Conflict is a substantial, pervasive activity in team collaboration. It may arise because of differences in goals, differences in ways of working, or interpersonal dissonance. The specific focus for this research is the conflict in distributed teams. As opposed to traditional teams, participants of distributed teams are geographically dispersed and rely heavily on computer-mediated communication. Understanding and managing conflict is a crucial task in these settings because it is at the crux of many other managerial issues (e.g., trust, leadership, and knowledge transfer). Conflict in distributed teams hides in asynchronous communication among team members. While this causes extra burdens in detecting and understanding conflict, it also makes it possible to rebuild conflict scenarios for the purpose of making sense of, and managing conflict in these teams. The objectives of this study are to make progress toward an initial design theory in the form of a novel conflict detection and analysis approach; to implement a faithful instantiation of this evolving theory; and to employ it to gain insight about the conflict phenomenon in the new setting. The work is organized and reported in three essays. Essay 1 develops a meta design of the approach (CM2) and describes its implementation as a novel conflict management system. The design builts on a new construct--the Vignette (vivid yet analytical, theory-laden descriptions of past experiences)--that describes conflict situations. A meta-model developed on basis of prior kernel theories underpins the conflict vignettes (the proposed conflict management approach) and CM2 (the implementation). The essay also describes an initial empirical pilot investigation that serves as the impetus for the study, and demonstrates the anticipated use of CM2 with a detailed use scenario. Essay 2 is aimed at automating the process of extracting conflict information from computer-mediated communication (CMC) data, such as emails and instant messages. The work focuses on the basic action in conflict--argument--and develops an automatic argument detection solution. Drawing on the argumentation theory, I propose a model for argument detection composed of features that reflect five categories of argumentation functions including: announcement; reasoning; modality; transition; and, affect, along with another set of language features that are informative for recognizing arguments. The evaluation results show that the model achieves higher accuracy and recall in detecting arguments in message sets compared to baseline models. Essay 3 extends prior design efforts to explore the conflict phenomenon in distributed settings. The work creates instruments to measure conflict elements as specified in the meta model and based on automatically detected argument information. Following a grounded theory approach, I employ the instruments to analyze 23,094 conflict situations in Bugzilla, an open source software development community. The analysis results reveal patterns associated with the occurrence of conflict, participants and their behaviors, and the temporal evolution of conflict. I then interpret these findings with the help of prior work to develop theoretical propositions that explain conflict in crowd collaboration settings that can provide directions for future research. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]