The research group is concerned with the possibilities of Big Data analyses: from the generation of new data sets to the combination of already existing data sets and the application of Big Data methods.
Today, a wealth of new data is becoming available from such sources as sensors, the Internet of Things, and the use of social platforms. This geometric rise in data volumes is leading to the increasing use of big-data analyses with their ability to exploit untapped potential in many fields of business. However, generating this data and making meaningful use of it requires special technologies, approaches and systems. The IW’s Big Data Analytics Research Group deals with the different aspects of big data but with a special emphasis on economic questions.
Our main points of focus
- Structured and unstructured data generated by new methods and technologies, such as Internet searches, website content, social media information and price information from Internet shops and auction platforms
- New ways of linking data sets
- Application of big-data methods such as machine learning to economic questions
- Application of big data in business research
- Identification of statistical twins by means of survey data, Internet data and machine learning (companies and households)
- Expanding on official statistics, for example, for the labour market
- Analysis of regional infrastructures
Example of current research work
The research group uses various analysis methods and approaches. In principle, Big Data methods can be applied to all relevant economic questions. One example is the network analysis based on text analysis, here exemplarily with regard to the German actors in the Covid-19 research.
The collection of regional price data by means of web scraping is another project of the research group. As an example, the prices for heating oil at zip code level in March 2021 are shown here.
The analysis of social media texts is also part of the research group's method portfolio. The following application example is a tonality analysis of tweets on the topic of artificial intelligence in 2018 and 2019.
Current publications can be found on the pages of the respective employees.
The Big Data Analytics research group is continuously accompanied by an advisory board. This committee consists of persons from science as well as from the free economy in order to develop the research group in a target-oriented way.
Permanent members of the advisory board are:
- Prof. Michael Hüther (Direktor, Institut der deutschen Wirtschaft)
- Dr. Hans-Peter Klös (Leiter Wissenschaft, Institut der deutschen Wirtschaft)
- Dr. Karl Lichtblau (Geschäftsführer, IW Consult)
- Christin Schäfer (Geschäftsführerin, acs plus und Mitglied der Datenethikkommission der Bundesregierung)
The Corona pandemic and the measures taken to contain the virus have delivered an asymmetrical shock to German business. This asymmetry is exemplified by the effects on the retail trade, an import ant part of the nation’s economy.
With the advent of electronic publishing and the Internet, the traditional business model of academic publishing, based on subscription fees paid by the readers/libraries (closed access [CA] journals), has to some extent been replaced and to some extent complemented by different types of open access (OA).
Data is an important business resource. It forms the basis for various digital technologies such as artificial intelligence or smart services. However, access to data is unequally distributed in the market. Hence, some business ideas fail due to a lack of data sources.
The COVID-19 measures of the federal and state governments have at times massively affected public life in Germany. The ban on contact has temporarily restricted the freedom to pursue a profession, the freedom of trade, compulsory education and religious freedom.
Economy Gross domestic product (GDP) figures for Germany’s 16 federal states are currently only published twice a year, with no quarterly figures available. This makes it impossible to pinpoint the exact timing of turning points in the economies of individual states.