Empirical findings from ten software teams from two large-scale software development projects in Ericsson and ABB demonstrated that teams receive and share their knowledge with a large number of contacts, including other team members, experts, administrative roles, and support roles.Along with human and organizational capital, social capital and networking are also necessary for participation in large-scale software development, both for novice teams and for mature teams working on complex, unfamiliar, or interdependent tasks.Social capital has the potential to compensate for gaps in human capital (i.e., an individual's knowledge and skills).The team network size and networking behavior depend on the following factors: company experience, employee turnover, team culture, need for networking, and organizational support.Along with investments in training programs, software companies should also cultivate a networking culture to strengthen their social capital and achieve better performance. ContextLarge software development projects involve multiple interconnected teams, often spread around the world, developing complex products for a growing number of customers and users. Succeeding with large-scale software development requires access to an enormous amount of knowledge and skills. Since neither individuals nor teams can possibly possess all the needed expertise, the resource availability in a team's knowledge network, also known as social capital, and effective knowledge coordination become paramount. ObjectiveIn this paper, we explore the role of social capital in terms of knowledge networks and networking behavior in large-scale software development projects. MethodWe conducted a multi-case study in two organizations, Ericsson and ABB, with software development teams as embedded units of analysis. We organized focus groups with ten software teams and surveyed 61 members from these teams to characterize and visualize the teams knowledge networks. To complement the team perspective, we conducted individual interviews with representatives of supporting and coordination roles. Based on survey data, data obtained from focus groups, and individual interviews, we compared the different network characteristics and mechanisms that support knowledge networks. We used social network analysis to construct the team networks, thematic coding to identify network characteristics and context factors, and tabular summaries to identify the trends. ResultsOur findings indicate that social capital and networking are essential for both novice and mature teams when solving complex, unfamiliar, or interdependent tasks. Network size and networking behavior depend on company experience, employee turnover, team culture, need for networking, and organizational support. A number of mechanisms can support the development of knowledge networks and social capital, for example, introduction of formal technical experts, facilitation of communities of practice and adequate communication infrastructure. ConclusionsOur study emphasizes the importance of social capital and knowledge networks. Therefore, we suggest that, along with investments into training programs, software companies should also cultivate a networking culture to strengthen their social capital, a known driver of better performance.

This article systemizes a spectrum of emerging work arrangements for teams, including hybrid teams, partially aligned teams and, more importantly, variegated teams with fully aligned alternation of office presence. Our team typology is based on the practical insights from “Alpha,” “InterSoft,” Valtech, IBM, Brandwatch, and Ericsson.

Agile methods and the related concepts of employee empowerment, self-management, and autonomy have reached large-scale software organizations and raise questions about commonly adopted principles for authority distribution. However, the optimum mechanism to balance the need for alignment, quality, and process control with the need or willingness of teams to be autonomous remains an unresolved issue. In this paper, we report our findings from a multiple-case study in two large-scale software development organizations in the telecom industry. We analysed the autonomy of the agile teams in the organizations using Hackman’s classification of unit authority and found that the teams were partly self-managing. Further, we found that alignment across teams can be achieved top-down by management and bottom-up through membership in communities or through dialogue between the team and management. However, the degree of team autonomy was limited by the need for organizational alignment. Top-down alignment and control were maintained through centralized decision-making for certain areas, the use of supervisory roles, mandatory processes, and checklists. One case employed a bottom-up approach to alignment through the formation of a community composed of all teams, experts, and supporting roles, but excluding managers. This community-based alignment involved teams in decision-making and engaged them in alignment initiatives. We conclude that implementation of such bottom-up structures seems to provide one possible mechanism for balancing organizational control and team autonomy in large-scale software development.