How Loyal are You? Continuance Intention and Word of Mouth in Free/Libre Open Source Software

Free/Libre Open Source Software (FLOSS) has begun to attract increasing numbers of non-technical end-users. Drawing upon information systems (IS) post-adoption research and other relevant research including IS success, consumer behavior, and FLOSS, the current proposed study will open a necessary but unexplored new research agenda: non-technical end-users’ continued FLOSS usage behaviors and examine the phenomenon by proposing a model. The study will further examine the proposed model by comparing two distinct user populations (i.e., regular loyal users vs. dedicated loyal users), and identify the factors that are more prominent in the dedicated loyal user population. The research will also conduct a case study on an exemplary community-led marketing campaign (i.e., Spreadfirefox.com) to examine how the practice of word of mouth is made more effective through its dedicated loyal users’ active contributions. In addition to its theoretical contribution to FLOSS research, the research will generate a range of practical implications for FLOSS communities as to how they can achieve a much stronger loyal user base and benefit from their contributions

Loyalty, Ideology, and Identification: An Empirical Study of the Attitudes and Behaviors of Passive Users of Open Source Software

Extant research on open source software (OSS) has primarily focused on software developers and active users but has paid limited attention to the less visible “passive” users who form the silent majority of OSS communities. Passive users play a critical role in the adoption and diffusion of OSS, and we need more research to understand their behaviors and motivations. We address this gap by drawing on the sociological theory of community markers. The three community markers in the context of OSS are loyalty, ideology, and identification. We also draw on marketing literature to propose four contributory behaviors of passive users of OSS that we theorize to be impacted by the community markers: user brand-extension, word-of-mouth, endorsement, and community involvement. We further classify passive users’ contributory behaviors according to the difficulty of their enactment and examine the differential influence of the OSS community markers. Partial-least squares (PLS) analyses of data obtained through a survey of passive users of an OSS product provide support for the majority of the hypotheses

Itinerary planner: A mashup case study

The wide adoption of Web Services and the availability of web APIs are transforming the web into a programmatic environment for developing innovative web applications that combine information from various sources to provide a rich user experience. These mashup applications are characterized by rapid development using existing data sources and the use of new technologies such as AJAX, JSON, etc. Developers often focus on delivering rich functionality via the browser environment and pay little attention to the design and maintainability of the applications. In this paper we describe our experience in developing an Itinerary Planner travel application, and discuss the challenges associated with developing mashups. In the conclusion, we briefly discuss the lessons learned in addressing these challenges and how these lessons can be applied to future mashup projects. © 2009 Springer Berlin Heidelberg

Online advertising: analysis of privacy threats and protection approaches

Online advertising, the pillar of the “free” content on the Web, has revolutionized the marketing business in recent years by creating a myriad of new opportunities for advertisers to reach potential customers. The current advertising model builds upon an intricate infrastructure composed of a variety of intermediary entities and technologies whose main aim is to deliver personalized ads. For this purpose, a wealth of user data is collected, aggregated, processed and traded behind the scenes at an unprecedented rate. Despite the enormous value of online advertising, however, the intrusiveness and ubiquity of these practices prompt serious privacy concerns. This article surveys the online advertising infrastructure and its supporting technologies, and presents a thorough overview of the underlying privacy risks and the solutions that may mitigate them. We first analyze the threats and potential privacy attackers in this scenario of online advertising. In particular, we examine the main components of the advertising infrastructure in terms of tracking capabilities, data collection, aggregation level and privacy risk, and overview the tracking and data-sharing technologies employed by these components. Then, we conduct a comprehensive survey of the most relevant privacy mechanisms, and classify and compare them on the basis of their privacy guarantees and impact on the Web.Peer ReviewedPostprint (author's final draft

Towards A Software Failure Cost Impact Model for the Customer An Analysis of an Open Source Product

ABSTRACT While the financial consequences of software errors on the developer's side have been explored extensively, the costs arising for the end user have been largely neglected. One reason is the difficulty of linking errors in the code with emerging failure behavior of the software. The problem becomes even more difficult when trying to predict failure probabilities based on models or code metrics. In this paper we take a first step towards a cost prediction model by exploring the possibilities of modeling the financial consequences of already identified software failures. Firefox, a well-known open source software, is used as a test subject. Historically identified failures are modeled using fault trees. To identify costs, usage profiles are employed to depict the interaction with the system. The presented approach demonstrates the possibility to model failure cost for an organization using a specific software by establishing a relationship between user behavior, software failures, and costs. As future work, an extension with software error prediction techniques as well as an empirical validation of the model is aspired

Upside Down Facebook: Raising Awareness of Behavioral Advertising Through Artistic Provocation

The majority of Americans are aware and concerned about corporations' collection and use of personal data for behavioral advertising, but are resigned to having little to no control. Opaque corporate data disclosures, limited privacy controls, complex data flows, and cognitive limitations impede understanding of behavioral advertising. Alternative tools created by privacy researchers seek to make data transparent and actionable, but fall short in creating an emotional response, fully clarifying behavioral advertising systems, and breaking through digital resignation. Using conceptual artistic perspectives on technology and privacy and privacy research from human-computer interaction as inspirations, this thesis proposes an approach to raising awareness of behavioral advertising through artistic provocation. Using Facebook's "Information About You" data download as a test-bed, I develop a prototype for a new kind of experience called Upside Down Facebook, which re-frames institutional privacy issues as social privacy issues through deliberately "creepy" posts about data made by a personified version of Facebook. In a preliminary evaluation study (n=7), a majority of participants were provoked by this experience to learn more about how their data is used for behavioral advertising and take action to change their settings. This work suggests the potential of Upside Down Facebook to help individuals learn about behavioral advertising and take action, as well as the potential for artistic provocation to inform new perspectives on designing privacy tools and research on data privacy.Master of Science in InformationSchool of Informationhttp://deepblue.lib.umich.edu/bitstream/2027.42/168560/1/20210427_Soonthornsawad,Joe_Final_MTOP_Thesis.pd

Doctor of Philosophy

dissertationThrough a case study analysis of 19th and 21st century communitarian innovation groups, this dissertation develops a business model that promotes innovation without the incentives of monopoly profits provided by patents. Social Utopian communities of the 19th century and Free and Open Source Software development communities share similar contributors' incentives and comparable organizational structures which provides a foundation for a business model that can be transported to other industries, specifically biotechnology. Communitarian innovation groups already exist within the biotechnology sector but have not yet been proven effective or capable of applying the communitarian business model through all stages of research and development. This dissertation provides the business model for communitarian innovation as well as recommendations on how to apply the business model to all stages of biotechnology innovation

Improving the Bangkok Refugee Learning Center: An Assessment of the Current Program and the Development of a Computer Literacy Course

The Bangkok Refugee Learning Center provides an education for urban refugees who would otherwise not receive one. This project sought to improve the BRLC, primarily by designing a computer literacy course. We conducted experimental classes to revise and improve the curriculum we developed. We produced twelve computer skills lessons and an online resource guide to provide additional educational material. We also provided a set of recommendations for improving the BRLC

Delivering Computer-Based Training Within State Prisons

Internet-connected devices are ubiquitous, and our built environment allows us to tap into formerly impossible solutions. As our world increasingly depends on technology to operate, one demographic cannot gain exposure to internet-connected devices or web-based educational programs: incarcerated individuals. The Department of Justice reports that 5 out of 6 State Prisoners are arrested and returned to prison within nine years of their initial release. Research shows that education is a pathway to reducing the U.S. prison population. Individuals who participated in any educational program are 43 percent less likely to return to prison.1 Prisons in the United States often partner with local organizations to provide job training and certification to incarcerated individuals, but few offer technical-vocational skills. Many programs rely exclusively on a partnership with a local college or lack the knowledge base to teach computer networking. By utilizing Docker containers to provide secure and isolated computerbased training, currently incarcerated individuals can increase their education beyond teacher-led classroom instruction. Providing computer access in prison presents significant security and accessibility challenges. The NIST Risk Management Framework implements proven cyber security access frameworks that help prevent unauthorized use. This study shows that combining robust cyber security frameworks with isolated Docker containers running the ToyNet learning suite helps break the cycle of recidivism among individuals incarcerated across the United States