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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 ...


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 ...


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 ...


Book Review: Seeds Of Greatness By Denis Waitley, Jennifer Maynard 2019 Brigham Young University

Book Review: Seeds Of Greatness By Denis Waitley, Jennifer Maynard

Marriott Student Review

Book review of Seeds of Greatness by Denis Waitley, personal anecdotes and summaries of research on the secrets to success in life and in the business world.


The Futurist, Ryan Stenquist 2019 Brigham Young University Marriott School

The Futurist, Ryan Stenquist

Marriott Student Review

Ubiquitous self-driving cars, robot workers, and massive political shifts may seem far away and irrelevant to our day to day lifestyles. However, Mr. Schenker proves that these changes are fast-approaching and come as timely responses to the problems and opportunities of today.


An Arm And A Leg: Medtech Perspectives On Human-Centered Design, Evan D. Poff 2019 Brigham Young University

An Arm And A Leg: Medtech Perspectives On Human-Centered Design, Evan D. Poff

Marriott Student Review

The art of human-centered design accounts for both technological and emotional specifications in order to deliver meaningful products that meet the specific needs of the individual customer. Every business professional can deepen his or her understanding of human-centered design – regardless of our industry of choice – by looking to perspectives that the business of medical technology offers. To that end, this article draws upon interviews with three figures in this remarkable field, distilling their insights on how to cultivate businesses that produce human-centered solutions.


Can Banks Placate Knowledgeable Depositors By Offering Higher Interest Rates During A Banking Crisis?, Glenn Boyle, Roger D. Stover, Amrit Tiwana, Oleksandr Zhylyevskyy 2019 University of Canterbury

Can Banks Placate Knowledgeable Depositors By Offering Higher Interest Rates During A Banking Crisis?, Glenn Boyle, Roger D. Stover, Amrit Tiwana, Oleksandr Zhylyevskyy

Oleksandr Zhylyevskyy

Using a conjoint analysis of 417 finance professionals from six countries, we find no evidence that higher interest rates cause knowledgeable depositors to moderate their withdrawals during a banking crisis. In fact, intended withdrawals are positively correlated with expected interest rate changes. After accounting for endogeneity, this relationship disappears, consistent with the attractiveness of higher returns being offset by increased doubts about bank solvency. The withdrawal decisions of finance professionals are also independent of their personal characteristics, but they appear to place considerable store on deposit insurance generosity and the presence of a formal insurance fund.


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.


Dos And Don'ts Of Data Science, Ryan Burton 2019 Capital Services

Dos And Don'ts Of Data Science, Ryan Burton

SDSU Data Science Symposium

In an ideal world, we avoid all mistakes in our work. Some mistakes are preventable and others are unavoidable. A few common mistakes in data science that can be minimized include assuming correlation implies causation, modeling with an unrepresentative sample, and focusing on the mean without understanding the distribution. This talk will give an overview of some of the simple yet common mistakes in data science and guidance on how to avoid them.


General Mental Ability And Goal Type As Antecedents Of Recurrent Adaptive Task Performance, Michael D. Howe 2019 Iowa State University

General Mental Ability And Goal Type As Antecedents Of Recurrent Adaptive Task Performance, Michael D. Howe

Management Publications

Even though considerable work has demonstrated a robust positive relationship between general mental ability (GMA) and task performance, recent work indicates that the expected relationship may not hold in the context of adaptive performance. By integrating the concept of choking, or performing worse than expected, with goal theory, the present work advances a theoretical framework aimed at furthering our understanding of how and when GMA is most likely to meaningfully impact performance. Drawing on this perspective, we propose that the relationship between GMA and adaptive performance is uniquely dependent on the type of goal individuals are striving to achieve. Additionally ...


Inside The Black Box Of Dictionary Building For Text Analytics: A Design Science Approach, Qi Deng, Michael J. Hine, Shaobo Ji, Sujit Sur 2019 Carleton University

Inside The Black Box Of Dictionary Building For Text Analytics: A Design Science Approach, Qi Deng, Michael J. Hine, Shaobo Ji, Sujit Sur

Journal of International Technology and Information Management

The purpose of this paper is to develop and demonstrate a dictionary building process model for text analytics projects following the design science methodology. Using inductive consensus-building, we examined prior research to develop an initial process model. The model is subsequently demonstrated and validated by using data to develop an environmental sustainability dictionary for the IT industry. To our knowledge, this is an initial attempt to provide a normalized dictionary building process for text analytics projects. The resulting process model can provide a road map for researchers who want to use automated approaches to text analysis but are currently prevented ...


A Systematic Review Of Process Modelling Methods And Its Application For Personalised Adaptive Learning Systems, Kingsley Okoye 2019 University of East London

A Systematic Review Of Process Modelling Methods And Its Application For Personalised Adaptive Learning Systems, Kingsley Okoye

Journal of International Technology and Information Management

This systematic review work investigates current literature and methods that are related to the application of process mining and modelling in real-time particularly as it concerns personalisation of learning systems, or yet still, e-content development. The work compares available studies based on the domain area of study, the scope of the study, methods used, and the scientific contribution of the papers and results. Consequently, the findings of the identified papers were systematically evaluated in order to point out potential confounding variables or flaws that might have been overlooked or missing in the current literature. In turn, a critical structured analysis ...


Social Justice, Numeracy, And Teaching Statistics At A Community College, Edward Volchok 2019 Queensborough Community College/CUNY

Social Justice, Numeracy, And Teaching Statistics At A Community College, Edward Volchok

Numeracy

The author of this article reflects on the issues of justice, democracy, and numeracy. As one who has taught statistics in a community college for over 12 years, spent 28 years as a Marketing Consultant, and holds a PhD in political science, the author’s thesis is that while an advanced, democratic society can only be just with a numerate citizenry, fostering numeracy is not easy. In this article the author describes the daunting tasks of trying to define what justice is and reviews activities from his statistics class that help students develop their numeracy.


Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. McCollum, Mary-Margaret Chantre, Gregory Campbell 2019 Capitol Technology University

Exploring Critical Success Factors For Data Integration And Decision-Making In Law Enforcement, Marquay Edmondson, Walter R. Mccollum, Mary-Margaret Chantre, Gregory Campbell

International Journal of Applied Management and Technology

Agencies from various disciplines supporting law enforcement functions and processes have integrated, shared, and communicated data through ad hoc methods to address crime, terrorism, and many other threats in the United States. Data integration in law enforcement plays a critical role in the technical, business, and intelligence processes created by users to combine data from various sources and domains to transform them into valuable information. The purpose of this qualitative phenomenological study was to explore the current conditions of data integration frameworks through user and system interactions among law enforcement organizational processes. Further exploration of critical success factors used to ...


Digital Forensic Tools & Cloud-Based Machine Learning For Analyzing Crime Data, Majeed Kayode Raji 2019 Georgia Southern University

Digital Forensic Tools & Cloud-Based Machine Learning For Analyzing Crime Data, Majeed Kayode Raji

Electronic Theses and Dissertations

Digital forensics is a branch of forensic science in which we can recreate past events using forensic tools for legal measure. Also, the increase in the availability of mobile devices has led to their use in criminal activities. Moreover, the rate at which data is being generated has been on the increase which has led to big data problems. With cloud computing, data can now be stored, processed and analyzed as they are generated. This thesis documents consists of three studies related to data analysis. The first study involves analyzing data from an android smartphone while making a comparison between ...


Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali 2018 The University of Western Ontario

Secured Data Masking Framework And Technique For Preserving Privacy In A Business Intelligence Analytics Platform, Osama Ali

Electronic Thesis and Dissertation Repository

The main concept behind business intelligence (BI) is how to use integrated data across different business systems within an enterprise to make strategic decisions. It is difficult to map internal and external BI’s users to subsets of the enterprise’s data warehouse (DW), resulting that protecting the privacy of this data while maintaining its utility is a challenging task. Today, such DW systems constitute one of the most serious privacy breach threats that an enterprise might face when many internal users of different security levels have access to BI components. This thesis proposes a data masking framework (iMaskU: Identify ...


Machine Learning The Harness Track: A Temporal Investigation Of Race History On Prediction, Robert P. Schumaker 2018 University of Texas at Tyler

Machine Learning The Harness Track: A Temporal Investigation Of Race History On Prediction, Robert P. Schumaker

Journal of International Technology and Information Management

Machine learning techniques have shown their usefulness in accurately predicting greyhound races. Many of the studies within this domain focus on two things; win-only wagers and using a very particular combination of race history. Our study investigates altering these properties and studying the results. In particular we found a race history combination that optimizes our S&C Racing system’s predictions on seven different wager types. From this, S&C Racing posted an impressive 50.44% accuracy in selecting winning wagers with a payout of $609.34 and a betting return of $10.06 per dollar wagered.


Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He 2018 Fairfield University

Crude Oil Prices Forecasting: Time Series Vs. Svr Models, Xin James He

Journal of International Technology and Information Management

This research explores the weekly crude oil price data from U.S. Energy Information Administration over the time period 2009 - 2017 to test the forecasting accuracy by comparing time series models such as simple exponential smoothing (SES), moving average (MA), and autoregressive integrated moving average (ARIMA) against machine learning support vector regression (SVR) models. The main purpose of this research is to determine which model provides the best forecasting results for crude oil prices in light of the importance of crude oil price forecasting and its implications to the economy. While SVR is often considered the best forecasting model in ...


Using Sas™ Software To Enhance Pedagogy For Text Mining And Sentiment Analysis Using Social Media (Twitter™) Data, Ramesh Subramanian, Danielle Cote 2018 Quinnipiac University

Using Sas™ Software To Enhance Pedagogy For Text Mining And Sentiment Analysis Using Social Media (Twitter™) Data, Ramesh Subramanian, Danielle Cote

Journal of International Technology and Information Management

This pedagogical paper describes how a graduate course in Text Mining was developed and taught in a fully online format at Quinnipiac University. The software used was SAS™ Enterprise Miner. This paper discusses the design, software used and the methodology followed in the course. A critical component of the course required the students to delve deep into social media data by completing a detailed project on analyzing sentiment analysis using large files of social media data. A sample report of this project, which was a key deliverable for the course, is described at length in this paper.


Table Of Contents Jitim Vol 27 Issue 3, 2018, 2018 California State University, San Bernardino

Table Of Contents Jitim Vol 27 Issue 3, 2018

Journal of International Technology and Information Management

Table of Contents


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