Self-destructive dynamics in large-scale

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Self-destructive dynamics in large-scale technochange and some ways of counteracting it

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Bongsug Chae Department of Management, College of Business Administration, Kansas State University, Manhattan, Kansas, USA, and

Giovan Francesco Lanzara Department of Organizations and Political Systems, University of Bologna, Bologna, Italy Abstract Purpose – Seeks to raise the question of why large-scale technochange is difficult and often failure-prone and to attempt to answer this question by viewing technochange as an instance of institutional change and design in which self-destructive mechanisms are inherently embedded. Design/methodology/approach – In order to explore the complex institutional dynamics of large-scale technochange the paper uses the exploration/exploitation framework originally developed by March and extended by Lanzara to the study of institution-building processes in the political domain. The argument is that problems in implementing large-scale technochange stem from learning dilemmas in the inter-temporal and inter-group allocation of material and cognitive resources. The paper uses a case of large-scale technology in a major US university system to illustrate the institutional perspective on technochange. Findings – It is argued and illustrated that the development and redesign of large-scale information systems involve both the exploration of alternative institutional arrangements and the exploitation of pre-existing ones, such that a delicate balance must be struck to overcome incoherences and dilemmas between the two activities. Research limitations/implications – The proposed framework to understand large-scale technochange is not examined empirically. The illustration of the framework relies on a single large-scale system project of a non-profit organization in the USA. Further empirical work and comparative research on multiple cases are needed. Practical implications – The paper discusses some sources of the failures of large-scale technochange and offers three interrelated mechanisms to counteract such failure sources, namely focal points, increasing returns, and bricolage. These counteracting mechanisms may help organizations to effectively deal with the dilemmas of exploration and exploitation in technochange. Originality/value – This paper fills the gap in understanding the nature of large-scale technochange, providing an explanation of why it is difficult and failure-prone and offering some modest proposals for intervention in large-scale system projects. Keywords Change management, Organizational change, Organizational culture, Information systems, Design and development, United States of America Paper type Research paper

Information Technology & People Vol. 19 No. 1, 2006 pp. 74-97 q Emerald Group Publishing Limited 0959-3845 DOI 10.1108/09593840610649970

1. Introduction Large-scale information systems development (ISD) or technology-driven organizational change (“technochange”) (Markus, 2004) has been a major trend in both private and non-profit organizations. Within the flood of business and technology

innovations over the past decade, the deployment of large-scale information systems such as enterprise resource planning (ERP) systems, customer relationship management (CRM) and supply chain management (SCM) systems has increased among both companies and higher education institutions. However, the industry data show that large-scale technochange (LST) tends to be failure-prone (see the industry data such as the Robbins-Gioia (2001) survey and Darrell et al. (2002)). As an example, a popular business press now notes that “ERP has failed to meet expectations or deliver on its value promise. It’s hard to find an expert who thinks otherwise” (Millman, 2004). Academic studies are reporting some similar results (e.g. Gibson, 2003; Robey et al., 2002). In this situation, studies (e.g. Besson and Rowe, 200; Hanseth et al., 2001) of industry cases of LST suggest that prevailing management perspectives on LST are characterized by such notions as management control, deliberate project design and planning, business process reengineering (BPR), and the like. However, in practice ERP implementation encounters the problem of more unpredictability/uncertainty and less controllability. It is characterized by side effects which often cause the outcome to be quite distant from what was originally intended (Hanseth et al., 2001). Thus, when such prevailing management perspectives are taken, the picture of ERP implementation can be often portrayed by a vicious circle: the tight, top-down control of the LST leads to the actual drift of the change initiative itself, and this reinforces the demand of more control which will lead to more drift (Hanseth et al., 2001). Organizational studies have recognized this phenomenon as deviation-amplifying feedback and unintended consequences of management control (Ashton, 1976). To this end, this article raises the issue of why LST encounters such difficulties and problems and attempts to find some ways to address this issue. What makes LST so difficult and failure-prone?[1] How come that human efforts at developing and re-engineering large-scale information systems often turn out to be self-defeating? This article attempts to answer these questions by viewing LST as an instance of institution building in which self-destructive mechanisms are inherently embedded (Lanzara, 1998, 1999). In order to explore the complex institutional dynamics of LST we use the exploration/exploitation framework originally developed by March (1991) and extended by Lanzara (1998) to the study of institution building processes in the political domain. Among the various schools of thought in institutional theory in general (Scott, 1995; Van de Ven and Hargrave, 2004) and in institutional design in particular (Goodin, 1996), the framework adopted in this paper specifically focuses on the cognitive rather than the political aspects of the development of large scale projects (Nielsen et al., 1995; Offe, 1996; Stark, 1995). Following a stream of organizational research (Eisenhardt, 2000; March, 1991; Weick, 2002) we emphasize the ambiguity and ambivalence of change phenomena and take issue with paradox and perversity. While the framework has been developed to explore the dynamics of organizational learning and institutional change, we claim that it can be usefully transposed in the domain of LST, helping to shed new light on why and how LST can be self-defeating. Large-scale information infrastructures and, for that matter, computer-based systems in general support a set of contractual and institutional arrangements between individuals, organizations and communities and can thus be regarded as institutions in their own right (Avgerou, 2002; Ciborra and Lanzara, 1994). We claim that the

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development and the redesign of large-scale information systems involve both the exploration of alternative institutional arrangements and the exploitation of pre-existing ones, such that a delicate balance must be struck to overcome incoherences and dilemmas between the two activities. However, efforts at handling dilemmas in the allocation and use of material and cognitive resources – both inter-group and inter-temporal – often generate counterproductive consequences that may distort the balance and defeat the initial design objectives. Therefore the argument of this article is that, despite all the positive assumptions about the need of LST for increasing organizational performance in the academic literature and the business press (Markus, 2004), LST contains the premises and the seeds of self-destructiveness. In the following we will first briefly present our view of large-scale technochange as an institutional process. Then we will discuss in detail the main sources of self-destructive dynamics in LST. Next, some counteracting mechanisms are described. A case of LST in a major US university system is finally discussed to illustrate our major points. 2. Large-scale technochange as an institutional process A number of points can be made in order to introduce our view of the institutional dynamics of technochange. First, from our perspective IS development or technochange is not the simple introduction of software into an organization or a new IT project (Sawyer, 2000). Rather, it is more accurate to say that technochange involves both typical IT projects and typical organizational change programs simultaneously (Markus, 2004). It focuses on both enhancing culture, employee behavior, work practices, and organizational processes and designing/implementing a new technology (or technologies) to improve technical performance. By bringing about specific sets of rules to organize social relations and perform business transactions, technochange means to a large extent changing and restructuring the institutional bonds and background conditions supporting human work and communication (Ciborra and Lanzara, 1994). In this vein, as some previous studies (Avgerou, 2002; Kling and Iacono, 1989) suggested, technochange can be better conceptualized as a process involving the (re)design of the institutional framework of IT systems. However, institutional redesign is not a smooth process most of the time, because technical systems tend to interact in subtle and unpredictable ways with the organization’s informal practices and rules and with deeply ingrained institutional norms which are the result of evolutionary processes and cannot easily be changed by design (Shrivastava, 1983). Therefore, as a consequence of such interaction, implementation becomes more difficult. Second, by “large scale” (Star and Ruhlender, 1996) technochange we refer to change initiatives involving organizational technologies and technological innovations (Gallivan, 2001) such as enterprise systems (Gailers et al., 2002; Gosain, 2004) and information infrastructures (Hanseth et al., 2001; Howcroft et al., 2005) rather than traditional systems such as executive information systems and group decision support systems. These organizational technologies and innovations comprise and connect multiple communities of practice within an organization or between organizations (Braa and Rolland, 2000), while those traditional systems were designed for a single community of practice. Thus, LST tends to be conducted in a mandatory setting where

initial decisions are made at the level of organizations or organizational units rather than individual users (Brown et al., 2002; Gallivan, 2001), often pursuing such goals as seamless integration of data, business and system integration, intra- and interorganizational coordination and knowledge sharing, standardization of business practices and procedures, and others. Thus, it is likely to involve large system specifications and requirements, high costs and risks, several stakeholder groups with divergent interests, a high magnitude of both intended and unintended consequences, large potential users and their diverse practices, various technical artifacts and organizational resources (e.g. skills), different geographical locations, and others (Bergman et al., 2002; Hanseth et al., 2001; Wagner and Newell, 2005). These heterogeneous socio-technical elements and their interactions greatly increase the level of complexity in LST (cf. Schneberger and McLean, 2003; Xia and Lee, 2004). Recent institutional theorists have recognized the similar kind of complexity in institutional design and governance (Jessop, 1997; Urry, 2003). Third, large-scale IS are generally embedded into other social/institutional structures, organizational arrangements and technologies (Ciborra and Hanseth, 2000; Star and Ruhlender, 1996). Therefore, LST is never from scratch, but it has to work with “what’s already in the organization and the project team”, often called legacy systems (Brooke and Ramage, 2001), which is a combination of legacy technologies, data, business processes, organizational structure, strategy, workflow, etc. It becomes inevitable that large-scale technochange has to deal with large-scale legacy systems by either replacing or succeeding them. The succeeding approach is, seemingly, exactly opposite to the fundamental idea of LST, while the replacing approach that has been the center of prevailing management perspectives has turned out to be unsuccessful, as shown in some previous studies (Besson and Rowe, 2001; Hanseth et al., 2001; Wagner and Newell, 2005). These three points suggest a strong similarity between large-scale IT development processes and the processes of institution building, With the former, the design and implementation of new technical standards and systems are at stake, while the latter entails the replacement of institutional structures and codes and the constitution of new ones. Thus, LST can be regarded an instance of institutional change inasmuch as it calls into question established standards, incentives and codes of behavior, which retain an institutional valence, and pushes for the creation of new structures, which themselves need to gain the value and meaning of an institution if they are to exert regulatory power. While the systems undergoing change are of a different kind, the institutional dynamics are surprisingly similar. 3. Sources of self-destructiveness in technochange In what follows we discuss the major sources of self-destructiveness that often plague processes of institution building (Lanzara, 1998) and are likely to be found in LST[2]. In order to better illustrate our argument we often refer to published cases of enterprise system implementation. 3.1 The dilemma of exploration and exploitation As noted earlier, LST always presupposes pre-existing socio-technical infrastructures or legacy systems. Various actors who are engaged in situations of IT-based organizational transition must choose between assigning their limited resources


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(attention, money, time, influence, etc.) either to the exploration of alternative organizational arrangements or else to the exploitation and use of the current (or legacy) ones. Such situations are recognized as dilemmas of exploration and exploitation in organizational learning (Levinthal and March, 1993; March, 1991). Organizations engage in exploration – the pursuit of new knowledge, of things that might come to be known. This includes things captured by terms such as search, variation, risk taking, experimentation, play, flexibility, discovery and innovation. And they engage in exploitation – the use and development of things already known. This includes such things as adaptation, refinement, choice, production, efficiency, selection, implementation and execution. Organizations that engage in exploration to the exclusion of exploitation are likely to find that they suffer the costs of experimentation and search without gaining many of their benefits, while systems that engage in exploitation to the exclusion of exploration are likely to find themselves trapped in suboptimal stable equilibria. Hence both strategies may incur in decreasing returns, although for different reasons and with different time spans. ERP-driven organizational change, for example, means not only a new enterprise software solution but also new work processes and organizational designs. LST always faces the question of how much change is desired. The actors involved in this process are likely to face a dilemma of exploitation and exploration. In an interview, the CIO of a major US university told us: Our university is currently planning ERP implementation. For this we visited several universities that have already implemented or have been implementing ERP. After all these visits, what we have is a dilemmatic situation about how much things should be changed. One university we visited with changed too much of what they already had (for example, by adopting more than 20,000 new processes) and as a result everything was so new to the people. On the other hand, the other university had changed very little except a new ERP solution and people were noting: What is new about this new system? What should our university do? This is our dilemma.

If an ERP initiative adopts exploration, which seems to be the prevailing case in industry practice (Suchman, 2002), the actors will encounter “the long arm of the past” (Offe, 1996, p. 216), or “installed base” (Ciborra and Hanseth, 1998). Indeed, new organizational arrangements or many features of organizational forms and customs (March, 1991) cannot be built on a tabula rasa (Offe, 1996): successor IS or the outcomes of LST are affected by the long arm of legacy systems (Ciborra and Lanzara, 1994; Star and Ruhlender, 1996). Researchers and practitioners (Kelly et al., 1999) may tackle the long arm of the past by undercutting the validity of old routines, including legacy technologies, organizational structures, culture, and practices, in an effort to create a kind of tabula rasa as a prelude to winning the loyalty of constituents to the newly designed institutional arrangements or IS (cf. Offe, 1996). This is attractive but dangerous. In the pursuit of radical changes, it is typical for organizations and their members to experience rising conflicts among goals, values and responsibilities, stress, emotional tensions, poor results in the short run, and failures of quick actions (Hedberg et al., 1976). On the other hand, more conservatively oriented LST suffers from a different kind of dilemma. Some researchers and practitioners may not comply with the idea of tabula rasa and tend to stress the necessity of evolutionary IT-driven organizational change, not deprived from the installed base (Christiansen, 1997). This approach may imply

lower costs, unpredictability and political conflict. Thus, in some cases, the initiators and planners of LST have to adopt a rather conservative approach to LST by reducing the depth and width of the change while exploiting existing technologies, organizational routines, and competence (Chae and Poole, 2005). This process produces fewer surprises due to accumulated experiences and proven rules, procedures and standard practices, and thus potentially increases reliability, which further allows improved average performance. Yet, a side effect of such conservative strategy is the increasing opportunity cost of exploration (Levinthal and March, 1993). If newly designed IT-based organizational arrangements can be depicted as being not so new after all but rooted in some respectable past that may add to their obligatory power from that past, then people will constantly be lead to ask: what’s new? This approach is likely to become effective in the short run but self-destructive in the long run. 3.2 Fast versus slow feedback In LST the disparity between short-run and long-run considerations is a recurring theme. Actors have different temporal horizons (Emirbayer and Mische, 2001). The actors (e.g. senior management, project initiators, etc.) in LST tend to have short-range expectations and expect fast positive feedback (e.g. return on investment) from their initiatives. Fast positive feedback is necessary to keep initiatives going and to get the changing process started. Lack of fast feedback would further depress expectations and impair action. In some cases, these situations would lead to de-escalation of commitment (Keil and Robey, 1999) in enterprise system development and implementation. However, any LST tends to have the “valley of despair” associated with a steep learning curve and a steep fall in organizational performance (Pyun, 2002) and take a long time. For example, a typical ERP implementation takes three years on average (Knorr, 1999). The consolidation of new technologies and processes embedded in them generally requires financial and cultural investments that yield returns in the long run (Huntona et al., 2003) and have slow, delayed feedback. Misfits and misalignments between a technochange solution and existing organizational arrangements (e.g. culture, business processes, work routines) are inevitable in any technochange initiative (Gosain, 2004). In these situations, returns on investment are uncertain and often delayed in time. Thus, if the actors give priority to short-range and fast feedback, they risk creating conditions that inhibit long-range commitments and investments, make long-run solutions impossible to instate, and indefinitely postpone significant organizational change driven by IT. Resolving this dilemma is not an easy task. Things are complicated because different actors have not only different expectations, but also different time horizons for their expectations. Coordination of the actors’ multiple time horizons is both a fundamental component and an outcome of technochange. 3.3 Sunk costs Legacy systems (e.g. work routines, culture, special competencies, engrained power or interest structures) embody “sunk costs” for the organization and the actors. Sunk costs originate from a capital stock of knowledge, skills, trust, shared expectations and mutual obligations that has been frozen in a fixed structural configuration. The longer the installed base has lasted and the more productive it has been in the past, the higher


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the sunk costs are likely to be. A legacy information system represents a massive, long-term investment from the perspective of both the organization and various individual actors within the organization. A technology and its social context such as large set-up costs and learning effects generate increasing returns and sunk costs (Arthur, 1989). In situations where an organizational transformation is envisioned, then, to what extent should actors put their energies and resources to the maintenance or regeneration of the current depleted or legacy systems or, on the contrary, should they concentrate their efforts into exploring new paths and configurations (Sneed, 1995)? Problems arise if they take either horn of the dilemma (cf. Offe, 1996). In general, while legacy systems become hard to maintain, they can be viewed as an asset to an organization, since they mean the accumulation of business rules, practices, know-how, and expertise (Kim, 1997; Kelly et al., 1999). In some cases of LST, actors may discourse the legacy system as “a great system of the past” (Alvarez, 2001). In other cases, actors may characterize a new IT-based solution as something bad or threatening and tend to respond by enacting organizational defensive routines (Argyris, 1990; Henfridsson and Soderholm, 2000). If actors choose to stick to existing organizational arrangements and technologies and try to exploit them further, in the first instance they may commit the error of putting resources into what they may soon discover to be an irreversibly depleted, basically unrecoverable structure; secondly, they might create conditions that further inhibit their future capability and willingness to change the framework when change is most needed and cannot be further delayed (Lanzara, 1998). On the other hand, if actors take a leap into a radical IT-driven organizational change, in the first instance they may commit the error of throwing away resources that, though depleted, might still be partly exploitable. A radical, IT-driven organizational change would result in significantly negative consequences by often relinquishing a stock of useful knowledge, skills, business processes, culture, etc., as appeared in the case of a package-driven BPR project in the financial services industry (Larsen and Myers, 1999). Second, they may be putting resources and energies into what they could later discover to be too premature or a “management fad/fashion” solution in such cases of IT-driven business process engineering (Biazzo, 1998), supply chain management (Newell et al., 2001), and knowledge management initiatives (Malhotra, 2004). The undesired and counterintuitive consequences of such an adventurous but premature leap are instability, additional ambiguity, and perhaps the actors’ retreat onto some more conservative positions. To sum up, in large-scale technochange, both the design of new systems and the adaptation of the pre-existing ones are plagued by self-destructive cycles. Due to self-destructive dynamics, pressures pushing for change and restructuration also create conditions that endogenously tend to undermine the very bases of change and restructuration. Conversely, pressures to maintain the legacy systems also create conditions that make them more and more suboptimal, and hence less and less desirable to an increasing number of actors (e.g. Kim, 1997; Kelly et al., 1999). Pressures to cast a new organizational order using a new IT solution may generate preferences and behaviors that counteract and disconfirm that order. In the corporate domain fear of change due to increasing uncertainty of the new system, sunk costs of legacy systems and potential political conflict coupled with unwillingness to pay the learning costs may provoke withdrawal.

4. Instances of self-destructive dynamics In the following we shall focus on the implications of self-destructive dynamics for three specific issues that, in our view, are central in LST. 4.1. Competency and resource endowments When the legacy system breaks down, a problem of competency arises. Whether legacy or new, the systems tend to generate and develop system-specific competencies and resources, which become endowments of specific actors (e.g. Larsen and Myers, 1999). These competencies represent accumulated experience, that is, what the actors know how to do with and within a specific system. They are essential for the sustenance and the reproduction of systems. This makes the establishment of new organizational arrangements with a new IT solution difficult and somehow dilemmatic: if existing competencies and human resources are kept out and not put to use in the process of innovation, LST suffers from lack of experienced personnel, and it stumbles; on the contrary, if the existing competencies are called in, they tend to implant most of the old rules, practices and habits, which may sabotage any innovative effort and reinstate many of the features of the previous regime. 4.2 Self-interest A widely held view in the social sciences considers self-interest as the engine of human action and choice. This view is often adopted in the studies of technochange (Lamb and Kling, 2003). Within such a view, the actors are driven to take action by the anticipated future consequences of individually preferred options. But it is difficult for them, in an unstable, ever-unfolding situation like LST, to fix stable criteria for calculating utilities and for establishing where their self-interests really lie. This is partly because uncertainty is high and it is hard to calculate the relative advantages associated with different organizational arrangements in the future, which are not clear and intrinsically unstable. Therefore, in the course of LST actors are wary about quitting the legacy system, even if they are getting decreasing returns from it, because there is uncertainty as to how the future organization with a new IT solution will look like. In sum, the pursuit of self-interest – either in the short or in the long run – creates conditions that prevent the achievement of it and may turn out to be bitterly self-defeating. As a consequence, it may lead to a reinforcement of stability (exploitation syndrome) or, alternatively, to an aggravation of instability (exploration syndrome). 4.3 Identity Identities, similar to legacy systems, have inertial and resilient properties. Therefore, during the effort at technochange, actors’ identities are threatened and actors even defend their identities through great stories of the capacities of the legacy system (Alvarez, 2001). LST means to form and consolidate new identities, distinguishable from the past ones, but it also means to establish some sort of legitimacy of the new identities based on precedent or exemplar anchored in the past. Indeed, in LST a common way of invoking legitimacy for a new institutional design is to appeal to some already established legitimate model that happened to be successful in the past. Familiarity seems to be a strong argument for legitimacy and acceptance of a new model (see Offe, 1996). The predicament for any innovative organizational framework


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using a new IT solution is that it must look “different” from the past – a break through the legacy system – and at the same time “descendant” from (or similar to) some relevant historical archetype. 5. Counteracting mechanisms The above discussion may deliver a message: technochange is characterized by self-destructive dynamics that tend to make it failure-prone. The previous section shows that the dilemma of exploitation and exploration is the key issue in technochange. A complete replacement of legacy systems is seldom a viable or safe strategy. An abrupt and radical “switch over” from habitual practices and structures is too costly and risky, and political actors and their relevant constituencies will not go for it. All elements of an irrational conflict among actors (Dunbar et al., 1982) are likely to be present in LST. Yet, self-destructive cycles can be counteracted or mitigated. Actors manage to steer IT-driven organizational transformations, and some (e.g. Cisco Systems, Dow Chemicals) are known to be successful (Gibson, 2003). In this section we discuss three basic mechanisms – focal points, increasing returns to adoption, and organizational bricolage – that may help organizations counteract the self-destructive dynamics. Focal points pertain to the emergence of coordination, increasing returns refer to the adoption and diffusion of organizational solutions due to positive feedback, while bricolage describes the making and the evolution of large (and loose) structures from smaller ones. Although organizations can be punctuated by momentous episodes of change (Gersick, 1991), most often change is ongoing and happens incrementally, by means of local adaptations over time (Weick and Quinn, 1999). In the occurrence of large-scale innovations (Orlikowski, 2000), actual social practices and organizational cultures are more persistent than technical/formal infrastructures and do not conform to them promptly. Our claim is that focal points, increasing returns, and organizational bricolage adequately respond to the dilemmas of LST. 5.1 Focal points In an organizational transition from legacy to new, what is first needed is coordination among actors (initiators, consultants, developers, users, etc.) with diverse (often conflicting) interests for the “design” of technochange. A focal point is a prominent, conspicuous feature of an ambiguous choice situation that, precisely because of its uniqueness and visibility, becomes a key or rather the key to solve a difficult problem of coordination (Schelling, 1960). When multiple actors with conflicting interests are involved in complex decision-making, considerations of “obviousness” or “visibility” of a solution can beat considerations of self-interest. Focal points generally emerge by accident, often unintendedly, but sometimes they can be socially constructed or searched for. In technochange, focal points can take different forms that are a function of culture, past practices, legacy technologies, or organizational routines. For example, some of the legacy technologies and practices that LST often aim at removing may emerge as focal points. They may offer relevant social actors a direction: Where to go from here and what to do from now on. Or, change agents purposefully shift or redirect organizational conversations to new “possibilities” and attract diverse organizational actors to a dialogue (Ford, 1999). In addition, change agents may search for the “taken-for-granteds” of his or her audience

to produce justifications that support his or her initiative. To count as focal points, whether they emerge by accident or are socially constructed or searched for, they must make sense to relevant social actors (Green, 2004). However, either way, telling ex ante what constitutes a focal point, and whether it will work as such, is extremely difficult, and might even be self-defeating. Once they have emerged, focal points become pivotal mechanisms for coordinating expectations and behaviors. Focal points can be “seeds” for the structuring of organizational arrangements with new IT solutions over time. By creating convergence in the short run, a focal point stabilizes a minimal structure (Barret, 1998) that, as it gains momentum, it may give a sense of organization and direction in the long run. “A little structure goes a long way” (Weick, 1993, p. 356). A focal point may constitute an “anchor” for establishing identities, meanings and mutual recognitions, a ground upon which trust and competencies can be built, and a focus for mobilizing increasingly large amounts of resources. A focal point is a small beginning, from which a sensible environment can be enacted. It is potentially exploitable, while at the same time providing a path or an ordered field for exploration, that otherwise would proceed in the wild. By channeling exploration, a focal point reduces its perceived risks and its costs and eventually helps actors to overcome mere efficiency considerations in the allocation of resources, such as sunk costs. Focal points represent small beginnings in emergent designs (Weick, 1993) of LST. 5.2 Increasing returns to adoption LST can be regarded as the outcome of a learning mechanism based on sequential choice and positive, self-reinforcing feedback. Starting from fortuitous events or small structures featuring as focal points, positive feedback allows for the emergence and consolidation of large and more stable structures, which yield increasing returns to adoption (Arthur, 1989). If a focal point is a source of a design, then “a self-confirming one that recycles and amplifies should produce a more stable design that organizes an increasingly large set of resources” (Weick, 1993, p. 356). When a particular technical solution or organizational routine is implemented and adopted by an increasing number of agents, a phenomenon of convergence to a collectively shared outcome may be generated. The convergence, in turn, may generate further convergence as adoption of a specific solution or structure spreads, making it more and more attractive to prospective actors and users (Arthur, 1989; David, 1986). Thus, something that started small in the form of a focal point can grow into a complex structure of actors who participate directly or indirectly in technochange. Through increasing returns, the technochange process that started from many loosely connected transactions can cluster and expand into a large coordinating and adaptive structure. 5.3 Organizational bricolage Large-scale systems of high functional and structural complexity can hardly be designed or re-engineered from scratch. Rather, they tend to be the outcome of patching up, recombination and bricolage. Bricolage is a design and compositional principle opposed to the “blueprint” re-engineering approach popular with today’s technochange initiatives. Bricolage-based practices rely on second-hand materials to build an artifact or a structure when nothing more appropriate is available. Pre-existing components and structures are creatively shaped to perform new functions, putting them to


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different uses from the old ones they had been originally designed for (Levi-Strauss, 1967). The bricoleur makes do with whatever is there, with whatever s/he encounters. This makes him/her quite different from the engineer, who usually starts from a pre-designed plan and fixed technical and functional specifications. Bricolage is believed to be what individual agents (e.g. system designers in Lanzara (1999)) do in their action in real time. In contrast to the idea of re-engineering or re-everything (“fresh new starts”), the bricoleur’s first practical step is retrospective. S/he interrogates the existing set of materials to find out what it contains (Weick, 1993). The materials represent whatever has been utilized and eventually discarded in the past. Thus, the more diverse these uses, and the more fully the materials themselves are understood, the more innovative will the bricoleur be in improvising new designs from this stock of materials. Bricolage is collective or organizational when it results from the combined effort of several individuals, groups and/or organizations. Organizational bricolage may be viewed as a second-best strategy after the engineering approach. However, it may be the only way to build and innovate in situations of IT-driven organizational change characterized by high uncertainty, political conflict and sunk costs. It is too costly or practically impossible to dismiss the capital stock of legacy systems and to devalue established sunk costs before new organizational arrangements (and investments) have had the time to yield returns. Thus a convenient strategy might be to convert old components and structures to new functions and uses. LST occurs not on the ruins but with the ruins of the old regime (cf. Offe, 1996), as available resources are redeployed to respond to emerging practical dilemmas. Tinkering at the margins of old structures may be thought as a form of exploitation, but this impression is misleading. Repackaging, transposing, and recombining old components can be acts of “creative reinventions”. Bricolage is thus neither pure exploitation nor pure exploration. Rather, it combines both principles. In the technochange process organizational bricolage can take different forms: transposition, patching-up (Genschel, 1997), and anticipated institution (Federowicz, 2000) or future. 5.3.1 Transposition. Stable structures can be adapted to evolving conditions by transposing them to new functions (Genschel, 1997). Actors turn back to already existent systems and try to figure out how they could be used to tackle whatever is the new problem at hand. New problems are likened to old problems, and the legacy systems that worked on the old problems are reassigned to the new ones. An example can be found in airline reservation systems (ARSs), which have evolved over a long period of time since the 1960s (Holland et al., 1999). ARSs that were initially designed for streamlining and routinizing internal organizational operations in the 1960s and 1970s transposed themselves for different needs, such as gaining market share in the 1980s and niche marketing through data mining in the 1990s (Kwon et al., 2002). Social elements of legacy systems or existent non-technical infrastructure are transposable as well. Social actors are capable of applying a wide range of different and even incompatible schemes and transposing them in developing new institutions (Sewell, 1992). For instance, organizational routines are not inert but instead can be an important source of flexibility and continuous change when enacted by people in contexts. Routines allow improvisational learning, which leads to constant changes as well as stability (Feldman and Pentland, 2003). Heeks’s (2002) study in IS development

in developing countries shows that schemes are local capacities which play a key role in the improvisation of both design and actuality and help to improve IS success. Lack of schemes in most developing countries impedes local improvisation for IS redesign by those countries. He argues that in such situations there will necessarily be less emphasis on emergent improvisation and greater emphasis on the initial design. This overall situation probably increases risks of IS failure. 5.3.2 Patching-up. Patching-up is a rather future-oriented strategy while following the same combinatory logic of transposition. It refers to patching up old structures (or legacy systems) with new structures. Unlike transposition, patching-up looks forward to solving new problems by creating new institutions (Genschel, 1997). However, rather than trying to undercut the validity of old routines in an effort to create a kind of tabula rasa or keeping old inefficient structures due to lock-in mechanisms and path dependency, this strategy aims at relieving specific bottlenecks and deficiencies of the legacy systems through patching up them with new social and technical components. Thus, patching up does not mean the total replacement of the existing IS, which results in high sunk costs and political conflict. Instead, a patching-up strategy seeks less noise and confusion in the transformation, less uncertainty than a switchover to totally new organizational arrangements and less political conflict than a switchover may cause. Patching up diffuses conflict by allowing for inconsistency. It does not seek for a universal system for everyone, but understands the impossibility of such attempts. Rather, it recognizes the reality of “partial translation” (Suchman, 1994) in place of claims for universality. Patching up tends to proceed in a decentralized manner in that all initiatives undertaken to make up for the deficiencies of a legacy system tend to be organized locally and ongoing in practice (Genschel, 1997). There may be less central coordination in patching up the legacy system with new ones. Thus, culture and organizational leadership that give legitimacy to these local-level actions are important for patching up. 5.3.3 Anticipated institution/future. Organizational bricolage does not mean lack of a plan or expectation in technochange. This third form understands the limitation of “design de novo” but at the same time stresses the need of considering a teleological character of transformation (Federowicz, 2000) or the importance of intentionality (Goodin, 1996) in LST. LST becomes inevitably incremental (Orlikowski and Hoffman, 1997) and path-dependent, but like institutional change (Federowicz, 2000) or technological innovation (Garud and Karnoe, 2001), can only be properly understood by taking into account, alongside path-dependent processes, the teleological role of human agency. This strategy suggests that no deep change through technochange management is possible without a future-oriented turn in people’s minds and behavior. Actors need to develop their expectations of the plausible organizational change. People’s expectations or collective efficacy (Bandura, 1997) matter not only at the cognitive level and at the behavioral level for the success of technochange. This form of organizational bricolage is related to other concepts such as information technology development creativity (Cooper, 2000), path creation in technological innovation (Garud and Karnoe, 2001) and imagination/mindful deviation in organizational learning (Weick, 2002). Anticipated institution in LST refers to neither the “replacement” of existing visions of the organization nor the mindless adoption of bandwagons. Rather, constructing anticipated institution/future needs to occur in action, while involving


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“reasoning grounded in its own organizational facts and specifics” (Swanson and Ramiller, 2004, p. 559). Attention to organizational specifics allows sound judgments about whether, when, and how to innovate through LST (Swanson and Ramiller, 2004). Thus, constructing anticipated institution becomes fundamentally a process of mindful deviation (Garud and Karnoe, 2001) that managers and the organization are involved in.

86 6. An illustration: self-destructive and countervailing processes in the Land Grant University System In this section we introduce a case of large-scale technochange in a major US university system in order to illustrate our concepts. In the case, both the self-destructive and the countervailing mechanisms discussed so far can be seen to be at work. Particularly, the case sheds light on the tensions which were built into the project design itself and which produced a drift from the original plan. The case setting is a large-scale technochange initiative (University System-wide Management Information Systems, or USMIS) at a major US university system (which we call Land Grant University System, or LGUS). Considerations of space prevent us from giving full details of the research methodology and of this technochange initiative. Such detailed descriptions can be found in Chae and Poole (2005). 6.1. Going for exploration: “one system for everyone” LGUS was established about 50 years ago, though several of its units have been in existence for over 100 years. It has grown through annexing existing universities and most of its units have been added in the past decade. Its 19 member units vary greatly in mission and purpose, from major universities to teaching colleges to research institutes and extension services. Traditionally there had been a decentralized culture within the system. Each unit regards itself as different from all the others and works to maintain its uniqueness and independence. Somewhat counter to this principle, business and IS integration have been emphasized and sought at the system level. USMIS, an enterprise information system that incorporates financial regulations applicable to the units of LGUS, is one of the major initiatives taken to pursue this end. Several internal and external factors and institutional arrangements contributed to the emergence of the USMIS system. In the 1980s LGUS already experienced a rapid growth and even more growth was expected since there were plans to add more units (universities and research agencies). The proper level of coordination among and control over units became an important concern for the top management at the LGUS Central System Administrative Unit (from now on labeled as HQ). The existence of separate financial management systems supporting diverse accounting rules and practices throughout LGUS created a major barrier for enterprise-wide integration and control. Thus, the aspiration was for the USMIS initiative to be a wholly new system that brought a new level of integration and centralization to LGUS. USMIS was first introduced in 1990 for the fiscal year 1991. The USMIS Project Team has been responsible for the development and support of USMIS since the late 1980s. The champions of USMIS took an “exploration” approach to technochange and planned to develop an enterprise information system to support not just financial management and interfacing with State-wide Management Information Systems

(SWMIS), but also other administrative functionalities, including contracts and grants management, purchasing, office automation and communication, ad hoc reporting and information management. The original plan was to develop “a fully integrated IS by the summer of 1990 for fiscal year 1991 and to implement USMIS completely in all units within four years”. At the outset, use of USMIS was planned to be mandatory: “everyone had to be on USMIS”.


6.2 Self-destructiveness: “the battle” The process of the USMIS development manifested the difficulties that typically characterize institution building. As noted by March and Olsen (1989, p. 65), “change rarely satisfies the prior intentions of those who initiate [. . .] change cannot be controlled precisely”. The development of USMIS was never fully designed and planned. USMIS as finally realized diverged considerably from the grand vision of the project initiators and the Board of Regents. Contrary to the aspiration for a wholly new system toward organizational integration and centralization, the final system did not turn out to be the fully integrated large-scale information system the MIS team set out to build, although it certainly served critical functions for LGUS. Most critically, the development of USMIS occurred in the context of various organizational structures, and this tempered its capacity to deliver radical change. For example, the decision on the new project was made at the top level of LGUS: the Board of Regents delivered the directive, and HQ had to execute the directive. In addition, adoption of USMIS was made mandatory for all units of LGUS. However, this “exploration” approach fostered strong resistance from LGUS’s decentralized organizational culture, which emphasized the uniqueness of each member and strong local autonomy. Particularly, the conflict between the research agencies and the USMIS project team and HQ was sharp enough to be clearly discerned in LGUS, and parties to the USMIS implementation referred to it as “the battle”. As observed by a top administrator in LGUS, “From the beginning of USMIS implementation in 1990 until July 1995, when engineering agencies were officially waived from using USMIS, there was a six-year battle between the system and engineering agencies”. Part of this battle can be found in a memo from a research agency to HQ: It is important to clarify the directives of the LGUS Board of Regents [. . .] Centralization seems to be effective in smaller State systems with less diversity of missions. Traditionally, the HQ had maintained a very workable interpretation of its role by providing overview and governance where a global perspective is necessary and where shared services reap benefits to the LGUS members. But the autonomy of the System members to exercise their authorities and means in order to do a good job is one that members have long cherished. In my opinion, the current USMIS philosophy threatens the traditional role of the HQ and threatens to share service even when such services are costly to some System members.

In addition, the diversity of LGUS’s constituencies was a major issue. Every unit had its own chart of accounts and the accounting practices throughout LGUS were very diverse. Few wanted to change their accounting. Some feared losing control due to USMIS. As a result, the project progress was unexpectedly slower than anyone anticipated. This whole situation evolved such that in late 1988 administrators of LGUS and its member units started to be concerned about the implementation of

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USMIS and asked whether USMIS would eventually be implemented. The former director of the USMIS project recalled: At that time no one wanted to write system requirements. Everyone said: “No time” [. . .] I was told from people: “I don’t care how you do it [. . .] Just go out and build it”.

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With regard to the technology there was a strong imprint put on USMIS by existing computing infrastructure and technical human resources within LGUS. For example, the project team had to conform to technical commitments embodied in two major information system procurements from the 1980s – SIS (Student Information Systems) and an IBM 3090-200E mainframe computer system. SIS used Software AG’s ADABAS as the primary database system and COBOL and NATURAL as the main development languages. The SIS procurement cost over $1.6 million and it became evident at that time that purchasing another database was not an option. In addition, the IBM system cost $8.2 million in 1987. The mainframe computer and SIS were taken for granted as important parameters in the new technochange environment. The expertise in COBOL and NATURAL developed during the implementation of SIS was brought into the USMIS project as several of the members of the MIS Project Team had helped to maintain SIS. The interface was a “green screen” because the IBM system and languages did not support a graphical user interface. As the project proceeded the project team had to recognize the diversity of LGUS and adopted a more “customer-oriented” rather than “enforcing” approach to USMIS development. It learned to accommodate different needs of different member units. The diversity of LGUS led the MIS project team to design an “average” system for all units – no matter whether they were large or small, universities or research agencies – while different parts maintained “shadow systems” to meet local needs not satisfied by USMIS. Some research agencies claimed that USMIS is for universities, not for them, while the smaller universities said it is too big for them. Reflecting on this, a key initial sponsor of the project commented: “One system for everyone is nothing for nobody”. Overall, sunk costs of legacy systems, time pressure and emerging local politics locked the USMIS project into a particular trajectory of development where both radical and conservative designs were apparently self-defeating. The “explorative” position taken by the initiators and the project team at the outset of the project was a sort of “willing what cannot be willed”. But soon they encountered the long arm of the past. As noted earlier, pressures pushing for radical change created conditions such as “the battle” that undermined the very bases of radical change. Unlike the initiators’ and project team’s expectations of fast technochange progress and positive feedback, the development of USMIS took a lot longer than anyone anticipated. This whole situation depressed expectations of some key initiators and further impaired certain explorative actions. For example, the former director who had been in charge of the project from the beginning in 1987 left LGUS in 1991. A top HQ administrator who was called by others “the father of USMIS” left LGUS as well. Their resignation caused serious problems in the continuation of USMIS implementation and led to a loss of direction in the implementation effort. In its subsequent developments the overall technochange approach took a more conservative turn, as exemplified by such events as selecting some legacy technologies and technical competencies as the bases of USMIS. However, the exploitation of available structures created unintended consequences as well. The selection of

software and hardware vendors, which sought short-term stability and efficiency, was made in April 1989 and increased confidence that USMIS would be implemented. This decision helped the initiative move forward, at least during that time. Later, however, this decision made USMIS more and more suboptimal, as time passed. Over the past years various constituencies, including the State, research agencies, new Chancellors, individual users, and even some of its founders, complained about USMIS’s inability to meet their expectations and needs. This had created various political, functional and social pressures for the institutional decay or deinstitutionalization (Oliver, 1992) of USMIS during its lifetime. The more “customer-oriented” approach also led to the unintended situation where the project team was forced to design an “average” system that would work for everyone, no matter whether they were large or small universities or research agencies. Thus the original idea of an integrated enterprise system for LGUS gradually faded away. As noted by one of the initiators of the project: After accommodating all the differences and tailoring LGUS, it turned out that different information systems at different parts of LGUS are running under the name of USMIS.

The discussion above sheds light on some of the instances of self-destructive dynamics that were presented earlier in the paper. If the existing technical competencies and human resources had not been put to use in the USMIS development, then the new system would have suffered from lack of experienced personnel and the initiative would eventually have been abandoned. On the other hand, when the existing competencies were called in, they implanted most of the old technologies and designs, which reinstated many of the features of the previous systems, as acknowledged by a top IT of a research agency: The project team was in on the vendor selection. They were less interested in a brand new system but more with a system that was compatible with SIS. They were looking at “Green screens” and “ADABAS and Natural”. I supported advanced technologies like Oracle. They argued with me that my solution was risky and their approach was less risky. Then I would ask them: “What is new about USMIS?”.

As noted earlier, the recognition of the diversity of LGUS and strong resistance to USMIS led the project team to adopt the customer-oriented approach and to accommodate the different needs of different members. This shifting approach represents a way of coping with issues of autonomy and identity. It led to increased familiarity with USMIS and less local politics among the member units. Familiarity was a strong argument for legitimacy and acceptance of the new system. However, the shift led USMIS to look more similar to the old technical and organizational arrangements. The unintended consequence was that various constituencies of LGUS, including even some initiators and original supporters of USMIS, considered the need of more innovative and explorative technochange using a new, advanced IT solution, as noted by top IT administrators of LGUS: There were proposals for replacing USMIS even in 1994, 95, 96 but those ideas were not materialized at that time because of the magnitude of USMIS.

6.3. Counteractive mechanisms at LGUS The champions of USMIS were initially in the “history does not matter” position. However, as discussed in the preceding subsection, their initial view drifted (and was


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strategically shifted) to a position that acknowledged path-dependencies in the development of systems. Transposition and patching up were observed in USMIS, because of institutional drift. As noted in section 6.2, transposition was observed in the early phase of USMIS development. The initiators and the project team turned back to already existing information systems and tried to figure out whether they could use those systems to tackle the new situation – enterprise-wide integration. They could not be free from the socio-technical installed bases supporting the pre-existing information systems inside and outside LGUS. Transposition was the initiators’ and project team’s improvised reaction to the situation rather than their planned strategy. Patching-up was also observed throughout the history of USMIS development and became a common, improvised action by the initiators and project team in the maintenance and governance of the system. For example, one major deficiency of (and complaint about) USMIS was lack of departmental user support. In order to relieve these specific bottlenecks and deficiencies in 1995, software for departmental download capability was purchased and combined with USMIS rather than altering it. Also there was a need to respond to the State auditor’s 1996 report that pointed out the lack of the capability of executive information systems to meet the information needs of System-level users. Rather than altering USMIS, the governance group in LGUS purchased NCR’s Teradata database to develop an executive information system that has a loose interconnection with USMIS. Over the years the champions of USMIS have attempted to handle some bottlenecks and deficiencies of USMIS through patching-up. Most recently, the MIS project team considers patching USMIS up with the utilization of middleware technologies such as the EntireX Broker. On the other hand, more forward-looking activities/strategies such as anticipated institution are not evident in USMIS. The original objectives of USMIS by top administrators of LGUS and the desire for centralization were not adequately shared through the entire organization at the outset of the initiative, as “the battle” implies. As noted earlier in section 6.2, even the underlying philosophy of the USMIS-driven technochange was questioned by some member units. Due to diverse and even competing goals and interests, coordination was daunting and a solution that could beat considerations of self-interest was never obvious, as implied in a memo from a research agency to HQ: We will be asked to pay for a system we do not need nor want. We will be asked to pay for a system that, at the very best, will be mediocre. Our internal system can be interfaced with the USMIS system to provide required data on a monthly or more frequent basis.

As of today, three member units have not committed to USMIS. Despite “the battle” and the lack of anticipated institutions, transposition and patching-up helped the USMIS initiative to be continued and experience increasing returns to adoption. The adoption process commenced in 1990 with three units and added five more units in 1991, and the remainder from 1992 through 1996. After the years, the USMIS has become a stabilized structure and accepted as an “institutional fact” by most units. People commented that USMIS has offered a common communication channel between the state and member organizations of LGUS and also introduced economies of scale. A unit that joined LGUS in 1995 noted:

We were allowed to choose an information system but we did not [. . .] the selection process for a new information system was needed because USMIS was our natural choice.

It is now perceived to be part of the installed base, something that is exogenously given and resistant to willful change, as a top administrator of LGUS commented: Some people have been talking about the replacement of USMIS, but they don’t know what they are talking about. In my opinion they have no idea of the complexity and scope of USMIS. If they knew it they would never talk about the replacement of USMIS. You know what? USMIS cannot be easily pulled back. It has its own life! (emphasis added).

While the discussion above illustrates how organizational bricolage and increasing return to adoption are played out in LST, the case also sheds light on the importance of focal points and anticipated institutions, and also on the difficulties associated with the process of developing them in large-scale systems development. Due to its scale, the USMIS project directly and indirectly involved a large number of heterogeneous groups of social actors, whose goals and needs were diverse and sometimes even competed with one another. In this instance, the individual members’ affiliation with LGUS and the mechanisms designed to ensure the proper level of coordination among the different units of the university system were “obvious” things that could serve as focal points for USMIS. However, these potential focal points faded away as soon as the top management at HQ overlooked several “taken-for-granted” characteristics, particularly the traditionally decentralized, consensus-based organizational structure and a culture emphasizing self-autonomy of member units, and instead “directed” to member units its top-down, grand vision of system-level integration and control driven by a single, mandated information system. In a design logic where attention to organizational specifics was clearly lacking, it was impossible to establish anticipated institution around the USMIS initiative. Similar to many other LST initiatives, the USMIS initially started with “the myth of large causes” and “the logic of replacement” (Weick, 1993; Weick and Quinn, 1999), which prevented the emergence and formation of focal points and anticipated institutions. 7. Conclusion In this article, being aware of the high rate of failure in large-scale technochange management initiatives driven by enterprise technologies (Darrell et al., 2002; Gibson, 2003; Malhotra, 2004), rather than pursuing the search for a further refined set of critical success factors, we have taken issue with the dynamic processes that cause such difficulties and problems in LST. Focusing on its institutional features, we have viewed LST as a process of building or redesigning technical infrastructures and institutional frameworks in which subtle self-destructive mechanisms are inherently embedded. We have showed that LST involves on the one hand the exploitation of legacy systems so that they can be adapted to new uses and, on the other hand, the explorative search of alternative institutional and technical arrangements. The high failure rate is not a surprising fact, but the consequence of emerging inconsistencies and dilemmas in the inter-temporal allocation of resources. Therefore, the argument of this article is that, despite all the positive assumptions and beliefs in the academic literature and the business press about the need of having LST in order to increase organizational performance, LST, as it is presently conceived and implemented in


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practice, contains the seeds of a self-destructive dynamics that often leads to gaps and mismatches between outcomes and expectations.. This alternative way of understanding LST allows us see the inherently complex, dynamic and emergent nature of large-scale information system development. As the historical experiences in institution building and governance suggest (Jessop, 2000), technochange initiatives are likely to be failure-prone due to embedded self-destructive mechanisms. Yet, learning how to deal with such self-destructive processes and their outcomes is difficult but not impossible for organizations and developers. Technochange requires learning how to strike a healthy dynamic balance between exploration and exploitation in order to cope with the emergence of deviation amplifying loops. During LST, organizations and key actors should learn how to better use the properties of focal points, increasing returns and bricolage for development and management purposes. As it is illustrated by the case of the University System, the three modest mechanisms proposed in this paper might help managers of technochange to pursue at the same time both the legitimacy and reliability of pre-existing technical and institutional arrangements and the variability and invention of new large-scale information systems. Notes 1. By “failure” we mean a situation in which outcomes or actual experiences do not meet plans or expectations; that is, when things do not quite work out as designers or project managers and administrators had envisioned. Whatever failure is, in this paper it should not be intended as a system crash or mechanical failure (such as when an aircraft, engine or bridge fails, etc.). Large-scale information systems development fails not because systems break down and annihilate performance, but because it falls short in making the intended change or performance happen. That may be due to understandable short- and long-term outcomes, including political turmoil among stakeholders, huge financial and emotional loss without improving performance, etc. For similar uses see other IS studies (Beynon-Davies, 1995; Heeks, 2002; Lyytinen and Hirschheim, 1987; Larsen and Myers, 1999). 2. “Self-destructive” is definitely a strong word, but it better expresses the kind of dynamics we want to highlight here; that is, the forces leading to change also create conditions and enact counter-forces that inhibit the intended change or make it problematic. Other terms like “side effects”, “negative externalities” or “unexpected consequences” focus on the outcomes of the dynamics rather than on the dynamics themselves and the mechanism that generate them. References Alvarez, R. (2001), “‘It was a great system’. Face-work and the discursive construction of technology during information systems development”, Information Technology & People, Vol. 14 No. 4, pp. 385-405. Argyris, C. (1990), Overcoming Organizational Defenses. Facilitating Organizational Learning, Allyn & Bacon, Needham, MA. Arthur, W.B. (1989), “Competing technologies, increasing returns, and lock-in by historical events”, Economic Journal, Vol. 97, pp. 642-65. Ashton, R.H. (1976), “Deviation-amplifying feedback and unintended consequences of management accounting systems”, Accounting, Organizations and Society, Vol. 1 No. 4, pp. 289-300. Avgerou, C. (2002), Information Systems and Global Diversity, Oxford University Press, New York, NY.

Bandura, A. (1997), Self-Efficacy: The Exercise of Control, W.H. Freeman, New York, NY. Barret, F. (1998), “Creativity and improvisation in jazz and organizations: implications for organizational learning”, Organization Science, Vol. 9 No. 5, pp. 605-22. Bergman, L., King, J. and Lyytinen, K. (2002), “Large scale requirements analysis revisited: the need for understanding the political ecology of requirements engineering”, Requirements Engineering, Vol. 7 No. 3, pp. 152-71. Besson, P. and Rowe, F. (2001), “ERP project dynamics and enacted dialogue: perceived understanding, perceived leeway, and the nature of task-related conflicts”, The Data Base for Advances in Information Systems, Vol. 32 No. 4, pp. 47-66. Beynon-Davies, P. (1995), “Information systems failure: the case of the London Ambulance Service’s Computer Aided Dispatch Project”, European Journal of Information Systems, Vol. 4 No. 1, pp. 171-84. Biazzo, S. (1998), “A critical examination of the business process re-engineering phenomenon”, International Journal of Operations & Production Management, Vol. 18 Nos 9/10, pp. 1000-16. Braa, K. and Rolland, K.H. (2000), “Horizontal information systems: emergent trends and perspectives”, in Baskerville, R., Stage, J. and DeGross, J. (Eds), Organizational and Social Perspectives on Information Technology, Kluwer Academic Publishers, Boston, MA, pp. 82-102. Brooke, C. and Ramage, M. (2001), “Organizational scenarios and legacy systems”, International Journal of Information Management, Vol. 21, pp. 365-84. Brown, S.A., Massey, A.P., Montoya-Weiss, M.M. and Burkman, J.R. (2002), “Do I really have to? User acceptance of mandated technology”, European Journal of Information Systems, Vol. 11, pp. 283-95. Chae, B. and Poole, M.S. (2005), “The surface of emergence in systems development: agency, institutions, and large-scale information systems”, European Journal of Information Systems, Vol. 14 No. 1, pp. 19-36. Christiansen, E. (1997), “Gardening: a metaphor for sustainability in information technology-technical support”, in Berleur, J. and Whitehouse, D. (Eds), An Ethical Global Information Society, Chapman & Hall, London, pp. 171-85. Ciborra, C. and Hanseth, O. (1998), “From tool to Gestell”, Information Technology & People, Vol. 11 No. 4, pp. 305-27. Ciborra, C. and Hanseth, O. (2000), “Introduction: from control to drift”, in Ciborra, C. (Ed.), From Control to Drift – The Dynamics of Corporate Information Infrastructures, Oxford University Press, London. Ciborra, C. and Lanzara, G.F. (1994), “Formative contexts and information technology: understanding the dynamics of innovation in organizations”, Accounting, Management & Information Technology, Vol. 4 No. 2, pp. 61-86. Cooper, R.B. (2000), “Information technology development creativity: a case study of attempted radical change”, MIS Quarterly, Vol. 24 No. 2, pp. 245-76. Darrell, R., Reichheld, F.F. and Schefter, P. (2002), “Avoid the four perils of CRM”, Harvard Business Review, Vol. 80 No. 2, pp. 101-9. David, P.A. (1986), “Understanding the economics of QWERTY: the necessity of history”, in Parker, W. (Ed.), Economic History and the Modern Economist, Blackwell, Oxford, pp. 30-49.


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Self-destructive dynamics in large-scale

Self-destructive dynamics in large-scale

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