The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research

Abstract

We conceptualize mechanisms that explain how social uses of media technologies, especially online platforms and crowds, reproduce, or modify inequalities, and explore these in the context of the crowdfunding of science. We distinguish between “supply side” factors related to the ability of actors given their institutional standing to use this funding approach, and “demand side” factors related to the crowd’s sensitivity to the institutional standing of those actors. We collected data on scientists requesting funding for their studies on Experiment.com , arguably the most popular scientific crowdfunding platform, and investigated the factors contributing to initiation and success. Supply side factors were important: crowdfunding appeals tended to come from scientists affiliated with larger, wealthier, and more active and prestigious institutions. However, demand side factors were not as important at the institutional level. Crowdfunding projects’ success was not predicted by the institution’s status, but rather by the number of appeals from an institution.

Keywords

crowdfunding knowledge industries inequality media and science science and economics

1. Introduction

The production of knowledge, in science and technology, literature, and popular culture could be conceptualized as a process of selection. Many knowledge creators have embryonic ideas, large numbers of them carry promise, but only a few come to fruition. In all these fields, the selection favors socially, symbolically, or economically stronger actors.

For decades, media scholars have been debating the role of communication technologies in knowledge production, consumption and acquisition (e.g. Donohue et al., 1975; Pool, 1983), and more specifically the extent to which technology weakens or intensifies the existence of social hierarchies in this domain. More recently, online platforms have become a key technological infrastructure connecting two or more sides of a transaction (Srnicek, 2017). Some have argued that the rise to prominence of a small set of online commercial platforms has constrained competition (Benkler, 2016; Khan, 2016), while others suggest that the impact of platforms is complex sometimes aiding already large prominent actors and other times aiding less well-known actors to succeed in the marketplace (Greve and Song, 2017). Common to the platform literature is the understanding that online platforms have meaningful political implications (Gillespie, 2015). In this article, we turn the spotlight on two sides of selection processes that involve online platforms and crowds: The “supply side” factors relate to the tendency of economically or socially stronger actors to seek and successfully secure resources necessary to fulfill their ideas and talents. The “demand side” factors relate to the preferences of the crowd. Online platforms and crowds could potentially play a role on both sides of the process, by lowering entry barriers on the supply and by allowing audience preferences to independently express themselves on the demand side, with less centralized gatekeeping. In this article, we examine the role of supply and demand factors in the context of the crowdfunding of scientific research.

Crowdfunding is a novel distributed online approach for raising finance for diverse types of endeavors and initiatives (Younkin and Kashkooli, 2016). Popular discourse regarding crowdfunding (Grant, 2014) has echoed optimistic assessments of the egalitarian impact of digital distributed technologies (Benkler, 2006) but some studies have found that social and geographic barriers are also evident in crowdfunding (Davidson & Poor, 2015, 2018; Mollick, 2014). In this study, we distinguish between supply and demand barriers and their operation in the crowdfunding of scientific research. We focus on the funding of science given that, unlike in realms such as artistic production, in which the reputation of contemporary producers is extremely fluid, and sometimes domain-specific (Becker, 2008), in the academic realm ranking is well defined, both institutionally and individually (Bourdieu, 1975).

The remainder of the article is organized as follows: We first consider the role of status in shaping supply and demand in general. We then turn to evidence of the operation of status in the traditional funding of science, and in crowdfunding. Based on this evidence, we generate and test a hypothesis and pose as well as answer research questions regarding the role of status in shaping the supply of scientific crowdfunding projects and the crowd’s demand for them on Experiment.com , the leading science-focused crowdfunding platform. We conclude the article with a discussion of the findings with a particular emphasis on the role of supply and demand side factors in the effects of technology on the allocation of resources in science and beyond.

2. Literature review

2.1. Supply and demand factors in the selection of knowledge products

The tendency of economically or socially stronger actors to seek and successfully secure resources necessary to fulfill their ideas and talents may stem from a variety of reasons. On the supply side, children of affluent parents receive material support that allows them to persist in their chosen occupation even if at first it is not especially lucrative (Friedman et al., 2016). In addition, some middle-class children are also exposed by their parents to diverse forms of culture and encouraged to engage in cultural pursuits. These, in turn, aid them in securing employment in creative occupations in which employers have similar diverse cultural tastes (Koppman, 2015). Furthermore, access to digital media technologies which is socio-economically stratified may be tied to the “propensity to engage in entrepreneurial activity” and is ultimately linked to achieving more financial success (Robinson et al., 2015: 575).

Demand side reasons for the success of high-status actors—“superstars” (Rosen, 1983)—in securing resources relate to the fact that familiarity and reputation are associated with risk reductions in business, sports, entertainment and many other domains. So, for example, when large Hollywood studios decide to fund projects offered by accomplished screenwriters and directors, the risk is lower based on the assumption that audience demand for the work of the acclaimed and well-known writer or directors will be high. Similarly, art work valuations are pegged to an artist’s track record and the identity of their associated galleries (Velthuis, 2005).

2.2. Science and institutional stratification

As in other domains (e.g. popular culture—Rosen, 1983), scientific resources such as research grants have traditionally tended to accumulate in the hands of a small minority of the scientific community. Such a “‘Matthew effect’ consists in the accruing of greater increments of recognition for particular scientific contributions to scientists of considerable repute and the withholding of such recognition from scientists who have not yet made their mark” (Merton, 1968: 58). Out of 562 American research institutions that report any federal research funding (The Center for Measuring University Performance, 2018), only 60 elite universities (10.7% of the 562 research institutions described above) accounted for 59% of all federal funding of research and development in universities (Association of American Universities, 2015).

The reasons for this concentration are linked both to supply and demand. On the supply side, start-up funding from well-endowed universities enables researchers to carry out pilot studies demonstrating the merit of their ideas. Such universities are also more likely to adopt new media technologies (Stephan, 2012) which are especially relevant to scientific crowdfunding given its dependence on the efficient production and distribution of well-crafted online messages (Wheat et al., 2013).

On the demand side, which has attracted more research attention, peer-reviews of grant proposals evaluate more positively proposals that include such preliminary evidence (Stephan, 2012). In interactions within grant-review panels, faculty affiliated with elite institutions might enjoy more influence and might take institutional affiliation into account in their grant evaluations (Lamont, 2009: 147). There is some evidence that the institutional affiliation of manuscript submitters or grant applicants impacts peer-review decisions although the evidence is not conclusive (Bornmann, 2011). Referees tend to judge scientific projects according to their own intellectual habitus and grant panelists tend to prefer research familiar to them from their own professional networks. As a result, the process “is perceived to be biased against daring and innovative research” (Lamont, 2009: 241). In other words, there is some evidence that peer-review as an expression of professional scientific demand for research is guided by status.

We wish to examine whether, when appealing to the public through crowdfunding rather than to dedicated institutional mechanisms controlled by the scientific establishment, status shapes the supply of crowdfunding projects and the public demand projects enjoy as reflected in the funding projects attract.

2.3. Hierarchies in crowdfunding

We turn now to research that has touched whether obliquely or more directly on the role of status in shaping the supply of crowdfunding projects or the public’s demand for such projects. A large portion of the multi-disciplinary literature focused on crowdfunding since its emergence, slightly more than a decade ago, has attempted to understand and identify the project attributes that predict funding success, often as a means of enunciating best practices for crowdfunding founders rather than as a means of building or testing theory (e.g. Frydrych et al., 2014; Mollick, 2014). On the supply side, the advantages enjoyed by producers located in large cultural hubs, where social norms legitimize cultural work as a worthwhile pursuit, and the talent and knowledge needed to develop creative projects is abundant (Currid, 2007; Scott, 2014), could also advantage producers who wish to crowdfund their project. Furthermore, there is evidence that platforms enhance such geographic advantage by selectively promoting centrally located projects more than projects located in the periphery (Davidson and Poor, 2018). Crowdfunding scientists noted in research interviews the central importance of effectively using various media channels to communicate the project with the public (Hui and Gerber, 2015). The facilities and skill sets needed to use these channels well might be more common in more prestigious universities that have the funds to invest (for example) in studios, video editing software and personnel mastering the art of producing an appealing pitch. On the demand side, some studies have focused on the importance of social ties both offline and online, and more generally on the existence of a community as a requirement for crowdfunding success. Such studies have generally found that many founders rely on existing friends and family for funding (Davidson and Poor, 2015; Hui et al., 2014; Hui and Gerber, 2015; Muller et al., 2016; Wang, 2016). Hence, the role of social hierarchies in crowdfunding has been identified indirectly as the reliance on friends and family signals that those from more affluent backgrounds might be more likely to financially benefit from links to affluent close others.¹

When taken as a whole, the results of more direct tests of how status might impact crowdfunding decisions are mixed. Scholars have found that the racial identity of entrepreneurs is related to their ability to raise funding from the crowd even when controlling for pitch quality (Younkin and Kuppuswamy, 2017) suggesting that the funding public is also sensitive to identity cues. In an analysis of an Australian equity crowdfunding platform, the proportion of directors with an MBA degree on a firm’s board, an indicator of status, was positively related to success (Ahlers et al., 2015).

Turning to gender, women enjoy more crowdfunding success than men. This success seems to be related to the support they receive from activist female funders who perceive female entrepreneurs to be under-represented (Greenberg and Mollick, 2015). Similarly, an analysis of scientific crowdfunding found that “women have higher odds of reaching their funding goal than men” (Sauermann et al., 2018: 13). In the related field of social lending, the better the credit grade a potential borrower has the higher the likelihood that amateur lenders will lend them the funds they request (Hildebrand et al., 2016). This suggests that when a crowdfunding platform provides a very clear signal of status (unavailable in many crowdfunding contexts), the crowd pays attention to this signal.

However, a comparison of the spatial dispersion of venture capital investment and successful crowdfunding in the United States found that successful crowdfunding projects tend to be more dispersed and located outside cultural hubs (as well as inside them) suggesting on the supply side that the crowd does relax some status-related constraints (Sorenson et al., 2016). Furthermore, a comparison of expert judges to the crowd found that the crowd supported the funding of more diverse theatrical projects than the experts did (Mollick and Nanda, 2015) suggesting that the importance of status is lower in crowdfunding than in traditional funding mechanisms.

In the specific case of the crowdfunding of science, an exploratory discussion of crowdfunding in the natural sciences argued that scientific projects need not focus on charismatic topics, and that it is the efforts scientists make to promote their crowdfunding project which will drive success or failure (Wheat et al., 2013). A study of scientific projects on a number of platforms found that academic ranking was not significantly related to crowdfunding success (Schäfer et al., 2016). A recent extensive analysis of individual level factors predicting crowdfunding success on the particular platform, we also study here, found that junior scholars enjoy more crowdfunding success than senior scholars (Sauermann et al., 2018). An interview-based study of scientists with crowdfunding experience suggested “scientists are judged less on their reputation” (Hui and Gerber, 2015: 38) when they crowdfund in comparison to when they apply for traditional grant funding. Given the mixed findings we will ask to what extent are crowd preferences related to the academic rank of project initiators and the status of the institution with which they are affiliated.

3. Hypothesis and research questions

General evidence of the “intergenerational gifting of capital” (Friedman et al., 2016: 9) in the culture industries, and evidence of the economic and cultural advantages researchers in elite institutions enjoy are manifested in academia in the start-up funds and light course loads of young faculty in well-funded research institutions. In turn, these advantages allow them to devote time to research and grant writing. Such a dynamic is consistent with initial findings suggesting status shapes the supply of crowdfunding projects. Similarly to the way parents in creative occupations expose their children to diverse cultural experiences (Koppman, 2015), the cultural emphasis in elite research institutions on grant seeking as an indicator of academic excellence as well as the intellectual infrastructure (e.g. students, mentors, training) provide an intellectual advantage to scholars in elite institutions. Furthermore, better access to new media technologies and products (e.g. software) in elite universities, required to produce effective crowdfunding campaigns, provides such scholars a technical advantage. For all these reasons, supply factors could reflect status differentials in the crowdfunding of science. We therefore hypothesize:

H1: The institutional standing of a research institution will be positively related to the likelihood that researchers affiliated with that institution will attempt to crowdfund.

On the demand side, there is some evidence that the peer-review process advantages researchers in elite institutions. In crowdfunding, the evidence is mixed: some studies suggest supporters back crowdfunding projects affiliated with high-status individuals, while other studies point out that in comparison to traditional forms of funding backers support a more diverse array of projects. Therefore, we ask:

RQ1: Is the standing of the institution with which a project is affiliated related to that project’s chances of success?

RQ2: Is the academic rank of the scientist initiating a project related to that project’s chances of success?

4. Method

To study these questions, we collected data on scientists requesting funding for their studies on Experiment.com , a platform dedicated to the crowdfunding of science. As of April 2014, this site had by a considerable margin the largest number of completed crowdfunded science projects of any crowdfunding platform whether general-purpose or dedicated to science (Schäfer et al., 2016). We collected data from 20 July 2014 till 7 April 2016. Data were manually collected from Experiment.com by research assistants. An assistant collected initial data (including URL) after the project was first posted because failed projects were usually less accessible after the funding period had concluded. A research assistant then returned to the project to collect full data on it after its funding period had concluded. In this period, 427 projects were posted on the website, of which we removed 77 projects that were proposed by teams that did not include at least one university-affiliated scholar (student, postdoc, researcher or faculty member). The analysis focuses on 333 projects that were proposed by teams that included at least one scholar affiliated with a US university, as data on university endowments and research grants were available only for US universities.

To study the institutional underpinnings of the crowdfunding of science, we compared US academic institutions from which project initiators originated, to US institutions from which no projects were initiated at the time of study, on four indicators of academic status and resources. Appropriate data were available from the Center for Measuring University Performance (MUP). Institutional data include 562 US institutions that as of 2011 had reported any federal research funding in the five preceding years according to MUP data. The full dataset included 782 institutions. However, due to missing data on institutional endowments, the number of cases dropped to 562 institutions for institutional analyses.

We used the most recent wave of data released by the center that preceded our data collection beginning in 2014. Student enrollment served as an indicator of an institution’s size. Measures were for 2009–2011 in thousands of students. Endowment was taken as an indicator of an institution’s wealth, and transformed into deciles because of its skewed distribution from MUP data on Endowment in 2011 in thousands of Constant 1998 USD for research institution (some institutions failed to report endowment data to MUP contributing to a decreased sample size). A measure of federal research grants received by the institution was included as an indicator of the volume and quality of research activity, and in particular of research requiring resources (indicator was measured in deciles transformed from MUP data in 2010 on Total Federal Research in thousands of Constant 1983 US dollars for research institution). Finally, the number of academy members in an institution, an indicator of institutional achievement and prestige, was taken from MUP data on National Academy Memberships of faculty members by institution in 2011.

In the institutional analysis, the number of initiated projects per institution served as one dependent variable. This measure related to the number of projects with at least one crowdfunding founder (member of the crowdfunding team initiating the project) affiliated with a given research institution. The affiliation data were collected manually from project pages on the crowdfunding platform where initiators were able to note current affiliation. As an alternative dependent measure, we transformed the above measure into a dichotomous initiation measure coded as a dummy variable: 1 = at least one project by a project founder affiliated with the institution; 0 = no researchers affiliated with the institution had initiated a project.

We coded the rank of project founders—a key independent variable at the individual level—on an ordinal scale: 1 = no rank, unknown, student, postdoc, adjunct; 2 = assistant professor; 3 = associate professor; 4 = full professor. All ranks were coded from the project page as indicated by project founders. Maximal rank is the rank of the highest ranked member in the team. Minimal rank is the rank of the lowest ranked member in the team.

To examine crowdfunding outcomes, we collected data on pledged funds raised by a project. These were collected manually from project pages after the funding period had concluded where they appeared in a dedicated field at the top right corner of the page. Furthermore, we collected data on the project goal—the amount of money the project founders indicated as their goal on the project page in the dedicated field at the top right corner of the page. We should note that in 21 of 350 cases we detected that the goal was lowered during the funding period. In those cases we utilized the updated goal. We then derived from these data a measure of success. We coded a project as successful when funds raised were equal or greater than the goal. We used this measure because the platform operates according to an “all or nothing model” whereby scientists received funding only when the funds raised reached the goal.

In our regression analysis, we controlled for geographic location for the institution. We created a dichotomous measure of institutional location in a hub or outside of it aggregated from the US state as indicated in 2015 MUP data. Missing data were added from the university name if the state was included, or else from the Google search profile for the institution in March 2017. Universities in Midwest (IN, MI, OH, WI, IL, IA), Northeast (CT, DC, DE, MA, MD, ME, NH, NJ, NY, RI, VT, PA), and Pacific (CA, OR, WA) states were coded as located in research hubs (1), we coded all other institutions as located outside research hubs (0). We also controlled for the existence of a project video for the number of team members given prior evidence of their positive impact on funding levels (Mollick, 2014; Muller et al., 2016).

Given the differences between scientific disciplines in the propensity to engage the public (Jensen, 2011), we also controlled for the disciplinary affiliation of the projects. We coded the research domain of a project based on disciplinary tags that appeared in structured fields on project pages: Life sciences (Paleontology, Medicine, Neuroscience, Biology, Ecology) = 1; Exact sciences (Mathematics, Physics, Materials Science, Earth Science, Engineering, Data Science, Computer Science, Chemistry) = 1; Human Sciences (including both social science and humanities: Education, Psychology, Anthropology, Art and Design, Political Science, Economics, Social Science) = Reference category.

4.1. Data analytic strategy

To study the supply side, at the institutional level we regressed initiation of at least one project by an institution, the number of initiated projects per institution and the success of at least one project affiliated with an institution on the aforementioned indicators of institutional standing as well as the geographic control variable. In the case of project success, we also included a measure of the number of projects affiliated with the institution. Furthermore, we examined the indirect effect of the independent variables on success of at least one crowdfunding project affiliated with a given US institution (mediated by the number of projects affiliated with an institution), using the PROCESS macro test for the significance of the indirect effect (Hayes, 2013).

We also conducted analysis at the level of the individual project to examine demand side factors. Here we regressed two measures of success—pledged funds and a ratio of pledged funds on initial goal—on a number of measures of the standing of individual members of the team: the highest academic rank of a member of a project team, and the lowest rank as well as the decile for the institution that raised the most federal funding among the institutions with which team members were affiliated among American academic research institutions in general. We also controlled for disciplinary affiliation, for the existence of a video on the project page, and for the number of project founders for a given project (see supplemental materials for datasets and syntax used in the analysis).

5. Results

In the period of study (roughly 22 months), on the most popular online platform for crowdfunding scientific research, USD 979,905 were donated by 12,359 individuals to support research at academic institutions worldwide. On average, the projects we analyzed on the prominent science-dedicated crowdfunding platform, Experiment.com , set funding goals of USD 5094.85 (SD = 7167.96), and were able to solicit USD 2871.18 (SD = 4330.92) per project. A majority of the projects (54.79%) reached their funding goal and got funded. This funding rate is higher than the overall success rate for projects on Kickstarter (Kickstarter.com, 2018)—a prominent general-purpose crowdfunding platform. Of those that succeed, most cluster just above the preset goal, similarly to the funding patterns for Kickstarter (Mollick, 2014). A majority of the projects belonged to the life sciences (69.74%), 11.01% to exact sciences, and 19.35% to the human sciences (social sciences and humanities). Sample project titles include: “How does our blood absorb light?,” “Eating disorders in college women—A new treatment approach,” “Next generation non-seeing eye prosthesis,” “Editing photographs in three dimensions,” “Can bacteria turn light into fuel?,” and “Can cognitive tests of shelter dogs improve their chances of adoption?”

H1 concerned the supply side of crowdfunding, and predicted that the standing of the institution will be related to the likelihood that researchers affiliated with the institution will crowdfund. To test for this hypothesis, we first compared institutions from which at least one crowdfunding appeal originated, to all other institutions, on a set of markers of academic standing. Results, presented in Figure 1, demonstrate that crowdfunding appeals are more likely to come from larger institutions (in terms of student enrollment, 19.61K, compared to 8.5K on average; t (199.74) = 9.81, p < .001), from institutions with larger endowments (948.5M compared to 209.8M, t (171.56) = 4.10, p < .001) and larger federal research budgets (49.6M compared to 7.38M, t (177.3) = 7.31, p < .001), and from institutions with more members of the National Academy of Sciences among their ranks (20.2 compared to 1.5; t (170.69) = 4.92, p < .001).

Figure 1.

Comparing institutions from which crowdfunding projects were initiated to other institutions.

As a test of whether these differences are accounted for by other factors, we conducted a logistic regression analysis predicting initiation of projects at the institution level using federal research funding, endowment, student enrollment, and the number of Academy members, controlling for geographic location, known in the research literature to be correlated with the success of crowdfunding projects (Mollick, 2014). Results (reported in Table 1, Model 1) demonstrate that these differences remained statistically significant even when controlling for one another, and for geographic location. This analysis explained 23.2% of the variance in initiation. The same was true when predicting the number of projects initiated in each of the institutions (the Poisson regression model, explaining 42% of the variance in the number of projects, is reported in Table 1, Model 2). That is, the more students enrolled at an institution, the more well-funded and well-endowed the institution, and the more the institution has reputable and accomplished faculty members among its ranks, the higher the likelihood that more crowdfunding projects were initiated by scholars at that institution.

Table 1.

Regression models predicting initiation, number of initiated projects, and success of at least one crowdfunding project in experiment.com (n = 562 institutions).

	Model 1:Initiation(logistic regression)		Model 2:# of initiated projects(Poisson regression)		Model 3:Success(logistic regression)
	B (SE)	EXP (B)	B (SE)	EXP (B)	B (SE)	EXP (B)
Federal research funding (by decile)	.13 (.06)*	1.14	.24 (.04)***	1.27	.07 (.08)	1.08
Endowment (by decile)	.13 (.05)**	1.14	.07 (.03)*	1.07	.02 (.06)	1.02
Student enrollment (in thousands)	.06 (.01)***	1.06	.03 (.00)***	1.03	.02 (.01)	1.02
Academy members	.02 (.01)*	1.02	.00 (.00)**	1.00	−.01 (.00)	.99
Geographic location (research hubs = 1)	.16 (.23)	1.17	.21 (.13)	1.23	.22 (.31)	1.25
Number of projects					1.03 (.16)***	2.81
Pseudo R²	.23		.42		.19

SE: standard error.

p < .05; **p < .01; ***p < .001.

In sum, initiation of crowdfunding projects at an institution is positively associated with its size, funds, current research grants and prestige, as expected by H1. Do these factors also contribute to the success of scholars from these institutions in securing funding for their projects from the crowd? This was the focus of RQ1. To investigate this question, we ran a logistic regression model predicting success of at least one of the projects from the institution, that is, that at least one of the crowdfunding projects initiated at an institution has succeeded in reaching its goal. Of course, more projects increase the odds of an institution to succeed, and this is why the number of projects is controlled for in the model. Results (Table 1, Model 3) demonstrate that, all else being equal, neither grants, endowments, Academy of Sciences memberships nor student enrollment were significantly associated with success. The only factor significantly associated with success was the number of projects. Each additional project initiated at an institution was associated with an increase of 281% in the odds that one of them will be successfully crowdfunded after controlling for all other factors.

Given that, as demonstrated above, the number of projects initiated at an institution was itself associated with endowments, federal grants, student enrollment, and Academy of Sciences memberships, we tested the possibility of an indirect impact of these factors on success at the institutional level, mediated by the number of projects initiated at an institution. This test found that the number of projects was a significant mediator in the association between these factors and success (see Table 2). That is, prestige, size, and financial resources contributed positively to the initiation of more crowdfunding projects, which in turn increased the odds of success. In other words, richer, larger, and more prestigious institutions do succeed more in crowdfunding because more projects are initiated in such institutions.

Table 2.

Indirect effect of independent variables on success of at least one crowdfunding project in experiment.com through the number of projects initiated in the US institutions of higher education (n = 562 institutions).

	B (bootstrap SE)	LLCI	ULCI
Federal research funding (by decile)	.04 (.02)*	.00	.09
Endowment (by decile)	.04 (.02)*	.01	.09
Student enrollment (in thousands)	.03 (.01)*	.01	.05
Academy members	.01 (.01)*	.01	.05
Geographic location (research hubs = 1)	.10 (.09)	–.08	.29

LLCI: lower limit confidence interval; SE: standard error; ULCI: upper limit confidence interval. Indirect effects, standard errors and confidence intervals were calculated using PROCESS macro (Hayes, 2013).

p < .05.

We also examined success at the individual project level as a means of analyzing the demand for scientific crowdfunding projects, in addition to examining the supply of projects at the institutional level. To do so, we investigated the factors contributing to the sum pledged to each of the projects (in US dollars) and the funding success rate (the ratio of funding raised to the funding goal). We regressed these two outcomes on several project characteristics: the highest and lowest academic rank of project initiators (on a scale varying between 1 = student or junior scholar and 4 = full professor), the field the project came from (both exact and life sciences were compared to human sciences), whether the initiators used a video to promote their projects, and the number of project initiators. As an indicator of the funding resources available at the institutions in which the teams operated, we ranked (in deciles) the universities in research grant terms. In cases where several scholars cooperated on a project, we used the highest ranking institution among team members. Results are presented in Table 3.

Table 3.

Regression models predicting pledged funds and pledged to goal ratio, crowdfunding projects with at least one creator originating from a US university (n = 335).

	Model 1:Pledged funds	Model 2:Pledged to goal ratio
Life sciences (= 1)	274.37 (587.65)	.05 (.09)
Exact sciences (= 1)	−1513.18 (858.42)^#	−.28 (.13)*
Video included (= 1)	1436.77 (489.63)**	.21 (.08)**
Maximal rank	−482.47 (300.38)^#	−.12 (.04)*
Minimal rank	433.00 (440.59)	.03 (.07)
Number of project founders	896.58 (206.04)***	.14 (.03)***
Maximal federal research grants (decile)	85.18 (76.63)	−.02 (.01)
R ²	.11	.12

#p < .10; *p < .05; **p < .01; ***p < .001.

RQ2 concerned the association between the academic rank of a scientist and her odds of securing funding in crowdfunding. We found that each one unit-increase on the 1–4 indicator of the maximal academic rank was associated with a decrease of USD 482 in the amount pledged by the team. That is, ceteris paribus, teams with a full professor raised on average USD 1929.6 less than teams including only students or junior scholars. Similarly to the institutional-level models, the university-level indicator of available research resources did not significantly impact success at the individual level. This result, when coupled with the institutional-level analysis above provides a consistent negative answer to RQ1.

As in past research, each additional team member was associated with an increase of USD 896.6 in the pledged amount. Echoing past research on crowdfunding, promoting the funding request with a video was associated with a USD 1436.8 increase in funds raised. Life sciences did not significantly differ from human sciences on both indicators of success. However, the exact sciences raised significantly less funds than the human sciences.

6. Discussion

Is crowdfunding equalizing the funding of science? While a previous analysis of individual level factors related to the crowdfunding of science has argued “that crowdfunding of scientific research broadens access to resources for groups that have been excluded or disadvantaged in traditional funding systems” (Sauermann et al., 2018: 16), we draw a more nuanced conclusion. Aided by our application of the distinction between supply and demand factors to the online funding of science, a particular form of knowledge production, we find that the answer to this question is complex. Our data show that, by far, initiators of crowdfunded projects come from large elite universities, well-resourced in terms of endowments and grants. Hence, the supply of scientific crowdfunding projects is shaped by institutional status, with scientists affiliated with higher ranked institutions more likely to consider a crowdfunding project. However, while scholars from such elite institutions tend to participate more in crowdfunding initiatives, their chances of success are not significantly higher than their counterparts from less prestigious, less well-funded universities. Thus, lay crowd members, who constitute the demand for scientific crowdfunding projects, do not seem to look more favorably upon projects initiated by scientists enjoying higher status.

We conclude that it is the supply side, but not the demand side, of crowdfunding that drives inequalities in recruiting funds from the public. This implies that, currently, graduate students and junior scholars from leading institutions benefit most from crowdfunding when they set out to crowdfund without a senior collaborator. Given that our findings show that institutional status is not associated with greater success, the scientific community should encourage junior scholars to independently crowdfund, especially if they operate in the academic periphery. This could allow gifted young researchers working in sparsely financed institutions to raise funds for their studies, and thus fulfill the utopian vision of the internet as a more egalitarian and meritocratic public sphere. Furthermore, our findings suggest that “the august array of insignia adorning persons of ‘capacity’ and ‘competence’—the red robes and ermine, gowns and mortar-boards of magistrates and scholars in the past, the academic distinctions and scientific qualifications of modern researchers” (Bourdieu, 1975: 20) are of muted importance when science funding decisions are handed over from members of the scientific community to the crowd.

Our study is theoretically situated within a fundamental question in the study of new media: do digital media technologies—especially online crowds and platforms—narrow, reflect, or broaden gaps in access to resources between the more and less affluent. The study also adds an important distinction between the supply and demand sides of resource allocation in the crowdfunding of science and cultural products more generally.

Our findings paradoxically support both sides of the debate on the role of the internet in shaping social hierarchy. Early expectations (now called by some utopian) that online technology would work to narrow gaps between haves and have-nots by lowering entry barriers to the public sphere received support from the finding that status did not significantly contribute to the success of individual projects, above and beyond controls. However, skeptics’ argument that stronger actors enjoy the benefits of online technologies more than relatively weaker ones also enjoyed the support of our data, in that, when not controlling for the number of projects initiated by institutions, larger, stronger, and more prestigious institutions received on average more funding.

It is possible that scholars from stronger universities simply invest more effort in crowdfunding. In turn, these differential efforts could themselves result from, or otherwise reflect, difference in the academic hierarchy. For example, it could be that it is not only that the academic culture in stronger institutions stresses the importance of more expensive research or of being funded. Rather than, or in addition to these pressures, junior scholars operating in a stronger environment enjoy more resources that are relevant for crowdfunding: more time given lower teaching loads, better media facilities to create more successful pitches and so forth.

We cannot tell whether funding goes to the more scientifically solid and deserving projects, but it is very likely (given the positive effects of posting a video and having more team members) that putting more effort into promoting the crowdfunding campaign increases the chances of success. It is unclear why teams without senior scholars are on average more successful in crowdfunding their research. It is possible that teams of junior scholars were more active in the promotion of their projects. In addition, it is possible that members of the public are reluctant to support researchers that they perceive as already well-funded.

6.1. Limitations and directions for future research

An important implication of our findings is that future research should pay closer attention to deciphering the mechanisms behind empirical findings demonstrating inequalities in the digital pooling of resources in crowdfunding, crowdsourcing, and other forms of collective action online. Such research should consider whether involving the public more directly in funding decisions will open opportunities for additional scientists, and what impact would such involvement have on the quality of the research produced. In addition, future research should pay more attention to the characteristics of the funding public more directly (and study, for example, whether social ties to more affluent friends, are related to crowdfunding success in the context of science). Such careful attention could potentially broaden our understanding of the complex association between technology in general and platform mechanisms specifically on the one hand and resource allocation on the other hand in additional domains and therefore offer more nuance to our understanding of the social implications of emerging media and online platforms.

We argued above that the context of science is suitable for exploring supply and demand factors’ role and their interaction with status in shaping resource allocation online given the fact that, in science, status is more explicit and perhaps salient compared to other domains. However, this choice has its limitations.

One should note that our study is limited to one particular mechanism—crowdfunding, in a particular knowledge industry—science, on a dominant though particular funding platform, and limited to the US context. On the one hand, in other cultural domains such as fine arts quality is “inscrutable” (Gambetta, 1994) and especially difficult to ascertain, and therefore status is a convenient shortcut shaping both supply and demand (Aspers, 2009). On the other hand, in knowledge industries beyond science, barriers to participation are now considerably lower (Doyle, 2013; Waldfogel, 2017) and therefore status could be of less importance in shaping the supply of knowledge producers appealing to the public directly for funding. Future studies should therefore test similar hypotheses and research questions in additional domains, contexts, and platforms. Furthermore, while we examine the institutional characteristics of the scientific community at the organizational and individual levels, we recognize the preferences of the funding public should be studied directly.

Supplemental Material

CF-Science-SPSS-syntax – Supplemental material for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research

Supplemental material, CF-Science-SPSS-syntax for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research by Roei Davidson and Yariv Tsfati in Public Understanding of Science

Supplemental Material

CF_science_institutions-SM-PUS – Supplemental material for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research

Supplemental material, CF_science_institutions-SM-PUS for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research by Roei Davidson and Yariv Tsfati in Public Understanding of Science

Supplemental Material

CF_Science_projects_data_only_academics-SM-PUS – Supplemental material for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research

Supplemental material, CF_Science_projects_data_only_academics-SM-PUS for The contribution of supply and demand factors to the reproduction of hierarchies online: The case of crowdfunding of scientific research by Roei Davidson and Yariv Tsfati in Public Understanding of Science

Footnotes

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iDs

Roei Davidson

Yariv Tsfati

Notes

Author biographies

Roei Davidson (PhD, University of Michigan, 2007) is a Senior Lecturer at the Department of Communication, University of Haifa, Haifa, Israel. He studies social aspects of media institutions and technologies, with emphases on inequality and cultural production.

Yariv Tsfati (PhD, University of Pennsylvania, 2002) is a Professor at the Department of Communication, University of Haifa, Israel. His research focuses on various aspects of audience perceptions of media.

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