Brief substantive summary of the workshop and presentation of the main issues that were raised during the discussions
The workshop discussed how economics will look like in the future networked economy – how to measure it and how to construct new models for understanding it.
• Business informatics: Internet information is a part of decision making now. Big data, Open data change models of making decisions in the enterprise activity.
o There are integration challenges: Enterprise taxonomy, portal intranet database integration, data fusion and linking for knowledge base
o linked open data provides the following benefits: Open standards based on and vocabularies. Search and semantic content extraction. Lightweight data integration and several research projects.
• we still don't have clear models for profit sharing, for cloud based projects, because the transactions have the transnational characteristics of the Internet.
• Open government data is reliable data that opens up for the creation of new businesses that are quickly developing now.
• Businesses may be quicker than governments in adopting new economics tools, which can affect the split between applied micro- and macroeconomics.
• There is much worse availability to data about the Networked Economy, for example App development for cell phones, than there is for the traditional industrial economy.
o This can be critical, since we need to understand what happens when small organizations in the Networked economy disrupt sectors in the traditional industrial economy. One example is WhatsApp, a company with 300 employees, acquired by Facebook for 19 billion dollars. It disrupted the whole segment of the telecom industry employing many people. We need metrics that conveys the winner take all aspect of the networked economy, that we haven't used in manufacturing and other areas where there's some equality inequality within the company but still a decent baseline. In the networked economy we don't know where the bottom is and if anyone is making any profits.
o An interimistic indicator for the networked economy can be job ads. Something more substantial is needed in the long run.
• A lot of measurable traditional business is disintermediated by Internet businesses that we don’t know how to measure.
o It’s difficult to measure the full impact of the Internet economy on GDP growth. There is an Internet paradox: computers are visible everywhere except in productivity statistics.
o Macroeconomists need numbers that show the link between policies and outcomes. Such numbers can be constructed by research. One example is how OECD collected data on in which countries websites were hosted and were able to link that to the ease of doing business in those countries.
• The digital trace from people’s cell phone usage, e.g. calling patterns, offers a wealth of data an possibilities for constructing new metrics and models.
o This source of information might replace surveys over time.
o This brings up issues of property rights, who owns the data? Who can sell the data that is cogenerated at best by users and network operators. It is fundamentally changing the factors of production in addition to land, labour and capital, days the data data and how do we quantify that and a value that are going to be challenges.
o Cell phone providers are sitting on a lot of data and are beginning to do business with it.
• Telecom regulation becomes important for the development of economics when the telecom providers sit on massive amounts of data of interest to economists.
• Economics is almost discrediting itself, because we are seeing the same problem addressed by different economists coming up with very different results. And the reason you can pick so many different models in this digital economy is because there are so many different things that aren't really right about the classic economic models.
o For example, a lot of classic economic models assume you're at equilibrium. Yet we're talking about disruptive technologies that in many cases are cutting costs by 50 percent a year.
o Traditional economics assumes individuals are motivated by making money or saving money. But with social media we're finding that those kind of economics don't explain what's going on. People are spending a huge amount of their time just because they get psychic rewards or because they're part of a team on a game or because they like to be part of a community. New economics models need to take broader psychological aspects of reward into account.
• National Statistics Organizations need new roles in the new networked economy.
• Much of the data of emerging importance is controlled by private big data companies, such as Google or Facebook. It is of growing interest of governments to get access to that data for economics, but the companies can have incentives to not want to share the data.