Business Commons^™

Leveraging The Granularity Of Healthcare Data: Essays On Operating Room Scheduling For Productivity And Nurse Retention, Jaeyoung Kim

All Dissertations

The primary objective of this dissertation is to provide insights for healthcare practitioners to leverage the granularity of their healthcare data. In particular, leveraging the granularity of healthcare data using data analytics helps practitioners to manage operating room scheduling for productivity and nurse retention. This dissertation addresses the practical challenges of operating room (OR) scheduling by combining the existing insights from the prior literature through various tools in data analytics. In doing so, this dissertation consists of three chapters that operationally quantify the operational characteristics of the operating room and surgical team scheduling to improve operating room outcomes, including OR …

Discovering Data-Driven Solutions: A Practical Guide For Small Businesses Implementing Data Analytics, Katherine Richoux

Information Systems Undergraduate Honors Theses

In today’s highly competitive business environment, small businesses are under growing pressure to fight for market share. To do this, a competitive advantage must be established to outperform other business competitors both big and small. One way that small businesses can create a competitive advantage is by utilizing their data and applying basic data analytics. Data analytics is the process of collecting and analyzing large sets of raw data using statistical tests to identify patterns and insights to make conclusions that inform business decisions. The use of data analytics is not exclusive to large corporations and can be greatly beneficial …

Regulating By New Technology: The Impacts Of The Sec Data Analytics On The Sec Investigations, Tian Deng

Dissertations and Theses Collection (Open Access)

Despite the Securities and Exchange Commission’s (SEC) growing emphasis on data analytics in recent years, there is scant research about whether the investment in data analytics accomplishes its objective of enhancing enforcement efficiency. This study examines the effects of the SEC regional offices’ use of data analytics on their investigation outcomes. The utilization of data analytics reduces information processing costs, thereby streamlining the enforcement process as a whole. I find that the SEC’s use of data analytics is associated with a 12% increase in the SEC’s investigation success rate. Such an improvement is greater for firms whose disclosure are more …

Data Analytics In Hotel And Integrated Resort Brands: An Evaluation Of Past Literature And Proposed Research For The Future, Luke Andrew Walocko

UNLV Theses, Dissertations, Professional Papers, and Capstones

Data analytics in hotel and integrated resort brands is a growing strategy implemented to support business decisions designed to generate revenue or save costs. This study utilizes a literature review of data analytics related publications to provide recommendations on future research topics to improve the quality of literature related to data analytics in hotel and integrated resort brands. The study is not limited to hospitality specific research and uses research from all industries to identify gaps in publications for hospitality scholars to explore. Three proposed research questions for future exploration were composed based on the comparison of literature written for …

What Are The Factors That Influence The Adoption Of Data Analytics And Artificial Intelligence In Auditing?, Grace Tsao

Honors Undergraduate Theses

Although past research finds that auditors support data analytics and artificial intelligence to enhance audit quality in their daily work, in reality, only a small number of audit firms, who innovated and invested in the two sophisticated technologies, utilize it in their auditing process. This paper analyzes three factors, including three individual theories, that may influence the adoption of data analytics and artificial intelligence in auditing: regulation (Institutional theory: explaining the catch-22 between the auditors and policymakers), knowledge barrier (Technology acceptance model's theory: explore the concept of ease of use), and people (algorithm aversion: a phenomenon that auditors believe in …

Changing The Focus: Worker-Centric Optimization In Human-In-The-Loop Computations, Mohammadreza Esfandiari

Dissertations

A myriad of emerging applications from simple to complex ones involve human cognizance in the computation loop. Using the wisdom of human workers, researchers have solved a variety of problems, termed as “micro-tasks” such as, captcha recognition, sentiment analysis, image categorization, query processing, as well as “complex tasks” that are often collaborative, such as, classifying craters on planetary surfaces, discovering new galaxies (Galaxyzoo), performing text translation. The current view of “humans-in-the-loop” tends to see humans as machines, robots, or low-level agents used or exploited in the service of broader computation goals. This dissertation is developed to shift the focus back …

Effective Data Analytics And Security Strategies In Internal Audit Organizations, Desiree Auchey

Walden Dissertations and Doctoral Studies

The digitization of the corporate and regulatory environment presents an opportunity for internal audit organizations to change their audit techniques and increase their value to corporations. Audit functions have not kept pace with these advancements, as evidenced by the massive frauds in recent years, and current audit methodology does not robustly incorporate analytics and security of data. Grounded in agency theory, the purpose of this qualitative case study was to explore successful strategies business leaders use to implement data analytics and security for internal auditing and fraudulent activity. The participants comprised 3 audit leaders in Pennsylvania, who effectively used data …

Price Prediction In The Sharing Economy: A Case Study With Airbnb Data, Brandon Mcneil

Honors Theses and Capstones

Many sharing-economy companies like Airbnb have their profits rely on the dynamic pricing market that they participate in. Airbnb hosts can set their own price based on what they deem the market will buy. Recent research argues that almost all hosts fail to maximize their potential profit due to poorly pricing their listing (Gibbs et al., 2018). While previous studies have looked at how specific variables effect the price of an Airbnb listing, this study aims to be the first to group variables separately into two distinct categories based on the host’s ability to control that variable. Looking at two …

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.

Data Analytics In An Audit: Examining Fraud Risk And Audit Quality, Sondra Smith

Doctor of Business Administration Dissertations

ABSTRACT

DATA ANALYTICS IN AN AUDIT: EXAMINING FRAUD RISK AND

AUDIT QUALITY

by

Sondra Smith

This study is comprised of two papers which examine, through interviews and an experiment, the current practices of data analytics of CPA firms, whether and how fraud risk impacts the usage of data analytics in an audit, and the effect data analytics has on the efficiency and effectiveness of an audit. The implementation of data analytics in an audit is relatively new, and there is not a good understanding of how it is currently being used in practice. Although historically the auditing profession has been …

Audubon Data Project Final Report, Askhat Beygenov, Valinur Kutlambetov, Shrikant Patel, Phoebe Roberts, Ulfat Sayyed, Shriram Sivaraman

School of Professional Studies

The Audubon Data Project was initiated as a Clark University Capstone project. The project’s client, Mass Audubon’s Shaping the Future of Your Community program, had identified a need to improve their data management methods and make better use of their data. The Capstone team, composed of Clark University graduate students, met with the client regularly to review the current state of the data and potential improvements to be made. The process began with a data review. During the review we worked with the client to explicitly define the purposes and requirements of the data, the current process for updating and …

Understanding The Implication Of Blockchain Technology On The Audit Profession, Brittany Jackson

Honors Undergraduate Theses

The purpose of this research is to identify the implications of blockchain technology on the auditing profession. By conducting interviews with current professionals in the auditing profession, as well as those in academic with a background in auditing, primary data was collected to aggregate what potential effects will be on the auditing profession in the next five years and the next decade. The data includes assumptions of how the accounting major itself, the auditing planning phase, assumptions of risk, and audit completions will change with the developing technology. The goal of this research is a better understanding of how auditing …

An Application Of Data Analytics To Outcomes Of Missouri Motor Vehicle Crashes, Jill Marie Bernard

Dissertations

Motor vehicle crashes are a leading cause of death in the United States, cost Americans $277 billion annually, and generate serious psychological burdens. As a result, extensive vehicle safety research focusing on the explanatory factors of crash severity is undertaken using a wide array of methodological techniques including traditional statistical models and contemporary data mining approaches. This study advances the methodological frontier of crash severity research by completing an empirical investigation that compares the performance of popular, longstanding techniques of multinomial logit and ordinal probit models with more recent methods of decision tree and artificial neural network models. To further …