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on Sociology of Economics |
| By: | Jian Wang; Reinhilde Veugelers; Paula Stephan |
| Abstract: | Research which explores unchartered waters has a high potential for major impact but also carries a higher uncertainty of having impact. Such explorative research is often described as taking a novel approach. This study examines the complex relationship between pursuing a novel approach and impact. Viewing scientific research as a combinatorial process, we measure novelty in science by examining whether a published paper makes first time ever combinations of referenced journals, taking into account the difficulty of making such combinations. We apply this newly developed measure of novelty to all Web of Science research articles published in 2001 across all scientific disciplines. We find that highly novel papers, defined to be those that make more (distant) new combinations, deliver high gains to science: they are more likely to be a top 1% highly cited paper in the long run, to inspire follow on highly cited research, and to be cited in a broader set of disciplines. At the same time, novel research is also more risky, reflected by a higher variance in its citation performance. In addition, we find that novel research is significantly more highly cited in “foreign” fields but not in its “home” field. We also find strong evidence of delayed recognition of novel papers and that novel papers are less likely to be top cited when using a short time window. Finally, novel papers typically are published in journals with a lower than expected Impact Factor. These findings suggest that science policy, in particular funding decisions which rely on traditional bibliometric indicators based on short-term direct citation counts and Journal Impact Factors, may be biased against “high risk/high gain” novel research. The findings also caution against a mono-disciplinary approach in peer review to assess the true value of novel research. |
| JEL: | I23 O31 O33 O38 |
| Date: | 2016–04 |
| URL: | http://d.repec.org/n?u=RePEc:nbr:nberwo:22180&r=sog |
| By: | Benedikt Fecher; Mathis Fräßdorf; Gert G. Wagner |
| Abstract: | We live in a time of increasing publication rates and specialization of scientific disciplines. More and more, the research community is facing the challenge of assuring the quality of research and maintaining trust in the scientific enterprise. Replication studies are necessary to detect erroneous research. Thus, the replicability of research is considered a hallmark of good scientific practice and it has lately become a key concern for research communities and science policy makers alike. In this case study we analyze perceptions and practices regarding replication studies in the social and behavioral sciences. Our analyses are based on a survey of almost 300 researchers that use data from the German Socio-Economic Panel Study (SOEP), a multidisciplinary longitudinal multi-cohort study. We find that more than two thirds of respondents disagree with the statement that replications are not worthwhile, because major mistakes will be found at some point anyway. Nevertheless, most respondents are not willing to spend their time to conduct replication studies. This situation can be characterized as a “tragedy of the commons”: everybody knows that replications are useful, but almost everybody counts on others to conduct them. Our most important finding concerning practical consequences is that among the few replications that are reported, a large majority is conducted in the context of teaching. In our view, this is a promising detail: in order to foster replicability, one avenue may be to make replication studies a mandatory part of curricula as well as of doctoral theses. Furthermore, we argue that replication studies need to be more attractive for researchers. For example, successful replications could be listed in the publication lists of replicated authors. Vice versa, data sharing needs to receive more recognition, for example by considering data production and subsequent data sharing as scientific output. |
| Date: | 2016 |
| URL: | http://d.repec.org/n?u=RePEc:diw:diwsop:diw_sp839&r=sog |
| By: | Christian Catalini; Christian Fons-Rosen; Patrick Gaulé |
| Abstract: | We test how a reduction in travel cost affects the rate and direction of scientific research. Using a fine-grained, scientist-level dataset within chemistry (1991-2012), we find that after Southwest Airlines enters a new route, scientific collaboration increases by 50%, an effect that is magnified when weighting output by quality. The benefits from the lower fares, however, are not uniform across scientist types: younger scientists and scientists that are more productive than their local peers respond the most. Thus, cheaper flights, by reducing frictions otherwise induced by geography and allowing for additional face-to-face interactions, seem to enable better matches over distance. |
| Keywords: | scientific collaboration, air travel, temporary co-location, face-to-face meetings |
| JEL: | R4 L93 |
| Date: | 2016–04 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:898&r=sog |
| By: | Fecher, Benedikt (DIW Berlin); Wagner, Gert G. (DIW Berlin) |
| Abstract: | In the New England Journal of Medicine, Longo and Drazen critically assessed the concept of data sharing. Their main concern is that a "new class of research person will emerge" that uses data, which were gathered by other researchers, for their own original research questions. The authors referred to this class of researcher as "research parasites". Longo and Drazen are right when they note that scientific data sharing deserves more recognition. However, they indicate that the most adequate form of recognition for data sharing is coauthorship. They suggest to work "symbiotically, rather than parasitically, with the investigators holding the data, moving the field forward in a way that neither group could have done on its own." Although this is true in particular cases, co-authorship as the sole instrument of credit will unnecessarily restrict the potential of data sharing. More suitable instruments for giving credit where credit is due would be a much greater appreciation of data sharing by research communities by introducing citations of data sets, bestowing awards for good datasets, and considering data "production" when assessing scientists' career prospects, funding applications, and research outputs. |
| Keywords: | data sharing, incentives, rewards, organism, culture |
| JEL: | B40 C80 Z11 |
| Date: | 2016–04 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp9895&r=sog |