It is surprising that the prevailing performance taxonomy for scientists (Star versus Non-Star) focuses only on individual output and ignores social behavior since scholars often characterize innovation as a communal process. To address this deficiency, I expand the traditional taxonomy that focuses solely on productivity and add a second, social dimension to the taxonomy of scientists: helpfulness to others. Using a combination of academic paper citations and Impact Factor-weighted publications to measure scientist productivity as well as the receipt of academic paper acknowledgements to measure helpfulness, I classify scientists into four distinct categories of human capital quality: All-Stars, who have both high productivity and helpfulness; Lone Wolves, who have high productivity but average helpfulness; Mavens, who have average productivity but high helpfulness; and Non-Stars, who have both average productivity and helpfulness. The first study examines the impact of 415 immunologists on the performance of their coauthors. Looking at the change in quality-adjusted publishing output of an immunologist's coauthors after the immunologist's death, I find that the productivity of an All-Star's coauthors decreases on average by 35%, a Maven's coauthors by 30% on average, and a Lone Wolf's coauthors by 19%, all relative to the decrease in productivity of a Non-Star's coauthors. These findings suggest that our current conceptualization of star scientists, which solely focuses on individual productivity, is both incomplete and potentially misleading as Lone Wolves may be systematically overvalued and Mavens undervalued. The second study builds upon the first study's finding that Mavens have a large impact on the performance of their coauthors. Using salary disclosures from 2008 at the University of California, I examine the extent to which each star type is compensated differently. While Mavens have a larger impact on the performance of their coauthors than Lone Wolves, Mavens are compensated less, providing preliminary evidence that these performance effects are spillovers. The third study examines the likelihood of an immunologist's mobility as a function of his observable and unobservable human capital. The greater a scientist's productivity (observable to the market), the greater his inter-institution mobility, while the greater a scientist's helpfulness (unobservable to the market), the lower his inter-institution mobility.

It is surprising that the prevailing performance taxonomy for scientists (Star versus Non-Star) focuses only on individual output and ignores social behavior since scholars often characterize innovation as a communal process. To address this deficiency, I expand the traditional taxonomy that focuses solely on productivity and add a second, social dimension to the taxonomy of scientists: helpfulness to others. Using a combination of academic paper citations and Impact Factor-weighted publications to measure scientist productivity as well as the receipt of academic paper acknowledgements to measure helpfulness, I classify scientists into four distinct categories of human capital quality: All-Stars, who have both high productivity and helpfulness; Lone Wolves, who have high productivity but average helpfulness; Mavens, who have average productivity but high helpfulness; and Non-Stars, who have both average productivity and helpfulness. The first study examines the impact of 415 immunologists on the performance of their coauthors. Looking at the change in quality-adjusted publishing output of an immunologist's coauthors after the immunologist's death, I find that the productivity of an All-Star's coauthors decreases on average by 35%, a Maven's coauthors by 30% on average, and a Lone Wolf's coauthors by 19%, all relative to the decrease in productivity of a Non-Star's coauthors. These findings suggest that our current conceptualization of star scientists, which solely focuses on individual productivity, is both incomplete and potentially misleading as Lone Wolves may be systematically overvalued and Mavens undervalued. The second study builds upon the first study's finding that Mavens have a large impact on the performance of their coauthors. Using salary disclosures from 2008 at the University of California, I examine the extent to which each star type is compensated differently. While Mavens have a larger impact on the performance of their coauthors than Lone Wolves, Mavens are compensated less, providing preliminary evidence that these performance effects are spillovers. The third study examines the likelihood of an immunologist's mobility as a function of his observable and unobservable human capital. The greater a scientist's productivity (observable to the market), the greater his inter-institution mobility, while the greater a scientist's helpfulness (unobservable to the market), the lower his inter-institution mobility.

Top researchers and outstanding scientists are an essential source of science-based innovation and regional development. The location pattern and international movements of the scientific elite, are, thus, of fundamental importance. However, despite a growing interest, there is only little empirical evidence about these core issues. Drawing on the results of a world-wide survey of 720 ―star scientists‖ (identified by the number of citations they generated in journals in the ISI databases in the period 1981-2002) this paper seeks to explore the role of islands of innovation in providing employment opportunities for stars. It is shown that US and European islands of innovation and their regional labor markets are at the forefront when it comes to produce (i.e. to educate) and to employ star scientists and to exchange them with other places. Furthermore, the paper provides evidence for the formation of a network among innovative regional labor markets based on international movements of the best and brightest scientific minds. (author´s abstract) / Series: SRE - Discussion Papers