A Scaling Perspective on AI Startups

Digital startups’ use of AI technologies has significantly increased in recent years, bringing to the fore specific barriers to deployment, use, and extraction of business value from AI. Utilizing a quantitative framework regarding the themes of startup growth and scaling, we examine the scaling behavior of AI, platform, and service startups. We find evidence of a sublinear scaling ratio of revenue to age-discounted employment count. The results suggest that revenue-employee growth pattern of AI startups is close to that of service startups, and less so to that of platform startups. Furthermore, we find a superlinear growth pattern of acquired funding in relation to the employment size that is largest for AI startups, possibly suggesting hype tendencies around AI startups. We discuss implications in the light of new economies of scale and scope of AI startups related to decision-making and prediction

On the Heterogeneity of Digital Infrastructure in Entrepreneurial Ecosystems

Digital infrastructure represents for startups in entrepreneurial ecosystems an important asset but also a major risk. Drawing on studies about digital entrepreneurship and ecosystems, we examine the determinants of the heterogeneity of startups’ tech stacks in ecosystems. Using publicly available data from the data aggregators Stackshare and Crunchbase, we identify popular endogenous categories in startups’ tech stacks. Then we conduct a visual network analysis and a multivariate regression analysis, utilizing the identified technology categories to measure the heterogeneity of the startups’ tech stacks. The analysis supports the propositions that firm age and increased funding are positively associated with tech stack heterogeneity, whereas funding rounds are negatively associated with tech stack heterogeneity. Implications of our findings on digital entrepreneurship and ecosystems are discussed

The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity

We analyze the growth, complexity, and generativity of the digital platform Otto.de, a revelatory case of a large German company that has opened up its internal IT platform to outside developers. We find indication for a superlinear growth pattern fueled by external developers and the introduction of microservices as well as the emergence of a structural separation within the platform. Furthermore, our research shows ways to explain the generativity of a digital platform based on the attention and activity received

A Social Citizen Dashboard for Participatory Urban Planning in Berlin: Prototype and Evaluation

Participatory urban planning enables citizens to make their voices heard in the urban planning process. The resulting measures are more likely to be accepted by the community. However, the parti-cipation process becomes more effortful and time-consuming. New approaches have been developed using digital technologies to facilitate citizen participation, such as topic modeling based on social media. Using Twitter data for the city of Berlin, we explore how social media and topic modeling can be used to classify and analyze citizen opinions. We develop a Social Citizen Dashboard allowing for a better understanding of changes in citizens’ priorities and incorporating constant cycles of feedback throughout planning phases. Evaluation interviews indicate the dashboard’s potential usefulness and implications as well as point to limitation in data quality and spur further research potentials

DATA GOVERNANCE STRATEGIES FOR DATA PLATFORMS – A MULTIPLE CASE STUDY IN NURSING CARE

It is long established that data from platforms can be useful for deriving patterned insights into people’s behavior and conduct. Data platforms are important in fields with limited data availability and strict regulatory and hierarchical structures, such as healthcare and nursing analytics. Hence, we carefully examine three forerunner initiatives in establishing data platforms in the context of nursing care along normative, organizational, and technical dimensions of governance. The cases were selected due to their high level of comparability and to demonstrate three different types of data governance strategies understood as actions to reconcile conflicting interests regarding data and dealing with prevalent data protection law – ranging from strictly processual approaches to the creation of synthetic data. These findings highlight the importance of considering data governance strategies concisely when building data platforms and suggest considerable variety in the configuration of data governance arrangements

Association Between Fatigue and Motor Exertion in Patients With Multiple Sclerosis - a Prospective Study

Background: Fatigue in multiple sclerosis (MS) is conceived as a multidimensional construct. Objectives: This study aims to describe the changes of balance and gait parameters after 6 min of walking (6 MW) as potential quantitative markers for perceptions of state fatigue and trait fatigue in MS. Methods: A total of 19 patients with MS (17 with fatigue) and 24 healthy subjects underwent static posturography, gait analysis, and ratings of perceived exertion before and after 6 MW. Results: 6 MW was perceived as exhaustive, but both groups featured more dynamic comfortable speed walking after 6 MW. Shorter stride length at maximum speed and increased postural sway after 6 MW indicated fatigability of balance and gait in MS group only. While most changes were related to higher levels of perceived exertion after 6 MW (state fatigue), higher fatigue ratings (trait fatigue) were only associated with less increase in arm swing at comfortable speed. Further analysis revealed different associations of trait fatigue and performance fatigability with disability and motor functions. Performance fatigability was most closely related to the Expanded Disability Status Scale, while for trait fatigue, the strongest correlations were seen with balance function and handgrip strength. Conclusions: Fatigability of performance was closely related to perceptions of exertion after 6 MW (state fatigue) and disability in MS but distinct from fatigue ratings, conceived as trait fatigue. Our study identified postural sway, arm swing during gait, and hand grip strength as unexpected potential motor indicators of fatigue ratings in MS