We examine how firms configure alliance portfolios—that is, networks of partnering firms—in order to exchange, share, or codevelop the capabilities they require to engage in digital innovation. We analyze data from 550 U.S. firms and the strategic alliances they formed within and across industrial sectors to study how the configuration of alliance portfolios in terms of size, degree of exploration, internationality, and competition affects the volume and quality of digital patents. We find that alliances appear to be an effective means, yet alliances for digital innovations require a different configuration when compared with alliances for non-digital innovations. Large and explorative alliance portfolios help with the creation of digital innovations while international alliances and alliances involving competitors do not. We discuss the implications of these findings for research on digital innovation and alliances. We also distill practical advice to executives charged with making strategic decisions about inter-firm partnerships.

Software development process ambidexterity (SDPA) is the ability to demonstrate both process alignment and process adaptability simultaneously. Realizing process ambidexterity has recently been suggested as an effective approach to improving the performance of software development (SD) projects. To understand the mechanisms underlying the effects of ambidexterity, we focus in this study on the mediating effects of coordination, one of the most important activity in SD projects. Specifically, we hypothesize a mediating effect of coordination costs and coordination effectiveness on the relationship between SDPA and project performance. We conducted a quantitative study involving 104 SD projects across 10 firms to test the model. The results strongly suggest that the positive relationship between SDPA and project performance is negatively mediated by coordination costs and positively mediated by coordination effectiveness. We validate our research model with a case study in an organization employing several hundred IT professionals and derive several practical implications on this basis.

Digital services are a key driver of contemporary businesses. In order to scale the implementation of design-centric development processes, companies increasingly assign design work to design novices. As design novices have limited design knowledge and experience, they are challenged to select adequate design techniques throughout the entire lifecycle of digital services. Thus, providing decision aids to design novices is becoming increasingly important. In this research, we investigate taxonomy-based and tags-based decision aids. We draw on cognitive fit theory to construct a research model explaining the relationship between different decision aids and selection accuracy while considering the cognitive effort and the decision styles of novice designers. To test our hypotheses, we conducted a between-subject laboratory experiment with 195 subjects. Our experimental results provide extensive support to our hypotheses. Taxonomy-based decision aids outperform tags-based decision aids concerning selection accuracy mediated by cognitive effort. Furthermore, the results suggest rational decision style as a moderator in the relationship between taxonomy-based decision aids and selection accuracy. Our results have practical implications: First, taxonomy-based decision aids should be primarily leveraged on decision support platforms supporting design processes. Second, design novices' decision style and cognitive effort are influential factors when developing decision aids to support digital service design processes.

The demand for and the number of software product offers are evolving rapidly. Despite the importance of the software industry, its representation within current classification systems is often obstructed. Therefore, researchers often neglect the variety of software products within their work. Using a systematic approach, we develop an industry classification for the software product industry. The empirical-to-conceptual approach allows us to establish concepts that are dominant in practice. As a result, we derive three major sectors, i.e. business function software, industrial software and consumer software. Experts from the software industry are interviewed to evaluate the results. The suggested industry classification helps practitioners to communicate clearly, identify competitors and possible innovations within the software product industry. The classification helps scholars to improve theory building.