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Strategic Management JournalStrat. Mgmt. J., 33: 277–302 (2012)

Published online EarlyView in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.950

Received 25 September 2009; Final revision received 7 July 2011

THE INFLUENCE OF PRIOR INDUSTRY AFFILIATIONON FRAMING IN NASCENT INDUSTRIES: THEEVOLUTION OF DIGITAL CAMERAS†

MARY J. BENNER1* and MARY TRIPSAS2

1 Carlson School of Management, University of Minnesota, Minneapolis, Minnesota,U.S.A.2 Harvard Business School, Boston, Massachusetts, U.S.A.

New industries sparked by technological change are characterized by high uncertainty. In thispaper, we explore how a firm’s conceptualization of products in this context, as reflected byproduct feature choices, is influenced by prior industry affiliation. We study digital camerasintroduced from 1991–2006 by firms from three prior industries. We hypothesize and findthat: (1) prior industry experience shapes a set of shared beliefs that results in similar andconcurrent firm behavior; (2) firms notice and imitate the behaviors of firms from the same priorindustry; and, (3) as firms gain experience with particular features, the influence of prior industrydecreases. This study extends previous research on firm entry into new domains by examiningheterogeneity in firms’ framing and feature-level entry choices. Copyright 2011 John Wiley& Sons, Ltd.

INTRODUCTION

Firms entering a nascent product market face acontext characterized by tremendous ambiguityand uncertainty, particularly when the new mar-ket is sparked by radical technological change.Potential customers have little or no experiencewith products, and their preferences are thereforeunformed and unarticulated. Even basic assump-tions about what the product is and how it shouldbe used are subject to debate. Similarly, from atechnological perspective, uncertainty exists aboutthe rate of performance improvement of the newtechnology, how components of a technologi-cal system will interact, and whether different

Keywords: technological innovation; industry evolution;dominant designs; managerial beliefs; digital photography*Correspondence to: Mary J. Benner, Department of StrategicManagement and Organization, 3-422 Carlson School of Man-agement, University of Minnesota, 321-19th Avenue SouthMin-neapolis, MN 55455, U.S.A. E-mail: [email protected]† The authors are listed alphabetically and contributed equally.

technological variants will work at all. Market andtechnological uncertainty are often compounded bycompetitive uncertainty as firms grapple with shift-ing industry boundaries and the convergence offirms from previously distinct domains. During thisperiod of turbulence, firms experiment with alter-native product configurations, functions, and tech-nologies, with competing alternatives converging,in many cases, on what researchers have labeled adominant design—a standard set of technologiesand interfaces as well as a shared understanding ofwhat performance attributes are important (Utter-back and Abernathy, 1975; Clark, 1985; Andersonand Tushman, 1990; Klepper, 1996).

While this basic pattern of evolution has beenwell established, important gaps in our understand-ing remain. First, prior research on entry in theearly stages of industries has treated entry as adichotomous variable with the focus on predict-ing which firms enter and the timing of their entry(e.g., Klepper and Simons, 2000). We lack a moregranular understanding of the many individual

Copyright 2011 John Wiley & Sons, Ltd.

278 M. J. Benner and M. Tripsas

choices that entry comprises. In particular weknow little about the forces that influence het-erogeneity in entrants’ interpretations of the newproduct market as reflected in product variantsintroduced, specifically at the level of product fea-tures. Firms’ decisions about product features arecritical as they influence consumer adoption anddiffusion, and ultimately whether the new mar-ket emerges (Rindova and Petkova, 2007). Second,while firm heterogeneity is a central tenet in strat-egy research, ‘we lack a clear conceptual modelthat includes an explanation of how this hetero-geneity arises’ (Helfat and Peteraf, 2003: 997). Theconvergence of firms with diverse backgroundsin a new domain could provide an opportunityto explore the origins of heterogeneity, however,existing research has emphasized only the differ-ential capabilities associated with prior industryexperience, showing that firms with related expe-rience are more likely to enter a new industry (Sil-verman, 1999; Klepper and Simons, 2000; Dan-neels, 2002; Helfat and Lieberman, 2002). Theinfluence of heterogeneous beliefs and assumptionsthat result from different prior industry experiencemay also be important, and this terrain remainsrelatively unexplored.

Finally, although a dominant design representsconvergence of both technological (supply-side)and market (demand-side) characteristics (Clark,1985), empirical studies of the emergence of dom-inant designs have focused primarily on the tech-nological dimension. For example, the 23 papersreviewed in Murmann and Frenken’s (2006) recentsynthesis of the literature all assessed the emer-gence of a dominant design in terms of technolo-gies, broadly defined, while the features embodiedin the dominant design were rarely examined. Wetherefore have little understanding of the marketdimension of dominant designs, including both ini-tial variance in product features and eventual con-vergence on a standard set of features. Insight intothis aspect is important for improving our under-standing of how dominant designs emerge, andmore broadly, how industry evolution unfolds.

In this paper, we address these gaps by explor-ing how a firm’s background, represented byits prior industry affiliation, influences its con-ceptualization of a nascent product market, asreflected by the product features it incorporates.A firm’s prior industry experience is likely to mat-ter due to a combination of capabilities, beliefs,and imitative behavior. Existing capabilities might

influence product-level choices in that a firmis likely to introduce products that leverage itscore strengths (Montgomery and Hariharan, 1991;Helfat and Raubitschek, 2000; Sosa, 2011). Giventhe ambiguity associated with a nascent industry,socio-cognitive processes may also play an influ-ential role as managers attempt to make senseof confusing and often conflicting signals (Weick,1990). Perceptions of the emerging market may,thus, be influenced by managerial beliefs derivedfrom a firm’s industry history (Huff, 1982; Porac,Thomas, and Baden-Fuller, 1989; Spender, 1989;Tripsas and Gavetti, 2000). Finally, during periodsof high uncertainty, decision makers often imi-tate the behaviors of other salient firms (Haveman,1993; Haunschild and Miner, 1997; Rao, Greve,and Davis, 2001), and the most salient firms arelikely to be those competing in the same priorindustry. So, how a firm interprets the emergingopportunity and its conceptualization of productsin the nascent domain are likely to be influencedby its prior industry background.

Our empirical context, the emergence of thedigital camera market,1 is an ideal setting foraddressing these issues. First, the emergence ofconsumer digital cameras was characterized byhigh uncertainty and the entry of firms fromthree prior industries—photography, computing,and consumer electronics—enabling a compari-son of the influence of firm background on deci-sions about which features a digital camera shouldinclude. Second, the digital camera market isunique in that technical capabilities were likelynot a primary driver of firms’ choices of whichfeatures to introduce. As we discuss in detail later,although some firms invested in developing propri-etary camera technology, and we control for tech-nical capability using patent data, a well-developedsupply chain gave all firms access to the samecore features, even if they had no internal capabil-ity. This allowed us to study influences of indus-try affiliation apart from technical capabilities onfirms’ choices of features. Finally, although firms’strategic decisions about market position mightinfluence their corresponding choices of features,and there were specific market niches in the digi-tal camera market such as studio and professional

1 Consistent with research on dominant designs, we use as ourunit of analysis a product market, in this case a digital camera,although digital cameras exist in the broader context of digitalimaging.

Copyright 2011 John Wiley & Sons, Ltd. Strat. Mgmt. J., 33: 277–302 (2012)DOI: 10.1002/smj

Prior Industry and Framing in Nascent Industries 279

cameras, we focus specifically on the consumer(mass) market for digital cameras. Thus, we areable to study heterogeneity in choices—and under-lying beliefs—for firms participating in the samemarket segment. We utilize a unique longitudinaldataset that includes the entry date and features ofalmost every camera in the history of the U.S. con-sumer digital camera industry from its inception in1991 through 2006.

We find that prior industry affiliation had a sig-nificant influence on a firm’s initial framing of thenascent product market. Qualitative data indicatethat digital camera product concepts and expecteduses varied systematically, ranging from an analogcamera substitute (photography firms), to a videosystem component (consumer electronics firms), toa personal computer (PC) peripheral (computingfirms) before converging on a product concept thatincluded elements of all three frames. Quantita-tive analysis of the timing of initial product featureintroduction further supports these systematic dif-ferences. Our results suggest that firms from thesame prior industry shared similar beliefs aboutwhat consumers would value as reflected in theirconcurrent introduction of features—firms weresignificantly more likely to introduce a feature,such as optical zoom, to the extent that other firmsfrom the same prior industry entered with the fea-ture in the same year, whereas concurrent entry byfirms from different prior industries had no influ-ence. Firms were also likely to imitate the behaviorof firms from the same prior industry, as opposedto that of firms from different prior industries inintroducing some, but not all features. Finally, wefind that as a firm’s experience with a particularfeature increased, the influence of prior industrydecreased.

Technological change, market uncertainty, andpatterns of industry emergence

Studies of industry evolution following majorchanges in technology2 have documented a con-sistent pattern of progress, falling into three proto-typical stages: an era of ferment, convergence on adominant design, and an era of incremental change(Utterback and Abernathy, 1975; Anderson and

2 Sometimes a radical technology from the perspective of oneindustry may actually be the application of technology that hasbeen incrementally developing over time in a different context(Levinthal, 1998; Tripsas, 2008).

Tushman, 1990; Klepper and Graddy, 1990).3 Highlevels of experimentation by both firms and cus-tomers dominate an era of ferment. For instance,early automobiles utilized a variety of mechanismsfor steering, ranging from a joy-stick-like tiller tosteering wheels; the internal combustion enginecompeted with electric and steam engines; andsome vehicles had three wheels, not four (Aber-nathy, 1978; Basalla, 1988). As Rao (1994: 33)put it, ‘The only point of agreement about theautomobile was that it could not be powered byanimals.’ In addition to technical variation, funda-mental beliefs about what the product is and whatfunctions it should perform vary. A customer’schoice in the era of ferment ‘involves both theformation of concepts with which to understandthe product, and the development of criteria tobe used in evaluation,’ (Clark, 1985: 244). Forinstance, early in the automobile industry’s his-tory, Americans conceived of an automobile as a‘horseless carriage’ whereas ‘the French thought interms of a road locomotive,’ (Langlois and Robert-son, 1989: 366). These different perspectives werereflected in the product design, features, and tech-nologies employed. Similarly, early in the evolu-tion of cochlear implants, alternative visions ofwhat the product should be resulted in completelydifferent performance metrics being valued (Garudand Rappa, 1994).

In some cases the industry coalesces around adominant design, which reflects both technologi-cal convergence—consensus about a set of stan-dard technologies, modules, and interfaces (Utter-back and Abernathy, 1975; Anderson and Tush-man, 1990; Utterback and Suarez, 1993)—as wellas cognitive convergence—a shared understandingof what the product is, how it will be used, andwhich core attributes will have value (Kaplan andTripsas, 2008). The process by which a dominantdesign emerges is a complex combination of eco-nomic, social, political, and cognitive dynamics,and scholars have demonstrated that the technolog-ically superior alternative does not necessarily win(Cusumano, Mylonadis, and Rosenbloom, 1992;Tushman and Rosenkopf, 1992; Utterback, 1994;Suarez, 2004). Although the dominant design rep-resents the core elements of a new product class,

3 These stages are essentially the same as what Utterback andAbernathy (1975) label fluid, transitional and specific stages,and what Klepper and Graddy (1990) label growth, shakeout,and stabilization stages.



its emergence does not imply that products can nolonger be differentiated. In fact, competition afterthe emergence of a dominant design is often basedon quality, reliability, brand, and new peripheralfeatures (Utterback, 1994).

While this pattern of high variation and eventualconvergence on a dominant design has been docu-mented in a range of industries, our understandingof the sources of initial heterogeneity is limited.Other than the general argument that de novo firmsare an important source of entry and innovativetechnology in many industries (Cooper and Schen-del, 1976; Tushman and Anderson, 1986; Chris-tensen and Bower, 1996; Martin and Mitchell,1998), we lack a good sense of whether and whydifferent firms might introduce systematically dif-ferent product variants in the same nascent mar-ket. Diversifying entrants play an important rolein many new industries, but the focus of mostresearch has been on whether firms enter, whenthey enter, and whether they survive—not on thevariation in product artifacts they introduce (e.g.,Mitchell, 1989, 1991; Carroll et al., 1996; Dow-ell and Swaminathan, 2006). In addition, researchhas assumed that differences stemming from priorindustry affiliation are a result of variation inresources and capabilities. For instance, radio pro-ducers, which had capabilities that were close tothose needed to produce televisions, were morelikely to enter the television receiver industry, toenter early, and to survive (Klepper and Simons,2000). Similarly, of diversifying entrants in theautomobile industry, bicycle and carriage manu-facturers were more likely to survive than enginemanufacturers (Carroll et al., 1996). Much lessconsideration has been given to the possibilitythat prior industry affiliation also reflects sharedbeliefs and a common set of peers that are noticedand potentially imitated. Given that technologicalchange is increasingly resulting in the competi-tive convergence of firms from previously distinctindustries (Brusoni, Jacobides, and Prencipe, 2009)a deeper understanding of the influence of priorindustry affiliation—one that takes into accountboth capabilities and cognition—is needed.

Moreover, empirical studies of the evolutionof new product markets have focused on thetechnological, not market dimension of a domi-nant design. For example, in Christensen, Suarez,and Utterback’s (1998) study of the rigid diskdrive industry, they identify and track four tech-nologies that make up the eventual dominant

design, the: Winchester architecture, under-spindlepancake motor, rotary voice-coil actuator motors,and embedded intelligence interface electronics.The demand-side product features that might beassociated with different assumptions about cus-tomer preferences and use are not considered inthe dominant design measure. Similarly, in Baum,Korn and Kotha’s (1995) study of the facsimiletransmission equipment industry, the ConsultativeCommittee on International Telephone and Tele-graph technical standards for facsimile transmis-sion were used to define the dominant design. Byexamining the market dimension of a dominantdesign, this paper fills an important gap in ourunderstanding of how different actors arrive at acommon interpretation of what a new product cat-egory represents.

The influence of prior industry affiliation onframing of a nascent product market

We next develop a set of hypotheses about howa firm’s prior industry affiliation influences theway managers frame a new product market, basedon a firm’s initial introduction of particular prod-uct features and its ongoing commitment to thosefeatures. In doing so, we explicitly distinguishbetween the influence of shared industry beliefsand the influence of imitative behavior, both con-structs that can result from common industryaffiliation.

Existing research suggests that similar priorexperiences and ongoing interactions give rise toa shared set of beliefs for members of the sameindustry. Huff (1982: 125) proposed the theoret-ical argument that managers of organizations inthe same industry develop ‘shared or interlock-ing metaphors or worldviews’ such as commonbeliefs about customer preferences, the role ofregulation, and future levels of industry demand.In subsequent research, scholars have providedstrong empirical support for the notion of industry-level frames. Spender (1989: 188) identified setsof ‘industry recipes,’ noting that ‘executives adopta way of looking at situations that are widelyshared within their industry.’ Similarly, Poracet al. (1989: 400) articulated a set of shared causalbeliefs held by Scottish knitwear manufacturersconcerning customers, suppliers, retail, and com-petition, noting that ‘over time the mental modelsof competing strategists become similar thereby



creating ‘group level’ beliefs about the market-place.’ Extending this work, Porac et al. (1995)developed the concept of an ‘industry model,’which represents collective recognition on the partof producers about what fundamental attributesshould be used to categorize competitors andwhich firms belong in which categories.

Industry-level beliefs are important because theyinfluence decision making and action (Levitt andMarch, 1988). In the photolithography industry,firms developed shared, but mistaken, assump-tions about the direction of change in the under-lying technology, and these resulted in erroneousprojections about performance limits by firmsin the industry (Henderson, 1995). Bogner andBarr (2000: 221) proposed that in hypercompet-itive industries, constant, rapid change became thenorm, and this ‘common cognitive framework’ ofindustry members in turn perpetuated the hyper-competitive environment. The manner in whichfirms evaluate acquisition targets has also beenshown to vary depending on industry background(Hitt and Tyler, 1991).

Commonly held perceptions, expectations, andassumptions become particularly salient whenfirms enter a highly uncertain emerging industrythat incorporates novel technologies with noveluses (Benner, 2010). In this context, managerslack concrete data about what consumers value andtherefore must make assumptions about how cus-tomers will use the product and what features willhave merit. The process by which firms with thesame prior industry affiliation may apply commonassumptions is twofold. First, managers may ‘rea-son by analogy,’ transferring beliefs about priorsituations to novel situations that they perceive tobe similar (Gavetti, Levinthal, and Rivkin, 2005).Past experience with similar customers may createcommon expectations about what customers willvalue in a new domain. Second, ongoing inter-action among firms from the same prior industrymay create a forum for direct sharing of infor-mation about the emerging industry since firmsare more likely to pay attention to and inter-act with familiar peers (Ocasio, 1997). A varietyof venues such as industry consortia, standardscommittees, trade associations, and industry con-ferences have been shown to facilitate relation-ships and sharing of information (Lampel, 2001;Rosenkopf, Metiu, and George, 2001). In aggre-gate, these mechanisms may reinforce common

expectations among firms from the same priorindustry.

Thus, firms from the same prior industry arelikely to make similar assessments of which prod-uct features customers will value and are thereforelikely to first introduce a given feature at a similartime. Put differently, we propose that concurrentintroduction of a feature is an indication of sharedbeliefs about the value of that particular feature.

Hypothesis 1: In the nascent stage of an indus-try, the greater the number of other firms fromthe same prior industry that introduce a prod-uct feature during a period (as opposed to firmsfrom a different prior industry) the greater thelikelihood a firm will introduce the product fea-ture in that period.

Neoinstitutional theory holds that firms in thesame industry, subject to similar institutionalforces, are also likely to imitate each other (DiMag-gio and Powell, 1983). Researchers have docu-mented that firms facing similar institutional envi-ronments tend to adopt similar structures andpractices, including, for example, civil servicereforms (Tolbert and Zucker, 1983), multidivi-sional structures (Fligstein, 1985), or naming con-ventions (Glynn and Abzug, 2002). Moreover,firms are more likely to imitate the practices andbehaviors of similar, comparable firms than to imi-tate firms they categorize as distant (Haveman,1993; Haunschild and Miner, 1997; Baum, Li,and Usher, 2000). The tendency for mimetic iso-morphism or imitation is heightened under condi-tions of high uncertainty such as entry into newmarkets (Haveman, 1993; Greve, 1996; Korn andBaum, 1999). Imitation is likely a factor not onlyin decisions about whether to enter new, emerg-ing domains but also in choices about how firmsenter, that is, how they conceptualize the new prod-uct and which features they include. In the highlyuncertain setting of an era of ferment, therefore,firms are likely to imitate the features that havealready been introduced by other firms from thesame industry background.

Hypothesis 2: In the nascent stage of an indus-try, the greater the previous introductions of agiven product feature by other firms from thesame prior industry, the greater the likelihood



a firm will imitate them and enter with that fea-ture (as opposed to imitate firms from a differentprior industry).

Thus, Hypothesis 1 suggests that due to sharedbeliefs, firms with the same background are likelyto behave in similar ways, while Hypothesis 2suggests that even absent shared beliefs, firmsare likely to imitate other firms from the sameprior industry, first observing the product attributesintroduced, and then engaging in the same behav-ior in a subsequent period.

Our discussion so far concerns the choices thatfirms make in their initial introductions of prod-uct features when they have limited data and mustrely on prior beliefs or observations of other salientfirms for making decisions. But these influencesmay dissipate over time as firms gain knowledgebased on their own experience. A wide body oforganizational learning research has shown that asthey gain experience in a product market, firmstend to engage in local search, introducing newproduct variants that are similar to previous models(Martin and Mitchell, 1998; Katila, 2002; Katilaand Ahuja, 2002). And in a study of South Koreanfirms in China, Guillen (2002) found that whilefirms imitated other firms from the same homecountry industry in their rate of foreign expan-sion, this effect decreased once a firm had made itsfirst foreign entry. Prior research has also shownthat although decision makers may initially imi-tate other firms in situations of high uncertainty,updated information based on experience can leadto abandoning a particular course of action (Fiskeand Taylor, 1991; Rao et al., 2001). Similarly, inour context, once a firm has introduced productswith particular features, it gains knowledge aboutthe level of demand and has access to informationfrom customers to better understand usage behav-ior. Thus, a firm’s own experience with featuresis likely to play a heightened role in subsequentdecisions about whether to continue to incorporatethose features in its products, and the influenceof prior industry beliefs and peers is likely todecrease.

Hypothesis 3: In the nascent stage of an indus-try, the more experience a firm has with aparticular product feature, the lower the influ-ence of other firms from the same prior indus-try on the firm’s commitment to that productfeature.

DATA AND RESEARCH SETTING

Overview of the digital camera industry

Digital camera technology utilizes semiconductorchips such as charge-coupled devices (CCDs) tocapture and convert light images to binary data,replacing the role of silver halide film in analogcameras. Beyond image capture, digital technol-ogy offers the benefits of transfer, manipulation,and storage of digital images. The first consumerdigital camera in the United States, a noncolorgrayscale, 90,240 pixel4 camera that could store 32images in internal memory, was available in 1991,and by 2003 sales of digital cameras exceededthose of analog cameras.

The emergence of consumer digital cameras pro-vides an ideal context in which to study the dif-ferential effects of prior industry background sincethe majority of the 83 entrants in the United Statesfrom 1991 to 2006 came from three prior indus-tries: photography (25 firms), consumer electronics(19 firms), and computing (25 firms). There wereonly nine de novo start-ups and five diversifyingentrants from unrelated industries (e.g., Mattel andDisney). Firms were classified as follows: if a firmmade analog cameras or film, it was coded as pho-tography, even if it also made other products (e.g.,Canon). Similarly, if a firm produced camcorders,televisons, stereos, or MP3 players, it was codedas consumer electronics (e.g., Sony). Firms thatmade PCs, peripherals, software and/or compo-nents were coded as computing. Table 1 providesa list of entrants’ prior industry classifications.There is clearly variation within our broad industrygroupings, but our approach is conservative in thatthis variation would tend to decrease the likelihoodof finding a prior industry effect. While selectionbias is an issue in some studies of entry, in this caseevery major analog camera, photographic film, andconsumer electronics firm entered the market, lim-iting possible selection issues to computing firmsthat could have entered, but did not (e.g., Dell,Microsoft). However the range of computing firmsthat did enter is reasonably broad, and based on acomparison, we have no reason to believe that thecomputing firms that did not enter differ system-atically from those that did.

The digital camera market is also ideal forstudying the role of prior industry affiliation in

4 Pixels measure the resolution of digital cameras.



Table 1. Prior industry affiliation of firms that enteredthe consumer digital camera market

Photography Consumerelectronics

Computing

Achiever Archos AiptekAgfa Casio AppleArgus Creative DXG BTCCanon Hitachi BenQChinon JVC D-LinkConcord LG Electronics DolphinFuji Photo Mitsubishi Epson

FilmJazz Photo Oregon Scientific Gallant ComputerKodak Panasonic GatewayKonica Philips Hawking TechnologyKyocera RCA Hewlett-PackardLeica Relisys IO MagicMinolta Samsung IntelMinox Sanyo JenimageNikon Sharp KB GearOlympus SiPix LogitechPentax Sony Micro Innovations

Syntax BrillianPolaroid Microtek LabsPraktica MustekPremier NECRicoh SoundvisionRitz Camera Spot TechnologyRollei ToshibaSigma UMAX TechnologiesVivitar Visioneer

shaping perceptions and interpretations in that wecan largely separate decisions about introducingproduct features from the capabilities required toimplement those features. While a subset of firmsinvested in developing technical capability thatallowed them to design and manufacture digitalcameras, firms with no technical expertise couldalso introduce digital cameras by utilizing a well-developed supply chain that had the expertiserequired to develop the features that were eventu-ally standard. For instance, Ritz Camera, a photog-raphy retailer with no product development exper-tise, introduced a consumer digital camera in 1995.‘Digital camera components are readily available,products can be developed fairly quickly and pro-duction (part assembly) can be done relativelyeasily,’ explained a financial analyst who coveredFuji Photo Film (HSBC Chemicals, 2000: 14).In addition, camera manufacturers could choosefrom multiple suppliers for each feature. A MorganStanley analyst report identified nine zoom lenssuppliers, 10 LCD screen suppliers, and 16 image

sensor chip suppliers (the ability to introducehigher megapixels was driven by sensor chips)(Hsu, Ho, and Gupta, 2002). Even componentdevelopers that participated in the digital cameraindustry generally supplied their components toothers. Kodak, an early leader in high-end CCDsensor technology created a separate Image Sen-sor Solutions division to serve as a merchantmarket supplier of both CCD and complementarymetal–oxide–semiconductor(CMOS) sensors, andKodak’s consumer digital cameras mostly incor-porated sensors from other suppliers.

In addition to component suppliers providingaccess to features, a vibrant OEM/ODM industrydeveloped early on providing design, integration,and manufacturing services to firms wishing tointroduce a digital camera. Firms could choosefrom a menu of features available in digital cam-era reference designs developed by original equip-ment manufacturers/original design manufacturers(OEMs/ODMs). Japanese firms such as Chinonwere producing cameras for others as early as1993. Taiwanese firms entered the OEM/ODMindustry in 1997, and by 1999 it was estimated that10 percent of digital cameras worldwide were pro-duced by Taiwanese OEMs/ODMs (Taiwan Eco-nomic News, 1999) rising to 20 percent in 2000(Taiwan Economic News, 2000).

Some firms that entered the digital camera mar-ket did invest in developing technological capa-bility, but these firms were the minority. Of the83 firms that entered the market, 31firms had nopatents in classes related to digital cameras from1983–2003, 20 firms had fewer than 50 patents,and a core set of 20 firms had over 1,000 patents(see Table 2 for a list of patent classes relatedto digital cameras.) One might expect that firmswould be more likely to introduce features thatleverage their technical capabilities, and we testfor this effect in our quantitative analysis, how-ever, qualitative data indicate that even amongthese firms, the timing of a new feature wasnot driven by this technological capability. Forinstance, although Kodak had one of the highestpatenting rates, the president of the digital andapplied imaging unit from 1997–2005 explainedto us in an interview that,

Kodak’s decisions to offer consumer digitalcameras with features such as optical zoom,movie clips, or higher resolution were driven byour perception of what consumers were willing



Table 2. Digital camera patent classes included in con-trols for technical capabilities

250 Radiant energy257 Active solid-state devices324 Electricity: measuring and testing327 Miscellaneous active electrical nonlinear

devices, circuits, and systems345 Computer graphics processing, operator

interface processing, and selective visualdisplay systems

348 Television355 Photocopying356 Optics: measuring and testing358 Facsimile and static presentation processing359 Optics: systems (including communications)

and elements360 Dynamic magnetic information storage or

retrieval361 Electricity: electrical systems and devices377 Electrical pulse counters, pulse dividers, or

shift registers: circuits and systems378 X-ray or gamma ray systems or devices382 Image analysis386 Television signal processing for dynamic

recording or reproducing396 Photography428 Stock material or misc articles430 Radiation imagery chemistry: process,

composition, or product thereof438 Semiconductor device manufacturing: process711 Electrical computers and digital processing

systems: memory725 Interactive video distribution systems

to pay for, not by our technical capability todevelop or manufacture the underlying compo-nents (Dr. Willy Shih, in-person interview, 23February, 2009).

By taking advantage of the characteristics ofthis setting, as well as directly controlling fortechnological capabilities in our models, we aretherefore able to better untangle firms’ framingand conceptualizations of the appropriate featuresfor a digital camera from considerations of theirtechnical capabilities in our tests of the influenceof prior industry.

Sources and data

Our dataset includes comprehensive longitudinaldata covering the history of consumer digital imag-ing in the United States from 1991 through 2006.It covers every firm to introduce a branded digital

camera in the United States (private label cam-eras are excluded), and every digital camera intro-duced by these firms from 1991 through 2006.Since we focus on the mass market for digitalcameras, we excluded from our analysis types ofdigital cameras that we determined were distinctproduct markets that would experience their ownseparate processes of variation and convergenceon a dominant design: studio/professional cameras,Webcams, single lens reflex cameras (SLRs), andmobile phone cameras.5

Quantitative data were hand collected from abroad range of primary and secondary industrysources including company and industry associ-ation archives. Detailed information on digitalcamera specifications came from a combinationof trade publications (e.g., Future Image Report,6

PC Photo, and Popular Photography), researchreports (e.g., International Data Corporation andForrester), archived product specifications fromcompany Web sites, archives from photographyindustry Web sites (primarily dpreview.com,imaging-resource.com, and dcviews.com), andpress coverage of the industry throughout the timeperiod. The entry date and specifications for eachcamera were cross-checked and confirmed by atleast two of these sources. In all, our datasetincludes 1,629 digital cameras introduced by 83firms during this period. Quantitative data weresupplemented by extensive field work, includingattendance at multiple industry conferences suchas the annual Photo Marketing Association con-ference, as well as in-person interviews with over50 individuals involved in the industry includingemployees of photography, consumer electronics,and computing firms, as well as outside industryexperts such as the editors of the Future ImageReport.

5 The earliest digital cameras in the mid-1980s were studio andprofessional cameras that resembled scanners, captured up to16 megapixels, were priced in the $16,000 to $20,000 range,and were produced and sold primarily by graphic arts firmsthat did not enter consumer digital photography. Webcams,sometimes called ‘eyeball’ cameras, were tethered to a PCand provided video-conferencing capability over the Internet.Consumer-oriented digital SLRs, while sharing some attributeswith consumer-oriented digital cameras, did not really emergeas a category until 2002, at which point non-SLR cameras werealready beginning to coalesce on a dominant design. Similarly,the first mobile phone cameras were not introduced in the UnitedStates until 2002, largely after our period of study.[0]6 Published 10 times a year by Future Image, Inc. of San Mateo,California, Future Image Report provides news and analysis ofnew technology in the photo-imaging industry.



Emergence of a dominant design in consumerdigital cameras

Consistent with the pattern found in prior researchon technological change (e.g., Utterback, 1994;Anderson and Tushman, 1990), the advent of digi-tal photography triggered rapid innovation, uncer-tainty, and competition among product designs,features, and technical variants, with eventualconvergence on a standard camera—a dominantdesign. To trace the emergence of a dominantdesign for digital cameras, we identified andtracked adoption of a set of key camera features.This approach is unique in that it focuses on themarket dimension in contrast to prior empiricalmeasures, which have focused almost exclusivelyon the technological dimension (e.g., Andersonand Tushman, 1990; Christensen et al., 1998, Sosa,2009). For instance, we examined whether a firmintroduced higher levels of camera resolution, butdid not examine what underlying sensor technol-ogy (CCD or CMOS) firms used to deliver thatresolution. Similarly, we examined whether a firmintroduced a removable memory feature on a cam-era, but not what technical variant of removablememory was included (e.g., Compact Flash ver-sus Microdrive). As suggested by Suarez (2004),we considered a dominant design to have emergedonly when over 50 percent of new models had allof the elements that were included in the design,and that percentage was continuing to increase.

The features we tracked were: liquid crystal dis-play (LCD), optical zoom lens, digital zoom soft-ware, movie clips, resolution, removable storage,and dual Webcam capability. We chose these fea-tures because they were included systematicallyin descriptions of digital cameras in both indus-try trade publications such as the Future ImageReport, and mass market publications such as Con-sumer Reports. Our goal was to capture featuresthat had uncertainty associated with them, so weexcluded features such as ‘color,’ since it seemedcolor would be an obvious choice for firms. Wealso excluded features that diffused rapidly suchas ‘flash,’ since they did not provide enough vari-ation in the timing of firm introduction to allowfor analysis. With the exception of dual Webcamcapability, all features became part of the dominantdesign.

Whether to include most camera features was abinary choice for a firm—either the camera had thefeature or it didn’t. Image resolution, however, is

what Rosenkopf and Tushman (1994) call a dimen-sion of merit. All digital cameras have resolution,so the choice firms faced was whether to incorpo-rate higher levels of resolution. We therefore sortedcameras into resolution categories, enabling us toalso analyze introduction of higher resolution cam-eras as a binary choice. The first category includedcameras with video graphics array (VGA) reso-lution (the 307,200 pixels of a computer screen)or lower. The next category comprised cameraswith higher than VGA resolution, up to and includ-ing 1 megapixel cameras. For higher resolutions,we followed the norm in the industry and cate-gorized models as 2 megapixel (2 million through2.9 million pixels), 3 megapixel, and so on.

Table 3 describes each of these features inmore detail and summarizes when they were firstintroduced and how quickly they were adopted.Figure 1 shows the percentage of new camerasintroduced each year that incorporated each fea-ture. Wide variance in features is evident in theearly years. For instance, in 1997, LCDs wereoffered in 63 percent of new cameras, optical zoomin 17 percent, digital zoom in five percent, movieclips in 12 percent, over VGA resolution in 28percent, removable storage in 70 percent, and dualWebcam capability in 10 percent. Uncertainty isalso evident in that the majority of features expe-rienced both increases and decreases in penetrationover time. By 2006, however, all features, exceptfor dual Webcam capability, were present in almostall new cameras (only 13% of new models haddual Webcam capability.) While individual fea-tures were introduced earlier, the first camera toincorporate all elements of the dominant designwas introduced in 1999, and it was not until 2004that the dominant design was solidified, with over50 percent of new models incorporating all ele-ments. We, therefore, define the nascent stage ofthe market as extending from 1991 through 2003and exclude subsequent years from our quantitativeanalysis.

The role of prior industry affiliation onframing: descriptive analysis

Before turning to a quantitative analysis of theintroduction of features, we first examine descrip-tive data on the initial introduction and subse-quent diffusion of features to identify prelimi-nary patterns that distinguish the influence of priorindustry. While in retrospect the elements of the



Table 3. Summary of Digital Camera Features

Feature Description ofmodel features

First year featurewas introduced

/firm(s) thatintroduced it

Year >50%of new

models havefeature

Percent ofmodels

with featurein 2006

Dominant Contains all elements of the dominant 1999 2004 88%design design: LCD, optical zoom, digital

zoom, movie clips, overVGAresolution, and removable storage

Sony, Casio, Toshiba

Optical zoom Incorporates a zoom lens with a 1992 2000 92%range of focal lengths instead of alens with a fixed focal length.

Fuji

Removable Incorporates a slot for memory 1992 1997 97%storage (typically a flash memory card)

that can be removed to transferimages to a PC or printer.

Fuji

Greater than Sensor captures more pixels than the 1995 1998 98%VGA VGA (640x480) resolution of a Kodakresolution computer display

LCD Includes an LCD that allows the user 1995 1997 99%to see an image before taking apicture and preview/selectivelydelete pictures after image capture.

Casio

Movie clips Has the ability to capture and store 1996 2000 98%short video clips. Ricoh

Digital zoom Enables software manipulation of the 1997 1999 95%image within the camera to createa “close-up,” which is a croppedversion of the original image.

Fuji, Epson, Hitachi

Dual webcam Has the ability to switch to a webcam 1997 Never 13%mode, which enables real time Apple, Soundvision, (peak 24% in 2002)streaming video through a PC. UMAX, Ricoh, Vivitar

dominant design may seem obvious, in the momentthere was high uncertainty about how productswould be used and what features would be valued(Munir, 2005; Srinivasan, Haunschild, and Grewal,2007). For example, in 1993, a vice president ofbusiness development from Leaf Systems notedin an interview, ‘the thing about scanning is thatthere already was a perception in the marketplaceof what a scanner was. . .Electronic photographyis quite different’ (Gerard, 1993). Table 4 com-pares the initial introduction and adoption rates offeatures by firms from each prior industry. Thesedescriptive data seem to reflect different interpreta-tions of what a digital camera represented depend-ing upon what industry a firm originated in.

Photography firms

Photography firms appear to have conceived of adigital camera as a device that would be used in a

manner similar to an analog point-and-shoot cam-era, including the printing of images. Indicativeof this mindset, these firms: led the introductionof high resolution, optical zoom, and removablestorage features; were later in their introductionof movie clips; and introduced few models withdual Webcam capability. Although the resolutionof digital cameras ultimately emerged as an impor-tant product feature, early on the perceived valueof exceeding the VGA resolution of a computerscreen depended upon whether members of a firmbelieved that consumers would primarily displayimages on a television or a computer, or whetherthey would also want to print pictures (in whichcase high resolution would be valued). The firstcamera to offer higher than VGA resolution wasintroduced by Kodak in 1995 and by 1996 overhalf of the photography firm models had high



Figure 1. Percentage of new cameras with feature, by year

resolution (compared with 1998 for consumer elec-tronics and computing firm models). Fuji was thefirst to introduce an optical zoom model in 1992,and by 1998 over half of the photography firmmodels had optical zoom, a feature that was com-mon in analog film point-and-shoot cameras. Incontrast, it wasn’t until 2004 that half of computerfirm models had optical zoom. Removable stor-age enabled users to remove a memory card andtake it to either a digital minilab or a retail kioskfor prints, similar to the behavior of consumersusing analog film cameras. This feature was alsofirst introduced by Fuji in 1992 and by 1995 overhalf of the photography firm models had removablestorage (compared to 1997 for consumer electron-ics and computing firms).

In contrast, photography firms were later tointroduce the movie clips feature, which allowedthe user to capture and store short video clips.As one photography industry executive told usin an interview, ‘Photography firms figured thatif people wanted to take movies, they’d use acamcorder. They didn’t need that feature in acamera.’ It wasn’t until 2001 that half of thephotography firm models had the movie clip fea-ture, compared to 1999 for consumer electronicfirm models. Similarly, the Webcam feature wasalso not perceived as valuable by photographyfirms, and the penetration of that feature peakedat 17 percent of camera models for photographyfirms.

Consumer electronics firms

Consumer electronics firms appear to have con-ceived of a digital camera as a video system com-ponent, and consistent with this vision, they ledthe introduction of LCDs and movie clip featuresand were slower introducing high resolution andremovable storage. LCDs were already a standardfeature of camcorders, and on digital cameras theyallowed the user to preview and selectively deleteimages taken with the camera. LCDs were firstintroduced in 1995 in the QV10 camera intro-duced by Casio. ‘Because it was not a camera orfilm company, Casio was unencumbered by tradi-tional concepts of what a ‘digital camera’ oughtto be,’ noted an industry analyst (Simpson andYeh, 1997). In fact, the original concept for theQV10 was not ‘a digital camera with an LCDscreen, it was to be an LCD television with abuilt-in digital camera’ (Aoshima and Fukushima,1998: 369). The television tuner feature was even-tually taken out as the product concept evolved.By 1996, half of the consumer electronics indus-try models had LCDs (compared with 1997 and1998 for photography and computing firm mod-els). Consumer electronics firms also led the adop-tion of the movie clips feature, reflective of theexpectation that consumers view a digital cameraas similar to a camcorder. Half of their mod-els incorporated the feature by 1999 (comparedwith 2001 for photography and computing firms.)The expectation that consumers would not print is



Table 4. Adoption of digital camera features, by prior industry

Feature Photographyindustry firms firms firms

(analog camerasubstitute frame)

Computerindustry(video system

component frame)

Consumerelectronics

(PC-peripheral frame)

Optical zoomFirst year introduced 1998 1996Year >50% new models have attribute 2004 1999

Removable storageFirst year introduced 1997 1996Year >50% new models have attribute 1997 1997

Greater than VGA resolutionFirst year introduced 1995 1996Year >50% new models have attribute 1998 1998

LCDFirst year introduced 1996 1996Year >50% new models have attribute 1997 1998

Movie clipsFirst year introduced 1996 1997Year >50% new models have attribute 2001 2001

Digital zoomFirst year introduced 1997Year >50% new models have attribute 1999

Dual WebcamFirst year introduced 1997 1998Peak adoption 17% in 2001 20% in 2002

19921998

19921995

19951996

19971998

1997200148% in

19971999

19951996

19971998

reflected in the later adoption of the high resolu-tion and removable storage features. One of thedevelopers of Casio’s first digital camera stated,‘It started with a more or less simple idea to feedthe image to a television. In this respect, imagequality similar to a VHS frame [76,200 pixels]was quite acceptable’ (Aoshima and Fukushima,1998:375). Similarly, in 1997 an industry analystnoted, ‘It never occurred to Sony that images froma digital camera would be displayed predominantlyon a computer as opposed to a TV’ (Gerard,1998).

Computer industry firms

Computer industry firms appear to have vieweda digital camera as a PC peripheral, with theexpectation that consumers would either leave theircamera tethered to a PC, or after taking pictures,upload them to a PC for transmission or display.Intel brochures from 1997 were quite explicit,promoting their product as a ‘PC camera.’ Sim-ilarly, the company press release announcing theLogitech Fotoman in 1991 described it as, ‘aportable, ergonomically designed digital camera

for IBM PCs’ (Logitech, 1991). This perceptionwas reflected in the relatively late adoption of highresolution, removable storage, and optical zoomas well as the relatively early adoption of dig-ital zoom and Webcam capability. Digital zoominvolves software manipulation of the image tocreate a ‘close-up,’ which is a cropped version ofthe original image. Over half of computing firmmodels had the feature in 1998 (compared with1999 for photography firms). The dual Webcamfeature enabled a camera to serve as a Webcam anddo real time streaming video through a personalcomputer over the Internet in addition to function-ing as a stand-alone camera. Although almost halfof the models from computer firms had the featurein 2001, for photography and consumer electron-ics firms the percentage of models with the featurepeaked at about 20 percent.

The role of prior industry affiliation onframing: quantitative analysis

The descriptive data suggest that prior industryaffiliation was an important influence on how firms



conceptualized a digital camera. We next use quan-titative data on the timing of camera feature intro-ductions to more formally test our hypotheses.

MEASURES

Dependent variables

Initial introduction of features

For testing Hypotheses 1 and 2, we used a binarydependent variable that has a value of 1 in thefirst year that a firm introduces a model with agiven product feature (e.g., LCD). The firm isat risk of introducing a feature starting the yearafter a digital camera with that product featurewas first introduced into the industry and endingonce the firm introduces a model, the firm exitsthe digital camera industry, or the time periodunder consideration (through 2003) ends. Since thechoice of features for a firm’s initial digital camerareflects the firm’s framing of the opportunity in thecontext of high uncertainty, we included the firstmodel introduced by a firm in the analysis.

Ongoing commitment to features

To test Hypothesis 3, we used two different depen-dent variables. For all features other than resolu-tion, we measured a firm’s ongoing commitmentto a feature as the number of digital cameras intro-duced by firm i in year t that had a particular fea-ture. The data for these analyses began in the yearfollowing the firm’s initial year of entry into thefeature. For the analyses of the digital camera reso-lution feature, we examined the timing of a firm’sentry into each subsequent megapixel generationfrom 2 megapixels to 6 megapixels, since an ongo-ing commitment to high resolution is indicated bya firm continuing to introduce increasingly higherresolution cameras, (as opposed to more cameraproducts with greater than VGA up to 1 megapixelresolution).

Independent variables

To test Hypothesis 1, that firms from the sameprior industry held shared beliefs, we comparedthe effect of concurrent entry by other firms fromthe same prior industry, and concurrent entry byfirms from a different prior industry , counts of thenumber of other firms with the same and with

different prior industry affiliations that introduceda particular feature in year t . If firms from thesame prior industry have similar beliefs about whatfeatures to incorporate in a camera, then theyshould be more likely to introduce a feature at thesame time, as opposed to at the same time as firmsfrom a different industry.

To test Hypothesis 2, that firms are likely tonotice and imitate firms from the same prior indus-try more than firms from a different prior industry,we compared the effect of cumulative previousentry by firms from the same prior industry andcumulative previous entry by firms from a differentprior industry, counts of the cumulative number ofother firms with the same and with different priorindustry affiliation that have introduced a partic-ular feature as of year t − 1 . For example, forphotography firms such as Nikon or Kodak, wemeasured the cumulative number of other photog-raphy firms that had introduced a camera with afeature (e.g., optical zoom) in prior years and thecumulative number of non-photography firms thathad introduced the feature in prior years.

For testing Hypothesis 3, that firm experiencewith a feature moderates the relationship betweenprior industry affiliation and a firm’s ongoing com-mitment to a feature, we examined the interactionbetween the market presence of firms from thesame prior industry in the feature and a firm’s ownexperience with the feature. Both main effects weremean centered, with mean-centered values used tocompute the interaction. We measured firms fromthe same prior industry present in feature as acount of the number of firms from the same priorindustry that are currently in the market with acamera that has the feature. We measured firmexperience in feature using the cumulative num-ber of models with the feature that the firm hasintroduced as of year t − 1 . If prior industry influ-ence diminishes with experience, the interactionbetween these two measures should be negative.Finally, we also controlled for firms from a differ-ent prior industry present in feature, a count of thenumber of firms from a different prior industry thatare currently in the market with a camera that hasthe feature.

Control variables

We controlled for several other factors that mightaffect the introduction of digital camera features,including a firm’s technological knowledge and



related capabilities, which may affect its intro-duction of particular features. Therefore, we con-trolled for technical capability using a cumulativecount of granted digital camera patents, coded byapplication date, starting in 1983. We obtainedpatent data from the National Bureau of Eco-nomic Research patent database (Hall, Jaffe, andTrajtenberg, 2001). Since the technologies usedin a digital camera are categorized in multiplepatent classes, we generated a comprehensive listof classes by searching the United States Patentand Trademark Office database for patent titles andabstracts related to each digital camera feature andrecording the classes. A list of the patent classesincluded for all features is shown in Table 2. Weused the log of patent counts (adding one beforelogging) in our models.

A firm’s commitment to and participation inthe broader digital imaging industry may influ-ence introduction of features, so we controlled forthe breadth of a firm’s digital imaging offerings,a time-varying measure calculated as the numberof digital imaging product categories in which afirm participates in a given year, including photoprinters, photo finishing/sharing Web sites, photoediting software, desktop scanners, and removablememory cards. Participation in closely related mar-kets may also influence feature introduction, so weincluded controls for whether a firm is present inthe Webcam, camcorder, and digital SLR marketsin year t. Each of these variables was set to 1 if thefirm was in that market in the current year. A Web-cam was defined as a device that is tethered to aPC and, with appropriate PC software, enables livevideo/audio streaming—videoconferencing. MostWebcams can also capture still images, which arestored on the PC. A camcorder was defined aseither an analog or a digital device that has aprimary function to capture video. A digital SLRcamera was defined as a device that has exchange-able lenses and through-the-lens viewing.

Firms that have more digital camera modelsavailable in the consumer market may have ahigher likelihood of introducing a feature simplybecause they offer more cameras. We thereforecontrolled for firm models on the market in year tusing a count of the number of digital cameras thatthe firm has on the market in the year. Since largerfirms may have the resources to experiment in abroader range, we controlled for firm size, mea-sured as sales at the corporate level. The firm sizedistribution is skewed, so we took the log of sales.

For public firms, data was obtained from Compu-stat. For private firms, data came from a combi-nation of Wards, Dun & Bradstreet, OneSource,and trade press articles in which the firm disclosedsales figures. Missing years for private firms wereinterpolated based on the years for which data wasavailable. Nine firms had no publicly availablesales data, but based on press releases and infor-mation about number of employees, these firmswere all classified as having sales of less than$10M. The firm size variable was constructed in$10M increments, so for firms with sales less than$10M, firm size = 1, $10–$20M, firm size = 2,$20–$30M, firm size = 3 and so forth. We con-trolled for whether a firm is public with a dummyvariable that equals 1 if it is publicly traded in thecurrent year. Finally, non-US is a dummy variableset to one if a firm has its headquarters outside ofthe United States.

Models

To test Hypotheses 1 and 2 concerning the influ-ence of prior industry background on the initialintroduction of product features, we used eventhistory analysis, specifically a Cox ProportionalHazard model. Event history models analyze thelength of time it takes for a specific event to occur.In our case, the event is a firm’s initial entry with aparticular camera feature. The hazard function canbe interpreted as the likelihood that a firm intro-duces a particular feature at time t . A Cox modelis advantageous because it does not make assump-tions about the particular shape of the underlyinghazard function. This method is appropriate for ouranalysis, since there is no theory to suggest anyspecific underlying functional form for the hazardof a firm introducing a new product feature duringthe advent of a new industry. In a Cox model, thehazard rate is a function of the unspecified baselinerate and the exponential of a vector of covariates,as represented by the following equation:

r(t) = h(t) exp(βX) (1)

where h(t) is the baseline hazard rate and βX rep-resents the influence of the vector of covariates.We split the data into annual spells to allow fortime-varying covariates and used robust standarderrors clustered by firm to account for interdepen-dence between observations from the same firm.We ran separate models for each feature since,



while we hypothesize that the effect of the vari-ables of interest will be in the same direction, wehave no reason to believe that the magnitude ofthe coefficients will be the same for all features.We ran the models using stcox in STATA.

To test Hypothesis 3, assessing whether firmexperience with a feature diminishes the influenceof prior industry, we used a negative binomialspecification. Our dependent variable for this anal-ysis is a count of camera models with a featureintroduced by firm i in year t . Models with countmeasures as dependent variables may be mis-specified if estimated with ordinary least squaresregression (King, 1988) and are more appropriatelymodeled with a Poisson specification. However,Poisson models rely on the strong assumption of aPoisson distribution, which requires that the meanand variance be equal. Overdispersion, when thevariance is not equal to the mean, violates thePoisson assumption (Cameron and Trivedi, 1990).Overdispersion can occur if the probability of laterevents exceeds that of earlier events, suggestingcontagion or diffusion. This situation is particu-larly likely in our setting with the growth in adop-tion of specific digital camera product attributesand technologies over time. To correct for overdis-persion, we employed a negative binomial model,which relaxes the assumption of equal mean andvariance and includes an error term to captureoverdispersion.

We used a panel data negative binomial specifi-cation with random effects (e.g., Guo, 1996), (thextnbreg command with the random effects optionin STATA). A random effects specification con-siders both between-firm as well as within-firmvariation, thus accounting for the nonindependenceof multiple observations for each firm and provid-ing robust standard errors. Results were similar formodels with and without random effects.

The panel negative binomial models are repre-sented by the following equation, modeled as thelogarithm of the mean count λit:

log λit = Xit β + σεi + µi (2)

alternatively, Pr (yit = r) = (λr ελ)/r!; where yit

is the observed count and r is an integer; X isa vector of characteristics of firm i at time t , σ isa correction for overdispersion, and µi is a time-invariant firm i effect, which in our model is treatedas a random effect.

For testing Hypothesis 3 in the context of cam-era resolution, we used a multiple event hazardmodel in which we examined a firm’s initial entryinto subsequent megapixel generations (using thestcox procedure in STATA). Following Wei, Lin,and Weissfeld (1989), we combined all megapixelgenerations (2–6 megapixels) into one model,such that a firm is at risk of entering eachmegapixel generation and can have multiple entryevents—one for each generation. We stratifiedthe data on megapixel generation, thus allowingeach generation to have its own baseline hazardfunction. We also clustered on firm and used robuststandard errors to control for the lack of indepen-dence of observations.

RESULTS

Table 5 shows the descriptive statistics broken outby each feature analyzed.

Table 6 displays the results of the hazard rateanalysis to test Hypotheses 1 and 2, examininghow a firm’s initial introduction of digital camerafeatures in the market was influenced by the firm’sindustry background.7 In support of Hypothesis1, concurrent entry by other firms from the sameprior industry was significantly associated with thelikelihood of entry for all features except higherthan VGA resolution. For each additional firmfrom the same prior industry that introduced aproduct with a particular feature during the year,the likelihood of a firm introducing that featureincreased, ranging from a 22 percent increase foran LCD (Model 1) to an 87 increase increase forthe dual Webcam feature (Model 7). In contrast,concurrent entry by firms from a different priorindustry did not have a significant effect on theintroduction of any features, and its coefficientwas significantly different from that of concurrententry by other firms from the same prior industryexcept for resolution. For the resolution feature(Model 4), the lack of significance may indicatethat uncertainty surrounding the desirability ofgreater resolution was not actually high. If thenotion that ‘more is better’ was widely sharedthroughout the industry, then the introduction of

7 We ran separate models to test Hypotheses1 and 2, and theresults were the same as when we ran one model with bothindependent variables of interest, so we have included only themodels with both independent variables in Table 4.



Tabl

e5.

Des

crip

tive

stat

istic

s

Fea

ture

LC

DO

ptic

alzo

omD

igit

alzo

omO

ver

VG

Are

sM

ovie

clip

sR

emov

stor

age

Dua

lW

ebca

m

Var

iabl

esM

ean

SDM

ean

SDM

ean

SDM

ean

SDM

ean

SDM

ean

SDM

ean

SD

Firm

entr

yin

tofe

atur

e0.

141

0.34

90.

107

0.31

00.

127

0.33

40.

138

0.34

60.

153

0.36

00.

164

0.37

10.

090

0.28

7Fi

rmex

peri

ence

infe

atur

e3.

912

7.75

12.

223

5.56

42.

542

6.03

01.

850

3.27

01.

884

4.46

64.

079

7.80

30.

585

1.60

9C

oncu

rren

ten

try,

sam

epr

ior

indu

stry

2.11

02.

647

1.67

21.

164

2.14

12.

169

2.03

11.

240

2.49

71.

922

2.34

52.

043

1.48

01.

345

Con

curr

ent

entr

y,di

ff.

prio

rin

dust

ry4.

621

4.10

23.

398

2.08

24.

768

3.90

64.

605

1.87

35.

729

3.34

25.

517

3.62

63.

712

2.57

2C

umul

ativ

epr

ev.

entr

y,sa

me

prio

rin

d.9.

249

6.42

47.

339

5.98

06.

444

6.42

49.

124

6.36

37.

308

6.68

011

.429

6.81

14.

153

4.30

3C

umul

ativ

epr

ev.

entr

y,di

ff.

prio

rin

d.17

.345

10.4

8614

.028

9.18

212

.009

10.3

7017

.917

11.7

7615

.581

14.0

4423

.205

13.4

639.

316

8.86

9Fi

rms

from

sam

epr

ior

indu

stry

w/f

eat

9.38

45.

570

7.12

14.

681

7.32

25.

797

7.68

14.

101

7.57

35.

933

10.3

285.

194

4.08

53.

331

Firm

sfr

omdi

ffer

ent

prio

rin

d.w

/fea

t17

.695

9.19

112

.876

6.90

914

.130

10.2

1315

.325

7.46

716

.282

12.3

4220

.655

9.59

29.

845

7.83

6

Con

trol

sM

ean

SD

Firm

size

(log

)5.

054

2.85

8N

on-U

.S.

HQ

0.68

60.

465

Firm

mod

els

onm

arke

t5.

347

5.80

3Pu

blic

0.72

00.

449

InW

ebca

ms

0.15

30.

360

Inca

mco

rder

s0.

246

0.43

1In

SLR

s0.

161

0.36

8B

read

thof

digi

tal

imag

ing

offe

ring

s1.

158

1.22

7Te

chni

cal

capa

bilit

y(l

npa

tent

s)3.

882

2.26

9



higher resolution cameras would not be influencedmore by prior industry peers. Overall, a firm wasmore likely to introduce a feature at a given timeif other firms from the same prior industry werealso introducing it (as opposed to firms from adifferent prior industry), reflecting stronger sharedbeliefs among firms with similar backgrounds thanamong all firms entering the new market.

Hypothesis 2, that firms will imitate other firmsfrom the same prior industry was supported forthree features: LCDs, digital zoom, and high reso-lution. As seen in Models 1, 3, and 4 of Table 6,cumulative previous entry by firms from the sameprior industry had a positive and significant coef-ficient whereas the coefficient on cumulative previ-ous entry by firms from a different industry was notsignificant. The strongest impact was for the digi-tal zoom feature; for each additional firm from thesame prior industry that had previously introduceda digital zoom camera, a firm was 17 percent morelikely to introduce a camera with the feature. Forother features, however, imitation of firms from thesame prior industry was not evident; and, for themovie clips feature, it appears that firms imitatedfirms from other prior industries. While imitationhas proven to be a powerful force in other set-tings, at the level of introducing product features,the results are mixed. It appears in this settingthat shared beliefs from prior industry affiliation,reflected by concurrent entry, had a stronger andmore consistent influence than mimetic behavior.

Technical capability, which we controlled forwith a cumulative count of digital imaging patents,did not have a significant effect on the timingof firm entry into particular features, and includ-ing these controls did not alter our core results.As a robustness check, we also ran models withfeature-specific technical capability measures thatwere created using a smaller, focused set of patentclasses for each feature and the results weresimilar.

Controls for experience with other imaging-related products had a significant effect in somecases. Not surprisingly, a firm’s presence in dedi-cated Webcams was a positive and significant fac-tor that more than tripled the likelihood that a firmwould introduce a camera with Webcam capabil-ity. Presence in the Webcam market significantlydecreased the likelihood of introducing an LCD,optical zoom, digital zoom, and removable stor-age. Since Webcams had no LCDs, zoom lensesor removable storage, firms present in this market

may have had a diminished belief in the value ofthese features.

Other firm controls had the expected effects foralmost all seven product features. With the excep-tion of the optical zoom feature, the more digitalcameras a firm had on the market in a given year,the more likely it was to introduce a camera witha particular feature. Firm size had a significanteffect on introduction of two features, and whetherheadquarters are outside the United States had asignificant effect on only one feature. Whether afirm is public had no effect on entry into anyfeatures. Exclusion of these variables from themodels does not change the primary results. A like-lihood ratio test comparing models that incorpo-rated only control variables with models reportedin Table 6 showed a significant improvement in fit,and coefficients on the control variables were con-sistent across models. (These results are not shownfor space considerations.)

Table 7 shows the results of analyses using neg-ative binomial count models to test Hypothesis 3,assessing whether firm experience with a featurediminishes the influence of prior industry on thecontinued introduction of models with specific dig-ital camera features.

Models 1–5 in Table 7 show strong support forHypothesis 3. For the optical zoom, digital zoom,movie clips, and removable storage features, theeffect of other firms from the same prior indus-try being present in a feature diminished as afirm gained experience with the feature as indi-cated by the negative and significant coefficienton the interaction term (between firms from sameprior industry present in feature and firm featureexperience), and for LCDs the interaction effectwas marginally significant. For instance, for theoptical zoom feature, the marginal effect of onemore firm from the same prior industry presentin the market was to increase a firm’s count ofoptical zoom cameras by 13.8 percent if the firmhad previously introduced only one product withoptical zoom, but if the firm had introduced 10products with optical zoom, the marginal effectof one more peer firm decreased to 9.4 percent.Similarly, for movie clips, the marginal effect ofan additional firm from the same prior industrywent from a 7.8 percent increase to a 3.7 percentincrease in movie clip cameras when a firm’sexperience with movie clips increased from oneto 10 products. Once a firm gains its own expe-rience with a product feature, beliefs based on



Tabl

e6.

The

influ

ence

ofpr

ior

indu

stry

shar

edbe

liefs

and

imita

tion

onin

trod

uctio

nof

digi

tal

cam

era

feat

ures

,C

oxH

azar

dm

odel

CO

EFF

ICIE

NT

(1)

(2)

(3)

(4)

(5)

(6)

(7)

LC

DO

ptic

alzo

omD

igita

lzo

omO

ver

VG

Are

solu

tion

Mov

iecl

ips

Rem

ovab

lest

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eD

ual

Web

cam

capa

bilit

y

H1

Shar

edbe

liefs

:co

ncur

rent

entr

yby

othe

r1.

224∗∗

∗1.

674∗∗

∗1.

340∗∗

∗1.

232

1.44

9∗∗∗

1.29

7∗∗∗

1.87

4∗∗∗

firm

sfr

omsa

me

prio

rin

dust

ry(0

.065

3)(0

.281

)(0

.098

4)(0

.171

)(0

.152

)(0

.087

2)(0

.307

)C

oncu

rren

ten

try

byfir

ms

from

a0.

986

0.97

61.

036

0.89

81.

031

0.99

71.

088

diff

eren

tpr

ior

indu

stry

(0.0

414)

(0.1

23)

(0.0

510)

(0.0

986)

(0.0

694)

(0.0

407)

(0.1

78)

H2

Imita

tion:

cum

ulat

ive

prev

ious

entr

yby

1.09

4∗∗1.

077

1.16

6∗∗∗

1.11

9∗∗0.

915

1.00

71.

032

firm

sfr

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esa

me

prio

rin

dust

ry(0

.045

0)(0

.054

2)(0

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5)(0

.059

5)(0

.058

9)(0

.032

4)(0

.090

9)C

umul

ativ

epr

evio

usen

try

byfir

ms

1.02

10.

983

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60.

982

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3∗∗∗

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026

From

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ffer

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prio

rin

dust

ry(0

.019

7)(0

.031

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.030

3)(0

.016

6)(0

.043

5)

Con

trol

s:pr

esen

cein

rela

ted

mar

kets

Firm

pres

ent

inW

ebca

mm

arke

tin

year

t0.

385∗∗

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978

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70.

270∗∗

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932∗∗

∗

(0.1

42)

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39)

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51)

(0.3

06)

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37)

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904)

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90)

Firm

pres

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ket

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1.33

51.

967

1.06

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823

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140∗

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)(0

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)(0

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)(0

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)Fi

rmpr

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tin

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tal

SLR

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ket

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0.40

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9∗0.

176∗∗

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270∗∗

0.64

10.

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(0.2

35)

(0.2

54)

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17)

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09)

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80)

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56)

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Bre

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tal

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ucts

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90.

925

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432∗

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0.84

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)(0

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)(0

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)(0

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)(0

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)

Oth

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ntro

lsFi

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odel

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ket

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art

1.18

3∗∗∗

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142∗∗

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359∗∗

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137∗∗

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293∗∗

∗1.

099∗∗

(0.0

623)

(0.0

803)

(0.0

504)

(0.0

615)

(0.0

385)

(0.0

503)

(0.0

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Firm

size

(ln)

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297

1.41

6∗∗0.

972

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085

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9(0

.132

)(0

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)(0

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)(0

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6)(0

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)Pu

blic

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pany

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811

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)(0

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)N

on-U

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2.01

0∗∗1.

203

1.22

30.

984

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5(0

.386

)(0

.562

)(0

.646

)(0

.420

)(0

.371

)(0

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)(0

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)Te

chni

cal

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bilit

y(l

npa

tent

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055

(0.0

903)

(0.1

09)

(0.1

14)

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05)

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(0.0

784)

(0.1

60)

Obs

erva

tions

147

211

143

153

173

144

192

No.

fail

4937

4247

5357

27L

oglik

elih

ood

−142

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64.8

−73.

99N

o.fir

ms

6565

6164

6465

59

Dep

ende

ntva

riab

le:

firm

initi

alin

trod

uctio

nof

afe

atur

e,ro

bust

stan

dard

erro

rsin

pare

nthe

ses,

coef

ficie

nts

are

haza

rdra

tios,

the

null

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thes

isis

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the

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tioeq

uals

1.∗∗

∗p

<0.

01,

∗∗p

<0.

05,

∗p

<0.

1



prior industry experience become less important,and the actions of firms from the same priorindustry have less impact. For the dual Web-cam feature (Model 6), a firm’s prior experiencewith the feature had the strongest influence onongoing commitment. The effect of prior experi-ence was negative and significant as one wouldexpect since the dual Webcam feature did notbecome part of the dominant design and waspresent in only 13 percent of new cameras by2006.

We next examine Hypotheses 3 in the con-text of resolution. Once a firm has introduceda camera with higher than VGA resolution, andhas increasing access to information about cus-tomers’ requirements for resolution given theirdesired use of digital images, we would expectthat the introduction of increasingly higher reso-lutions (2, 3, 4 megapixels, etc.) would be lessinfluenced by the adoption of other firms from thesame prior industry. As seen in Table 7, Model7, firm experience, measured as a firm havingpreviously entered a megapixel generation, had astrong positive effect on the likelihood of entryinto a higher megapixel generation. The interactionbetween firms from same prior industry presentin feature and firm experience was also signif-icant and negative (hazard ratio coefficient lessthan one) indicating that the effect of firms fromthe same prior industry present in a megapixelgeneration decreases if a firm has previouslyentered with a megapixel camera, thus supportingHypothesis 3.

Other controls were in the expected direction,with overall number of models a positive and sig-nificant predictor of a firm’s introductions of dig-ital cameras with particular features. A likelihoodratio test comparing the models in Table 7 withmodels incorporating only the control variablesshowed a significant improvement in the model fitwith the addition of our independent variables ofinterest and the interaction variable (these resultsare not shown here for space considerations).

To test the overall robustness of our results,we examined a number of alternative specifica-tions and measures. To test Hypotheses 1 and 2regarding initial introduction of a feature, we alsoanalyzed the data using a piecewise exponentialmodel, which allows the hazard rate to vary acrossdifferent time periods, and the main results didnot change. For all models in Tables 6 and 7, wetried defining the end of the period of ferment as

2002 instead of 2003, therefore excluding all yearsafter 2002 (instead of 2003) and the results did notchange. We also excluded Sony from the analy-sis, since, as a major component supplier for CCDchips, Sony’s expertise may have played a role inthe timing of their introduction of features, andagain, the results were unchanged.

In summary, our results provided general sup-port for Hypothesis 1. We found that concur-rent introduction of a digital camera feature byother firms from the same prior industry was asignificant predictor of entry into digital cam-era features, including LCD, optical zoom, dig-ital zoom, movie clips, and dual Webcam, butnot significant for the high resolution feature. Wefound mixed support for Hypothesis 2. Depend-ing upon the feature, firms sometimes imitatedother firms from the same prior industry in theirchoices of digital camera features. Hypothesis 3was also supported. We found that the influenceof adoption by other firms from the same industrydecreased the more experience a firm has with afeature.

Addressing alternative explanations

We considered several possible alternative expla-nations for our results. First, although our setting isunique in that firms without technical capabilitiescould introduce features that were readily avail-able through the supply chain, one could arguethat firms that did have technical capability mightbe more likely to introduce a given feature. Wetherefore controlled for technological capabilitiesusing firms’ cumulative digital camera patenting.We found that technological capabilities did nothave a significant effect on introduction of fea-tures and that our primary results still held. Asecond alternative explanation might be that somefirms had greater power over their supply chain,and this affected access to particular features, thusinfluencing the timing of introduction. But as dis-cussed earlier, in this setting there were multiplesuppliers for each feature giving all firms access,and such power on the part of buyers is likely tocorrelate with firm size, which we control for inour models. In addition, one could ask whether it isshared beliefs driving our results or whether firmsfrom the same prior industry are just pursuing sim-ilar approaches because these are appropriate (andwill ultimately be correct). Our study addressesthis in two ways: (1) although firms from different



Tabl

e7.

Firm

ongo

ing

com

mitm

ent

toa

feat

ure:

the

effe

ctof

firm

feat

ure

expe

rien

cean

dpr

ior

indu

stry

affil

iatio

n

Var

iabl

eN

egat

ive

bino

mia

lm

odel

with

rand

omef

fect

s:an

nual

coun

tof

firm

new

mod

els

with

feat

ure

Cox

Haz

ard

Mod

el+

(1)

(2)

(3)

(4)

(5)

(6)

(7)

LC

DO

ptic

alzo

omD

igita

lzo

omM

ovie

clip

sR

emov

able

stor

age

Dua

lW

ebca

mca

pabi

lity

Meg

apix

elge

nera

tions

Firm

sfr

omsa

me

prio

rin

dust

rypr

esen

tin

feat

ure

−0.0

050.

110∗∗

∗0.

022

0.05

0∗∗0.

044∗∗

∗0.

032

1.05

1(0

.016

)(0

.029

)(0

.015

)(0

.021

)(0

.016

)(0

.052

)(0

.083

7)Fi

rmex

peri

ence

infe

atur

e(c

umul

ativ

em

odel

st−

1)0.

014∗∗

−0.0

050.

009

−0.0

110.

011∗∗

−0.1

27∗∗

7.53

6∗∗∗

(0.0

05)

(0.0

11)

(0.0

07)

(0.0

12)

(0.0

06)

(0.0

56)

(5.0

83)

H3

Firm

sfr

omsa

me

prio

rin

dust

rypr

esen

tin

feat

ure

X−0

.002

∗−0

.004

∗∗−0

.002

∗∗−0

.004

∗∗−0

.002

∗∗∗

0.02

60.

847∗

Firm

expe

rien

cein

feat

ure

(0.0

01)

(0.0

01)

(0.0

01)

(0.0

02)

(0.0

01)

(0.0

19)

(0.0

727)

Firm

sfr

omdi

ffer

ent

prio

rin

dust

rypr

esen

tin

feat

ure

0.00

40.

044∗∗

0.00

30.

023∗∗

0.01

4∗0.

008

0.83

0∗∗∗

(0.0

08)

(0.0

17)

(0.0

08)

(0.0

11)

(0.0

07)

(0.0

30)

(0.0

409)

Con

trol

s:pr

esen

cein

rela

ted

mar

kets

Firm

pres

ent

inW

ebca

mm

arke

tin

year

t−1

.061

∗∗∗

−1.0

73∗∗

∗−1

.110

∗∗∗

−0.8

45∗∗

∗−1

.045

∗∗∗

−0.0

460.

626

(0.1

97)

(0.3

38)

(0.2

63)

(0.2

19)

(0.2

10)

(0.2

65)

(0.3

39)

Firm

pres

ent

inca

mco

rder

mar

ket

inye

art

−0.0

24−0

.024

−0.0

240.

310

0.17

40.

517

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4(0

.139

)(0

.268

)(0

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)(0

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)(0

.339

)Fi

rmpr

esen

tin

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tal

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ket

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−0.1

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−0.1

800.

654

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(0.1

92)

(0.1

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82)

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Firm

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020

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(0.0

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50)

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(0.0

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(0.0

92)

(0.0

295)

Firm

mod

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year

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072∗∗

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132

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08)

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13)

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08)

(0.0

29)

(0.2

10)

Publ

icco

mpa

ny−0

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6−0

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2∗1.

252

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58)

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Non

-U.S

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Q0.

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50.

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773

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(0.3

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95)

Tech

nica

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pabi

lity

(ln

pate

nts)

0.03

60.

038

0.01

60.

061

0.04

2−0

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∗∗1.

118

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31)

(0.0

51)

(0.0

32)

(0.0

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(0.0

33)

(0.1

31)

(0.0

860)

Con

stan

t1.

804∗∗

13.0

231.

962∗

12.7

870.

905

8.65

9(0

.811

)(4

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16)

(1.1

38)

(353

.258

)(0

.553

)(3

6.87

0)O

bser

vatio

ns17

213

012

212

619

174

440

Num

ber

offir

ms

3731

3544

4627

59L

oglik

elih

ood

−330

.3−2

25.0

−245

.2−2

32.2

−355

.0−8

7.14

−316

.6

Mar

gina

lri

skof

entr

yin

to2M

P,3M

P4M

P,an

d5M

P,st

ratifi

edby

MP

gene

ratio

nan

dcl

uste

red

byfir

m,

coef

ficie

ntis

haza

rdra

tio.

∗∗∗

p<

0.01

,∗∗

p<

0.05

,∗

p<

0.1,

robu

stst

anda

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rors

inpa

rent

hese

s.



industries pursued different approaches, it was notthe case that a particular prior industry was alwaysfirst in adopting the features that would eventuallycomprise the dominant design; and (2) in the caseof the dual Webcam feature, firms in our studyalso pursued the ‘wrong’ feature (i.e., its inclusionin cameras initially rises but then decreases and itdoes not become part of the dominant design) andintroducing this feature was also strongly drivenby prior industry.

Finally, it is important to ask whether firms’choices about features to introduce reflect hetero-geneity in their market positioning strategies ormarketing capabilities—that is, do they seek toserve particular customer niches or take advan-tage of particular distribution channels, which inturn affects their choices of features? Our find-ings suggest this is not the case. As discussedearlier, although there were distinct market nichesin digital cameras, such as the professional andstudio markets, or SLRs, that might correspondwith different sets of features, we focus on firms’choices within the same mass market segmentfor digital cameras. So while marketing capabil-ities might influence a firm’s decision to targetthe mass market as opposed to other segments,we control for that by evaluating choices withinjust the one segment. In addition, the distribu-tion channels for mass market digital camerasincluded broad-based retailers such as Best Buy,that were already carrying analog cameras, com-puters, and consumer electronics such as cam-corders and televisions. It is, therefore, not likelythat firms introduced particular features primarilyto take advantage of different distribution rela-tionships. Moreover, despite heterogeneity in theirinitial choices of features, firms from all priorindustries do converge on a standard constella-tion of features by 2004, suggesting that firms’strategic market positioning choices do not pro-vide an explanation of this process. Thus, while allalternative explanations cannot be explicitly con-trolled for in our quantitative models, the prepon-derance of the evidence indicates that it is likelyour results reflect the influence of shared beliefsand imitation arising from prior industry affilia-tion rather than an unobserved process that leadsfirms to initially introduce the same set of fea-tures.

DISCUSSION

New product markets sparked by technologicalchange are characterized by high uncertainty, inparticular about the characteristics that will ulti-mately emerge as part of a successful dominantdesign. In this context, managers, lacking concretedata about customer preferences, must develop ini-tial product concepts based on their assumptionsabout the emerging market. But how do man-agers develop those assumptions and what explainsthe heterogeneity in their interpretations? Specifi-cally, do firms from different industries differ sys-tematically in the way in which their managersframe a new product concept in a nascent mar-ket? While prior empirical work has documentedhigh technical variety during the early period ofturbulence followed by technical convergence ona dominant design, it has not explored cogni-tive variety and convergence on a dominant cat-egory concept, as reflected in the product featuresfirms introduce as part of the unfolding dominantdesign.

We explored these issues through an in-depthlongitudinal study of the emergence of consumerdigital cameras. Our findings, both descriptive andquantitative, show the important influence of afirm’s prior industry affiliation on framing duringthe nascent stage of an industry. Qualitative datasuggested that photography firms were more likelyto frame a digital camera as an analog camera sub-stitute, consumer electronics firms to frame it as avideo system component, and computing firms toframe it as a PC peripheral. Quantitative analysisof the timing of product feature introductions rein-forced the conclusions of our qualitative analysis.In particular, firms were more likely to introducenew product features concurrent with other firmsfrom their prior industry, reflecting shared indus-try beliefs. The common understanding that firmsdevelop when competing in an industry is, thus,an important source of firm heterogeneity whenfirms from multiple industries converge in a newindustry. We also found that firms imitated otherfirms from the same prior industry in their intro-ductions of some, but not all, product features.Our results imply that firm choices in this instancearose both from common worldviews or mindsetsthat resulted in concurrent action as well as fromsocial comparisons or mimetic behavior. In addi-tion, we found that as firms developed experience



with a product feature, the influence of indus-try background diminished. Thus, beliefs based onprior industry may be less deeply embedded thanother beliefs and not a significant source of long-term cognitive inertia.

Our study makes several contributions toresearch. A challenge in trying to understand therole of managerial cognition is that it is diffi-cult to untangle managerial cognition from firms’capabilities. Behaviors that are assumed to resultfrom managerial mindsets may, in fact, be drivenby capabilities and vice versa. The nature of oursetting allows us to take a major step toward dis-entangling the differential influence of these twofactors. The digital camera features we studiedcould be introduced by firms with little or notechnical capability due to the presence of a well-developed component supply chain and a set ofOEM/ODM firms that could serve as system-leveldesigners. Thus, firms could generally select froma menu of features offered by a range of existingsuppliers. In addition, we used firm-level cumu-lative counts of patents to control for technolog-ical capabilities broadly related to digital imag-ing technologies. Thus, our setting and controlsallowed us to study the outcomes of organiza-tional perceptions about which features to includein a camera, while controlling for firm capabili-ties. Our results, thus, highlight a fundamentallydifferent source of firm heterogeneity. While firmcapabilities/resources are generally important indistinguishing why firms behave differently, wefind that managerial beliefs associated with indus-try experience are also a key factor in how firmsapproach new product markets. Thus, examiningboth capabilities and beliefs is important whenevaluating the competitive landscape, and researchthat focuses only on capabilities or only on beliefs,may reach spurious conclusions. Similarly, man-agers who focus only on competitors’ capabilitiesmay be blinded to differences in how firms applytheir capabilities if they do not also consider theassumptions and beliefs that those firms bring tothe table.

Our work also contributes to research on tech-nological evolution, specifically illuminating theprocesses that underlie cognitive convergence ona dominant design. Despite demand-side featuresbeing an important part of the theory behind theemergence of a dominant design, prior empiricalwork has focused almost exclusively on trackinghow the selection of technologies unfolded in an

emergent dominant design. We document variationand convergence in the demand-side product fea-tures associated with the new product category.Competing perceptions of what a digital camerawould be used for and, therefore, what consumerswould value, converged on a standard set of fea-tures by 2004. Interestingly, the dominant framereflected a combination of the features and usageoccasions associated with the initial photographyframe (removable storage), consumer electronicsframe (LCD and movie clips), and computingframe (digital zoom).

Industry convergence, which can occur when anew technology facilitates the blurring of bound-aries between previously distinct industries, is asignificant phenomenon, given the prevalence ofdigital technology in multiple industries (Green-stein and Khanna, 1997; Yoffie, 1997). But empir-ical research delving into the phenomenon islimited, with exceptions such as Gambardella andTorrisi (1998), who examine whether and howtechnological convergence is related to industry ormarket convergence, and Lee (2007), who exploresthe role of alliances and networks during periodsof convergence. By tracking the dynamics of con-vergence in features that are initially introduced byfirms from heterogeneous industries, we shed lighton these processes.

These results also raise compelling questions forfuture research. In contrast to many settings, inthe digital camera market, start-up firms did notplay a major role—few entered and of those thatdid, none became major players, raising questionsabout the conditions under which entrepreneurialopportunities exist. In the context of digital cam-eras, it might be that the convergence of estab-lished firms from different backgrounds made itmore difficult for start-ups to identify unoccupiedniches or blind spots, resulting in less entry. Itcould also be that the complementary assets of theestablished firms, such as access to distribution,made it difficult for start-ups to compete (cf. Trip-sas, 1997). More work in settings that representthe convergence of multiple industries is neededto systematically address this question.

In cases where start-ups are a primary source ofnew technologies and features, it would be inter-esting to better understand what factors are respon-sible for the heterogeneity in approaches. Founderswho spin off from established firms inherit knowl-edge (Klepper and Sleeper, 2005), and in the med-ical device and automobile industries have been



found to outperform other entrants (Klepper, 2002;Chatterji, 2009). Founders’ backgrounds have alsobeen found to have a lasting influence on firmcharacteristics such as employment models (Baron,Hannan, and Burton, 1999). But this raises thequestion of whether founders also inherit indus-try mindsets, and if so, how does that influenceboth how start-ups conceptualize a new industryand ultimately how they perform?

This study has focused on a specific productmarket that is part of a broader network character-ized by interfirm modularity. Digital cameras donot operate in isolation, but are part of a systemthat includes scanners, printers, software, imag-ing Web sites, and memory cards among otherelements. The emergence of a broader digital imag-ing industry architecture—where modular bound-aries are drawn and where in the system firmscompete—is an important aspect of new industryemergence (Jacobides, Knudsen, and Augier, 2006;Baldwin, 2008; Santos and Eisenhardt, 2009). Aninteresting avenue for future research would be toexamine how different firm backgrounds influencethe preferred industry architecture.

Another valuable area for future work is to bet-ter understand the implications of prior industryaffiliation for firm performance. While researchhas addressed the role of capabilities stemmingfrom prior industry experience, our theoretical andempirical understanding of what influences perfor-mance when firms with distinct industry mindsetsconverge on a new domain is much more limited.In addition, prior research has examined how adop-tion of the dominant design affects firm survival(Suarez and Utterback, 1995; Christensen et al.,1998), but this work has focused on the techni-cal dimension of a dominant design. An inter-esting extension would be to explore how theadoption—and timing of adoption—of the fea-tures that emerge as part of the dominant designaffects both firm performance and survival. Relatedto this question is the issue of whether and howfirms can influence which features become part ofthe dominant design. Existing research has focusedon how firms can influence technological variants,but it may be just as important to proactively shapecustomer perceptions of a new product domain andthus impact what product framing becomes dom-inant. We hope that this paper inspires additionalresearch on these important questions.

ACKNOWLEDGEMENTS

The authors thank Yaichi Aoshima, Juan Alcacer,Carliss Baldwin, Connie Helfat, Rebecca Hender-son, Sarah Kaplan, Andrew King, Dan Levinthal,Cynthia Montgomery, Jan Rivkin, Lori Rosenkopf,J. Myles Shaver, Willy Shih, Harbir Singh, BillSimpson, Mike Tushman, Joel Waldfogel, mem-bers of the Harvard Business School Entre-preneurial Management and Technology andOperations Management units, and seminar partic-ipants from the Consortium on Cooperation andCompetitiveness, Hitotsubachi University, Stan-ford SIEPR, the University of Michigan RossSchool of Business, IESE, the University of Wis-consin at Madison, and the University of Cali-fornia at Irvine for their helpful comments. Wealso thank Hagar Doitel, Margot Hollick, Tal Levy,Avanti Paranjpye, Jim Perry, and Victoria Song forresearch assistance.

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