Christian Hovestadt

(University of Cologne)

Pascal Budner

(University of Cologne)

Zoom Meeting

Artifacts becoming Actors – On the Trail of Digital Agents

Janek Richter

(University of Cologne)

Janina Weingarth

(University of Cologne)

Zoom Meeting

Becoming agile can take many routes - exploring identity in agile transformations

Many companies have embarked on agile transformation journeys across industries with similar goals such as customer centricity, fast identification of and reaction to market changes, increased innovation, high degree of self-organization, and flat hierarchies. Agile transformation challenges and changes what it means to be a manager and leader, how work is organized between business and IT departments, and finally the organization itself. This changes individual work identities and collective professional identities of both managers and employees, as well as organizational identities. We conduct two in-depths case studies of incumbent companies that are undergoing an agile transformation in the insurance and automotive industry. We explore when and how both business and IT managers and non-managers engage in identity work connected to the agile transformation at the individual, collective, and organizational level. We observe identity work along three dimensions: intentionality, trajectory across levels of analysis, and tensions. We add to the identity work literature by investigating identity work in an industry-spanning phenomenon, with a unique integrated analysis of the individual, collective, and organizational level while comparing different industry contexts.

Alexander Herwix

(University of Cologne)

Zoom Meeting

Taking the Next Step in Design Science Research: Toward a Research Agenda for Tool Support

Design science research (DSR) has become an increasingly accepted research paradigm. Nevertheless, there are still pragmatic challenges associated with conducting and publishing rigorous and relevant DSR. Research on tool support in DSR has been emerging as a solution-oriented approach to overcoming these challenges. However, most of the work so far remains disconnected. This is problematic because any single study is unlikely to provide a final solution to the complex socio-technical challenges that tool support in DSR is aiming at. A research agenda and concerted research efforts are needed to lift the full potential of tool support in DSR. This paper works toward closing this gap and presents insights from a literature review and an in-depth analysis of expert interviews (n=12). We aim to clarify the multifaceted nature of tool support in DSR and develop a comprehensive research agenda with the goal of improving the effectiveness and efficiency of DSR.

Kai Spindeldreher

(University of Cologne)

Zoom Meeting

Ecological Sustainability or Capitalistic Exploitation? Disputes in the Sharing Economy Discourse in Germany

The sharing economy is perceived as a potentially disruptive business model due to its ability to leverage under-utilized resources and network effects through digital platforms. The emergence of the sharing economy has spurred controversial debates on its economic, ecological and societal impact. Various stakeholders such as sharing economy intermediaries, incumbent firms, and regulators engage in this discourse with various, at times opposing standpoints. Stakeholders try to gain legitimacy by justifying their positions on particular benefits and drawbacks of the sharing economy (e.g. by relating to environmental sustainability, competitive conditions, labour rights). However, comprehensive theoretical understanding of the sharing economy discourse is still lacking. In this paper, we address this issue by examining the discourse on the sharing economy in Germany. We find that 12 stakeholders groups engage in the discourse. The stakeholders (combined) hold 14 positive standpoints and 12 negative standpoint which are grounded in six different value systems. We identify disputes that exist across stakeholders and value systems. Based on our findings, we derive a typology of dispute types which may be generalized towards similar public controversies over disruptive digital business models.

Florian Pethig

(University of Mannheim)

Zoom Meeting

Helpful or Harmful? Negative Behavior Toward Newcomers and Welfare in Online Communities

New members are important for the survival of online communities. However, hostility toward newcomers is pronounced in many online communities, often exercised through downvotes, rejections, and negative comments from established members. Online communities have realized that such negativity can take a toll on newcomers. In this paper, we study a new intervention aimed at reducing hostility toward newcomers: a “newcomer nudge,” which informs members when they are interacting with a newcomer post and nudges them to be more lenient toward its author. We use a natural experiment research design and analyze 5,027 newcomer posts published in a 90-day time window before and after the introduction of the nudge. We observe a strong increase in upvotes and number of responses as well as a decrease in negative sentiment in the responses. Taking advantage of the panel data, we find that newcomers who are socialized with the nudge are significantly more likely to post again in the following 12 months than newcomers socialized without the nudge.

Daniel Fürstenau

(Free University of Berlin)

Zoom Meeting

AI and Scale-Up: A Scaling Perspective on AI Startups

The purpose of this talk is to understand scaling differences between AI startups and other digital startups, especially platform and professional service startups. An AI startup is a young, growth-oriented firm focussing on innovative behavior using AI as the core of its value creation and capture. Scale-ups are firms with growth rates in sales revenue, employee count, or profit of twenty percent per year over three consecutive years. While previous research has illuminated important scaling factors for digital startups such as digital infrastructure, knowledge, and access to funding, understanding scaling differences between AI startups and other digital startups, if any, is lacking and would be important to inform investment decisions, mitigate risks, and realize technological potentials.

Using Geoffrey West’s theory of universal scaling laws as a background, we perform a large-scale analysis of scaling behavior of ~2,000 AI startups, ~7,250 platform startups, and ~10,000 professional service startups using Crunchbase data. For a selected sample of these startups, we perform a critical resource analysis comparing factors related to their digital infrastructure, including analytics usage and scope of services, knowledge, including technological talent and managerial capabilities, as well as funding, including investor and regional network.

Our preliminary results indicate scaling differences for employee x revenue and employee x funding between AI startups and professional service startups, while differences between AI startups and platform startups are less pronounced. AI startups on average only need around half as many employees for generating $1 in additional revenue than professional service startups. The ß for employee x revenue is below 1.0, indicating sublinear scaling. The ß for employee x funding is above 1.0, indicating superlinear scaling. The critical resource analysis gives additional insights into driving factors for scaling and shows differences in some scaling factors especially related to digital infrastructure and knowledge.

Above all, our research stimulates thinking about the differences between AI startups and other types of startups. Differences of some scaling factors in the comparison of AI startups and other digital startups also calls for future theory building on what makes AI startups different in their operating conditions and architecture from other types of digital startups.

While previous research has considered scaling, our analysis adds to the knowledge base a large-scale account of scaling in digital startups, especially considering differences between AI startups and platform and professional service startups. The results address differences in the conditions of AI startups enabling or restricting scaling their operations.