Managing a Socially Constructed Technology: The Case of CT ...

Proceedings of the 28th Annual Hawaii International Conference on System Sciences - I995

Managing a Socially Constructed Technology: The Case of CT Scanning

J.-C. Spender

Faculty of Management, Rutgers University, Newark NJ 07 102

Abstract

The effective management of technology must recognize that technology is embedded in social processes and that technology is shaped by both technical and social forces. This paper illustrates the study of technology through an examination of the interaction of these scientific, engineering, professional and social practices. Specifically we examine the case of computed tomography (CT) scanning, introduced in 1972 by EMI, an English firm. Despite EMI’s early success, a handful of US, German and Japanese firms now dominate the global market. The question of whether EM1 managed their entry into and exit from this business well has attracted considerable attention in the literature. We offer a new interpretation.

Introduction

It is easy to think that technologies develop along trajectories which are proscribed internally. Thus the steady progress from the early 4K DRAM semiconductor memories to today’s 256M memory chips seems to be the result of laboratory work wholly removed from the rough and tumble of Silicon Valley business practices and the aspirations of Nintendo gamesters. Yet the laboratory story turns out to be only a small part of the whole. In this paper we focus on computed tomography (CT scanning). This is a new way of handling X-ray data, making it possible to build up detailed three dimensional, as opposed to the crude two dimensional big plate shots with which we are all familiar. This development spawned a new industry, medical imaging, and a new range of medical tests and technologists. The case provides us an ideal opportunity to examine the subtle interplay of technological and social activity.

The Study of Technological Innovation

Organization theorists, including those developing theories of strategy and of the management of innovation,

have been poorly served by thinking of technology as the linear application of scientific invention. Invention, this mode1 suggests, moves seriatim through innovation and implementation to become product. The debates about the difference between invention and innovation (Daft, 1982; Zaltman, Duncan & Holbek, 1973) correctly focus on the process of implementation, for an innovation is applied while an invention merely has some potential.

But this kind of debate tends to overlook the changes that implementation requires and creates in the context in which it generates innovation. Organizations, and markets, often need to change before an invention can become an innovation. Thus implementation depends on the pattern of activity to be affected. Damanpour’s (1991:583) meta-analysis of the innovation management research suggests that organizational context is crucial. The literature is unbalanced when it ignores the context. We might say that the invention and the context together determine the possibility of implementation.

In the same way the innovation management literature restricts itself by presuming the rigidity of the technology. Technology is often inherently flexible and able to take many forms. The technology’s eventual form is heavily influenced by the context and social interactions among those involved (Bijker, Hughes & Pinch, 1987; Bijker & Law, 1992). Feedback from the users influences the process of invention quite as much as the products of invention constrain the implementer’s possibilities (von Hippel, 1976).

In this paper we argue that technology, invention and implementation arise out of the interaction of the processes of invention (and design and development) and those in the context in which it is implemented. While this seems generally reasonable it is not immediately obvious how we can operationalize the thought.

Following Callon (1987) we argue that we do this kind of interactive analysis by identifying the various actors who make up the technology’s relevant context (the actor- network) as well as the disparate interests that these actors bring to their interactions. This moves our analysis into a complex social framework. But we also risk over emphasizing the different amounts of power that these

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Proceedings of the 28th Annual Hawaii International Conference on System Sciences - 1995

actors bring to the interaction, so neglecting the degree to which they are constrained by the science of the situation. In the end the inventors’ and designers’ knowledge power interacts with the social power of both the technology’s users and those who control the necessary resources. In short, we need to foster an understanding of the technology from inside the social system of which it is part as well as from within its science. A technology is thus both as a body of technical knowledge and a social system (Layton, 1977: 198).

Tbe Social Construction of Technology

The nuivetk of the innovation management literature is evident in the widespread adoption of the ‘linear’ model of innovation (e.g. Marquis, 1972). The transition from invention to innovation is divided into an arbitrary number of s’erial steps such as R&D, prototyping, production, and marketing. This overlooks the specific content of the technology, and cannot therefore be understood in terms of the community of scientific practice from which the invention itself emerges. It also eliminates any consideration of the social context in which this community is embedded. The analysis simplifies the organizational context, describing it only with classic structural variables (such as formalization, centralization, and differentiation), and cultural variables such as administrative intensity, and managerial tenure (Damanpour, 1991:558). Thus the historical contingencies and social aspects of the actor network tend to be ignored (Pinch & Bijker, 1987:22).

These ways of looking at the development of technology eliminate by assumption the crucial interplay and feedback which the social construction theorists argue is central to the actual process (Bijker & Law, 1992). It is this interplay that gives the technology its ‘interpretive flexibility’, its different meaning to different people, and thus the possibility of its developing in a variety of different directions. The way in which it ultimately develops is determined neither by what is most effective from a scientific point of view, nor by any evolutionary dynamic internal to the technology. The technology moves from being merely exploratory to becoming embedded in social practice (or work) in ways that are influenced and mediated by purely social factors.

Social Actors and Power Relations

Callon (1987:92) illustrates the use of ‘actor-networks’ with the example of the electric car (VEL) which the French electricity monopoly (EDF) proposed in the 1970s. He points out that the proposal had severe implications for vehicle users as well as for the other car manufacturers

(especially Renault, another French state organization) and for the increasing environmentally conscious public. The EDF contracted with the CGE (Compagnje G&n&de d’ElectriciteJ to develop the motor and battery systems for the first generation of VELs. It was intended that they would also develop the electrochemical fuel cells which would power later generations. The EDF strategy was partly based on its power as a State agency. But it was also a reflection of their assessment of the likely trajectory of fuel cell technology.

In the event, things turned out quite differently. After the initial excitement died down, Renault and others fought back. As they began their own researches into fuel cell technology, they found the EDF projections unsound, and concluded that the zinc/air batteries suggested would require a vast network of service stations to take the VEL’s spent electrolyte and replace it with fresh. They also showed that much of the public dissatisfaction with the present generation of automobiles could be dealt with by pollution control and by better urban transport and parking facilities. In so doing, they showed the richness of the symbiosis between modem society and the technological form of the motor car. Irrespective of the technical merits of an electric car, its social ramifications were enormous, which is why work continues today on the ‘California Car’. In the end, the weakness of the me1 cell technology caused the longer term interactions about the technology of private electricity based transportation to founder in France. As different set of interactions keep it alive in the us.

Callon argues that the actor network suggested in this case appeared as a set of nodes (Renault, EDF, CGE, environmental interests, etc.). The power relations among these nodes were social, i.e. political rather than economic or scientific. Yet each node was also a network in its own right. The integrity of the upper level network, which was the locus of the electric car as a social innovation, was contingent on the integrity of the lower level technical and professional networks, on each accepting the role assigned (Callon, 1987:93). Some of these nodes were grounded in the community of science. As scientific faith in the progress of fuel cells waned, so that node collapsed. On its own, this would not have lead to the collapse of EDF’s project since, with state backing, the first generation (lead/acid) technology could certainly have been implemented. In the end the failure of the VEL project must be located in a wider social framework.

Each of these actor networks defines a context for action and interaction. Thus, in the preceding example, the tussle between EDF and Renault, two state agencies, was clearly highly political in the conventional sense of the term. The upper-level actor network was dominated by political activity, and this demanded knowledge and experience which was not at all technological. The development of



the technology was mediated by this political knowledge and activity. This may have been less true of some of the subsidiary actor networks, though the provision of urban transport and parking was and is highly political at the local level. The fuel cell technologists were influenced by other types of activity, largely scientific, as they tested alternative possibilities and generated data for the economists and corporate strategists. The integrity of any one subsidiary node was unlikely to be related to that of any other. Each depended on a different pattern of power, knowledge, resource and experience. Thus the application of scientific knowledge to the social world involves knowledge and processes which can never be analyzed from a purely scientific standpoint.

The Knowledge in the Actor-network

A number of the writers analyzing the interaction of technology and organizations are sensitive to the limitations of the purely scientific point of view. They often draw on Polanyi (1962) and argue that reasoned organizational activity involves both ‘objective’ and ‘tacit’ knowledge (e.g. Nelson & Winter, 1982; Kogut & Zander, 1992; Teece, 1987). Sometimes this tacit knowledge appears as the uncritical acceptance of the ‘technology regime’ or ‘technology paradigm’ (van den Belt & Rip, 1987:137). In this sense it is a cognitive constraint. Sometimes tacit knowledge appears in the skilled practice of those involved in the actor network. Polanyi (1966; Gelwick, 1977) argues that tacit knowledge is crucial to the progress of science. In general we can say that since technology involves practice, both shaping and enabling different practices, it must involve types of knowledge other than the pure abstractions of scientific thought.

A number of empirical researchers have put some flesh on this rather abstract idea. Scribner (1986) reports a series of researches into the ‘practical intelligence’ applied in the work place. She illustrates the wide gulf between the heuristics employed by most practitioners and the theoretical algorithms suggested by scientific analysis. She shows how practitioners develop highly contextualized skills, while the scientific analysis is purely general. For instance, packers in a dairy warehouse develop the ability to work with non-decimal base numbers and choose to calculate according to the number of items in a case. Despite their sophistication these abilities were not transferable to a classroom setting. Similarly Lave (1988) investigates the remarkable mathematical skills of experienced shoppers. In this sense, Scribner and Lave suggest tacit knowledge is practical (embedded in a particular set of contextualized practices) rather than that which conforms to the canons of science and the classroom.

Other researchers suggest that practical knowledge may have further dimensions. Orr (1990) considered the knowledge that service technicians bring to their work on photo-copier machines. He argues that it is practical in that it goes far beyond the scientific knowledge which the designers build into the photocopy machines and reflect in the repair and maintenance manuals. Technicians develop a sophisticated body of practical knowledge, much as photocopier users develop local knowledge about how to fit this facility into their work processes. But Orr also shows how the technicians meld into a community of practice as they develop, share and draw on a collective body of knowledge (Brown & Duguid, 1991). In the same way, Spender (1989) argues that there is a collective body of knowledge within an industry about the problems which managers must consider and the likely means of their solution. He calls this the ‘industry recipe’ in the same way that Orr moves towards identifying the ‘photocopier technicians’ recipe. This kind of knowledge is practical in that it is embedded in activity rather than in abstract theory.

Both Scribner and Orr, in their respective discussions of individual and collective practical knowledge, assume that the practitioners are conscious of the knowledge that they bring to their activity. Polanyi, in contrast, stresses the non-conscious dimensions of practical knowledge, arguing that “we know more than we can say”. He illustrates this by suggesting that skilled practice as a swimmer or a cyclist is not dependent on knowledge that can be communicated to others. Sociologists have long recognized that much of an actor’s knowledge is taken-for- granted and submerged below the level of consciousness (Schutz, I972).

Bargh (1989) deals systematically with the ‘automatic’ dimensions of an individual’s practical knowledge. He suggests an analysis based on the different dimensions of awareness, attention, intention and control. Automatic@ is revealed when (a) the actor is unaware of knowledge which leads to skilled performance. In the extreme, when the actor is in a state of ‘flow’ (Csikszentmihalyi, 1988), performance becomes effortless. Automaticity is also revealed when activities do not require conscious attention, as when one jumps at a loud bang or catches a suddenly falling object. It is also revealed when activity is without a known goal, though psychiatry may help to bring the goal into the field of consciousness. Finally automaticity is revealed by the inability to control habits, even when one is consciously trying to control them. Current psychological research shows that automatic behavior is widespread. Similarly much sociological research is devoted to surfacing the taken-for-granted aspects of everyday life. In general much of what workplace practitioners know is automatic and beyond being identified, even by the actors themselves.



These different dimensions of workplace knowledge can be illustrated as a matrix (Figure 1). The contrast between the individual and the social is also familiar to systems theorists as the contrast between the properties of the parts and those of the system as a whole.

Individual Social

Explicit Conscious Objectified

Taken-for Granted Automatic Collective

Figure 1. Types of pralctical knowledge

We can expect the knowledge being applied in any real actor network to comprise all these types. Organizations comprise complex bodies of knowledge. On the one hand they depend on the workplace knowledge and skills of their members. But they also have collective knowledge embedded in their organizational routines (Nelson & Winter, 1982), and can draw on objective scientific knowledge in their decision making. Thus, at any one time, inter-organizational relations may be dominated by any one of these types of knowledge.

The Social Construction of CT Scanning

The history of computed tomography (CT) scanning is well known (Bartlett, 1983; Blume, 1992; Iglehart, 1982; Martin, 1984:9-13; Susskind, 1981; Trajtenberg, 1990; Scherer, 1992:78). As the story is normally told, in 1967 Godfrey Hounsfield, an engineer working for EMI, realized that much medical X-ray information was lost using the normal method of flat plate photographs. He conceived the idea of collecting data using a narrow beam X-ray gun and a small detector and scanning from several different directions, so achieving multiple ‘fixes’ on the same body feature. The key to this new method was the computer power and software which would integrate the information into a two dimensional image which could be presented on a screen as highly detailed representation of a ‘slice’ through the patient.

Hounsfield quickly developed a working prototype of the X-ray equipment and the computer analysis system, for which he eventually won the Nobel Prize in 1979. EMI announced their machine in April 1972 and introduced the first commercial version to an astounded world at the November 1972 Convention of the Radiological Society of North America (RSNA). The radiologists immediately saw the merit of the new

technology and orders began to flow into EMI. Indeed CT scanning was hailed as the greatest advance in medical imaging since X-rays themselves. But the major X-ray equipment suppliers also realized that CT scanning was a major step forward and rushed to develop their own equipment. By late 1975, ten other companies were delivering scanners, while EMI was backlogged with 250 orders for its machine. In 1980, Thorn who had acquired EMI in 1979, announced withdrawal from the CT scanning business, and most of the CT assets were sold to their principal competitor, GE, who now dominates the business.

The context of the implementation process

At first sight, this is a classic story of managerial failure, since EMI’s strategy was based on scientific knowledge which could be readily appropriated by others (Teece, 1987: 187 & 208). Teece suggests that h,ad EM1 been able to secure complete control of the technology, they could have leveraged that into control of the complementary assets and so into secure control of the entire CT scanning industry. Their failure to do this was “‘a strategic error” (Teece, 1987:207). Here Teece seems to adopt the notion of a discrete technology, wholly owned by EMI, with its own trajectory, which could remain in EMI’s possession so long as they (a) maintained a level of R&D activity sufficient to sustain market interest and prevent others engineering around their patents, and (b) avoided major financial or other managerial errors. The strategic implications are easy to see.

The reality facing the company was quite different, involving many other powerful players in this actor network. We shall see that EM1 did make ‘errors’ of the type that Teece implies. But we shall also see that these errors were incidental to the unfolding events, and that the likelihood of long-term control of the market was always vanishingly small. To unravel this picture, we must first identify some of the otber actors. Secondly, we must get a sense of their interactions and of the body of knowledge each brought to that interaction.

Until 1972 EM1 was not in the medical X-ray business. Hounsfield was a research engineer working on signal processing and pattern recognition. His interest in CT scanning was merely as an application for his signal processing discoveries. Blume (1992: 162) and Scherer (1992:79) tell how the funds at Hounsfield’s disposal were those set aside for speculative R&D, and, before he had built or tested any equipment, these were exhausted. In the meantime Hounsfield’s boss, Len Broadway, became enthusiastic and, after reviewing the medical imaging market worldwide, felt that ten machines could be sold if only they could be completed. Broadway therefore sought

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Proceedings of the 28th Annual Hawaii International Conference on Systena Sciences - 1995

the help of the Department of Health and Social Security (DHSS), better known as the parent body to the UK’s National Health Service. The DHSS were interested in developing a mass screening program for breast and lung cancer. Broadway told the DHSS that since the CT scanner could detect a tumor as small as lmm. it was perfect as a whole body device for this program. However, the DHSS quickly realized that the machine was far too expensive for this kind of mass program and directed BroadWay’s attention to scanning only the brain. There was a pressing need for procedures which were less invasive that those currently available.

Blume (1992164) writes that Hounsfield began work using a gamma ray source and a small water-filled ‘phantom’. Having adopted a data handling algorithm, and programmed the computer, he was able to produce a fuzzy though definite picture. In January 1969, the DHSS team, plus a radiologist, were sufftciently impressed that they agreed to back the project to the point of clinica trials to a limit of $17,500. By January 1970 the equipment was working on slices of human brain with X-rays. The results were promising and the DHSS renewed their support. They also to set up an advisory team to oversee the project and clinical trials which included a leading neuroradiologist, James Ambrose.

By mid 1971 all parties began to comprehend the immense scale of this project. If working machines were to be produced, the DHSS backing would have to increase their support to around $250,000, a substantial part of their R&D budget. They agreed to buy one prototype and underwrite the construction of four more. At the same time EM1 began to debate whether they should license the technology to others who were active in and understood the radiology field, or whether they should continue on their own. In 1971 they approached GE, whose powerful US marketing force might well generate over 50% of EMI’s total sales, After concluding that they would be unlikely to sell more than 30 machines, GE declined EMI’s offer (Scherer, 1992:80). Meanwhile a new technical director, John Powell, joined EM1 from Texas Instruments in October 197 1, re-assessed EMI’s electronics businesses and persuaded them to go it alone, in spite of the multi-million dollar resources that would be required. He appreciated that the US was the primary market for the machine, so in April 1972 he announced the technology and in November, together with Hounstield and Ambrose, he went to Chicago and the National convention of the Radiological Society of North America to show their first working unit. In the meantime Hounsfield published the basic technical ideas in the 1973 British Journal of Radiology. This was followed by Ambrose’s 1973 BJR paper describing the use of the CT scanner and speculating on its eventual place in neuroradiology.

At this point we can see the initial actor network as made up of EM1 and the DHSS, with DHSS defming the problems which CT scanning was to solve, using their power over scarce resources to enforce their view. The DHSS also had the scientific knowledge which Hounsfield and the rest of the EMI team lacked about the possible applications of the evolving technology. Hounsfield, on the other hand, understood that the core of the invention was his signal processing innovation. The immediate clinical task was to show that the equipment was capable of creating X-ray images of the human brain without over- exposing the living subject. Aside from Ambrose’s tentative paper, little thought was given to the meaning or diagnostic value of these images.

EM1 Interacts with the radiologists’ world

By 1973, things were changing rapidly. The 1972 RSNA announcement and the publication of Hounsfield’s and Ambrose’s papers opened up the network to many other actors. In particular, it connected Hounsfield’s work to the previous US work of Oldendorf and Cormack. In a 1961 paper, Oldendorf, a neurologist, expressed his profound dissatisfaction with angiography and ventriculography, the two available methods of brain imaging. He constructed a working model and took out a patent in 1963, but was not able to interest other radiologists or any equipment suppliers in his ideas. Cormack, a physicist, had similar ideas and published a 1963 article in the Journul of Applied Physics. Cormack was to share Hounsfield’s Nobel prize. But these early articles indicated that US radiologists had a broad understanding of Hounsfleld’s invention and its implications, possibly greater than Hounsfield himself.

The radiologists also understood the tacit knowledge necessary to interpret the images produced. Among medical specialties, radiologists have developed one of the most sophisticated and dominating communities of medical practice (Freidson, 1970; Larson, 1977). Larkin (1978) and Brown (1973) show that by the 1950s radiologists had secured an exclusive license to interpret medical images. This required excluding engineers and physicists from medical radiography, even though they were responsible for designing the imaging equipment, and barring other physicians from interpreting films, and by controlling the education and registry of radiology technologists (Barley, 1986:87). For these radiologists, CT scanning was not a radical technological innovation in the sense that it created an entirely new set of practices. It was merely an important extension of their current practice. But, as Barley shows, in the detail work patterns of the hospital, the machine technologists and younger doctors challenged their control over the use of this new


Proceedings of the 28th Annual Hawaii international Conference on System Sciences - 1995

type of medical imaging. While in different hospitals this was achieved in different ways, there were no failures as the professionals beat out the technologists (Barley, 1986: 105). The radiologists successfully co-opted the CT system to sustain the existing actor networks of hospital practice.

While the radiologists were powerful, the hospitals were the paying customers and therefore became members of the expanding actor network that controlled EMI’s destiny. Whether CT scanning was a medical advance or not, it fitted the hospital’s needs in quite another respect. While the DHSS and various other nationalized health systems installed scanners, the US market was immediately well over 50% of the world market. Prior to 1983 this market was shaped by the institution of third party reimbursement. The CT scanner provided hospitals the opportunity to offer a completely new service which could be charged separately. The possession of a scanner was also a powerful way of competing against neighboring hospitals, as well as for attracting leading physicians (Trajtbnberg, 1990:55). Thus the US market for scanners developed and segmented extremely rapidly, even though the scanner’s actual diagnostic value remained in some doubt. By 1984 virtually every 400+ bed hospital had its own scanner, while only 3% of the ~100 bed hospitals were so equipped.

Such rapid expansion attracted two kinds of attention and added two further actors to the network. First, competition exploded. The work of Oldenburg and Cormack provided a base from which a good number of other engineers and physicists could work to produce competing equipment. There was a rapid evolution of the technology which went through four clear generations before the pace slowed in the mid 1980s (Trajtenberg, 1990:68). The second generation multiplied the number of pencil beam sources and detectors, the third generation adopted a fan shaped beam and multiple rotating detectors, while the fourth generation established the stable ‘dominant design” with a complete ring of fixed detectors. The immediate objective of this evolutionary development was to reduce the scan time from minutes to fractions of a second. This was partly to reduce dosage, but also to deal with the practical problems of keeping the patient still while the image was being generated. If there was movement, such as breathing, the image quality fell accordingly. The later designs also significantly improved image resolution. Finally more powerful computing reduced the image reconstruction time (Hendee, 1983).

EMI’s ownership of this technology was fleeting, given the early US patents and the rapid pace of development behveen 1972 and 1985. While, by 1986, they held the greatest number of the relevant patents (123), other firms had made significant advances and had also secured important patents (GE, 52; Philips, 50; Picker Int., 47;

Siemens, 51; Toshiba, 18). But the relationships between the equipment suppliers and their customers were not driven solely by the number of patents. EMI’s competitors were those firms, such as GE and Siemens, that aheady held powerful positions in the X-ray equipment market. Not only did these established suppliers deal directly with the radiologists who specified the equipment which the larger hospitals we so keen to buy, they also knew how the equipment fitted into the work practices of the radiology department (Scherer, 1992:81). This kind of tacit knowledge enable them to shape their engineering development in ways that EM1 struggled to comprehend and emulate. They responded to the new market situation by setting up task forces to reinforce their relationships with the radiological and hospital community (Callahan & Salipante, 1979).

Finally, the explosive growth of the US market attracted the attention of the Federal government who became concerned that the third-party reimbursement system combined with inter-hospital competition in ways that were socially dysfunctional. This led to profound changes in the Federal health policies. They were alarmed at the money being spent, and made, on CT scanning (Iglehart, 1982:76). As a result the government attempted to slow the introduction by establishing Certificates of Need (CON) under Section 1122 of the Social Security Act. To a certain extent this dampened the market. But with Reagan’s election and the demise of many types of regulation the radiologists began to take matters into their own hands, setting up private CT clinics. The market peaked for a second time. But by now it was beginning to be saturated, with all the large hospitals equipped. In addition a brand new competitor appeared in the shape of an alternative and even more expensive technology, magnetic resonance imaging (MRE). While CT installations cost around $% million, MRI ran between $1 and $2 million apiece.

The interplay of the actors’ interests

In this section we see how the CT scanning technology was shaped by many actors and many concerns. The DHSS directed strategic shift from body scanning to brain scanning was almost immediately reversed by EMI’s US competitors as they demonstrated their profound understanding of their domestic market and developed the second generation Automatic Computerized Transverse Axial (ACTA) machines. Ultimately the transition through all four generations of equipment was driven by the need to reduce scan times, improve image quality and reconstruction times, but most of all by the need to fit the new equipment into the existing pattern of radiological and hospital commercial practices. These needs were



defined by the practice of radiology departments which were, in turn, dominated by radiologists with particular medical and commercial objectives in mind.

The technological generations were not in any sense the unfolding of a technological trajectory, except in retrospect. The general heuristic displayed in most technological development programs is the pursuit of economies of scale and automation (van den Belt & Rip, 1987:140). In semiconductors, for example, this leads to rapidly improving performance and falling prices. In the CT program the machine costs escalated and the operator interface became more complex while performance improved qualitatively. But since the machines were also substantial money earners, given the peculiarities of the US healthcare system, this proved to be no constraint. When the government stepped in to try and control the diffusion of the technology, the radiologists circumvented the system. But by 1985 the market was becoming saturated, the boom years were over as quickly as they had begun.

The Strategic Lessons

The management of socially constructed technological systems is daunting, since, by definition, the managers producing the technology are but one of several actors in the system. There are several different types of uncertainty present (Spender, 1989:42). In addition to the scientific and technical uncertainties of the technology itself, ignorance about the nature of the phenomena and their consequences, there is also substantial indeterminacy due to the presence of other actors. There is considerable incommensurability as management struggles to bring new combinations of factors into a coherent and stable relationship. Eventually the technology stabilizes and dominant designs emerge, but seldom in the way anticipated. While the pattern of development is clearly unpredictable, because of interpretive flexibility, we see that ideas about actor networks and interactive power illuminate the process. The power relations are themselves often influenced by the bodies of knowledge interacting in the network.

In retrospect we can see that the most important lesson is the brevity of the CT scanning business as a separate activity. X-ray equipment supply had been a large and stable business for almost a hundred years when this apparently revolutionary technology appeared. There seemed no immediate reason to think that CT imaging would not become a large and stable business in its own right. But we can also see that there was little new in the X-ray technology and therefore it was unlikely that the new system would create additional practices and market demands. The danger of market saturation existed from

the beginning, as GE’s and Powell’s estimates of the market size suggested. The real technical advance was in Hounstield’s computerized signal processing techniques. These are even better applied in the MRI technology which further diminishes the interpretive burden on the radiologists and their tacit skills. What EMI failed to appreciate, since they were not part of the X-ray ‘actor- network’, was how quickly the CT scanning technology would be co-opted and made part of the broader medical imaging business.

The question of whether EM1 made a strategic error in deciding to go it alone is extremely moot. Their decision certainly gave them a speed advantage and they extracted tremendous value from the rapid deployment of their equipment. Until the US government’s introduction of the CON controls in 1978, they were in a commanding position and were reaping significant profits (Blume, 1992: 186). But the setback in the US market hurt EM1 deeply, especially as it occurred at the same time that the parent company was getting into deep financial trouble and becoming extremely concerned about the spiraling costs of CT R&D.

The underlying strategic weakness was the limited size of the market and the likelihood of its being saturated within a short time. In this sense EMI’s mistake was to enter such a limited and exposed market in the first place. Given Oldenfield’s and Cormack’s earlier work, it is clear that the other suppliers, such as GE, Technicare and Siemens, were relatively aware of the possibilities. Indeed, it is not immediately obvious why these established actors judged the market conditions unfavorable for the commercial development which EMI’s machine precipitated, why no ‘product champions’ pushed the product forward earlier. But once EMI, in their ignorance of the real forces active in the business, had triggered the CT scanning market, these competitors had little option but to enter.

The way EM1 managed the appropriability question is a rather different strategic issue. Even their new technical director was able to see that they could not depend on their patents for protection (Blume, 1992: 166; Scherer, 1992:79). The best that they could do was to achieve ‘first mover’ advantages. As the pace of development slowed these advantages would disappear. Unless EM1 had, in the meantime, established an effective monopoly position, they would the thrown into a toe-to-toe commercial slugfest with competitors with many more resources. In the end their advantage could not be technological, since once the equipment was in the field, it would be inspected by the competition and there was little that could not be reverse-engineered or ‘engineered around’. The advantages had to be in terms of customer loyalty. Here EM1 faced two problems. First, they were competing with entrenched suppliers who had a long history of

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relationships with the radiologists. Second, the only way they could build up their own relations with the radiologists was by exposing their technology through the journals and at the RSNA conventions. In short, they had to expose their technology in order to legitimate themselves and so establish their place in the market. This followed unavoidably from their being outsiders trying to break into an existing medical imaging business.

Teece’s view, based on Martins journalistic interpretation, is that CT was an invention which created a new industry, and that EMI let this go. This is clearly incorrect and there is little evidence that EMI thought this way. Powell understood that EMI was getting into a fast moving match with heavyweights. In the end EM1 was not the only technologically successful CT manufacturer to quit the market. Pfizer, who had introduced the ACTA machine, withdrew before EMI. They argued that those heavily invested in the X-ray equipment supply business had to protect their long-term position, but for the other companies who had stumbled into CT imaging as a side business, it made little sense to stay once a dominant design emerged which they did not own.

The technology’s development, especially its rapid pace, was a result of the interaction between the radiologists, who saw CT scanning as a professional status symbol, their hospitals, who were hungry for new fee-earning equipment, the established X-ray equipment suppliers, who sought to protect their position as the new practices diffused through their market, and the government, who sought to restrain the rapid adoption which the competitive fee-earning healthcare system precipitated. Had the pace been less explosive and the window of opportunity longer EMI might have had a modest chance to operate without undue competition, but that is imagining a different world from the one that existed.

In the end it is difficult to conclude that EM1 gave the CT business anything less than a good shot. They overcame their unfamiliarity with the radiology business, dealt with new types of manufacturing, with marketing in the US against the world’s best, and made a great deal of money. But the unexpectedly rapid pace of the technology, the number of competitors prepared to enter the market, and the rising capital investments in R&D, design, manufacturing and distribution meant that EM1 were doomed unless they also managed to remain the dominant player in the relevant actor-network. Their exit strategy was not as orderly as it might have been since the timing was determined by the more serious financial and management problems affecting the parent company. But if accusations of strategic ineptitude are to be leveled it would seem that it was GE that made the real strategic error in failing to recognize the value of CT scanning when EM1 first approached them in 197 1. Ironically, this failure did not deny them the top spot in the industry, but

it did lead to Toshiba’s strong position. As Scherer (1992:82) reveals, EMI’s US design team eventually moved to Japan and became one of Toshiba’s principal assets.

Conclusion

In this paper we have presented a framework for considering the development of socially constructed technological systems. These arise because the position adopted within most innovation studies, that technology is the application of science to human affairs, is seldom tenable. Just as social activity is influenced by technology, so the evolution of technology is influenced by the society in which it emerges. We use several devices to clarify the framework. First we see that technology evolves within a dynamic actor network. Second, there are power relations between the actors and the technology becomes a medium in their struggle. Third, some of these power relations are shaped by the differing knowledge which the actors bring to their interactions. Finally, the network is shaped by the relative rates at which the actors learn. When one periods leaders fail to sustain their learning, the initiative can switch and new leaders emerge. EMI’s initial advantage in knowing how to make the equipment work was rapidly overtaken, not only by the other equipment manufacturers, but also by the hospitals and the radiologists who understood how this equipment would be integrated into the existing set of medical practices. Almost immediately EM1 were playing catch-up, being forced to leapfrog competitors’ designs in order to meet the rising demands of their customers.

This kind of analysis admits many more uncertainties and it gets very messy when compared to the naive linear model so favored in the innovation literature. It illustrates how difficult it is to play successfully in a situation in which many different actors are also engaged. But technology is inevitably this way. We do not end up with a tidy prescription, other than that one must try to identify the other actors and estimate their relative learning capabilities. We hope merely to clarify the kind of understanding which corporate strategists must develop as they try to manage their evolving technological resources.

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