Who Benefits from Entrepreneurship Opportunities? Check the Norms!

Many nations want more entrepreneurship to grow the economy. Many individuals want public support of their entrepreneurship efforts, or at least removal of barriers. When policies to make entry into entrepreneurship easier are introduced, a common logic is that they should benefit the economically weaker people because the privileged have the necessary resources to enter entrepreneurship. This logic has a problem, though: researchers have found that it is sometimes right and sometimes wrong.

Understanding the reasons for the inconsistency was the motivation behind research by Grady W. Raines, Peter S. Polhill, Shon R. Hiatt, and Ryan S. Coles published in Administrative Science Quarterly. Their underlying idea was that most support for entrepreneurship is about reducing financial barriers or friction in the form of difficult business registration requirements. Barriers against entrepreneurship don’t just come in the form of time and money, however, so these types of changes may not be enough. Other barriers exist in the mind: who in society think of themselves as potential entrepreneurs and are thought of by others as potential entrepreneurs? And another barrier resides in social relations and norms: who does a society believe should be entrepreneurs?

Why do these distinctions matter? Well, let’s imagine a society in which men are thought of as more natural entrepreneurs and where norms see men as those who should lead anything, including businesses. We don’t need to imagine it, of course, because many societies are patriarchal like that. In this research, the authors focused on reforms in Mexico that were intended to make entrepreneurship easier by reducing required procedures and office visits and thereby speeding up the business registration process by a lot – from a month to a day and a half.

So, what happened?  Mexico got more entrepreneurs, as we would expect. Male entrepreneurs. For women, there was no increase in the number of entrepreneurs following this reform, suggesting that the norms disfavored them. And remarkably, this lack of change was the best news from the perspective of women. Now for the really bad news: Fewer women had paid employment following this reform. Why? Because more of them did unpaid labor in the entrepreneurial enterprises of their male relatives. So, in this patriarchal society at least, easier entrepreneurship meant more male entrepreneurs and more unpaid women workers.

Is this a reason to be wary of entrepreneurship or of policies supporting entrepreneurship? Probably not. Is it one more reason to think that norms of inequality, such as patriarchy, find many ways to hurt society? Yes. And it is not clear that we have a good solution for this.

Raines, G.W., P.S. Polhill, S.R. Hiatt, R.S. Coles. 2024. Cultural Norms and the Gendered Impact of Entrepreneurship Policy in Mexico. Administrative Science Quarterly forthcoming.

Why Quit Your Job? Resources in Black and White

Employers have always been interested in why workers quit their jobs. It is often, and rightly, seen as a waste because those who quit to join another company are clearly seen as more valuable there, or see the other company as more valuable for them, suggesting that they were not used well enough or appreciated highly enough in their current job. High quit rates are problematic for companies.

They are also problematic for society because quit rates display racial differences. All racial groups in the US society have slightly different quit rates, but a glaring concern is that black workers quit so often even though they face discrimination in getting a new job. Why?

Recent research by Adina D. Sterling published in Administrative Science Quarterly gives a clear answer: it is about resources. In resource access, there is, on average, a big black and white difference. Black workers face greater problems with public transportation and health, both of which can prevent workers from staying in their jobs. White workers have greater resources for starting a new venture or returning to education, and this allows many of them to leave their jobs. So, the same behavior – quitting the job – has very different meaning, though the root in both cases is resources: too few resources for the black worker to stay, too many resources for the white worker to want to stay.

If the answer is all about resources, where is the discrimination? We can find it in two places. The first is the economic and social history behind these resource differences. If we look at the family income distribution by race, we see that black workers’ families are a majority in the bottom 25th percentile of family income even though they are a minority in US society. Sure, they are also found in the top 25th percentile, but given the lasting effects of slavery and legalized segregation and discrimination, there they are scarce.

The second place is in black workers’ greater difficulty in gaining jobs, and especially gaining jobs that are close enough to their homes to reduce their dependence on public transportation for getting to those jobs. Difficulty in gaining a nearby job translates to lack of resources and inability to keep the job, which too often places black workers on the job market again, facing the same difficulty. Sterling’s research highlights this vicious circle: a crucial step in keeping employers and policymakers focused on providing what can matter most for a worker trying to stay on the job.

Sterling, Adina D. 2024. “This Is Why I Leave”: Race and Voluntary Departure. Administrative Science Quarterly, forthcoming.

How to Detect Fraud in Cryptocurrency Markets? Learning From Ambiguity and Cues

How do you like cryptocurrencies? How do you like fraud? As we know from the press, especially news reports on
convictions such as that of SamBankman-Fried, the two questions are closely related. The unregulated nature of cryptocurrencies means that actions that are blatantly illegal in regular securities markets have a weaker legal proscription in cryptocurrency markets, and some people take advantage of it. That creates a problem for those who want to keep such markets healthy and make use of the currencies.

How they deal with this problem was the question studied by Bryan Spencer and Claus Rerup in research published in Administrative ScienceQuarterly. They examined a crypto-investment community that was hit by a series of fraudulent promotions by a group of actors who coordinated with each other to execute classic “pump-and-dump” schemes of minor cryptocurrencies. The problem, of course, was that the world of cryptocurrency movements and the world of online news are both ambiguous, so detecting coordinated fraud is difficult.

A major reason the researchers could detect that fraud was happening and that the investors were – after a while – becoming aware of this was that the researchers had access to the database containing public and group chats about the cryptocurrencies, which included the conversations among the fraudsters that were kept hidden from the other crypto-investors.

So, what did the investors do? Over time, they learnt. But they followed a path of nontraditional learning based on learning by making inferences from interpreting cues. They would question the intent behind the appearance of innocent-looking information (such as false analyst reports) supporting a currency. They would look for similarity between new information releases and earlier fraud cases. They would infer the intent behind the release of information even when they did not know who was behind the information release. And once they had made enough interpretation and inference, they would have stories ready about the true nature of the unfolding events and would be able to act in response. They acted by more systematically monitoring releases of information and by routinizing public responses to information releases that looked suspicious, so that other investors would become aware of the price pumping and could avoid entering.

In all, this article is a very interesting report on how a community can act to protect itself in the face of ambiguous information and repeated fraud attempts. But also, it is a reminder of why markets are regulated and why financial markets are regulated especially strictly. After all, the lengthy penalty of Sam Bankman-Fried was based on wrongdoing not in the cryptocurrency operations, but in regular and regulated financial markets.

Spencer, Bryan and Claus Rerup. 2024. The Dynamics of Inferential Interpretation in Experiential Learning: Deciphering Hidden Goals from Ambiguous Experience. Administrative Science Quarterly, forthcoming.

Learning from No Experience: How Firms Handle an Unprecedented Crisis

“Learning from experience” describes a process that underlies many of our essential skills. I am grateful that I was made to practice driving before getting my driver’s license, and grateful that others did too. By the same token, most people would worry about how they might respond to a critical situation that they had never seen. I was in Tokyo during the 2011 Tohoku earthquake (Magnitude 9) and was pleased with myself after coping with the shaking building and two small kids and knowing when and how to evacuate. Still, I can imagine other surprises that I would handle less well.

Similarly, firms sometimes encounter a completely new crisis. How do they handle it? I looked for answers in research published in Strategy Science onhow the airline industry responded to the COVID-19 crisis and the suddenrestrictions on mobility. This was a pandemic the likes of which the world had not seen since the 1917-1918 Spanish Flu, long before the airline industry existed. The best solution was timely storage of many aircraft and scrapping of others, but this was a difficult decision to make. Would the data show evidence that some airlines handled the crisis better than others because of learning? Surprisingly, the answer was yes.

Understanding why this happens requires taking a broader view of learning. The airlines had never seen nation states shutting down mobility, including air traffic, in response to a pandemic, but some of them had experienced abrupt reductions in demand before. The 9/11 attack led to a big drop in air travel in the USA, and the Financial Crisis had a similar effect in most rich countries. Airlines in any of those places at the time of the crisis, but not those that were founded later, responded better to the pandemic. Their current leadership could draw from stories about the old crisis and their good and bad responses, including those of their competitors at the time. They learnt from history.

Equally important, airlines that were in regions that were hit hard by the crisis also responded well, and not just by imitating their nearby peers. Observing a severe crisis allowed them to understand many different actions taken by their peer firms, accelerating their learning and allowing better responses. We often refer to such learning as bricolage, because the executives were picking up many pieces of information and putting them together to form better decisions. They learnt from diversity.

Learning from experience is not just learning from taking the same action repeatedly, and from facing the same situation repeatedly. Firms learn from history and diversity in ways that involve more consideration, and such learning allows some firms to perform better than others.

Greve, Henrich R. 2024. Airline Responses to the COVID Collapse:Applying Learning to an Unprecedented Crisis. Strategy Science, forthcoming.

Founders Forming Startup Cultures: Why Atypical Cultures Transfer Better

When a new venture is founded, does the founder create the culture? Much rhetoric from the founders of high-tech firms suggests they do – some even post manuals of the firm culture for others to admire and copy. But coming to think of it, the founders might be influential but still not important in the end. In any firm that scales the founder quickly becomes a small minority, and employees form the culture too.

So, which is it? That is the question answered in research by Yeonsin Ahn and me published in Organization Science. We looked at the cultures of information technology firms listed in Crunchbase and used descriptions of the firms at Glassdoor as data to do a linguistic analysis of their cultures. That way, we could compare the cultures of any firm, and we went on to detect how much the new venture culture was related to the culture of the previous employer of the founder. That’s because founders typically carry along the culture of their employer even when they try to create something new.

What did we discover? New venture cultures, on average, do not show much trace of the founder creating the culture. The keyword here is “on average” because the exceptions are very interesting. The first is atypicality. There is a wide range of organizational cultures also in technology firms, and there is a mix of more-or-less typical organizational cultures along with more atypical organizational cultures. Do employees like atypical cultures? That is hard to tell, but we know from the data that founders could more easily transfer atypical cultures than typical ones. Most likely this is because atypical cultures are more distinct, so employees can more easily notice the culture that the founder is used to and likes, and they can copy it.

Are there any other interesting effects? Yes, we made one more discovery. In general, cultures are not necessarily congruent – they contain internal contradictions that cannot be resolved, but instead lead to compromised or case-by-case choices. This is true of culture in general, and also of organizational cultures. We found that congruent cultures transferred more easily, again indicating that ease of learning the founder’s organizational culture makes the founder more influential.

So founders can create organizational cultures under the right conditions. The culture needs to be atypical enough to be recognized, and congruent enough to be easy to learn. A simple answer to a complicated question.

Ahn Yeonsin and Henrich R. Greve. 2024. Cultural Spawning: Founders Bringing Organizational Cultures to Their Startup. Organization Science, forthcoming.

Hiring Minorities Solves Our Discrimination Problem, Right? Wrong!

There has been long-standing discrimination in US workplaces against women and minorities of all kinds. The salary difference between men and women doing comparable work is well known, and so are the problems of getting hired and retained faced by people of color and immigrants. The solution mandated by many employers and recommended by others is to ensure that hiring new employees is non-discriminatory in job description, advertisement, and selection processes. This focus has proven effective in getting to fair hiring practices.

But, less well known, what happens afterward has not been fixed: promotion and even retention (keeping the job) show the same discrimination as hiring used to do. Why? This is where research by Tanya Y. Tian and Edward B. Smith in Administrative Science Quarterly provides some very compelling answers. They zoomed in on Black professors in a major research university – the employees most affected by discrimination and the workplace most serious about fixing this problem – and checked what happened after a period of fair hiring practices.

To understand their research, it is important to understand that evaluating professors’ productivity is not very different from evaluating other professionals like lawyers and consultants. Good output volume and quality measures are available and are used for retention and promotion decisions, and to some extent they are over-used compared to less measurable contributions because the decision to fire an employee may have to be defended in court. Another important feature of universities is that they contain a combination of standard and customized positions, and customization can be used to create positions that address the university’s diversity needs or to fit in Black applicants whose CVs do not exactly fit what might be sought for a given standard position.

And that’s where the problems begin. Both the customized positions and the general status of being Black and thus a signal of diversity mean that the employee has to produce more output along the less measurable dimensions, the ones that count less for promotion. Given that hours per day is a constant and junior faculty work as much as they can to begin with, Black professors are disadvantaged in the promotion process. The research showed that this was true. Also, it showed that their lower retention rate was because Black professors were disproportionately placed in non-standard positions. And this held true even when taking into account their research productivity – which didn’t matter because non-standard positions led to lower research productivity.

So fair inclusion is a good thing, except that it isn’t good when fairness happens only at the point of hiring, not later. This serious problem is not well known among employers or job seekers, and it urgently needs more attention. That is why research like this is important.

Tian, Tanya Y. and Edward B. Smith. 2024. Stretched Thin: How a Misalignment Between Allocation and Valuation Underlies the Paradox of Diversity Achievement in Higher Education. Administrative Science Quarterly, forthcoming.

Firm Governance Advice: Why Math and Machine Learning Disagree

It has been a long time since agency theory started dictating management theory thinking about firm governance. According to this theory, management are primarily selfish and secondarily interested in firm profits and shareholder value creation. This makes them unreliable agents of the ultimate owners, the shareholders, so it is necessary to prescribe many medicines in the form of better surveillance of their actions and better alignment of their pay with firm outcomes. And so a small industry of governance research and advice has grown, resulting in many practices that are supposed to improve things.

Everything is backed by the mathematics of game theory and proofs showing that managers (well, CEOs primarily) will behave better if they are controlled. That makes the advice an undisputable fact except for one thing. The equations are not exactly the same as the practices, and there are many ways actual human beings will either fail to act according to predictions, as when boards do not implement the practices well enough, or will have counter-measures against the predictions, as when CEOs manipulate the board. So in a world of actual humans acting as directors on boards and CEOs of firms, does the advice hold true?

This is what we (Andrew Shipilov, Yeonsin Ahn, Timothy Rowley, and me) examined in research published in Journal of Organization Design. Our approach was simple. We had data on firm adoptions of 11 different governance practices and a series of firm outcomes, and we focused on Return on Assets, Debt, and Dividends distributed to shareholders. These are outcomes that shareholders care about because they concern profitability, risk, and money returned to the owners. We used modern machine-learning techniques to find out which of the practices predicted these outcomes best.

So, what did we find? The best way to summarize our findings is that what works in equations does not work in practice. Hardly any of the 11 practices had any effect on the three outcomes. Two that had effects – and independent audit committee improved profitability and director evaluations increased dividends – suggest that a major mechanism contributing to impact is whether directors have reason to pay close attention to the firm and counter-act selfish CEO actions. That is at least some encouraging news, though overall our findings suggest that much governance advice is hot air.

Shipilov, Andrew V., Yeonsin Ahn, Henrich R. Greve, and Timothy J. Rowley. 2024. The Impact of Governance Practices on Firm Outcomes: A Machine-Learning Exploration. Journal of Organization Design, forthcoming.

Life of The Disenfranchised Entrepreneur: Discrimination, Success, and Stigma

We love the stories of entrepreneurs who advanced from poverty to success and riches. How much do these stories reflect reality, and not wishful thinking? What are these stories missing? Recent research by Leandro S. Pongeluppe published in Administrative Science Quarterly examines a more modest – and so more realistic – story of social advance through entrepreneurship, and it offers a piece of realism and some important lessons.

The story of entrepreneurship being the path to success is quite realistic because poverty is often a result of labor market discrimination, so there is no way out except through entrepreneurship. Labor market discrimination is a powerful exclusion because employers discriminate against those who are visibly different: often minorities or women. In this research, such discrimination was against people living in the Brazil slums (“favelas”), who are easy to distinguish by their language dialect and address.
 

Entrepreneurship by the disenfranchised is not easy, though, and the whole foundation for the research was a set of programs teaching favela residents skills for forming and operating businesses. The skills were useful, because those who received the training were able to start businesses more often than their peers. Importantly, this happened even though those who received the training were no more likely to get a job after the training than those who did not—despite the fact that training someone for running a business also makes them more capable as an employee of a business. Labor market discrimination is a powerful exclusion.

So, with more entrepreneurship and higher income, after training we have a nice story of success, right? That’s where the traditional success story is incomplete. We are forgetting that discrimination against groups happens because they are not supposed to be successful, so when they succeed against the odds that’s wrong too in the eyes of others. They carry the stigma of their disenfranchised background in the favelas, and this stigma is imposed more strongly by others the more successful they are. More income means more prejudice and more stigma from those who are fortunate enough to be born to a middle-class life.

What to do? Obviously, training the disenfranchised for entrepreneurship is still right, and equally obvious it is hard, or impossible, to control the irrational responses of others. Even the old stories of entrepreneurs who advance from poverty are not enough. But we know the reason, of course. In the novels and the movies, those entrepreneurs looked just like the audiences. The stigma will not fade until we tell more stories of favela dwellers and minorities who succeed through entrepreneurship, and we learn to celebrate them too.

Pongeluppe, Leandro S. 2024. The Allegory of the Favela: The Multifaceted Effects of Socioeconomic Mobility. Administrative Science Quarterly, forthcoming.

Hire Those You Trust! But Actually It Is More Complicated

What is the relationship between trust and hiring? We all know the simple answer. Employers hire those who seem trustworthy, so trust and hiring are pretty much the same thing. But there is also a more complicated answer, and that one involves looking at how national cultures differ in the general trust levels. Suppose that two cultures differ in the level of trust – will employers in the high-trust culture hire more people than those in the low-trust culture? No, of course not, employers hire as many people as they need. But social trust levels still matter.

How they matter is the topic of research by Letian Zhang and Shinan Wang published in Administrative Science Quarterly. It involves a novel idea and some nifty analysis, and fortunately it is easy to summarize. Trust does not mean hiring more people, but it does mean hiring different people. The reason is that low social trust is associated with hiring for a specific job, with less expectation that the employee can develop new skills. High social trust means hiring for the firm, with an expectation that the employee can develop new skills and fill other jobs. High trust, then, means hiring for foundational skills rather than advanced skills. It means hiring an analyst for general math ability more than for skills in Laplace transformations.

This idea raises two questions. First, is it true? Using data on job postings from the European Union countries, Zhang and Wang found that it was indeed true. Employers in nations with high social trust hire based on more foundational skills than nations with low social trust. Moreover, the same multinational firm would hire more based on foundational skills in nations with high social trust than in nations with low social trust, so the same relation holds within employers as well. Job characteristics such as university education or work experience requirements reduced this effect but did not make it go away.

Second question, is it consequential? Well, look at the figure above. Nations in Europe differ quite a bit in social trust levels, as the horizontal scale shows (the range is from zero to one). The vertical scale is not so easy to understand, but perhaps it helps to know that a difference of 0.6 is less than the difference between attentiveness and mathematics (foundational skills), and electricity principles and Java (advanced skills). The figure shows that the average hire in each nation differs significantly by the trust level.

There are many possible consequences of these differences. We don’t yet know whether they all happen, but it is valuable to check each one. Hiring in high-trust nations means hiring for the long term and for multiple roles, giving greater room for personal growth and firm flexibility. Hiring in high-trust nations means less emphasis on specific expertise and credentials, so symbolic collection of certificates to get hired is unnecessary. Hiring in high-trust nations allows more diversity in teams doing a single task and better communication within teams, increasing creativity and productivity. Employers in low-trust nations may have lower access to all these benefits.

We do not know whether all these differences result from different levels of societal trust. Now that we know how societal trust changes hiring practices, we should be aware that they might exist, and both employers and employees might think of employment practices and careers differently.

Zhang, Letian and Shinan Wang. 2024. Trusting Talent: Cross-Country Differences inHiring. Administrative Science Quarterly, forthcoming.

Networks and Discrimination: Why Female Artists are Disadvantaged, and What They Can Do About It

It is not easy being an artist. Recognition of talent and creativity can be slow, sales only happen in small galleries, and initial sales are domestic and even local. The last thing artists need is discrimination in addition, but that is exactly what female artists get: a recent investigation showed that comparable paintings sell at a 42 percent discount if the artist is female.

Is there anything that can be done about such discrimination? This was the question that we (JungYun Han, Henrich R. Greve, and Andrew Shipilov) wanted to address with data on Korean artists and their exhibitions abroad. We found that female artists were less successful in exhibiting abroad, as expected, but that difference was not our main interest. Instead, we wanted to know whether we could identify anything in their careers that reduced or eliminated their disadvantage. We could.

An important step in the careers of many artists is a residency stay in which they share workspace in studios provided by the residency and also get to meet other junior and senior artists to gain inspiration and advice. Residency programs help artists succeed, which is exactly their purpose, but unexpectedly this was only true for female artists. Education in an elite art school provides top-notch technical training and artistic appreciation. Elite education helps artists succeed, which is exactly its purpose, but again there was a surprise: it benefited female artists more.

What is going on here? The best explanation for these two effects is not training, but social networks. Art residency programs and elite schools connect artists with others who can provide advice on how to approach galleries and even direct contacts to them. The best explanation for the male and female difference is that female artists have more to prove, so the benefit from a network tie is greater for them. In network effects we often see such effects – those who are accepted purely by who they are gain some benefit from a good social network, but not nearly as much as those who are discriminated against and need a social network to be introduced to the right people and become recognized for their achievements.

These effects offer clear advice for how to help women succeed in art, and probably also in other kinds of entrepreneurship and work. They also offer a warning to society because such differences can only exist because of discrimination.

Han J, Greve HR, Shipilov A (2024) The liability of gender? Constraints and enablers of foreign market entry for female artists. Journal of International Business Studies.

If Women Can’t Network and Women Can’t Move, Why is it Better for Women to do Both?

Among the many disadvantages that women have at work, here is one that is often overlooked: they have fewer opportunities to form beneficial networks, and even if they succeed, they gain less benefit than men. This matters greatly for their careers because network ties to coworkers help employees gain skills,learn about opportunities, and execute plans. A particular disadvantage is women’s problems in getting brokerage positions in network. A network broker is connected to people who are not directly connected to each other. Brokers gain separate pieces of information quickly and can quickly assemble them to form opportunities.

Why is it hard for women to become brokers? To begin with, it is hard for anyone because it requires reaching beyond the immediate work group. It is also hard because people are suspicious of brokers and may be reluctant to share information with them. In fact, the most effective brokers are those who are not known to be brokers. For women, these suspicions are especially strong because of the gendered belief that women maintain closer relations with proximate friends and coworkers. As a result, they gain less access to brokerage and less benefit from brokerage.

Changing jobs has many of the same disadvantages, even if the job change is just a reassignment ordered by the employer. But here is the interesting part: when women move, the brokerage disadvantages disappear. Both disadvantages. Women who move gain brokerage positions just as easily as men who move, and women who move obtain the same performance benefits as men who move. This is a new discovery from a paper by Evelyn Zhang, Brandy Aven, and Adam Kleinbaum published in Administrative Science Quarterly. Their idea, which turned out to be true, is that moving gives “license to broker” because network ties in the new workplace are necessary, and maintaining contacts with the prior workplace is expected – especially for women, who are supposed to be more stable network partners than men (again a gendered belief). So in this case two wrongs make a right.

Interesting? Let us not see this as encouraging information though. Even when workers benefit from gendered beliefs like this, the beliefs still create a warped workplace where opportunities and rewards are unfairly distributed.

 

Zhang,Evelyn Y., Brandy L. Aven, and Adam M. Kleinbaum. License to Broker: How Mobility Eliminates Gender Gaps in Network Advantage. Administrative Science Quarterly, forthcoming.