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2022

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Full-Text Articles in Databases and Information Systems

An Empirical Study On The Impact Of Deep Parameters On Mobile App Energy Usage, Qiang Xu, James C. Davis, Y Charlie Hu, Abhilash Jindal Jan 2022

An Empirical Study On The Impact Of Deep Parameters On Mobile App Energy Usage, Qiang Xu, James C. Davis, Y Charlie Hu, Abhilash Jindal

Department of Electrical and Computer Engineering Faculty Publications

Improving software performance through configuration parameter tuning is a common activity during software maintenance. Beyond traditional performance metrics like latency, mobile app developers are interested in reducing app energy usage. Some mobile apps have centralized locations for parameter tuning, similar to databases and operating systems, but it is common for mobile apps to have hundreds of parameters scattered around the source code. The correlation between these "deep" parameters and app energy usage is unclear. Researchers have studied the energy effects of deep parameters in specific modules, but we lack a systematic understanding of the energy impact of mobile deep parameters. …

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Data Processing In A Database Management System Using Parallel Processing, Stephen Shears Jan 2022

Data Processing In A Database Management System Using Parallel Processing, Stephen Shears

Williams Honors College, Honors Research Projects

This research project will be focused on parallel processing as it is used with database management systems to process data. Specifically, the goal is to see if creating a database management system with parallel processing at the forefront of its data processing can offer enough of an efficiency increase to warrant using it against a sequential database management system and is it possible to make that system just as reliable as those databases without parallel processing. A parallel processed database will be created with a focus on monitoring its data reliability and consistency. It will then be compared to two …

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Resume Parser And Job Search, Stephan Gunawardana Jan 2022

Resume Parser And Job Search, Stephan Gunawardana

Williams Honors College, Honors Research Projects

The basic goal of this project was to create a four-tier web application which would allow users to upload their personal resumes to the website, and it ultimately would parse the resume and look for keywords. Then using these keywords, it would use a job API to look for these values and ultimately display job information to the user based on their skills. While applications exist which would look for jobs based on skills, it was mostly manually inputted skills. However, with my application you can simply upload your resume to the website, and it will basically take care of …

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Non-Parametric Stochastic Autoencoder Model For Anomaly Detection, Raphael B. Alampay, Patricia Angela R. Abu Jan 2022

Non-Parametric Stochastic Autoencoder Model For Anomaly Detection, Raphael B. Alampay, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Anomaly detection is a widely studied field in computer science with applications ranging from intrusion detection, fraud detection, medical diagnosis and quality assurance in manufacturing. The underlying premise is that an anomaly is an observation that does not conform to what is considered to be normal. This study addresses two major problems in the field. First, anomalies are defined in a local context, that is, being able to give quantitative measures as to how anomalies are categorized within its own problem domain and cannot be generalized to other domains. Commonly, anomalies are measured according to statistical probabilities relative to the …

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Whole File Chunk Based Deduplication Using Reinforcement Learning, Xincheng Yuan Jan 2022

Whole File Chunk Based Deduplication Using Reinforcement Learning, Xincheng Yuan

Master's Projects

Deduplication is the process of removing replicated data content from storage facilities like online databases, cloud datastore, local file systems, etc., which is commonly performed as part of data preprocessing to eliminate redundant data that requires unnecessary storage spaces and computing power. Deduplication is even more specifically essential for file backup systems since duplicated files will presumably consume more storage space, especially with a short backup period like daily [8]. A common technique in this field involves splitting files into chunks whose hashes can be compared using data structures or techniques like clustering. In this project we explore the possibility …

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Improving User Experiences For Wiki Systems, Parth Patel Jan 2022

Improving User Experiences For Wiki Systems, Parth Patel

Master's Projects

Wiki systems are web applications that allow users to collaboratively manage the content. Such systems enable users to read and write information in the form of web pages and share media items like videos, audios, books etc. Yioop is an open-source web portal with features of a search engine, a wiki system and discussion groups. In this project I have enhanced Yioop’s features for improving the user experiences. The preliminary work introduced new features like emoji picker tool for direct messaging system, unit testing framework for automating the UI testing of Yioop and redeeming advertisement credits back into real money. …

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Exploring Implementation Strategies Of Iot Technology In Organizations: Technology, Organization, And Environment, Khanhhung Hoang Pham Jan 2022

Exploring Implementation Strategies Of Iot Technology In Organizations: Technology, Organization, And Environment, Khanhhung Hoang Pham

Walden Dissertations and Doctoral Studies

AbstractAfter organizations successfully adopt the internet of things (IoT) technology, many corporate information technology (IT) leaders face challenges during the implementation phase. Corporate IT leaders' potential failures in implementing IoT devices may impede organizations from integrating IoT solutions and promoting business benefits. Grounded in technology-organization-environment (TOE) theory, the purpose of this qualitative, pragmatic inquiry study was to explore strategies that corporate IT leaders use to implement IoT technology in their organizations. The participants were six corporate healthcare IT leaders who successfully used implementation strategies for implementing IoT solutions for their organizations. Data were collected using semistructured interviews and industry security …

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Deep Learning For Video-Grounded Dialogue Systems, Hung Le Jan 2022

Deep Learning For Video-Grounded Dialogue Systems, Hung Le

Dissertations and Theses Collection (Open Access)

In recent years, we have witnessed significant progress in building systems with artificial intelligence. However, despite advancements in machine learning and deep learning, we are still far from achieving autonomous agents that can perceive multi-dimensional information from the surrounding world and converse with humans in natural language. Towards this goal, this thesis is dedicated to building intelligent systems in the task of video-grounded dialogues. Specifically, in a video-grounded dialogue, a system is required to hold a multi-turn conversation with humans about the content of a video. Given an input video, a dialogue history, and a question about the video, the …

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Examination Of Strategies To Implementing Chip-And-Personal Identification Number Credit Card Authentication Infrastructures, Neville Arthur Gallimore Jan 2022

Examination Of Strategies To Implementing Chip-And-Personal Identification Number Credit Card Authentication Infrastructures, Neville Arthur Gallimore

Walden Dissertations and Doctoral Studies

Chip-and-Personal Identification Number (PIN) technology is seen as a game changer in many e-commerce industries and a transformational technology in the 21st century. However, security concerns have made chip-and-PIN adoption relatively slow. Massive unauthorized card payment transactions in the United States (U.S.) cost victims an estimate totaling billions of dollars. Information Technology (IT) managers are concerned with credit card fraud's financial loss and liability cost. Grounded in Rogers’s diffusion of innovation theory, the purpose of this qualitative pragmatic study was to explore strategies used by IT managers to transition their e-commerce organizations to chip-and-PIN credit card authentication infrastructures. The participants …

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Modernization Of Legacy Information Technology Systems, Rabie Khabouze Jan 2022

Modernization Of Legacy Information Technology Systems, Rabie Khabouze

Walden Dissertations and Doctoral Studies

Large enterprises spend a large portion of their Information Technology (IT) budget on maintaining their legacy systems. Legacy systems modernization projects are a catalyst for IT architects to save cost, provide new and efficient systems that increase profitability, and create value for their organization. Grounded in sociotechnical systems theory, the purpose of this qualitative multiple case study was to explore strategies IT architects use to modernize their legacy systems. The population included IT architects in large enterprises involved in legacy systems modernization projects, one in healthcare, and one in the financial services industry in the San Antonio-New Braunfels, Texas metropolitan …

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Relationship Between Vendor/Client Complementarity, Vendor Technology Maturity, Vendor Financial Stability, And It Outsourcing Project Outcomes, Everton A. Wilson Jan 2022

Relationship Between Vendor/Client Complementarity, Vendor Technology Maturity, Vendor Financial Stability, And It Outsourcing Project Outcomes, Everton A. Wilson

Walden Dissertations and Doctoral Studies

Business and IT leaders in financial services are concerned with the limited benefits they are reaping from information technology outsourcing (ITO) projects, despite continued heavy investments in ITO. Grounded in the transaction cost, agency, and resource-based view theories, the purpose of this quantitative correlational study was to examine the relationship between vendor/client complementarity, vendor technology maturity, vendor financial stability, and ITO success. Participants were 65 business and IT leaders in financial institutions engaged in ITO projects. The result of the multiple linear regression was significant, F(3, 61) = 4.845, p = .004, R2 = .192. In the final analysis, vendor/client …

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Increasing Nurse Leader Knowledge And Awareness Of Information And Communication Technologies, Cory Stephens Jan 2022

Increasing Nurse Leader Knowledge And Awareness Of Information And Communication Technologies, Cory Stephens

Walden Dissertations and Doctoral Studies

Due to the recent coronavirus disease (COVID-19) pandemic, rapid technological innovation and nursing practice transformation exposed a deepening divide in the knowledge and awareness of information and communication technologies (ICT) among nurses. This technological skills gap undermines the benefits of ICT to nursing practice such as increased nurse satisfaction, improved care quality, and reduced costs. Nurse leaders are positioned to promote the use of ICT among nurses but may suffer from the same knowledge deficit of ICT as their followers. Guided by Locsin’s technological competencies as caring in nursing theory, Staggers and Parks’ nurse-computer interaction framework, and Covell’s nursing intellectual …

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Strategies For Cybercrime Prevention In Information Technology Businesses, Sophfronia G. Tucker Jan 2022

Strategies For Cybercrime Prevention In Information Technology Businesses, Sophfronia G. Tucker

Walden Dissertations and Doctoral Studies

Cybercrime continues to be a devastating phenomenon, impacting individuals and businesses across the globe. Information technology (IT) businesses need solutions to defend and secure their data and networks from cyberattacks. Grounded in general systems theory and transformational leadership theory, the purpose of this qualitative multiple case study was to explore strategies IT business leaders use to protect their systems from a cyberattack. The participants included six IT business leaders with experience in cybersecurity or system security in the Midlands region of South Carolina. Data were collected using semistructured interviews and reviews of government standards documents; data were analyzed using thematic …

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Employee Training Strategies For New Technology Implementation In Small Business, Eddy Varela Jan 2022

Employee Training Strategies For New Technology Implementation In Small Business, Eddy Varela

Walden Dissertations and Doctoral Studies

Failure to implement new technology creates a barrier to success for small businesses. Small business owners must create competitive advantages by implementing new technology as there is a need to maintain an advantage when competing in the local market economy. Grounded in the human capital theory, the purpose of this qualitative multiple case study was to explore the employee training strategies small business owners use to implement new technology. The participants were five small business owners in Central Florida who used employee training strategies to implement new technologies Data were collected using (a) semistructured interviews, (b) member checking interviews, (c) …

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Beyond Triplet Loss: Person Re-Identification With Fine-Grained Difference-Aware Pairwise Loss, Cheng Yan, Guansong Pang, Xiao Bai, Changhong Liu, Xin Ning, Jun Zhou Jan 2022

Beyond Triplet Loss: Person Re-Identification With Fine-Grained Difference-Aware Pairwise Loss, Cheng Yan, Guansong Pang, Xiao Bai, Changhong Liu, Xin Ning, Jun Zhou

Research Collection School Of Computing and Information Systems

Person Re-IDentification (ReID) aims at re-identifying persons from different viewpoints across multiple cameras. Capturing the fine-grained appearance differences is often the key to accurate person ReID, because many identities can be differentiated only when looking into these fine-grained differences. However, most state-of-the-art person ReID approaches, typically driven by a triplet loss, fail to effectively learn the fine-grained features as they are focused more on differentiating large appearance differences. To address this issue, we introduce a novel pairwise loss function that enables ReID models to learn the fine-grained features by adaptively enforcing an exponential penalization on the images of small differences …

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Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard Jan 2022

Contextual Documentation Referencing On Stack Overflow, Sebastian Baltes, Christoph Treude, Martin P. Robillard

Research Collection School Of Computing and Information Systems

Software engineering is knowledge-intensive and requires software developers to continually search for knowledge, often on community question answering platforms such as Stack Overflow. Such information sharing platforms do not exist in isolation, and part of the evidence that they exist in a broader software documentation ecosystem is the common presence of hyperlinks to other documentation resources found in forum posts. With the goal of helping to improve the information diffusion between Stack Overflow and other documentation resources, we conducted a study to answer the question of how and why documentation is referenced in Stack Overflow threads. We sampled and classified …

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Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo Jan 2022

Approximate K-Nn Graph Construction: A Generic Online Approach, Wan-Lei Zhao, Hui Wang, Chong-Wah Ngo

Research Collection School Of Computing and Information Systems

Nearest neighbor search and k-nearest neighbor graph construction are two fundamental issues that arise from many disciplines such as multimedia information retrieval, data-mining, and machine learning. They become more and more imminent given the big data emerge in various fields in recent years. In this paper, a simple but effective solution both for approximate k-nearest neighbor search and approximate k-nearest neighbor graph construction is presented. These two issues are addressed jointly in our solution. On one hand, the approximate k-nearest neighbor graph construction is treated as a search task. Each sample along with its k-nearest neighbors is joined into the …

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A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani Jan 2022

A Blockchain-Based Self-Tallying Voting Protocol In Decentralized Iot, Yannan Li, Willy Susilo, Guomin Yang, Yong Yu, Dongxi Liu, Xiaojiang Du, Mohsen Guizani

Research Collection School Of Computing and Information Systems

The Internet of Things (IoT) is experiencing explosive growth and has gained extensive attention from academia and industry in recent years. However, most of the existing IoT infrastructures are centralized, which may cause the issues of unscalability and single-point-of-failure. Consequently, decentralized IoT has been proposed by taking advantage of the emerging technology called blockchain. Voting systems are widely adopted in IoT, for example a leader election in wireless sensor networks. Self-tallying voting systems are alternatives to unsuitable, traditional centralized voting systems in decentralized IoT. Unfortunately, self-tallying voting systems inherently suffer from fairness issues, such as adaptive and abortive issues caused …

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Predictive Models In Software Engineering: Challenges And Opportunities, Yanming Yang, Xin Xia, David Lo, Tingting Bi, John C. Grundy, Xiaohu Yang Jan 2022

Predictive Models In Software Engineering: Challenges And Opportunities, Yanming Yang, Xin Xia, David Lo, Tingting Bi, John C. Grundy, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-performed studies in various research domains, including software requirements, software design and development, testing and debugging, and software maintenance. This article is a first attempt to systematically organize knowledge in this area by surveying a body of 421 papers on predictive models published between 2009 and 2020. We describe the key models and approaches used, classify the different models, summarize the range of key application …

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Correlating Automated And Human Evaluation Of Code Documentation Generation Quality, Xing Hu, Qiuyuan Chen, Haoye Wang, Xin Xia, David Lo, Thomas Zimmermann Jan 2022

Correlating Automated And Human Evaluation Of Code Documentation Generation Quality, Xing Hu, Qiuyuan Chen, Haoye Wang, Xin Xia, David Lo, Thomas Zimmermann

Research Collection School Of Computing and Information Systems

Automatic code documentation generation has been a crucial task in the field of software engineering. It not only relieves developers from writing code documentation but also helps them to understand programs better. Specifically, deep-learning-based techniques that leverage large-scale source code corpora have been widely used in code documentation generation. These works tend to use automatic metrics (such as BLEU, METEOR, ROUGE, CIDEr, and SPICE) to evaluate different models. These metrics compare generated documentation to reference texts by measuring the overlapping words. Unfortunately, there is no evidence demonstrating the correlation between these metrics and human judgment. We conduct experiments on two …

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Kg4vis: A Knowledge Graph-Based Approach For Visualization Recommendation, Haotian Li, Yong Wang, Songheng Zhang, Yangqiu Song, Huamin. Qu Jan 2022

Kg4vis: A Knowledge Graph-Based Approach For Visualization Recommendation, Haotian Li, Yong Wang, Songheng Zhang, Yangqiu Song, Huamin. Qu

Research Collection School Of Computing and Information Systems

Visualization recommendation or automatic visualization generation can significantly lower the barriers for general users to rapidly create effective data visualizations, especially for those users without a background in data visualizations. However, existing rule-based approaches require tedious manual specifications of visualization rules by visualization experts. Other machine learning-based approaches often work like black-box and are difficult to understand why a specific visualization is recommended, limiting the wider adoption of these approaches. This paper fills the gap by presenting KG4Vis, a knowledge graph (KG)-based approach for visualization recommendation. It does not require manual specifications of visualization rules and can also guarantee good …

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Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy Jan 2022

Why Do Smart Contracts Self-Destruct? Investigating The Selfdestruct Function On Ethereum, Jiachi Chen, Xin Xia, David Lo, John C. Grundy

Research Collection School Of Computing and Information Systems

The selfdestruct function is provided by Ethereum smart contracts to destroy a contract on the blockchain system. However, it is a double-edged sword for developers. On the one hand, using the selfdestruct function enables developers to remove smart contracts (SCs) from Ethereum and transfers Ethers when emergency situations happen, e.g., being attacked. On the other hand, this function can increase the complexity for the development and open an attack vector for attackers. To better understand the reasons why SC developers include or exclude the selfdestruct function in their contracts, we conducted an online survey to collect feedback from them and …

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M2lens: Visualizing And Explaining Multimodal Models For Sentiment Analysis, Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu Jan 2022

M2lens: Visualizing And Explaining Multimodal Models For Sentiment Analysis, Xingbo Wang, Jianben He, Zhihua Jin, Muqiao Yang, Yong Wang, Huamin Qu

Research Collection School Of Computing and Information Systems

Multimodal sentiment analysis aims to recognize people's attitudes from multiple communication channels such as verbal content (i.e., text), voice, and facial expressions. It has become a vibrant and important research topic in natural language processing. Much research focuses on modeling the complex intra- and inter-modal interactions between different communication channels. However, current multimodal models with strong performance are often deep-learning-based techniques and work like black boxes. It is not clear how models utilize multimodal information for sentiment predictions. Despite recent advances in techniques for enhancing the explainability of machine learning models, they often target unimodal scenarios (e.g., images, sentences), and …

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Orchestration Or Automation: Authentication Flaw Detection In Android Apps, Siqi Ma, Juanru Li, Surya Nepal, Diethelm Ostry, David Lo, Sanjay K. Jha, Robert H. Deng, Elisa Bertino Jan 2022

Orchestration Or Automation: Authentication Flaw Detection In Android Apps, Siqi Ma, Juanru Li, Surya Nepal, Diethelm Ostry, David Lo, Sanjay K. Jha, Robert H. Deng, Elisa Bertino

Research Collection School Of Computing and Information Systems

Passwords are pervasively used to authenticate users' identities in mobile apps. To secure passwords against attacks, protection is applied to the password authentication protocol (PAP). The implementation of the protection scheme becomes an important factor in protecting PAP against attacks. We focus on two basic protection in Android, i.e., SSL/TLS-based PAP and timestamp-based PAP. Previously, we proposed an automated tool, GLACIATE, to detect authentication flaws. We were curious whether orchestration (i.e., involving manual-effort) works better than automation. To answer this question, we propose an orchestrated approach, AUTHEXPLOIT and compare its effectiveness GLACIATE. We study requirements for correct implementation of PAP …

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On The Reproducibility And Replicability Of Deep Learning In Software Engineering, Chao Liu, Cuiyun Gao, Xin Xia, David Lo, John C. Grundy, Xiaohu Yang Jan 2022

On The Reproducibility And Replicability Of Deep Learning In Software Engineering, Chao Liu, Cuiyun Gao, Xin Xia, David Lo, John C. Grundy, Xiaohu Yang

Research Collection School Of Computing and Information Systems

Context: Deep learning (DL) techniques have gained significant popularity among software engineering (SE) researchers in recent years. This is because they can often solve many SE challenges without enormous manual feature engineering effort and complex domain knowledge.Objective: Although many DL studies have reported substantial advantages over other state-of-the-art models on effectiveness, they often ignore two factors: (1) reproducibility—whether the reported experimental results can be obtained by other researchers using authors’ artifacts (i.e., source code and datasets) with the same experimental setup; and (2) replicability—whether the reported experimental result can be obtained by other researchers using their re-implemented artifacts with a …

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Information Communication And Technology Strategies For Improving Nonprofit Organizations’ Effectiveness, Richard T. Evans Jan 2022

Information Communication And Technology Strategies For Improving Nonprofit Organizations’ Effectiveness, Richard T. Evans

Walden Dissertations and Doctoral Studies

AbstractSome nonprofit organization leaders lack strategies to incorporate information communication and technology (ICT) into the business operations of organizations. A nonprofit organization lacking strategies involving integrating technology into their business operations decreases the likelihood of being efficient, productive, and effective. Grounded in the information technology (IT) competency model, the purpose of this qualitative single case study was to explore the ICT strategies of a nonprofit organization leader in the south suburbs of Chicago. Data were collected through semi-structured interviews, direct observations, and reviews of organizational documents. The Marshall and Rossman seven-step process was used to analyze data. Three themes emerged …

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Exploring Critical Success Factors For Implementing It Modernization Systems In Michigan State Agencies, Luc Armand Kamdem Jan 2022

Exploring Critical Success Factors For Implementing It Modernization Systems In Michigan State Agencies, Luc Armand Kamdem

Walden Dissertations and Doctoral Studies

Since 2001, most government organizations’ IT modernization programs had failed because of ineffective implementation strategies from IT leaders. The research problem was the absence of effective strategies to modernize IT legacy systems. The purpose of this qualitative single case study was to explore effective IT modernization strategies to revolutionize IT legacy systems. The researcher sought to answer how organizations create effective strategies to modernize IT legacy systems. The study used purposeful sampling, including 13 IT leaders, IT technicians, and customers based on their experience in implementing successful IT modernization programs’ strategies. Data were collected using semi-structured interviews and agency documentation. …

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Using Agile Strategies To Improve Project Success Rates, Tim Kirkland Jan 2022

Using Agile Strategies To Improve Project Success Rates, Tim Kirkland

Walden Dissertations and Doctoral Studies

Project failures can be costly to businesses, but on average, program managers’ (PMs’) success rates for managing information technology (IT) projects is less than 35%. Organizational cultures struggle to adapt to agile project management (APM) that provides stakeholder flexibility for dynamic environments. Grounded by project management theory, the purpose of this qualitative multiple case study was to explore strategies project managers use to reduce IT project failures. The participants consisted of nine project managers in the northeastern United States with APM experience managing successful IT projects. Data were collected from virtual semi-structured interviews and journal notes. Ten open-ended interview questions …

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Equipment Rental Companies Leaders’ Customer Retention Strategies, Katrell Shalaine Mcneil Jan 2022

Equipment Rental Companies Leaders’ Customer Retention Strategies, Katrell Shalaine Mcneil

Walden Dissertations and Doctoral Studies

Equipment rental business leaders that employ inadequate customer retention strategies negatively impact organizations’ performance and profitability. Improved customer retention strategies might improve key customer retention and increase market share. Grounded in the customer retention management theory, the purpose of this qualitative multiple case study was to explore strategies rental leaders use to retain customers. Participants were 10 equipment rental leaders from the Southwest Region of the United States that successfully retained their key customers through effective customer retention strategies. Data were collected using semistructured interviews and a review of materials from organizational websites regarding customer order fulfillment and technology. Through …

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Optimal Domotic Systems Based On Archival Data Trend Analysis, Bettina Yvette Moore Jan 2022

Optimal Domotic Systems Based On Archival Data Trend Analysis, Bettina Yvette Moore

Walden Dissertations and Doctoral Studies

Domotics is the integration of technology into building systems. Due to the rapid growth in the use of domotic systems in recent years, the industry is struggling to establish consistency and standardization. The purpose of this archival-based qualitative case study was to identify current trends and patterns in scholarly domotic research to create an instrument to evaluate domotic systems and domotic interrelationships using bibliometric searches. The facilities management and modeling system provided the framework for the study. Archival research data were examined to identify trends and patterns in domotic research and provide visualization of domotic relationships through technology trajectory mapping …

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