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The project mission was to organize a workshop aimed to explore how the US data science community can cooperate with and benefit from collaborations with partners in Serbia and the West Balkan region. The scope included fundamental data science methods and high-impact applications related to big data processing, security and privacy in critical infrastructures, biomedical informatics, and computational archeology. The proposed workshop facilitated closing the gap between data science research in the US and Serbia and the region and brought together data scientists with researchers from disciplines that until recently had little exposure to data science methods, potentially enabling collaborative breakthroughs in those scientific fields. A large fraction of participants from both sides were early career researchers including advanced level graduate students, postdoctoral research associates, and assistant/associate professors within 10 years of obtaining their Ph.D. The participants included a large fraction of female and minority scientists. The workshop objective was achieved by including the following inter-related objectives: (1) Establishing new multidisciplinary international collaborations between data science, mathematics, and sciences that generate big data and require advanced methods; (2) Reinforcing collaboration mechanisms between the NSF and Serbia’s Ministry of Education, Science and Technological Development and organize joint research projects; and (3) Widening the impact of the workshop, by involving researchers and stakeholders from the West Balkan region. The workshop consisted of four tracks, each co-chaired by 3 investigators from the US, Serbia and another West Balkan country. Tangible outcomes from the workshop include a report describing workshop activities for each of four tracks and a proposal recommending research collaboration areas of interest for all parties and determining collaboration mechanisms and programs to facilitate collaboration.
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Stars in Their Constellations: Great Person or Great Team?
Although much attention is accorded to star performers, this paper considers the extent to which stars, themselves, benefit from the contribution of their collaborators (the constellation). By considering stars, constellations, and the synergies between them, we address a key question: To what extent is collaboration performance driven by the great individual or by great constellations? We introduce a novel approach that uses a matching model to uncover the complementarities driving collaboration formation. We use formal value-capture theory to estimate the relative contribution of stars and constellations to joint value creation. Analyzing a sample of academic research collaborations, we document that stars’ relative contribution exceeds that of their constellations in less than 15% of collaborations, although constellations provide a greater relative contribution in 9%. In most collaborations, neither party dominates: Innovation is a collective endeavor driven equally by the star and the constellation. Joint value creation and relative contribution are explained by the subtle interplay between complementarities in joint work and the substitutability of collaborative parties in the market. Joint value creation increases with the strength of complementarities between parties in a match. Relative value creation, and hence dominance, increases with the substitutability of one’s collaborative partner. Interestingly, joint value creation is greatest in collaborations where both stars and constellations offer bundles of rare attributes and where neither the star nor the constellation dominates. This paper was accepted by Olav Sorenson, organizations. Funding: D. Mindruta gratefully acknowledges funding from the HEC Foundation and from the French National Research Agency (ANR) “Investissements d’Avenir” (LabEx Ecodec/ANR-11-LABX-0047). J. Bercovitz and M. Feldman gratefully acknowledge funding from the Science of Science Approach to Analyzing and Innovating the Biomedical Research Enterprise (SCISIPBIO) program of the U.S. National Science Foundation (NSF) [Grant 1934875]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2021.01969 .
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- Award ID(s):
- 1935023
- PAR ID:
- 10557938
- Publisher / Repository:
- Informs
- Date Published:
- Journal Name:
- Management Science
- ISSN:
- 0025-1909
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1287/mnsc.2021.01969
