The scientist–practitioner gap has garnered a substantial amount of attention in the field of industrial and organizational (I-O) psychology, and rightfully so (Aguinis & Lawal, Reference Aguinis and Lawal2013; Banks et al., Reference Banks, Pollack, Bochantin, Kirkman, Whelpley and O’Boyle2016; Rotolo et al., Reference Rotolo, Church, Adler, Smither, Colquitt, Shull, Paul and Foster2018; Rynes, Reference Rynes and Kozlowski2012). Although we agree that the topic is worthy of discussion, and the focal article does an admirable job of initiating an important conversation, the empirical approach used by Zhou et al. (Reference Zhou, Campbell and Fyffe2024) lacks the rigor required to draw meaningful conclusions. The emphasis of evaluating the scientist–practitioner gap should be just that: quantifying the divide between academic I-O psychologists and those practicing in areas such as human resources (HR), organizational behavior (OB), organizational development (OD), and so forth. The focal authors’ study fails to shed significant light on the issue at hand by instead examining the divide between scientists and a more general audience (i.e. small business owners).
A brief critique of the methodological approach
We start our commentary by briefly highlighting a few of the methodological issues in the focal study. First, as alluded to above, academic journal articles are rarely intended to be consumed by small business owners, nor the general public, as the end user. Rather, the ideal end users for any practical article are the practitioners themselves, who are trained consumers and implementers of the research. Although articles regarding the improvement of communicating psychology research to nonexperts, in general, have emerged (Stricker et al., Reference Stricker, Chasiotis, Kerwer and Günther2020), others argue that the improvement in communication necessary for the fields of I-O psychology and management lies between the academics and the practitioners (Timming & MacNeil, Reference Timming and Macneil2023; Rynes, Reference Rynes and Kozlowski2012).
A second critique is related to the use of abstracts and practical implication sections in the empirical design. Abstracts are intended to provide a high-level summary of the article and often leave little room for detail, creating a problematic confound in the study design as abstracts are often not appropriate for drawing conclusions about implementation. Regarding the practical implication sections, although these should resonate more with business leaders, when taken out of context and consumed in isolation they are likely to be confusing and difficult to read without a working knowledge of the steps taken to draw such conclusions.
Finally, the approach to selecting articles for this review may not have resulted in an accurate representation of where research has been conducted. In conducting their article search, Zhou et al. acknowledged that although many studies may include small businesses, they focused only on articles that specifically called out “small businesses” (or some derivative search term). At the same time, the focal authors do not provide any estimate to quantify how many studies specifically mention “large organizations” (or some derivative search term). As a result, we’re left without a true estimate of the scope of the research gap between organizations of various sizes.
Suggestions for further exploration and addressing the scientist–practitioner gap
We have provided the above critique of the current study to encourage additional research to help us better quantify the scientist–practitioner gap. We now turn to our specific recommendations for continuing to explore and address this divide.
Coordinated efforts from both scientists and practitioners
Although the use of abstracts and practical implications sections may not provide the most compelling evidence to quantify the scientist–practitioner gap, we concede that academic articles often provide the “Cadillac” version of tools or methods for organizations. As such, one way that academic articles may help diminish the gap and provide more broadly applicable guidance is to develop scalable recommendations for practice. For instance, in a selection context, researchers studying personality assessment may suggest those scales of their selection system they deem to be critical for predicting performance as a basic tier, followed by tiers that provide incremental validity to predicting a desired performance outcome, which can be added where resources allow but which may not be essential. Given that the practical implications sections may not be specifically tailored, perhaps the development of scalable recommendations can facilitate practitioner understanding and implementation of academically developed solutions. This added context may provide a foundation for practitioners to reflect on, modify appropriately with guidance, and implement solutions (Czarniawska & Sevon, Reference Czarniawska and Sevon2005; Schön, Reference Schön1995).
Additionally, looking at journal articles only represents half of the gap that separates scientists and practitioners, failing to gather data from the practice side. For example, the literature suggests that practitioners may prefer intuitive methods of selection over empirically developed and validated tools (Buckley et al., Reference Buckley and Norris2000; Highhouse, Reference Highhouse2008; Rynes, Reference Rynes and Kozlowski2012), highlighting that the issues with implementation are not solely due to academic article clarity. As such, we argue that bridging the gap between scientists and practitioners should not fall on academic institutions or journals alone. Regarding our previous suggestion, although the practitioners would bear the burden of appropriately scaling and implementing solutions based on theoretical guidance, systems in which scientists can provide appropriate feedback on the implementation of solutions could be valuable in narrowing the divide. Rynes (Reference Rynes and Kozlowski2012) similarly suggests that providing support to practitioners during implementation, when possible, may help close the gap. Whether it be through journals, conferences, or practitioner-led research institutes, collaborative efforts that promote the sharing of solutions in real-world situations (i.e. small sample sizes) would be extremely valuable in the continued effort to bridge science and practice.
Consider different distinctions to better understand the gaps
Zhou et al. also ask if the focus on small businesses is warranted. We agree it is valuable to create identifiable subsets of the economy using some consistently defined variable(s). Doing so allows for research that can be focused on better understanding the nuances of how work gets done in that specific job, industry, or category of organization instead of attempting to conduct research that is generalizable across the entire economy (Bamberger, Reference Bamberger2008; Collins, Reference Collins2004; Johns, Reference Johns2001; Rousseau & Fried, Reference Rousseau and Fried2001). However, it’s less clear to us that organizational size as defined by Zhou et al. is a meaningful (or actionable) distinguishing characteristic of organizations when it comes to the scientist–practitioner gap.
Issues with using organizational size as a distinguishing feature are illustrated by the data the focal authors cite regarding organizational size in the U.S. economy. The authors cite statistics that show that large businesses (over 500 employees) make up less than 1% of the total number of U.S. businesses, but those businesses employ over 50% of the total U.S. workforce (Zhou et al.). From a statistical perspective, it would be impossible to use this definition and draw meaningful comparisons between large and small businesses with organizations as our level of analysis. At the same time, focusing only on small businesses (fewer than 500 employees) would ignore most of the total U.S. workforce. So, the argument that research done on large businesses is not applicable to a majority of the workplaces is countered in that it is applicable to a larger percentage of the workforce.
One of the fundamental challenges in creating a meaningful distinction among organizations is determining the appropriate criteria for making such a distinction. We suggest that the most valuable criteria will create categories of businesses between which there are substantial differences, either in the way work gets done (which would impact the applicability of research findings) or in the scientist–practitioner gap itself (impacting the way research findings get translated into practice). For example, using the distinction proposed by Zhou et al. would we expect to see different results in their subject matter expert (SME) survey if large business owners or employees were also included in the study? We don’t see any reason to hypothesize that large business owners or employees are more capable of reading, comprehending, and interpreting scientific research. Therefore, we expect that large business owners or employees would report the same challenges that small business owners reported in reading and understanding research journals.
Similarly, we might ask: Would large organizations find the scientist–practitioner gap any less challenging to address than small businesses? Larger organizations certainly have access to more resources (e.g., employees, leaders, and financial support) that would make some aspects of implementing a research-based change easier. However, apart from these logistical issues, we believe large organizations would face many of the same challenges as small businesses. In our experience working internally at large organizations, challenges related to the scientist–practitioner gap (e.g., gaining buy-in for theoretical solutions, translating research into real-world applications, and controlling the quality of implementation of solutions across various departments or leaders) are still very much present in large organizations.
Taken together, we doubt there is a meaningful difference in the scientist–practitioner gap between categories of organizations by size. However, we do recognize the call for, and interest in, contextualized research (Rynes, Reference Rynes and Kozlowski2012). We suggest that it may be more beneficial to understand and reduce the gap between science and practice by considering other distinctions.
For example, Devoe and Pfeffer (Reference Devoe and Pfeffer2009) found that hourly workers focus more on their income when evaluating their happiness than do their salaried counterparts, suggesting that studies of workplace motivation conducted on salaried employees may not be generalizable to an hourly workforce. Other research has shown that leaders in nonprofit organizations behave differently than leaders in for-profit organizations (Bowers & Hamby, Reference Bowers and Hamby2013) and that volunteers may attend more to organizational constraints than paid employees, and volunteers’ own sense of efficacy in making a difference in their community can moderate the impact of those constraints (Harp et al., Reference Harp, Scherer and Allen2016). Results such as these suggest that categorizing workforces by hourly or salaried, or workplaces as for profit or not for profit might be useful designations for focusing research intended to close the scientist–practitioner gap.
Summary
To summarize, we appreciate the authors bringing attention to the scientist–practitioner gap and find that their review provides a reasonable catalyst to the conversation, and hopefully a resolution. Although we believe that the study itself isn’t sufficient for drawing conclusions about potential solutions, we offer a few suggestions for moving forward. First, we suggest that we evaluate alternative criteria for splitting organizations into meaningful categories as the large- versus small- business classification may be misleading when addressing this issue. Identifying a consistent and meaningful approach to categorization will enable the second step, which is to conduct a more thorough investigation of the scientist–practitioner gap to see if there are differences between those categories of organizations. We also suggest that addressing this gap does not fall solely onto academic institutions or journals; a more comprehensive approach includes more feedback loops between scientists and practitioners, more opportunities for sharing best practices, or more emphasis on building applied research teams or institutions that will focus on practical implementation of academic research or producing research from applied settings.
