Interpreting Co-evolution and Information Systems Emergence: Interpretive Case Studies and Analysis

Over the past 30 years, much valuable research has been undertaken to understand Information Systems (IS) implementation, particularly failures or spiralling costs, through the study of critical success factors, implementation processes, technology resistance, risk management, or misalignment of the product and organisation. This significant body of work has advanced our understanding of IS implementation phenomena. Yet there exists, by and large, an underlying assumption that regards implementation as an isolated feat and not as an ongoing achievement, thereby overlooking the contextual and mutually constitutive nature of systems and organisations. Furthermore, there is a tendency to adopt either a stance of technological determinism, where outcomes are directly attributed to qualities inherent to the system, or sociological determinism, where outcomes are directly attributed to social orchestration. By doing so, the co-evolutionary nature of IS engagement, in which the interplay between system and organisation unfolds in new and largely unanticipated directions, is ignored. In contrast, I regard engagement as a co-evolutionary process where the software system, the vendor, the organisation, and individual stakeholders are each forced to adapt continually to the changing context wrought by the movements of one another. In this thesis, therefore, I seek to understand (a) how software systems and organisations co-evolve in practice, and (b) the dynamics through which an IS emerges or fails to emerge in the overall environment. I investigate this research question by conducting two longitudinal, interpretive case studies. The first case study concerns the implementation of a novel academic scheduling system at a large research-intensive Australian university. This case study is analysed from the perspective of two quite different theories, complex adaptive systems theory (CAS) and actor-network theory (ANT), to highlight different aspects of the case and to better understand the strengths of each theory. I argue that complex adaptive system theory provides an excellent lens to study the motor of co-evolution, due to its ability to frame the strategies and reinforcement models of actors. I illustrate this ability by recounting five narratives of the interaction, selection, and adaptation of actors. Furthermore, I consider how the complexity of the engagement emerges from the interrelationship of these narratives and how the adaptive behaviour of the various actors is both a response to and a driver of co-evolution within the engagement. From ANT, we understand how ordering emerges in the form of blackboxes and how this outcome is achieved through processes of enrolment of human and non-human allies and the translation of their interests. I characterise the academic timetable as a stabilised actor-network and show how re-negotiation with all actors is required when the project is initiated and the blackbox of timetabling practice opened. In particular, I consider the interplay of ambiguity, clarification and durability in the work of enrolling allies and how actors translate the interests of others by bridging inscriptions, creating chains of translation, and using obligatory passage-points to hold the other’s interests stable. From this perspective, we see how ordering emerges within the case. The second case study investigates the dynamics of the research management process at this same university. It differs from the first, because it investigates a complex socio-technical system in-situ to (a) understand how software systems and organisations have co-evolved in practice, and (b) determine how the phenomenon of research management has emerged in the overall environment. I show that CAS deals with intentionality and a state-based view of a system and its dynamics–through interaction, selection mechanisms, and adaptation; whereas ANT provides the narrative on the transformations and their mechanics–through enrolment, translation, punctualisation, and blackboxing. ANT reveals how heterogeneous actors are constructed, aligned, and sustained as actor-networks. Within ANT, however, the goal-seeking behaviour of actors is implied, and we are left wondering why actors behave as they do. Whereas in CAS, transition is implied, and we are left wondering how things play out as they do. I contribute to ongoing IS research by showing the combined value of these theories to improving our understanding of co-evolutionary dynamics during an IS engagement. An analysis of selection mechanisms from CAS is useful to understand adaptive, goal-seeking behaviour of actors. An analysis using ANT provides the language and apparatus to reveal how calculation, that facilitates selection, is made possible. I conclude with a discussion of the insights gained by applying complex adaptive systems theory and actor-network theory and consider the implications for the practice and future research of IS engagement