r1 - toward exemplary research in the management of technology-an introductory essay

8/2/2019 R1 - Toward Exemplary Research in the Management of Technology-An Introductory Essay

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Journal of Engineering and Technology Management, 10 (1993) 7-22Elsevier

Toward exemplary research in th e ma na gemen t oft echnology-An int rodu ctory essayPhilip AndersonJohnson Graduat e School of Management, Cornell Univ ersit y , Ithaca, NY 14853, USA

A bs t r a c t

This article examin es the current status of man agement of techn ology (MOT) as an academicfield of study, and suggests wh at scholars in the area mu st d o to foster its in tellectual developmen t.Attacks on the fuzzy definition of innovation and th e lack of a paradigm governing the field donot identify what mu st be d one to realize progress. The field requ ires widely accepted exemp larsthat permit a transition to pu zzle-solving. Without exemp lars we cann ot identify anomalies, bor-row by analogy from other fields, or form a vibrant research commu nity. Some rules of thum b forgenerating exemp lary research are proposed. The pap ers in this special issue are briefly profiledto highlight the sign posts they provide toward exemp lary research in MO T.

Keywords. Man agement of techn ology; Paradigms; Research commu nities; Theory development

1. In t rod uc t i on

Academics, like most ent repr eneu rs, exploit gaps th at r eflect th e ten or oftheir times. When stagflation dominated the economic landscape in the late197Os, a spa te of papers appear ed t o explain how th is could be so. When ar eassuch as Silicon Valley and the Rout e 128 ar ea of Massa chu sett s experiencedenorm ous economic growth , academ ics flocked to topics su ch as regiona l sci-ence-based development , un iversity-indust ry par tn ership, and entr epreneu-rial networks. The frenet ic takeover an d leveraged buyout ma rk ets of th e 1980smay be partially responsible for the upsurge of publications using agency the-ory to examine managerial incentives.

Similarly, recent dramatic growth in the number of scholars who professint erest in th e ma na gement of technology (MOT) reflects the spir it of th e age.This is an a rea of int erest which ha s emerged principally from t he pra cticalneeds of indu str y for tr ained personnel, not from a brea kthr ough discoverywhich ha s signa lled to a cademics t ha t a fert ile field of explora tion ha s becomeCorrespondence to:Professor Philip And erson, John son Grad uate School of Managemen t, MalottHa ll, Corn ell Univers ity, Ith aca, NY 14853, USA.

0923-4748/93/$06.00 0 1993 Elsevier Scien ce Pu bl ish ers B.V. All righ ts rese rved .


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more accessible or tractable. An interest in technology is tr aceable t o the rootsof most social scient ific disciplines. As Morga n (1980) notes, hu ma ns organ izethought via metaphors, and it is difficult to employ a mechanistic conceptionof anything without viewing technology as a key var iable. Yet th e emergenceof techn ology in r elat ively recent t imes as the prim ar y lever of compet itiveeconomic advant age ha s creat ed a deman d for personnel who can help enter-prises ta ke advan ta ge of technological innovat ion. That deman d more thananything else is responsible for the growth of technology management as anacademic specialty.

The burgeoning of interest in this ar ea is no guara nt ee that it will come toconstit ut e a vibra nt int ellectu al field th at cont ribu tes to social scient ifickn owledge over th e long ter m. Cran e (1972) suggests th at a growth pha se ischa ra cter istic of most scient ific doma ins, th ough its usu al impet us is a specificdiscovery or breakthrough. As a result of rapid growth, specialization arises.Once an ar ea is well-defined, its leaders tend t o defend th eir own ideas andres ist th ose of newcomer s, ma king it difficult to recru it new member s. With outan influx of new perspectives, the field stagnates, because as older problemsare solved, specialists are unable to define interesting new ones, due to theirrestricted intellectual range. Anomalies arise, and scientists abandon fieldsthat cannot produce new approaches to deal with them. In the evolutionaryview of scholar s su ch a s Toulm in (1966 ), specialt ies seldom a dap t via Kuhn iancrisis-an d-response; ra th er, science pr ogresses thr ough t he growth an d declineof hundreds of lines of inquiry, or research programmes (Lakatos, 1970). Thecau tionar y im plicat ion is th at MOT, like ma ny topics before it, ma y prove tobe a fad ra th er than an endur ing featu re of th e intellectu al lan dscape.

The rootin g of th is fields growth in pr actical dem an ds for tr ain ed personnel,rather than in a scholarly breakthrough, creates particular hazards for aca-dem ic inqu iry. As Brief an d Duker ich (1991) note, exhort ing people to con-str uct useful theories m ay impede theory development . Pr actitioners requiremodels that pr edict wha t will be; often , pr edictive power can be obta ined onlyby ta king the par ticular s of a cas e int o accoun t, sa crificing gener alizability an dleading to an infinite regress of cont ingencies. Scholarsh ip adva nces when itis aimed at t heoretically interest ing a nomalies, which may almost definition-ally be un int erest ing t o ma na gers (Davis, 1971). Ca ut ions Van Str ien ( 1978),pra ctical pa ra digms have a way of becoming cau ght up in effort s t o improveprocess consultation knowhow, leading scholarly progress to peter out.

Wha t is th e cur rent sta tu s of MOT? What should scholar s in th is ar ea do tofoster its intellectu al development an d protect it from st agna tion? How do th epapers in th is special issue lead us toward exemplary research in th e man age-men t of technology? These th ree quest ions ar e th e subject of th is int roductoryessay.


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2 . Cu r r e n t p ro b le m s o f t h e fi e ldResear ch in th e ma na gement of innovat ion an d technological cha nge has

been reviewed repeatedly in recent years (e.g. Adler, 1990; Bamberger, 1991;Van de Ven, 1986). Ther efore, th ere is no need for a nother ma pping of th efield, nor does the present venue provide space for an extensive literature re-view. What is needed is an a na lysis of the ma in obsta cles th at sta nd in the wayof scientific progress in this area of scholarship. For criticism of its develop-men t has focused on t wo bar riers to fur th er a dvance, neith er of which corr ectlyidentifies what must be done to realize progress.

The first line of at ta ck is repr esent ed by Bam berger (1991), who highlight sdefinitional dissens us as th e key problem of innovation resea rch. Scholars can -not agr ee how to define an inn ovat ion, how techn ical an d admin istr at ive in-novations differ, or how to generat e a list of innovat ions. Fu rt her more, th emeasu res used in inn ovation stu dies lack demonst ra ted reliability a nd validity.Until consensus over such basic issues is reached, Bamberger argues, innova-tion research will not advance.

Disagreement over terminology and fundamental principles certainly hind-ers th e growth of research, but it is ha rdly fat al. Kuhn (1970a) notes th at basicterms in science (e.g. cell, ma ss, an d elemen t) ha ve cha nged in mea nin gover time. Brya nt (1975) cites a long list of t er ms in sociology wh ose mean ingis the subject of sharp debates. Not the least of these is the term sociologyitself. As Kuh n (1970a) notes, 19t h cent ur y chem ists were able to sha re fun -damen ta l tools su ch as const an t proport ion despite disagreeing about such fun-damen ta l concepts as th e nat ur e of ma tt er. Ultima tely, definitiona l cont rover-sies ar e not resolved by scholast ic deba te but by th e intr oduction of powerfulth eories wh ich favor one set of definitions over an oth er. It is un likely th atprogress will stem from further criticism and debate aimed at achieving defi-nitional consensus among MOT scholars.

The second line of att ack focuses on t he lack of a par adigm cha ra cter izingth e man agemen t of technology. The lack of a par adigm is a sign of an imm at ur ediscipline (Lakat os, 1970). P ra gma tically, th e more par ad igmat ic a disciplineis, the more power it wields within the university and overall scientific com-mu nities (Pfeffer an d Moore, 1980). H ence, ca lls for pa ra digm developm entcha ra cter ize virtu ally all youn g in ter disciplinar y fields of inquir y, for inst an ceent repr eneu rsh ip (MacMillan an d Kat z, 1992) an d inform at ion syst ems (VanGigch a nd Le Moigne, 1989). The cent ra l question is whet her a specialt y suchas MOT can advan ce th eoret ically in th e absen ce of a par adigm. Kuhn (1970a)suggests that in the natural sciences at least, scientific advance cannot takeplace with out a par adigm. However, th e term par adigm ha s been used soloosely by so many scholars that it is difficult to pin down precisely what thelack of one mean s, what kind of obsta cle is creat ed a nd wha t mu st be done tomake intellectual headway.


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Some s ociologists an d organ izat ion th eorist s ar gue th at for th ese disciplines,convergence on a pa ra digm would be dysfun ctional. Daft an d Lewin (1990))for inst an ce, crit icize organ ization th eory for closing too ra pidly on a par adigm(presu ma bly open-systems cont ingency th eory) an d fost ering norma l sciencebefore th e discipline ha s ma tu red. Pre-par adigmat ic th inking, th ey argue, pro-duces scholar s with out prejudice, aler t t o novel phenomena . Oth er scholar s(e.g. Pondy an d Boje, 1981) su ggest th at th e coexistence of severa l pa ra digmsis to be encour aged in organ ization th eory. Morgan (1980) ar gues th at s inceno one metaphor can capture the totality of organizational life, theorizing issimply a subjective enterprise concerned with generating one-sided views oforganizational life. Hence, it is healthy for many metaphors to co-exist, anddanger lies in accepting any one par adigm a s a more concrete represent at ionof organizations than another.Is th e lack of a par adigm cha ra cterizing MOT a virtu e or a barr ier to prog-ress? To understand why paradigms are crucial to the health of the field, wemu st distinguish what a par adigm is an d is not. As Ha rvey (1982) ha s noted,too often th e word pa ra digm is used loosely a s a way of const ru cting ar bitr ar ypigeon-holing schemes for s ets of ideas. The cru cial point is th at a par adigm isnot simply a theoretical perspective or way of analyzing the world. For in-sta nce, Marxism is not a paradigm; neither is str uctur al-fun ctiona lism. Suchth eoretical orient at ions are better un derstood as th emat a (Holton, 1975 ), fun-da men ta l presu ppositions or ways of viewing th e world. Un like perspectives,paradigms never characterize an entire scientific discipline (Eckberg and Hill,1979).

Building on Masterman (1970)) Eckberg and Hill (1979) distinguish threetypes of beliefs referred to by th e ter m pa ra digm. Fir st , met a-par ad igms a reepistem ological viewpoint s which act as un quest ioned presu ppositions sha redby members of a discipline. For instance, logical positivism is the meta-para-digm tha t cha ra cterizes most work in organization th eory a nd the ma na gementof technology. Second, a disciplinar y mat rix (Kuhn, 1970a) en compa sses t heshared generalizations of a specialized community within a discipline. Thisincludes symbolic gener aliza t ions (e.g. action equals rea ction), models whichsupply th e group with preferr ed an alogies/meta phors, an d sha red values. MOTlacks a disciplinar y m at rix, which is why it is not yet a discipline. Th ird, an dmost import an t, is th e exemplar, which is th e most centr al m eaning of a Kuhn-ian par adigm.

An exemplar is a concret e pr oblem-solut ion th at sh ows scient ists by exam-ple how their job is to be done. However, Mast erm an (1970) suggests th at it isless importa nt to un derstand what an exemplar is tha n what it does. I t allowsthe members of a research community to solve puzzles by using a picture ofone thing to represent another. By doing exemplary problems the student ac-quires the ability to see several different situations as being like each other.Kuhn employs t he example of Newtons second law, which st at es th at force


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equa ls ma ss t imes accelerat ion (F= ma ). Th e st uden t of physics comes to seeth at such appa rent ly dist inct problems as th e ra te of fall of a body or th e heightof a swinging pendulum are all solved the same way, using the second law.What one a cquir es by work ing thr ough exemplary problems is a facility foran alogy, in t his cas e a way of seeing tha t a problem can be solved by a pplyingthe second law. The student acquires this facility by being shown situations inwhich other scientists solved problems by drawing an analogy to an exemplarysolution (Kuhn, 1970a).

Thus to say th at MOT lacks a par adigm is to say, most import an tly, t ha t itlacks widely accepted exemplar s. Without exemplar s, a field of inqu iry canconfront problems bu t it can not genera te a nd solve puzzles. Pu zzle-solving isthe unique activity that characterizes normal science. Without puzzle-solvingth ere is no norma l science, an d with out norm al science, th ere is no scient ificprogress (Kuhn, 1970a). The key distin ction between puzzle-solving an d prob-lem-solving is th at in the form er case, it is known th at a solut ion exists. Thedetails of working out the solution require cleverness and ingenuity, but thepar adigm (in th e form of an exemplar) provides n ot only ru les specifying a naccepta ble solut ion but also a tool for solving t he puzzle plus a descript ion ofhow th e tool is t o be applied (Mast erm an , 1970).

Master ma n suggests th at th e exemplar int erpret at ion of par adigm an-swers th e quest ion th at P opperia n models of scient ific developmen t can not-how do new area s of inquiry em erge? For a pre-par ad igmat ic specialt y such asMOT, th is is a cru cial question. Master ma n ar gues th at in th e beginning, afield is cha ra cter ized by a tr ick, an embr yonic technique plus an insight ap-plicable to the field. Later, through mathematization and the development ofexperiment al procedures, th is beginning is elaborated into a set of ha bits tha tcha ra cter ize a comm un ity of scholar s. But in th e beginning a combina tion ofinsight a nd techn ique allows puzzle-solving by applying t he tr ick in a nu m-ber of settings.

Eckberg a nd Hill (1979) cite as an illust ra tion th e cognitive dissona nce r e-search progra m. Once t he insight was un derstood, similar experimenta l t ech-niques were applied to dozens of situations in which one might expect disso-nance, generating and solving a large number of puzzles. To this illustrationwe might a dd th e applicat ion of game theory in economics. The insight is th atdynamic problems with asymmetric information can be modeled while retain-ing st rict ind ividua l-level ra tiona lity as sum pt ions . The tr ick is using back-ward induction to locat e a Nash equilibrium. It h as been employed again andagain in extra ordin ar ily clever wa ys to solve puzzles, economic situ at ions whichotherwise appear intractable. Similarly the insight that characterizes popula-tion ecology in organ ization th eory is th at t he ent ry an d exit of firm s, ra th erth an t he ada pta tion of firms, may drive tr an sforma tions in populat ions of or-gan izations. Th e tr ick is to ana lyze exit ra tes with event -hist ory techn iquesthat employ spell splitting to examine the effect of time-varying covariates.


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It has been used to study a wide variety of influences on organizational exitrates .

These inst an ces illust ra te the key role of exempla rs in gett ing a field off theground by ma king puzzle-solving possible. As Eckber g and Hill (1979) em-pha size, a par adigm is not simp ly a th eoret ical pers pective. Ongoing pu zzle-solving occur s only when a group exists which shar es a consist ent body of be-lief. Thr ough long-term tu telage via exempla r, st udent s lear n where to look forpuzzles. In the above examples, puzzles are situations where the insight-and-technique of cognitive dissonance, game theory, or organizational ecology di-rects scholars t o seek applicat ion of th e exemplar , secur e in th e knowledge th ata solut ion probably exists if th e resea rcher applies th e tool in a clever enoughway. The exemplar directs at tent ion to a set of puzzles th at it is well-suited toattack, permitting cumulation and refinement of the paradigm through re-peated applicat ion in different sett ings. This is why paradigms n ever chara c-ter ize ent ire disciplines, becau se exten ded puzzle-solving is not possible at sobroad a level.

The core argument of this paper is that the lack of exemplary research inMOT creates three specific obstacles to scholarly progress which must be ad-dress ed. Fir st , without exemplar s we can not det ect a noma lies. Second, withoutexemplars it is difficult to progress via analogy and to provide analogies thatwould cause other fields to draw upon this one. Third, without exemplary re-search, it is impossible for a genuine invisible college, a research community,to coalesce around th is area of inquiry. The suggestion th at MOT needs a par -adigm does not t ell us wha t t o do. As Kuhn (1970b) notes, social scient istscan not improve t he st at us of their field by legislat ing agreement on fun damen-ta ls an d th en tur ning to norm al science. Following Mas ter ma n (1970), it ismore importa nt for scholar s in th is ar ea to grasp what an exemplar should dothan to debate what it should be.

One of th e most import an t th ings th at n orm al science puzzle-solving achievesis to m ak e it possible for s cholars to det ect an oma lies. It is th e recognition ofan oma lies th at is th e corn erst one of genuine scientific progress. An an oma lyis more than simply a result we did not expect. All sciences, even the mostpar adigmat ic, cont ain inconsisten cies and a re un able to explain a wkward facts(Mast erm an , 1970). These a re difficult ies th at s cient ists in para digmat ic fieldsexpect t o clear up event ua lly. An a nomaly poses a more serious cha llenge-nodismiss al or post-hoc explan at ion su ffices t o rest ore th e overall theory t o plau -sibility. The only wa ys t o explain it with in t he confines of existin g theory woulddest roy th e elegan ce of th ese theories. When th e logical exten sion of th e exist-ing par adigm leads to para doxical resu lts, th e th eory collapses, an d only in th isway do better th eories m ake th eir appear an ce.

Why is norm al science puzzle-solving based on exemplar s a prer equisite fordetecting an oma lies? The reason a nomalies ar e observed is th at norma l sci-ence has pushed the exactitude and scope of observation forward to such an


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extent th at one k nows with precision th at t he resu lts one expected did notoccur . If one does n ot kn ow with precision wha t t o expect, it is easy to at tr ibut e(post hoc) sur prising resu lts to an overlooked cont ingency, dism iss th e un ex-pected finding a s an ar tifact of inexactly opera tionalizing a cons tr uct, or ac-coun t for th e discrepan cy as measurem ent error. This is precisely the st at e ofMOT (an d ma ny social science specialties) today. Tru ly coun ter -intuit ivefindings ar e difficult to ima gine, becau se t her e is no body of work t ha t a ppliesthe same insight to many different areas. Cognitive dissonance theory, for ex-am ple, ha s worked so well in so man y situ at ions th at were it clearly shown notto hold in a sett ing wher e it ought to, we would kn ow we were ont o an import an ttr ail. This can not ha ppen when an unexpected finding merely ru ns coun ter toan observation th at ha s been shown to hold in one or two insta nces.

With out a para digm, ther e can be no an omaly. Fur th ermore, the history ofscience su ggests th at an oma lies a re usu ally observed before th ey ar e recog-nized. In par adigma tic fields, scient ists wr ongly dism iss puzzling findings be-cau se they a re un able t o shed a certa in world view. Eventu ally, th e persistenceof these findings causes someone to reconstruct the paradigm in order to ex-plain t hem; when an an oma ly is explained by a new theory, it is th e basis for apar adigm sh ift. However, in pre-par adigma tic fields, th e an oma lous observa-tion is not even recognized as posing a threa t t o a theory system. It is entirelypossible tha t MOT scholar s ha ve alrea dy produced some of th e most import an tobservations of th e next t wenty years, an d ha ve dismissed them or failed torecognize their significance because there was no exemplar to indicate thatthey posed critical problems.

The second obst acle th rown u p by th e lack of exemplar s is th e inability toprogress via an alogical borr owing. A par adigm is more th an just a tool. It isa lso a way of seeing, a concrete pictu re of a thin g (A) us ed to descr ibe an otherth ing (B) (Mast erm an , 1970). For example, mu ch progress in decipherin g thegenetic code depen ded on seeing th e code as a langua ge, an d thus dr awing uponlinguistic concepts such as gramm ar an d synt ax. Similar ly, organizations ar eclearly not biological organisms, but biological analogies have allowed popu-lat ion ecologists t o tr an sport highly useful meth ods and concepts (e.g. mu -tu alism, densit y-dependen t selection) from one arena to th e oth er.

Pickering (1980) suggests th at a n exemplar is th e concret e embodiment ofan a na logy. It is a paper or collection of pap ers t ha t m ak es a conn ection be-tween a n esta blished body of kn owledge an d a problem on th e front ier ofknowledge. It pushes science forwa rd by bringing to bear conceptu al an d met h-odological appar at us inh erited from a differen t specialt y. Pickering cites theexample of a new area of physics which languished for five years until it wasdemonst ra ted t ha t well-known meth ods from quan tu m electr odynam ics couldbe applied to elabora te th e novel th eory. It is th e ability of an exemplar to helpus draw conn ections between what we know an d what we wish to know tha thelps normal science progress rapidly.


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Conversely, one sign of a vibra nt field is th at its exempla rs serve as ana logiesupon which other specialties draw. The success of neural science has contrib-uted heavily to the development of neural network concepts in computer sci-ence. The insight s provided by pun ctu at ed equilibrium models of paleontologyha ve led both organ ization th eorist s an d political s cient ists to propose an alo-gous models in their fields. The emerging science of chaos is providing a richseries of models which oth er disciplines ar e exploring as ways to explain an om-alous findings. Th e aim of th ose who would ma ke MOT a discipline sh ould beto develop exempla rs t ha t not only explain how technology is ma de ma na gea-ble but which also prove useful for oth er specialties t o borr ow as tools for fra m-ing an d solving a differen t set of puzzles.

The third obstacle to progress posed by the lack of exemplary research inth is field is th at with out exemplar s, a resear ch commu nity can not coalescearound a problem. Kuh n (1970a) ma kes th e pivota l point t ha t a par adigmgovernsnot a subject m at ter but a group of scholars . There can be no para digmcha ra cter izing t he topic of technology ma na gement . Th ere can only be exem-plars that provide shared understanding to a group of scholars interested inth e subject. Asking wh ere th e field is an d wher e it is going is simply a short ha ndway of ask ing how th e communit y of scholar s who sh ar e th is specialty isevolving.

Every resear ch ar ea cont ain s t wo types of subgroups (Cra ne, 1980). Thefirst is groups of collaborators, who interact with each other face to face andoften co-author papers with one another. In MOT, the Minnesota InnovationResearch Program (Van de Ven and Associates, 1988) has spawned such agroup.The second subgroup is th e commu nicat ion network t ha t links groups ofcollabora tors. After Pr ice an d Beaver (1966), th is is ter med a n invisible col-lege, since it s mem bers ar e tied together by reading each others pap ers, notnecessar ily th rough pers ona l cont act. Such invisible colleges ar e net workswhose m embers a re fam iliar with each oth ers work and with a core str eam ofprevious work s th at ha ve influen ced t he definition of th e problem class and itsboundaries. The confines and dynamics of research communities have beenst ud ied th rough co-cita tion ana lysis (Gar field, 1979); Klava ns (1991) pro-vides an interest ing overview of this literat ur e and of the r esearch comm un itiesmost centr al to scholar s who stu dy techn ology man agement.

Research commu nit ies typically coalesce a round a set of jour na ls, one ofwhich is th e most centr al in th e co-cita tion net work . Some r esear ch comm u-nit ies become ingrown a nd isolat ed: a sma ll group of resea rcher s ends up talk -ing to each other bu t not t o a broader comm un ity. Most of th e cita tions toarticles in their central journal are from other articles in the same journal,which have litt le impa ct elsewhere. The consequ ence-regar dless whether theyagree upon a par ad igm-is typically sta gna tion an d decline. In cont ra st, vi-bra nt fields ar e densely conn ected to oth er r esear ch comm un ities. They em -


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ploy cutting-edge developments in related invisible colleges while producingnovel facts an d explan at ions th at in tu rn pr ovide grist for th e mill of oth erresearch programs.

Klavans an alysis suggests th at to dat e, resea rch comm un ities focusing solelyon issues rela ted to technology ma na gement (e.g. th e ma na gement of resea rchan d developmen t) ha ve been isolat es. No ident ifiable in visible college has yetcoalesced a round t he problem class of technology ma na gement ; inst ead, schol-ar s in this ar ea have published th eir work in jour na ls which ar e par t of oth ernetworks, principally devoted to other domains.

The pr imar y r eason for t his s ta te of affairs is th e lack of widely acceptedexemplar s. Ther e is no invisible college in MOT becau se t her e is no set ofpapers t ha t provides a model or guidepost for oth er r esearch. What mu st emergefor th e field to pr ogress is a body of kn owledge which mem bers of a comm unit yma ster , refer to, and build upon. A research commu nity can not ar ise th roughth e esta blishmen t of social t ies, th e foun ding of a professiona l society, or th eestablishmen t of a jour na l. What is required is widespread agreement t ha t apar ticular exemplar-an insight combined with a techn ique tha t defines puz-zles an d suggests potent ially profita ble an alogical borr owings-is a model forresea rch wort h doing in a variety of sett ings. A jour na l or professiona l orga-nizat ion or social net work can facilita te t he emergence of th at consen sus. How-ever, th e presen t situ at ion in which MOT ar ticles seldom cite each oth er orsha re comm on references will cont inue un til th ere appea rs some common bodyof knowledge which one must master to carry out leading-edge research intechnology management.3. How can t he fi e ld p r ogres s?

Int ellectu al progress in th e ma na gement of technology depends prima rily onour ability to generate exemplary research. Simple continued cumulation ofexisting lines of resear ch will not s uffice. We n eed exemplar s t o help us ident ifyanomalies, develop useful analogies that permit us to draw upon existing bod-ies of knowledge, and provide a focus for the emergence of an invisible collegewhich bu ilds upon a core st rea m of art icles while rema ining densely conn ectedto oth er resear ch comm un ities. Such exemplars a re problem-solutions th atserve as models wh ich can be a pplied to a wide var iety of doma ins.

How and wher e can such seminal problem-solut ions ar ise? Ther e is no for-mu la by which we can produce t hem ; puzzle-solving models ar e not t hem selvesth e solut ions to higher-order puzzles. One possibility is simply to borr ow u sefulexemplars from other areas. Hence, one could ask what would happen if tech-nology ma na gement were merely a repea ted ga me, or if innovation projectswere ana logous to genes, or if technology could be thought of as a cult ur alsymbol system to be deconst ru cted. The genera l problem with this st ra tegy isthat the more powerful the analogy is, the less it can support a distinctive


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academ ic specialt y. Suppose for exam ple th at a ll problems in technology ma n-agem ent could be modeled gam e-theoret ica lly a s economic choices. MOT wouldsimply become a topic ar ea with in economics. Genu ine a cademic specialt iescan seek inspirat ion from exemplars in oth er a reas, but cann ot borrow t hemwholesale.

For guidance on how to do exemplary resea rch, we ma y tu rn t o recent worksexam ining th e psychology an d sociology of discoverin g. This line of resea rchha s been pioneer ed pr incipally by h istorian s an d philosophers of science, whohave ask ed wheth er th ere is a pat tern to insightful discoveries across scient ificdisciplines an d problem ar eas. No clear pictu re ha s emerged tha t t ies togethera lar ge nu mber of diverse discoveries, but some int erest ing ru les of th um b ha vebeen p roposed.

Oliver (1991) provides a rich illus tr at ion of one of th e grea t par adigm sh iftsof th is cent ur y, the emer gence of plat e tectonics as th e dominan t way of view-ing geology. F rom his experience as a geologist, h e empha sizes th e importa nceof origina l observat ion. Fir st , he suggests th at n ew observat ions of import an tphen omena alm ost always produce sur prise an d discovery. For example, thefirst geologists t o explore th e sea bed were almost ass ur ed of finding someth ingint erest ing (an d in fact a noma lies discovered on th e ocean floor led t o plat etectonics). Second, he argues th at t he most consist ent ly successful way to ma kediscoveries is to bring instr um ents and m easur ement techn iques from onebranch of science into a different branch for the first time. Again he empha-sizes th at th e ability to observe phenomena no one else ha s ever seen is th emost likely way to produce an exemplary discovery. Third, he urges scholarsto learn what the majority of scholars in an area are doing, not to criticize oremulat e the ma instr eam bu t t o ask what is being overlooked. The discoverersof plate tectonics focused on the sea bed while most other geologists concen-trated exclusively on the land.

Root-Berns tein (1989) ar ticulat es no fewer th an 43 prin ciples, or ru les ofthumb, for maximizing discoveries. Of these, six seem to be most useful forMOT scholar s. Firs t, he suggests th at discoveries a re most likely in area s ofgreatest ignorance. Second, areas undergoing rapid change are most likely toproduce breakthroughs. Third, previously well-plowed fields that have beenabandoned can be fertile sources of discovery later, when new techniques andinsight s a llow us to view th em in fresh ways. Four th , seek ar eas where theoryand da ta appea r to cont ra dict, especially where the cont ra diction ha s beensmooth ed over in an a d hoc way. Fifth, look for wha t is said to be impossible.Sixth, look for the intersection of different lines of inquiry.

Applying th ese heur istics to MOT requ ires us to specify roughly what t hedoma in of the field is, what ar e its boun dar ies. With out an idea what th e fieldcont ains, we can not know wha t observations have been made, what t he ma in-str eam is doing, with in wha t ar eas ignoran ce is maximal or chan ge ha s beenmost rapid, where different lines of inquiry might intersect. Any mapping of a


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field is boun d to be incomplete and pa rt ially a ma tt er of ta ste; as with mostma pping exercises, th e chief benefit is th e process, not th e resu lting doma indefinition. Certain ly no claim is ma de tha t t he pictu re present ed h ere is objec-tive or compr ehen sive.Na rr owly, t echn ology is an y mea ns of accomplish ing a ta sk; shoveling d irtis a technology. By incorpora tin g engineering an d technology ma na gement , werest rict our domain to techn ologies embodied in products or processes t ha trequ ire some engineerin g/scient ific kn owhow to compr ehen d. We fur th er re-strict our domain to cases where some uncertainty and choice are involved,technologies need to be man aged when th ere ar e alt ern at ive ways of effectinga product or process a nd technical explora tion is required to un dersta nd th ena tu re and limits of th e altern at ives. In such cases, MOT principally addr essesth ree levels of ana lysis: who car ries out t echn ical explora tion, how it is car riedout , and what its impact is on t he organizat ion an d its environment .

At t he first level of an alysis, MOT focuses on individual a ctors an d th eirdecision pat tern s. The principal question is what pr actices optimize th e inn o-vat ive capa bility of individua ls involved in techn ical explora tion; illust ra tivetopics include managing technical careers, motivating technical professionals,an d renewing capabilities an d competen ces. At th e second level of an alysis,MOT concentrates on ways of organizing technical exploration routines. Illus-tr at ive topics include ma na ging a cross-fun ctional technology developmen tteam, organizing an R&D laboratory, designing products for manufacturabil-ity, or transferring knowhow from one area to another. At the third level ofan alysis, th e field is concerned with st ra tegic ma na gement , h ow techn ologyaffects t he organ izat ion-environm ent fit. Illust ra tive topics include how tech-nology evolves, how sta nda rds em erge, how differen t techn ologies int era ct sy-ner gistically, how techn ological subs tit ut ion ta kes place, an d how techn ologi-cal chan ge alter s ma rket a nd compet itor relationships.

In which of th ese area s is exemplary research most likely to a ppear, an d howma y we impr ove th e odds of doing exemplar y r esear ch? A useful h eur istic mightbe to apply ru les of th um b for gener at ing d iscoveries t o th e gener al ar eas of.study outlined above:

l Make new observations of important phenomena, perhaps by using in-struments imported from other branches of science. At the individual level,cognitive ma pping t echn iques developed in social psychology might perm itgenuinely original observations. At the organizational level, efforts to trackthe explicit timing and sequence of events (e.g. Van de Ven and Associates,1988) have produced new data that seem quite promising. At the strategiclevel, a long-sta nding model su ggests that following th e emergence of a domi-na nt design, process inn ovation should exceed product innovat ion, yet no oneha s creat ed a metr ic by which th is assertion could be test ed.

l Seek th at wh ich is being overlooked, explore th e sea bed when oth ers a reexploring the land. At the organizational level, for example, most attention is


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focused on innovation project teams. An opportunity exists to examine tech-nical exploration via other avenues. At the strategic level, breakthrough in-novations ha ve received consider able at ten tion at the expense of innovat ionswhich might have been discontinuous advances, but which failed to substitutefor the technologies they were intended to supplant.

l Search in th e ar eas where ignoran ce is greatest . As Bamberger (1991)suggests, we kn ow very litt le about how product an d process innovat ions differor how technological adva nces depend on complemen ta ry brea kt hr oughs whichma y be adm inistra tive innovat ions. Examining th ese fun damen ta l sour ces ofignorance th at str ike at th e heart of what innovat ion is ma y be an importa ntavenue toward pr oducing exemplary research.

l Search in ar eas cha ra cterized by r apid cha nge. Due t o gam e-th eoretican alysis, models incorporat ing net work externa lities a nd the development ofstandards have far outrun empirical observation testing their implications.Similar ly, cognitive processing models based on neu ra l science ha ve developedra pidly without cau sing MOT scholar s to re-thin k how individual techn icalprofessionals conceive of innovations.

l Re-examine ar eas th at were aba ndoned years ago as well-plowed. An in -ter estin g example her e is J elinek a nd Schoonh ovens (1990) ret ur n to th e orig-inal Burn s and St alker (1961) suggestion th at organic organization is requiredin an innovat ive milieu. Through field stu dies in Silicon Valley, th ey foun dthat innovative firms deviate significantly from the organic model, leading tointriguing insights about organizing for innovation.

l Seek areas where th eory cont ra dicts dat a or where dat a ar e cont ra dictory.For example, th eory suggests th at older techn ologies appr oach per form an celimits with mat urity; data suggest tha t t hese limits a re demolished when a newtechn ology appear s as a compet itive th reat . Theory suggests th at increment alprogress accounts for the majority of technical progress, but data suggest thisis often not th e case. Cont ra dictory dat a seem to imply that pioneering tech-nologies somet imes confer first -mover advan ta ges and somet imes do not. Con-tr ad ictions suggest th e possibility of producing an exempla ry solut ion whichbecomes widely accepted because of its ability to bridge an apparent paradox.

l Examine th at which is th ought impossible. It ha s been suggested th atbehind every innovat ion sta nds a product or process cha mpion, th at innova-tions can not pr oceed with out cha mpions. Diffusion th eory suggests th at thera te of diffusion can never become negat ive. Economic th eory suggests th at itis impossible for incompa tible techn ologies to achieve significan t ma rk et pen-etration in the presence of strong network externalities. Examining such im-possibilities ma y be a route t o producing powerful discoveries.

l Exam ine ar eas wher e lines of inqu iry int ersect. For exam ple, both micro-level an d orga nizat ion-level th eorist s a re int erest ed in how skills an d compe-tences are built up and transferred via individual or organizational learning.


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In such cases , an opport un ity for d iscovery ar ises when one in dividual is broadenough to bridge the gap between differing perspectives or units of analysis.

In sum ma ry, no ana lysis can p redict t he direction in which MOT will evolve.Rath er, it is hoped th at by sensitizing a potent ial commu nity to the need forexemplary research a nd su ggesting how it might be generat ed, the developmentof model problem-solut ions can be encour aged an d rea ders might be st imu lat edto think about why the problems that interest them might lead to suchbreakthroughs.4. R e s e a rc h i s s u e s i n t h e m a n a g e m e n t o f t e c h n o lo g y: Pe r s p e c t i ve s a n dm o d e l s

In th is first special issu e of the J ourn al of En gineering and Techn ology Man-agement, we sought papers that point toward ways in which exemplary re-sear ch m ight develop. Th is set of art icles is also mea nt to provide some insightint o dir ections in which t he invisible college of techn ology ma na gemen t schol-ar s is likely to evolve. Th e work s in t his issu e collectively st imu lat e th ough tabout wha t types of issues will occupy th e technology ma na gement resea rchcommu nity, what t ypes of methods its members will employ, an d what otherresearch programs its members will rely on for inspiration and will in turnprovoke with novel findings and interpretations.

Andrew Van de Ven encourages members of this invisible college to focus onhow novel technologies ar ise from a social infra str uctu re t ha t incorpora tes notonly t he st ru ctu re of an emerging indust ry but also basic societal endowmentsand inst itut iona l a rr an gements. This research illust ra tes th e power of speci-fying what is being overlooked, an d how MOT might benefit from exploitingint ersecting lines of inquiry. His work s uggests th at technology ma na gementscholars must be conversant with and will contribute to sociological researchprogra ms str essing how int erorganizational ties ar e formed an d, subsequently,constrain the life chances of individual enterprises.

Leona rd Lynn , Henry Piehler, and Mar k Kielers ar ticle illustr at es th e po-ten tia l of lar ge-scale, cross-cult ur al sur vey resea rch. This work su ggests th epower of being the first to make new observations of important phenomena.Exam ining car eer pat ter ns an d inform at ion flows, th ey un cover a novel factand suggest an original interpretation of Japanese engineering careers: whatwould be the consequences of developing a cadr e of older professiona l gat ekee-pers ? And wha t a re th e degrees of difference in pra ctices between t he U.S. andJapan? This paper demonstrates that scholarship in careers and communica-tion networks will continue to stimulate investigations into technologymanagement.

Stephan Schrader, William Riggs, and Robert Smith bring the heritage ofresearch in problem framing and solving to bear upon the way in which tech-nical pr ofessiona ls app roach t echn ical puzzles. Their pa per proposes n ew link-ages between technology resea rch and th e litera tu re on decision-mak ing, prob-


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lem-solving, and lear ning, keying on th e way in which techn ical problem solversth ink about th e degree of un certa inty an d ambiguity inheren t in the task s th eyun derta ke. The th ru st of th is work is to suggest a way to bring mea sur ement sfrom another branch of science to bear on MOT; those who build on this re-search are almost assured of making novel observations.

Na ncy DiToma so, George Fa rr is, an d Rene Corder 0 retu rn to a classic workon scientist s in organizations to ask wheth er its cha ra cterization of productiveresearch climates holds in an era where American males constitute an ever-shrinking fraction of the scientific work force. The thrust of their work is toheighten our sensitivity into the ways in which changing work force demo-graphics might alter long-held assumptions in our field. It conveys a sense ofthe insights that arise from returning to fields that were thought to be well-plowed with fresh insight s a nd original qu estions. It also suggests th at tech-nology ma na gement may in th e fut ur e more strongly dra w from a nd cont ributeto the research program of social demography.

Fr an k Dubinsk as employs eth no-met hodological techniqu es to genera te novelobservat ions in an area of relat ive ignora nce, h ow developmen t projects ac-tually evolve. He generates two powerful metaphors, the vat and the funnel,which in turn provide analogies for other specialties seeking to borrow ideasfrom MOT. This work illust ra tes th e way in which persona lly exam ining ph e-nomena th at ar e usu ally report ed a t arms length can lead to int riguing andoriginal insights.

Michael Hitt, Robert Hoskisson, and Robert Nixon build upon one of themost important emerging themes in strategic management, how organiza-tional capabilities create value. This is an area experiencing rapid advance ina relat ed field wher e th e int erest s of resea rcher s at all th ree levels of technologymanagement intersect. The authors propose a novel point of view on the valueof cross-fun ctional int egrat ion, a rguing th at its benefits ma y be pa rt ially in-direct an d cont ingent . Their work su ggests th at t he tr emendous growth of re-sear ch in stra tegy an d in technology ma na gement is likely to proceed ha nd-in-han d, since so man y issues centr al t o both intert wine.

Collectively, t hese paper s provide a sense of wher e the t echn ology ma na ge-ment research comm un ity sta nds and h ow it is evolving. Each paper illust ra tesa way of doing r esear ch in MOT th at can lea d to import an t discoveries a ndexemplary research. They provide interesting templates for those who wouldrea ch toward th e types of puzzle-solut ions th e field requ ires at th is sta ge of it sdevelopmen t. They also suggest which oth er fields ar e likely to be most closelylinked to th e invisible college of techn ology ma na gemen t. F or MOT to becomea giving specialty, an area from which these linked fields draw inspiration andwhose work th ey cite, we mu st develop exemplar s which by an alogy illum ina tea variety of problems an d show how to solve th em as puzzles. The ar ticlescollected her e serve as prototypes an d guideposts for th ose whose r esear ch wouldprovide th e foun dat ion for such an achievemen t.


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r1 - toward exemplary research in the management of technology-an introductory essay

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