Research on business analytics (BA) has made various incongruent assumptions about how BA systems are applied in business processes and how they create value. Meanwhile, machine learning (ML) is changing how BA systems create value, but research streams on ML and BA have yet to come to a shared view on process-level value creation. In this theoretical literature review, we draw on the Information Value Chain (IVC) to synthesize 176 articles from top journals and present a model of process-level value creation from BA systems. We contextualize and extend the IVC with six distinct value creation paths, explain how the characteristics of ML-based BA systems change value creation paths, and propose a research agenda.

Achieving effective inter-team coordination is one of the most pressing challenges in large-scale software development. Hybrid approaches of traditional and agile development promise combining the overview and predictability of long-term planning on an inter-team level with the flexibility and adaptability of agile development on a team level. It is currently unclear, however, why such hybrids often fail. Our case study within a large software development unit of 13 teams at a global enterprise software company explores how and why a combination of traditional planning on an inter-team level and agile development on a team level can result in ineffective coordination. Based on a variety of data, including interviews with scrum masters, product owners, architects and senior management, and using Grounded Theory data analysis procedures, we identify a lack of dependency awareness across development teams as a key explanation of ineffective coordination. Our findings show how a lack of dependency awareness emerges from misaligned planning activities of specification, prioritization, estimation and allocation between agile team and traditional inter-team levels and ultimately prevents effective coordination. Knowing about these issues, large-scale hybrid projects in similar contexts can try to better align their planning activities across levels to improve dependency awareness and in turn achieve more effective coordination.

Pervasive applications have been designed to support users in their everyday life. For this purpose, they are able to interact with their physical environment, their context. They are aware of their context and use this information for configuration decisions. Furthermore, they can actively modify the context to meet their user's needs. This leads to new challenges in multi-user environments as applications which are executed simultaneously share a common context and thus can directly impact each other. In this paper we present a framework to coordinate multiple pervasive applications explicitly considering their context-interactivity. We show how application coordination can be integrated in an existing component-based system exemplified by our system PCOM. We conduct measurements for the extended system and discuss the obtained results.