Authors:
Raina Brands – London Business School
Isabel Fernandez-Mateo – London Business School

Interviewer:
Madeline King – Stern School of Business, New York University

Article link: http://journals.sagepub.com/doi/abs/10.1177/0001839216678847

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Listen below to the September installment of the ASQ Blog Podcast Series:

Transcript of Podcast:

MK: Hi, I’m Madeline King from NYU Stern, and I’m one of the co-organizers of the ASQ blog. We’re thrilled to have the opportunity today to sit down with Raina Brands and Isabel Fernandez-Mateo to ask them some questions about their paper titled “Leaning out: How negative recruitment experiences shape women’s decisions to compete for executive roles.” One of the purposes of the ASQ blog is to get insights into the processes that went into the final paper that we see in ASQ. So thank you both for making the time to be here today.

This topic is fascinating, a very interesting paper, and very timely as female representation in organizations has been a hot topic in popular press recently. And your paper, starting with the title and other portions of the paper, directly referenced Sheryl Sandberg’s 2013 book Lean In. And this has become a very popular mantra in the mainstream discussion about women’s mobility within organizations. Do you think that your findings challenge her advice? Or do you think that it adds a piece to this very complicated puzzle?

IFM: We actually think that the book is much more nuanced than it has been reported in the press. If you actually go and read the book, it shows Sandberg’s account of why you find so few women at the top of organizations. It incorporates both demand-side mechanisms—that is, that there are organizational practices that are biased and so on and so forth—and also supply-side mechanisms. However, she goes on to focus mostly on how can we change the supply side, that is how can we act on women’s behavior, and that’s what has been picked up by the press, for the most part.

We don’t actually think that our findings challenge her advice. Her advice is perfectly fine according to how the state of the world is right now. However, it is a bit more nuanced, because what we are pointing out is that the choices and the behavior that women make in organizations cannot be understood independently of the demand-side environment, of the things that are happening to them, because of biased practices or discrimination or experiences of exclusion.

So if you are an organization, you need to understand how your demand-side practices affect those choices. So they are basically not independent, but they are not contradictory.

MK: That’s great. And I’m very interested to hear about the motivation for this paper in general—I mean how this maybe came out of the observed phenomenon in the world, or working with data. Can you speak a little bit towards that?

IFM: Yeah, so we give you the honest story of how this came up.

MK: Great! We love the honest story.

IFM: This is Isabel, by the way. So this started quite a few years ago when I was actually doing research on hiring and executive search, and in the interviews, the topic of rejection started to come up, which it was not something I have thought about or was in the literature. But these headhunters kept telling me that how they managed rejection of candidates was basically their most important task.

MK: Interesting.

IFM: It was the thing that they had to care about the most. And out of that, I wrote a paper that was published in Organization Science a few years ago, in which I showed the benefits and the disadvantages of managing rejection in the hiring process. In the process of doing that, this was not a gender paper at all. But when looking at the data, it was very obvious that this effect of rejection discouraging executives from applying again was stronger for women, so the data were saying this is stronger for women. And we have no explanation or theories or research that would speak—at least that I was aware of—to why this was the case. And that’s when Raina came in, and we started thinking about figuring this out: how can we learn more about this phenomenon in this data that is telling us that this rejection effect is stronger for women? Can we figure it out? And that’s basically how it came up, right?

RB: Mm-hm, yeah.

MK: The mechanism that you talk about in the paper is this idea of belonging uncertainty and the way in which it influences men and women’s reactions to procedural justice and injustice. And I’d love to hear a little bit more about the generalizability about this mechanism and how it might apply to other populations who may also feel that they don’t belong in certain contexts, particularly the upper echelons of organizations.

RB: I think that this is a very generalizable mechanism. Any group that is underrepresented and negatively stereotyped in a particular domain, be that high-level leadership or a particular occupational domain, would be susceptible to these feelings of “I’m not sure if I belong here, so I’m not sure if I want to stay in this particular context.” So it would certainly, I assume, generalize to the question of race representation in upper leadership. But even if you could imagine a domain where, say, white men were negatively stereotyped and underrepresented, I think we’d see the same effects playing out.

MK: And do you think that this could work in the same way for non-categorical variables? Say there are other triggers that could make people feel that they don’t belong, such as aesthetics or taste. Do you feel like it could extend that far?

RB: Yes, the need to belong is obviously fundamental to all human beings, and of course we know that people consider idiosyncratic aspects of fit when they’re thinking about whether or not they join an organization or pursue a particular career. So “Does this meet with my interest, and my taste, and my preferences? Is this the kind of culture that I want to work in?” These are questions that everybody would ask themselves. And if the answer was no, you’re probably not going to pursue that particular direction.

I think the question about broad social categories is perhaps more potent, because when you have these broad social categories there’s a possibility for existence of negative and positive stereotypes about your fit for certain domains, where then we see these belonging pressures acting separately on different groups of people. So absolutely, it would apply to idiosyncratic aspects of belonging, but I think in terms of predicting outcomes that organizations care about, it’s those broad social categories that are more meaningful.

MK: So now this paper is extremely ambitious in that it employed multi-methods: it works with field data, survey data, and an experiment. So I’d be very interested to hear how the order of this multi-method approach developed.

RB: Yeah, well, obviously Isabel had the field data, so that’s what we started with, but that was just showing the effect. And I personally always work across field to experiment.

MK: Always in that direction? 

RB: No, not necessarily. Usually, you have the field data first, but not always in that direction. There’s no rules. [laughs]

So we have this very robust and huge dataset showing the effect, but any effect that’s real should be able to replicate. So we needed to replicate, and we also needed to find out what was driving it. So we went then to the survey, and actually, the survey that’s in the paper is the second survey we conducted. The first survey was actually just with an MTurk sample to see if we could replicate the effect. And I will say that this is probably the most robust effect I’ve ever worked with. It never fails. And then we went to the experiment to really try and explore the mechanism. And actually then, we went back to survey to get the executive population, then went back to experiment to get the executive population for that experiment.

MK: So two iterations…

RB: Yeah, and I think it’s important to highlight that because that’s very typical for me. You can find the effect, but the data that ends up in the paper is usually different to the data you start out with.

In terms of what would I do differently in hindsight, I think the only thing is when we first started looking into the effect, or sort of theorizing about the mechanism, we settled fairly quickly on procedural justice. But in the review process, the reviewers quite rightly pushed us for the mechanism behind the mechanism. “But why procedural justice?” was basically the question they were asking. And I think you learn something in every paper that you publish, and certainly now with the benefit of hindsight, I would have been looking for that proximal effect from day one. That’s probably the only thing I would have done differently is to search for the mechanism behind the mechanism early on.

MK: Do you have any other advice for Ph.D. students who are thinking about tackling multi-method projects?

RB: Well, I think, and this advice comes from mostly doing a lot of reviewing for journals, if you don’t have the training in a particular domain—so if you’re not an experimentalist, or if you don’t work with huge field datasets, which is the collaboration [laughs] . . .

MK: The synergies here, yeah . . .

IFM: I have never done an experiment before, so I needed Raina.

RB: And I certainly couldn’t work with the sort of data that Isabel works with. If you don’t have the expertise, then collaborate. Because I do review a lot of papers where it’s quite clear that no one on the team is a trained experimentalist or is trained in these huge field data sets. And you just can’t come up to the level of expertise you need to execute it properly, so the advice I have would be seek collaborations with people with complimentary skill sets.

MK: Fantastic. So thinking about this paper kind of as a whole and this mechanism that you found, these incredibly robust findings, I’m interested to hear—now that you’ve brought both supply- and demand-side explanations together— how big or impactful you see this being for organizations?

IFM: So I like footnotes [laughs]. I have lots—I put lots of footnotes in my papers, and sometimes I think that the most intriguing things about the paper are in the footnotes, so look at footnote 16 of the paper. So in the process of getting this paper through the review process, this question came up: “So yes, you find this, we believe you. How important is this for organizations?” We actually went and tried to assess this with a little formal model, in which what we show was that if this was the only thing, the only mechanism—so women’s lower persistence after rejection—that was affecting the percentage of women in the pipeline, how would this over time affect the amount of women available to fill positions for a firm, let’s say? And if you do a very, very basic formal model you actually realize that the effect is quite significant. In only a few periods, if this is the only thing that’s going on, the firm is going to find itself with fewer and fewer women to select from.

So obviously that was a toy model. It was by no means a serious attempt to explore this question. But I do think it opens up, the findings of our paper open up a lot of opportunities for further and further research for organizations to try to understand when they are looking at their leaky pipelines, if you wish. So the fact that they are very worried that the women are not making [it] up to the top, and very often they’re worried they’re leaving, what are the solutions? Are there solutions about acting on the women’s behavior, or can they do something in the organizational side that might actually make the supply side less of a problem, without trying to act on the women, but acting on their practices?

That’s an open question, but we do think it has important theoretical implications and huge practical implications, actually—that the demand side and the supply side are not independent is something we need to keep in mind.

MK: And where the interventions might be…

IFM: Where the interventions may be, yes. And more visible, to be honest. Because organizations may have more leeway way to act on their selection processes, to act on their inclusiveness, and this may have consequences on the supply side that might be indirect but much stronger than if you try to change the supply side only. So hopefully we’ll keep doing that.

MK: Well, fantastic! Thank you so much for making the time to sit down and talk to us today. Our listeners appreciate it. And this article will be published in the September issue of ASQ, so look for it there. Thank you so much.

IFM: Thank you.

[Thank you to the ASQ blog community for listening. Look for the next podcast in November and several blog interviews between now and then! As always, if you’re interested in getting involved in the ASQ Blog, email asqblog@gmail.com for information about joining our community of scholars and bloggers.]