Appendix 4: Emerging Global Frameworks related to Data Business

In the data economy, the proliferation of big data, analytics and AI has led to the creation of information intensive services where information interactions exert the greatest effect on value creation. Thus, a new category of business, ‘Data Business’, may be envisaged that collects / manages / or otherwise manages data, and meets certain threshold criteria. i.

One study 59 developed a nine-factor framework for data-based value creation in information-intensive services. The factors include (1) data source, (2) data collection, (3) data, (4) data analysis, (5) information on the data source, (6) information delivery, (7) customer (information user), (8) value in information use, and (9) provider network.

Globally, such a concept of defining a new category of ‘Data Business’ is only emerging. Here are a few examples of related global taxonomies.

1. Bureau of Economic Analysis (BEA), USA definition of Digital Economy 60 – BEA in a 2018 working paper includes the following categories under Digital Economy: i.

ii.

Digital-enabling infrastructure needed for a computer network to exist and operate – computer hardware, software, telecommunications equipment and services, structures like data centres, IoT, and support services e-Commerce – digital transactions that take place using that system – Business-to-business (B2B) e-commerce, Business-to-consumer (B2C) e-commerce, Peer-to-peer (P2P) e-commerce

iii.

Digital media – the content that digital economy users create and access

2. OECD classification of data-enabled services 61 – In a 2018 paper on recording and measuring data, OECD categorizes data-enabled services as follows: i.

Providing services for free or at very low prices to gather data of users which are subsequently used to detect behavioural patterns to provide other producers with targeted advertising services (like Google Ads, Facebook, etc.), or to offer other services (e.g. using information from payment systems etc.)

ii.

Using data generated as part of the primary production process, to improve the efficiency of the internal operations and/or to detect behavioural pattern to

59 Chiehyeon Lim et al., “From data to value: A nine-factor framework for data-based value creation in information-intensive services”, International Journal of Information Management, Volume 39, April 2018, Pages 121-135 60https://www.bea.gov/sites/default/files/papers/defining-and-measuring-the-digital-economy.pdf 61http://www.oecd.org/officialdocuments/publicdisplaydocumentpdf/?cote=SDD/CSSP/WPNA(2018)5&docLa nguage=En

iii. iv.

v.

vi.

3. support own sales. (like Amazon using dynamically generated recommendations, Walmart using analytics to optimise supply chain and pricing models.) Creation of new types of services by using and analysing big data. Provision of data-related services by collecting data from a vast number of different, mostly free, available data sources, normalising formats and providing access, with revenues from subscription or usage fees. Data facilitators, providers of data tools such as providing storage media, servers and workstations, data collection, analysis and visualisation software, database management software, encryption technology and software, data protection technology, etc. Creation of freely available information or knowledge by communities of people,

providing their contributions for free. (like Wikipedia, ResearchGate) A framework 62 for establishing the ‘data-drivenness’ of a market: i.

ii. iii.

Market definition (user centric) – an index of data-drivenness applied at the industry level would indicate, for instance, industry A has a high degree of datadrivenness and therefore mandatory data sharing is warranted, whereas industry B is only mildly data-driven such that there should be no mandatory data sharing. Study the demand side of the market: what drives users’ consumption utility? Study the supply side of the market: what drives objective measures of product quality?

62 Jens Prüfer, Friedrich-Ebert-Stiftung, "Competition Policy and Data Sharing on Data-driven Markets", 2020, library.fes.de/pdf-files/fes/15999.pdf