Competition in a Multimarket Environment

7/28/2019 Competition in a Multimarket Environment

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Competition in a Multimarket Environment: The Case of Market Exit

Author(s): Warren Boeker, Jerry Goodstein, John Stephan and Johann Peter MurmannReviewed work(s):Source: Organization Science, Vol. 8, No. 2 (Mar. - Apr., 1997), pp. 126-142Published by: INFORMSStable URL: http://www.jstor.org/stable/2635306 .

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Competition in a MultimarketEnvironment: h e C a s e o f M a r k e t E x i t

Warren Boeker * Jerry Goodstein * John Stephan * Johann Peter MurmannLondon Business School, Sussex Place, Regent's Park, London, United Kingdom, NW1 4SAWashingtonState University,Vancouver, Washington98663University t Buffalo/SUNY, Buffalo, New York14260Columbia University,New York,New York10027

T his paper exploreshow multimarketheorychallenges he normalassumptions f competitionnindividualmarkets.Using a sample of hospitals, the authors found that the degree to whichcompetitorscompete in similar markets has a negativeeffect on market exit. Organizationshatcontract or servicesand consequently ace fewer internalbarriers o exit are morelikelyto exitfromservicemarkets. John W.Slocum,Jr.

AbstractStudies of competition typically have two underlying assump-tions: that competition occurs within the boundaries of indus-tries or markets and that all firms in a market or industry areaffected equally by competitive pressures. The concept ofmultipoint competition challenges both assumptions. Multi-point theory addresses how different levels of contact be-tween firms across multiple markets affect competition inindividual markets. Its main argument is that high levels ofcontact between firms across markets will induce mutualforbearance, causing multipoint competitors to refrain fromaggressively attacking each other.The restraint stems from the fact that high levels ofintermarket contact enable a firm to respond to an aggressiveaction by a multipoint rival in markets other than the one inwhich the action takes place. That possibility raises thepotential costs of aggressive moves and serves as a credibledeterrent, especially if a firm can respond in several markets.In addition, multipoint competition helps firms to interprettheir rivals' intentions and signal their own, reducing thelikelihood of costly misunderstandings.The authors elaborate on those ideas to examine how ahospital's degree of intermarket contact with its competitorsin a particular service market affects the likelihood that itwill exit that market. They find that hospitals are less likelyto exit markets in which they meet large numbers of theirmultipoint rivals. As a result of mutual forbearance, competi-tive rivalry is reduced across the markets that multipointrivals share, lessening the types of pressures that typicallyprompt market exit. With lower levels of competitive rivalry,markets shared by multipoint rivals are relatively more hos-pitable environments in which to operate and are less likely

to be exited. Rather than competing intensely, multipointrivals appear to adopt a "live and let live" approach towardeach other.The fact that multipoint contact across markets may lessencompetitive pressures within individual markets has implica-tions for the contact between firms in several settings. Multi-market contact can occur across different product or servicemarkets and also across different geographic markets, thusaffording an intriguing perspective for the investigation ofthe rivalry between emerging transnational firms. Truetransnationals, by successfully integrating global operationswhile still addressing local market concerns, have been seenby some as having the capabilities necessary for successfulperformance in international competition. Perhaps transna-tional firms, because they have an integrated decision-makingstructure, can coordinate their actions to reduce competitiverivalrywith each other across the markets they share. If so,markets dominated by transnationals may become more sta-ble than the current state of international competition wouldpredict.(Competition; Market Exit; Multipoint Theory; Multi-market Contact; Hospitals)

IntroductionThe central question posed by theoretical and empiri-cal research in corporate-level strategy is: In whatbusinesses should the firm compete? One of the mostimportant ways in which firms modify their corporatestrategy is by entering new markets and exiting currentmarkets. Although corporate strategic change has been

126 ORGANIZATION SCIENCE/ Vol. 8, No. 2, March-April 19971047-7039/97/0802/0126/$05.00Copyright ? 1997. Institute for Operations Researchand the Management Sciences

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WARREN BOEKER, JERRY GOODSTEIN, JOHN STEPHAN AND JOHANN PETER MURMANN Competition n a MultimarketEnvironment

examined mainly in terms of entry into new marketsand businesses (Haveman 1993), the exit of firms frommarkets in which they currently compete can have animportant impact on both the strategy of the firm andthe competitive landscape of an industry (Lieberman1990).Competition with other organizations is a key factorin the exit decision (D'Aveni 1994, Porter 1980). Mostempirical work linking competition to market exit hasexamined only the interrelationships of firms operatingwithin a single market (Heggestad and Rhoades 1978).The focus on intramarket competition is somewhatsurprising given the rise of the multibusiness firm,which competes within single markets and also acrossmarkets, often meeting the same rival(s) in severaldifferent markets. Both business historians (Chandler1962) and sociologists (Fligstein 1985) have docu-mented in great detail the rise of such firms in eco-nomic organization in the twentieth century. Well-known examples of multiproduct firms are Kraft andNabisco (both subsidiaries of tobacco-selling compa-nies), which have competed against one another notonly in dairy products (e.g., Parkay and Fleischmann'smargarine) but also in cold cereals. Similarly, Bic andGillette are rivals in markets for both pens and razors.The most important competitive implication of theintermarket relationships of multibusiness firms is thatthey provide an opportunity for actions taken in onemarket to be countered across several markets. Theissue of whether firms' relationships outside a particu-lar market can affect exit decisions within that markethas received little empirical investigation (but see Judd(1985) for a game-theoretic approach). The lack ofattention is particularly striking because multibusinessfirms contemplating market exit are likely to assess notonly their position in the market under consideration,but also their positions (and those of their competitors)in the full range of markets in which they compete.Consideration of markets other than the one fromwhich exit is contemplated seems particularly impor-tant because the firm must determine its likely futureprospects in arenas in which it will remain as well as inthose from which it is contemplating withdrawal if thespecific exit decision is to benefit the entire firm.

We examine how the extent of intermarket contactbetween rival firms influences competitive pressuresfelt by those firms. We develop hypotheses linkingintermarket effects to the likelihood of market exit byindividual firms in particular markets. Building on theidea of multipoint competition, specifically on the im-pact of intermarket contact between firms (Edwards1955), we argue that higher levels of intermarket con-

tact can benefit firms that maintain such contacts. As aresult, those firms may be reluctant to abandon suchsituations (Karnani and Wernerfelt 1985).A similar conclusion is suggested in the context of anetwork analysis of competitive environments. Networktheorists have traced the accrual of benefits in variousenvironments to particular positions occupied by actorswithin a system of relationships connecting them toone another. In a network model, firms benefit fromtheir position to the extent that they are able to obtaininformation on other actors and influence their actions(Burt 1980). That perspective provides support for theargument that firms attempt to build and maintainconnections to their rivals.The multipoint and network arguments extend tradi-tional views of competition, which typically pertain tointramarket forces only. By incorporating intermarketeffects, we more fully describe both competitive influ-ences and their effects on organizational strategies,such as exit decisions.To elaborate the theoretical arguments that linkintermarket competition to market exit, we investigatea focal organization's degree of overlap in products andservices with other organizations. Because exit deci-sions are based, to a great extent, on the level ofcompetition within a specific product or service, we usethe exit decision at the product or service level as theunit of analysis. In addition to examining the effects ofcompetition associated with market overlap, we assessthe significance of performance and exit barriers facingthe firm as antecedents of market exit decisions. Evenwhen competitive forces are particularly strong, marketexit may be precluded by economic, strategic, andmanagerial exit barriers. To examine the dynamics ofmarket exit over time, we analyze changes in the ser-vices offered by 283 hospitals during a six-year period,1980 to 1986.

TheoryTheorists representing a wide variety of disciplines andperspectives have been interested in the effects ofcompetition on the development of individual organi-zations and entire industries. However, most empiricalwork has treated competition as a property of anindustry at a particular point in time, the implicitassumption being that industries are in equilibrium(Hannan and Carroll 1992).Research in network theory (Burt 1980) and strategy(Barnett 1993) has examined the extent to which amore differentiated depiction of the relationship be-tween firms helps to capture more accurately the com-

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petitive nature of individual industries. Barnett's (1993)study illustrated that competitive influences were notlimited to single markets, but extended to other mar-kets in which rivals faced each other. Network theoristshave demonstrated that actors are better able to achievetheir goals when they operate from within a coordi-nated group of fellow actors (Burt 1982). A criticalrequirement for organizational coordination is thatfirms maintain relationships with each other and moni-tor each other's activities through participation in simi-lar sets of markets. Firms that maintain a presence inseveral markets in which their competitors also partici-pate can draw on cross-market information flows toenhance their knowledge about the type and likelihoodof competitive behaviors by their rivals. Such knowl-edge facilitates greater coordination among the firms.Multipoint CompetitionTheoretical predictions and empirical findings in theeconomics and ecological literatures have linked greaternumbers of competitors with higher levels of competi-tion (Hannan and Freeman 1989, Scherer and Ross1990). Scholars in both areas have persuasively arguedand repeatedly demonstrated that increased competi-tion within a single market results in higher rates ofmarket exit. By the economic and ecological logic, amarket with more players would be viewed as morecompetitive than one with fewer players.However, the link between the number of competi-tors and market competition can understate the com-plexity of the actual relationships between firms. Firmswith elaborate relationships across markets, which canencourage them to coordinate their behaviors, may beable to reduce the levels of competition they face bycontaining competitive forces. Empirical research oncompetition has documented numerous interfirm struc-tures that are designed to limit competitive pressureslegally (Pfeffer 1992). Recent empirical evidencedemonstrates that cross-market effects can lead toreduced levels of competition in individual markets(Barnett 1993, Scott 1982).Edwards (1955) was one of the first to note thatrivalries extending across multiple markets may lead tolessened competition in individual markets, a conditionhe labeled as "mutual forbearance." Specifically, Ed-wards hypothesized that a firm competing in severalmarkets will compete less aggressively with a rival ifthat rival also competes with it in several other mar-kets. Because the rivals compete in more than onemarket, they are attentive to how competition in onemarket will affect competition in other markets. Such"multipoint rivals"become more concerned with main-

taining equilibrium across the several markets in whichthey compete than with competing vigorously in anysingle market (Gimeno 1994).For a focal firm, maintaining a presence in marketswhere one's competitors are operating can also beunderstood as a deliberate strategy to establish morepoints of contact between the firm and its rivals. Suchcontacts provide a variety of avenues for influencingthe actions of the firm's competitors and reducing theoverall level of competition. Karnani and Wernerfelt(1985) present a compelling argument for the mainte-nance of so-called "mutual footholds" by multipointrivals who meet each other in several different geo-graphic arenas. The footholds, or token presences ineach other's markets, enable the rivals to deter compet-itive attacks without relying on other mechanisms suchas inherently uncertain trust-based agreements. Specif-ically, Karnani and Wernerfelt argue that multipointcontact allows for "limited war" equilibriums that re-strict aggressive competition to very circumscribed ar-eas. A more extreme possibility is a mutual-footholdequilibrium whereby each firm with a foothold in an-other's territory completely refrains from attacking theother because of the increased likelihood of aggressiveresponse. Once such footholds are established, a multi-point competitor is unlikely to abandon them. Doing sowould reduce the number of avenues for influencing itsrivals' behavior and reduce its deterrent capability be-cause the number of markets in which it could respondwould decline.Using a different vocabulary, network theorists havealso been interested in the influence of specific typesof relationships between actors on various outcomes.Burt (1980) documented the benefits of informationflows within competitive environments and the relativeadvantages of high degrees of interconnectednessamong network actors. The more points of contact anorganization has with its competitors, the more easily itcan obtain information about its competitors' behavior.With more points of contact, acquired information canbe verified more accurately, which reduces uncertaintyabout competitors' potential actions. Contact with simi-larly positioned organizations also facilitates the coor-dination of actions as information can serve as a sig-nalling device to indicate intentions.Empirical results have demonstrated that higher lev-els of multipoint contact result in less competitiveenvironments across markets along a number of dimen-sions, making firms reluctant to abandon those envi-ronments. For example, Heggestad and Rhoades (1978)found that market shares were more stable when bank-ing firms met their rivals in a greater number of

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geographic markets. They suggested that the organiza-tions in their sample were likely to want to remain inthe less competitive arenas characterized by mutualforbearance. The benefits derived from the establish-ment of mutual footholds, mutual forbearance andinformation flows accompanying higher levels of multi-point contact suggest a low likelihood of severing suchrelationships once they have been established. Theeffect of multipoint rivalry on exit can be simply stated:A given organization will be less likely to exit a specificmarket if other organizations with which it competes inthat market also compete with it in other markets.Barnett (1993) provides the only direct empirical testof the effect of multipoint competition on market exit.He found that markets for private branch exchange(PBX) equipment within the U.S. telephone industrythat contained higher numbers of multipoint competi-tors (on a geographic basis) had lower exit rates thanmarkets that contained higher numbers of competitorswhose operators were confined to a single geographiclocation. Those results offer some support for thenotion that, ceterisparibus, higher levels of multipointcontact will lower the likelihood of exit by individualfirms that have such contacts.Firms with higher levels of multipoint competitionshould find it advantageous to maintain a presence inthe array of markets in which their competitors arepresent. Consequently, at higher levels of multipointcontact, mutual forbearance is likely to occur whichwill reduce competitive pressures. Firms will be lesslikely to exit such markets in which they currentlycompete.

Hi. Organizations with higher levels of multipointcontact with competitors in a particular market are lesslikely to exit that market than organizationswith lowerlevels of multipointcontact.Exit BarriersIn addition to the competitive environment, the sever-ity of exit barriers will influence market exit. Exitbarriers are factors that limit the ability of organiza-tions to scale back or divest business operations. Re-searchers have identified several important structural,strategic, and managerial factors that are likely toaffect market exit (Porter 1976, 1980; Tirole 1988). Forexample, firms typically exit when their revenues fail tocover the marginal cost of providing a product orservice. However, high sunk costs associated withdurable and specialized assets may impede exit. Porter(1976) notes that if an organization has invested incostly equipment to manufacture a product or provide

a service and cannot dispose of such equipment easilyand profitably, incremental costs are likely to be wellbelow average costs. In that case, the organization willpersist in providing the product or service despiteoverall losses. Exit does not become feasible until theequipment wears out or becomes obsolete. We includeseveral such factors as controls, but pay particularattention to two variables that have been linked to thelikelihood of strategic change in general and, morespecifically, to market exit.Mode of Product or Service OfferingTransaction cost theorists have pointed out that orga-nizations have two basic choices for how they willprovide the products and services they offer. Organiza-tions can operate in markets either by providing prod-ucts and services developed with their own assets orthrough market-based transactions such as contractualagreements with other organizations (Williamson 1985).Much of the work on hierarchical versus market-based structuring has examined the stages within avertical manufacturing process (e.g., Harrigan 1985;Mahoney 1992). Activities at each stage can be con-tracted or performed in-house. A logical extension ofthe former approach is the contracting for the provi-sion of an entire product or service. For example, manyappliance manufacturing firms contract their serviceand maintenance to independent authorized servicecenters. Large retailers often contract with smallerspecialty dealers to supply and staff various depart-ments within their stores.

An organization's use of contracting to provide aproduct or service may influence whether the organiza-tion exits that market. Two prominent factors makemarket exit more likely when participation is character-ized by contractual agreements. First, market-basedcontractual arrangements have been considered mucheasier for organizations to terminate than those ar-rangements requiring an organization to invest in as-sets itself (Monteverde and Teece 1982). By avoidinglarge investments that raise exit barriers, organizationsthat contract for various functions maintain flexibilityand can adapt easily as environments change (Harrigan1985). The high barriers that often accompany verticalintegration have been seen as an impediment to suchflexibility. For example, D'Aveni and Ilinitch (1992)found that vertically integrated firms have higher risksof bankruptcy than others because the greater com-plexity of the vertically integrated organization slowsreaction to environmental changes.In addition, contractual arrangements are likely tominimize intraorganizational resistance that would al-

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most certainly accompany the proposed abandonmentof specific markets. Managers with their own organiza-tional assets at risk are likely to resist attempts toeliminate specific activities under their control, eitherbecause they would be left with less power in theorganization (if they remained as managers at all) orbecause threat-rigidity responses are more likely toprevent timely adaptation when one has personallyallocated resources to particular projects (Staw et al.1981, Brockner 1992). Moreover, Porter (1976) notesthat managers may be reluctant to exit a market be-cause such actions may be interpreted negatively byoutside parties, and thus reduce the manager's mobilityshould he or she subsequently leave the firm. Hence,organizations that participate in a market through con-tractual relationships would be more likely to exit thanones that utilize their own assets.

H2. Organizationshatparticipate n a marketthroughcontractingare more likely to exit the market than firmsthat participatethrough in-house investments.Chief Executive ChangeManagerial and, more specifically, CEO attachment tospecific products or businesses is a significant barrierto market exit (Duhaime and Grant 1984, Porter 1980).Therefore, changes in top management may be neces-sary to overcome organizationally-based constraints onmarket exit. Considerable research has shown the im-portance of organizational leaders as motivators of thestrategic change process (Bantel and Jackson 1989,Hambrick and Fukutomi 1991, Wiersema and Bantel1992). Theorists have argued that executive change, inparticular a chief executive change, is an importantmechanism for overcoming inertia and political resis-tance (Boeker and Goodstein 1993). Stressing the in-fluence of executive succession in overcoming inertia,several empirical studies have provided support for theidea that strategic change becomes more likely follow-ing a change in an organization's leadership (Helmichand Brown 1972, Wagner et al. 1984).Besides acting as a catalyst for organizational change,succession introduces new perspectives on the way theorganization should be operated. The longer the tenureof the chief executive, the less innovative, receptive tonew information, and flexible he or she is likely to be(Miller 1991). The longer an individual works in anorganization, the greater the likelihood that "habitualways of doing things, customary sources of informationand ways of information processing" develop whichincrease managerial attachment to the status quo(Pfeffer 1983, p. 325). A new chief executive with new

skills and perspectives on how the firm should behavein its different markets is likely to make decisions andtake actions that produce strategic changes. Hence, achange in chief executive is more conducive to exitfrom current markets.H3. Organizationswitha new chief executivearemorelikely than others to exit markets.

PerformanceAnother critical determinant of market exit, althoughnot an exit barrier in the traditional sense, is organiza-tional performance. Changes in performance have beenlinked to motivating organizational adaptation. Severalmodels of organizational adaptation have stressed thetriggering role of poor performance as a necessaryprecursor to strategic change (Lant et al. 1992). Ac-cording to Tushman and Romanelli (1985), only whenpoor performance signals that current goals are notbeing met are the prevailing ways to doing thingsquestioned and changes in strategy attempted to bettermatch the new environment.Poor performance seems likely to exacerbate pres-sures for market exit, because firms may respond to aperformance downturn by reducing services and down-sizing the organization. Duhaime and Grant (1984), forexample, found that the financial performance of di-vesting firms was significantly lower than the perfor-mance of nondivesting competitors.

H4. Poorly performing organizationsare more likelyto exit markets than betterperformingorganizations.MethodologyWe tested our hypotheses with data on 286 Californiahospitals for the period 1980 to 1986. The data wereobtained from the California Health Facilities Com-mission's (CHFC) annual disclosure survey. The CHFCsurveys California hospitals on such matters as owner-ship and management, financial status, and servicedelivery. Several characteristics of the hospital industryin California make it particularly attractive for anempirical examination of multipoint competition. Incontrast to most industries, it provides a fairly fixed setof services. Hence, the range of services that our sam-ple of hospitals could exit was basically constant overthe study period. Being able to identify a fixed set ofservices minimizes having to account for temporal (e.g.,life-cycle) changes in the set of possible services inwhich a firm can operate and potentially exit. Weexamined a broad spectrum of medical services cover-ing the following areas identified by the CHFC: acute

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care (e.g., surgical intensive care), partial day care (e.g.,psychiatric day care), home care (e.g., home nursingcare), emergency services (e.g., emergency room ser-vices), ancillary services (e.g., X-ray services), clinicservices (e.g., dermatology), and other services (e.g.,dietetic counseling). Detailed longitudinal informationwas available on exit from that common set of services,as well as information on competitors and organiza-tional variables such as contracting, chief executivechanges and performance that were also predicted toinfluence market exit.Definition of CompetitiveEnvironmentResearchers have used geographic areas such as acounty or standard metropolitan statistical area (SMSA)to define hospital environments. We followed that ap-proach by using county boundaries to delineate a hos-pital's environment. County market definitions havebeen found to yield market areas close to those basedon patient-origin methodology (Alexander et al. 1986).Observations represent one service for each hospitalfor a given year, and hospitals could offer up to 163different services. We used the complete dataset of 286hospitals to compute all competitive measures (e.g.,multipoint contact, density and competitors contract-ing). However, three hospitals were eliminated fromthe final analysis because of missing data, leaving afinal sample size of 283.Dependent Variable

Market Exit. The dependent variable, market exit,was measured as a dichotomous variable representingthe event of withdrawal from a market. An observationwas included in the dataset if, for a given service, ahospital offered the service in the prior year (and thuswas capable of exiting that market in the current year).Market exit was coded as 1 (i.e., a service was offeredin the previous period and not offered in the currentperiod) and continued market participation was codedas 0.Independent Variables

MultipointCompetition. Because we were interestedin the influence of interorganizational contact acrossdifferent product-service markets on the actions of afocal hospital, multipoint competition was operational-ized for each of a hospital's services as the extent towhich that hospital's other services were also offered byits competitors in that particular service market withinits county. Specifically, multipoint competition wasmeasured for each service market in which a hospital

currently operated (and thus was capable of exiting) asthe average fraction of the services currently offered bythe focal hospital that were offered by other hospitalsalso currently in that service market within a county.Multipoint competition was therefore a service-levelconstruct and differed not only across hospitals, butalso within a given hospital as a hospital's direct com-petitors in any one service market could differ fromthose in another (and thus its degree of overlap withthose rivals on other services could differ as well). Ourmeasure of multipoint contact ranged from a high of100%, when each of the other hospitals offering, forexample, dialysis in a county also offered every otherservice that the focal hospital did (those rivals mighthave offered additional services not offered by thefocal hospital), to a low of zero when all hospitalsoffering a particular service offered no other servicesin common.

We considered using a single hospital-level measureof the extent of service overlap. However, such ameasure would obscure market-level differences stem-ming from the fact that hospitals do not neatly mirrortheir competitors on all services they offer. Given ourfocus on exit from specific service markets and theimpact that the extent of contact in other markets(outside the focal one) could have on such action, aservice-level measure seemed better able to capturethe variation in effects across different service marketconfigurations. A detailed description of how our mul-tipoint measure was constructed is provided in theAppendix.Mode of Service Offering. The way in which a ser-vice was provided was measured as a dummy variabledenoting whether a hospital contracted for the serviceor undertook its provision itself.ChiefExecutiveChange. Chief executive successionswere coded for each year of the study. A change wasconsidered to have taken place when the chief execu-tive for a given year was different from the one for theprevious year.Performance. Given that hospital performance is amultidimensional construct, we developed two mea-sures for assessing it. One was the occupancy rate (theaverage percentage rate of beds occupied in the hospi-tal). Zucker (1987) notes that occupancy rate is themost common measure of performance in hospital re-search. It was an appropriate performance measure forour study because it indicates how well a hospital'sservice mix matches demand. The extent to which beds

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are filled or empty has a direct link to a hospital'scurrent service offerings (beds would not be filled ifmost service offerings were not demanded).Because our sample included for-profit hospitals, wethought it necessary to use a measure that indicated ahospital's financial performance. We calculated finan-cial performance as the ratio of net income to operat-ing revenues for each year.Control Variables

Density. Organizational ecologists have given con-siderable attention to the effect of density on popula-tions of organizations (e.g., Hannan and Freeman 1989).Density is also prominent in the I/O literature as ameasure of competitive intensity (Scherer and Ross1990). Empirical results from both perspectives showthat higher numbers of competitors (e.g., higher densi-ties) produce higher levels of competition, promptingmore organizations to exit the market as their profitsdecline. To control for those effects, we measureddensity at the service level as the total number ofcompetitors offering the service within a county,a measure consistent with previous research (e.g.,Hannan and Freeman 1989).

Competitors Contracting. At an aggregate level, theextent to which competitors use contractual agree-ments should influence the competitive landscape asso-ciated with a particular market and consequently thelikelihood of market exit by individual firms. Thestrategic flexibility provided by contracting (Harrigan1985) is likely to affect the level of an organization'scommitment to maintaining a presence in a serviceprovided through contracting arrangements. With moreof their own resources at stake, rival organizationsproviding services in-house are likely to defend theirmarkets vigorously, increasing competitive pressureswith those markets (Chen and MacMillan 1992). Tocontrol for effects associated with the level of contract-ing within a service market, we calculated the numberof hospitals providing the service under contract withina county.

Historic Exit Rate. We treated all services currentlyoffered by each hospital as equally likely to be exited.Obviously, each service has specific characteristics thatmight encourage or discourage exit, even within therelatively homogenous group of hospital services weexamined. Research on strategic change has under-scored the importance of partialling out external, mar-ket-related effects to isolate firm-specific forces pro-moting strategic change (Amburgey and Miner 1992).

We used a measure of the historic exit rate for eachservice in an attempt to capture and control for itsunique characteristics that make it more or less likelyto be exited than other services. Services with high exitrates are likely to be easier to exit whereas ones withlow exit rates might be more difficult to exit or moredesirable to retain.The historic exit rate for each service was measuredby totaling the number of exits from the service in theprior year(s) in the entire sample and dividing the totalby the number of hospitals that could have exited theservice each year. We used a cumulative average. Theexit rate for the first year of our sample (1981) was thepercentage of hospitals that exited the service (of thosethat could) in the prior year (1980). Starting with thesecond year 1982, the exit rates for the prior two years(1980 and 1981) were averaged. The rates for the priorthree years (1980-1982) were averaged to obtain therate for the third year, and so on.

Statewide Service Density. Because we treated allservices as equally likely to be exited, we needed toprovide some indication of which services constituted abasic set of services that all hospitals offered andwhere the probability of exit was likely to be low. Forexample, some hospitals seek accreditation from theJoint Council on Hospital Accreditation (JCHA). TheJCHA has designated a fairly well defined set of ser-vices that a hospital must provide in order to beaccredited. We included a measure of the proportionof hospitals in our entire sample that provided eachservice in each year as a control.

MDs per Capita. Competition for critical resourcesmay also have an important effect on market exit. Forexample, hospitals may be in an environment of in-tense competition for physicians, who are needed bothto provide services to patients and to refer patients tothe hospital. Such hospitals are likely to view attractingphysicians as an important activity and this concerncould potentially increase the significance of physicianinfluence as a potential barrier to market exit. Physi-cians may prefer working for and referring their pa-tients to a hospital with a comprehensive set of ser-vices, creating pressure on the hospital to maintain theservices it currently offers (Fennell 1980). Such pres-sure is likely to be greatest when physicians are inrelatively short supply, and thus have bargaining powerwith the hospital. To control for that possibility, weincluded a measure of physician availability, the num-ber of physicians per capita in a county, in our models.




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Ownership. Ownership type may have an importantinfluence on strategic change. Because for-profit hospi-tals have a higher level of market orientation thannot-for-profit hospitals, they would be more likely toreact to market and competitive pressures by exitingservices (Shortell et al. 1990). Several studies indicatethat for-profit hospitals are more likely to respond tocompetitive and regulatory changes through the addi-tion, divestiture and reorganization of hospital services(Goodstein and Boeker 1991; Goodstein et al. 1994,Shortell et al. 1990). We represented ownership as adichotomous variable indicating whether a hospital op-erated on a for-profit or not-for-profit basis.

Hospital Size. To control for the differences in mar-ket exit due solely to hospital size, we included twocontrol variables in our models. Our first measurecalculated size as the average number of beds availablein a hospital in a given year. Number of beds relatesmore closely to the potential for multimarket coverage(more likely with larger hospitals) than other measuresof size. Our second measure of size was a count of thenumber of services a hospital currently offered. We feltthis measure was necessary because hospitals with fewservices might have high levels of overlap due to thefact that they offer only a basic set of services found inall hospitals and thus would tend to mimic small rivalsexactly. A count of the number of services currentlyoffered by a hospital in each year controls for thatpossibility.Model SpecificationWe used a lagged structure to model market exit. Thedependent variable measured whether an exit had oc-curred in a given service market from period t tot + 1. Each of the explanatory variables was measuredin the prior period (t).p (market exit) t, ?+

= f( MultipointContact, ServiceMode, CEO Change,Performance,Density, Numberof ComnpetitorsContracting,Historic Exit Rate, Statewide ServiceDensity, MDsper Capita, Ownership,TotalBeds,Numberof Services).

Because the dependent variable takes on only twovalues (1 = service exited; 0 = service still offered), wetested our models using logistic regression, a procedure

that relates binary dependent variables to one or morecontinuous independent factors utilizing maximumlikelihood estimation. Logistic regression was appropri-ate also because our focus was on the effects of multi-point competition on the behavior of individual hospi-tals, rather than its effect on an aggregate market rate.We included dummy variables representing each yearand each county in our sample to control for temporaldifferences and differences in the basic carrying capac-ity of the counties. Although each model containedthese dummy variables, we do not report the associatedparameter estimates to improve the readability of thetables. We ran a hierarchical regression, entering ourcontrol variables in the first step, our service mode,CEO change and performance measures in the secondstep and our multipoint variable in the last step.A critical issue in estimating models based on datasuch as ours is whether the assumption of indepen-dence of observations is tenable. Because multipointtheory holds that firms attempt to coordinate theiractions across markets, some of a firm's moves (such asexiting several markets simultaneously) may be part ofa coordinated strategy and thus not statistically inde-pendent. Lack of statistical independence would vio-late a key assumption of maximum likelihood estima-tion and could bias the results.Prior multipoint studies have noted this problem andemployed various techniques to deal with it. For exam-ple, Barnett (1993) chose to treat this issue as a sam-pling problem. He inversely weighted the exit decisionsof the multipoint firms in his sample. However, heacknowledged that such an approach does not dealdirectly with the independence problem. We handledthis problem in a different way, one which deals withthe independence question directly. Liang and Zeger(1986) showed that maximum likelihood estimation withsamples similar to ours is not prone to bias in theestimates of the parameters. Their analysis demon-strates that it is the estimates of the standard errors ofthe parameters that are likely to be affected by a lackof statistical independence among the observations.They present a formula for calculating adjusted stan-dard errors that produces unbiased and consistent esti-mates. Using their approach, we calculated adjustedstandard errors, which then served as the basis for allsignificance tests of our parameter estimates. (Thedetails of the procedure are available from the authors.)

Subsample AnalysesWe conducted a series of subsample analyses to ascer-tain whether the effects of two of our independent

ORGANIZATION SCIENCE/VOL. 8, No. 2, March-April 1997 133



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variables extended beyond those captured by the esti-mated parameter alone. Because both mode of serviceoffering and ownership were measured as dummy vari-ables, the interpretation of their estimated coefficientsis limited to a difference in intercept between the twocases represented by the binary coding.As the discussion leading to H2 indicates, providinga service in-house and contracting for it involve differ-ent levels of both psychological commitment and in-vestment of firm assets. Exiting a market in whichparticipation is achieved under contract and exitingwhen a firm's own assets are employed are thereforelikely to be substantially different events, with poten-tially different antecedent influences. Constraining theparameters for the other variables in our model to beequal for those two conditions, which is the implicitassumption when a dummy variable is used, maskssuch differences. To investigate the possibility that theother variables in our model affect exit from con-tracted services and in-house services in unique ways,we split our sample into two subsamples, one forobservations of services provided under contract andone for observations of services provided in-house. Weran logistic regressions of our full model (including allcontrol and hypothesized variables) on the two subsam-ples. That procedure enabled us to determine whetherthe two modes of service offering differ beyond adifference in intercept because the estimated coeffi-cients for all independent variables were allowed tovary across the two subsamples.We followed the same procedure with the ownershipvariable, creating two subsamples based on the form ofhospital ownership (for-profit and not-for-profit) andtesting the full model on each. The influence of for-profit ownership is likely to extend beyond that cap-tured by the parameter for the dummy variable alone.For example, for-profit hospitals, because they typicallyhave higher percentages of physicians on their boards(Goodstein and Boeker 1991), are likely to react tochanges in physician availability in the environmentmore readily than not-for-profit hospitals. In additionthe two types of hospitals are likely to differ in theirdegree of adaptation to competitive conditions. Theintroduction of the prospective payment system (PPS)in 1983 shifted the burden of cost control to hospitalsand created a new incentive to direct resources fromless profitable to more profitable services. In addition,throughout the 1980s competitive pressure to controlcosts and manage hospital services more effectivelyintensified with the growth of managed care institu-tions such as HMOs (Meyer et al. 1990). Those changesincreased competitive rivalry for all hospitals, but for-

profit hospitals have been more responsive and marketoriented in adapting to these environmental changes(Shortell et al. 1990). We discuss the results of thesubsample analyses after reporting our results for thefull sample.

ResultsMeans, standard deviations and zero-order correlationsfor the variables in our models are reported in Table 1.The results of the analyses based on the entire sampleare reported in Table 2. As our primary interest isintermarket competitive influences on exit, we begin bydiscussing the effects of our control variables. In par-ticular, we partial out intramarket measures of compet-itive intensity of controlling for density and competi-tors contracting. We then evaluate how performanceand factors contributing to exit barriers, such as theprovision of the service in-house or under contract,affect the likelihood of exit. Finally, we add our mea-sure of multipoint contact to assess its contribution tothe explanatory power of the expanded model andaddress the overall effectiveness of the three models.We then discuss the two subsample analyses.Effects of Control Variables on Market ExitModel 1 in Table 2 contains only the dummy variablesfor year and county. It is included to provide a baselinecomparison for the subsequent models. Model 2 repre-sents the effects of our eight control variables on thelikelihood of market exit: density, number of competi-tors contracting, historic exit rate, statewide densityrate, MDs per capita, ownership and two measures ofhospital size. We discuss density last. At first glance, itappears that markets generally characterized by higherlevels of contracting also seem to exhibit a higherlikelihood of exit. However, once the variable repre-senting whether or not a given service is contracted byan individual hospital enters the model (see Model 3),service markets with a greater incidence of contractingare associated with a reduced likelihood of exit, asexpected.The results for the historic exit rate control variableindicate that, although it was necessary for partiallingout interservice differences that our treatment of eachservice could not capture directly, it did not have asignificant effect of its own. The positive sign indicatesthat services with higher rates of exit had a greaterlikelihood of exit than those with lower exit rates, butthe measure fails to achieve significance in any of ourmodels. Our statewide density measure appears to benecessary to control for basic hospital service plat-

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WARRENBOEKER, JERRY GOODSTEIN, JOHN STEPHAN AND JOHANN PETER MURMANN Competition n a MultimarketEnvironment

Table1

Means,

Standard

Deviationsand

CorrelationsforMarketExitModela

Correlation

Coefficients

Mean

S.D.

Range

1

2

3

4

5

6

7

8

9

10

11

12

13

1

Marketexit

0.06

0.24

0-1

2

Multipoint

0.72

0.13

0-1

-0.017

3

Service

contracted

0.16

0.36

0-1

0.056

-0.037

4CEO

Change

0.20

0.40

0-1

0.017

0.070

-0.001

5

Performance(financial)

0.06

0.29-3.62-8.96

-0.036

-0.043-0.006-0.066

6

Performance(occupancy)

0.66

0.18

0-1.56

-0.044

-0.214

0.066-0.299

0.192

7

Density

40.61

43.98

1-137

-0.041

0.007

0.051

0.116

0.002

-0.207

8

Numberof

competitors

7.40

14.26

0-79

-0.029

-0.061

0.295

0.064

0.004

-0.122

0.652

contracting

9

Historicexitrate

0.01

0.01

0-0.48

0.082

0.020

-0.015

-0.006

0.004

0.031

-0.148

-0.131

10

Statewise

densityrate

0.65

0.26

0.01-0.98

-0.241

0.009

-0.031

0.054

-0.018

-0.133

0.355

0.233

-0.388

11MDsper

capita

0.28

0.12

0.11-0.78

0.038

0.045

-0.029

-0.074

0.037

-0.013

0.060

0.035

-0.004

-0.083

12

For-profit

ownership

0.39

0.49

0-1

-0.025

0.170

0.119

0.178

-0.054

0.399

0.237

0.151

-0.028

0.150

-0.124

13Size:Totalbeds

198.99

150.83

6-1015

0.037

-0.171

0.154

-0.069

0.041

0.269

-0.006

0.019

0.031

-0.174

0.273

0.395

14Size:

Numberof

services

75.42

25.64

10-167

0.061

-0.253

-0.184

-0.081

0.005

0.326

-0.150

-0.117

0.066

-0.242

0.229

-0.483

0.738

aAll

correlation

coefficients

greaterthan0.007are

significantatthe0.001level.

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WARREN BOEKER, JERRY GOODSTEIN, JOHN STEPHANAND JOHANN PETER MURMANN Competition n a MultimarketEnvironment

Table 2 Maximum Likelihood Estimates of Logistic Regressionsa Dependent Variable = Market Exit (t, t + 1)Independent Variables (t) Model1b Model 2 Model 3 Model 4Density - 0.784*** - 0.097*** -0.119***No. competitors contracting 0.122** - 0.062*** - 0.065***Historic exit rate 0.116 0.074 0.072Statewide density rate - 0.432*** - 0.424*** - 0.412***MDs per capita -0.410 - 0.450 0.440For-profitownership 0.191*** 0.135*** 0.138***Size: Total beds -0.107*** - 0.051 *** - 0.051 ***Size: Number of services 0.043*** 0.039*** 0.014***Service contracted 0.186*** 0.184***CEO change 0.023** 0.024**Performance (financial) 0.048** 0.048**Performance (occupancy) -0.139** -0.149**Multipoint - 0Q073**x2 for covariates 728.222*** 4143.969*** 4861.329*** 4912.014***df 32 40 44 45Number of hospitals 283 283 283 283aStandardized parameter estimates are reported. Adjusted standard errors were used to determine significance levels.bModel 1 contains year and county dummies only (forfive years and 29 counties). All models contained these year and county dummies, buttheir coefficients are not reported to improve the readabilityof the tables.** -p < 0.01

=p < 0.001forms. Hospitals were less likely to exit services withhigher statewide densities. Our measure of resourceavailability, MDs per capita, did not significantly influ-ence the likelihood of market exit. The probability ofmarket exit is associated with ownership type. For-profit hospitals were more likely to exit service marketsthan not-for-profit hospitals. Results for hospital sizeproduce an interesting picture, suggesting that differ-ent measures of size capture different aspects of ahospital's operations. Whereas offering a greater num-ber of services in associated with an increased likeli-hood of market exit (as expected), large hospitals, asmeasured by number of beds, were less likely thensmaller ones to exit service markets. Perhaps largehospitals were better matched to their patients' needs,or additional services were deemed necessary to fillavailable beds.Contraryto our expectations and both ecological andeconomic arguments, density has an inverse relation-ship with exit, with higher density levels associated witha decreased likelihood of market exit. Apparently, mar-ket exit is less likely in markets with a greater numberof hospitals and presumably more intense competition.That finding may be related to the particular context ofthe hospital industry. Hospitals have been character-ized as being very status- and prestige-oriented institu-tions (Fennel 1980, Lee 1971). To attract top physi-

cians and consequently increase their own prestige,hospitals in our sample may have been unwilling toabandon service offerings for fear of reducing theirappeal to that critical constituency. Such prestige pres-sure may have been much greater for hospitals inservice markets with large numbers of competitors.Results of HypothesesH2 pertains to the effect of market participation mode(in-house or through contract) on market exit. Buildingon research on strategic flexibility, we posited that exitwould be more likely with contracted services becausetheir exit barriers are lower and organizations typicallyhave less invested in contractual arrangements, so lessorganizational resistance is generated when such ar-rangements are severed. The results shown in Model 3of Table 2 support H2.H3 posited that a change in chief executive wouldfoster exit from markets. The results for Model 2support a positive relationship between chief executivechange and market exit.H4 states that poorly performing organizations aremore likely to exit from markets than better perform-ing ones. The results for Model 3 provide mixed sup-port for that hypothesis. When performance is mea-sured by occupancy, poorer performance (i.e., loweroccupancy rates) increases the likelihood of market




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exit. Poor performance along that dimension appearsto force organizations to modify their strategic posture,supporting the argument that poor performance moti-vates organizational adaptation, including the exitingof markets. However, when performance is measuredin financial terms, better performance increases thelikelihood of market exit, contrary of H4.Effects of Multimarket Competition on Market ExitThe central focus of the paper was on the effects ofcompetition, especially multimarket competition. Weexpected that organizations facing the same competi-tors in several other markets would be less likely to exita given market, because such exit would reduce theirability to acquire information about and influence com-petitors in other markets in which they compete. Model4 of Table 2 indicates support for that notion. Asposited in H4, organizations with higher levels of mul-tipoint contact in particular markets were found to beless likely to exit from those markets. Apparently, toperpetuate mutual forbearance and present a credibledeterrent to aggressive action through the use of mu-tual footholds, a firm should maintain a multiplicity ofmarket contacts with its rivals.The three models also include an overall assessmentof the combined effects of the explanatory variables.As Table 2 reports, the chi-square statistics for allthree models are highly significant (p < 0.001). Exam-ining the changes in the chi-square statistic from Model1 to Model 4, we see that Model 2 represents asignificant improvement over Model 1 (a change in x2from 728 to 4144 with eight additional degrees offreedom, p < 0.01). Adding our explanatory variablesincreased the chi-square statistic to 4861, again a sig-nificant increase (p < 0.01) with the addition of onlyfour degrees of freedom. Model 4, with our multipointmeasure added, significantly improves upon Model 3(an increase in x2 to 4912 with one additional degreeof freedom, p < 0.01). That increase clearly supportsour position that the competitive landscape, capturedby multipoint measures, is an important considerationfor firms contemplating strategic change.Table 2 reports standardized parameters, enablingus to directly compare the relative effects of the vari-ables in our models on the likelihood of market exitdespite the differences in their units of measure. Thestatewide density rate appears to have the greatesteffect on the likelihood of exit. Apparently, when agiven service is considered essential for hospital opera-tions (i.e., it has a high statewide density), exit fromthat service is unlikely. Our multipoint measure is atabout the middle among our measures in its relative

influence on market exit. Although it is does not havethe strongest influence (statewide density, density andoccupancy, for example, have larger standardized pa-rameter estimates), it has a substantial effect on thelikelihood that a firm will exit a service market, aneffect that is greater than that of two of our hypothe-sized variables (CEO change and financial perfor-mance).

Analysis of SubsamplesWe divided our sample into two subsamples to investi-gate whether the mode of service provision and profitorientation would effect other variables in our modelwhen the equality constraint on the estimated parame-ters for those variables was relaxed. The results of thesubsample analyses are reported in Table 3.To determine whether the coefficients of the respec-tive pairs of subsamples differ significantly (e.g.,whether the coefficients for multipoint contact differsignificantly between for-profit and not-for-profit hos-pitals), we conducted an additional series of analyses.We individually added the interaction of each indepen-dent variable with the appropriate dummy variablerepresenting each subsample split to the completemodel (Model 4, Table 2). The difference between thecoefficients for each pair of subsamples is significant ifthe interaction term is significant. The significant dif-ferences are indicated in boldface in Table 3.On the issue of whether a hospital's mode of serviceprovision affects how competitive pressures and exitbarriers influence the likelihood of market exit, ourresults indicate that there is, in fact, a larger impactthan that captured solely by a difference in intercept(see columns 1 and 2 of Table 3). Multipoint contactappears to have a direct influence on market exit onlywhen a firm's assets have been invested and a service isprovided in-house. Although the sign of the multipointmeasure for the contracting subsample is negative, it isnon-significant. Similarly, none of our hypothesizedrelationships materialize in the contracting subsample.Those results suggest that organizations react to com-petitive pressures by restructuring only the products orservices that entail the use of their own assets. Inaddition, the inertial effects of exit barriers such as along-tenured CEO apparently are not related to con-tractual agreements to provide services. The results donot mean that contracted services are never exited. Infact, in our model using the full sample, contractedservices were more likely to be exited that servicesprovided in-house. What the results show is that thefactors influencing exit from service markets are likely




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WARREN BOEKER, JERRY GOODSTEIN, JOHN STEPHANAND JOHANN PETER MURMANN Competition n a MultimarketEnvironment

Table 3 Maximum Likelihood Estimates of Logistic Regressions for In-House / Contract and For-Profit / Not-for-ProfitSubsamplesa Dependent Variable = Market Exit (t, t + 1)

Independent Variables (t) In-House Contract For-Profit Not-for-ProfitDensity - 0.1 73*** 0.126*** - 0.215*** - 0.095***No. competitors contracting 0.046*** -0.270*** -0.060*** 0.013***Historicexit rate 0.089 0.038 0.043 0.100Statewide density rate - 0.409*** - 0.496*** - 0.359*** - 0.460MDs per capita -1.158 0.430 - 0.249 - 0.734For-profitownership 0.1 35*** 0.115***Size: Total beds - 0.013*** - 0.060*** - 0.236*** 0.059***Size: Number of services - 0.023*** 0.028*** 0.066*** - 0.025***Service contracted 0.159*** 0.168CEO change 0.034*** -0.007 0.004 0Q035*Performance (financial) 0.057*** 0.049 -0.083*** 0.077Performance (occupancy) - 0.1 49*** -0.104 - 0.098*** - 0.1 15**Multipoint - 0.089*** -0.031 - 0.123*** - 0.037**x2 for covariates 3013.082*** 1243.337*** 2425.812*** 1243.337***dfb 44 44 37 42Number of hospitals 283 278 135 148aStandardized parameter estimates are reported. Adjusted standard errors were used to determine significance levels. Allregressions includeddummy variables for county and year whose parameter estimates are not reported. Within each subsample pair (in-house/contracted;for-profit not-for-profit),boldface coefficients for each independent variable differsignificantly (at the p < 0.05 level or better).

bDifferentdegrees of freedom are due to the elimination of county dummies for counties with only for-profitor not-for-profithospitals.=p < 0.05=p < 0.01=p < 0.001

to have a different effect when a service is offeredunder contract than when it is provided in-house.For-profit and not-for-profit hospitals were alsomodelled separately (see columns 3 and 4 of Table 3).The differences between the two types of hospitalownership are not as pronounced as those betweencontracting and in-house service provision, but severalof the differences are interesting. Both types of hospi-tals were less likely to exit services that were alsooffered by their multipoint rivals, which suggests thatthey both benefit from multipoint arrangements. Asexpected, financial performance affected the likelihoodof market exit only for for-profit hospitals. That findingmight explain the opposite effects found for financialperformance and occupancy when the whole sample

was used. For-profit hospitals were less likely to exitservices when performance was good on both of ourperformance measures, supporting H4. For not-for-profit hospitals, however, only the occupancy measureof performance had a significant relationship with thelikelihood of market exit.Surprisingly,a change in chief executive appeared toprompt strategic change only in the not-for-profit sub-

sample. Perhaps CEOs in that subsample were longertenured, making a change much more of a break withthe past than in the for-profit group. Although we donot have specific data on CEO tenure, we found somesupport for that contention, as there were relativelymore changes of CEO in for-profit than in not-for-profithospitals (an average of 0.30 and 0.14, respectively).CEOs in for-profit hospitals may also be more attunedto market developments and pre-disposed to respondquickly to changes in their environments.Exit decisions have complex dynamics. Our resultssuggest that a combination of factors are capable ofinfluencing exit and that these factors affect hospitalsdifferentially, depending on their mode of service pro-vision and form of ownership. Clearly, students ofcompetition are well advised to expand models thatbegin with traditional competitive measures such asdensity by taking into account both internal organiza-tional factors and a firm's external relationships.DiscussionThe primary purpose of our study was to examine theeffect of multipoint competition at the service level on




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market exit. We extended the mutual forbearance ar-guments of Edwards (1955), Barnett (1993) and othersand the rationale for establishing mutual footholds(Karnani and Wernerfelt 1985) to explore how compe-tition in one market is interdependent with the posi-tion of competitors in other markets. Our underlyinghypothesis was that a firm would be less likely to exit amarket if its competitors there were firms with which itcompetes in other markets. The study results suggestthat firms are indeed reluctant to exit markets in whichthey encounter competitors that are its rivals in othermarkets as well.Our results also provide a thought-provoking exten-sion to current network theories about competition.Burt (1992) analyzes how actors in a competitive envi-ronment are able to out-perform their rivals. He exam-ines how the relationships those actors have with oth-ers in their networks yield preferential positions andprovide information that enable them to exploit oppor-tunities and earn higher profits than their rivals. Hisargument details the relationships competitors havewith others, but he excludes relationships betweendirect competitors from his analysis. He recommendsthat network actors seek only a minimum number ofcontacts with other actors for efficiency, arguing thatadditional contacts yield redundant information at ahigh maintenance cost. However, if one considers theintermarket relationships between competitive actorsthemselves, our multipoint results underscore the ad-vantage of additional points of contacts for securingmarket-related information on one's competitors. Indirect competitor relationships, trust is a scarce com-modity and additional points of contact with individualcompetitors are essential for verifying the reliability ofinformation acquired through those channels. The valueof our research derives from our demonstration thatnetwork analyses of competitive relationships must in-corporate an appreciation for the context of a relation-ship. As competitors often deliberately distort informa-tion they provide, the reduction in uncertainty derivedfrom an additional tie to a rival organization mayoutweigh the costs of being overinformed by redundantnetwork ties.Exit BarriersIn addition to the effects of competition on marketexit, we examined several variables representing exitbarriers. Of particular interest was the influence oforganizational contracting on market exit. Our findingsindicate that although multipoint contact did not influ-ence exit from contracted services, contracting firms ingeneral were able to exit markets more easily.

The study of the effects of contracting on marketexit has important implications for the expanding liter-ature on outsourcing. To the extent that organizationsare able to outsource many of their services, they maybe able to reduce costs and enhance their strategicflexibility (Harrigan 1985). More recently, many ob-servers have argued that such a "hollowing out" of theorganization can lead to a decline in the set of corecompetencies needed to compete in newly emergingand rapidly transforming markets in the future (Bettiset al. 1992, Prahalad and Hamel 1990).Recent work in organization ecology suggests thatorganizations are capable of finer-grained adaptationsto environmental factors (Haveman 1993). Market exitis one potential approach to incremental adaptation tothe environment. However, if such adaptation resultsin a reduction in the scope of core competencies typi-cal to "hollow" organizations, outsourcing may have animportant influence on the long-term viability of thefirm. If core areas become besieged by competitivepressures, a reduced range of competencies might causepopulations of such organizations to have more in-stances of organizational death than of adaptation, aconsequence is keeping with traditional ecological ar-guments.Future ResearchThe most critical future research need is the examina-tion of exit at the product or service level in otherindustries. We selected hospitals for our study of mar-ket exit because of the availability of detailed marketdata for identical sets of services among competitors.The depth and detail of the longitudinal data availableseemed to compensate for the limitations of a single-industry study. Expansion of our research to competi-tors in other industries and to emerging and decliningmarkets is necessary for a fuller understanding of thephenomenon of exit in competitive environments.Several other extensions of our research would beworthwhile. To understand better the mechanism ofstrategic change, more detailed measures of multipointcompetition might be incorporated. Often, a firm willderive a major proportion of its revenue or profits froma relatively small number of its markets. An opera-tionalization of multipoint competition that includessome measure of the importance of individual marketsto the firm (possibly by weighting each in terms of itscontribution to revenue or profits) would advance thecurrent state of knowledge on the effects of multipointcompetition.Additionally, it would be useful to include informa-tion about the level of participation in particular mar-

ORGANIZATION SCIENCE/VO1. 8, No. 2, March-April 1997 139



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kets. In our study, market exit was defined as completewithdrawal from a market, operationalized as a di-chotomous dependent variable. Rather than completewithdrawal, organizations may decide on major down-scaling of participation (e.g., reducing the provision ofa particular service by 50% or scaling back the numberof different product models that are offered) while stillremaining in the market. By examining changes in thecontribution of each service to revenue or profit, re-searchers could gain a greater understanding of thedifferences between total exit from a market and majorchanges in the level of participation in that market.Our study was a first attempt to test multipointarguments within a multiproduct environment, extend-ing prior research that has focused primarily on thecompetitive effects of multipoint contact across geo-graphic markets in the United States. Subsequent stud-ies should extend and integrate the two approaches.With the rapid rise of globalization, the dynamics ofmultimarket relationships across national boundaries isan important area for investigation. As national firmsincreasingly face foreign competition that prompts theirown entry into foreign markets, multimarket contactacross nations will increase and shape these firms'competitive behavior. Industry analysts have used thislogic to explain Scott Paper's recent acquisition byKimberly-Clark (Thomas 1995). By acquiring ScottPaper, Kimberly-Clarkincreased its multipoint contactwith a key rival, Procter & Gamble, on both aproduct-market and an international geographic basisby obtaining Scott Paper's established market positionsin Europe.Bartlett and Ghoshal (1989) point out that the likelywinners in global competition will be transnationalfirms that are able to achieve both the global integra-tion of their operations and local responsiveness toindividual market conditions. Perhaps as more firmsattain transnational status, the integration of their in-ternational operations will increase the salience ofmultimarket contacts with their rivals on a firmwidebasis. By having an integrated decision-making struc-ture, such rivals would be better able to establishmultimarket equilibriums of the type described by mul-tipoint theories. It would be of both significant theoret-ical and practical interest to determine whether it isonly the transnationals that are able to exploit aninternational multipoint environment effectively.

ConclusionsInvestigations of the role of competition in market exithave centered primarilyon competition at the industry

level rather than differences in competitive relation-ships among organizations within industries (Carroll1993). Based on theories of multipoint competition andnetwork analysis, our research is an important steptoward exploring the effects of contact across severalmarkets on competition and market exit.Our results also extend the findings of organizationalecologists, who have tended to define market exit interms of organizational failure. Following up on somerecent work (Haveman 1993), we demonstrate thatorganizations are capable of finer-grained adaptationsto competitive environments, as they can strategicallyexit particular service markets in lieu of a total shut-down. The multipoint perspective offers suggestive evi-dence that firms are able to structure their environ-ments to reduce the competitive pressures they face,perhaps increasing their survival chances. By takinginto consideration multiple sources of competitive in-tensity, we can better understand the strategies oforganizations over time as they change the mix ofbusinesses in which they compete.AcknowledgmentThe authors wish to thank Eric Abrahamson, Don Hambrick, MarvinLieberman, Murray Low and Mike Tushman for their helpful com-ments and insights during the preparation of this manuscript. Theauthors would also like to thank Daniel Rabinowitz for his invaluableassistance with several methodological issues that arose during thisstudy.AppendixMeasurement of Multipoint CompetitionMeasures of multipoint competition must capture the extent towhich a firm'sproduct-market scope outside a focal market is similarto that of other firms also participating in the focal market. We usedthe following procedure for determining the degree of multimarketoverlap among hospitals in a given geographic region. Assume acounty has four hospitals that are capable of offering any combina-tion of three services. Their current service configurations are asfollows:

Services OfferedHospital A 1 2Hospital B 2 3Hospital C 1 2 3Hospital D 1

Hospitals A, B and C can exit service 2 (i.e., they all currentlyoffer the service). For those three hospitals, the degree of serviceoverlap they have with the other hospitals also offering service 2 isshown below, with the rows representing the focal hospital andcolumns their overlap with other hospitals currently offering service2. Note that the overlap of each hospital with hospital D is notcalculated because hospital D does not currently offer service 2.




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Overlap for Hospitals Able to Exit from Service 2A B C D AVG

A 50% 100% NA 75%B 50% - 100% NA 75%C 67% 67% NA 67%D

The average overlap for each of the three hospitals (A, B and C)is calculated by dividing the sum of the individual overlap percent-ages by the total number of other hospitals offering service 2 in theircounty. A similar process is carried out for each service from which aparticular hospital can possibly exit. When the process is completed,we obtain data similar to the following, which characterizes a hospi-tal's overlap with its rivals for each service it can exit.

Service1 2 3

Hospital A 75% 75%Hospital B 75% 100%Hospital C 50% 67% 67%Hospital D 100%

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