Fairness Heuristic Theory & Networks

In my last post, I discussed Soft Systems Methodology, which I am using to explore the role of fairness in collaborative networks. In this post, I share the basic premise of Fairness Heuristic Theory. In my next post, I will talk about what I have been learning about how network leaders view their network culture.

Fairness Heuristic Theory

E. Allan Lind and his colleagues first proposed the Fairness Heuristic Theory (FHT) in 1992. In brief, the theory is that perceptions of fairness act as a "rule of thumb" for measuring whether one should invest in a collaborative effort. If one perceives that fairness will reign within that collaboration, one is vastly more likely to to lend one's resources and--more importantly--one's identity to the effort, according to this theory.

According to Lind, the most essential aspects of people's perception of fairness are rooted in whether one feels valued and has standing as part of the group. They render this judgment based on feelings of inclusion, ability to effectively raise concerns, and sensing respect in the way others treat them. In cases where the person feels they have standing and will be treated fairly, they will willingly become part of a whole.

Fairness Heuristic Theory in Collaborative Networks

FHT comes out of organizational science, and particularly explores how employees might become willing collaborators in the plans of their boss. Why, for example, should someone put in long hours at work rather than please themselves with more spare time? Why should they do a job very well rather than do what is easiest for them personally? Fair treatment (including a sense of standing in the group), Lind and others argue, is a significant part of the answer.

But the tension between the part and the whole is, I argue, at the heart of collaborative networks as well. A network is not a top-down structure giving marching orders to soldiers, it is a bottom-up gathering of diverse perspectives on a complex problem. Members must autonomously agree to collaborate to achieve a purpose, even while their own individual purpose is distinct.

Consider the example below, in which a network has formed to end malnutrition. Member A experiences the part/whole tension in that this organization (which focuses on childhood malnutrition) must be willing to lend its identity and resources to some efforts that are beyond the scope of its own concern: for example ending malnutrition among the geriatric population. Members B and C experience the part/whole tension differently, in that their mission encompasses many things beyond the scope of the network. In this sense, the network competes with other valuable work they might do.  In all three cases, there may be times that the good of the whole network actually runs counter to the member purpose: for example perhaps in some cases, increasing arable land decreases rather than increases hunger--putting Member B in a dilemma.

Now, when these members are asked to participate in the network, they are confronted first not with an outcome, but with the question of participating--that is, collaborating. They must decide whether, in essence, to write a check that consists of their identity and resources for a product (the end of malnutrition) that is a very long way from delivery. They could choose not to participate, or, as those of us in collaborative networks know very well, they might just to "participate" just enough to stay on the mailing list so they stay in the know, but without truly lending their identity and resources to the network's purpose. But they just might choose to participate at a very high level, which, as it happens, is the only way they can achieve the shared purpose.

Unlike an organizational setting, there is not a strong authority figure who can compel at least some level of participation. Members must decide to do it entirely themselves, making fairness even more essential.

The point of my research is to test perceptions of fairness among network stakeholders and to develop feasible recommendations to improve perceptions of fairness. Ideally, subsequent research would revisit both the desirability and feasibility of implementing them, and determine if resultant improved perceptions of fairness do indeed improve member willingness to collaborate deeply.

I will return to Fairness Heuristic Theory later, but my next post will share what I am learning already from network leaders about their network culture. This is important because, without understanding the landscape, it would be very challenging to make recommendations that are both relevant and feasible.