Capitalism and the principal-agent problem

Within a capitalist system, perhaps there’s more than one way to distribute moral hazard.  Here’s a concrete view of an investor-dominated approach at Apple, as compared to a managerial-dominated approach at Google.

Which principal-agent problem is more vexing? Stock-market returns are one, albeit imperfect, way of answering this question and since the initial developments, Google has far outperformed Apple. But that pattern is flipped if the time frame is restricted to the past year. So it won’t be known for many years to come if Apple or Google has a sharper financial strategy.

More importantly, though, how do these strategies impact the lives of everyday people? A capitalist system aims for the efficient allocation of capital, and indeed, workers have a better shot at seeing median wages increase when money is being put to its most productive use. So to an extent, how they fare under each system has to do with who is deciding where and how profits get invested. When managers reallocate profits, that reallocation benefits from the capabilities and knowledge that companies have built over decades, but suffers from the possibly poor incentives of managers. When investors are the ones reallocating profits, however, the scope of the reallocation can be broader, theoretically leading to more innovation; at the same time, those investors don’t have preexisting organizational capabilities and they may suffer from their own short-term time horizons.

Even if one considers the disparities in the shares of wealth accruing to labor and capital problematic—and there certainly are other strategies for addressing those disparities—making sure that managers and investors are dividing their responsibilities on capital allocation efficiently is critical for making the economic pie as big as it can be. And in that regard, while the problems of Google’s model are significant, they are also well appreciated. The excesses of Apple’s model and the widespread deployment of share buybacks are just as dangerous—and not nearly as well understood.

“Capitalism the Apple Way vs. Capitalism the Google Way” | Mihir A. Desai | July 10, 2017 | The Atlantic at https://www.theatlantic.com/business/archive/2017/07/apple-google-capitalism/532995/

The Atlantic: Capitalism the Apple Way vs. Capitalism the Google Way

Question for systems community: How to apply systems thinking?

Hi all systems people!

I am a recent graduate from Aalto University, Finland, where I studied in the interdisciplinary Creative Sustainability master’s degree program. Systems thinking was one of the bedrocks of the program, and we were fortunate to have David Ing teach us about systems sciences in one of our courses. David has been giving me advice after the course, and after a recent conversation about how to apply systems thinking, he requested that I post my question to SysCoI. So here goes.

My question is: How would you advice a recent graduate entering the workforce to apply systems thinking? Where would you start and what practices would you implement? I would also love to hear any stories of how you have applied systems thinking and practices to real life problem settings.

Thank you already in advance!

JP

 

Learning-by-trying

Working with social computing technologies can involve a lot of learning-by-trying.

While there is some similarities with “innovation configurations” research on implementation knowledge, this definition of learning-by-trying focuses on the integrating.

“Each configuration is built up from a range of components to meet the very specific requirements of the particular use organization. Configurations therefore demand substantial user input and effort if they are to be at all successful, and such inputs can provide the raw material for significant innovation” (Fleck 1994, 637–38).

Configuring social computing technologies don’t follow the characteristics of wicked problems. The issues are typically complicated rather than complex, and can be worked out with time.


Fleck, James. 1994. “Learning by Trying: The Implementation of Configurational Technology.” Research Policy 23 (6): 637–652. doi:10.1016/0048-7333(94)90014-0.