Processes and Technologies for Small and Large Team Collaboration Minitrack

Permanent URI for this collection

https://hdl.handle.net/10125/42304

The "Processes and technologies for small and large team collaboration" minitrack focuses on:

Theoretical foundations and design methodologies for collaborative work practices and technologies
Processes and tools for establishing and maintaining shared focus and shared mental models over time
Processes, technologies, and theoretical breakthroughs to improve and speed up shared sense-making
Process and technologies for rapid, collaborative decision-making during crisis
Methods and technologies for eliciting and capturing tacit knowledge from experts (i.e., externalization) and sharing/incorporating that knowledge into collaborative efforts (i.e., team internalization)
Human collaboration with artificial agents and the evaluation of computer systems as team members, including agent-based support for individual decision makers
Automation of collaborative processes and agent-based support for group facilitation
Facilitation methods, techniques, patterns, and procedures to improve (a)synchronous collaboration between co-located and distributed people, teams, or groups
Assessment models and methods for team collaboration and performance
Design, codification and reuse of work practices and pattern languages for group collaboration

Minitrack Co-Chairs:

Douglas C. Derrick (Primary Contact)
University of Nebraska at Omaha
Email: dcderrick@unomaha.edu

Joel H. Helquist
Utah Valley University
Email: joel.helquist@uvu.edu

Christopher B. R. Diller
University of Arizona Eller
Email: cdiller@unomaha.edu

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Now showing 1 - 7 of 7

Theoretical Fashions in Crowdsourcing: A Snapshot of IS Research
(2017-01-04) Tripathi, Abhishek; Tahmasbi, Nargess; de Vreede, Gert-Jan
When new information technologies emerge, they stimulate the curiosity of Information System (IS) research and practice. Research and practices regarding emerging technologies can be characterized as IS fashions, which can lead to IS innovations. Yet, researchers and practitioners often wonder if these fashions are the next big thing or just a passing fad. One way to determine the contribution of a scientific fashion is to understand its theoretical state and maturity as reported in the literature. We performed a theoretical assessment of one specific IS fashion: crowdsourcing. The main objective of our research is to understand the characteristics of theories in crowdsourcing research and to determine the origins of these theories. Using Gregor’s (2006) taxonomy, we performed a systematic literature review to identify and categorize the type of theories developed and used in crowdsourcing research. Close to forty percent of the surveyed articles are explanatory in nature, focusing on cause and effects relationships. Most articles use established theories to motivate research questions or hypotheses. Least common is theoretical research to motivate the design of crowdsourcing related artifacts.
Peer-reviewed Brainstorming to Facilitate Large Group Collaboration
(2017-01-04) Helquist, Joel; Kruse, John; Diller, Christopher
This paper examines the impact of peer-reviewed brainstorming on the quality of brainstorming ideas. Peer-reviewed brainstorming aims to improve the quality of the brainstorming ideas and reduce the number of noisy comments. A pilot study was conducted that compared traditional, free brainstorming to a peer-reviewed brainstorming process, which requires each idea to be reviewed and edited by peers. The peer-review process did reduce the number of low quality ideas. This process was also rated higher in satisfaction ratings than traditional brainstorming.
Examining Collaboration among Student Teams relying on Web Applications to Coordinate Software Development
(2017-01-04) Boyd, Brian; Townsley, Ayden; Walter, Charles; Johnson, Callen; Gamble, Rose
Training students in software engineering should attempt to mimic industry practices. Thus, student teams develop non-trivial software products, which includes interacting with collaborative tools deployed as web applications. The interaction may be mechanistic or organic, and occur for different durations. Collaboration studies tightly control these factors, relying on manual activity logging, very specific software requirements, surveys and interviews. Since these tools allow simultaneous interaction and capture revision histories, collaboration may be more objectively measured. This paper investigates social media conversations, revision histories, and commit logs from undergraduate student teams performing software development. The objective is to examine how this form of data could be translated into collaborative activities and whether the same performance relationships are achieved in a class setting. A small pilot study shows that the translation methodology did not produce the exact relationships from other studies, but it does shed light on a team’s perception of collaborators.
Convergence on Self-Generated vs. Crowdsourced Ideas in Crisis Response: Comparing Social Exchange Processes and Satisfaction with Process
(2017-01-04) Seeber, Isabella; Merz, Alexander; De Vreede, Gert-Jan; Maier, Ronald; Weber, Barbara
Social media allow crowds to generate many ideas to swiftly respond to events like crises, public policy discourse, or online town hall meetings. This allows organizations and governments to harness the innovative power of the crowd. As part of this setting, teams that process crowd ideas must engage in social exchange processes to converge on a few promising ideas. Traditionally, teams work on self-generated ideas. However, in a crowdsourcing scenario, such as public participation in crisis response, teams may have to process crowd-generated ideas. To better understand this new practice, it is important to investigate how converging on crowdsourced ideas affects the social exchange processes of teams and resulting outcomes. We conducted a laboratory experiment in which small teams working in a crisis response setting converged on self-generated or crowdsourced ideas in an emergency response context. Our findings suggest that teams converging on self-generated ideas have better social exchange processes in terms of dominance and coordination. We found support that evaluation and coordination positively affect team member satisfaction under both experimental conditions. Implications for research and practice are discussed.
Collaborative Distance: Multi-level Analysis Framework for Recommending Structure and Safeguards
(2017-01-04) Derrick, Douglas; Ligon, Gina; Lundmark, Leif; Pleggenkuhle-Miles, Erin; Elson, J S
We developed a framework that assists in capturing the differences between two organizations. Collaborative distance captures the degree of similarity between the cooperating organizations across four separate levels of analysis: sector, organization, functional, and individual. Organizations that are very similar to each other are said to have “low collaborative distance” and organizations that differ on important characteristics are said to have “high collaborative distance”. We propose that this measure coupled with problem complexity ought to dictate the structure and safeguards for inter-organizational collaboration. We show a sample calculation of this measure. \
Collaboration Engineering Methodology: Horizontal Extension to Accommodate Project and Program Concerns
(2017-01-04) Randrup, Nils L.; Briggs, Robert R.
A Collaboration Engineering Methodology (CEM) comprises a set of defined, standardized, documented, and discoverable objectives, deliverables, key actions, tools/templates, principles and policies for establishing effective, efficient, satisfying collaborative work practices for high-value organizational tasks. First-generation CEMs address design and development CE solutions. Existing CEMs, though, focus on the design/build phase, but lack the pre-design and post-build elements that are common to methodologies for adjacent disciplines. We use Design Science Research to situate existing design/build CEMs in the larger context of CE programs and projects. We develop and validate an extended CEM in four phases: 1) Opportunity Assessment, 2) Development, 3) Deployment, and 4) Improvement (ODDI). Phase 1 concerns CE portfolio management and CE project planning; Phase 2 encapsulates existing design/build CEMs; Phase 3 concerns roll-out planning, change management, and implementation; Phase 4 concerns continuous optimization of a deployed work practice. The ODDI model advances CE another step towards becoming a fully realized professional practice, but more research is still required to derive a complete a design theory for CE.
Introduction to Processes and Technologies for Small and Large Team Collaboration Minitrack
(2017-01-04) Derrick, Douglas; Helquist, Joel; Diller, Chistopher

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