Dynamics of governance and control in inter-organizational software development

In recent years, development of information systems (IS) has rapidly changed towards increasing division of labor between firms. Two trends are emerging. First, client companies increasingly outsource software development to external service providers. Second, the formerly oligopolistic enterprise application software industry has started to disintegrate into focal partnership networks – so called platform ecosystems. Despite the increasing prominence of IS outsourcing and platform ecosystems, many of these inter-organizational partnerships fail to achieve expected benefits. Ineffective governance and control frequently plays a pivotal role in producing these failures. While designing effective governance and control mechanisms is always challenging, inter-organizational software development projects are often business-critical and exhibit additional dynamics and uncertainty. As a consequence governance and control have to be adapted over time. The three research projects included in this book provide a better understanding of how and why governance and control can be effectively adapted over time. The implications for successful management of inter-organizational software development projects are highly relevant for theory and practice.

Network Dynamics in Natural Resource Governance: A Case Study of Swiss Landscape Management

Structural characteristics of social networks have been recognized as important factors of effective natural resource governance. However, network analyses of natural resource governance most often remain static, even though governance is an inherently dynamic process. In this article, we investigate the evolution of a social network of organizational actors involved in the governance of natural resources in a regional nature park project in Switzerland. We ask how the maturation of a governance network affects bonding social capital and centralization in the network. Applying separable temporal exponential random graph modeling (STERGM), we test two hypotheses based on the risk hypothesis by Berardo and Scholz (2010) in a longitudinal setting. Results show that network dynamics clearly follow the expected trend toward generating bonding social capital but do not imply a shift toward less hierarchical and more decentralized structures over time. We investigate how these structural processes may contribute to network effectiveness over time.