Digital transformation & strategy

Hardly any other topic is currently as omnipresent in the economy and entails as many challenges and opportunities for companies as the digital transformation (Porter & Heppelmann 2014; Downes & Nunes 2013; Lucas & Goh 2009; Matt et al. 2015). In order to adequately address these challenges, companies are developing and introducing digital transformation strategies (Dremel et al. 2017; Stockhinger & Teubner 2018), launching digitalization programmes and implementing new management roles, such as that of a Chief Digital Officer (Lee et al. 2014; Singh & Hess 2017).

Within this research area, we examine the digitalization processes of organizations, in particular their structures, roles and strategies as well as opportunities and risks, primarily enabled by the new IoT technologies. The aim of this research area is both to question existing management practices and to find new approaches.  

Big Data & Analytics & Strategy

Big data and analytics (BDA) describes the increasing amount of data generated in the course of digitalization and the powerful analysis methods used to evaluate and utilize it. Early publications address the competitive effects of BDA (Davenport 2006: 3; McAfee and Brynjolfsson 2012: 62). As a result, a consensus is emerging in BDA research that the use of BDA increases competitiveness. However, much of this debate is based on simplistic and optimistic ideas (Caesarius & Hohenthal 2018: 130). To date, there has been a lack of in-depth studies on the strategic consequences of BDA, as the majority of studies focus on the technological functionality of BDA (Günther et al. 2017: 200) to solve operational problems (Grover et al. 2020: 272). Important questions that arise from this and currently remain unanswered include the following: How can BDA support established competitive advantages and/or create new competitive advantages? What are the risks if competition increasingly shifts towards 'price' due to similar BDA strategies and increasing efficiency? How can BDA lead to disruptive business model innovations? What risks arise when business models converge through the replication of technological best practices? How does the public discourse contribute to the positive portrayal and exaggerated expectations of BDA? What effect can such a discourse have on strategy development processes?

Corporate digital responsibility and technological responsibility

Megatrends such as digitalization and big data not only bring opportunities for companies, but also come with challenges. One such challenge is the regulatory gaps in the global and digital spheres that companies have to deal with. Multinational enterprises (MNEs) in particular have economic power similar to that of states and can influence regulatory gaps (Scherer & Palazzo 2011). In the context of digitalization and big data, strategies of technological responsibility are therefore becoming increasingly important, as they enable companies not only to exploit and create regulatory gaps, but also to address and close them for the benefit of their stakeholders (Schrage & Gilbert 2019). The topic of sustainability in the digital space is still in the early stages of development. Topics such as data protection, the ethical use of artificial intelligence, social working conditions in platform business models and fake news play a role here (Flyverbom et al. 2018; West 2019; Zuboff 2015). The aim of a final thesis on this topic is to analyze corporate strategies for technological responsibility. An empirical analysis could be carried out, for example, through a document analysis of sustainability reports and/or qualitative interviews with one or more companies, or by analyzing existing technology responsibility initiatives such as the Corporate Digital Responsibility Initiative of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection.