product modularity and the product life cycle: new dynamics in the interactions of product and...

Int. J. Technology Management, Vol. 42, No. 4, 2008 365

Copyright © 2008 Inderscience Enterprises Ltd.

Product modularity and the product life cycle: new dynamics in the interactions of product and process technologies

Peter Cebon* Melbourne Business School University of Melbourne 200 Leicester Street Carlton, VIC 3053, Australia E-mail: [email protected] *Corresponding author

Oscar Hauptman Blue Skyline, Inc. 270 SW Natura Avenue Deerfield Beach, FL 33441, USA E-mail: [email protected]

Chander Shekhar Department of Finance University of Melbourne Parkville VIC 3010, Australia E-mail: [email protected]

Abstract: Many aspects of product life cycle theory – which underlies the theories of technical innovation in economics, strategy, marketing, operations management and product development – are based on the implicit assumption that products are integrated wholes. We argue that the modularisation of products undermines specific synergies that are associated with integrated product designs and that have been characterised as driving the product life cycle. We suggest how this effect of modularity impacts the structure of organisations, the boundaries of industries and the structure of economies.

Keywords: economics of innovation; modular innovation; process innovation; product innovation; product life cycle; product modularity; dominant design.

Reference to this paper should be made as follows: Cebon, P., Hauptman, O. and Shekhar, C. (2008) ‘Product modularity and the product life cycle: new dynamics in the interactions of product and process technologies’, Int. J. Technology Management, Vol. 42, No. 4, pp.365–386.

Biographical notes: Peter Cebon is currently a Senior Lecturer at the Melbourne Business School at the University of Melbourne, Australia. He has a PhD in Management (Organisation Studies) from the MIT Sloan School of Management. He teaches subjects in Organisational Behaviour and the Management of Innovation. His ongoing research involves issues in

366 P. Cebon, O. Hauptman and C. Shekhar

high-technology innovation processes in Australia, innovation governance, social construction processes in innovation, and the role of institutional processes in innovation. His recent publications include two books (MIT Press, Melbourne University Press) and articles in management and sociology journals.

Dr. Oscar Hauptman holds a PhD in Management of Technological Innovation from the MIT Sloan School of Management. He was on the faculty of the Harvard Business School, Carleton University (Ottawa, Canada), the Melbourne Business School (Australia) and Singapore Management University. His research has contributed to the fields of management of software development, technological forecasting, management of R&D and new process and product development teams, product design and concurrent engineering. His research for the current paper was conducted and funded by Melbourne Business School and the SMU-Wharton Research Center of Singapore Management University. Presently, he is a self-employed businessman and entrepreneur.

Chander Shekhar is currently a Senior Lecturer in the Department of Finance, the University of Melbourne, Australia. He has a PhD in Business Administration (Management Science and Finance) from the Pennsylvania State University and teaches Corporate Finance and Mergers and Acquisitions. His ongoing research involves issues in corporate governance, takeovers, IPOs, the evolution of markets and technological progress. His research addresses topics such as governance and value, merger premiums, multiple bidders and takeover strategies. His research has been published widely in finance, accounting and management journals.

1 Introduction

The product life cycle model, with its premise about the interrelationships of innovation and market development, is one of the most widely used frameworks for research on the management of technological innovation. It pervades research in management strategy (e.g., Abernathy and Clark, 1985; Abernathy and Utterback, 1978; Anderson and Tushman, 1990; Foster, 1986), industrial economics (e.g., Jenkins, 1975; Jovanovic and MacDonald, 1994; Klepper and Simons, 2000a; Mueller and Tilton, 1969; Sinclair et al., 2000), marketing (e.g., Urban and Star, 1991; Weitz and Wensley, 1988), and operations management (e.g., Hayes et al., 1988). Central to the model are the propositions that an industry is built around a core product (e.g., automobiles, computers) and that an industry’s innovation processes can be analysed at the product level. In the past decade or so, some researchers have examined innovation processes at the subsystem or component level (Henderson and Clark, 1990; Sanchez and Mahoney, 1996). Recently, Sanchez (1995) and Tushman and Murmann (1998) have argued that the introduction of product architectures based on discrete subsystems and components shifts the locus of innovation in an industry to the subsystem and component level, thereby fundamentally changing innovation dynamics within an industry. In this paper, we suggest how modularisation of products changes the traditional product life cycle both in the general case and specifically for the extension of the model proposed by Tushman and Murmann (1998).

Product modularity and the product life cycle 367

2 Products on a continuum from integrated to modular

An end-product is typically a set of components that are linked together so as to be useable as a relatively stand-alone unit by an end-user.1 Products vary on a design continuum from integrated to modular (Gawer and Cusumano, 2002; Schilling, 2000). This continuum arises for three reasons. First, some products contain technologies which are inherently more amenable to encapsulation in modular components than others. For example, software may be easier to realise as modular components than automobile components because it has lower material content (Whitney, 1996). Second, different product designers, either for reasons of strategy or design competence, may choose to exploit modularisability to a greater or lesser extent. For example, firms with high brand equity associated with particular products may intentionally create designs that limit the ability of customers to combine those products with modules manufactured by a third party. Third, even in a product with high levels of modularity, there will always be some cost involved in substituting modules.

In essence, a modular system is composed of subsystems or components whose interfaces are designed so that their internal complexity is ‘hidden’ from other subsystems or components and from the environment external to the system (Baldwin and Clark, 1997; 2000). In this discussion, we use the term module to refer to a subsystem or component of a modular system, and the term interface to refer to the set of technical specifications that define how modules interact with each other in a product design. An architecture of a design consists of both the decomposition of the overall functionalities of a product into a set of functional components (modules) and the set of interfaces that define how the functional modules interact in the product design (Sanchez, 1995; Sanchez and Mahoney, 1996). An architecture is modular in as far as it supports the substitutability of module variations (Sanchez, 1995; Sanchez and Mahoney, 1996; Schilling, 2000; Victor and Boynton, 1998), with more modular systems supporting more extensive substitutions of module variations. A subsystem, as defined by Tushman and Murmann (1998), lies between an integrated product and a module. It has the characteristics of a module, in that it ‘hides’ complexity within the subsystem behind an interface. However, it does not necessarily meet the other requirement for modularity – possessing an interface designed to permit substitutability.

It is also useful to distinguish between open and proprietary (or closed) architectures (Garud and Kumaraswamy, 1995a; Sanchez and Collins, 2001). With open architectures, the interface specifications are available to all players in the industry. Open-architecture interface specifications may be determined by a dominant firm or coalition of firms, or through some standards-setting process. Open architectures often create positive network externalities (Sanchez, 2000b), such as lower costs in the large-scale production of common components, but yield very little control to one firm unless it can control the standards defining the open architecture and/or innovate faster than the competition (Garud and Kumaraswamy, 1995a). An architecture is proprietary if its interface specifications are restricted to a single firm or cooperating group of companies such as a central company and its suppliers. With proprietary architectures, a firm may derive significant market benefits from modularisation, such as greater product variety and more rapid upgrading, but will forego the benefits of positive network externalities (e.g., Sanchez and Collins, 2001). Moreover, retaining control over a proprietary architecture may give a firm a degree of control over competition. More commonly,


however, proprietary architectures are hybrids, composed of both open and closed architectures. For instance, an industrial robot with a proprietary architecture may nevertheless use an open-architecture interface to its memory cards.

Finally, modular products may be characterised as having interfaces that are non-specifically synergistic, while integrated products have synergistically specific interfaces (Schilling, 2000). This means that in integrated product designs, the functionality of the design is optimised by creating interfaces that optimise overall product performance for a specific set of sub-systems. This implies that overall performance declines if one substitutes sub-system variations into the design. By contrast, modular products can create synergies in the form of equivalent levels or alternate forms of performance when module variations are substituted into the design. For example, a user can replace the Cathode Ray Tube (CRT) display for her computer with a Liquid Crystal Diode (LCD) display with essentially no change in utility (an perhaps even realising a performance improvement). Because a modular CRT display performs well with the computer (in fact, as well as it would if it were integrated into the computer), the modular CRT display and the computer are synergistic. However, because the user can swap the CRT display for a LCD display, the synergy is not specific to the CRT display, and indeed the computer is equally synergistic with a LCD display. Thus, the CRT display and the computer are characterised as non-specifically synergistic.

3 Dominance of modular over integrated product designs

In this article we make no claim about the relative strategic merits of modular versus integrated product designs. However, we note that some researchers have proposed that modular designs may be an integral part of a new dominant strategy in many industries (Sanchez, 1995; Sanchez and Mahoney, 1996), particularly in those which demand high levels of product configurability (Sanchez and Mahoney, 1996), or where designers must deal with high levels of product complexity. In terms of strategic flexibility, some researchers see fundamental changes in market demand for flexibility in product design as driving a trend towards modularisation in particular industries (e.g., Baldwin and Clark, 2000; Garud and Kumaraswamy, 1993; Sanchez, 1995; Schilling, 2000; Victor and Boynton, 1998). Modularisation in the form of open architectures may also bring strategic advantages through positive network externalities (Sanchez, 2000b). For example, if a firm wishing to produce a new product can purchase key modules in the open market, it may be much cheaper and faster to create a product design based on a set of modules compatible with the open architecture standards than to design a proprietary product architecture. Furthermore, such product designs may be easier to upgrade by incorporating innovations in modules that can be purchased rather than developed internally. Finally, a firm may also choose to design modules that conform to an open architecture so that it can sell modules in the market (Sanchez, 2000b), thereby further increasing positive network externalities.

These strategic incentives at the firm level are manifested in new industry-level structures and interactions. As Gawer and Cusumano (2002, pp.4–5) observe:

“An increasing number of industries today consist of different firms that each develop one component of a big jigsaw puzzle. This evolution has happened in the computer industry, where companies like vertically integrated IBM and Digital Equipment Corporation (DEC) have left center stage for specialist


hardware component maker Intel and specialist software component maker Microsoft – and the plethora of complementary developers around them. The reasons industries evolve this way are widely discussed, but a central tenet of many theories is the concept of modularity.” (Italics in original)

In terms of complexity, other researchers (e.g., Baldwin and Clark, 1997; Sanchez and Mahoney, 1996), building on authors such as Simon (1981), have argued that products are essentially bundles of embodied knowledge (including technological knowledge) that are either physically embodied in a product as artefact or embedded in processes of design and manufacture that create and realise a product. Designers may also modularise designs to avoid creating unmanageable complexity in coordinating the many forms of embodied knowledge involved in creating a product.

For the reasons mentioned above, it may be the case that modular products are often cheaper and faster to design and manufacture. Comparative cost analytics are hard to come by, but “…broad measures suggest the substantial impact that modular architectures can have on technologically determined economics of product creation” Sanchez (1999, p.102). Sanchez goes on to point out that after adopting modular design approaches in 1989, Chrysler Corporation reduced the time to create a new automobile design from 72 months to less than 30 months. Additionally, the cost of development was reduced from $2–$3 billion to less than $1 billion, and the development team reduced from as many as 5000 people to only 700–900 people. Chrysler is not the only automaker to reap cost and speed benefits from modularisation. General Motors claims that it will dramatically increase the variety and performance of its power train systems while reducing costs by embracing modularity (Corbett, 2002). Similarly, Ford expects to achieve dramatic cost savings through the use of modularity in both its conventional and hybrid vehicles (Shirouzu, 2003; Waurzyniak, 2003). These cost savings and speed improvements are not limited to the automobile industry. Sanchez and Collins (2001) report that at GE Fanuc Automation, the modular approach to product creation reduced the human resources and the development time required to create factory automation systems by as much as 50% to 60%. Sanchez (2004) also documents unit cost reductions of 52% for Philips powered toothbrushes after adopting “coordinated modular product and process architectures”. Langlois (2000) argues for benefits of modularity in semiconductor wafer fabrication equipment.

Gawer and Cusumano (2002, p.206) illustrate the benefits of modularity with Handspring, the company started by the Palm Pilot entrepreneurs who left Palm after it was acquired by 3Com:

“…As of mid-2001 Handspring was a leader of the emerging Palm economy – the group of firms building complements to the Palm Pilot….Handspring adopted a platform approach to product design….Handspring engineers designed the hardware around this concept in a bold move to make modules or peripherals as easy as possible to connect. The expansion modules literally snapped into the expansion slot on the back of the Visor PDA. Palm devices lacked such a simple mechanism for expansion when Handspring introduced this innovation….But Handspring also encouraged external companies to develop products that acted as accessories or modules to Visors.”

Gawer and Cusumano list about ten such modules, ranging from financial calculator add-ons to wireless modems to digital cameras to AM-FM radios, all of which worked seamlessly with the Handspring platform.


We reiterate that we are not arguing here that modular designs always dominate integrated counterparts. Integrated products may be cheaper to produce and thus offer cost advantages when flexibility and complexity are not significant issues. There may also be conditions under which integrated product designs can achieve higher performance and provide higher utility. On could argue, for instance, that the trend towards modularisation in the design of management education programmes, whereby knowledge is bundled into various chunks of three or six hours, inherently reduces their value because it is harder to teach broad, encompassing ‘big ideas’ in small modules. Furthermore, the cost of modularising a design may not be justified if the product is not complex and neither its market nor underlying technologies are changing quickly.

4 Innovation in modular systems

The non-specific synergies in modular designs allow four types of innovation (Henderson and Clark, 1990; Sanchez and Mahoney, 1996). Designers can incrementally innovate within an existing type of module design. In such incremental innovations (which may not be ‘incremental’ in their effects), neither the technology used within the module nor the nature of the interfaces between the module and other modules changes significantly. In hard-drive storage devices for personal computers, for example, most of the 100 000-fold increase in storage capacity from 5 MB in the mid-1980s to 500 GB today was achieved by progressive refinements of the parts or components within hard-drive modules and of the way they interact with each other.

Alternatively, designers can replace a module based on one technology with a functionally similar module based on another technology – a modular form of innovation (Langlois and Robertson, 1995) in which the internal content of the module changes, but the interface specification remains the same. Examples include substituting a hard drive for a floppy drive on the original IBM PC, a CD player for a record player (Langlois and Robertson, 1992), or an LCD screen for a CRT screen.

Third, designers can create an architectural innovation in which the interfaces between two or more modules change while maintaining the same kinds of components within a product design. Examples include changes in the interfaces between peripheral storage devices and the CPU of a computer (e.g., MFM, IDE, SCSI), and the adoption of the Universal Serial Bus (USB) which allows connectivity of many kinds of peripherals in common use (printers, personal organisers) with no internal changes in designs of other modules.

Finally, designers can create new product innovations that provide new bundles of functionalities to users through new sets of components. The laptop computer is a product innovation based on new components (e.g., rechargeable batteries) that provide the functionality of portability in a personal computer. New products usually involve new architectures that combine one or more new kinds of modules with a number of pre-existing modules, some of which may have been incrementally improved or otherwise modified.


5 Modularity and the product life cycle model

The implications of modularity in product designs for the product life cycle can be derived by explicating how an integrated product is presumed to follow the product life cycle, and then assessing how the introduction of modularisation would lead to deviations from the model. We start by summarising the product life cycle model and showing how it rests implicitly on an assumption of increasing synergistic specificity (a characteristic of integrated product designs) not only between the components of the product, but also between the product, the organisation which designs it, and the market which consumes it. We then consider how possibilities for modular and architectural forms of innovation in modular product designs undermine the core predictions of product life cycle theory.

5.1 The product life cycle and patterns of innovation

Various elaborations of the product life cycle model (e.g., Abernathy and Clark, 1985; Anderson and Tushman, 1990; Clark, 1985; Foster, 1986; Jenkins, 1975; Jovanovic and MacDonald, 1994; Klepper and Simons, 2000a; Mueller and Tilton, 1969; Sanchez, 1995; Sanchez and Heene, 2004; Sinclair et al., 2000; Weitz and Wensley, 1988) and industry evolution models based upon it (e.g., Hayes et al., 1988; Tushman and Rosenkopf, 1992; Tushman and Anderson, 1986; Urban and Star, 1991) rest on the core idea that there is a temporal and causal connection between the nature of the market for a product and the evolution of both the technologies that it embodies (product technologies) and the technologies that support and enable it (process technologies). The connection between product technologies and product markets is predicated upon the need for firms that are creating new products to experiment with product designs to learn enough about customer needs to assure the acceptance and diffusion of a new product concept. The connection with process technologies is predicated upon the changing economics of production as a new product concept evolves from innovation to mass production and commoditisation. The transition from novel products to mass production is marked by the emergence of a dominant design.

A widely used version of the product life cycle model (Abernathy and Clark, 1985) can be summarised as follows. The evolution of an industry begins with the innovation and market introduction of a novel product by a firm. Since the innovation must create a new market, there are no pre-existing links to customers, and the innovation is likely also to call for significant reorganisation of existing industry value chains. The innovation requires the firm to master technical competences that did not previously exist in that market space. These actions lead to an ‘architectural innovation’ in a broad sense, because it “lays down the architecture of the new industry” (Abernathy and Clark, 1985, p.60).2 Because the technical capabilities required to compete are new, the players in the nascent industry are assumed to be either start-ups or players in related industries. At this stage, the product concept is still evolving, and numerous firms may begin to participate in its design, refinement and production development, experimenting with features, materials, and design approaches with a view to creating product configurations that appeal to the market. If successful in creating a viable new product concept, the nascent industry may be attractive economically, with early entrants sharing in high returns and rapidly growing demand.


Eventually, one firm develops a product design which integrates technologies and features in such a way that it is both attractive to a significant market and is economical to develop and produce. This product design becomes the ‘dominant design’ for the new industry, and the company creating the dominant design may be able to achieve a dominant market share (Anderson and Tushman, 1991) and then to derive profit advantages by achieving superior economies of scale. During the shakeout that follows the emergence of the dominant design, companies that are able to imitate the dominant design may survive and succeed as participants in an oligopolistic market (Klepper and Simons, 2000b), while other firms exit the industry or retreat to market niches not served by the dominant firms. In the ensuing mature phase of the industry, the remaining players produce essentially the same product design – i.e., the same configuration of components (Christensen, 1997; Cusumano et al., 1992; Rosenbloom and Cusumano, 1987; Utterback, 1994). Firms then compete on the basis of price and product performance (Abernathy, 1978).

As competition evolves from between-configuration competition to within-configuration competition, the primary locus of innovation shifts from product innovation to process innovation (Abernathy and Utterback, 1978; Henderson, 1995). Eventually, opportunities for major process innovations are exhausted, and manufacturing processes become more rigid (Leonard-Barton, 1992). Product price and production efficiency and reliability become the main factors that separate winners from losers (e.g., Abernathy, 1978).

During this evolution, the dominant design is refined in two ways. Along one dimension, new product variations are developed, creating products for and channels to new customers (‘niche innovations’). On a second dimension, the main design itself is progressively refined (‘regular innovation’), and new product offerings are clustered around the progressively refined design (Tushman and Murmann, 1998). The process of regular innovation – achieved through means such as more specialised machinery, greater economies of scale, and the development of relatively closed communities of practice within and between firms (Dosi, 1988) – erects perceptual, political, and technical barriers that prevent the manufacturers of the dominant design from detecting novel or emergent designs, or from implementing them even if detected. In this way, what were originally core competences may become core rigidities (Leonard-Barton, 1992). The product market may then be open for a new entrant to introduce a revolutionary product innovation that initiates a new product life cycle that transforms the industry and the competences that underpin it (Anderson and Tushman, 1990; Tushman and Rosenkopf, 1992; Tushman and Anderson, 1986; Tushman and Murmann, 1998).

These processes of innovation and market growth are summarised in Figure 1.


Figure 1 Product life cycle and patterns of technological innovation for integrated products

Sales(PLC)

InnovationIntensity

(product andprocess)

Time

Time

Dominantdesign

0

0

Product

Process

Source: Adapted from Abernathy (1978)

5.2 The dominant design and synergistic specificity

The foregoing version of the product life cycle model hinges on the concept of dominant design and an ensuing “specific path, along an industry’s design hierarchy, which establishes dominance among competing design paths” (Utterback and Suarez, 1993, p.49). The ‘design path’ founded on the dominant design drives innovation processes both at the beginning and at the end of the product life cycle. The emergence of a dominant design thus dramatically affects the nature and direction of competition, and the structure and evolution of the industry (Abernathy and Utterback, 1978; Utterback and Suarez, 1993). At the beginning of the cycle, the emergence of the dominant design leads to a shakeout that consolidates and rationalises the industry, and enables firms using the dominant design to build both their skills and market positions (Utterback and Suarez, 1993).

Early researchers emphasised the role of increasing technical specialisation, scale economies (Abernathy and Clark, 1985), and embedded competences (Henderson and Clark, 1990; Leonard-Barton, 1992) in maintaining the dominance of a dominant design. All three of these factors derive their competitive benefits from increases in synergistic specificity (Schilling, 2000). The increasing synergistic specificity that leads to the cost and performance improvements derived from the dominant design results not only from refinements of interfaces between components in the product design, but also from refinements of interactions between elements of the product, the organisation (broadly defined), and the market. In the first case, the skills of the product designers and production engineers become specific to the particular design. In the second case, the organisation of the production system becomes specific to the design. In the third case,


the cognitive orientations of the people involved in both providing and using the product become aligned with the dominant design (Henderson and Clark, 1990; Leonard-Barton, 1992; Tushman and Murmann, 1998).

Researchers have also clarified ways in which important network externalities develop around specific complementary assets used in developing and producing the dominant design (Teece, 1988; Sanchez, 2000b), such as occurred in connection with videocassette recorders (Cusumano et al., 1992), typewriters (David, 1985), and the Unix operating system (Garud and Kumaraswamy, 1993). Emergence of a dominant design also permits formation of more stable and reliable relations with suppliers, vendors, and customers. From a market perspective, a dominant design also reduces product-class confusion and often brings dramatic decreases in product cost (Anderson and Tushman, 1990). All of these benefits, once again, result from increases in several forms of synergistic specificity in the interactions between the product design, producers, suppliers, and customers.

It is important to emphasise that the core rigidities that prevent firms from responding to competitive threats posed by radically new technologies near the end of a product life cycle also result from these same increases in synergistic specificity. These rigidities might reside in the particularities of increasingly specialised production systems (Anderson and Tushman, 1990; Leonard-Barton, 1995) or in the entrenchment of distribution channels to customers (Christensen, 1997). If an innovative new product comes along and transforms the industry, a new cycle of progressive increases in synergistic specificity will ensue among the cognitive orientations of product designers, the specialisation of production systems, commitments to market channels, and the expectations of customers.

5.3 The impact of modularity on drivers of the product life cycle

As we have argued above, the central assumption of the product life cycle model is that product market evolution is initially driven by increasing synergistic specificity between a dominant design, the organisation of production, the competences involved in design and production, and market expectations. Eventually, however, the specific synergies that lead to increasing specialisation, scale economies, embedded competences, and network externalities are exhausted and leave industry participants locked in an industry structure that is no longer capable of innovation. In modular products, however, the interfaces between product components are synergistically non-specific. In this section we examine how the non-specificity of the synergies within a modular product design affects specialisation, scale economies, embedded competences, network externalities, and ultimately innovation processes in an industry founded on a modular dominant design. Our core argument is that the locking in processes associated with integrated products are mitigated significantly or eliminated completely.

With regard to technical specialisation, there is considerable evidence that companies pursuing modular design strategies develop specialist expertise in both the design and production of particular modules and in the design of product architectures (Sanchez, 2000a–b; 2001). However, those forms of expertise do not necessarily lead to an increase in synergistic specificity between an organisation, its technical competences, and production systems. Because a modular product design can ‘strategically partition’ a product into modules that are loosely coupled in the design, it becomes possible for the organisation to ‘modularise’ the technical groups that design and manufacture modules,


even to the point of out-sourcing these activities (Sanchez, 2000a–b). Consequently, design or production groups can be substituted into and out of development or production processes without disrupting the organisation and flow of the process. In effect, modularisation of designs affords the synergy benefits of technical specialisation without leading to lock-in among specific participants in an industry.

The television industry provides an example of how modular designs enable synergies from technical specialisation and scale effects without creating the ‘lock-in’ that ultimately inhibits innovation associated with either specialisation or scale economies among industry participants. Television is a ‘mature’ product in terms of the product life cycle, but its industry remains innovative in its ability to create higher performing products at steadily falling prices. Within the modular designs of televisions today, well-defined types of industry-standard components (Sanchez, 1995; 2006) are combined to create a broad range of television models and to achieve increases in television performance, such as 100 Hz image refresh rates, high-resolution screens, and the digitalisation of signals. Major assemblers of televisions are also large-scale producers of standard components for televisions, and firms like Philips and Matsushita have business units developing and marketing standard components that rival in scale their assembled television business units. Television assemblers around the world seek out the components that offer the best combination of performance and cost for their televisions from any component producer, including from the component business units of their rivals in selling assembled televisions. The ability to ‘plug and play’ mass-produced industry-standard types of components within modular television architectures has kept innovation in components at high levels and led to steadily falling costs even though the television has been a mature product for at least a quarter century.

Modularisation may also counteract the tendency of firms to become locked-in by their embedded competences. As a general rule, modularisation forces organisations to make their tacit technical knowledge about the interactions between components explicit by constructing clear and fully defined interface specifications (Sanchez, 2001). Furthermore, in modular product designs, the remaining embedded knowledge and associated competences tend to be confined within the boundaries of individual modules, and consequently within the modularised organisational units which design and produce them. This compartmentalisation of knowledge, which mirrors the strategically partitioned component structure of the product design, enables the substitution of different groups with different knowledge and competency sets into a firm’s design and production processes (Sanchez, 2000a). This substitutability of knowledge sets in a modular design and production process helps to prevent the lock-in of an organisation to an existing knowledge base, thereby avoiding the tendency to develop ‘core rigidities’. Because of the non-specific nature of the knowledge synergies in modular designs, there is a much lower likelihood of lock-in and stasis between particular sets of embedded knowledge and competences in the interactions of organisational, technological, and market systems.

Finally, lock-in associated with network externalities results from synergistic specificity between particular product designs and complementary assets in the marketplace (David, 1985). In as far as those complementary assets are substitutable, however, the extent of such lock-in effects is likely to be significantly reduced. For example, VHS and Betamax formats in videocassette recorders could have co-existed just like electric and gas stoves if people had only used videocassette recorders to play back


homemade videos and to record and replay television shows (Cusumano et al., 1992). VHS only triumphed decisively over Betamax when video rentals became a significant business and video rental stores found it uneconomic to carry inventory of videos in two formats (Cusumano et al., 1992). By contrast, DVD players are today being equipped with several software modules that enable them to interpret a number of signal protocols on DVDs, thus creating non-specific synergies between DVDs and DVD players.

In summary, modularisation of product designs helps to reduce, and in some cases may eliminate, the four principal drivers of lock-in for dominant designs – scale economies, specialisation, embedded competences, and network externalities. In the next section we examine how this undermining affects innovation dynamics in the product life cycle.

5.4 Innovations in modular systems and the product life cycle

The progressive increases in synergistic specificity realised in non-modular (integrated) dominant designs arise largely through incremental and component forms of innovation – i.e., incremental improvements within existing component technologies, or changes in the technology used in a given type of component. Such innovations tend to stabilise value chains in a product life cycle model (Foster, 1986; Tushman and Anderson, 1986) because they induce the lock-in effects we have discussed. With modular product designs, however, innovation can occur at architectural and product levels as well, leading to product and process innovations that can be much more rapid and chaotic (see Figure 2). Product, architectural, modular, and incremental innovations may happen in any order. Innovation processes no longer stabilise the industry, but rather destabilise it. This destabilising force limits the specific synergies that might be obtained from current design and product systems within an industry, thereby weakening the incentives that lead to lock-in.

Figure 2 Innovation patterns for modular and integrated products

Innovationintensity for

integratedproducts

Time

Time

Product innovation Introduction of innovativenew integrated design

Innovationintensity for

modularproducts

Process innovation


To illustrate how innovation might unfold in a modular market, a new product might start with an architectural innovation, in which pre-existing modules are organised in a new kind of product architecture that invites creation of new kinds of modules. For example, the addition of a high-speed data port to personal computers opened up the market for external devices that could feed audio and video content to the computer, and for software to manage the content. Similarly, the creation of new kinds of modules that are compatible with existing product architectures can drive the creation of new products that make use of those new modules. For instance, the development of small motors and high-fidelity headphones that could be combined with pre-existing audio components for personal cassette players such as the Sony Walkman (Sanderson and Uzumeri, 1997) led in turn to the innovation of the personal radio, the personal CD-player, the personal MP3 player, and the personal mini-disc player. Of course, factors such as the market power of manufacturers and the extent to which a product architecture is open or proprietary will also affect the temporal ordering of such innovations.

6 Modularity and the dominant design

We have suggested that modularisation can undermine the drivers of lock-in and create simultaneous possibilities for multiple types of innovation. We now consider the impact of modularity and its associated innovation processes on the establishment and dislodgement of a dominant design and dominant producers in the product life cycle model. First, we suggest that the traditional modes of interactions between new products and markets that lead to the establishment of a dominant design will decline in importance as products become more modular. When producers offer modular product designs that enable consumers to swap modules in a given architecture, experimentation by consumers to determine preferred combinations of function, features, and performance levels can be relatively cheap (Sanchez, 1999). This suggests the possibility for widespread market acceptance and mass production (at the component level) of a new product type before – and possibly without – the emergence of a single version of a product as a dominant design (see Anderson and Tushman, 1990).

The establishment of a dominant design has also been characterised as marking a transition from competition between design configurations to competition within a design configuration (Anderson and Tushman, 1990). The more modular a new product design is, however, the less likely such a sharp transition will occur. When innovative technology can be ‘packaged’ and added as a new type of module to an existing architecture, new product concepts based on expanded product architectures can be innovated at the same time that the components in the original architecture continue to evolve. The greater ability of modular architectures to ‘spin-off’ new architectures also increases the number of market niches that can be occupied by a modularised technology when it can be embedded into a number of different architectures. For example, ‘Zip’ drive technology originally developed for PCs was subsequently incorporated in workstations, industrial robots, and many kinds of automation devices. Moreover, the addition of Zip storage technology to PCs made the original host architecture more flexible, and therefore able to occupy more niches (Pine, 1993; Sanchez, 1999; von Hippel, 1998).


When product markets are based on ‘open’ modular architectures (i.e., interface specifications are public knowledge), the ability of a few large producers to become entrenched in the maturity stage of the product life cycle will be reduced, because it is possible for new entrants to configure new product variations by purchasing modules from existing suppliers. For example, Dell entered a mature PC market by purchasing industry standard PC components and introducing innovations in logistics and supply chain management.

In conventional models of technological change, technological discontinuities are characterised as competence-enhancing or competence-destroying. “A competence-enhancing discontinuity builds on know-how embodied in the technology that it replaces” (Anderson and Tushman, 1990, p.11) and thereby strengthens the position of incumbents, while a competence-destroying discontinuity replaces existing know-how and thus undermines the advantages of incumbents. With modular and architectural innovations, however, the impact of a given innovation on competences of incumbents may not be so clearly divided, and may vary greatly among component producers and final product assemblers. For example, for some component producers the 3.5″ hard disk drive would be evaluated as competence-destroying, because of the way it impacted the fortunes of some disk drive manufacturers (Christensen, 1997). However, the 3.5″ hard disk drive dramatically enhanced the competences of computer assemblers. It also facilitated a key architectural innovation – the laptop computer – and thereby enhanced the competences of new entrants that used the laptop as a vehicle to enter the PC market (e.g., Toshiba, Sony). To the extent that laptops have replaced traditional desktop PCs, however, the innovation of the 3.5″ hard disk drive can also be said to be competence-destroying for some PC makers. Consequently, whether or not an innovation is competence-enhancing or competence-destroying depends on the roles of specific actors in an innovation process.

More broadly, Tushman and Murmann (1998) have argued that modularisation does not change the logic of the product life cycle, but shifts ‘product life cycle logic’ to operate at a different level of analysis, namely at the level of modules. They construct their argument by induction from one case, namely the development of the airplane during the 1920s and 1930s. However, analysis of the product life cycle in other industries refutes this view. Consider, for example, the computer. Before the introduction of the modular IBM 360, computers were integrated machines. Once IBM created the modular 360 design, however, Tushman and Murmann’s model would suggest that individual modules (mainframes, disk drives, printers, terminals, operating systems) would follow the product life cycle model, even if the IBM 360 did not. However, if one traces the histories of each of those modules in the 360, one can find many cases of components and sub-assemblies that were simply replaced through innovation of new modular components, such as disk arrays replacing tape drives, rather than evolving through a module-level product life cycle.

7 Further implications of modular designs

We now suggest these further implications of modularisation: the impacts of modularisation on rent capturing, on technology diffusion processes, and on the organisation of industries.


7.1 Rent capturing with modular products

In the traditional product life cycle model, the emergence of a dominant design precipitates a shakeout that reduces the number of firms in the industry (Utterback and Suarez, 1993). Some incumbents and potential new entrants lack the resources (including managerial skills) to construct the competences and synergies (such as economies of scale) that are necessary to survive as the market size grows (Anderson and Tushman, 1990; Henderson and Clark, 1990; Utterback and Suarez, 1993). The few competent firms that survive shakeout control the dominant design, use it to attract oligopolistic rents (Klepper and Simons, 2000b; Utterback and Suarez, 1993), and exert control over other players in the value chain (Utterback and Suarez, 1993).

For modular product markets based on proprietary (closed) architectures, rent capturing through the product life cycle is likely to be similar to rent capturing by integrated designs. Firms that can produce the requisite functionalities in their product designs will capture oligopolistic rents. For modular products with open architectures, however, it is harder to capture rents through product designs per se, because appropriability of product designs is weak.

Thus, in open architectural product markets, firms must seek to generate rents through new approaches to exploiting the modular attributes of a product or its market. The examples below illustrate three strategies for doing so.

First, Garud and Kumaraswamy (1993) show how Sun Microsystems gave away its technology to capture rents from transient monopolies. Sun made its Sparcstation the dominant design by making its operating system an open architecture that became the de facto standard for workstations. Sun then used its organisational learning ability to lead the rapid evolution of the market. In effect, Sun was able to capture rents by converting embedded competences into network externalities that made Sun’s products more attractive than products based on closed architectures (Hax and Wilde, 1999). More generally, being continually first to market with innovations is essential to capturing rents in open architecture markets. Such strategies are likely to drive hypercompetition (see D’Aveni and Gunther, 1994; Schilling, 2000).

Second, a company can use its market power to integrate an otherwise modular product and capture a monopoly rent. Virtually the entire Microsoft antitrust case can be understood in this way.3 In particular, Microsoft attempted to integrate a browser into its operating system, while Netscape was trying to offer a modular alternative. Similarly, Sun Microsystems developed Java to make computing operating-system-independent (i.e., modularise part of the functions). Microsoft attempted to undermine this aspect of Java by changing key aspects of the Windows® implementation. It manipulated product interfaces by threatening to change the operating system so it would not run with some products (e.g., Real Audio and Quicktime) and by manipulating the way products were put together through its bundling strategy (e.g., Internet Explorer). It manipulated process architectures by withholding licenses from companies at critical times (e.g., IBM’s license to bundle Windows 95®) and by withholding key technical information for future versions of Windows® from potential providers of competing products (e.g., Netscape).

Finally, companies can create transient value by increasing the modularity of the system. In as far as process and product interfaces are implicit (i.e., the interfaces are poorly defined) the module manufacturers and assemblers may be bound to each other through contractual and trust relations. This is expensive both in terms of the cost of maintaining the relationship, and in terms of allocating rents between the parties, since


each can potentially hold the other to ransom. As interface complexity increases, so does this cost. As a result, if the companies do not hold the product as a joint monopoly, one or both has an incentive to create wealth through architectural innovation. So, for example, a contract assembler of computers might offer ‘design for manufacturing’ services and logistics services to clients. In so doing, it simultaneously increases the value of its offering, but rationalises the process further so as to reduce the rent it can capture from the value it adds. Fasteners provide an extreme case of this: nuts and bolts are so standardised that manufacturers have little opportunity to capture rents from these standard products. As such we expect that, given a relatively stable architecture, and the lack of a joint monopoly, firms will constantly attempt to add value by making the product and process interfaces more explicit and, in so doing, they will modularise the relationship even further.

7.2 Technological evolution and diffusion in modular markets

The ‘S-Curve’ (Foster, 1986) is a common heuristic for representing the evolution of a technology towards a physical limit. S-Curves are also used to represent the diffusion of a technology through a market (Rogers, 1983). Technology evolves up an S-Curve through regular innovation (Foster, 1986), and as it proceeds up its S-Curve, it diffuses to fill the market circumscribed by the limits of the needs it can satisfy.

Because technologies, markets, and products can be effectively decoupled in modular markets, the evolution of a technology need not be tightly coupled to a given product or market. Modules are not necessarily specific to architectures and may be used in architectures of diverse product classes – such as ‘Zip’ drives used in personal computers and in industrial robots. The incentives that drive the evolution of a technology embodied in a module may vary widely with the different architectures it is used in for different markets. In effect, each product architecture and each of the associated modules may have their own S-Curves. Thus, in modular markets, instead of thinking in terms of a single S-Curve for an individual product, it is more useful to think of a mesh of intersecting S-Curves for components used in various architectures. We call such a representation an innovation mesh (see Figure 3). In an innovation mesh, the columns correspond to the set of architectures that use a technology, with each column representing an architecture. The rows correspond to the modules used in each architecture. A product corresponds to an architecture and a specific set of modules used with it (shown by the circles at the intersections of module rows with an architecture column). As suggested by the S-Curves for each module and architecture, each module and architecture in an innovation mesh could be at different points in its technological evolution.

In an innovation mesh, technological change can be seen to happen in four ways. First, in incremental innovation, a module may advance up its S-Curve. Second, in modular innovation, a new kind of module may be added to one or more architectures. Third, in architectural innovation, an architecture may evolve technologically (through refinements and extensions of interface specifications). Fourth, in product innovation, a new product architecture using existing and new modules may be added.

The innovation mesh helps to make clear that a technology embodied in modules may evolve at a rate independent of the development of the market for any given product, and that that technological evolution both within modules and between modules, that is in the ways modules are interrelated in product designs – i.e., in architectures.


Figure 3 Innovation mesh framework for the analysis of innovation in modular systems (see online version for colours)

Stage oftechnologicalevolution ofarchitecture

Module 3

Module 1

Module 2

Module 4

Module 5

ArchitectureA

ArchitectureB

ArchitectureC

ArchitectureD

Stage oftechnologicalevolution of

module

7.3 Organising for modular innovation

The optimal form of organisation according to product life cycle theory is the ambidextrous organisation (Leonard-Barton, 1995; Tushman and Murmann, 1998) that can both produce the incremental innovation that drives technology evolution during the convergent phases of the product life cycle, and that is also able to ‘reinvent’ itself and its products by changing to new technologies and architectures. In contrast, modularisation not only enables components to be decoupled technically, but also enables development processes for components to be decoupled (Sanchez and Mahoney, 1996). Efficient forms of organisation for driving innovation in modular systems may therefore involve a meta-level organisation that defines architectures and the structure of modules, and decoupled development units which design the modules (Sanchez, 2001). Innovative organisations in modular markets are characterised by an ability to coordinate simultaneous processes of architecture development and module development that drive innovation at the module, product, and architectural levels (Sanchez, 2000a–b; 2001; Sanchez and Collins, 2001).

Modular markets typically involve two types of organisation, one specialising in designing and making modules (module manufacturers) and the other specialising in creating architectures that aggregate modules and in assembling modules into final products (assemblers). In such a situation, the optimal form of industrial organisation tends to become a network of module makers and assemblers rather than a dominant manufacturer with tiers of subservient suppliers (Langlois and Robertson, 1995; Piore and Sabel, 1984; Saxenian, 1994; Truffer et al., 1998). As Sanchez (2001) observed, it is not a coincidence that the most dynamically innovative product markets of our time (PCs and telecoms, for example) are also the most highly modularised in designs and the most vertically disintegrated in organisation.


In such an environment, we expect to see extensive entrainment (temporal organisation) of firms to a system-wide schedule (Ancona and Chong, 1996). Consider two computer assemblers. If one pressures its module suppliers to produce new modules by June and December, so it can release its new products at trade shows in September and March, the other will have access to the same new modules at the same time. It will then schedule its product releases for the same trade shows, and put pressure on those of its suppliers which do not supply its competitor to deliver in June and December as well. Those suppliers will put similar demands on third tier suppliers, and will make modules available to other assemblers, possibly outside the narrow sectors in which the two original firms operate. Once the market (e.g., the computer magazines) gets used to this schedule, it will build its own expectations. Consequently, we can expect an entire complex of firms to be entrained into the same timing schedule.

8 Conclusions and further research

In this paper we attempted, building on previous research in modularity (Baldwin and Clark, 1997; Garud and Kumaraswamy, 1995b; Gawer and Cusumano, 2002; Sanchez, 1995; 2001) to explore the impact of modularisation of technology on various aspects of the product life cycle. Specifically, our conceptualisation suggests that key aspects of the product life cycle and its links with innovation theory are challenged and even dramatically altered.

Our arguments suggest that in the ideal case, in which a product has full non-specific synergy among modules and subsystems, the product life cycle will be significantly altered and attenuated, although the effects of institutional inertia, brands, and the market power of dominant firms may still work to preserve some basic characteristics of the product life cycle model. The tension between the forces of modularity and these traditional factors behind the product life cycle will have effects on the nature of rent capturing, the way in which products diffuse, and the structuring of organisations and industries. It remains an empirical question to determine the scale of the effects we hypothesise and the full details and dimensions of the phenomena we discuss. In this regard, we offer some concluding ideas about how to address these issues empirically by developing ways to measure the degree of modularity of design and then the impact of modularity on the product life cycle.

Presently, the biggest challenge in empirical research on modularity is quantifying modularity. One promising approach would be to measure the cost of developing a new component design as a fraction of the total redesign cost for an architecture the component is used in, thereby taking into account the impact of any modification of one component on the rest of the components (Balachandra, 2002). If an architecture is highly modular, this fraction should be close to one. If an architecture is integrated, then it will be a small fraction. This approach could also be adapted to process modularity, as Schilling and Steensma’s (2001) work on outsourcing suggests. With adequate measures of modularity, the key propositions presented in this article could be tested.


Acknowledgements

This research was supported by Wharton-SMU Research Center, Singapore Management University (Ref: C207/MS01B020) and Melbourne Business School faculty support funds. The authors would like to thank Carliss Baldwin, Roger Bohn, Andy Boynton, Raghu Garud, Eric von Hippel, Andrew King, Jeffrey Liker, Roberto Mariano, Pang Eng Fong, Ron Sanchez, Kanaan Sethuraman, Augustine Tan, Tan Wee Liang, Tsui Kai Chong, Michael Tushman, and Andrew Van de Ven for their comments on earlier drafts.

References

Abernathy, W.J. (1978) The Productivity Dilemma: Roadblock to Innovation in the Automobile Industry, Baltimore, MD: Johns Hopkins University Press.

Abernathy, W.J. and Clark, K.B. (1985) ‘Innovation: mapping the winds of creative destruction’, Research Policy, Vol. 14, pp.3–22, reprinted in Tushman, M.L. and Moore, W.L. (Eds.) (1988) Readings in the Management of Innovation, 2nd ed., HarperBusiness.

Abernathy, W.J. and Utterback, J.M. (1978) ‘Patterns of industrial innovation’, Technology Review, Vol. 50, No. 7, pp.40–47.

Ancona, D.G. and Chong, C.L. (1996) ‘Entrainment: pace, cycle, and rhythm in organizational behavior’, in L.L. Cummings and B.M. Staw (Eds.) Research in Organizational Behavior, Greenwich, CT: JAI Press, Vol. 18, pp.251–284.

Anderson, P. and Tushman, M.L. (1990) ‘Technological discontinuities and dominant designs: a cyclical model of technological change’, Administrative Science Quarterly, Vol. 35, pp.604–633.

Anderson, P. and Tushman, M.L. (1991) ‘Managing through cycles of technological change’, Research/Technology Management, May–June, pp.26–31.

Balachandra, R. (2002) Modular Design and Technological Innovation: The Case of the Hard Disk Drive, University of California San Diego, Information Storage Industry Center, Vol. 44.

Baldwin, C.Y. and Clark, K.B. (1997) ‘Managing in an age of modularity’, Harvard Business Review, Vol. 75, No. 5, pp.84–93.

Baldwin, C.Y. and Clark, K.B. (2000) Design Rules, Cambridge, MA: MIT Press.

Christensen, C.M. (1997) The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Boston, MA: Harvard Business School Press.

Clark, K.B. (1985) ‘The interaction of design hierarchies and market concepts in technological evolution’, Research Policy, Vol. 14, pp.235–251.

Corbett, B. (2002) ‘GM’s engines going modular’, Ward’s Auto World, Vol. 38, p.16.

Cusumano, M.A., Mylonadis, Y. and Rosenbloom, R.S. (1992) ‘Strategic maneuvering and mass-market dynamics: the triumph of VHS over beta’, Business History Review, Vol. 66, No. 1, pp.51–94.

D’Aveni, R.A. and Gunther, R.E. (1994) Hypercompetition: Managing the Dynamics of Strategic Maneuvering, Maxwell Macmillan Canada, Maxwell Macmillan International, New York and Toronto: The Free Press.

David, P.A. (1985) ‘Clio and the economics of QWERTY’, American Economic Association Papers and Proceedings, Vol. 75, No. 2, pp.332–337.

Dosi, G. (1988) ‘Sources, procedures, and microeconomic effects of innovation’, Journal of Economic Literature, Vol. 26, No. 4, p.1120.

Foster, R.N. (1986) ‘Timing technology transitions’, in M. Horwich (Ed.) Technology in the Modern Corporation: A Strategic Perspective, London: Pergamon.


Garud, R. and Kumaraswamy, A. (1993) ‘Changing competitive dynamics in network industries: an exploration of sun Microsystems’ open systems strategy’, Strategic Management Journal, Vol. 14, pp.351–369.

Garud, R. and Kumaraswamy, A. (1995a) ‘Coupling the technical and institutional faces of Janus in network industries’, in W.R. Scott and S. Christensen (Eds.) The Institutional Construction of Organizations: International and Longitudinal Studies, Thousand Oaks, CA: Sage, pp.226–243.

Garud, R. and Kumaraswamy, A. (1995b) ‘Technological and organizational designs for realizing economies of substitution’, Strategic Management Journal, Vol. 16, pp.93–109.

Gawer, A. and Cusumano, M.A. (2002) Platform Leadership: How Intel, Microsoft, and Cisco Drive Industry Innovation, Boston, MA: Harvard Business School Press.

Hax, A.C. and Wilde, D.L.I. (1999) ‘The delta model: adaptive management for a changing world’, Sloan Management Review, Winter, pp.11–28.

Hayes, R.H., Wheelwright, S.C. and Clark, K.B. (1988) Dynamic Manufacturing: Creating the Learning Organization, New York: Free Press.

Henderson, R. (1995) ‘Of life cycles real and imaginary: the unexpectedly long old age of optical lithography’, Research Policy, Vol. 24, No. 4, pp.631–643.

Henderson, R. and Clark, K.B. (1990) ‘Architectural innovation: the reconfiguration of existing product technologies and the failure of established firms’, Administrative Science Quarterly, Vol. 35, pp.9–31.

Jenkins, R. (1975) Images and Enterprise: Technology and the American Photographic Industry, 1939–1925, Baltimore, MD and London: The John Hopkins University Press.

Jovanovic, B. and MacDonald, G.M. (1994) ‘The life cycle of a competitive industry’, Journal of Political Economy, Vol. 102, pp.322–347.

Klepper, S. and Simons, K.L. (2000a) ‘Dominance by birthright: entry of prior radio producers and competitive ramifications in the U.S. television receiver industry’, Strategic Management Journal, Vol. 21, pp.997–1016.

Klepper, S. and Simons, K.L. (2000b) ‘The making of an oligopoly: firm survival and technological change in the evolution of the U.S. tire industry’, Journal of Political Economy, Vol. 108, pp.728–760.

Langlois, R.N. (2000) ‘Capabilities and vertical disintegration in process technology: the case of semiconductor fabrication equipment’, in N.J. Foss and P.L. Robertson (Eds.) Resources, Technology, and Strategy, London: Routledge, pp.119–206.

Langlois, R.N. and Robertson, P.L. (1992) ‘Networks and innovation in a modular system: lessons from the microcomputer and stereo component industries’, Research Policy, Vol. 21, pp.297–313.

Langlois, R.N. and Robertson, P.L. (1995) Firms, Markets, and Economic Change: A Dynamic Theory of Business Institutions, London: Routledge.

Leonard-Barton, D. (1992) ‘Core capabilities and core rigidities: a paradox in managing new product development’, Strategic Management Journal, Vol. 13, pp.111–126.

Leonard-Barton, D. (1995) Wellsprings of Knowledge: Building and Sustaining the Sources of Innovation, Boston, MA: Harvard Business School Press.

Mueller, D.C. and Tilton, J.E. (1969) ‘R&D costs as a barrier to entry’, Canadian Journal of Economics, Vol. 2, pp.570–579.

Pine, B.J. (1993) Mass Customization: The New Frontier in Business Competition, Boston, MA: Harvard Business School Press.

Piore, M.F. and Sabel, C.F. (1984) The Second Industrial Divide: Possibilities for Prosperity, New York: Basic Books.

Rogers, E.M. (1983) Diffusion of Innovations, 3rd ed., New York: Free Press.

Rosenbloom, R.S. and Cusumano, M.A. (1987) ‘Technological pioneering and competitive advantage: the birth of the VCR industry’, California Management Review, Vol. 29, pp.68–84.


Sanchez, R. (1995) ‘Integrating technology strategy and marketing strategy’, in H. Thomas, D. O’Neal and E. Zajac (Eds.) Strategic Integration, New York: John Wiley and Sons, pp.337–363.

Sanchez, R. (1999) ‘Modular architectures in the marketing process’, Special Issue, Journal of Marketing, Vol. 63, pp.92–111.

Sanchez, R. (2000a) ‘Modular architectures, knowledge assets, and organizational learning: new management processes for product creation’, Int. J. Technology Management, Vol. 19, No. 6, pp.610–629.

Sanchez, R. (2000b) ‘Product and process architectures in the management of knowledge resources’, in N.J. Foss and P.L. Robertson (Eds.) Resources, Technology and Strategy: Explorations in the Resource-Based Perspective, London and New York: Routledge, pp.100–122.

Sanchez, R. (2001) ‘Product, process, and knowledge architectures in organizational competence’, in R. Sanchez (Ed.) Knowledge Management and Organizational Competence, Oxford: Oxford University Press, pp.227–250.

Sanchez, R. (2004) ‘Creating modular platforms for strategic flexibility’, Design Management Review, Vol. 15, Winter, pp.58–67.

Sanchez, R. (2006) ‘Integrating design into strategic management processes’, Design Management Review, Fall, pp.10–17.

Sanchez, R. and Collins, R.P. (2001) ‘Competing and learning in modular markets’, Long Range Planning, Vol. 34, No. 6, pp.645–667.

Sanchez, R. and Heene, A. (2004) The New Strategic Management: Organization, Competition, and Competence (Textbook), New York and Chichester: John Wiley & Sons.

Sanchez, R. and Mahoney, J. (1996) ‘Modularity, flexibility, and knowledge management in product and organization design’, Strategic Management Journal, Vol. 17, Winter Special Issue, pp.63–76.

Sanderson, S.W. and Uzumeri, V. (1997) Managing Product Families, Chicago, IL: Richard D. Irwin.

Saxenian, A. (1994) Regional Advantage: Culture and Competition in Silicon Valley and Route 128, Cambridge, MA: Harvard University Press.

Schilling, M. (2000) ‘Toward a general modular systems theory and its application to interfirm product modularity’, Academy of Management Review, Vol. 25, pp.312–334.

Schilling, M.A. and Steensma, H.K. (2001) ‘The use of modular organisational forms: an industry-level analysis’, Academy of Management Journal, Vol. 44, No. 6, pp.1149–1168.

Shirouzu, N. (2003) ‘Ford may broaden its hybrids with an offering from Volvo’, The Wall Street Journal Europe, p.A5.

Simon, H.A. (1981) The Sciences of the Artificial, 2nd ed., Cambridge, MA: MIT Press.

Sinclair, G., Klepper, S. and Cohen, W. (2000) ‘What’s experience got to do with it? Sources of cost reduction in a large specialty chemicals producer’, Management Science, Vol. 46, pp.28–45.

Teece, D.E. (1988) ‘Profiting from technological innovation: implications for integration, collaboration, licensing, and public policy’, in M.L. Tushman and W.L. Moore (Eds.) Readings in the Management of Innovation, Harper Business, pp.621–646.

Truffer, B., Cebon, P.B., Dürrenberger, G., Jaeger, C., Rudel, R. and Rothen, S. (1998) ‘Innovative responses in the face of global climate change’, in P. Cebon, U. Dahinden, H. Davies, D. Imboden and C. Jaeger (Eds.) Views from the Alps: Regional Perspectives on Climate Change, Cambridge, MA: MIT Press, pp.351–434.

Tushman, M. and Rosenkopf, L. (1992) ‘Organisational determinants of technological change’, in L.L. Cummings and B.M. Staw (Eds.) Research in Organizational Behavior, Vol. 14, pp.311–347.


Tushman, M.L. and Anderson, P. (1986) ‘Technological discontinuities and organizational environments’, Administrative Science Quarterly, Vol. 31, pp.439–465.

Tushman, M.L. and Murmann, J.P. (1998) ‘Dominant designs, technology cycles, and organisational outcomes’, in L.L. Cummings and B.M. Staw (Eds.) Research in Organisational Behavior, Greenwich, CT: JAI Press, Vol. 20, pp.231–266.

Urban, G.L. and Star, S.H. (1991) Advanced Marketing Strategy, Englewood Cliffs, NJ: Prentice-Hall International.

Utterback, J.M. (1994) Mastering the Dynamics of Innovation: How Companies Can Seize Opportunities in the Face of Technological Change, Boston, MA: Harvard Business School Press.

Utterback, J.M. and Suarez, F.F. (1993) ‘Innovation, competition, and industry structure’, Research Policy, Vol. 22, No. 1, pp.1–21.

Victor, B. and Boynton, A.C. (1998) Invented Here: Maximizing Your Organization’s Internal Growth and Profitability, Boston, MA: Harvard Business School Press.

Von Hippel, E. (1998) ‘Economics of product development by users: the impact of “sticky” local information’, Management Science, Vol. 44, No. 5, pp.629–644.

Waurzyniak, P. (2003) ‘Ford’s flexible push’, Manufacturing Engineering, Vol. 131, p.47.

Weitz, B.A. and Wensley, R. (1988) Readings in Strategic Marketing, New York: Dryden Press.

Whitney, D.E. (1996) ‘Why mechanical design will never be like VLSI design’, Research in Engineering Design, Vol. 8, pp.125–138.

Notes

1 This definition has high heuristic value, but surprisingly little analytical value. For instance, while we think of a printer as being a ‘product’, a printer has very limited use unless attached to a computer.

2 Note that the term ‘architectural innovation’ has two meanings within the literature. In this case, it refers to the creation of a new industry. For most of this article, as previously discussed, an architectural innovation refers to a change in the relationship between the modules in a product.

3 See http://www.usdoj.gov/atr/cases/ms_index.htm.

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