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Full-Text Articles in Computer Sciences

User Awareness And Knowledge Of Cybersecurity And The Impact Of Training In The Commonwealth Of Dominica, Jermaine Jewel Jean-Pierre Jan 2021

User Awareness And Knowledge Of Cybersecurity And The Impact Of Training In The Commonwealth Of Dominica, Jermaine Jewel Jean-Pierre

Walden Dissertations and Doctoral Studies

The frequency of cyberattacks against governments has increased at an alarming rate and the lack of user awareness and knowledge of cybersecurity has been considered a contributing factor to the increase in cyberattacks and cyberthreats. The purpose of this quantitative experimental study was to explore the role and effectiveness of employee training focused on user awareness of cyberattacks and cybersecurity, with the intent to close the gap in understanding about the level of awareness of cybersecurity within the public sector of the Commonwealth of Dominica. The theoretical framework was Bandura’s social cognitive theory, following the idea that learning occurs in …

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"Who Can Help Me?'': Knowledge Infused Matching Of Support Seekers And Support Providers During Covid-19 On Reddit, Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth Jan 2021

"Who Can Help Me?'': Knowledge Infused Matching Of Support Seekers And Support Providers During Covid-19 On Reddit, Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth

Publications

During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs). Currently, knowledgeable human moderators match an SS with a user with relevant experience, i.e, an SP on these subreddits. This unscalable process defers timely care. We present a medical knowledge-infused approach to efficient matching of SS and SPs validated by experts for the users affected by anxiety and depression, in the context of with COVID-19. After matching, each SP to …

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Single And Differential Morph Attack Detection, Baaria Chaudhary Jan 2021

Single And Differential Morph Attack Detection, Baaria Chaudhary

Graduate Theses, Dissertations, and Problem Reports (ETD)

Face recognition systems operate on the assumption that a person's face serves as the unique link to their identity. In this thesis, we explore the problem of morph attacks, which have become a viable threat to face verification scenarios precisely because of their inherent ability to break this unique link. A morph attack occurs when two people who share similar facial features morph their faces together such that the resulting face image is recognized as either of two contributing individuals. Morphs inherit enough visual features from both individuals that both humans and automatic algorithms confuse them. The contributions of this …

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Strategies To Sustain Small Construction Businesses Beyond The First 5 Years Of Operation, Catherine Nyasha Mukopfa Jan 2021

Strategies To Sustain Small Construction Businesses Beyond The First 5 Years Of Operation, Catherine Nyasha Mukopfa

Walden Dissertations and Doctoral Studies

Small business owners employ over half the U.S. labor force, yet only 50% of small businesses survive beyond 5 years. When small business owners understand the factors that lead to their business failure, they can develop strategies to remain sustainable and profitable within the first 5 years, thus reducing the potential of business failure. Grounded in the resource-based theory, the purpose of this qualitative multiple case study was to explore strategies five small construction owners in central Georgia used to remain in business beyond 5 years. Data were collected from semi structured interviews, a review of organization income statements and …

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Strategies Security Managers Used To Prevent Security Breaches In Scada Systems' Networks, Oladipo Ogunmesa Jan 2021

Strategies Security Managers Used To Prevent Security Breaches In Scada Systems' Networks, Oladipo Ogunmesa

Walden Dissertations and Doctoral Studies

Supervisory Control and Data Acquisition (SCADA) systems monitor and control physical processes in critical infrastructure. The impact of successful attacks on the SCADA systems includes the system's downtime and delay in production, which may have a debilitating effect on the national economy and create critical human safety hazards. Grounded in the general systems theory, the purpose of this qualitative multiple case study was to explore strategies SCADA security managers in the Southwest region of the United States use to secure SCADA systems' networks. The participants comprised six SCADA security managers from three oil and gas organizations in the midstream sector …

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Strategies To Protect Against Security Violations During The Adoption Of The Internet Of Things By Manufacturers, Sixtus Anayochukwu Ekwo Jan 2021

Strategies To Protect Against Security Violations During The Adoption Of The Internet Of Things By Manufacturers, Sixtus Anayochukwu Ekwo

Walden Dissertations and Doctoral Studies

Security violations have been one of the key factors affecting manufacturers in adopting the Internet of Things (IoT). The corporate-level information technology (IT) leaders in the manufacturing industry encounter issues when adopting IoT due to security concerns because they lack strategies to protect against security violations. Grounded in Roger’s diffusion of innovations theory, the purpose of this qualitative multiple case study was to explore strategies corporate-level IT leaders use in protecting against security violations while adopting IoT for manufacturers. The participants were senior IT leaders in the eastern region of the United States. The data collection process included interviews with …

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Reliable Data Collection: A Tool For Data Integrity In Nigeria, Stella Tonye Whyte Jan 2021

Reliable Data Collection: A Tool For Data Integrity In Nigeria, Stella Tonye Whyte

Walden Dissertations and Doctoral Studies

Unreliable and poor-quality data is a significant threat to governmental institutions because of its devastating impact on nations' social and economic well-being. Managers in government organizations require reliable data to inform economic planning and decision-making. Grounded in the theory of total quality management, the purpose of this qualitative multiple case study was to explore strategies information technology (IT) managers in sub-Saharan African countries use to ensure the reliability of data. The participants were 12 IT managers in three government establishments in Port Harcourt, Rivers State, Nigeria, responsible for ensuring the data reliability for economic planning and decision-making. The data collection …

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Relationships Among Dimensions Of Information System Success And Benefits Of Cloud, William Harold Stanley Jan 2021

Relationships Among Dimensions Of Information System Success And Benefits Of Cloud, William Harold Stanley

Walden Dissertations and Doctoral Studies

Despite the many benefits offered by cloud computing’s design architecture, there are many fundamental performance challenges for IT managers to manage cloud infrastructures to meet business expectations effectively. Grounded in the information systems success model, the purpose of this quantitative correlational study was to evaluate the relationships among the perception of information quality, perception of system quality, perception of service quality, perception of system use, perception of user satisfaction, and net benefits of cloud computing services. The participants (n = 137) were IT cloud services managers in the United States, who completed the DeLone and McLean ISS authors’ validated survey …

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Addressing High False Positive Rates Of Ddos Attack Detection Methods, Alireza Zeinalpour Jan 2021

Addressing High False Positive Rates Of Ddos Attack Detection Methods, Alireza Zeinalpour

Walden Dissertations and Doctoral Studies

Distributed denial of service (DDoS) attack detection methods based on the clustering method are ineffective in detecting attacks correctly. Service interruptions caused by DDoS attacks impose concerns for IT leaders and their organizations, leading to financial damages. Grounded in the cross industry standard process for data mining framework, the purpose of this ex post facto study was to examine whether adding the filter and wrapper methods prior to the clustering method is effective in terms of lowering false positive rates of DDoS attack detection methods. The population of this study was 225,745 network traffic data records of the CICIDS2017 network …

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Create A New Login Authentication And User Authorization Using Ms Sql Server, Safet Jahaj Jan 2021

Create A New Login Authentication And User Authorization Using Ms Sql Server, Safet Jahaj

Open Educational Resources

The document describes the steps on creating a new login authentication using the mixed mode, and adding user authorizations.

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Football’S Future: An Analytical Interpretation Of The Premier League, Hunter Witeof Jan 2021

Football’S Future: An Analytical Interpretation Of The Premier League, Hunter Witeof

Williams Honors College, Honors Research Projects

This project looks to take the statistics of soccer players and run them through an algorithm to determine how well a player is performing. The system that will be designed in the project will look to accomplish 3 main goals: allow the user to enter new statistics, store the data for all 38 game weeks for all 20 teams, and compute a score for each player’s performance for each game as well as the average of all of the player's scores.

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Cura Personalis: Institutionalizing Compassion During Emergency Remote Teaching, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito Jan 2021

Cura Personalis: Institutionalizing Compassion During Emergency Remote Teaching, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito

Department of Information Systems & Computer Science Faculty Publications

Faced with the fears and anxieties brought on by the COVID-19 crisis, educational institutions had to devise new compassion-based teaching and learning policies and approaches that recognized and provided for the pandemic’s psychological and emotional toll. This paper describes how the Ateneo de Manila University in the Philippines enacted its core value of cura personalis, care for the entire person, in the context of emergency remote teaching. We describe the circumstances that prompted the greater emphasis on compassion and the adjustments to classroom management, course content, class interactions, and assessment. Finally we describe the tradeoffs or costs of this …

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Transactional Distances During Emergency Remote Teaching Experiences, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito Jan 2021

Transactional Distances During Emergency Remote Teaching Experiences, Ma. Monica L. Moreno, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Timothy Jireh Gaspar, Jenilyn L. Agapito

Department of Information Systems & Computer Science Faculty Publications

The Transactional Distance Theory posits that successful remote learning occurs when teachers decrease psychological or transactional gaps. Narrowing the transactional distance can be achieved through a balance of appropriate course structure and dialogue, fostering healthy student autonomy in the process. This paper describes the Emergency Remote Teaching experiences of faculty and students of the Ateneo de Manila University in the Philippines. It examines these experiences in the context of the transactional distance framework. Findings show that a sudden shift to remote learning mandates greater student autonomy, which increases transactional distance. Because of this, efforts by faculty to increase student-teacher dialogue …

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Xiphias: Using A Multidimensional Approach Towards Creating Meaningful Gamification-Based Badge Mechanics, Jonathan D.L Casano, Jenilyn L. Agapito, Nicole Ann F. Tolosa Jan 2021

Xiphias: Using A Multidimensional Approach Towards Creating Meaningful Gamification-Based Badge Mechanics, Jonathan D.L Casano, Jenilyn L. Agapito, Nicole Ann F. Tolosa

Department of Information Systems & Computer Science Faculty Publications

This paper shows the design and initial testing of three new Xiphias Badges --Presence; Mastery; and Antifragility – based on the merging of the salient features from James Clear’s Behavior Change model (2016); Johann Hari’s Lost Connections model (2018); and Jordan Peterson’s recent interpretation of the Big Five model of Personality Traits (2007). This multidimensional approach is an attempt to cater to the multidimensionality of a user and aims to be a more universal gamification approach that taps into internal motivations. The badge mechanics were tested on 69 undergraduate students using a Low-Fidelity Gamified Tracker. The results of a survey …

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Comparison Of English Comprehension Among Students From Different Backgrounds Using A Narrative-Centered Digital Game, May Marie P. Talandron-Felipe, Kent Levi A. Bonifacio, Gladys S. Ayunar, Ma. Mercedes T. Rodrigo Jan 2021

Comparison Of English Comprehension Among Students From Different Backgrounds Using A Narrative-Centered Digital Game, May Marie P. Talandron-Felipe, Kent Levi A. Bonifacio, Gladys S. Ayunar, Ma. Mercedes T. Rodrigo

Department of Information Systems & Computer Science Faculty Publications

This paper reports the continuation of the field testing of a narrative-centered digital game for English comprehension called Learning Likha: Rangers to the Rescue (LLRR) with a two-fold goal: first, identify the differences in terms of usage, attitudes towards, and perceptions of the English language between students from southern Philippines and the National Capital Region, and second, to determine how the LLRR in-game performance, post-test comprehension scores, engagement, and motivation of students differ between the groups. The participants who are grade school students from a province in southern Philippines answered questionnaires about their attitude towards and perception of English, played …

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For People And Planet: Teachers’ Evaluation Of An Educational Mobile Game And Resource Pack, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Janina Carla M. Castro, Abigail Marie T. Favis, Ingrid Yvonne Herras, Francesco U. Amante, Hakeem Jimenez, Juan Carlo F. Mallari, Kevin Arnel C. Mora, Walfrido David A. Diy, Jaclyn Ting Ting M. Lim, Ma. Assunta C. Cuyegkeng Jan 2021

For People And Planet: Teachers’ Evaluation Of An Educational Mobile Game And Resource Pack, Ma. Mercedes T. Rodrigo, Johanna Marion R. Torres, Janina Carla M. Castro, Abigail Marie T. Favis, Ingrid Yvonne Herras, Francesco U. Amante, Hakeem Jimenez, Juan Carlo F. Mallari, Kevin Arnel C. Mora, Walfrido David A. Diy, Jaclyn Ting Ting M. Lim, Ma. Assunta C. Cuyegkeng

Department of Information Systems & Computer Science Faculty Publications

For People and Planet: An SDG Adventure refers to a freely available Android-based narrative adventure game and teacher resource pack that helps learners see the United Nations Sustainable Development Goals (SDGs) in their day-to-day lives. In this paper, we describe the results of an evaluation of both the game and the resource pack by eight (8) middle school teachers. After playing the game and reading the resource pack, teachers gave their feedback about what they liked best and least about the materials, how they could use these resources for their classes, and how these resources could be improved further. Overall, …

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Introducing A Test Framework For Quality Of Service Mechanisms In The Context Of Software-Defined Networking, Josiah Eleazar T. Regencia, William Emmanuel S. Yu Jan 2021

Introducing A Test Framework For Quality Of Service Mechanisms In The Context Of Software-Defined Networking, Josiah Eleazar T. Regencia, William Emmanuel S. Yu

Department of Information Systems & Computer Science Faculty Publications

In traditional non-distributed networking architecture, supporting Quality of Service (QoS) has been challenging due to its centralized nature. Software-Defined Networking (SDN) provides dynamic, flexible and scalable control and management for networks. This study introduces a test framework for testing QoS mechanisms and network topologies inside an SDN environment. Class-Based Queueing QoS mechanisms are tested as an anchor to test the introduced framework. Using a previous study as a benchmark to test the introduced framework, results show that the test framework works accordingly and is capable of producing accurate results. Moreover, results in this study show that the distributed Leaf-enforced QoS …

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Activity Based Traffic Indicator System For Monitoring The Covid-19 Pandemic, Justin Junsay, Aaron Joaquin Lebumfacil, Ivan George Tarun, William Emmanuel S. Yu Jan 2021

Activity Based Traffic Indicator System For Monitoring The Covid-19 Pandemic, Justin Junsay, Aaron Joaquin Lebumfacil, Ivan George Tarun, William Emmanuel S. Yu

Department of Information Systems & Computer Science Faculty Publications

This study describes an activity based traffic indicator system to provide information for COVID-19 pandemic management. The activity based traffic indicator system does this by utilizing a social probability model based on the birthday paradox to determine the exposure risk, the probability of meeting someone infected (PoMSI). COVID-19 data, particularly the 7-day moving average of the daily growth rate of cases (7-DMA of DGR) and cumulative confirmed cases of next week covering a period from April to September 2020, were then used to test PoMSI using Pearson correlation to verify whether it can be used as a factor for the …

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Novel Techniques In Recovering, Embedding, And Enforcing Policies For Control-Flow Integrity, Yan Lin Jan 2021

Novel Techniques In Recovering, Embedding, And Enforcing Policies For Control-Flow Integrity, Yan Lin

Dissertations and Theses Collection (Open Access)

Control-Flow Integrity (CFI) is an attractive security property with which most injected and code-reuse attacks can be defeated, including advanced attacking techniques like Return-Oriented Programming (ROP). CFI extracts a control-flow graph (CFG) for a given program and instruments the program to respect the CFG. Specifically, checks are inserted before indirect branch instructions. Before these instructions are executed during runtime, the checks consult the CFG to ensure that the indirect branch is allowed to reach the intended target. Hence, any sort of controlflow hijacking would be prevented. There are three fundamental components in CFI enforcement. The first component is accurately recovering …

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Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam Jan 2021

Analyzing Tweets On New Norm: Work From Home During Covid-19 Outbreak, Swapna Gottipati, Kyong Jin Shim, Hui Hian Teo, Karthik Nityanand, Shreyansh Shivam

Research Collection School Of Computing and Information Systems

The COVID-19 pandemic triggered a large-scale work-from-home trend globally in recent months. In this paper, we study the phenomenon of “work-from-home” (WFH) by performing social listening. We propose an analytics pipeline designed to crawl social media data and perform text mining analyzes on textual data from tweets scrapped based on hashtags related to WFH in COVID-19 situation. We apply text mining and NLP techniques to analyze the tweets for extracting the WFH themes and sentiments (positive and negative). Our Twitter theme analysis adds further value by summarizing the common key topics, allowing employers to gain more insights on areas of …

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Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin Jan 2021

Deep Unsupervised Anomaly Detection, Tangqing Li, Zheng Wang, Siying Liu, Wen-Yan Lin

Research Collection School Of Computing and Information Systems

This paper proposes a novel method to detect anomalies in large datasets under a fully unsupervised setting. The key idea behind our algorithm is to learn the representation underlying normal data. To this end, we leverage the latest clustering technique suitable for handling high dimensional data. This hypothesis provides a reliable starting point for normal data selection. We train an autoencoder from the normal data subset, and iterate between hypothesizing normal candidate subset based on clustering and representation learning. The reconstruction error from the learned autoencoder serves as a scoring function to assess the normality of the data. Experimental results …

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Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He Jan 2021

Coherence And Identity Learning For Arbitrary-Length Face Video Generation, Shuquan Ye, Chu Han, Jiaying Lin, Guoqiang Han, Shengfeng He

Research Collection School Of Computing and Information Systems

Face synthesis is an interesting yet challenging task in computer vision. It is even much harder to generate a portrait video than a single image. In this paper, we propose a novel video generation framework for synthesizing arbitrary-length face videos without any face exemplar or landmark. To overcome the synthesis ambiguity of face video, we propose a divide-and-conquer strategy to separately address the video face synthesis problem from two aspects, face identity synthesis and rearrangement. To this end, we design a cascaded network which contains three components, Identity-aware GAN (IA-GAN), Face Coherence Network, and Interpolation Network. IA-GAN is proposed to …

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Facial Emotion Recognition With Noisy Multi-Task Annotations, S. Zhang, Zhiwu Huang, D.P. Paudel, Gool L. Van Jan 2021

Facial Emotion Recognition With Noisy Multi-Task Annotations, S. Zhang, Zhiwu Huang, D.P. Paudel, Gool L. Van

Research Collection School Of Computing and Information Systems

Human emotions can be inferred from facial expressions. However, the annotations of facial expressions are often highly noisy in common emotion coding models, including categorical and dimensional ones. To reduce human labelling effort on multi-task labels, we introduce a new problem of facial emotion recognition with noisy multitask annotations. For this new problem, we suggest a formulation from the point of joint distribution match view, which aims at learning more reliable correlations among raw facial images and multi-task labels, resulting in the reduction of noise influence. In our formulation, we exploit a new method to enable the emotion prediction and …

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Proxy-Free Privacy-Preserving Task Matching With Efficient Revocation In Crowdsourcing, Jiangang Shu, Kan Yang, Xiaohua Jia, Ximeng Liu, Cong Wang, Robert H. Deng Jan 2021

Proxy-Free Privacy-Preserving Task Matching With Efficient Revocation In Crowdsourcing, Jiangang Shu, Kan Yang, Xiaohua Jia, Ximeng Liu, Cong Wang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Task matching in crowdsourcing has been extensively explored with the increasing popularity of crowdsourcing. However, privacy of tasks and workers is usually ignored in most of exiting solutions. In this paper, we study the problem of privacy-preserving task matching for crowdsourcing with multiple requesters and multiple workers. Instead of utilizing proxy re-encryption, we propose a proxy-free task matching scheme for multi-requester/multi-worker crowdsourcing, which achieves task-worker matching over encrypted data with scalability and non-interaction. We further design two different mechanisms for worker revocation including ServerLocal Revocation (SLR) and Global Revocation (GR), which realize efficient worker revocation with minimal overhead on the …

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Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction, Qiuyuan Chen, Xin Xia, Han Hu, David Lo, Shanping Li Jan 2021

Why My Code Summarization Model Does Not Work: Code Comment Improvement With Category Prediction, Qiuyuan Chen, Xin Xia, Han Hu, David Lo, Shanping Li

Research Collection School Of Computing and Information Systems

Code summarization aims at generating a code comment given a block of source code and it is normally performed by training machine learning algorithms on existing code block-comment pairs. Code comments in practice have different intentions. For example, some code comments might explain how the methods work, while others explain why some methods are written. Previous works have shown that a relationship exists between a code block and the category of a comment associated with it. In this article, we aim to investigate to which extent we can exploit this relationship to improve code summarization performance. We first classify comments …

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Adversarial Specification Mining, Hong Jin Kang, David Lo Jan 2021

Adversarial Specification Mining, Hong Jin Kang, David Lo

Research Collection School Of Computing and Information Systems

There have been numerous studies on mining temporal specifications from execution traces. These approaches learn finite-state automata (FSA) from execution traces when running tests. To learn accurate specifications of a software system, many tests are required. Existing approaches generalize from a limited number of traces or use simple test generation strategies. Unfortunately, these strategies may not exercise uncommon usage patterns of a software system. To address this problem, we propose a new approach, adversarial specification mining, and develop a prototype, DICE (Diversity through Counter-Examples). DICE has two components: DICE-Tester and DICE-Miner. After mining Linear Temporal Logic specifications from an input …

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Technical Q8a Site Answer Recommendation Via Question Boosting, Zhipeng Gao, Xin Xia, David Lo, John Grundy Jan 2021

Technical Q8a Site Answer Recommendation Via Question Boosting, Zhipeng Gao, Xin Xia, David Lo, John Grundy

Research Collection School Of Computing and Information Systems

Software developers have heavily used online question and answer platforms to seek help to solve their technical problems. However, a major problem with these technical Q&A sites is "answer hungriness" i.e., a large number of questions remain unanswered or unresolved, and users have to wait for a long time or painstakingly go through the provided answers with various levels of quality. To alleviate this time-consuming problem, we propose a novel DeepAns neural network-based approach to identify the most relevant answer among a set of answer candidates. Our approach follows a three-stage process: question boosting, label establishment, and answer recommendation. Given …

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Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy Jan 2021

Context-Aware Retrieval-Based Deep Commit Message Generation, Haoye Wang, Xin Xia, David Lo, Qiang He, Xinyu Wang, John Grundy

Research Collection School Of Computing and Information Systems

Commit messages recorded in version control systems contain valuable information for software development, maintenance, and comprehension. Unfortunately, developers often commit code with empty or poor quality commit messages. To address this issue, several studies have proposed approaches to generate commit messages from commit diffs. Recent studies make use of neural machine translation algorithms to try and translate git diffs into commit messages and have achieved some promising results. However, these learning-based methods tend to generate high-frequency words but ignore low-frequency ones. In addition, they suffer from exposure bias issues, which leads to a gap between training phase and testing phase. …

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Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman Jan 2021

Sustainability Of Rewards-Based Crowdfunding: A Quasi-Experimental Analysis Of Funding Targets And Backer Satisfaction, Michael Wessel, Rob Gleasure, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Rewards-based crowdfunding presents an information asymmetry for participants due to the funding mechanism used. Campaign-backers trust creators to complete projects and deliver rewards as outlined prior to the fundraising process, but creators may discover better opportunities as they progress with a project. Despite this, the all-or-nothing (AON) mechanism on crowdfunding platforms incentivizes creators to set meager funding-targets that are easier to achieve but may offer limited slack when creators wish to simultaneously pursue emerging opportunities later in the project. We explore the related issues of how funding targets seem to be selected by the creators, and how dissatisfaction with the …

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Creators And Backers In Rewards-Based Crowdfunding: Will Incentive Misalignment Affect Kickstarter's Sustainability?, Michael Wessel, Rob Gleasure, Robert John Kauffman Jan 2021

Creators And Backers In Rewards-Based Crowdfunding: Will Incentive Misalignment Affect Kickstarter's Sustainability?, Michael Wessel, Rob Gleasure, Robert John Kauffman

Research Collection School Of Computing and Information Systems

Incentive misalignment in rewards-based crowd-funding occurs because creators may benefit disproportionately from fundraising, while backers may benefit disproportionately from the quality of project deliverables. The resulting principal-agent relationship means backers rely on campaign information to identify signs of moral hazard, adverse selection, and risk attitude asymmetry. We analyze campaign information related to fundraising, and compare how different information affects eventual backer satisfaction, based on an extensive dataset from Kickstarter. The data analysis uses a multi-model comparison to reveal similarities and contrasts in the estimated drivers of dependent variables that capture different outcomes in Kickstarter’s funding campaigns, using a linear probability …

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