THE GENERATIVE MECHANISMS OF DIGITAL INFRASTRUCTURE EVOLUTION 1

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1 SPECIAL ISSUE: CRITICAL REALISM IN IS RESEARCH THE GENERATIVE MECHANISMS OF DIGITAL INFRASTRUCTURE EVOLUTION 1 Ola Henfridsson Warwick Business School, The University of Warwick, Coventry CV4 7AL UNITED KINGDOM {[email protected]} Bendik Bygstad Norwegian School of IT, Schweigaards gt. 14, 0185 Oslo NORWAY and Department of Informatics, University of Oslo, Oslo NORWAY {[email protected]} The current literature on digital infrastructure offers powerful lenses for conceptualizing the increasingly interconnected information system collectives found in contemporary organizations. However, little attention has been paid to the generative mechanisms of digital infrastructure, that is, the causal powers that explain how and why such infrastructure evolves over time. This is unfortunate, since more knowledge about what drives digital infrastructures would be highly valuable for managers and IT professionals confronted by the complexity of managing them. To this end, this paper adopts a critical realist view for developing a configurational perspective of infrastructure evolution. Our theorizing draws on a multimethod research design comprising an in-depth case study and a case survey. The in-depth case study, conducted at a Scandinavian airline, distinguishes three key mechanisms of digital infrastructure evolution: adoption, innovation, and scaling. The case survey research of 41 cases of digital infrastructure then identifies and analyzes causal paths through which configurations of these mechanisms lead to successful evolution outcomes. The study reported in this paper contributes to the infrastructure literature in two ways. First, we identify three generative mechanisms of digital infrastructure and how they contingently lead to evolution outcomes. Second, we use these mechanisms as a basis for developing a configurational perspective that advances current knowledge about why some digital infrastructures evolve successfully while others do not. In addition, the paper demonstrates and discusses the efficacy of critical realism as a philosophical tradition for developing substantive contributions in the field of information systems. Keywords: Digital infrastructure, case study, case survey, configuration theory, critical realism, generative mechanism, information infrastructure, multimethod, adoption, innovation, scaling Introduction 1 No idea in our field is more enduring than the notion that the introduction of a new IT-based information system improves 1 John Mingers, Alistair Mutch, and Leslie Willcocks served as the senior editors for this special issue and were responsible for accepting this paper. The appendix for this paper is located in the Online Supplements section of the MIS Quarterly s website ( the possibility of effectively managing an enterprise. Yet, it is becoming increasingly recognized that the pervasive adoption and use of information technology in contemporary organizations makes the relationship between information systems and organization increasingly complex (Zammuto et al. 2007). As information systems become interconnected, most organizations face the challenges of controlling an entire array of systems and technologies, typically introduced over many years and for different purposes (Ciborra et al. 2000). As a result, the effectiveness of the single system is largely MIS Quarterly Vol. 37 No. 3, pp /September

2 conditioned by an installed base of extant socio-technical arrangements, making it useful to apply modes of inquiry that offer a conceptual basis for going beyond the scope of the single system. To understand this phenomenon, there is an emerging literature that has adopted the notion of infrastructure as a way of conceptualizing interconnected system collectives (rather than stand-alone information systems). In fact, the past 15 years or so have witnessed research on digital infrastructure 2 covering different settings (e.g., health, telecom, natural resources, government, and manufacturing), levels of analysis (e.g., group, organization, industry, and society), and technologies (e.g., standards, platforms, and the Internet). Yet, as highlighted in Tilson et al. s (2010) recent research commentary, there is an urgent need to theorize the evolution of digital infrastructures as our field s attention moves beyond administrative systems and individual tools (p. 748). Such a need calls for approaches with the ambition to explicate the inner workings of digital infrastructure. It also indicates the usefulness of a philosophical tradition that would build the intellectual structure for such explanation. Covering the two main philosophical traditions in IS research (Mingers 2004), typically referred to as positivism and interpretivism, 3 extant infrastructure research displays slightly different foci. It tends to be occupied with either situated contexts of practice, or directly observable managerial aspects. Adhering to interpretivism, considerable attention has been paid to the evolution of digital infrastructure as it plays out in the complex interdependencies between socio-technical elements (Braa et al. 2007); networks of human and nonhuman actors (Hanseth and Monteiro 1997); and the relationships between organized practices (Star and Ruhleder 1996). In studies underpinned by positivist assumptions, the research has primarily dealt with strategic IT portfolio management and the alignment of IT imperatives with business strategy (Broadbent and Weill 1997). As an alternative intellectual structure for theorizing digital infrastructure, we propose critical realism (Archer et al. 1998; 2 The current literature uses different concepts for capturing this phenomenon including information infrastructure, IT infrastructure, e-infrastructure, and so on. Following Tilson et al. s (2010) call for infrastructure research, we use the term digital infrastructure throughout this paper. 3 We use the terms interpretivism and positivism to align our terminology with previous writings on philosophical traditions in the information systems literature (see Orlikowski and Baroudi 2001; Walsham 1995). However, it should be emphasized that both labels span multiple philosophical strands. For instance, as suggested by one of our anonymous reviewers, interpretivism includes both idealists and realists, taking different ontological positions. Bhaskar 1997; Sayer 1992) for its emphasis on generative mechanisms (Bhaskar 1997, 1998). While there are a few studies identifying specific mechanisms of digital infrastructure (see Bygstad 2010), little, if any, research has been geared toward developing a comprehensive understanding of the range and contingencies of causal structures in its evolution. Understanding these issues is important, since more knowledge about what drives digital infrastructures would be highly valuable for managers and IT professionals confronted by the complexity of managing them. Our paper deals with the following research question: Which mechanisms contingently cause digital infrastructure evolution? We address this research question using a multimethod research design (Mingers 2001), recently proposed as an important principle for conducting critical realist case study research (Wynn and Williams 2012). We first conducted indepth case study research (George and Bennet 2005; Gerring 2007) at a Scandinavian airline to identify key mechanisms of digital infrastructure. Then, we conducted case survey research (Larsson 1993) based on a sample of 41 cases to analyze the causal paths through which these mechanisms are combined to produce successful digital infrastructure evolution. Our research makes a number of contributions. First, we identify three generative mechanisms of digital infrastructure and how they contingently lead to evolution outcomes. Second, we use these mechanisms as a basis for developing a configurational perspective that describes infrastructure evolution as an outcome of multiple paths of interconnected contextual conditions and mechanisms (El Sawy et al. 2010; Meyer et al. 1993; Pawson and Tilley 1997). This perspective advances current knowledge about why some digital infrastructures evolve successfully while others do not. Finally, the paper demonstrates and discusses the efficacy of critical realism as a philosophical tradition for making substantive contributions in the field of information systems. Related Research and Conceptual Basis Digital infrastructure evolution can be broadly referred to as a gradual process by which a digitally enabled infrastructure changes into a more complex form. Viewing digital infrastructure as the collection of technological and human components, networks, systems, and processes that contribute to the functioning of an information system (Braa et al. 2007; Tilson et al. 2010), this evolutionary process entails both social and technical elements (Vaast and Walsham 2009). However, reviewing the literature, it is clear that definitions vary, and, 908 MIS Quarterly Vol. 37 No. 3/September 2013

3 over the years, the concept itself has largely served as the lowest common denominator for IS researchers who have shifted attention from single organizations to organizational networks, and from systems to infrastructures (Ciborra et al. 2000). Views on Digital Infrastructure 4 There exists a relatively large volume of research that uses the notion of infrastructure without necessarily dealing substantively with the phenomenon itself (Tilson et al. 2010). In such cases, infrastructure is typically used as an independent variable to explain something else (for examples, see Bharadwaj 2000; Malhotra et al. 2005; Rai et al. 2006; Tanverdi et al. 2007), and it often refers to a collection of information technologies and systems that jointly produce a desired outcome. For instance, Malhotra et al. s (2005) study of information sharing between actors in the supply chain understands IT infrastructure as partner interface-directed information systems that enable an enterprise to process information collected from its supply chain partners so as to create new knowledge (p. 156). In prior literature where digital infrastructure in fact is at the center of attention, four streams of research can be distinguished (see Table 1). Three of these streams manifest interpretivist assumptions, while the fourth reflects positivist assumptions. 5 First, complexity models presume that there is 4 Drawing on Webster and Watson (2002), we conducted a concept-centric literature review of research on digital infrastructure. First, our ambition was to include most, if not all, relevant articles published in the AIS basket-ofeight IS journals, science and technology journals, and other journals (e.g., Information & Organization, Information Society, Information Technology & People, and Computer Supported Cooperative Work) that were likely to publish infrastructure studies. In addition, we added articles from conference proceedings and books on an ad hoc basis. We used the Citeseer ABI/Inform research database and the selected articles had the phrases digital infrastructure, information infrastructure, information technology infrastructure, IT infrastructure, information systems infrastructure, or IS infrastructure in the title, abstract, keyword, or body of the publication. From the large number of publications that met this criterion, we briefly read the papers to identify articles with digital infrastructure as an important object of study. We analyzed the selected publications to identify key concepts that were used to characterize the nature of digital infrastructure. These concepts were then clustered with the intention of identifying dominant research streams in the digital infrastructure literature. The identified research streams were then labeled complexity, network, relational, and strategic asset to reflect their main theoretical emphasis. 5 Some readers may feel that typifying infrastructure research into families of philosophical traditions such as positivism and interpretivism faces the risk of simplifying research in a substantive area by enforcing grand thought structures on it and its representative scholars. Appreciating this risk, we value the possibility to surface philosophical assumptions and their consequences for theorizing. As suggested by Lee (2004), recognizing philosophical underpinnings can lead to findings that would help the information no single source of digital infrastructure evolution. Grounded in literature on complexity (Holland 1995; Mol and Law 2002; Urry 2003), such models typically highlight the complexity of digital infrastructures as a multitude of actors simultaneously enact their own goals. In other words, infrastructure evolution is seen as the process by which heterogeneous and autonomous human, or organizational, actors seek to use information technology in their adaptation to each other and their external environments (Braa et al. 2007; Ciborra and Failla 2000; Hanseth et al. 2006). For instance, Braa et al. (2007) advance the notion of flexible standardization as a key process for addressing the complexity of accommodating both global needs of scalability of infrastructure standards and local needs of sensitivity to contextual differences. Second, network models assume that networks of human and technical elements drive digital infrastructure evolution. This stream of research is typically grounded in some of the early writings of actor network theorists such as Callon (1986) and Latour (1987). It views infrastructure evolution as a process by which multiple human actors translate and inscribe their interests into a technology, creating an evolving network of human and nonhuman actors (Aanestad and Blegind Jensen 2011; Hanseth and Monteiro 1997; Yoo et al. 2005). For instance, Hanseth and Monteiro (1997) note how barriers to end-user involvement were inscribed by human actors involved in the integration of the EDIFACT standard in Norwegian healthcare. These barriers, the authors claim, were the result of an actor network beyond any single stakeholder s control. Third, relational models premise that infrastructure should be appreciated through the sensemaking of its users and stakeholders. This stream of literature has its intellectual basis in theories on learning and work practices (Engeström 1990; Lave and Wenger 1992). As noted in Star and Ruhleder s (1996) seminal article, digital infrastructure is a relational property that becomes meaningful as an element of organized activity. In this regard, infrastructure evolution is seen as a process by which socio-technical relations emerge from information technology-mediated activities meaningful in a given community-of-practice (Pipek and Wulf 2009; Star and Ruhleder 1996; Vaast and Walsham 2009). For instance, Vaast and Walsham (2009) propose a perspective on trans-situated learning and how such learning is supported by the local universality of an information infrastructure whose use becomes embedded with other infrastructures (p. 547). systems research community do better information systems research (p. 18). Also, it should be emphasized that in a number of cases the philosophical tradition is explicitly indicated in the methods section of individual articles and/or in their reference literature. MIS Quarterly Vol. 37 No. 3/September

4 Table 1. Research Streams and Definition Research Streams Philosophical Tradition Complexity Interpretivist Complexity theory Holland (1995) Mol and Law (2002) Urry (2003) Network Interpretivist Actor network theory Callon (1986) Latour (1987) Relational Interpretivist Work practice and learning theory: Engeström (1990) Lave and Wenger (1992) Foundational Literature Definition (of DI Evolution) Example References The process by which heterogeneous and autonomous human, or organizational, actors seek to use information technology in their adaptation to each other and their external environments. The process by which multiple human actors translate and inscribe their interests into a technology, creating an evolving network of human and nonhuman actors. The process by which socio-technical relations emerge from IT-mediated activities that become meaningful in a given community-of-practice. Braa et al. (2007) Ciborra and Failla (2000) Hanseth et al.(2006) Aanestad and Blegind Jensen (2011) Hanseth and Monteiro (1997) Yoo et al. (2005) Pipek and Wulf (2009) Star and Ruhleder (1996) Vaast and Walsham (2009) Strategic Asset Positivist Strategic choice theory Beckert (1999) Child (1972, 1997) The process by which managers initiate and implement changes in an organization s portfolio of systems and tools for increasing the alignment between its IT resources and strategic imperatives. Broadbent and Weill (1997) Broadbent et al. (1999) Finally, strategic asset models view digital infrastructure evolution as the process by which managers initiate and implement changes in an organization s portfolio of systems and tools for increasing the alignment between its information technology resources and strategic imperatives. In this regard, a strategic choice view (Beckert 1999; Child 1972, 1997) is implied, that is, political action is given primacy in analyzing organizational responses to environmental contingencies. For instance, Broadbent et al. (1999) explain how the creation of a certain level of IT infrastructure capability is needed to successfully implement business process redesign. The Promise of Critical Realism In this research, we seek to understand which mechanisms contingently cause the evolution of digital infrastructure. We argue that the explanatory power of such mechanisms has been masked in prior research by the adoption of philosophical assumptions inattentive to structures operating beyond (1) the rich texture of people s meaning-making of the sociotechnical world (interpretivist streams), or (2) events directly observable in the empirical domain of infrastructures (the positivist stream). Interpretivism invites attention to actors sensemaking and the generation of process accounts on digital infrastructure evolution. In the relational stream of research (e.g., Pipek and Wulf 2009; Star and Ruhleder 1996; Vaast and Walsham 2009), for instance, this attention to sensemaking has been materialized as a focus on the patterned activity that results from situated actors interaction and dealing with technology in their work settings. The positivist assumptions underpinning the strategic assets stream of research (Broadbent and Weill 1997; Broadbent et al. 1999) imply attention to characteristics of strategy and a portfolio of systems that can be directly observed and measured. This may lead to overly simplistic assumptions about the relationship between digital infrastructures and business success. Although divided by two broad, but significantly different, sets of philosophical assumptions, we argue that the extant literature on digital infrastructure generally tends to shy away from causality. To pick up on Tilson et al. s (2010) call for infrastructure theory, we should seek explanations that take into account both the dynamic character of digital infrastructures and the contingent causality characterizing their evolution. We adopt critical realism as an intellectual structure for reconciling existing perspectives of digital infrastructure. 910 MIS Quarterly Vol. 37 No. 3/September 2013

5 Critical realism has been increasingly recognized in our discipline as a promising philosophical tradition to overcome objectivism relativism chasms (Mingers 2004; Smith 2010; Volkoff et al. 2007). It combines a realist ontology with an interpretive epistemology (Archer et al. 1998); although our knowledge of the world is socially constructed and fallible, that world exists, often independent of human beings (Mingers 2004). Contrary to judgmental relativism, critical realism therefore holds that some theories approximate reality better than others, making methodological approaches to assess knowledge claims meaningful. In addition, research should not only concern recording of constant conjunctions of observable events (Bhaskar 1997; Mingers 2004), as suggested in so-called covering law theories of causality grounded in Hume s skeptic discussion of causality (Elder- Vass 2010, Lee 2004). Generative Mechanisms Following Bhaskar (1997, 1998), we define generative mechanisms as causal structures that generate observable events. In contrast to Humean causality, critical realists typically ascribe such structures causal powers (Sayer 1992). Causality is contingent; that is, the outcome of a mechanism depends on other mechanisms (Elder-Vass 2010; Sayer 1992). In this regard, mechanisms act transfactually. The event or events that they are the powers to instantiate may never actually be instantiated; the powers may remain unactualized, yet these powers remain in existence (Fleetwood 2009, p ). 6 A generative mechanism is one of the processes in a concrete system that makes it what it is for example, metabolism in cells, interneuronal connections in brains, work in factories and offices, research in laboratories, and litigation in courts of law (Bunge 2004, p. 182). In this vein, our research question, about which mechanisms contingently cause the evolution of digital infrastructure, is partially geared toward defining what constitutes a digital infrastructure. Previous literature reviews suggest that this is a fundamental issue for furthering research in the area (see Bygstad 2008), not least by directing attention to the underlying mechanisms that produce observable events. Drawing on Hedström and Swedberg s (1998) work on mechanisms, we make three assumptions about mechanisms of 6 There is an extensive literature on the nature and definition of mechanisms, both in the philosophy of social sciences (Demetriou 2009; Glennan 2009; Hedstrom 2008), and in the critical realist community (Fleetwood 2009, 2011; Mingers 2010). While we relate broadly to this literature, it is beyond the scope of this article to engage fully in this discourse. digital infrastructure and their generic structure (see Figure 1). First, digital infrastructure mechanisms are self-reinforcing (Hanseth and Aanestad 2003). A self-reinforcing mechanism recursively feeds on itself. Since the control of an infrastructure typically is distributed across multiple actors, infrastructures are for practical and economic reasons difficult to govern. It is partly relying on positive, or negative, feedback loops beyond single stakeholders control (Hanseth and Braa 2000). The phenomenon of self-reinforcement is wellknown in technology and diffusion research (Katz and Shapiro 1985), and has been attributed a central role for understanding organizational stability and change (Sydow et al. 2009). Second, digital infrastructure mechanisms are composites. They interconnect three types of mechanisms: situational mechanisms (macro micro level), action-formation mechanisms (socio-technical action), and transformational mechanisms (micro macro level) (DeLanda 2006; Hedström and Swedberg 1998). Macro micro mechanisms explain how the infrastructure as a whole enables and constrains its various components. For instance, the Internet as an infrastructure has proved to enable unprecedented innovation possibilities for individual entrepreneurs, as long as they are following its standard interfaces (Hanseth and Lyytinen 2010; Zittrain 2006). Action-formation mechanisms explain how a specific combination of individual desires, beliefs, and action opportunities generate a specific action (Hedström and Swedberg 1998, p. 23). Continuing our example, Internet entrepreneurs in Silicon Valley display new forms of learning in innovative path creation (Hagel et al. 2010). Micro macro mechanisms explain emergent behavior, that is, how different components interact in order to produce an outcome at a macro level. Completing our example, new innovation path creation leads to new services and products that reinforce the Internet as a basis for innovative activity. Third, although most established work on mechanisms only addresses the social (Hedström and Swedberg 1998; Merton 1967), it goes without saying that a necessary element in digital infrastructures is technology. Technology plays an active role at both the structural level and the action level (Volkoff et al. 2007), and the interaction between social and technical elements is the constituting process of the mechanism A Configurational Perspective Mechanisms are characterized by contingent causality (Elder- Vass 2010; Sayer 1992). The actualization (or lack of actualization) of the powers of a mechanism may lead to one outcome in a particular context, and another in a different context MIS Quarterly Vol. 37 No. 3/September

6 Digital Infrastructure Macro to micro Micro to macro Socio-technical action Figure 1. The Self-Reinforcing Socio-Technical Mechanism (see Ragin 2008). This multifinality (George and Bennett 2005) largely depends on the existence of other mechanisms in the same context. Such dependence also indicates that there are multiple causal paths through which a particular outcome can occur, and suggests that investigations of digital infrastructure should seek to analyze how different mechanisms are configured and triggered to produce successful outcomes. A configurational perspective (El Sawy et al. 2010; Fiss 2007; Pawson and Tilley 1997) can be seen as a viable approach to investigate the causal complexity associated with such equifinality 7 (George and Bennett 2005). It allows analysis of possible configurations of mechanisms and relevant contextvariation to explain a particular outcome (Pawson and Tilley 2009). However, it should not be considered as a covering law (cf. Elder-Vass 2010), but as a conjectural explanation, being the basis of further refinement. Using Pawson and Tilley s (2009) context mechanism outcome (CMO) scheme as a basis, Figure 2 illustrates the starting-point for our configurational analysis, where we derived four possible configurations of relevant context variation from the literature and suggested a hypothetical space of 2 n configurations of mechanisms that together lead to the same outcome (success 8 ). This configurational perspective provides the basis for our analysis of the causal paths that explain how, in certain contexts, a digital infrastructure mechanism (or a combination of mechanisms) may lead to successful evolution. Our configurational perspective rests on two assumptions. First, we assume that the key mechanisms 7 Equifinality refers to situations where different causal paths may lead to the same outcome (Fiss 2009; George and Bennett 2005; Rihoux and Ragin 2009). Multiple determination is a similar term used by Bhaskar (1979) (see also Elder-Vass 2010). 8 Of course, a similar space of configurations can be created for failures. of digital infrastructure interact, that is, a mechanism may produce different outcomes, depending on its actualization in combination with other mechanisms. Second, we buy into the current wisdom that infrastructures consist of both social and technical elements (Ciborra et al. 2000; Edwards et al. 2009; Vaast and Walsham 2009). Our literature review of contextual conditions was, therefore, geared toward covering both types of elements in our configurational perspective. On the social side, type of control stood out as an important contextual condition (e.g., Ciborra 2000; Hanseth and Braa 2000; Hanseth et al. 1996; Pipek and Wulf 2009; Rolland and Monteiro 2002; Sahay and Walsham 2006). In particular, the idea of decentralized control of digital infrastructures (Ciborra et al. 2000) has been considered a strong alternative to prevailing centralized approaches (see Broadbent and Weill 1997). On the technical side, architecture, in particular loosely coupled architectures, has come to the fore as an important condition for infrastructure evolution (Aanestad and Blegind Jensen 2010; Fabri 2009). Based on the extant infrastructure literature, we therefore propose that decentralized control and loosely coupled architecture work as key contextual conditions of digital infrastructure evolution. Before presenting our empirical study, we also need to clarify the outcome dimension of our configurational perspective. Ever since DeLone and McLean s (1992; see also 2003) seminal article, it has been generally agreed that IS success is a multidimensional construct involving measures such as system quality, information quality, service quality, organizational impact, and user satisfaction. However, defining success for digital infrastructures requires consideration of the fundamental difference between traditional in-house information systems and infrastructures. While the former typically involves a relatively well-defined evaluation context in terms of objectives and end-user group, the latter refers to open, evolving networks of interconnected systems having many stakeholders, for whom success may be interpreted differently (Hanseth and Lyytinen 2010). Infrastructures often evolve 912 MIS Quarterly Vol. 37 No. 3/September 2013

7 Figure 2. A Configurational Perspective on Digital Infrastructure into larger and more complex structures (such as the Internet), without any predefined end state as they are continuously extended and typically operate outside the control of a single stakeholder. It therefore makes sense to relate an infrastructure s success to its role in, and fit with, the environment it inhabits. Using a biological metaphor, success can then be seen as a question of survival in a volatile business ecosystem. In this vein, we view infrastructure evolution success as an outcome realized when (1) the infrastructure survives in a business ecosystem by filling a relevant role over time, and (2) the infrastructure s affordances cannot be escaped endogenously but is only vulnerable to exogenous shocks (see Vergne and Durand 2010). Given this theoretical background, we set out to develop a configurational perspective by using a multimethod research design (Mingers 2001). We first conducted a 4-year in-depth case study (Gerring 2007; George and Bennett 2005) of an airline in order to identify mechanisms with the power to cause digital infrastructure evolution. We then conducted a case survey (Larsson 1993) to analyze the causal paths through which these mechanisms are combined to produce successful digital infrastructure evolution. The next section outlines the in-depth case study. The Norwegian Case Study Norwegian Corp is an international airline carrier that pioneered the low-price airline market in Scandinavia. Enabled by the European deregulation of the airline industry, the firm s strong growth started in 2002 as it established a national network of destinations. Some 9 years later, in 2011, Norwegian operated a total of 303 routes to 118 destinations in Europe and the Middle East, and carried 15.7 million passengers. The company had 2,500 employees and revenues were $1.9 billion. Over this nine-year period, Norwegian has MIS Quarterly Vol. 37 No. 3/September

8 successfully used information technology in new ways, cultivating the digital infrastructure that was the focal point of our in-depth research. Methods We selected the case for our in-depth research based on two criteria. First, long-term involvement and access was deemed important, since studies of evolution benefit from rich longitudinal data. Such data also resonates well with critical realism s theorizing process, commonly referred to as retroduction, that is, taking an empirical observation and hypothesizing a mechanism that might explain that particular outcome (Danermark et al. 2002; Sayer 1992). Second, among cases to which we had access, we used a so-called extreme technique of case selection by engaging in intense data collection and analysis of a digital infrastructure perceived to be unusually successful. Extreme cases correspond to a case that is considered to be prototypical or paradigmatic of some phenomenon of interest (Gerring 2007, p. 101) and is useful for theory generation because extremes or ideal types typically define theoretical concepts. Compared to a representative case selection technique, we anticipated that the selection of the airline Norwegian would offer access to ideal types formed by the one-sided accentuation of one or more points of view (Weber, 1949, p. 90). In this regard, the case study generated conceptual constructs that manifest theorizing through idealization (Lopreato and Alston 1970; Ohlsson and Lehtinen 1997). Data Collection: We did not begin our study at Norwegian with the intention of studying the mechanisms of digital infrastructure evolution (see Plowman et al. 2007). It started as an inquiry into service innovation in a fast-growing firm. As the study unfolded, however, we discovered how Norwegian s success in terms of becoming an important player on the Scandinavian aviation market was intimately related to its evolving infrastructure. We therefore gradually appreciated the process as a paradigmatic example of digital infrastructure success and reoriented the study to inquire into the underlying generative mechanisms of this evolution. We used three methods to collect our data: interviewing, participant observation, and document analysis. First, we conducted 31 semi-structured interviews with a total of 19 respondents (we interviewed 6 respondents more than once). Some interviews were tape-recorded and transcribed verbatim, while others relied on field notes. We interviewed the CIO, two top managers, three business line managers, two business analysts, two IT managers, two systems developers, two project managers, one booking assistant, one consultant, one vendor representative, and two customer representatives. Second, participant observation was another important source of data. In addition to system demonstrations and observations of direct system use, we spent approximately 12 hours observing 7 meetings related to Norwegian IT and strategy projects. In addition to these discrete events, we conducted ongoing debriefings after meetings and numerous informal interviews with Norwegian employees. Finally, our study included a significant volume of archival data, including business plans, project plans, joint venture contracts, and IT architecture documents. We also had access to 18,846 Facebook postings of how Norwegian communicated with their customers during the European airspace ash crisis in Although many of the documents we collected were confidential and could not be used directly in this research, the material served to confirm or disconfirm interpretations made throughout the data analysis process. Data Analysis: We used a four-step approach (see Table 2) for analyzing the data collected at Norwegian. First, we used an open coding procedure to discover key events. While many events were deemed important a priori (e.g., business decisions or contract agreements), others emerged from data analysis (e.g., the importance of the IT architecture and the use of Facebook). This coding procedure helped us establish a timeline of key events that occurred over time (see Figure 3). Then, in the second step, we identified the objects of the case (see Danermark et al. 2002). We then used Hedström and Swedberg s (1998) work on mechanisms for typifying the identified objects as being potential elements in macro micro, socio-technical action, or micro macro mechanisms (see DeLanda 2006). We visualized the objects of the Norwegian case as a data display (Miles and Huberman 1994; see Table 3). The third step was retroduction, that is, the identification of key mechanisms among candidate mechanisms. We started by analyzing the interplay of objects, in particular the interplay between social and technical objects, which allowed for the identification of socio-technical mechanisms. With the infrastructure as point of departure, we tried to identify macro micro mechanisms, that is, enabling socio-technical features of the digital infrastructure. Transcripts from the cases were analyzed in order to identify these enabling conditions. These were tracked through organizational behavior (socio-technical action) and the self-feeding outcome, that is, how the emergent behavior at the micro-level increased the capabilities of the infrastructure (micro macro). At this point in the analysis, we had identified six candidate mechanisms. They were detailed and assessed through backward-chaining (Pettigrew 1985), going from outcomes to causes (mechanisms), and through forward-chaining, going from causes to 914 MIS Quarterly Vol. 37 No. 3/September 2013

9 Table 2. In-Depth Data Analysis Steps Tasks Outputs 1. Coding key events a. Identify key events in the data material b. Establish a time line of the key events 2. Identification and typifying components 3. Retroduction of mechanisms 4. Establish contexts and outcomes of mechanisms a. Identify networks of social and technical components b. Use Hedström and Swedberg (1998) for typifying components as macro micro, socio-technical action, or micro macro c. Display components and related data a. Investigate interplay between micro and macro elements to explain outcomes b. Identify and analyze candidate mechanisms. Assess explanatory power of each. c. Define mechanisms and develop measures to be used in the case survey a. Analyze mechanisms to confirm contextual conditions and outcomes b. Develop contextual typology A chronology of key events of the case (Figure 3) A set of components and related data (Table 3) Three digital infrastructure mechanisms (adoption, innovation, and scaling) including definitions and measures (Table 4) A typology of contextual conditions of mechanisms over two dimensions: control and technical architecture National network of destinations established Bank Norwegian Call Norwegian Service-oriented architecture introduced Low-price calendar established Internet bank Mobile portal In-flight broadband services Internet bookings Digital customer communication dominated Facebook used during the ash crises Figure 3. Chronology of Key Events outcomes. In this way, we assessed the explanatory power of each one of them, in relation to the empirical evidence, and finally arrived at three (see Table 4) that consistently could explain the sequence of events over time. Finally, in the fourth step, we analyzed the three selected mechanisms to establish contextual conditions and outcomes. Whether a mechanism is actualized or not is contingent (Pawson and Tilley 1997). In our analysis at Norwegian, the decentralized control and loosely coupled architecture of the digital infrastructure stood out as important conditions of the mechanisms observed. Given that these empirical results resonated well with our initial assumptions grounded in prior literature, we decided that mode of control and technical architecture would be important conditions to be investigated further in the case survey. MIS Quarterly Vol. 37 No. 3/September

10 Table 3. Events and Objects Overview Key Events Objects Data Establishing a service oriented architecture (SOA) Internet bookings Enterprise Service Bus (ESB), booking systems, IT architects, data center Internet portal, booking systems, Amadeus, users CIO and two architects designed the SOA open source software for ESB run at outsourcing data center Internet portal integration with Amadeus, allowed for direct booking user-printed tickets Low-price calendar SOA, business developers, IT staff SOA-enabled low-price calendar new user pattern triggered Digital customer communication dominating Bank Norwegian established Call Norwegian established Using Facebook during the ash crises SOA, marketing department, customers Business developers, SOA, banking systems Mobile portal, SOA, vendors, GSM network successful portal and services 85% of customer communication was electronic in 2006 the bank was innovated on experiences from the airline solutions SOA allowed for short time-to-market the telecom services extended services to airline customers mobile phones is perceived as the most important user platform Facebook, customers, crisis team fast response to the ash crisis in 2010 Facebook used for problem solving Case Findings In 2002, a virtually unknown airline, Norwegian Air Shuttle, decided to challenge the dominant airline on the Scandinavian market, SAS. The deregulation of the European airline market paved the way for Norwegian s ambition to outperform the incumbent airline through a low-price strategy. As a new entrant without legacy, Norwegian started with a IT solution only consisting of the most necessary systems for making an airline work, such as a basic booking system and a simple back-office solution. As the company expanded, however, it was soon realized that a professional approach to IT was imperative. In less than a year, the unknown airline flew more than 300,000 passengers and, given plans to grow internationally, the IT solution soon turned out to be illdimensioned. Accordingly, Norwegian hired a CIO and two IT architects with extensive experience from the airline business. Starting in 2003, this team took a strategic outlook on IT governance. The team envisioned an IT infrastructure that would need to scale over time to be at par with Norwegian s growth ambitions. Based on his earlier experiences of battling legacy systems when pursuing change ambitions, the CIO recalled: We knew exactly what we needed; a service oriented architecture, enabling easy communication and reuse of components across different technologies. We settled for a simple, but fast open-source enterprise service bus, which could be scaled up in order to handle transaction growth. Since we had no legacy systems we could implement the solutions within months, including the integration with the Amadeus system. The new architecture was mainly designed in 2004, and, as outlined below, it gradually expanded into a large-scale infrastructure over the following years. Figure 3 provides a chronology of this infrastructure evolution. Reflecting an entrepreneurial culture with little bureaucratic control, each new service was typically conceptualized in a meeting with business developers and IT seniors, and then developed and deployed during a short project. You see, commented a business director, we do not have IT projects in Norwegian, only business projects, with a clear economic objective. As an example of the agile approach, usability issues were typically not seriously addressed in early releases. However, after the launch of a new service, use patterns were systematically monitored, and used as a basis for quick adjustments in an iterative fashion. 916 MIS Quarterly Vol. 37 No. 3/September 2013

11 Internetworking with customers: Since travel agent services were considered too expensive for a low-cost airline, Norwegian s first challenge was to enable Internet bookings. In 2004, the airline launched its Internet portal to by-pass travel agents. This launch was enabled by a solution that allowed customers to print their boarding cards at home, making the traditional paper ticket obsolete. The printout tickets included a bar code, which was scanned at the gate. This strategy turned out to be successful, not least because customers quickly adopted this new type of travel processing. In fact, in 2006, when the airline flew a total of 5.1 million passengers, 90 percent of all customer interaction, including and web marketing, on-line sales, booking, and checkin, was digital. Capitalizing on the service-oriented architecture, the Internet portal gave birth to another innovation, the so-called lowprice calendar. The low-price calendar provided an overview of the cheapest flights to any chosen destination. It helped customers adjusting their travel to dates when traveling was good value for money. Addressing a problem perceived by customers in the low-price segment, the new innovation was an outstanding success, substantially increasing the number of bookings after its inception in The low-price calendar was later copied by many other airlines, including Norwegian s competitor, SAS. Branching out: In 2007, the company, somewhat surprisingly, decided to enter banking by establishing a bank called Bank Norwegian. Motivating this boundary-crossing initiative, Norwegian s CEO, stated, Today we have one of the most visited web pages in Norway, with 2 to 3 million visitors each month. We aim at coupling this traffic with bank services. In addition to the large volume of potential customers, this radical diversification could be traced to the architecture of digital infrastructure, which allowed quick integration with its banking partner s systems. As the Director of Business Development commented, We had established a very flexible IT architecture, and we realized at the time that it would be possible to innovate new services on this. First we were just brainstorming rather freely: how could a combination of brand and technology generate new business? The establishment of the Internet bank took a mere 6 months and, in 2008, it served 50,000 customers. Stimulated by the success in banking, the company launched a telecom company, Call Norwegian. Initially, Call Norwegian involved a mobile portal to enable easy airline booking, and to offer airport Wi-Fi hotspots and GSM network services. The Mobile Portal Director commented, We focused on how to make money on new services, analyzing which services we should provide ourselves, which we should buy and how they should be integrated. At the same time we are very concerned about our architecture. A chief ambition is to maintain it as clean as possible. We don t really go for cutting-edge solutions. Rather, we combine known and stable components in new ways. Between 2009 and 2011, the mobile solution was further enhanced to include cell phone-enabled bar code tickets, a wide-range GSM and mobile broadband services, and onflight broadband services (as the first airline in Europe). As the CIO commented, We strongly believe that the mobile phone will become our key customer platform. This belief proved relevant earlier than anticipated. In April 2010, a volcano in Iceland, the Eyjafjallajøkull, erupted and an enormous, shifting ash cloud covered parts of Europe for about 10 days. Most of the North and Central European airspace was closed, and hundreds of thousands of air passengers were grounded. Angry passengers started to contact airline and travel agent call centers, which quickly collapsed. As an improvised response, Norwegian quickly established a large-scale Facebook-enabled customer communications and problem-solving operation, which actually addressed most of the problems. Facebook was not only used for information purposes, but also to negotiate customer rerouting and new tickets. The team leader commented afterward, Frankly, we do not know where this Facebook thing will take us, but we certainly realized that our customers preferred this communication channel in this urgent situation. Looking back at this evolution, Norwegian was characterized by modularity in both organization and technology. The business units of Norwegian were loosely connected, allowing for modular innovation, while still being able to draw on business and technical resources of other units. As an example, the IT architect of Norwegian strongly believed that successful infrastructure evolution depended on balancing increasing variety, on the one hand, and modularization, on the other. If increasing variety (resulting from continuous innovation) was not balanced with continuous modularization of the architecture, it would lead to chaos. Indeed, the IT architect reasoned, My first and top priority is protecting the integrity of the SOA structure, no matter how important a project deadline is. Mechanisms at Norwegian The remarkable success of Norwegian s digital infrastructure was characterized by growth along three dimensions: (1) ser- MIS Quarterly Vol. 37 No. 3/September

12 vices, such as the web portals, the low-price calendar, the bank, and mobile services; (2) users, from a few thousand in 2002 to several million in 2011; and (3) stakeholders, as Norwegian aligned a number of networks to its infrastructure over time. Our fieldwork revealed at least two conditions that provided a powerful environment for digital infrastructure evolution. First, the enabling service-oriented architecture, which allowed the addition, replacement, or change of components with relative ease. Second, the entrepreneurial and open culture that supported an evolution that was not totally dependent on top management directives. While these conditions triggered the evolution, our data analysis showed that there were three mechanisms behind the successful evolution observed at Norwegian. The innovation mechanism: As evidenced by the testimonies of our respondents, there existed a profound optimism that Norwegian would be able to expand its business proposition beyond its original scope. The malleability of the service-oriented architecture created a space of possibilities that served as a melting pot for innovation. In fact, this space of possibilities spawned a pace of service innovation that, at the time, was largely unheard of in the institutionalized airline industry. The infrastructure malleability fostered a creative process involving IT personnel, business managers, and external vendors, which allowed them to start recombining infrastructure resources such as technical elements, business routines, vendors, and user groups. This recombination resulted in new ideas for services, which in many cases materialized at Norwegian. These services were typically designed in relatively short, intensive projects, and then launched. In the Norwegian case, it had to do with patterns of assembling different components into new services (Figure 4). We refer to this mechanism as the innovation mechanism, that is, a self-reinforcing process by which new products and services are created as infrastructure malleability spawns recombination of resources. The adoption mechanism: Norwegian managed to attract customers to purchase tickets online. Although the webbased infrastructure initially was relatively unsophisticated, it was easy to use and relied on resources readily available to customers. For instance, customers quickly embraced the laser printing of tickets, available at their work or home office. Indeed, the growth was so strong that by 2006 only two years after the introduction of the services online buyers of tickets were a majority of customers (85 percent). This convinced top management that the Internet strategy was paying off, and that the airline should further exploit the momentum of growth. Accordingly, with more users adopting the infrastructure services, more resources were allocated to improve and extend the infrastructure. For instance, resources were spent on maintaining rapid response time in spite of increased website traffic, which, in turn, allowed for more services offered. As the number of users of the digital infrastructure increased, revenues increased, which, in turn, attracted more resources to the infrastructure for providing more and improved services. We refer to this mechanism as the adoption mechanism (Figure 5), that is, a self-reinforcing process by which more users adopt the infrastructure as more resources invested increase the usefulness of the infrastructure. As indicated above, new services is the outcome of the innovation mechanisms and more services are offered is the starting point of the adoption mechanism. It makes analytical sense to keep the two mechanisms apart, rather than viewing them as parts of a single, more complex mechanism. Essentially, the two mechanisms involve different sets of actors. While business and technology developers drive the innovation mechanism, users drive the adoption mechanism. The scaling mechanism: The infrastructure at Norwegian did not only succeed by expanding its services and user base. It also increased its scope by including the partner solutions of its emerging network of stakeholders. Norwegian s business infrastructure was unusually open, which lowered the barriers for outside actors to integrate with the airline s infrastructure. For instance, early on, Norwegian standardized its central business bus to achieve compatibility with the European Amadeus system, opening up an entire array of possible partners. Furthermore, in 2005, Norwegian provided full access (through an application programming interface referred to as the Norwegian Application Interface) to its services to agencies and search engines. As a result, Norwegian started to attract partners such as travel agencies, other airlines, hotel chains, and car rental companies. Partner solutions were integrated with the web portal, which, as a result, increased the reach of the infrastructure. We refer to this as the scaling mechanism (Figure 6), that is, a self-reinforcing process by which an infrastructure expands its reach as it attracts new partners by creating incentives for collaboration. Table 4 summarizes the definitions of the mechanisms generated from our in-depth case study research at Norwegian. The case survey, presented in the next section, uses these conceptualizations as a starting-point for analyzing how mechanisms interact in infrastructure evolution. Looking back at the Norwegian case study, there were clear indications that the three mechanisms interacted. The innovation mechanism 918 MIS Quarterly Vol. 37 No. 3/September 2013

13 Digital Infrastructure Technical malleability New services Recombination Figure 4. The Innovation Mechanism Digital Infrastructure More services offered More resources invested More users adopt Figure 5. The Adoption Mechanism Digital Infrastructure Partners attracted Reach expanded Partner solutions added Figure 6. The Scaling Mechanism Table 4. Mechanisms Mechanism Innovation Adoption Scaling Definition A self-reinforcing process by which new products and services are created as infrastructure malleability spawns recombination of resources A self-reinforcing process by which more users adopt the infrastructure as more resources invested increase the usefulness of the infrastructure A self-reinforcing process by which an infrastructure expands its reach as it attracts new partners by offering incentives for collaboration MIS Quarterly Vol. 37 No. 3/September

14 interacted with the adoption mechanism, in the sense that it provided the new services that attracted more users. At the same time, the adoption mechanisms provided the financial resources necessary to maintain the innovation mechanism. We also observed that the scaling mechanism increased the space of innovation by adding more elements to the infrastructure. This type of contingencies between mechanisms is explored in more depth in the following sections. The Case Survey Our in-depth case study research at the unusually successful Norwegian company yielded three mechanisms of digital infrastructure evolution. We chose the company as an extreme case, since deriving ideal types is typically seen as a useful starting-point for theory generation (Gerring 2007). However, to substantiate this theoretical inquiry, we decided to survey whether (1) these mechanisms were activated and (2) resulted in a successful outcome, in other cases as well. Taking a critical realist stance, we hypothesized the existence of equifinality in digital infrastructure evolution. In other words, we anticipated that there would be a set of different causal paths by which the mechanisms could be combined to produce successful outcomes. To investigate these issues further, we conducted a case survey (Larsson 1993) of 41 cases of infrastructure evolution reported in the scholarly literature to analyze its space of configurations. Configurational thinking has emerged as powerful way of studying any multidimensional constellation of conceptually distinct characteristics that commonly occur together (Meyer et al. 1993, p. 1175). Among critical realists, Pawson and Tilley s (1997) thinking epitomizes the promise of configurational analysis and, as outlined in the theoretical background above and further elaborated in the description of methodological choices below, their work serves as a backdrop to our analysis. Methods A case survey involves systematic collection and coding of case studies, where preference is given to the case characteristics rather than the original authors analysis and conclusions (Yin and Heald 1975). Bridging nomothetic surveys and ideographic case studies, the case survey method is an inexpensive way of learning from many rich case studies (Larsson 1993) and is ideal for configurational theorizing (Fiss 2007). Case Selection and Data Collection: Similar to Rivard and Lapointe s (2012) recent study of IT implementers responses to user resistance, we (1) collected a large sample of digital infrastructure studies from scholarly sources, (2) refined the initial sample using inclusion and exclusion criteria (Yin and Heald 1975), and (3) coded the cases using the definitions of the mechanisms identified in the in-depth study. The initial sample, including journal articles, peer-reviewed conference papers, book chapters, and working papers, covered well over 60 cases. In our further investigation, the inclusion criteria were (1) that the case documented the evolution of a digital infrastructure, and (2) that the case narrative was long enough to provide sufficiently rich data. The main exclusion criterion was that the case was not rich enough to make it possible to determine whether mechanisms were actualized or not. All in all, we included 41 cases in our sample (see Appendix). The research database included cases from articles published in information systems journals (e.g., MIS Quarterly, Information Systems Research, Journal of AIS, and Information & Organization), medicine (e.g., Methods of Information in Medicine), development studies (e.g., Information Technology for Development), as well as science and technology studies (e.g., Science, Technology & Human Values). It also included cases from articles published in conference proceedings (e.g., the International Conference on Information Systems and the International Federation for Information Processing). In addition, cases were selected from book chapters and working papers. The cases covered a variety of settings including banking, healthcare, natural resources, pharmaceutics, public sector, and telecom. Coding: We used Pawson and Tilley s (1997) configurational framework for designing a coding scheme focusing on three elements: context, mechanisms, and outcome. First, we drew on our in-depth case study and the literature review to distinguish technical architecture and organizational control as two key contextual conditions. In the in-depth case study, we discovered that a loosely coupled architecture and decentralized control were important conditions at Norwegian for activating the power of the identified mechanisms. Based on this insight, we returned to our database of related literature and studies to (1) assess what other possible architectures were present in digital infrastructure evolution and (2) assess what other modes of control were present. In the architecture case, our assessment yielded several examples of infrastructures that were based on tight integration (see Hanseth and Braa 2000). We decided to label this category tightly coupled architecture. In the case of control as contextual condition, previous studies strike a difference between top-down implementation and bottom-up cultivation of infrastructures. We decided to label this distinction as centralized versus decentralized control (see Kirsch 2004; Yoo et al. 2010). 920 MIS Quarterly Vol. 37 No. 3/September 2013

15 Then, the three mechanisms (and their definitions, see Table 4) generated from the in-depth study were used as a basis for our coding of the studies included in the case survey. The coding of mechanisms required careful assessment of whether the mechanism in question in fact was actualized. For example, most (if not all) digital infrastructure projects have the ambition of user adoption, and therefore involve management interventions designed to achieve this. However, the sheer presence of management intervention to achieve user adoption was not considered sufficient to code the adoption mechanism as actualized. Rather, this would require evidence that user adoption was self-reinforcing, as described in Figure 1. As an example, consider that a management team may stimulate user adoption (action-formation) through a commercial campaign in the hope that it would increase user adoption of the infrastructure. However, if we, in this hypothetical example, could not verify that this management intervention paid off in a self-reinforcing process that generated resources (transformation) that maintained user adoption beyond the end of the campaign, we reasoned that the mechanism was not actualized. Similarly, the other two mechanisms were coded positively only to the extent that they were self-reinforcing. In this context, it should be emphasized that, in specific cases where mechanisms were coded as unactualized, the claim of actual presence of such unactualized mechanisms builds on an assumption of coherence across cases of infrastructure evolution. Finally, we coded outcomes based on the relative success of the evolution process. Starting from the assessment of the author(s), we critically examined if the infrastructure had reached a state where it displayed a capacity to endure, and adapt to environmental changes. In particular, we interpreted if (1) the infrastructure filled a relevant role in its business ecosystem, and (2) the extent to which the infrastructure s affordances were possible to escape for its stakeholders. If in doubt, we supported our interpretations by disciplined imagination of possible scenarios through which individual stakeholders would be able to reverse the infrastructure s state of success or failure. Three people independently coded the 41 studies included in the sample. In addition to the two authors of this paper, a Master s student served as a coder. In case of disagreements, the coders reread the case and discussed the coding until 100 percent agreement was achieved. The inter-reliability of the coding was approximately 85 percent in the first round of independent coding. Data Analysis: We first examined the relationship between the eight possible combinations of the three mechanisms (adoption, innovation, and scaling (AIS), AI, AS, IS, A, I, S, and none) and their outcomes (Table 5). This revealed clearly that the absence of activated mechanisms was strongly associated with a negative outcome, and that two configurations were highly successful. Second, in order to understand the causal paths of the two successful configurations (AS and AIS), we conducted a qualitative investigation of all cases associated with these configurations. The first step involved comparative analysis between the cases in the same configuration. This analysis revealed how the mechanisms interacted. The second step involved a comparison of cases across the two successful configurations. This helped us understand why both AS and AIS produced a successful outcome. Third, we analyzed contextual conditions and their relation to the two configurations. One interesting observation was that the activation of mechanisms in one configuration (AS) appeared to be less dependent on the two contextual conditions advocated in the literature than the other configuration. Case Survey Results Table 6 outlines the descriptive statistics of the 41 cases of infrastructure evolution included in our sample. It shows the frequency distribution of the cases across mechanism configurations and evolution outcome. Since the three mechanisms (adoption (A), innovation (I), scaling (S)) can be combined in eight different ways (none, A, I, S, AI, AS, IS, AIS), there are eight logically possible configurations of which a particular case can be a member (see Appendix for coding details of each case). Among the cases in the sample, the IS subset was the only mechanism configuration that remained unactualized. Furthermore, we identified 11 cases (26.8 percent) where none of the 3 mechanisms were actualized, all of which resulted in unsuccessful digital infrastructure evolution. At the other end of the spectrum, we identified 12 cases (29.3 percent) as members of the AIS subset and 7 cases (17.1 percent) as members of the AS subset. These 19 cases were coded as successes, and will be the primary focus for our further analysis. Our in-depth study at Norwegian established three individual mechanisms: adoption, innovation, and scaling. It also suggested that the actualization of all three of them in the same case would effectively contribute to a successful outcome of digital infrastructure evolution. 9 The descriptive statistics of our case survey support this suggestion by indicating a strong correlation between the AIS configuration and a successful 9 As highlighted by one of the anonymous reviewers, this is not to suggest a closed system. Consistent with critical realism assumptions, there might always be other mechanisms lurking around the corner. MIS Quarterly Vol. 37 No. 3/September

16 Table 5. Case Survey Data Analysis Steps Tasks Outputs 1. Descriptive statistics a. Examine relationships between combinations of mechanisms and outcomes b. Identify highly successful and highly unsuccessful combinations of mechanisms 2. Qualitative analysis a. Comparative analysis of cases within the two successful combinations (AS and AIS) b. Comparative analysis between the two successful configurations c. Examination of alternative explanations 3. Analysis of contextual conditions a. Analyze the effect of decentralized control on the two combinations b. Analyze the effect of loosely-coupled architecture on the two combinations c. Assess explanatory power of the configurations Frequency distribution of the cases across combinations of the three identified mechanisms (Table 6) A systematic assessment of causal relationships in the successful cases. Two configurations of successful infrastructure evolution (Figure 7) Completion of two successful causal paths in digital infrastructure evolution Table 6. Descriptive Statistics Mechanism Unsuccessful Successful Combination N (%) Infrastructure Infrastructure Total NONE 11 (26.8%) (100%) A 3 (7.3%) (100%) I 4 (9.7%) (100%) S 1 (2.4%) (100%) AI 3 (7.3%) (100%) AS 7 (17.1%) (100%) IS 0 (0%) (100%) AIS 12 (29.3%) (100%) Total: 41 (100%) 17 (41.5%) 24 (58.5%) outcome. Beyond this confirmation of the Norwegian case study results, we can make at least two additional observations. First, the actualization of a single mechanism is insufficient for leading to a successful outcome. For instance, our case survey suggests that the innovation mechanism alone is insufficient for a successful outcome. Although there were a few exceptions, our results show that the innovation mechanism is contingent on the adoption and scaling mechanisms. These findings resonate well with critical realism s assumption of contingent causality, suggesting that the outcome of a mechanism depends on other mechanisms (Elder-Vass 2010; Sayer 1992). Second, the results also suggest that the actualization of the innovation mechanism is not a necessary condition for success if the adoption and scaling mechanisms are interacting in the same evolution process. This is interesting, since our analysis of the Norwegian case suggested it as a vital mechanism for adoption and scaling in the AIS configuration. This insight indicates that the natures of the AIS and AS configurations are qualitatively different and warrant further attention. In view of these initial insights of our case survey results, we further investigated how the mechanisms interacted in the two successful configurations (AIS and AS). In the Norwegian indepth case study (as an example of the AIS configuration), we noted how the three mechanisms interacted. In what follows, we investigated whether the same type of interaction existed in the 12 AIS cases included in the survey case. We also investigated the seven cases with the AS configuration to further understand how the adoption and scaling mechanisms alone can interact to produce successful infrastructure evolution. In doing so, we also turned to the contextual conditions of architecture and mode of control for both configurations to understand the differences in causal paths. Manifesting our 922 MIS Quarterly Vol. 37 No. 3/September 2013

17 Figure 7. Configurations of Digital Infrastructure Evolution configurational perspective, Figure 7 portrays the causal paths that we identified through our analysis, including the number of cases that followed each path. Adoption-Innovation-Scaling: Our examination of the AIS cases (Case #6, The Internet; Case #10, Environmental Health in the French Public Health Administration; Case #12, Local Danish Electronic Patient Record initiative; Case #22, The SWIFT Network; Case #23, Criminal Case Management in Finland; Case #27, Pharmaceutics; Case #29,Gateways versus Standards; Case #30, Internet IPv6; Case #32, Telecom; Case #33, Broadband Mobile Services in South Korea; Case #39, U.S. Petroleum Company; Case #41, and U.S. Retail Company) 10 included in the case survey revealed a similar interplay of mechanisms as we found in the Norwegian case study. The innovation and adoption mechanisms fed on each other, which created fertile ground for the scaling mechanism as combinatorial possibilities (innovation) increased and the provision of more users (adoption) leveraged the scope of the infrastructure. In the Local Danish Patient Record initiative (Case #12, Aanestad and Blegind Jensen 2011), as one of 10 See Appendix for sources and coding. three examples 11 summarized in Table 7, the innovative way of using existing systems to achieve standardized extraction of patient data (SEP) triggered adoption from county hospitals, which, in turn, created the resources for establishing a national SEP project that could support the initiative s scale and scope. Starting as a local initiative supported by two county hospitals, the SEP infrastructure counted 4.3 million Danes as users some 9 years after its inception. Similar interaction between mechanisms existed in the seemingly quite different SWIFT network case (Case #22, Scott and Zachariadis 2010), in which 68 banks in 11 countries joined forces to create an infrastructure for financial transactions that developed from an efficiency initiative driven by a closed society of banks to a network innovation of world-class standing (p. 2). The widespread adoption by banks of SWIFT in the 1970s created incentives for innovating the infrastructure further, where speed, costs, volume, security, and uniform formats were benefits that were targeted in a series of improvements of the infrastructure over the years. 11 Our selection of illustrative examples of the AIS configuration was done with emphasis on making sense to readers without too much contextual background. MIS Quarterly Vol. 37 No. 3/September

18 Table 7. Content Analysis of Adoption Innovation Scaling Configuration 12. Local Danish Electronic Patients Records initiative: The SEP project in Denmark was a local initiative in 2000 to share patient data, but expanded into a national solution during a nine-year period. 22. International Financial Communication Network: SWIFT is an infrastructure for financial transactions, now used in 200 countries. Starting in 1971 as a standard, SWIFT went live in 1977 and expanded into a global infrastructure. 23. Criminal Case Management in Finland: The Criminal Case Management system in Finland was introduced in 1992, and developed into a national integrated infrastructure. Contextual conditions Mechanisms Outcome Reference Architecture: Modularized, many systems involved Control: Distributed Architecture: SWIFT is a network, with a common standard implemented in a large number of financial systems Control: Distributed, SWIFT is owned by member banks Architecture: Modular, expanded into service oriented architecture Control: Centralized (but managed by representatives of user institutions) Innovation: Started as a simple problem-solving initiative, using existing systems in new ways. This was cleverly expanded into a national patient database. Adoption: Starting with pilot in two counties, gradually expanded into a national solution. Patients were also allowed access. Scaling: First accessing one EPR and PAS, later including all such systems in Denmark into the solution. Innovation: Building on Telex solutions, financial actors and technology vendors designed and developed the network with continuous innovation. Packet switching was introduced in 1979, and SWIFT 2 was launched in Adoption: Initiated by 68 banks in 11 countries. As services expanded, even more banks and countries joined. Scaling: The expansion was characterized by negotiations and adaptations. Moving from a closed society, SWIFT became a global network. Innovation: The Sakari solution helped transforming the whole legal criminal case process, and was extended with new services annually. Adoption: Courts, police, prosecutors and prisons were gradually enrolled as new services were integrated. Scaling: Linking into other structures was a key strategy. Our empirical material describes two Danish initiatives, where a national project failed to deliver interoperable Electronic Patient Record systems while a small, local solution grew and now offers a nation-wide solution for sharing patient record information (p. 161). SWIFT developed into one of the world s key infra-structures, proving fast, seamless and secure exchange of financial transactions. Over time, what began as a closed society grew into an industry cooperative supporting an enthusiastic community of practice and transformed into an unexpected network phenomenon (p. 2). Sakari was considered a success in Finland. It is recognized that it has helped make criminal proceedings quicker and more accurate, () and the system has also helped to create a useful exchange of information and practices among the different organizations and actors involved (p. 123). Aanestad and Blegind Jensen (2011) Scott and Zachariadis (2010) Fabri (2009) The financial infrastructure scaled considerably in terms of its coverage and scope, and has since long become the most comprehensive one in the global bank sector. Regarding the Criminal Case Management system in Finland (Case #23, Fabri 2009), innovation in the civil procedure rules (e.g., elimination of original signature requirement) boosted new civil case management applications. The new infrastructure was rapidly adopted by debt collecting companies, while lawyers use progressed well but more slowly. Stimulated by this success, the infrastructure increased its reach by expanding into criminal cases, which usually is considered more difficult since more stakeholders are involved. In view of the similarities in interaction between the mechanisms in the AIS configuration cases, we further explored the contextual conditions that actualized the AIS configuration. As shown in Figure 7, and in line with the extant infrastructure literature, there was a high correlation between loosely 924 MIS Quarterly Vol. 37 No. 3/September 2013

19 coupled architecture and decentralized control and the AIS configuration. One plausible explanation is that the innovation mechanism is a less predictable process than adoption and scaling, and that the innovation mechanism is dependent on a space of possibilities (Bygstad 2010; Davenport and Short 1992) that centralized control and tightly coupled IT architectures cannot trigger. Adoption-Scaling: Compared to the AIS cases, the examination of the AS cases (Case #1, Health IS in Developing Countries; Case #9, Legal IS in Austria; Case #15, Power Systems; Case #21, Health IS in India; Case #28, OSI Versus IP standards; Case #34, University Software; and Case #36, E-Government in Germany) 12 showed significantly different results. The results suggested that as long as the adoption and scaling mechanisms were actualized, the powers of the innovation mechanism did not have to be actualized. In view of our analysis of the AIS configuration, where we noted that the innovation mechanism helped in actualizing the adoption mechanism, this result requires further analysis. The Legal IS in Austria (Case #9, Bernroider and Koch 2009), as one example summarized in Table 8, was a result of inhouse development work carried out by the Federal Chancellery, sometimes done with the support of external systems development firms. The system was initially adopted for increasing efficiency. Over time, however, more users including the ministries and eventually citizens were adopting the infrastructure. Once citizens came into the picture, a webbased version was developed in parallel to the system used inhouse to facilitate user access. The reach of the infrastructure increased as citizens were provided comprehensive law information through this web-based system. Later on, the infrastructure was further extended in reach by digitally supporting the process for producing judicial material from inception to Internet publication. This coincided with the Council of Ministers decision to adopt the infrastructure in all ministries. Similar interaction between the adoption and scaling mechanisms could be observed in the Health in India (Case #21, Sahay and Walsham 2006) and e-government in Germany (Case #36, Pipek and Wulf 2009) cases. Given this interaction between adoption and scaling, which was qualitatively different from the mechanisms interaction in the AIS cases, we turned to the contexts of the cases. As illustrated in Figure 7, three (Legal IS in Austria; Health IS in India; and e-government in Germany; see Table 8) out of the seven AS cases were characterized by centralized control and a tightly coupled architecture. This breaks with some of the 12 See Appendix for source and coding. seminal works in the infrastructure literature, which argue that loosely coupled architecture and distributed control are important elements in making evolution processes successful. It appears that the adoption and scaling mechanisms reinforce each other in a way that leads to successful evolution, and that central control and tightly coupled architecture sometimes are important conditions in making this happen. For instance, in the Health IS in India case, centralized control supported the scaling of the infrastructure beyond the pilot to align health centers. Increasing the reach, in turn, the health IS solution became more attractive to adopt. However, as a concluding remark, it should be emphasized that our investigation of contextual conditions of the AS configuration does not provide a clear-cut picture. Although being beyond the scope of this study, this observation indicates that there exist other contextual conditions that interact with these mechanisms, suggesting an opportunity for further research. Discussion The adoption of critical realism has helped us to explore a number of issues that challenge the way we think about digital infrastructure. In particular, we highlight the existence of three generative mechanisms (adoption, innovation, and scaling) that serve as causal powers in digital infrastructure evolution. In addition, we develop a configurational perspective that suggests multiple causal paths of such evolution. In what follows, we outline implications for infrastructure research and discuss the usefulness of critical realism in information systems research. In addition, we highlight the study limitations and future issues of research. Implications Our work synthesizes and conceptualizes earlier insight on self-reinforcing mechanisms (Grindley 1995; Katz and Shapiro 1985; Sydow et al. 2009), innovation (Arthur 2009; Schumpeter 1980), and scaling (Hanseth and Lyytinen 2010; Pollock et al. 2007; Sahay and Walsham 2006) as generative mechanisms. This is useful, since the causal powers of each of the mechanisms have been largely masked in prior research. Our critical realist conception of digital infrastructure recognizes that mechanisms act transfactually (see Fleetwood 2009) and that the actualization of their powers is contingent on other mechanisms. In this regard, our research indicates that successful digital infrastructure evolution cannot be explained by merely attending to a single mechanism. Among the 41 cases included in our sample, there were only 3 cases where an individual mechanism coincided with a successful outcome (see Case #18, Hanseth and Aanestad 2003; MIS Quarterly Vol. 37 No. 3/September

20 Table 8. Content Analysis of Adoption-Scaling Configuration 9. Legal IS in Austria: The LIS system is a legal repository and supports the workflow for law making in Austria. Developed since Health IS in India: The design, development, and implementation of a Health Information System in Southern India. 36. e-government in Germany: The case is a solution to support work processes connecting the state government located in the state's capital with the German Bundesrat. Contextual Conditions Mechanisms Outcome Reference Architecture: Tightly coupled (first mainframe, then Internet version) Control: Centralized (managed in-house in ministry) Architecture: Tightly coupled (but adaptable) Control: Centralized (through HISP project and state authorities) Architecture: Tightly coupled workflow system Control: Centralized, cooperation Adoption: First, only internal users, then professional users, and finally the public. Scaling: The Internet version was launched in 1996, and extended with elaw access. Adoption: Starting with a simple solution and pilot users, more services were added, which increased the user base. Scaling: Starting with a pilot, the solution was scaled in two steps, first to 46 health centers, then to the whole state. Adoption: Comprehensive requirements elicitation process with users, started growing use and adaptation. Scaling: A solution that first was proprietary, and later was expanded to Internet technology. This facilitated the alignment of new stakeholders. The LIS was used by 4.5 million users per month, and was considered successful, both in terms of internal efficiency and public access. It ensured support for the law process. It provided transparency and services to citizens. The HISP solution was in full use in Andhra Pradesh. The infrastructure was scaled to support a whole state in a lowresource setting. Adoption, although challenging, was steadily increasing. The solution was considered successful, with a consistent growth of services and users. Transition to Internet technology was problematic, but solved. Bernroider and Koch (2009) Sahay and Walsham (2006) Pipek and Wulf (2009) Case #31, Rolland and Monteiro 2002; Case #20, Scott and Walsham 1998). In all of the other 21 successful cases, the outcome was traced to a configuration of two or three mechanisms. Although there is accumulating evidence on what drives infrastructure evolution in the literature, the generative mechanisms reported in this paper offer the analytical distinctiveness needed not only to zoom in on specific aspects of infrastructure but also to zoom out to understand its contingencies. In addition, while the literature is full of testimonies that express the complex relationships between elements that make up an infrastructure (Braa et al. 2007; Ciborra et al. 2000; Ciborra and Failla 2000; Hanseth et al. 2006), there have been few, if any, attempts to formulate perspectives that allow the simultaneous study of multiple causes. Concurring with its critical realist underpinnings, our configurational perspective recognizes both the inherent complexity of infrastructures and the need of an analytical lens for making sense of them. As an example, consider that we observed that successful infrastructure evolution does not depend on the innovation mechanism as long as the powers of the adoption and scaling mechanisms are actualized. Both the AS and AIS configurations lead to successful evolution. Such equifinality is accommodated by our configurational perspective, which allows investigation of specific causal paths as well as the multiplicity characterizing digital infrastructure. Moreover, previous work on digital infrastructure has suggested that centralized control is detrimental to the outcome of the evolution process (Ciborra et al. 2000). Our research provides a less polarized view, where we found significant empirical support for the prevalent stance in the case of the AIS configuration, while our evidence for the AS configuration tells another story. The same applies to architecture: while a loosely coupled architecture is found to be a valuable trigger for the AIS configuration, a tightly coupled architecture does not impede the AS configuration from a successful outcome. In other words, it seems that there is no specific relationship between mode of control and architecture in successful cases of combining the adoption and scaling mechanisms. 926 MIS Quarterly Vol. 37 No. 3/September 2013

21 We believe that these findings have important implications for practitioners who face the challenge of managing the evolution of digital infrastructures. Understanding the difference between the two configurations is seminal for the choice of management strategy. The AIS configuration describes the causal path of the really ambitious undertakings, where interaction between the three mechanisms is crucial, and where the innovation mechanism should be targeted as the driver. Typical examples of such projects are the Norwegian (our indepth case study) and the International Financial Communication Network (Case #22, Scott and Zachariadis 2010) cases. In such cases, managers should note that the dynamics of the configuration require a loosely coupled architecture and decentralized control in order to create the space of possibilities necessary for actualizing the innovation mechanism. Also, tight scheduling is detrimental, because the configuration feeds on exploration until momentum is established. Our study also suggests that the AS configuration involves lower stakes than AIS because the interplay between the adoption and scaling mechanisms is relatively straightforward. It allows for a wider choice of management interventions. Seeking to actualize this configuration, managers should have confidence in traditional project management techniques, and observe that both loosely coupled and tightly coupled architectures may be effective. The Usefulness of Critical Realism in Information Systems The promises of critical realism as a philosophical tradition for information systems research have been voiced for some time now (Mingers 2004, 2010, Smith 2010). However, to date, there is a paucity of empirical research, underpinned by critical realist assumptions, that makes substantive contributions to established streams of information systems research. While there exist a few exceptions (Bygstad 2010; Smith 2010; Volkoff et al. 2007), current writings on critical realism in our discipline mainly provide useful conceptual guidance. Our research is an early example to challenge some of the conventional wisdom in the extant literature of a substantive area of information systems research. The delay between the initial recognition of a philosophical tradition and its wider adoption in the community is understandable. As an applied discipline, information systems is largely motivated by its members capacity to generate knowledge with a capacity to, directly or indirectly, contribute to the corresponding community of practitioners (Lyytinen 1999). In this regard, recognition of new developments and directions in the philosophy of science is a necessary but not sufficient step for paving the way for a philosophical tradition in the discipline. For instance, it took some 10 years until the early writings of Boland, Orlikowski, and Walsham on interpretive research were appropriated in the field as a broadly recognized basis for conducting high-quality research. One important element of this consolidation was examples of empirical research that could demonstrate its value in generating new knowledge deemed relevant by the community. In doing this, they then served as sources of inspiration for research to come. In a similar vein, we view this article as an intermediate step between the pioneering writings on critical realism and its adoption in wider circles in the community. In particular, we view the research design, combining the in-depth case study and case survey methods, and the adoption of configurational thinking as a promising direction for leveraging qualities of critical realism in our discipline. For instance, as the field is beginning to deal with complex phenomena such as digital innovation (Yoo et al. 2010), digital infrastructure (Tilson et al. 2010), and platforms (Tiwana et al. 2010), conceptions of causality that recognize contingency and multiple paths are needed (see El Sawy et al. 2010). Our configurational perspective offers an approach to accommodate such a view on causality that can be reused in other settings. As indicated in the implications section, we offer a number of contributions to extant infrastructure literature that can be traced back to our adoption of critical realism for information systems purposes. Limitations and Issues for Future Research Future studies could address several limitations in our work. First, as noted by Rivard and Lapointe (2012), the use of secondary data in case survey research certainly introduces some limits to what can be inferred from the cases included in the sample. The cases were originally written for a different purpose, meaning that it would be unrealistic to imagine that we would be able to create a situated understanding of the particulars associated with each of the cases. However, our use of inclusion and exclusion criteria for deciding which cases to include in the sample restricted our inquiry to studies that reported sufficiently rich accounts of the case setting. In order to offer scholars of infrastructure the opportunity to challenge our coding, we also included an overview of the coding in the Appendix. This makes it possible for original contributors to assess our coding, and it enables use of our data material in future research. Second, the use of the case survey method necessarily quantifies qualitative data in a way that risks draining ideographic accounts of their richness. We compensated for this loss of situated understanding by considering 41 cases in the same study in a relatively ideographic MIS Quarterly Vol. 37 No. 3/September

22 manner. Third, mechanisms are causal structures that generate observable events, and we offer an understanding of three mechanisms, as well as their combinations and contextual conditions, that lead to successful infrastructures. We acknowledge that the granularity of our analysis of causality is at a relatively high level, suggesting the existence of nested causal paths in digital infrastructure evolution left unaddressed in this study. Thus, we do not claim that we have discovered all of the mechanisms relevant for infrastructure evolution. For instance, while identifying mechanisms of successful evolution of digital infrastructures, we have not addressed negative self-reinforcing mechanisms. One example of such a mechanism is described by Hanseth et al. (2006) as reflexive standardization. Generally increasing the complexity of an infrastructure, this mechanism has been confirmed in recent cases, such as the European ecustoms case (Case #25, Henningsson and Henriksen 2011). Future research that adopts critical realism for studying negative selfreinforcing mechanisms would be worthwhile. Finally, focusing on successful configurations, our research primarily deals with the equifinality of infrastructure evolution. While our case survey findings also indicate multi-finality, we did not further analyze why particular configurations result in different outcomes (e.g., A, I, and AI). Our understanding of digital infrastructure would benefit from future research on this issue. Conclusion This paper proposes an alternative understanding of digital infrastructure evolution, which emphasizes the relevance of more closely examining its generative mechanisms. The paper details and illustrates a critical realist approach to digital infrastructure where configurational thinking serves as a vehicle for understanding the combinations of mechanisms that lead to successful evolution. We suggest that this approach may serve as a foundation for informing our understanding, as well as future studies, of digital infrastructure and its inner workings. Our perspective provides insights into the contributions and limitations of previous understandings of digital infrastructure. To date, the four streams of digital infrastructure research identified in our literature review have paved the way for establishing an area of research that recognizes the arrays of systems and technologies that confront today s managers and CIOs, rather than the conventional inquiry in information systems within the confines of the single system. However, as our research shows, conventional wisdom in the area falls short when it comes to articulating the multiple paths by which successful digital infrastructure evolution comes about. In the extant literature, there is a tendency to offer partial explanations, rather than focusing attention on the complete set of key mechanisms and their interaction. This is problematic since it tends to inhibit a comprehensive understanding of how and why digital infrastructures evolve the way they do across cases. In response, our critical realist approach accommodates both the interpretivist and positivist assumptions manifested in the extant infrastructure literature. The plausibility of this accommodation is demonstrated in the paper by offering theoretical implications that challenge some of the hegemony in infrastructure studies. It may appear somewhat ironic that our perspective draws on many of the findings already available in the area, yet brings new light on established truths by introducing new philosophical assumptions. We attribute this result to the power of a philosophical tradition, critical realism, which offers a set of new pillars for approaching substantive areas in information systems. We hope that our example will inspire others to adopt critical realism in their attempts to advance areas of information systems research where the findings in prior literature need to be released from some of their long-established convictions. Acknowledgments We thank Carsten Sørensen, Olga Volkoff, Youngjin Yoo, the two anonymous reviewers, the associate editor, and the senior editors for constructive and insightful comments on earlier versions of this manuscript. Special thanks to Ole Hanseth for intellectual support in designing and crafting this research. We are also thankful for the feedback received when presenting our work to researchers in the global infrastructure group at the Department of Informatics, University of Oslo. 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A Using the Case Survey Method to Analyze Policy Studies, Administrative Science Quarterly (20:3), pp Yoo, Y., Henfridsson, O., and Lyytinen, K The New Organizing Logic of Digital Innovation: An Agenda for Information Systems Research, Information Systems Research (21:4), pp Yoo, Y., Lyytinen, K., and Yang, H The Role of Standards in Innovation and Diffusion of Broadband Mobile Services: The Case of South Korea, Journal of Strategic Information Systems (14), pp Zammuto, R. F., Griffith, T. L., Majchrzak, A., Dougherty, D. J., and Faraj, S Information Technology and the Changing Fabric of Organization, Organization Science (18:5), pp Zittrain, J. L The Generative Internet, Harvard Law Review (119), pp About the Authors Ola Henfridsson is a professor of Information Systems and Management at Warwick Business School, University of Warwick. He is also an adjunct professor at the Department of Applied Information Technology, Chalmers University of Technology. His research interests include digital innovation and technology management. Ola s research has been published in Information Systems Research, MIS Quarterly, and other journals in the information systems discipline. He is a senior editor of Journal of Information Technology and a former senior editor of MIS Quarterly. He also serves on the editorial boards of Information Technology and People and Journal of the Association for Information Systems. Bendik Bygstad is a sociologist who is currently a professor at the Norwegian School of Information Technology, and an adjunct professor at the University of Oslo. His main research interests are IT-based service innovation and the relationship of IS and organizational change. He is also interested in IS research methods, in particular the philosophical and methodological implications of critical realism. He has published articles in journals such as Information Systems Journal, Journal of Information Technology, and International Journal of Project Management. MIS Quarterly Vol. 37 No. 3/September

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27 SPECIAL ISSUE: CRITICAL REALISM IN IS RESEARCH THE GENERATIVE MECHANISMS OF DIGITAL INFRASTRUCTURE EVOLUTION Ola Henfridsson Warwick Business School, The University of Warwick, Coventry CV4 7AL UNITED KINGDOM Bendik Bygstad Norwegian School of IT, Schweigaards gt. 14, 0185 Oslo NORWAY and Department of Informatics, University of Oslo, Oslo NORWAY Appendix Sample Cases Contextual Conditions Architecture: tightly coupled (0); loosely coupled (1) Control: centralized (0); decentralized (1) Mechanisms Adoption (A): unactualized (0); actualized (1) Innovation (I): unactualized (0); actualized (1) Scaling (S): unactualized (0); actualized (1) Outcome: unsuccessful (0); successful (1) Comb: combination of mechanisms No Case 1 Health Information Systems Project HISP: A successful standardization strategy in lowresource countries, based on flexible and simple solutions. Continuously from National Hospital: A case of increasing complexity of requirements, leading to paralysis. Contextual Conditions Mechanisms Arc Con A I S Outcome Comb Reference AS Braa, J., Hanseth, O., Heywood, A., Mohammed, W., and Shaw, V Developing Health Information Systems in Developing Countries: The Flexible Standards Strategy, MIS Quarterly (31:2), pp Hanseth, O., Jacucci, E., Grisot, M., and Aanestad, M Reflexive Standardization: Side Effects and Complexity in Standard Making, MIS Quarterly (30:2), pp MIS Quarterly Vol. 37 No. 3 Appendix/September 2013 A1

28 No Case 3 Norsk Hydro: A case of an expanding corporate standard in the 1990s, leading to broad adoption, but difficult to scale 4 IBM: An innovative CRM project, with scaling problems. 5 EDI: An ambitious project in health, but failing to align a complex network of actors and technology. 6 Internet: Describes how the dynamics of bootstrapping and adaptation explains the success of the Internet. 7 Genome project: An ambitious scientific community project, which fails to establish a sustainable solution. 8 Statoil: An innovative project of knowledge management, which fails to trigger internal dynamics. 9 Legal systems: An expanding legal infrastructure in Austria, growing organically from Environmental Health in the French Public Health Administration: Analyzes a successfully distributed network of practice, 2000 to 2005, supported by an emerging information infrastructure. Contextual Conditions Mechanisms Arc Con A I S Outcome Comb Reference AI Hanseth, O., and Braa, K Who s in Control: Designers, Managers or Technology? Infrastructures at Norsk Hydro, in From Control to Drift The Dynamics of Corporate Information Infrastructures, C. U. Ciborra, K. Braa, A. Cordella, B. Dahlbom, A. Failla, O. Hanseth, V. Hepsø, J. Ljungberg, E. Monteiro, and K. A. Simon (eds.), Oxford: Oxford University Press, pp AI Ciborra, C., and Failla, A Infrastructure as a Process: The Case of CRM at IBM, From Control to Drift The Dynamics of Corporate Information Infrastructures, C. U. Ciborra, K. Braa, A. Cordella, B. Dahlbom, A. Failla, O. Hanseth, V. Hepsø, J. Ljungberg, E. Monteiro, and K. A. Simon (eds.), Oxford: Oxford University Press, pp Monteiro, E., and Hanseth, O Social Shaping of Information Infrastructure: On Being Specific about the Technology, in Information Technology and Changes in Organizational Work, W. J. Orlikowski, G. Walsham, M. R. Jones, and J. I. I DeGross (eds.), London: Chapman & Hall, pp AIS Hanseth, O., and Lyytinen, K Design Theory for Dynamic Complexity in Information Infrastructures: The Case of Building Internet, Journal of Information Technology (25:1), pp Star, S. L., and Ruhleder, K Steps Toward an Ecology of Infrastructure: Design and Access for Large Information Spaces, Information Systems Research (71), pp Hepsø, V., Monteiro, E., and Rolland, K Ecologies of einfrastructures, Journal of the AIS (10:5), pp AS Koch, S., and Bernroider, E Aligning ICT and Legal Frameworks in Austria s e- Bureaucracy: From Mainframe to the Internet, in ICT and Innovation in the Public Sector: European Studies in the Making of E- Government, F. Contini and G. F. Lanzara (eds.), Basingstoke, UK: Palgrave Macmillan, pp AIS Vaast, E., and Walsham, G Transsituated Learning: Supporting a Network of Practice with an Information Infrastructure, Information Systems Research (20:4), pp A2 MIS Quarterly Vol. 37 No. 3 Appendix/September 2013

29 No Case 11 French Rail: Aiming to transfer an airline booking system to a railway context. Fails because of translation problems. 12 Local Danish Electronic Patient Record initiative: A local initiative, which surprisingly develops and scales into a national Danish Electronic Patient Record solution. 13 Health: A national Danish Electronic Patient Record standardization initiative, which never gets off the ground. 14 GIS in India: An attempt to introduce GIS technology into an Indial local administration. Fails because of translation problems. 15 Power systems: En epic description of how the US electric grid and companies expanded as networks of power. 16 Health Broadband Networks: A telemedicine solution at the National Hospital is successfully innovated and adopted by health personnel. 17 Health: An EDI initiative gets mired in standardization issues, and never comes off the ground. 18 Telemedicine: A successful case of telemedicine in ambulances, but mainly as a pilot project. 19 EDIFACT standard: A national standardization initiative fails because of technical and organizational complexity. 20 Banking: A study of an innovative decision support system, with limited adoption and scaling. 21 Health IS: A successful adoption and scaling of a health information system in an Indian state. Contextual Conditions Mechanisms Arc Con A I S Outcome Comb Reference Mitev, N Toward Social Constructionist Understandings of IS Success and Failure: Introducing a New Computerized Reservation System, in Proceedings of the 21 st International Conference of Information Systems, Brisbane, Australia, pp AIS Aanestad, M., and Blegind Jensen, T Building Nation-Wide Information Infrastructures in Healthcare Through Modular Implementation Strategies, Journal of Strategic Information Systems (20:2), pp Aanestad, M., and Blegind Jensen, T Building Nation-Wide Information Infrastructures in Healthcare Through Modular Implementation Strategies, Journal of Strategic Information Systems (20:2), pp Sahay, S., and Walsham, G Implementation of GIS in India: Organizational Issues and Implications, International Journal of Geographical Information Systems (10:4), pp AS Hughes, T. P The Evolution of Large Technical Systems, in The Social Construction of Technological Systems, W. E. Bijker, T. P. Hughes, and T. Pinch (eds.), Cambridge, MA: MIT Press, pp AI Hanseth, O., and Aanestad, M Design as Bootstrapping. On the Evolution of ICT Networks in Health Care, Methods of Information in Medicine (42), pp Hanseth, O., and Aanestad, M Design as Bootstrapping. On the Evolution of ICT Networks in Health Care, Methods of Information in Medicine (42), pp A Hanseth, O., and Aanestad, M Design as Bootstrapping. On the Evolution of ICT Networks in Health Care, Methods of Information in Medicine (42), pp Hanseth, O., and Monteiro, E Inscribing Behaviour in Information Infrastructure Standards, Accounting, Management and Information Systems (7:4), pp I Scott, S. V., and Walsham, G Shifting Boundaries and New Technologies: A Case Study in the UK Banking Sector, in Proceedings of the 19 th International Conference on Information Systems, Helsinki, Finland, pp AS Sahay, S., and Walsham, G Scaling of Health Information Systems in India: Challenges and Approaches, Information Technology for Development (12:3), pp MIS Quarterly Vol. 37 No. 3 Appendix/September 2013 A3

30 No Case 22 The SWIFT Network: A successful standards innovation in early 1970s, and the gradual expansion into a global financial network. 23 Law: A Criminal Case Management system in Finland was developed and expanded gradually from 1992 into a successful legal network. 24 Law: The Civil Trial Online project is aimed at improving the workflow between courts and lawyers in Italy, had almost no results after 6 years, due to growing complexity. 25 e-customs in Europe: An ambitious EU project to integrate customs had some local successes, but has problems in scaling and adoption. 26 Health: The NHS summary care record project is characterized by a number of problems, and fails to establish a sustainable development. 27 Pharmaceutics: The evolution of an intranet, from corporate asset to local adaptation in a loosely coupled architecture. 28 OSI vs. IP standards: Compares the development and adoption of the OSI and IP standards, explain-ing the success of IP as the successful balancing between flexibility and standardization 29 Gateways vs. standards: Analyzes a standards war in Scandinavia in the 1980s, concluding with the importance of gateways. 30 Internet IPv6: The case investigates the efforts in the early 90s to address the IP address shortage. Aligning the various actor-networks and protecting the installed base proved successful. Contextual Conditions Mechanisms Arc Con A I S Outcome Comb Reference AIS Scott, S., and Zachariadis, M A Historical Analysis of Core Financial Services Infrastructure: Society for Worldwide Interbank Financial Telecommunication (S.W.I.F.T.), Working Paper Series, No 182., London School of Economics and Political Science AIS Fabri, M E-Justice in Finland and in Italy: Enabling Versus Constraining Models, in ICT and Innovation in the Public Sector: European Studies in the Making of E-Government, F. Contini and G. F. Lanzara (eds.), Basingstoke, UK: Palgrave Macmillan, pp Fabri, M E-Justice in Finland and in Italy: Enabling Versus Constraining Models, in ICT and Innovation in the Public Sector: European Studies in the Making of E-Government, F. Contini and G. F. Lanzara (eds.), Basingstoke, UK: Palgrave Macmillan, pp A Henningsson, S., and Henriksen, H. Z Inscription of Behaviour and Flexible Interpretation in Information Infrastructures: The Case of European e-customs, Journal of Strategic Information Systems (20:4), pp Greenhalgh, T., Stramer, K., Bratan, T., Byrne, E., Mohammad, Y., Russell, J Introduction of Shared Electronic Records: Multi-Site Case Study Using Diffusion of Innovation Theory, British Medical Journal (337: a1786; doi: /bmj.a1786) AIS Ciborra, C. U From Alignment to Loose Coupling: From Mednet to in From Control to Drift The Dynamics of Corporate Information Infrastructures, C. U. Ciborra, K. Braa, A. Cordella, B. Dahlbom, A. Failla, O. Hanseth, V. Hepsø, J. Ljungberg, E. Monteiro, and K. A. Simon (eds.), Oxford: Oxford University Press, pp AS Hanseth, O., Monteiro, E., and Hatling, M Developing Information Infrastructure: The Tension Between Standardization and Flexibility, Science, Technology, and Human Values (11:4), pp AIS Hanseth, O Gateways Just as Important as Standards: How the Internet Won the Religious War about Standards in Scandinavia, Knowledge, Technology and Policy (14:3), pp AIS Monteiro, E Scaling Information Infrastructure: The Case of the Next Generation IP in Internet, The Information Society (143), pp A4 MIS Quarterly Vol. 37 No. 3 Appendix/September 2013

31 No Case 31 Maritime Classification Company: Balancing local contexts and corporate standards, adoption was successful, but scaling problematic. 32 Telecom: The case explores the balance between central control and local autonomy. Relinquishing control led to innovative and successful infrastructure. 33 Broadband Mobile Services in South Korea: The case explains the rapid diffusion of broadband mobile services in Korea. 34 University software: SAP module/uni module: The successful generification and adaptation of two university software packages. 35 Health: A case on an innovative regional health network in Greece, with adoption and scaling problems, because failing to take part in a power network. 36 egovernment: A project aimed at improving workflow between a state and federal level, with sustainable growth. 37 Health: A large NHS project in the UK fails because of too technical focus and no clear adoption strategies. 38 US petroleum company CostCo: Infrastructure project with limited effect because of strong focus on cost reduction. 39 US petroleum company: Innovative infrastructure project with redesigned business processes and sustaining growth. 40 US retail company: Innovative project with adoption and scaling problems. 41 US retail company: Opportunity oriented project with redesigned processes and successful adoption and scaling. Contextual Conditions Mechanisms Arc Con A I S Outcome Comb Reference I Rolland, K., and Monteiro, E Balancing the Local and the Global in Infrastructural Information Systems, The Information Society (18:2), pp AIS Nielsen, P., and Aanestad, M Control Devolution as Information Infrastructure Design Strategy: A Case Study of a Content Service Platform for Mobile Phones in Norway, Journal of Information Technology (21), pp AIS Yoo, Y., Lyytinen, K., and Yang, H The Role of Standards in Innovation and Diffusion of Broadband Mobile Services: The Case of South Korea, Journal of Strategic Information Systems (14), pp AS Pollock, N., Williams, R., and D Adderio, L Global Software and its Provenance: Generification Work in the Production of Organizational Software Packages, Social Studies of Science (37:2), pp I Constantinides, P., and Barrett, M Large-Scale ICT Innovation, Power, and Organizational Change: The Case of a Regional Health Information Network, Journal of Applied Behavioral Science (41:1), pp AS Pipek, V., and Wulf, V Infrastructuring: Toward an Integrated Perspective on the Design and Use of Information Technology, Journal of Association for Information Systems (10:5), pp I Greenhalgh, T Adoption, Non-Adoption, and Abandonment of a Personal Electronic Health Record: Case Study of HealthSpace, British Medical Journal (341: c5814; doi: /bmj.c5814) S Broadbent, M., Weill, P., and St.Clair, D The Implications of Information Technology Infrastructure for Business Process Redesign, MIS Quarterly (23:2), pp AIS Broadbent, M., Weill, P., and St. Clair, D The Implications of Information Technology Infrastructure for Business Process Redesign, MIS Quarterly (23:2), pp A Broadbent, M., Weill, P., and St. Clair, D The Implications of Information Technology Infrastructure for Business Process Redesign, MIS Quarterly (23:2), pp AIS Broadbent, M., Weill, P., and St. Clair, D The Implications of Information Technology Infrastructure for Business Process Redesign, MIS Quarterly (23:2), pp MIS Quarterly Vol. 37 No. 3 Appendix/September 2013 A5