the company’s history, recent products, competitive advantages, and reasons for the success of the Switch. It also provides an analysis of Nintendo’s ...


The Importance Of School District Quality In The Columbus Real Estate Market, Ryan Karapas 2019 Otterbein University

The Importance Of School District Quality In The Columbus Real Estate Market, Ryan Karapas

Honors Thesis Projects

Using a random sample of 100 houses sold between the months of October 2018 and January 2019 in the greater Columbus, Ohio area, this paper investigates the relationship between school district quality and the selling price of houses. The results show that school district quality has a positive and statistically significant influence on the Columbus real estate market. An increase of one letter grade in school district quality (calculated using output-related factors such as student performance) leads to a 13% increase in the selling price of a house. When using the average house price in my data set of $254 ...


The Use Of Blockchain Technology To Solve Common Challenges In The Supply Chain, Michael Cohen 2019 University of Southern Maine

The Use Of Blockchain Technology To Solve Common Challenges In The Supply Chain, Michael Cohen

Thinking Matters Symposium

When blockchain was first invented by Satoshi Nakamoto in 2008 it was thought to only be used for Bitcoin; a digital currency. It had been used to record transactions made without needing a third party authenticator. Blockchain showed the ability to reduce costs, speed up transactions, and reinvent the processes of how things are done. Once people fully understood what blockchain does, entrepreneurs and investors realized it could be used for much more than just a cryptocurrency. It could be applied to transportation, products sold, food, the medical industry, and much more.
With the help of blockchain, industries can operate ...


Strategic Audit Of Proxibid, Maxim van Klinken 2019 University of Nebraska - Lincoln

Strategic Audit Of Proxibid, Maxim Van Klinken

Honors Theses, University of Nebraska-Lincoln

Proxibid is a platform for connecting buyers and sellers of high-value items. As part of their continued growth, they are running into issues with the categorization of their goods into their hierarchy since the classification of these items is becoming a monumental task that will become unreasonable for humans to do. They have dedicated employees to manually classify well over 10,000 incoming items into over 2000 categories every week. The bulk of those items come in the later half of the work week. This paper will focus on how to tackle this problem while remaining competitive and preventing future ...


Amarcord Inc: Combating Money Laundering Using Data Analytics, Alyssa Ardai 2019 Merrimack College

Amarcord Inc: Combating Money Laundering Using Data Analytics, Alyssa Ardai

Honors Program Contracts

This case study of Amarcord Incorporative will be discussing how Amarcord combats money laundering using data analytics. With the addition of new laws from 1970-current, it is harder for money laundering to be committed due to the requirement of reports and bank inspections. Using data analytics techniques such as the time-series analysis, we can analyze data sets to look closer and tell what transactions are money laundering, and what are actual ones.


Effects Of Terrorism On The U.S. Stock Market: Evidence From High Frequency Data, Kyla Scanlon 2019 Western Kentucky University

Effects Of Terrorism On The U.S. Stock Market: Evidence From High Frequency Data, Kyla Scanlon

Honors College Capstone Experience/Thesis Projects

This paper investigates the effects that terrorist attacks and mass shootings had on the U.S. stock market, using high frequency intraday data to identify stock price and variability reactions in the hours after the attack. The impact that terrorist attacks had on price level variability was examined using the generalized autoregressive conditional heteroskedasticity (GARCH) model. The market reaction to domestic versus foreign attacks was examined to measure a potential for contagion across financial markets. The potential for flight-to-safety/quality and capital reallocation in response to terrorist attacks were measured using ordinary least squares (OLS) model, measuring the respective betas ...


Development And Protection Of Economic Competition In Kosovo: Case Study Gjilan Region, Gani Asllani, Bedri Statovci, Gentiana Gega 2019 James Madison University

Development And Protection Of Economic Competition In Kosovo: Case Study Gjilan Region, Gani Asllani, Bedri Statovci, Gentiana Gega

International Journal on Responsibility

This paper investigates development and protection of economic competition in Kosovo focusing on the analysis of the level of competition in one region of Kosovo (the Gjilan region). The paper deals with the legislative aspects of competition, the sensitive sectors (banks, insurance, gas stations and pharmacies) where the competitions is damaged and finally are presented the measures on improvement based on the EU practices. Like other economies in transition, the economy in Kosovo the activity for protection of competition is faced with many challenges. Moreover, these challenges result from the fact that Kosovo was the last country in South Eastern ...


The Unfree Space Of Play: Emergence And Control In The Videogame And The Platform, Logan Brown 2019 Indiana University, Bloomington

The Unfree Space Of Play: Emergence And Control In The Videogame And The Platform, Logan Brown

Markets, Globalization & Development Review

This article attempts to understand the economic and informatic ramifications of the convergence between increasingly connective games and massive online platforms by considering recent trends in both that center around designing for emergence. Scholarship on emergence as a property of games overwhelmingly treats emergent design as a liberating force that privileges player agency in a virtual space. Yet, as games fuse with surrounding platform ecosystems like Steam, Facebook, and Google, those emergent behaviors are subject to vast systems of inscription that analyze user behavior in order to reshape the free space of emergence and extract greater social and financial capital ...


Influence Of The Event Rate On Discrimination Abilities Of Bankruptcy Prediction Models, Lili Zhang, Jennifer Priestley, Xuelei Ni 2019 Kennesaw State University

Influence Of The Event Rate On Discrimination Abilities Of Bankruptcy Prediction Models, Lili Zhang, Jennifer Priestley, Xuelei Ni

Jennifer L. Priestley

In bankruptcy prediction, the proportion of events is very low, which is often oversampled to eliminate this bias. In this paper, we study the influence of the event rate on discrimination abilities of bankruptcy prediction models. First the statistical association and significance of public records and firmographics indicators with the bankruptcy were explored. Then the event rate was oversampled from 0.12% to 10%, 20%, 30%, 40%, and 50%, respectively. Seven models were developed, including Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and Neural Network. Under different event rates, models were comprehensively evaluated and ...


Comparison Of Bankruptcy Prediction Models With Public Records And Firmographics, Lili Zhang, Jennifer Priestley, Xuelei Ni 2019 Kennesaw State University

Comparison Of Bankruptcy Prediction Models With Public Records And Firmographics, Lili Zhang, Jennifer Priestley, Xuelei Ni

Jennifer L. Priestley

Many business operations and strategies rely on bankruptcy prediction. In this paper, we aim to study the impacts of public records and firmographics and predict the bankruptcy in a 12-month-ahead period with using different classification models and adding values to traditionally used financial ratios. Univariate analysis shows the statistical association and significance of public records and firmographics indicators with the bankruptcy. Further, seven statistical models and machine learning methods were developed, including Logistic Regression, Decision Tree, Random Forest, Gradient Boosting, Support Vector Machine, Bayesian Network, and Neural Network. The performance of models were evaluated and compared based on classification accuracy ...


A Comparison Of Machine Learning Algorithms For Prediction Of Past Due Service In Commercial Credit, Liyuan Liu M.A, M.S., Jennifer Lewis Priestley Ph.D. 2019 Analytics and Data Science

A Comparison Of Machine Learning Algorithms For Prediction Of Past Due Service In Commercial Credit, Liyuan Liu M.A, M.S., Jennifer Lewis Priestley Ph.D.

Jennifer L. Priestley

Credit risk modeling has carried a variety of research interest in previous literature, and recent studies have shown that machine learning methods achieved better performance than conventional statistical ones. This study applies decision tree which is a robust advanced credit risk model to predict the commercial non-financial past-due problem with better critical power and accuracy. In addition, we examine the performance with logistic regression analysis, decision trees, and neural networks. The experimenting results confirm that decision trees improve upon other methods. Also, we find some interesting factors that impact the commercials’ non-financial past-due payment.


Saving Lives With Effective Data Visualization: Evaluating The Effectiveness Of Indiana’S Driver Education Curriculum, Aditi Vatse, Amratansh Sharma, Matthew A. Lanham Prof. 2019 Krannert School of Management

Saving Lives With Effective Data Visualization: Evaluating The Effectiveness Of Indiana’S Driver Education Curriculum, Aditi Vatse, Amratansh Sharma, Matthew A. Lanham Prof.

Engagement & Service-Learning Summit: Connecting Through Listening & Scholarship

No abstract provided.


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