Firm organization and the adoption of information and communication technologies

Project Information

ORGANDICT

Grant agreement ID: 101076790

DOI

10.3030/101076790

EC signature date 16 March 2023

Start date 1 August 2023

End date 31 July 2028

Funded under

• European Research Council (ERC)

Total cost

€ 1 486 378,00

EU contribution

€ 1 486 378,00

Coordinated by

EBERHARD KARLS UNIVERSITAET TUEBINGEN
Germany

Periodic Reporting for period 1 - ORGANDICT (Firm organization and the adoption of information and communication technologies)

Reporting period: 2023-08-01 to 2026-01-31

Summary of the context and overall objectives of the project

Since the industrial revolution, novel technologies have repeatedly reshaped how we work and do business. From the steam engine to electricity to computers and the internet, each wave of innovation has transformed our economy in fundamental ways. Currently, machine learning (ML) and artificial intelligence (AI) are reshaping the economy.
Breakthrough innovations affect three critical areas: firms’ productivity and innovative capacity; firms’ internal organization and the organization of their supply chains; and the implications for workers’ careers and wages. While the ML and AI transformation is still underway, the last major technological revolution—the rise of information and communication technologies (ICT), such as computers, internet, and software—can provide important insights into its likely impacts.
This project tackles a major gap in our understanding of the economic effects of ICT by asking three key questions: How does ICT adoption change the way firms organize themselves internally, and what does this mean for firm performance and employee outcomes? How does embracing digital technologies affect how firms integrate into global value chains, and what impact does this have on domestic workers, their employment prospects and wages? And how does ICT change the way firms source innovation from abroad, possibly affecting domestic innovation capacities?
Previous research has been limited by incomplete data—studies typically look at only one piece of the puzzle at a time. Our project breaks new ground by creating comprehensive datasets that combine detailed information about firms' technology use, their global value chains, financial performance, and patent activities, together with complete information about their employees' characteristics, tasks, and wages. Rather than just identifying what happens when firms adopt new technologies, we dig deeper to understand why and how these changes occur. This approach helps us uncover the economic mechanisms that drive technological transformation.
The insights from this research will help policymakers design better labour market, education, innovation, and trade policies. Firms will gain valuable guidance for developing strategies to navigate technological change effectively. By understanding exactly how digital technologies reshape firms and affect workers, we can better prepare for future technological waves while ensuring their benefits are broadly shared.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

High-quality data forms the foundation of any meaningful research on technology's economic impact. We have made substantial progress in assembling the comprehensive datasets needed to answer our research questions. First, we constructed a groundbreaking integrated dataset that links detailed employee information from German social security records with firm-level data on balance sheets, technology use, and internet infrastructure. This combination allows us to disentangle how technological changes affect firms, their organization and productivity, and how changes affect individual workers, their tasks, careers, and wages. Second, we created another novel dataset combining information on German firms' international trade in both goods and services with business registry data as well as production and input use surveys. This provides unprecedented insight into firms’ integration into global value chains and the implications for domestic employment. Third, we successfully completed complex administrative procedures to obtain permission for linking social security data with services trade information from Germany's central bank—a significant achievement that opens new research possibilities for the understanding of the heterogeneous effects of globalization on individual employees.
Our empirical analyses are currently underway. Preliminary results reveal important findings about how ICT and global value chain integration affect employees differently depending on their skill levels and roles within firms. These insights are particularly relevant as we consider the potential impacts of new AI-based digital technologies on the workforce.
Beyond our specific research goals, we are developing innovative machine learning techniques to solve common problems researchers face when working with administrative data, such as changes in job classification systems over time. These methodological contributions will benefit the broader research community studying technological change and labour markets.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Our research promises to deliver insights that go far beyond current understanding of how technology transforms the economy. By examining the impact of ICT at the individual worker level rather than just looking at firms or local labour markets, we can identify which types of workers benefit from technological change and which face challenges. This detailed understanding will enable policymakers to design targeted support programs and educational initiatives that help workers adapt to technological transformation.
Our findings will also reveal the specific mechanisms through which ICT affects firm organization and boosts productivity—knowledge that firms can use to complement their technology investments.
Perhaps most importantly, our research provides a roadmap for navigating the current AI revolution. By understanding exactly how previous digital technologies reshaped work and business, we can anticipate similar patterns with artificial intelligence and machine learning. This foresight allows both policymakers and firms to prepare proactively rather than simply reacting to change.
The methodological innovations that we are developing will also have lasting impact beyond our specific research questions. Our machine learning approaches for handling complex administrative data will help other researchers working with similar data.