Henry Sauermann

Increasing web survey response rates in innovation research: An experimental study of static and dynamic contact design features

Web surveys have become increasingly central to innovation research but often suffer from low response rates. Based on a cost–benefits framework and the explicit consideration of heterogeneity across respondents, we consider the effects of key contact design features such as personalization, incentives, and the exact timing of survey contacts on web survey response rates. We also consider the benefits of a “dynamic strategy”, i.e., the approach to change features of survey contacts over the survey life cycle. We explore these effects experimentally using a career survey sent to over 24,000 junior scientists and engineers. The results show that personalization increases the odds of responding by as much as 48%, while lottery incentives with a high payoff and a low chance of winning increase the odds of responding by 30%. Furthermore, changing the wording of reminders over the survey life cycle increases the odds of a response by over 30%, while changes in contact timing (day of the week or hour of the day) did not have significant benefits. Improvements in response rates did not come at the expense of lower data quality. Our results provide novel insights into web survey response behavior and suggest useful tools for innovation researchers seeking to increase survey participation.

Conflicting Logics? A Multidimensional View of Industrial and Academic Science

A growing body of research views industrial and academic science as characterized by conflicting institutional logics. However, other scholars have long claimed that stark differences between the two sectors exist in theory but not in practice. Drawing on both views and the broader organizational literature, we develop a conceptual framework to compare and contrast industrial and academic science along four interdependent dimensions: 1 the nature of work, 2 characteristics of the workplace, 3 characteristics of workers, and 4 the disclosure of research results. We then employ detailed survey data on a sample of more than 5,000 research-active life scientists and physical scientists to examine key aspects of the framework empirically. Our results suggest that the conflicting logics view tends to overstate differences across sectors while ignoring important heterogeneity within sectors. We further advance the understanding of institutional logics by examining the relationships among dimensions of science, including the degree to which differences in the nature of work explain differences in how work is organized and results are disclosed. We discuss directions for future research on the institution of science as well as implications for managers and policy makers concerned with scientific activity within and across sectors.

Crowd Science User Contribution Patterns and Their Implications

Significance Involving the public in research may provide considerable benefits for the progress of science. However, the sustainability of “crowd science” approaches depends on the degree to which members of the public are interested and provide continued labor inputs. We describe and compare contribution patterns in multiple projects using a range of measures. We show that effort contributions can be significant in magnitude and speed, but we also identify several challenges. In addition, we explore some of the underlying dynamics and mechanisms. As such, we provide quantitative evidence that is useful for scientists who consider adopting crowd science approaches and for scholars studying crowd-based knowledge production. Our results also inform current policy discussions regarding the organization of scientific research. Scientific research performed with the involvement of the broader public (the crowd) attracts increasing attention from scientists and policy makers. A key premise is that project organizers may be able to draw on underused human resources to advance research at relatively low cost. Despite a growing number of examples, systematic research on the effort contributions volunteers are willing to make to crowd science projects is lacking. Analyzing data on seven different projects, we quantify the financial value volunteers can bring by comparing their unpaid contributions with counterfactual costs in traditional or online labor markets. The volume of total contributions is substantial, although some projects are much more successful in attracting effort than others. Moreover, contributions received by projects are very uneven across time—a tendency toward declining activity is interrupted by spikes typically resulting from outreach efforts or media attention. Analyzing user-level data, we find that most contributors participate only once and with little effort, leaving a relatively small share of users who return responsible for most of the work. Although top contributor status is earned primarily through higher levels of effort, top contributors also tend to work faster. This speed advantage develops over multiple sessions, suggesting that it reflects learning rather than inherent differences in skills. Our findings inform recent discussions about potential benefits from crowd science, suggest that involving the crowd may be more effective for some kinds of projects than others, provide guidance for project managers, and raise important questions for future research.

Credit where credit is due? The impact of project contributions and social factors on authorship and inventorship

We examine the extent to which different types of substantive project contributions as well as social factors predict whether a scientist is named as author on a paper and inventor on a patent resulting from the same project. Using unique survey data from over 2000 life scientists, we find that the predictors of authorship differ from those of inventorship. A wider range of project contributions may result in authorship, and social factors appear to play a larger role in authorship decisions than in inventorship decisions. We also find evidence that project contributions and social factors interact in predicting authorship, suggesting that the two sets of factors should be considered jointly rather than seen as independent determinants of attribution. In addition to providing novel insights into the functioning of the authorship and inventorship system, our results have important implications for administrators, managers, and policy makers, as well as for innovation scholars who often rely on patents and publications as measures of scientists’ performance.

Not All Scientists Pay to Be Scientists: PhDs’ Preferences for Publishing in Industrial Employment

It is often assumed that academically trained scientists have a strong taste for science and are willing to “pay” for the ability to openly disclose their research results. However, little is known regarding how scientists considering jobs in industrial R&D make trade-offs between positions that allow publishing on the one hand and positions that do not allow publishing but offer higher pay on the other. Using data on over 1900 science and engineering PhD candidates about to enter the job market, we find that while some are unwilling to give up publishing at virtually any price, over one third of those most likely to seek positions in industrial research are willing to forego publishing for free. We develop a simple model of the “price” scientists assign to publishing in firms and explore potential sources of heterogeneity empirically. We find that the price of publishing increases with individuals’ preferences for various benefits from publishing such as peer recognition and contributing to society, but it decreases with their preference for money. Scientists who believe themselves to be of high ability and who train at top tier institutions have a higher price of publishing. Yet, they are more expensive to hire (not less) even if publishing is allowed. We discuss implications for research on the economics of science and on compensating differentials, for managers seeking to attract and retain academically trained personnel, and for firms considering their participation in open science.

Why pursue the postdoc path

Complex, diverse rationales require nuanced policies Concerns have been raised about labor market imbalances that see a growing number of postdoctoral researchers pursuing a limited number of faculty positions (1–4). Proposed demand-side solutions include capping the duration of postdoc training or hiring more permanent staff scientists (1, 4, 5). Others focus on the supply side, arguing that Ph.D.s need better information about labor market conditions and nonacademic career options (4, 6, 7). Unfortunately, it is not clear why Ph.D. students pursue postdoc positions and how their plans depend on individual-level factors, such as career goals or labor market perceptions. We describe evidence of a “default” postdoc and of “holding patterns” that suggest a need for increased attention to career planning among students, their mentors, graduate schools, and funders.

The declining interest in an academic career

There is increasing evidence that science & engineering PhD students lose interest in an academic career over the course of graduate training. It is not clear, however, whether this decline reflects students being discouraged from pursuing an academic career by the challenges of obtaining a faculty job or whether it reflects more fundamental changes in students’ career goals for reasons other than the academic labor market. We examine this question using a longitudinal survey that follows a cohort of PhD students from 39 U.S. research universities over the course of graduate training to document changes in career preferences and to explore potential drivers of such changes. We report two main results. First, although the vast majority of students start the PhD interested in an academic research career, over time 55% of all students remain interested while 25% lose interest entirely. In addition, 15% of all students were never interested in an academic career during their PhD program, while 5% become more interested. Thus, the declining interest in an academic career is not a general phenomenon across all PhD students, but rather reflects a divergence between those students who remain highly interested in an academic career and other students who are no longer interested in one. Second, we show that the decline we observe is not driven by expectations of academic job availability, nor by related factors such as postdoctoral requirements or the availability of research funding. Instead, the decline appears partly due to the misalignment between students’ changing preferences for specific job attributes on the one hand, and the nature of the academic research career itself on the other. Changes in students’ perceptions of their own research ability also play a role, while publications do not. We discuss implications for scientific labor markets, PhD career development programs, and science policy.

Authorship and contribution disclosures

What do contribution statements on articles tell us that author order does not—and how can they be improved? Most scientific research is performed by teams, and for a long time, observers have inferred individual team members’ contributions by interpreting author order on published articles. In response to increasing concerns about this approach, journals are adopting policies that require the disclosure of individual authors’ contributions. However, it is not clear whether and how these disclosures improve upon the conventional approach. Moreover, there is little evidence on how contribution statements are written and how they are used by readers. We begin to address these questions in two studies. Guided by a conceptual model, Study 1 examines the relationship between author order and contribution statements on more than 12,000 articles to understand what information is provided by each. This analysis quantifies the risk of error when inferring contributions from author order and shows how this risk increases with team size and for certain types of authors. At the same time, the analysis suggests that some components of the value of contributions are reflected in author order but not in currently used contribution statements. Complementing the bibliometric analysis, Study 2 analyzes survey data from more than 6000 corresponding authors to examine how contribution statements are written and used. This analysis highlights important differences between fields and between senior versus junior scientists, as well as strongly diverging views about the benefits and limitations of contribution statements. On the basis of both studies, we highlight important avenues for future research and consider implications for a broad range of stakeholders.

Fire in the Belly? Employee Motives and Innovative Performance in Startups versus Established Firms

Scholars have long sought to understand the advantages different types of firms may have in generating innovation. A popular notion is that startup companies are able to attract employees with “fire in the belly,” allowing them to be more productive. Yet research has paid little attention to the motives and incentives of startup employees. This paper compares startup employees’ pecuniary and non-pecuniary motives with those of employees working in small and large established firms and examines the extent to which existing differences in motives distinguish employees’ innovative performance. Using data on over 10,000 U.S. R&D employees, we find significant differences across firm types with respect to motives, although these differences are more nuanced than commonly thought. We also observe that startup employees have higher patent output, an effect that is associated primarily with firm age, not size. Moreover, we find evidence that differences in employee motives may indeed be an important factor distinguishing the innovative performance in startups versus established firms. Rather than intrinsic motives or the quest for money, however, it is employees’ willingness to bear risk that appears to play the most important role. We discuss implications for future research as well as for entrepreneurs, managers, and policy makers.

Educational Mismatch, Work Outcomes, and Entry Into Entrepreneurship

A growing body of research explores how employees’ organizational context shapes their entrepreneurial activity. We add to this work by examining how “educational mismatch”—when a job does not utilize the skills an employee has acquired during education—relates to subsequent transitions into entrepreneurship. While prior research has focused on mismatch due to labor market frictions, workers may also enter mismatches for other reasons, such as family obligations or a change in career interests. Different reasons, in turn, may relate in distinct ways to wages and job satisfaction and thus to the opportunity costs of entering entrepreneurship. Moreover, mismatch may also affect human capital development, including the formation of a broader range of skills that is beneficial in entrepreneurship. Using longitudinal data from over 25,000 scientists and engineers, we document a broad range of reasons for educational mismatch and show that the relationships between educational mismatch and wages, job satisfaction, and skill variety differ significantly depending upon the reason for a mismatch. Mismatched individuals are more likely to enter into entrepreneurship in a subsequent period, an effect that goes beyond higher labor mobility per se. Both lower opportunity costs—primarily low job satisfaction—and greater skill variety appear to link educational mismatch to subsequent entrepreneurship. We discuss implications for research, managers, and policy makers.