Operations Research, Systems Engineering and Industrial Engineering Commons^™

Enterprise Systems: Installing And Configuring Erpnext On Macos, Yazan Abbasi

Senior Honors Theses

Enterprise Resource Planning (ERP) systems integrate business processes across organizations onto unified digital platforms through data and workflow consolidation. However, high licensing costs of proprietary ERP solutions like SAP and Oracle limit adoption for small and medium enterprises. This led to the emergence of open-source ERP alternatives like ERPNext which provide sophisticated capabilities at much lower total cost of ownership. However, ERPNext faces documentation gaps that hamper onboarding, customization, and widespread adoption. Accelerating ERPNext implementation by developing a comprehensive installation and configuration guide tailored for developers using Mac environments will be examined furthermore.

The background on ERP systems explores critical …

Sports Analytics: Putting The Fun Back Into Analytics, Walt Degrange

Operations Management Presentations

With the recent success of sports teams heavily using analytics (Dodgers, Patriots, Capitals, Warriors, Leicester City F.C.), does this mean that analytics has gained a foothold in the sports world? I use a k-means clustering model to determine if performance since 2015 in the four major US sports can support this question. And is there a career path that a high school student can use to become a sports analytics professional? This presentation attempts to answer that question by exploring all the areas of the application of analytics in sports. The final point the brief makes is that by using …

Characterizing Statin Use Among Prediabetic Patients With Predictive Analytics, Alexandra Gentile

Industrial Engineering Undergraduate Honors Theses

Diabetes is one of the leading causes of death in the United States and can cause severe impairments to those diagnosed. Prediabetes is a state when a patient has higher fasting plasma glucose levels than a non-diabetic person but is not quite high enough to be considered diabetes. Both diabetic and prediabetic patients are at higher risk for cardiovascular diseases (CVD), which is the leading cause of death in the United States. The primary form for prevention and treatment of CVD is through statin therapy. Statins are a class of medications used to treat and prevent CVD by limiting cholesterol …

Decision Science For Community Development And Social Change, Michael P. Johnson Jr.

Michael P. Johnson

Understanding The Impact Of Virtual-Mirroring Based Learning On Collaboration In A Data And Analytics Function: A Resilience Perspective, Nabil Raad

Wayne State University Dissertations

Large multinational organizations are struggling to adapt and innovate in the face of increasing turbulence, uncertainty, and complexity. The lack of adaptive capacity is one of the major risks facing such organizations as the rapid change in technology, urbanization, socio-economic trends, and regulations continues to accelerate and outpace their ability to adapt. This is a resilience problem that organizations are addressing by investing in Data and Analytics to improve their innovation and competitive capabilities. However, Data and Analytics projects are more likely to fail than to succeed. Competing on data and analytics is not only a technical challenge but also …

Diversity And Or/Ms/Analytics: Deepening The Impact Of Our Research, Broadening Access To The Profession, Michael P. Johnson Jr.

Michael P. Johnson

Socio-Economic Planning Sciences Special Issue: Indices For The Betterment Of The Public, Vincent Charles, Ali Emrouznejad, Michael P. Johnson Jr.

Michael P. Johnson

Emerging Trends And New Frontiers In Community Operational Research, Michael P. Johnson Jr., Gerald Midgley, George Chichirau

Michael P. Johnson

A Motion Capture System Framework For The Study Of Human Manufacturing Repetitive Motions, Francis Mendez, David Wierschem, Jesus Jimenez

15th IMHRC Proceedings (Savannah, Georgia. USA – 2018)

Our research proposes a framework to obtain and analyze real time data concerning the dynamic and natural motion of individuals in manufacturing-like processes that involve human labor. The framework that we propose consists of five main components: a tracking system, a system of sensors, a processor that collects time series data, data processing and discovery module, and an alert or reporting component. Using motion capture cameras, data is collected on a variety of human subjects performing simulated labor-intensive manufacturing operations. This data is analyzed for identification of actual and optimal activity motions. This project has significant potential impact for contribution …

Improving Decision-Making Skills Of Nonprofit Professionals, Michael P. Johnson Jr., George Chichirau, Jason Wright

Michael P. Johnson

Community-Engaged Operations Research: Trends, New Frontiers And Opportunities, Michael P. Johnson Jr.

Michael P. Johnson

An Agenda For Diversity And Inclusion-Related Research Within Or/Ms/Analytics, Michael P. Johnson Jr., George Chichirau

Michael P. Johnson

The Impact Of Analytics Utilization On Team Performance: Comparisons Within And Across The U.S. Professional Sports Leagues, Lee A. Freeman

Journal of International Technology and Information Management

Business analytics, defined as the use of data to make better, more relevant, evidence-based business decisions, has received a great deal of attention in practitioner circles. Organizations have adopted business analytics in an effort to improve revenue, product placement, and customer satisfaction. Professional sports teams are no different. While analytics has been used for over 30 years, the use of analytics by professional sports teams is a relatively new concept. However, it is unclear whether the teams that have adopted analytics are seeing any results. If not, then perhaps analytics is not the right solution. Analyses across the four, major …

Renewable Energy Investment Planning And Policy Design, Alireza Ghalebani

USF Tampa Graduate Theses and Dissertations

In this dissertation, we leverage predictive and prescriptive analytics to develop decision support systems to promote the use of renewable energy in society. Since electricity from renewable energy sources is still relatively expensive, there are variety of financial incentive programs available in different regions. Our research focuses on financial incentive programs and tackles two main problem: 1) how to optimally design and control hybrid renewable energy systems for residential and commercial buildings given the capacity based and performance based incentives, and 2) how to develop a model-based system for policy makers for designing optimal financial incentive programs to promote investment …

Predictive Analytics For Outpatient Appointments, Nang Laik Ma, Khataniar Seemanta, Dan Wu, Serene Seng Ying Ng

Research Collection School Of Computing and Information Systems

Healthcare is a very important industry where analytics has been applied successfully to generate insights about patients, identify bottleneck and to improve the business efficiency. In this paper, we aim to look at the patient appointment process as the hospital is experiencing high volume of ?no shows. ?No shows have a high impact on longer appointment lead time for patients, poor patient satisfaction and loss of revenue for hospital. We use data analytics to identify pattern of ?no shows, develop a statistical model to predict the probability of ?no shows and finally operationalizing the model to embed the analytics solution …

A Stand-Alone Methodology For Data Exploration In Support Of Data Mining And Analytics, Michael Gage

Master's Theses

With the emergence of Big Data, data high in volume, variety, and velocity, new analysis techniques need to be developed to effectively use the data that is being collected. Knowledge discovery from databases is a larger methodology encompassing a process for gathering knowledge from that data. Analytics pair the knowledge with decision making to improve overall outcomes. Organizations have conclusive evidence that analytics provide competitive advantages and improve overall performance. This paper proposes a stand-alone methodology for data exploration. Data exploration is one part of the data mining process, used in knowledge discovery from databases and analytics. The goal of …