Technology Evolution and Demand Heterogeneity: Implications for product and process innovation Ron Adner INSEAD Boulevard de Constance 77350 Fontainbleau Cedex, France firstname.lastname@example.org Daniel Levinthal University of Pennsylvania, The Wharton School 2000 Steinberg Dietrich Hall Philadelphia, PA 19104 email@example.com DRAFT – September 1999We thank George Day, Connie Helfat, John Kimberly, Bruce Kogut, Hans Pennings, ChristopheVan Den Bulte, and Sid Winter as well as seminar participants at the University of Pennsylvania, Insead, the University of Michigan, and London Business School. We thank the Hunstman Center for Emerging Technology at the University of Pennsylvania for funding.
2 Abstract While research on the evolution of new technologies has emphasized the “supply side”activities of firms, there is growing recognition that the external demand environment canexercise significant influence over these activities. This paper presents a demand-based view oftechnology evolution that is focused on the interaction between technology development and thedemand environment in which the technology is ultimately evaluated. We develop a formal model that explicitly considers the influence of heterogeneity inmarket demand – the presence of consumers with different needs and requirements – on firms’innovation choices. The model is analyzed using computer simulation. The model is used toexamine the dynamics of product and process innovation (Utterback and Abernathy, 1975). Theanalysis reveals that demand heterogeneity offers an alternative to supply-side explanations of thetechnology life cycle. Further, by considering the possibility of technologically satisfiedconsumers, the model also suggests a rationale for a new stage in the technology life cyclecharacterized by increasing performance at a stable price. This stage has not yet been treatedformally in the literature, but is increasingly evident in digital and information basedtechnologies.
31. Introduction The challenge of understanding the dynamics of technological development has long beena concern of the management field. Two dominant approaches inform the discussion oftechnological change: one suggests that innovation is driven by the external requirements of themarket (Schmookler, 1966), while the other views the activities and internal capabilities of firmsas the primary drivers of innovation (Dosi, 1982). Taken in isolation, each approach highlightskey aspects of technological development but, as many have argued, the greatest insight derivesfrom their joint consideration (Mowery and Rosenberg, 1979). Despite this call for balance, by far the larger portion of work on technological change isconcentrated on the ‘supply-side’ dynamics --- whether at the macro level of technologicaltrajectories (Dosi, 1982; Sahal, 1985) or the path dependent nature of individual firm capabilities(Helfat, 1996). Relatively under explored in these discussions of innovation is the effect of thedemand environment on the development and evolution of technology (though see Clark, 1985;von Hippel, 1988; Christensen, 1997 for important exceptions). Technical developments are afunction of the opportunity structure that firms perceive. This opportunity structure, in turn, is afunction of the firm’s current set of capabilities (Dosi, 1982; Neslon and Winter, 1982; Cohenand Levinthal, 1989), the inherent possibilities offered by the alternative technologies (Sahal,1985), and the market context in which the firm operates (Christensen, 1997). We develop a demand-based view of technology evolution that is focused on theinteraction between technology development and the demand environment in which thetechnology is ultimately evaluated. A critical element in our framework is the inherent diversitythat underlies the notion of ‘market’ demand. The latent set of consumers may have widely
4differing needs and requirements. We characterize consumers by two attributes: the minimumperformance requirements that a product technology must satisfy in order for the consumer to bewilling to consider purchasing a good, and the consumer’s willingness to pay for productperformance. We examine the evolution of a technology whose development is locallyconstrained, and in turn path dependent, but globally unconstrained regarding the absolute, orasymptotic, limits to its progress. The model is used to examine the dynamics of product and process developmentthroughout the technology life cycle. Currently, the pattern of product and process innovation isunderstood as the result of the emergence of dominant designs (Utterback and Abernathy, 1978;Anderson and Tushman, 1990) and of shifting appropriability regimes (Cohen and Klepper,1996). In contrast, we suggest that this pattern may be an outcome of locally adaptive behavior offirms in a heterogeneous demand environment. In a heterogeneous demand environment, early technological development is motivatedby the drive to meet market requirements. Depending on the initial functionality and cost of thetechnology, this may lead to an early emphasis on product technology to enhance thefunctionality of the technology in order to meet the demand requirements of users or on processtechnology to reduce the price to a level that corresponds to consumers’ willingness to pay. Inlater stages of development, when the technology has surpassed market requirements, technicaldevelopments are driven by the desires of competitive firms to maximize their profits in the faceof ‘technologically satisfied’ consumers. This latter stage of development suggested by the model implies the existence of a newstage in the technology life cycle characterized by increasing performance at a relatively stableproduct price. This stage has not yet been treated in the literature, but is increasingly evident in
5electronic based product technologies. As firms operating in these industries benefit from thebiannual doubling of performance predicted by Moore’s Law (The Economist, 1997), theirtechnology management challenge shifts from the focused pursuit of performance improvementto include the ways in which these improvements are valued and applied by their customers. Insettings in which the rate of technological improvement outpaces the demand for thisimprovement, consumers’ marginal utility from performance increases plays a critical role inshaping firms’ pricing and development choices. Consider the price performance histories of videocassette recorders and personalcomputers shown in Figures 1 and 2. A striking similarity between them is the stability ofproduct price in the later stages of product evolution, even as their objective performancecontinues to increase. While computing power more than quadrupled between 1992 and 1996,the average unit price for a personal computer remained stable at around $2000 throughout theperiod (Computer Intelligence Info Corp, 1996).1 Similarly, VCR prices remained relativelystable from 1990 to 1997, even as new features were introduced yearly (Consumer Reports,1990-97). Thus, rather than price increasing toreflect a premium that suppliers can extract for the greater functionality delivered, or stablefunctionality at decreasing prices, we observe functionality increases at stable prices. Similarhistories could be compiled for fax machines, modems, copiers, and numerous other productswhose core technology are digital logic circuits. The remainder of the paper is structured as follows. We first explore existing approachesto the technology life cycle and the treatment of market demand in the literature on technologyevolution. We then develop the conceptual framework of demand heterogeneity. In section 4,
6the model is analyzed using a computer simulation. We conclude by examining the distinctiveimplications that derive from a view of technological development that is informed by this moredetailed consideration of market demand.2. Dynamics of Product and Product Innovation The technology life cycle describes the dynamics of product and process innovation andhas long held a central place in the literature on technology management (Meuller and Tilton,1969; Utterback and Abernathy, 1975; Clark, 1985; Utterback, 1994; Klepper, 1996). Thepattern that has been widely described is illustrated in Figure 3. Porter (1983:22) provides asuccinct summary of the dominant explanation for this behavior: Initially, . . . product design is fluid, and substantial product variety is present. Product innovation is the dominant mode of innovation and aims primarily at improving product performance. Successive product innovations ultimately yield a “dominant design” where the optimal product configuration is reached. Process innovation is initially minor in significance, and early production processes are characterized by small scale, flexibility, and high labor skill levels. As product design stabilizes, increasingly automated production methods are employed and process innovation to lower costs takes over as the dominant innovation mode. Ultimately, innovation of both types begins to slow down. The primary focus of the dominant design approach is on the supply side coordination ofuncertainty reduction that allows for investment in specialized production equipment. While thisapproach recognizes that consumer requirements influence the establishment of a dominantdesign, it is silent on the role of demand on post-dominant design developments. Several of theassumptions underlying the dominant design explanation are problematic. First is theassumption of a clear ordering between product and process innovation which posits that firmswill tend to ignore the production process and control of costs until the product design has been1 This price has dropped significantly since 1997 with the introduction of $1000 desktop computers. The implication
7fixed (DeBresson and Townsend, 1985). While design improvements are a primary driver ofmarket acceptance, in many instances cost savings provide the critical motivation fortechnological substitution and are therefore an early focus of innovative effort. A secondproblem is the assumption of the depletion of product improvement opportunities. Thegeneralizability of claims of diminishing technological opportunities, however, is refuted inseveral studies that closely examine this issue (e.g. Christensen, 1992; Henderson, 1995). An alternative explanation for the technology life cycle (Cohen and Klepper,) suggeststhat the shift in innovative focus from product to process development is driven by changes in theability of innovating firms to appropriate returns on their investments in innovation. Accordingto this perspective, the value of process innovation is proportional to the level of output producedby a given firm. Thus, as an industry matures and firms get bigger, firms have increasingincentives to pursue process innovations. In contrast, since returns to product innovations arerelated to the acquisition of new customers rather than the magnitude of the existing customerbase, the relative return to product innovation declines over time. This scale-appropriability approach predicts the rise of process innovation withoutplacing exogenous limits on opportunities for product innovation or interdependence betweeninnovation regimes. However, it does not address the continued pursuit of product innovationthat is exhibited in industries such as consumer electronics and computers, which are dominatedby the large firms that are predicted to shy away from product innovation. Indeed, in reviewingthe patent counts compiled by Gort and Klepper (1982) for over 46 product classes, Klepperhimself states that “neither series reflects the decline over time in product innovation conjecturedin the PLC [product life cycle]...” (1997: 167).of this change for the arguments presented here are discussed later in the paper.
8 Common to both the dominant design and the scale-appropriability approaches is a focuson the dynamics of supply without an explicit examination of the demand context in which theinnovating firm operates. We develop a finer grained consideration of the demand context andhow this can inform our understanding of the evolution of technology in general, and thetechnology life cycle in particular.3. Heterogeneity and Markets Demand is not homogenous, rather it varies within a market comprised of individualconsumers. This assertion is not novel. Indeed, it is present in any consideration of strategy thatdifferentiates between niche segments and mainstream markets (Kotler, 1991; Porter, 1980).Consumers can be distinguished by their preference structures and the relative value they placeon different product attributes. A key element in such a preference structure in the context ofemerging technologies is the minimum performance threshold that a product must reach if it is tobe of value to a given consumer. The focus in this analysis is heterogeneity in the minimum performance threshold amongconsumers and in consumers’ willingness to pay for products that meet this performancethreshold.Thresholds The notion of heterogeneous thresholds is well established in a variety of literaturesincluding consumer choice (McFadden, 1986; Green and Wind, 1973), the diffusion ofinnovation (Stoneman, 1987; Thirtle and Ruttan, 1987), and is embodied in the notion ofreservation prices in microeconomic models (Varian, 1978). The basic notion common to these
9applications is that the adoption of a technology or the purchase of a good is a discrete decisionthat is prompted by some threshold of “attractiveness” being surpassed. We define a consumer’s functionality threshold as the minimum objective performance(independent of price) that a given product must deliver in order for the consumer to consider it.Associated with this functionality threshold is a consumer’s net utility threshold which specifiesthe highest price that a consumer is willing to pay for a product that just satisfies his or herfunctionality requirements. The value of considering the two thresholds jointly, rather thancombining them both into a single construct, is that it allows for an explicit consideration oftechnology improvements in both performance and price. A functionality threshold specifies the performance level below which a consumer willnot accept a product, regardless of its price. A product that falls below a given consumer’sfunctionality threshold is, for that consumer, ‘junk’ and would not be accepted at any positiveprice. The same product, however, may well be acceptable to a consumer with a differentfunctionality threshold. Functionality thresholds are determined, in part, by inherent task requirements and, inpart, by context. Thus, a machinist drilling high precision parts cannot make use of a drill presswith loose tolerances, no matter how low its selling price, because such a machine is not able tosupport the intended application. Alternatively, functionality requirements can be externallyimposed, by the demands of downstream customers (e.g., producers of goods for the luxurymarket will need higher quality materials than those producing for the economy market) or byexternally imposed regulations (e.g., electricity producers in California require cleaner generatingstations than producers in North Dakota in order to be certified for operation).
10 Net utility thresholds capture the interaction of product performance and price. The netutility reflects the highest price a consumer is willing to pay for a product that just meets his orher requirements. Consumers with the same functionality threshold may have different net utilitythresholds. Variation in willingness to pay may be driven by differences in budget constraints,but more importantly, particularly in the context of firms, by non-budgetary differences as well. Consumers may differ in the value they derive from the product for a number of reasons.Consumers may differ in their ability to exploit the product as a result of heterogeneity in internalresources and capabilities, or human capital. For instance, a skilled programmer may be able toderive more benefit from a given computer system than a less skilled one. Alternatively,differences in net utility thresholds may stem from the scale at which the buyer can apply theproduct. A firm that can apply the product toward the production of a good that it can then sell toa large downstream customer base would be willing to pay more for the product than a potentialbuyer with a smaller customer base. Finally, differences in willingness to pay may reflectvariation in the availability and presence of a substitute product or service. A firm that haspreviously invested in a substitute good will benefit from the new product only to the extent thatthe product provides an improvement relative to the existing substitute; alternatively, a similarfirm, not in possession of a substitute, will value the product on the basis of the absolute benefitit provides.Diminishing Returns While consumers have a minimum threshold for acceptable performance, there is noanalogous boundary that specifies a maximum limit to the functionality that a consumer wouldbe willing to accept. At the same time, it is reasonable to assume that there is diminishing
11marginal utility to increases in functionality (Meyer and Johnson, 1995). Correspondingly, it isreasonable to assume that consumers show a positive, but decreasing, willingness to pay forimprovements beyond their requirements. Thus, as consumer requirements are exceeded, their willingness to pay for improvementwill become increasingly small to the point that firms will be unable to extract any meaningfulpremium for further improvement. However, even if consumers place little value onperformance differences at sufficiently high absolute levels of functionality, they will still, allelse being equal, choose the more advanced product. As a result, in a competitive context thisresponsiveness to functionality improvements forces firms to continue to enhance functionalityeven when such enhancements have little effect on consumers’ willingness to pay.Dynamics of Technology in Heterogeneous Markets The presence of different threshold levels for both functionality and net utility impliesthat consumers will vary in the degree to which a product technology at a given state is capableof satisfying their requirements. In turn, there will be variation in the type, and amount, ofdevelopment that is required before the product becomes relevant to a given consumer. Whilemodels of the diffusion of innovation explicitly consider demand heterogeneity in explaining thedifferences in adoption rates and decisions, they tend to focus on the diffusion of a fixedinnovation (Brown, 1981; Rogers 1994), and thus fail to consider the interaction betweenchanges in the innovation that result from further development and consumers’ adoptiondecisions (Thirtle and Ruttan, 1989; Rogers, 1994; Reingenum, 1989).22 Those few models that do examine a changing innovation (Stoneman, 1987; Jensen, 1982) do so in the context oftwo period models which do not really speak to an evolutionary pattern, and address product changes of only onetype (either price decrease or quality improvement) but not both simultaneously.
12 In mature markets, functionality and price are often confounded as consumers with high(low) functionality requirements generally buy more (less) expensive products. However,functionality and price need not be coupled. In markets for emerging technologies, potentialconsumers with a high willingness to pay for the product who have, at the same time, lowfunctionality requirements, play an important role in both the development and adoption of aninnovation. The military has been the quintessential example of this sort of early purchaser whois willing to cover development costs (Klein, 1977). Early in a technology’s development, highperformance products may not be available, not because of the absence of willing purchasers, butbecause of still unsurmounted difficulties with the technology itself (e.g. consider the case ofsuperconductors or solar energy). As such, early consumers may also be individuals who arecharacterized by their low-functionality requirements, or, their ability to derive unusual benefitfrom products of objectively low functionality. For instance, the early market for xerography was comprised of firms that made originalmaster plates for offset printing. Because these firms were able to integrate the machine into aspecialized activity, they were able to benefit from it at a time when other potential consumersfound them unacceptably complex and unreliable. It was only after extensive furtherdevelopment that Xerox machines were able to satisfy the much higher functionality demands ofthe mainstream office market (Dessauer, 1971). In such cases, finding consumers who arewilling to pay a high price for a relatively crude product maybe critical to firms’ ability to engage in the development effort. In the context of emerging technologies, firms do not have the option of positioningthemselves anywhere in the attribute-price space. This contrasts with the spirit of the classicsegment-target-position (STP) marketing paradigm (Kotler, 1991), in which firms are told to first
13segment the market, then examine the characteristics of consumers in these individual segmentsand then consider ways of tailoring the product to meet segment specific needs. Such anapproach is appropriate when firms can manipulate product attributes at will, as in typicalmarketing examples of varying sweetness, saltiness, and tartness in a food product. When the manipulation involves challenging performance attributes which cannot beeasily or quickly changed, such as reliability, size, and speed, this tailoring approach becomesless managerially tractable. In such situations, an approach which considers the interaction ofconsumer needs with both short and long term technological possibilities may be moreinformative. We explore the path-dependent development of technology, where path dependenceresults from both the “supply-side” constraints of technical change at any moment in time, andthe history of feedback from the demand contexts in which the technology has been applied.4. Model Structure The model structure has two basic components -- a characterization of consumers andconsumer preferences which comprises the demand environment, and a mechanism by whichproducts move through this market space. The market space is defined by a functionalitydimension and a price dimension. In every period, firms make development decisions that affectthe location of the product technology in this space; consumers, in turn, respond to the productofferings by either purchasing or not a unit quantity of the product. It is assumed that consumers engage in repeat purchasing behavior such that the entirepopulation of consumers considers making a purchase in every period and that consumer
14preferences are stable over time.3 Although preferences are stable, consumer purchase decisionsvary as product performance and price vary over time. Consumers are assumed to be wellinformed4, in that they have accurate information about product performance each period. Firmsare assumed to maximize current period profits.5 In the model, consumers are characterized by two basic factors. The first factor, Fi0 ,specifies individual i’s minimum functionality requirement. The second factor, Ui0 , specifiesconsumer i’s minimum utility requirement, which determines the price, Pi0, that consumer iwould be willing to pay for a minimally acceptable product. The population of consumers isspecified by independently drawing values of Fi0 and Ui0 from a uniform distribution of sufficientrange such that multiple innovation attempts are required to reach all consumers in the market.The functional benefit, Bij, that consumer i derives from product j is determined by thefunctionality offered by the product in excess of the consumer’s minimum functionalitythreshold:3 This situation is characteristic of a market for durable goods with regular entry of consumers, such as the entry ofsome fixed number of new households into an economy every year. Alternatively, this type of repeat purchasingbehavior could characterize a fixed population purchasing a non-durable good. The assumption of some sort ofcontinuing purchase, whether through a renewing population of single good purchasers or a fixed population ofrepeat purchasers, is important to the model in that it is the potential of attracting existing as well as new customersthat drives firms to innovate. As a result, a single purchase, fixed population model would not generate the behaviorobserved in the last phase of the current model because, in effect, such a model stipulates the ‘end of history’ afterfull penetration. A less extreme model, however, such as one in which goods face obsolescence after some numberof periods would generate incentives for continued innovation on the part of firms as they compete for whicheverconsumers are active in the market in each period.4 The current model makes the simplifying assumption that consumers are perfectly informed regarding productperformance. Because the interest is in the qualitative pattern of behavior, consumer uncertainty would be a relevantfactor if it were to affect firms’ development decisions in a systematic way. With no compelling reason to biasconsumers’ assessment of product performance in either the positive or negative direction, the error in theassessment would have to be modeled as a symmetric distribution around the true value. Such an error, whileaffecting the absolute values associated with the observed outcomes, would not affect the qualitative nature of theresults and would thus only be an unnecessary complication.5 This can be thought of as price skimming behavior (Kotler, 1991) and is the same assumption made in Klepper(1996).
15 Fj – Foi + 1 if Fj – Foi ≥ 0(1) Bi(Fj) = 0 otherwise The utility, Uij, that consumer i derives from product j is specified as a Cobb-Douglasutility function which trades off price and functionality as6: α 1-α(2) Ui(Fj , Pj) = Bi(Fj) (1/Pi) , where 0 < α < 1. Consumers will reject any product that does not meet both their functionality and utilityrequirements, such that Bi ≥ 1, and Uij ≥ Ui0. Thus, Pi0, is the highest price a consumer will bewilling to pay for a product that just satisfies his or her functionality requirement, (i.e., Bij = 1)and is characterized as:(3) Pio = ( Uio )1/(α - 1) As discussed above, consumers value functionality improvements beyond their thresholdrequirements, ∂Uij/∂Bij > 0, but at a decreasing rate, ∂2Uij/∂Bij2 < 0. This property of diminishingreturns to improvements holds for α values below 0.5. From the utility function we solve for Pij,the maximum price a consumer would be willing to pay for a product that meets his or herfunctionality requirements, as7: α/ Pij = Pio ( Bi(Fj) ) 1-α(4)6 Note that [logU]/(1-α) = α/(1-α)logB – logP. Hence, our model is a monotonic transformation of the utilityfunction of standard vertical differentiation models, where U=KB - P (Tirole, 1988). The current model differs fromthe standard model in that it introduces minimum thresholds for functionality and diminishing returns to functionalimprovements.7 To find Pij we identify the product j such that Ui (Fj , Pj ) = Uo.
16 Given a choice among a set of acceptable products, a consumer will select the productthat maximizes his or her utility. In every period, the entire population of consumers is exposedto the available products and each consumer selects his or her own best choice.Evolution of Product Technology Products are represented by their functional performance and by a cost of production.Following the characterization used in previous analytical models (Cohen and Klepper, 1996;Klepper, 1996), the effect of product and process innovations is reflected in changes in theproduct’s functional performance and cost. Product innovation enhances functionality by a fixedamount, Fprod, and leads to a fixed production cost increase, Cprod. Thus, a product innovationaffects product j in the following manner: (5) Fj, t+1 = Fj,t + Fprod (6) Cj, t+1 = Cj,t + Cprod Process innovation leaves product functionality unchanged, while lowering the cost ofproduction by a constant percentage, ∆c. Thus, a process innovation affects product j as follows: (7) Fj,t+1 = Fj,t (8) Cj, t+1 = Cj,t (1 - ∆c) The geometric decrease in cost due to process innovation has an empirical basis, asdiscussed in the learning curve literature (Boston Consulting Group, 1972). On the productinnovation side, modeling product improvement as an arithmetic increase implies that the rate atwhich firms can pursue improvement is fixed --- firms can’t engage in time compression byexecuting two innovations in a single period.
17 In reality, the rate of innovative improvement is a function of the resources devoted toinnovation, as well as technological possibilities. The S-curve literature (Foster, 1986) showsthat, at later stages of development, increasingly larger resource investments are required tomaintain a constant rate of performance improvement. Often, these investments are justified bythe (expected) growth of the market in which the innovations are deployed. Because the purposeof this model is to examine the effects of demand heterogeneity on technology development, andnot the technological limits to development themselves, the simplifying assumption of linearimprovements is used. In every period firms can choose to pursue a mix of product and process innovation or toforgo innovative activity. The current state of the product is determined by the entire history ofdevelopment activity and is therefore path dependent. Innovative outcomes are cumulative andtherefore product cost and functionality cannot be manipulated instantaneously. In the model, firms choose innovative activity on the basis of local search. Firms areassumed to be able to predict consumer reaction to each incremental change to the product (i.e.development outcomes that will ensue within a single product or process innovation). However,firms do not make evaluations of potential consumer demand further away from their currentproduct offering. We explore behavior that corresponds to a symmetric Nash Equilibrium of a series ofone-shot games among firms with firms choosing innovation activity and price so as to maximizetheir own payoff assuming that their competitors’ behavior remains constant. Thus, firms aremodeled as making profit-maximizing choices, but based only on next period’s payoff. Finally,we make the simplifying assumption that firms’ initial product offerings are the same. 88 In the current modeling effort, we are trying to understand the effect of consumer heterogeneity on the pattern of
18 The model is analyzed under two different product pricing regimes. The first pricingregime, ‘market pricing’, posits that firms are fully informed regarding consumers’ responses topricing and that the firms can, given their product’s performance and production cost, determinethe price point which will yield them the greatest profit. The second pricing regime, ‘heuristicpricing’, assumes that firms price at a fixed markup over costs. This simplified pricing structure,while clearly non-optimizing, is the most common form of pricing rule employed by businessestoday (Monroe, 1990: 143). The model results, discussed below , are remarkable for their robustness given that thesetwo pricing regimes represent polar cases of firm pricing decisions. While the choice of pricingregime affects the absolute values of the simulation results, the pattern of product and processinnovation behaviors that is the focus of this analysis is consistent for both settings.9 To facilitatethe exposition of the results, we present figures from the heuristic pricing case.5. Analysis The model is analyzed using a computer simulation programmed in Pascal. The firstprocedures of the simulation initialize both the population of consumers and the initialcharacteristics of the product technologies. The population of consumers is composed of onehundred individuals, with each individual characterized by a minimum functionality requirementand a minimum utility level. The values of individual consumers’ Fi0 are uniformly distributedfrom 1 to 20 and Pi0 values range from 1 to 7. The range of consumers’ minimum functionalproduct and process innovation for a single technological trajectory. A separate question is how differenttechnological trajectories may compete with one another.9 Because the market pricing regime allows for behavior that is more sensitive to immediate market opportunities(i.e., the particular preferences among consumers considering purchasing the product), the price patterns displaygreater variance than those observed under the heuristic pricing. The relative pattern of product and processinnovation, however, holds true for both cases.
19thresholds is such that approximately twenty product innovation attempts are necessary to spanthe distance between the minimum requirements of the least and most demanding customer in themarket. Product technologies are introduced to the market at different points of functionaldevelopment. We characterize two different settings of product entry. One is a “new to the worldtechnology”. This is the typical setting examined in technology life cycle studies in which theinitial product technology is functionally crude. With this initial setting, we observe theconventional technology life cycle in which product development is initially emphasized with alater shift in emphasis towards process innovation. The other setting is a “new to the market” technology. Product technologies can beintroduced in forms that are, relative to market demands, functionally advanced. This situation ischaracteristic of product technologies that are being modified for application in a new tasksetting, after having been previously introduced to other application domains. In this setting, theinitial emphasis is on process innovations in order to lower the costs of the product sufficiently topenetrate larger segments of the latent market. “New to the world” technologies are introduced at an initial performance level of 2 andan initial cost of 4. ‘New to the market’ technologies are introduced at an initial cost of 10 and aninitial performance of 15. For all the runs shown, α = 0.2, Cprod = 0.2, Fprod = 1, ∆c = 0.05, andthe heuristic markup is 20 percent. The firms’ choice set for allocating development effortbetween product and process innovation is: pure product; 75% product, 25% process; 50%product and process; 25% product, 75% process; and pure process. After this initialization, the following sequence of events is repeated for one hundredperiods. First, each firm independently surveys its demand environment to determine the profit
20expectations for each possible development action. Second, the firms commit to the activity thatwill the yield highest expected profit. Third, every consumer then independently evaluates theavailable product offerings and decides whether any product satisifies their minimumfunctionality and utility requirements and, if so, what product provides them the maximum utilitylevel. Finally, market outcomes are tallied and firms experience their actual market payoffs. To test for stochastic robustness, the simulation was run fifty times with differentrandomly drawn populations. While the duration of each of the distinct phases of technologyevolution varied with each specific population draw, the relative rates of innovation followed asimilar pattern. The absolute and relative attractiveness of product and process innovation is determinedby the relationship among Fprod , Cprod, and ∆c. These variables affect the qualitative results in astraightforward manner (increasing Fprod or decreasing Cprod makes product innovation moreattractive, while increasing ∆c makes process innovation relatively more attractive). The value ofparameter α, affects the price trends observed when in the mature demand phase (as discussedbelow). The parameters which most dramatically affected the qualitative pattern of behavior arethe initial cost and performance attributes of the product. These variables affect the early stagedynamics of how consumer thresholds are met.6. Results Three canonical phases of development activity can be identified during the course of thesimulation according to their relative rates of product and process innovation. In the first phase,which is termed attribute equalization, development actions are focused on achieving a balancebetween price and performance relative to the demands of the market. In this phase, one of the
21two innovation types is the dominant development mode. In the second phase, termed marketexpansion, development activities serve to expand market penetration through reductions inprice, and thus process innovations are dominant. Finally, in the third phase of demand maturity,innovation activity alternates between product and process innovation so that price remainsrelatively stable as product functionality increases. The phases are identified by observing inflections in product pricing behavior. Theboundary between the first and second stages is defined as the point of greatest negative changein the price slope. The boundary between the second stage and third stage is defined as the pointof greatest positive change in the price slope. A representative simulation run for new to theworld introductions isshown in Figure 4. The figures graph the levels of functional performanceand price over time. The pattern of product and process innovation is most readily observed byfollowing changes in product price, since in the case of heuristic pricing price is coupled toproduction cost and thereby directly reflects firms’ innovation choices. Price increases signal afocus on product development, while price decreases signal a focus on process development. The first phase is characterized by an increase in product price, reflecting a focus onproduct development. The second phase in which price decreases, reflecting the dominance ofprocess development begins at period 12 and ends at period 33. It is followed by the third phaseis characterizedby relative price stability in the face of performance improvements. Figure 5 depicts the dynamics of technology development for products that are introducedto the market at a relatively advanced state of product development. In this case the attributeequalization stage focuses on price reduction that not only balances the relative value of priceand performance to meet market preferences, but at the same time also results in increasedmarket penetration. As a result, the stages of attribute equalization and market penetration are
22effectively collapsed onto one stage. The third phase, demand maturity, begins in period 23 andhas the same characteristics depicted for the case of ‘new to the world’ product technology. Examples of such ‘new to the market’ technologies are the commercialization of spacetechnology, or the ‘consumerization’ of industrial goods. The development of home videocassette recorders, which built on a related product technology developed for industrialapplications (Cusumano and Rosenbloom, 1987), falls into this category; indeed, the price-performance history presented for VCRs in Figure 2 is similar to the these simulations results.Attribute equalization Recall that for a consumer to purchase a product, the product must satisfy or exceed theconsumer’s threshold functionality and the product’s price must be such that the net utility willsatisfy or exceed the consumer’s threshold utility level. At the early stage of market penetration,the innovation effort that will yield the greatest increases in sales and profit is the one that willmeet the threshold requirements of the greatest number of current non-buyers. This attribute,whether functionality or price, will be the focus of the initial innovative efforts. The attribute equalization phase of innovative activity ends when the relative values ofmarket price and product functionality correspond to consumers’ preferences regarding thetradeoff between price and functionality. Development efforts face a tension between attractingnew customers through engaging in product development and losing satisfied customers who areunwilling to pay the higher price charged for an improved product. In the conventional setting inwhich early innovative efforts focus on product innovation, this loss of established consumersdue to price increases associated with product development is initially offset by the addition ofnew consumers with higher quality thresholds and greater revenue per product associated with
23their purchases. After a certain point, however, efforts at market penetration via productenhancements become self-defeating as large numbers of former purchasers find the new price-performance combination unattractive. Clearly, the product’s initial cost and performance will determine the dimension on whichinitial innovative efforts are directed. In the traditional technology life cycle, this initial phase isdominated by product development activity. In the new to the world case, the model predicts anearly focus on product development when the market penetration of the initial embodiment of aproduct is limited by its performance. Consider for example the market for early personalcomputers. The initial penetration of PCs was limited largely by the low functionality of theearly PCs, rather than a prohibitive price. Early automobiles also suffered from an initialperformance crisis: a car that breaks down every fifteen miles is no substitute for a horse,regardless of price. In contrast, for product technologies that are introduced to the market at a functionalitylevel that is high compared to their affordability, price is the primary barrier to marketpenetration and, as a result, process development is the primary focus of early developmentefforts. Commercial applications of space technologies provide a clear example of suchproducts. For example, the critical task for the commercialization of the Global PositioningSystem was not to improve the precision of the transmitter, but rather to lower the cost of thesystem from the thousands of dollars paid by government agencies to the $500 price range atwhich commercial introduction was feasible (Pearce, 1994).
24Market penetration The next phase of innovative activity is dominated by process developments which serveto ‘fill in’ the market via price reductions. Some of these ‘fill in’ customers are formercustomers who stopped purchasing when the product became too expensive. Others are ‘bargainhunters’, consumers whose functionality thresholds are relatively high, but who are unwilling topay the high early market price. Product price is reduced until the sales increases due to lowerprice no longer offset the revenue lost per product.Demand maturity Eventually firms’ development efforts yield a product whose functionality satisfies thecore of the market to the point where performance improvements no longer attract a pricepremium from a significant part of the market. At this point, consumers’ diminished valuation ofperformance improvements would seem to reduce the appeal of product innovation. However,despite the reduction in willingness to pay for improvement on the part of consumers, firms,driven by competitive pressures, engage in significant levels of product innovation. Although the market as a whole is ‘satiated’ with the existing quality of product offerings,in that the prospect of incremental performance improvements will not significantly affect buyingbehavior with regards to either willingness to pay or number of active buyers, individual firmsstill perceive opportunities for market share gains through offering consumers better products.Because each firm evaluates its development options with regards to it’s rival’s existing ratherthan potential product, each firm believes that market share gains will ensue if it offers a betterproduct than was previously available to consumers. In the context of the model, a superior
25product is one of equivalent performance at a lower price or of higher performance at a similarprice, than the products offered in the previous period. Consider the firm’s opportunities at the point at which consumer willingness to pay forperformance improvement has diminished. If the firm chooses a to focus on product innovation,its production costs will increase. As it attempts to pass these increases onto the market,consumers at the low end will begin to drop out. As the market shrinks, the gains from higherproduct prices becomes insufficient to offset the loss of buyers and process innovation becomesthe more attractive alternative. If the firm chooses to focus on process innovation and therebyreduces its production costs, competitive pressures will force the firm to pass some of thesesavings on to consumers. Successive process innovations lead to reductions in both the cost andthe price of the product, eventually leading to pressure on profit levels and, in turn, increasingthe attractiveness of product innovation. Thus, at the point at which consumer willingness to pay for performance improvements isrelatively low, innovating firms face a tension between the loss of revenue due to decreases inunit volume associated with the higher prices that result from product development efforts andthe loss of revenue due to the price decreases associated with process development. In themodel, firms manage this tension by choosing to balance product and process innovation ,keeping product price in a critical range that corresponds to the way that the aggregate markettrades off the value of product performance and price. This tradeoff is determined by the valueof the parameter α in consumers’ utility function. Lower (higher) values of α lead to a lower(higher) price level at maturity.1010 Since α effectively represents consumers’ preference for the product relative to all other uses for money (i.e. allother goods and services in the economy), its empirical value is likely to be quite low.
26 At this stage, product development becomes a way of maintaining product price ratherthan satisfying the needs of new customers. As a result of competition in the face of maturedemand product price remains relatively stable while product functionality experiences a steadyrate of improvement. The competitive dynamics underlying this third stage can be further illustrated byconsidering the observed development pattern under the case of a monopolist firm. Figure 6illustrates representative results under a monopolist regime for a new to the world productintroduction. Because the monopolist firm is not forced to offer consumers a more attractiveproduct than its rival, it need only offer a product that satisfies consumers’ minimumrequirements. As such, the demand landscape which the monopolist faces is a rather differentone than that faced by a competitive firm leaving the monopolist freer to initially exploitwillingness to pay higher prices for higher performance among higher end consumers.Significantly, however, when demand matures the monopolist ceases to innovate entirely, and thesustained improvement observed under the competitive regime is absent. Indeed, for the caseshown in Figure 6 all innovative activity ends in period 50. The early phases of technology development are motivated by the drive to meet marketrequirements. In contrast, after the onset of demand maturity, development is driven bycompetition among firms for the same consumers. When there is only one firm in the market,there is no contention for its consumers; in the absence of a rival product offering the consumerswill stay with the firm. Therefore when innovation ceases to expand the market and consumers’willingness to pay for improvements declines, the monopolist ceases innovation activity andconsumers are faced with a static product. This qualitative pattern holds for both pricing regimes.
27 Firms in competitive situations seek to differentiate themselves from rivals in order togain market advantage (Porter, 1980). This need for differentiation continues as a function ofrivalry, independently of the state of consumer satisfaction. The question still remains as to whyproducers do not offer lower priced products at the functionality level at which consumerwillingness to pay is largely exhausted, rather than improving functionality beyond this point. Price reductions are attractive only to the extent that they attract new customers. After acertain point, the returns to market expansion via greater price reduction are outweighed by theforegone revenues from existing customers. As the product price falls below consumers’willingness to pay, the consumers’ purchasing behavior is not changed. There is simply anincrease in consumer surplus. Certainly price competition is a powerful driver of firm behavior,but to the extent that other avenues for attracting and retaining customers are available to firms,price competition will be attenuated. The issue of satisfied demand raises the related question of why consumers wouldpurchase advanced products that are clearly beyond their needs rather than holding out for moreprimitive products with lower prices. Ultimately, what the market dynamics generate isconsumer surplus in the form of ‘luxurious bargains’. As long as the magnitude of theincremental quality improvements that derive from product development offset any associatedprice change, there will be a net increase in consumer surplus and the luxury of increasedfunctionality will indeed be a bargain. Another issue, outside the structure of the model, is the prospect that consumers’minimum functional requirements may rise with time. Such a dynamic would necessitate the
28purchase of increasingly advanced products. Changes in minimum thresholds can result fromchanging expectations or from changing objective requirements.11 The sudden appearance of sub $1000 personal computers in 1997 presents a different sortof complication (Ramstad, 1997) – the emergence of a new application domain, the Internet,which (1) posed a lower performance requiremennt than the existing competitive threshold; and(2) introduced a large number of new price sensitive consumers into the market (purchasers of2nd computers and first time lower income buyers spurred by announcements of the importance totheir future of ‘getting wired’.6. Discussion The model developed in this essay explores the interaction of innovation choices andconsumer demand during the course of a technology’s development. It shows that considerationof demand offers an alternative to supply side explanations of the technology life cycle. Early ina technology’s development, innovation is guided by a drive to meet market requirements. In thelater stages of development, after the market’s price and performance requirements are met,innovation is driven by competition among suppliers faced with ‘technologically satisfied’consumers. Under conventional (‘new to the world’) initial conditions, the demand based modelgenerates behaviors that are highly consistent with those documented in technology life cyclestudies (e.g., Utterback and Abernathy, 1978; DeBresson and Lampel, 1985). Both approaches11 The quintessential example of evolving minimum thresholds is found in the context of personal computers. Theminimum requirements of computers are continually ratcheted up as new software programs become moredemanding of the technical requirements of the machines. The introduction of a new standard platform such asWindows95, which provides consumers with the motivation to demand more powerful hardware, demonstrates howthe presence of complementary goods can act to raise threshold requirements.
29predict a product development focus and low market volumes in the early phases ofdevelopment, with a process development focus in the intermediate stage accompanied by highmarket growth, and slower market growth in the final stage. While these patterns have beengenerally explained in terms of production technologies and producer entry (see Klepper, 1997for a review), the logic which drives the present results has a very different basis and is rooted inthe underlying heterogeneity of the market environment. The demand-based model developed here also offers insight into the developmentpatterns of products introduced under less conventional conditions which do not follow thetraditional technology life cycle. Furthermore, while previous models (Gort and Klepper, 1982;Utterback and Abernathy, 1975; Abernathy, 1978; Klepper and Graddy, 1990) of the product lifecycle predict decreased innovation activity in later stages of the life cycle, the model developedhere suggests the possibility of high levels of innovative activity for mature product classes,consistent with a number of empirical findings (Henderson, 1995; Christensen, 1992; Klepper,1997). By introducing demand-based factors, the current model sheds new light on thisobserved, but previously unexplained behavior in the product life cycle. While price trends similar to those predicted by the model for later stages of developmentare suggested by production experience curves (Boston Consulting Group, 1972), experiencecurve explanations do not substitute for the demand-based framework presented here but rathercomplements it. The present argument differs from experience curves in that it is concerned withan evolving product technology, whereas experience curve arguments focus on the perfection ofmanufacturing techniques for a generally static product (Grant, 1995). As a result, experiencecurve arguments do not speak to the relative intensity of product and process innovation.
30 In addition to abstracting from possible learning curve effects on product cost, the modelalso does not explore possible consumption or network externalities that might influencepurchase behavior (Arthur, 1989; David, 1985). To the extent that such externalities are present,they would allow consumers to derive greater utility from a given product as the user base, thenumber of consumers already purchasing, increases. This increase in utility would result in adownward shift of individual consumer’s F0i. This lowering of consumers’ functionalrequirements would, in turn, allow firms to satisfy consumers’ requirements earlier and with lessdevelopment effort, but should not affect the qualitative dynamics of the innovative process. The model also does not explore the effects of product line strategies on firms’development decisions. While outside the scope of the current model, we can leverage ourunderstanding of the current baseline dynamics to shed some light on the expected dynamics ofproduct lines. The key point of differentiation between the single product setting and that of amulti-product product line occurs when early consumers threaten to stop purchasing the productbecause its price is rising due to improvements which they do not particularly value. At thispoint, a firm might offer a ‘basic’ product to maintain its existing customer base and a higher end‘advanced’ product, which it would actively improve, to capture new customers. The marketwould thus be segmented according to functionality and price. However, competitive pressurewould force firms to improve their product in all market segments in order to maintain their sharewithin each segment. Thus, the basic dynamics characterized here should hold in the presence ofproduct line strategies. The central assumption underlying the result of “luxurious bargans” is that the potentialfor technological progress remains unexhausted even after the population’s willingness to pay forimprovement is largely exhausted. While the potential of technology performance relative to
31demand requirements can only be assessed on a case specific basis, the rising dominance ofelectronic, computer, and information technology that has heralded the dawn of the ‘informationage’ suggests that the prevalence of such settings may be increasing (Kelly, 1997). It is nocoincidence that the price histories of Figures 1 and 2 are drawn from the realm of electronics.Electronic product technologies have demonstrated a seeming inexhaustible potential forimprovement, both on the product performance side, with increases in speed, compactness, andreliability, as well as on the production process side, with tremendous reductions in the cost ofobtaining these levels of performance. As such, they provide an ideal setting to study thedynamics of technology development where exogenous limits to development are not a primaryconstraint. Viewing the evolution of technology through a demand-based lens suggests that the earlyevolution of technologies is guided by responding to the unsatisfied needs of the market. Aftersufficient development however, firms face the intriguing possibility that these guiding needshave largely been satisfied. The framework developed here suggests that product maturity maybe as much a function of satiated needs as it is of exhausted technologies. The dynamicshighlighted by the model suggest that price sensitivity to technological improvements can be astrong signal of the state of demand satisfaction. Highlighting the role of demand heterogeneity,adds to our understanding of the role of selection forces on the evolution of product technology.While the exploration of path dependence has motivated a significant volume of work ontechnology evolution, the role of the demand context in which firms operate has received lessattention. This bias in the literature has undermined our appreciation of the complexity of thedemand environment and its potential for enriching our understanding of technology evolution.
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35 Figure 2: VCR Price History 1977 black and white 1400 60 min record 1980 timed programming 1200 1978 41 lbs 1982 cb interference; 25 lbs; auto record; 1000 humidity light; counter jack for wired 1983 price (1982$) remote; resolution wireless remote; cable tv tuning 250 lines 800 1985 - varactor tuning (presets); 4/12 programming 1987- 1 touch record; intr. hi fi models 1988-editing features; 5.4/72 prg; on screen prg. 600 1990-5.3/155 prg; 70 cable channels 1993-6.5/264 programming ‘94-digital tuner standard; 8/365prg 400 ‘95-VCRplus; 4 heads universal remote 1996- menu driven, 200 remote prog; 125 channels 1997-childproof; self setting clock; go-to search 0 1975 1980 1985 1990 1995 2000compiled from data on models featured in Consumer Reports. Product Innovation Process Innovation Rate of Innovation Time Figure 3: Dynamics of Product and Process Innovation