Reviewing Economics & Business books,
as input for Big Data Economics
Let me share with you some titles:
-1) Planet Google by Randall Ross
This book reviews the growth of Google, as an addition of goals followed through, starting with indexing the information of the Internet to make it searchable, and going through Youtube, Googlemap, etc...
The book is quite well structured, allowing to understand the systematic pursuit of business objectives rooted in facts (science & engineering, market). The exploration and chartering of the world's information, as completely as possible, performed by google is an amazing piece of work, and this book describes it very well.
Interesting read for anyone interested in the economics of big data, naturally...
-2) Googled, the end of the world as we know it, by Ken Auletta
This book has a very different approach to the one above. It is more a classical business story told well, with details of interest. I have liked the beginning where the author sketches a biography of the two founders, and their family background in advanced mathematics for one (father lecturing on Riemannian geometry, mother with advanced mathematics & biology degrees) and computer science for the other (two parents university professor & lecturer).
-3) An Introduction to Sustainable Development, by Peter P Rogers, Kazi F Jalal & John A Boyd
This book has a few chapters which connect well with the problems of starting economic analysis where market prices may not be available or not be the only criterion:
their chapter 9 on the economics of sustainability, chapter 10 on externalities, valuation and time externalities, and chapter 11 on natural resource accounting.
However, it is not a toolbox from which one can extract what we need for Big Data Economics, at best an eye opener, and an encouragement to develop models in certain directions, proven to be usable in a domain different from Big Data, with the commonality that it still has some "terra incognita" features yet to be explored and mapped.
-4) Fighting the banana wars and other Fairtrade battles by Harriet Lamb
This book may interest you because the Fairtrade scheme brings a new set of economic standards and criteria in the food market ( and other) arena: respect the planet, respect the people (producers or consumers), introduce sustainability and risk reduction in an otherwise fierce competition with commodity price volatility.
Why is it relevant to the analysis of economics for big data? For the reasons above, but also and probably more importantly because big data as source data (source data sets, flow) is the commodity of the digital age, and it is interesting to build on the experience gained in the area of physical commodities and ways to address their price volatility (and potentially chaotic availability depending on crops, good or bad weather, natural disasters).
-5) Marx, the key ideas, by Gill Hands ("teach yourself" series)
Do not smile before you know why I put this book here.
I started from the reflection that today the economics of the digital markets is governed by a production equation adding the costs of software to the costs of networks, and most of the time ignoring data costs or not paying much attention to them.
Marx may be criticised: his ideas may have led to human catastrophes. However as an economist he managed to convince everyone that Labour aspects (labour costs, workers' condition, etc) needed extra care in the age of the industrial revolution. He added Labour as a key variable into the production equation where other costs could be called "Kapital" and Assets.
Hence if we want to highlight "source data" in a context where "my software is valuable and your data needs to be free to me" or where yet another conflicting view says "my network is valuable, and your software needs to pay for consuming it", we may learn from how Labour as an economic parameter was recognised as a key driver of the coal & steam age.