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Due to the young age of proptech, little is known about the dynamics of its expansion. In particular, there is limited agreement about a definition of “proptech,” while different categorizations are popping up. A severe lack of information emerges for the proptech scenario in Italy. The goal of this paper is to systematize multiple proptech maps in the attempt to create a framework for comparison of country-specific trends and an overarching definition of proptech. The research examines the evolutionary stage of the Italian digital real estate sector and compares it to the international context.

An in-depth analysis of 12 proptech maps at both national and international level was conducted based on online research. A list of Italian proptech companies was composed through multiple methods. A map was built for a cross-country comparison.

Each country or organization tends to develop its own categorization. This creates a multifaceted context where comparison and analysis are challenging. The Italian proptech sector seems underdeveloped compared to neighboring countries. Big room for improving the proptech business in this country still exists.

The results are valuable for proptech start-ups, business investors and well-established real estate actors to build on new entrepreneurial initiatives. The opportunity to advance proptech mapping and categorization emerges as a prospect for future research.

This research adds an overview of cross-country proptech categories and proposes the first analysis of Italian proptech. This will contribute to support entrepreneurial opportunities.

Previous research on automation and job disruption is only marginally related to the real estate industry and its characteristics. This study investigates the effects of digitization on jobs in German real estate sector, in order to assess the proportion of jobs threatened to be replaced by automation. Since Germany is the largest EU economy insights for the German real estate market allow a first approximation for Europe.

An extensive database of the German Federal Employment Agency containing job definitions and occupation titles is matched with real estate criteria to create a subset with the relevant real estate occupations. This data is combined with a database of the German Institute of Employment Research reflecting to what extent tasks within jobs can be automated by current technical capabilities.

For the 286 identified occupations within the real estate sector a weighted average of 47 percent substitution probability through current technological capabilities is derived for tasks within the examined occupations.

This contribution indicates the extent of the structural change the real estate sector has to face due to digitization: One out of two real estate jobs will have to be re-created.

This research quantifies the magnitude of the job killer aspect of digitization in the real estate sector.