Business Commons^™

Making Vending Machines Smarter With The Use Of Machine Learning And Artificial Intelligence: Set-Up And Architecture, Dashmir Istrefi, Eftim Zdravevski

UBT International Conference

Machine Learning and Robust Optimization techniques can significantly improve logistics operations and improve stock quantity and maintenance intervals. Machine Learning will be used to forecast item demands for each of the vending machines, taking into account past demands and calendar effects. By performing such predictions which are forwarded to a Robust Optimization model, and whose outputs will be the cash transport that each vending machine should require. These transports guarantee that demand is fulfilled up to the desired confidence level, preventing downtime of vending machines due to unplanned maintenance and out-of-stock situations, while also satisfying additional constraints arising in this …

Towards High Performance Stock Market Prediction Methods, Warren M. Landis, Sangwhan Cha

Other Student Works

Stock markets of today, and will continue to in the future, rely on the metrics of timeliness and efficiency to reach optimal profits. A way stock investors have continued to strive for the best of these two factors of the business is through the use of predictive machine learning systems to help aid in their decision making. However, among the many systems currently in use, it could be said that the myriad of data that they are based on may not be sufficient. In an effort to devise an ensemble learning predictive system that will utilize an array of big …

Creating A Culture Of Data-Driven Decision-Making, Kevin Bryan Rogers

Doctoral Dissertations and Projects

Researchers have consistently shown that a supportive culture is one of the most crucial success factors in the implementation of any big data solution. Creating a culture that supports data-driven decision-making is a difficult but ultimately required step in transforming an organization into one that can readily and successfully adopt business intelligence technologies. The purpose of this qualitative case study was to understand the ways in which organizations can foster a culture of smarter decision-making and accountability so that businesses can improve operational metrics and ultimately profitability. Participants identified three major themes that drive the adoption of a data-driven culture. …

Black-Scholes And Neural Networks, Gabriel Adams

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Neural networks have been proven to be universal approximators. We use neural networks to investigate the relationship between the quality of input data and the quality of outputted predictions from a neural network. We show that neural networks perform better on option pricing data with quality data and perform worse with lower quality data.

Hopeless Ugly Food? Estimating Heterogeneous Treatment Effects Of Marketing Strategies On Consumer Attitude And Wtp Via Machine Learning Approaches, Ran Li

LSU Master's Theses

Around one-third of food produced for human consumption is wasted every year, partially caused by consumer's unwillingness to purchase ugly food. We explore opportunities to favorably support consumer's considerations for ugly food by analyzing survey responses from 1099 U.S. adults. We find that without any marketing strategies applied, a great discount has to be provided to sell ugly food. By using appropriate marketing strategies, consumer's attitudes and willingness to pay for ugly food can be changed positively. However, the effects of ugly food marketing attributes are heterogeneous among consumers with different attitudes towards ugly food. Consumers with negative attitudes towards …

Analysis On Suicidal Ideation Among Adolescents (12-17 Years) In The Usa, Himani Raturi

Electronic Theses, Projects, and Dissertations

Suicide is one of the leading health concerns in United States among adolescents and the presence of suicidal ideation (SI) is quite high, with ~20-30% of adolescents reporting it at some point. Though we have seen growth and development in the prevention of suicide, there is limited research on the ability to identify the adolescents which might be at risk for SI. The objective behind the project is to identify adolescents with SI using machine learning.

The project shows statistics from different articles on adolescents in the U.S. For this study, adolescent data was taken from NSDUH 2018. Moreover, detailed …

A Predictive Analytics Model For Differentiating Between Transient Ischemic Attacks (Tia) And Its Mimics, Alia C. Stanciu, Mihai Banciu, Alireza Sadighi, Kyle A. Marshall, Neil Holland, Vida Abedi, Ramin Zand

Faculty Journal Articles

Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors because of the subjective nature of findings and the lack of clinical and imaging biomarkers. The goal of this study was to design and evaluate a novel multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, to predict the likelihood of TIA, TIA mimics, and minor stroke.

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …

Disruptive Innovation Within The Legal Services Ecosystem, Donald G. Billings, Douglas G. Campbell

International Journal of Applied Management and Technology

Many law firms have done little to address the opportunities and threats presented by potentially disruptive technology (DT), such as artificial intelligence (AI) and machine learning (ML). The purpose of this multiple case study was to explore strategies that some law firm leaders use to address the potentially detrimental influences of DT on their organizations. The systems approach to management was employed as the conceptual framework. Data were collected from 6 participants at 2 international law firms with offices in California, using semi-structured interviews and organizational artifacts. Data were analyzed using inductive and deductive coding and thematic analysis, resulting in …