How ‘movers and shakers’ move and shake
We know them well, those people who make things happen. Leaders, entrepreneurs, creators, builders, movers and shakers. Those who see opportunities where others might not, or take risks when others won’t. Some have built – or are building – global empires. Think Elon Musk or Jeff Bezos. Others make things happen at a smaller scale, perhaps in less glamorous industries or with a preference to avoid the limelight. But they are active: building a business, a political movement or fighting for a social cause.
Economists have been slow to understand what makes successful movers and shakers. Our theories generally assume that where profitable opportunities exist, a competitive market will allow entrepreneurs to fill the void. We care little about explaining the characteristics of those entrepreneurs who see the gap in the market first, and then manage to beat the competition. That is, until now.
A forthcoming paper in the Quarterly Journal of Economics attempts to do just that. The authors, Robert Akerlof (son of Federal Reserve Chair Janet Yellen and Nobel Prize winner George Akerlof) and Richard Holden, construct a mathematical model that has two types of agents: managers (or entrepreneurs – the ‘mover and shaker’) and investors. The managers form social connections with investors and then bid to buy control of an investment project. The winning bidder then has to make other investors aware of the project, and these investors then have to decide whether to invest in the project or not.
The model shows that of the many managers that start, there is only one ‘mover and shaker’ that emerges victorious, and that this manager earns a high payoff for doing so. The noteworthy contribution is that the success of this ‘mover and shaker’ depends on their network: “the most connected manager ends controlling the projects”. Other qualities, like a manager’s skill at running the project, their talent in communicating with investors, and the amount of capital they have personally, will also influence the outcome. But, most importantly, a larger network of connections may often compensate for a deficiency in one of these other dimensions.
The authors use William Zeckendorf, a well-known US property developer in the 1950s and 1960s, as a case in point. Zeckendorf was responsible for many ambitious building projects in the US and Canada, and his autobiography attributes his success to his social connections: “the greater the number of … groups … one could interconnect … the greater the profit”.
Akerlof and Holden’s model provide theoretical support for the increasing body of empirical evidence which shows that social networks matter, now and in the past. My PhD student, Christie Swanepoel, have found, for example, that those settler farmers in South Africa’s eighteenth-century Cape Colony that were well-off also had extensive networks of debt and credit.
What is clear, though, is that it is not necessarily the number of connections that matter, but the quality of those connections. In a recent summary of the literature on social networks, Matthew Jackson, Brian Rodgers and Yves Zenou argue that the network structure of a society can have large implications for how innovation and new ideas spread through it. “Not only does the average number of relationships per capita in a society matter, but also higher variance in connectivity matters since highly connected individuals can serve as hubs that facilitate diffusion and contagion.”
Understanding the network structure of a society is, therefore, essential for businesses and policy-makers. At the most basic level, marketers may find that a customer’s decision to buy is heavily influenced not only by the price or quality of the product, but who their customers are shopping with. (My grocery basket looks remarkably different when I do the groceries with or without my wife.) At a more macro level, policy-makers should realise that networks can have a significant impact on the success of policies ranging from education, public health, segregation, finance, and even policing. Let’s take the latter as an example. Movers and shakers operate, of course, not only within the bounds of the legal economy. The mafia is a classic example of the success of an interlinked network. Using Swedish criminal records, two researchers at Stockholm University have shown that if the police target ‘key players’ – i.e. the mafia bosses – in the criminal network, they can reduce crime much more than if they had just focused on tracking the most active criminals or, worse, just tracked any criminal without considering their position in the network. Using network analysis in their crime fighting strategy, they suggest, the police can reduce crime by 37%.
From criminal networks to political networks to business networks, identifying movers and shakers, and the reasons for their success, can be a very useful strategy in fighting crime, securing votes or boosting profits. But networks vary across many dimensions, and so too its applications; size, clearly, isn’t everything. Understanding network structures in a diversity of social settings will be a fruitful avenue for future interdisciplinary research, fertile ground for the next academic ‘mover and shaker’.
*An edited version of this first appeared in Finweek magazine of 11 August.