@proceedings {petridis2023anglekindling, title = {AngleKindling: Supporting Journalistic Angle Ideation with Large Language Models}, year = {2023}, doi = {10.1145/3544548.3580907}, url = {https://savvaspetridis.github.io/papers/anglekindling.pdf}, author = {Petridis, Savvas and Diakopoulos, Nicholas and Crowston, Kevin and Hansen, Mark and Henderson, Keren and Jastrzebski, Stan and Nickerson, Jefrey V and Chilton, Lydia B} } @article {2023, title = {Perceived benefits of open data are improving but scientists still lack resources, skills, and rewards}, journal = {Humanities and Social Sciences Communications}, volume = {10}, year = {2023}, month = {Jan-12-2023}, doi = {10.1057/s41599-023-01831-7}, author = {Borycz, Joshua and Olendorf, Robert and Specht, Alison and Grant, Bruce and Crowston, Kevin and Tenopir, Carol and Allard, Suzie and Rice, Natalie M. and Hu, Rachael and Sandusky, Robert J.} } @article {2021, title = {Hybrid intelligence in business networks}, journal = {Electronic Markets}, year = {2021}, month = {Nov-06-2021}, issn = {1019-6781}, doi = {10.1007/s12525-021-00481-4}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/Ebel2021_Article_HybridIntelligenceInBusinessNe.pdf}, author = {Ebel, Philipp and S{\"o}llner, Matthias and Leimeister, Jan Marco and Crowston, Kevin and de Vreede, Gert-Jan} } @article {2020, title = {GitLab: Work where you want, when you want}, journal = {Journal of Organizational Design}, volume = {9}, year = {2020}, month = {2020/11/16}, pages = {23}, abstract = {
GitLab is a software company that works {\textquotedblleft}all remote{\textquotedblright} at the scale of more than 1000 employees located in more than 60 countries. GitLab has no physical office and its employees can work from anywhere they choose. Any step of the organizational life of a GitLab employee (e.g., hiring, onboarding and firing) is performed remotely, except for a yearly companywide gathering. GitLab strongly relies on asynchronous coordination, allowing employees to work anytime they want. After highlighting some of the main practices implemented by GitLab to effectively work all remotely and asynchronously, I asked renowned organizational scientists their thoughts on this interesting case and to question the generalizability of the all remote asynchronous model. Understanding whether and under what conditions this model can succeed can be of guidance for organizational designers that are now considering different remote models in response of the COVID-19 shock and its aftermath.
}, isbn = {2245-408X}, doi = {10.1186/s41469-020-00087-8}, attachments = {https://crowston.syr.edu/sites/crowston.syr.edu/files/s41469-020-00087-8.pdf}, author = {Choudhury, Prithwiraj and Crowston, Kevin and Dahlander, Linus and Minervini, Marco S. and Raghuram, Sumita} } @inbook {2019, title = {Comprehensive collaboration plans: Practical considerations spanning across individual collaborators to institutional supports}, booktitle = {Strategies for Team Science Success}, year = {2019}, pages = {587-611}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {This chapter provides a framework for integrating and applying the principles and strategies for effective team science that are described in this volume. The framework, called Collaboration Planning, aims to guide a deliberative approach to assess and plan for ten key influences on both scientific and collaborative success. These influences range from the initial scientific rationale for a team science approach to the collaboration readiness of participating individuals and institutions to team communication and coordination mechanisms to quality improvement for team functioning. The Collaboration Planning framework guides current or future collaborators through dialogue and planning around each influence. It draws their attention to key issues for consideration related to each influence, and facilitates discussion of how to leverage facilitating factors and plan for, or mitigate, challenges. Decisions are captured in a resulting written document called the Collaboration Plan. The Collaboration Plan summarizes the various ways the team plans to build the foundation for, and support, effective collaboration across the lifespan of the team science initiative. Collaboration Plans can be used in multiple ways. The Plans{\textquoteright} core function is as a roadmap to facilitate effective team formation and functioning. The Plan also can be used for benchmarking or guiding quality improvement-oriented evaluation. Collaboration Plans also can be used to communicate a team{\textquoteright}s likelihood of collaborative success, goals, and needs to a wide variety of audiences, including funders, current and future team members, stakeholders in the team{\textquoteright}s success, and organizational leaders. In addition, they can be used as models to guide future teams in laying the foundation for success.}, isbn = {978-3-030-20990-2}, doi = {10.1007/978-3-030-20992-6_45}, author = {Hall, Kara L. and Vogel, Amanda L. and Crowston, Kevin}, editor = {Hall, Kara L. and Vogel, Amanda L. and Croyle, Robert T.} } @inbook {2017, title = {Lessons Learned from a Decade of FLOSS Data Collection}, booktitle = {Big Data Factories}, year = {2017}, pages = {79 - 100}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, isbn = {978-3-319-59185-8}, issn = {2509-9574}, doi = {10.1007/978-3-319-59186-5}, url = {http://link.springer.com/content/pdf/10.1007/978-3-319-59186-5}, author = {Crowston, Kevin and Squire, Megan}, editor = {Matei, Sorin Adam and Jullien, Nicolas and Goggins, Sean P.} }