global integration and innovation: multicountry knowledge generation within mncs

Strategic Management JournalStrat. Mgmt. J., 35: 869–890 (2014)

Published online EarlyView 14 June 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.2140

Received 21 December 2011 ; Final revision received 15 February 2013

GLOBAL INTEGRATION AND INNOVATION:MULTICOUNTRY KNOWLEDGE GENERATIONWITHIN MNCs

HEATHER BERRY*George Washington University, School of Business, Washington, District ofColumbia, U.S.A.

This paper examines both conditions that can enable collaborative and combinative knowledgegeneration within multinational corporations (MNCs) and benefits that firms can achieve fromthese types of innovations. I posit that more basic relationships that have been establishedthrough manufacturing integration can enable multicountry collaborative innovations and thatthese innovations will bring together diverse knowledge that is likely to spawn further innovationwithin firms. Empirical analysis of a panel that includes comprehensive and confidential data onthe worldwide operations of U.S. MNCs and their worldwide patents reveals robust support forthese arguments. Overall, this paper broadens extant research on knowledge generation withinMNCs by exploring both the antecedents and benefits of multicountry collaborative innovations.Copyright 2013 John Wiley & Sons, Ltd.

INTRODUCTION

A fundamental issue within the field of manage-ment concerns the generation, exploitation, andsharing of firm knowledge. In the strategic man-agement literature, a growing body of researchaddresses how firms can achieve sustainableadvantages through exploiting, reconfiguring, andextending their knowledge assets (Cohen andLevinthal, 1990; Eisenhardt and Martin, 2000;Grant, 1996; Kogut and Zander, 1992). Similarly,a basic premise within the field of internationalmanagement is that the possession of intangible,knowledge-based assets allows firms to both over-come liabilities of foreignness and successfullycompete in foreign markets (Buckley and Casson,

Keywords: innovation; knowledge; multinational cor-porations; multicountry innovations; manufacturingintegration*Correspondence to: Heather Berry, George Washington Uni-versity, School of Business, Funger Hall 401T, 2201 G Street,Washington DC 20052, U.S.A. E-mail: [email protected]

Copyright 2013 John Wiley & Sons, Ltd.

1976; Hymer, 1960; Kogut and Zander, 1993;Tallman, 2003). Furthermore, researchers haveargued that multinational corporations (MNCs)who can successfully combine knowledge acrosscountry locations can generate competitiveadvantages that other firms will have difficultyreplicating, matching, or surpassing (Gupta andGovindarajan, 2000; Kogut and Zander, 1993;Martin and Salomon, 2003).

At the same time, official publications show thatR&D is one of the least internationalized activitiesof firms (see the 2004 and 2005 World Invest-ment Reports from UNCTAD, for example). Thecosts associated with managing dispersed knowl-edge activities and the difficulties associated withtrying to share and integrate knowledge acrossdistances (Szulanski, 1996; Teece, 1977) makeinternational R&D strategies complicated to imple-ment and difficult to oversee (Berry, 2006; Pearce,1999). Managers report that they are reluctant tolocate their R&D activities abroad for fear of los-ing control over their innovation process fromboth quality and competitor spillover perspectives

870 H. Berry

(UNCTAD, 2004). Though MNCs can generatesuperior performance by combining and exploitingknowledge from different source locations (Pheneand Almeida, 2008), firms based in very differ-ent home countries pursue relatively little of this,choosing instead to concentrate the vast major-ity of their R&D and innovative activities in theirhome country (UNCTAD, 2005).1

In this paper, I analyze how firms can over-come the difficulties associated with cross-borderknowledge sharing to generate multicountry inno-vations that combine knowledge from differentlocations. I seek to better understand cross-countrycombinative knowledge generation within MNCsby exploring both conditions that can allow firmsto overcome some of the difficulties associatedwith internationalizing their R&D and the benefitsfirms can achieve from multicountry collaborativeinnovations. Building on arguments from theknowledge-based view of the firm and the foreignknowledge-seeking literature, I consider howcommunication channels, a common knowledgebase, and increased visibility that come frommanufacturing integration can enable foreignoperations to play increasingly important rolesin firm innovation processes and lead to collab-orative multicountry innovations. In addition, Iconsider how multicountry collaborations differfrom single country innovations and posit thatmulticountry collaborations can bring togetherdiverse knowledge that is more likely to be usedin subsequent innovations by firms.

To test these arguments, I created a uniquedataset that combines comprehensive and con-fidential data on the worldwide operations ofU.S. multinational corporations from the Bureauof Economic Analysis (BEA) with data on theforeign-invented patents of these firms from theUnited States Patent and Trade Office (USPTO).I explore different approaches to foreign patent-ing by U.S. MNCs and show a significantincrease in multicountry collaborations from 1989to 2004. Conditional on firms doing foreign R&D,

1 The 2005 World Investment Report found that foreign affiliatesof U.S., UK, and small European country MNCs spend 13.3% oftheir total R&D expenditures in their foreign affiliates. Japanesefirms represent the low end, with only 4% of total R&Dexpenditures taking place in foreign affiliates while Swedenrepresents the high end, with 43% of total R&D expenditurestaking place in foreign affiliates. The comprehensive database onU.S. MNCs used in the analysis below shows that U.S. MNCsspend 11% of their total worldwide R&D expenditures outsideof the United States.

I show that the increasing trend in multicountrypatenting within MNCs is significantly related tohigher manufacturing integration as measured byintrafirm product flows. In addition, the resultsshow that multicountry collaborative innovationsdraw on a wider pool of technological knowl-edge than single country foreign innovations,and that multicountry collaborations involvingparent and subsidiary inventors are significantlymore likely to be used in subsequent inno-vations by MNCs than single country foreigninnovations.

Overall, this paper examines both conditionsthat enable collaborative and combinative knowl-edge generation within MNCs and benefits thatfirms can achieve from these innovations. Whileit has long been argued that MNCs are in uniquepositions to access diverse sets of technical inputsacross their operations from a variety of coun-try locations (Grant, 1996; Kogut and Zander,1992; Martin and Salomon, 2003), our under-standing of when and how MNCs do success-fully combine knowledge across different sourcelocations is underexplored. The comprehensivedatabase used in the empirical analysis revealsthat collaborative multicountry patents have grownfrom one-fifth to one-third of new foreign patentsby U.S. MNCs over the past two decades, andthis paper shows the significant role that man-ufacturing integration has played in generatingthese multicountry collaborative innovations. Fur-thermore, the results show that these multicountrycollaborative innovations are both more techno-logically diverse and more likely to spawn furtherinnovations within MNCs than other firm foreigninnovations.

KNOWLEDGE AND MULTINATIONALCORPORATIONS

A well-established rationale for the existence ofMNCs in the international management literaturecomes from these firms’ abilities to transferand exploit knowledge more efficiently throughinternal expansion than through external marketmechanisms (Buckley and Casson, 1976; Guptaand Govindarajan, 2000; Hymer, 1960; Teece,1977). Over the last two decades, there hasbeen growing emphasis on the important rolethat foreign subsidiaries can play in knowledgecreation (Almeida, 1996; Cantwell and Mudambi,

Copyright 2013 John Wiley & Sons, Ltd. Strat. Mgmt. J., 35: 869–890 (2014)DOI: 10.1002/smj

Global Integration and Innovation 871

2005; Frost, 2001), with subsidiaries developingexpertise that may not be available in a firm’shome country (Cantwell, 1989; Patel and Pavitt,1999; Singh, 2008; Zhao, 2006). Because countriesdiffer in their knowledge profiles (Chung andYeaple, 2008; Furman, Porter, and Stern, 2002),firms can draw from diverse clusters of knowledgeand know-how when they engage in foreign R&D(Alcacer and Chung, 2007; Almeida and Phene2004; Singh, 2008). An MNC is thus in a uniqueposition to access diverse sets of technical inputsacross their worldwide operations to generatenew innovations and combinations of existingknowledge (Singh, 2008; Zhao, 2006).

Enticing as these benefits may be, the costsassociated with managing dispersed knowl-edge activities and the difficulties of sharingknowledge across distances (Szulanski, 1996)make international R&D strategies difficult tomanage effectively (Berry, 2006; Teece, 1996).Though dispersed R&D can provide access tonew knowledge in foreign markets, it can alsocreate inefficiencies, duplication, and complicatedorganizational structures to control. Further,organizational inertia in innovation, rooted inthe historical organization of R&D in the homecountry, can make firms less receptive to knowl-edge from abroad (Cohen and Levinthal, 1990;Pearce, 1999), and several studies have shownthat organizations tend to have biases that blockthem from seeing potentially more effective oralternative problem-solving approaches (Nelsonand Winter, 1982). Firms are often less receptiveto knowledge from abroad (Gupta and Govin-darajan, 2000), instinctively reacting negativelyto external ideas—the so-called not invented heresyndrome. Furthermore, research has shown thatfirms have difficulties with technology transferwhen the source is “not perceived as reliable”(Szulanski, 1996).

Over the past two decades, several researchershave highlighted the increasing importance andgrowth of multicountry collaborations in the globalinnovation strategies of firms (Guellec and vanPottelsberghe de la Potterie, 2001; OECD, 2004;Yamin and Otto, 2004). Though the majority ofpatents list more than one inventor (as inventorsoften work in teams), these types of innovationsrefer specifically to collaborative innovations byinventors located in different countries. Whileprior research has focused on the rise in multi-country collaboration within European countries

Figure 1. Growth in the proportion of collaborativepatents by U.S. MNCs from 1989 to 2004.

(Guellec and van Pottelsberghe de la Potterie,2001; OECD, 2004; Yamin and Otto, 2004),there has also been an increase in multicountrycollaborations for U.S. MNCs as shown inFigure 1, which displays the rise in the propor-tion of multicountry collaborative patents by U.S.MNCs each year from 1989 to 2004.

Researchers who have focused on multicountrycollaborations (Bergek and Berggren, 2004; Guel-lec and van Pottelsberghe de la Potterie, 2001;OECD, 2004) argue that these types of collabora-tions can enhance the flexibility and formation ofnew innovation processes within multinational cor-porations (Yamin and Otto, 2004; Zander, 2004).However, just as transferring knowledge cannot betaken for granted (Kogut and Zander, 1993; Teece,1977), not all firms will be able to combine knowl-edge from different source locations to generatenovel innovations. In addition, extant research onknowledge sharing more generally has not tendedto analyze how the outcomes and subsequent usageof shared knowledge generation may differ fromother types of firm innovation (for exceptions, seeHaas and Hansen, 2007; Hansen, 1999; Hender-son and Clark, 1990), limiting our understand-ing of whether or how cross-country combinativeknowledge can differ from other firm innovations.Below, I explore conditions that can allow firms toovercome some of the difficulties associated withboth international R&D and cross-country knowl-edge sharing and the benefits firms can achievefrom these types of multicountry collaborativeinnovations. I start by considering how more basicrelationships that come from cross-border manu-facturing integration can lead to higher level col-laborate relationships for knowledge generation.


872 H. Berry

Manufacturing integration and knowledgecollaboration

Knowledge sharing is difficult, even within orga-nizations (Ambos and Ambos, 2009; Szulanski,2000; Zander and Kogut, 1995). Past researchshows that one way to encourage knowledgesharing is to establish intraorganizational rela-tionships that link subunits together (Almeida,Grant, and Song, 1998; Phene and Almeida, 2008)because knowledge sharing is facilitated by priorrelationships (Hansen, 1999; Levin and Cross,2004). Studies have shown that firms can benefitfrom both strong and weak relationships (Flem-ing, Mingo, and Chen, 2007; Hansen, 1999), withstrong ties allowing for more successful sharingand integration of complex knowledge (Hansen,1999; Reagans and McEvily, 2003) and weakties providing access to nonredundant and diverseknowledge (Burt, 2004; Hansen, 1999). Strongrelationships are often necessary for tacit knowl-edge transfer (Gupta and Govindarajan, 2000;Levin and Cross, 2004; Reagans and McEvily,2003) because these types of relationships createfamiliarity and trust, which supports an environ-ment of sharing and mutual understanding (Rea-gans and McEvily, 2003). But weak ties havebeen shown to help firms overcome problems withgroupthink or recycling of ideas (Burt, 2004; Har-gadon and Sutton, 1997).

An important intraorganizational linkage thathas remained underresearched in the knowledge-sharing literature comes from manufacturing inte-gration. This despite the fact that product per-formance has been shown to be significantlyenhanced if manufacturing is involved in productdesign (Bergen and McLaughlin, 1988) becausein many contexts, product design cannot happenwithout a deep understanding of the manufactur-ing process (Pisano and Shih, 2012). Manufactur-ing has been shown to be a particularly importantsource of process innovation (Hatch and Mow-ery, 1998), with learning-by-doing on the produc-tion floor providing new ideas and improvements(Argote, 1999), and close linkages between designand manufacturing often being necessary for suc-cessful product innovations (Gomes et al., 2003).Michael Idelchik, vice president of AdvancedTechnologies for GE Global Research (who holds12 patents), argues that without a strong footholdin manufacturing, the ability to innovate can besignificantly compromised because researchers can

lose their understanding of the manufacturing pro-cess and what it can do (Rotman, 2012). Productdevelopment researchers have increasingly iden-tified the interaction among components and sys-tems as one of the most important issues in manag-ing new product development (Baldwin and Clark,2000; Eppinger et al., 1994; Ulrich, 1995).

Manufacturing integration occurs when firmsorganize their operations so that one unit isproviding inputs that are used in another unit’smanufacturing activities. There are two primarybenefits that MNCs can gain from integrating theirmanufacturing activities across their worldwideoperations. First, firms can gain advantages fromspecialization, where advanced technology man-ufactured in one location provides componentsand inputs for operations in a different location(Bernard, Jensen, and Schott, 2009; Feenstra andHanson, 1997; Hanson, Mataloni, and Slaughter,2005). Second, firms can benefit from moreefficient production from arbitraging factor costdifferentials across countries (Brainard, 1997;Hansson, 2005; Head and Ries, 2002). For eachof these benefits to occur, firms need to align theiroperations, share manufacturing and productioninformation, and exchange technology and designsupport (Handfield, 1993). Knowledge and infor-mation sharing is necessary to not only cut downon total costs, but to also coordinate and transferknowledge for product adaptations or alterations.

When firms integrate their manufacturing activi-ties, they tend to have high coordination and infor-mation sharing across their operations (Patel andPavitt, 1999), suggesting that manufacturing tiesacross firm operations located in different countriescan provide MNCs with increased communicationand common experiences with firm products andproduction processes. Furthermore, these manufac-turing relationships create overlapping competen-cies, with a common knowledge platform acrossthese units. When foreign operations are inte-grated through product and component transferswith other firm operations, they create relation-ships both in production lines and through indi-vidual contacts that can provide more opportuni-ties for complex knowledge transfers, which canenable further extensions to a firm’s knowledgeassets from more diverse sources.

The World Investment Report (UNCTAD,1998) has described the case of Ford’s productintegration in Europe, when it decided to integrateits European production operations and perform



specialist tasks within each plant. Ford applied thisapproach to the production of the Ford Fiesta. Fordhas three final assembly plants located in Spain,the UK, and Germany. These plants assemble bodypanels into a finished car using components andparts produced at nine other locations in differentparts of Europe, each of which specializes in a fewspecific components. Through product integration,these operations have become very dependent oneach other, with the performance of one opera-tion highly dependent on other firm operations.This type of integration increases the need forcommunication, joint planning, and goal setting.More recently, in their 2011 annual report, Forddescribes how they have established one lead prod-uct development engineering center for each vehi-cle (for the Focus, this center is in Germany), witheach hub supported by regional engineering cen-ters to help deliver products tuned to local marketcustomer preferences. Ford has thus created bothspecialized production with high levels of knowl-edge sharing across its subunits so that its worldcar can both be produced more efficiently throughglobal platforms and offer advances in technologythat come from different locations. Ford benefitsfrom the strong relationships it has createdacross its manufacturing operations because ithas combined the best ideas and know-how fromacross its operations to generate technologicaladvances in both manufacturing processes andnew product designs. Herrigel and Zeitlin (2010)give examples of not only automobile industryfirms but also electronics firms as pursuing thesetypes of complex integration strategies.

Manufacturing integration also allows foreignoperations to have increased visibility and promi-nence. Ferdows (1997) has documented howHewlett-Packard’s (HP) Singapore operationsevolved from a manufacturing site that producedcalculators for other MNC operations to one thatperformed R&D and codeveloped a new printerfor HP. In HP’s case, product integration createdopportunities for new knowledge generation,while also reducing biases against foreign R&Dand inertial tendencies around R&D. Foreignoperations that have higher product integrationwith home country operations are likely to be morevisible (Hansen and Haas, 2001) and prominent tothe parent firm operations, who tend to control theR&D function in firms. When foreign operationsdevelop a reputation for quality, this can help toaugment further collaborations (Hansen and Haas,

2001; Monteiro, Arvidsson, and Birkinshaw,2008). Strong connections across units located indifferent country markets can help subsidiariesbe perceived as reliable (Levin and Cross, 2004;Reagans and McEvily, 2003; Szulanski, 1996)to the parent firm operations, as in the case ofHP. Manufacturing ties across firm operationslocated in different countries can thus allow firmsto both share complex knowledge and draw fromdifferent pools of knowledge in more effectiveways. These ties can help reduce biases againstnew and different approaches to both productdesign and production, and help the foreignsource of new knowledge be perceived as reliable(Szulanski, 1996). Thus, the communicationschannels, common knowledge, and visibility thatare created when two units integrate their produc-tion can be particularly helpful in overcoming thedifficulties associated with combining knowledgefrom different country locations.

These arguments form the basis of the firsthypothesis. Manufacturing ties across firm opera-tions located in different countries provide connec-tions and information sharing on firm product andproduct processes, establish relationships acrossindividuals located in different countries, and pro-vide increased visibility and prominence with otherfirm operations. Manufacturing ties thus help tocreate the conditions necessary for multicountryknowledge sharing and innovation within MNCS.

Hypothesis 1 (H1): Multicountry knowledgegeneration is more likely in foreign operationsthat have higher manufacturing integration withother MNC operations.

Diverse technological knowledge

It has long been argued that MNCs are in aunique position to gain competitive advantagefrom knowledge recombination that integratesdiverse streams of knowledge across their geo-graphically dispersed operations (Cantwell, 1989).Knowledge recombination occurs when differenttypes of expertise are synthesized into novel ideasor when competencies are reconfigured due to newinsights from new sources of knowledge (Eisen-hardt and Martin, 2000; Galunic and Rodan, 1998).Because countries offer different knowledge pro-files (Furman et al., 2002), foreign subsidiariescan tap into knowledge in host countries thatmay not exist elsewhere in the MNC’s operations


874 H. Berry

(Alcacer and Chung, 2007; Almeida and Phene,2004; Ambos, 2005; Singh, 2008). When firmengineers, employees, and inventors from differ-ent country locations come together to generatenew knowledge, they are likely to draw on thisdiversity and bring together different perspectivesand ideas from their local country environment.Foreign operations that are working on similarproduct lines give MNCs access to multiple per-spectives and experiences that can be integratedto generate new production processes or prod-ucts for firms. Firms can thus extend, develop,and transform their knowledge base by combin-ing home and foreign knowledge (Subramaniamand Youndt, 2005) as new insights and competen-cies from foreign operations can trigger modifica-tions in the firm’s knowledge base (Galunic andRodan, 1998).

In contrast, single country foreign innovationsare not as likely to bring together such diverseknowledge. Similar to home country innovations,innovations that are generated in a single for-eign country are more likely to build on theexpertise that is available within that one loca-tion. In contrast to accessing nonredundant anddiverse knowledge (Burt, 2004; Hansen, 1999),single country innovations are more likely to suf-fer from the groupthink or recycling of ideas(Burt, 2004; Hargadon and Sutton, 1997) that cancome from individuals with similar backgroundsand perspectives. Further, single country foreigninnovations are not as likely to offer multina-tional firms the types of innovations that otherfirms will have difficulty replicating (Gupta andGovindarajan, 2000; Kogut and Zander, 1993;Martin and Salomon, 2003) without being inthe same multiple country locations. By bring-ing together inventors who are located in differ-ent countries, multicountry collaborations are morelikely to bring together knowledge and ideas fromdifferent perspectives, cultures, backgrounds, orknowledge clusters. Thus, in the second hypoth-esis, I posit that multicountry collaborative inno-vations are more likely to draw from a widerpool of knowledge than single country foreigninnovations:

Hypothesis 2 (H2): Multicountry collaborativeinnovations are more likely to draw from a widerbase of technological knowledge than singlecountry innovations.

Subsequent knowledge development

In addition to bringing together more diverseknowledge, multicountry collaborations are likelyto differ from single foreign country innovationsin one other respect that relates to further inter-nal development of firm knowledge. When firmshave interdependencies in their manufacturing andknowledge activities, it is easier and more likelythat these firm innovations will be leveraged withineach of these operations to obtain maximum valueand returns (Alcacer and Zhao, 2012; Zhao, 2006).An organization with strong internal knowledgelinkages will be able to detect and absorb internalfirm innovations and increase the lead time overcompetitors (Cohen, Nelson, and Walsh, 2000;Levin et al., 1987). Further, several studies haveshown that when firms strategically increase inter-dependencies across their operations, they canminimize loss from knowledge spillovers to com-petitors (Alcacer and Zhao, 2012; Feinberg andGupta, 2009; Zhao, 2006), suggesting that estab-lished knowledge linkages across firm operations,can be used in subsequent knowledge developmentprojects that involve proprietary firm know-how.For multinational firms in particular, innovationscan be further developed both in the locationsin which the knowledge originated and in otherfirm operations that have linkages with the focaloperations.

More basic, multicountry collaborations canalso make further development of that knowledgeinside the firm more likely because they pro-vide internal “springboards” (Chung and Yeaple,2008) that can foster the development of subse-quent firm knowledge based on this newly com-bined firm knowledge. The strong relationshipsthat come from manufacturing integration acrossfirm operations provide a sense of group owner-ship in these different country-based operations,which makes it more likely that collaborators willadopt and extend these ideas (Fleming et al., 2007;Hansen, 1999). This is particularly relevant formulticountry firm collaborations because separatecountry operations of the firm have intimate con-tact with the knowledge that has been generatedthrough collaborative innovations, suggesting thatboth further collaborations across these geograph-ically separated operations and even subsequentdevelopment of this knowledge within each ofthese operations will result. Thus,



Hypothesis 3 (H3): Multicountry collaborativeinnovations are more likely to be further devel-oped within MNCs than single country foreigninnovations.

DATA

To examine my hypotheses, I combined confiden-tial firm-level data on the worldwide operationsof U.S. MNCs from the BEA with data on theworldwide patents of these firms from the USPTO.Every year, the BEA collects detailed informationon the foreign operations of U.S. MNCs, whichinclude data reported for U.S. parent companiesand their foreign affiliates. Because the BEA sur-veys are mandatory, these data provide the mostcomprehensive information on the operations ofU.S. MNCs that is available.2

In the BEA data, separate survey reports arefiled for U.S. parent companies and their foreignaffiliates. For foreign affiliates of a given U.S. par-ent company in a given host country, reporting ona consolidated basis for multiple affiliates is per-mitted if the affiliates operate in the same detailedindustry or are otherwise integral parts of thesame business operations. This means that firmsmay have multiple affiliates in one annual countryreport that is returned to the BEA. This also meansthat I do not have foreign addresses for eachforeign affiliate of each U.S. MNC. Instead, I havecountry information on the foreign operations ofthese firms. Because I do not know when an MNChas aggregated their affiliate data, I aggregatedall foreign affiliate information to the countrylevel for each MNC in each year. This means thatthe foreign operations of each MNC refer to thecountry level of operations for each firm.

Because patents from different patent authoritiesacross the world are not comparable to each other,it is common practice to use data from a singlepatent-granting country (Jaffe and Trajtenberg,2002) to standardize the measure of innovation.Given that I am analyzing U.S. MNCs, I use dataon U.S. patents from the USPTO. I included all

2 Specifically, the International Investment and Trade in ServicesSurvey Act requires U.S. MNCs to report detailed informationon the financial and operating activities of both U.S. parentcompanies and their foreign affiliates, as well as informationon the value of transactions between the parents and affiliates.(See Mataloni and Yorgason, 2006, for a thorough descriptionof definitions and survey methodology used by the BEA.)

patent applications between 1989 and 2004 thatwere ultimately granted by the USPTO.

The difficult part of analyzing how foreigninputs relate to foreign outputs is that thereare no numerical identifiers across the USPTOdatabase or almost any other database that hasfirm-specific information. Instead, one is left withthe names of firms across these databases asthe common identifier on which to merge. Toidentify unique firm names from the BEA data, Ifirst identified over 5,000 unique U.S. parent firmnames in the BEA database over the 1989–2004time period. I then matched these names withthe USPTO names.3 After researching the addressand locations of all parent firm name matches,I found that 3,048 firms applied for patents thatwere ultimately granted during this time period.This means that roughly 60 percent of all U.S.MNCs patented during the time period. I restrictedthe sample to manufacturing industries (SIC codes200–399) because product-flow measures are lessmeaningful for service industries and the majorityof the patents (80%) were granted to firms whosemain industry is manufacturing. Of the 3,048 U.S.MNCs with patents during my time period, 1,742classify themselves as manufacturing firms.

The USPTO has recorded the name, address,and country of each inventor on each patent.Following standard practice, I consider the coun-try of residence of the inventors as the countrywhere an innovation takes place. For summaryinformation, I follow the majority rule approachand assign a patent to the country with the mostnumber of inventors. (This approach turns outto be very similar to a first-inventor approach,as inventor names are not alphabetical and themajority country is often the first listed countryon international patents.) Using the majority ruleapproach, 621 MNCs applied for patents that wereultimately granted that have at least one foreigninventor included. This translates to 35% of U.S.manufacturing MNCs who patent as having atleast one foreign-invented patent. In total, thesefirms were granted 37,051 patents with at leastone foreign inventor during the 1989–2004 timeperiod. This compares to a total of 333,690 U.S.patents for these 1,742 MNCs. This translates

3 I am extremely grateful to Juan Alcacer for sharing his name-matching program that I used to match firm names across theBEA and patent databases.


876 H. Berry

to 11 percent of all new patents by U.S. MNCsbeing foreign patents.

MEASURES

Dependent variable

To operationalize multicountry knowledge genera-tion, I consider the foreign patents that have beengranted to U.S. MNCs by the USPTO that haveinventors from more than one country.4 For apatent to be granted, it must be novel, legally defin-able, and nonobvious. I included all patent appli-cations during the period 1989–2004 that wereultimately granted when creating this measure.

Independent variables

My main independent variables are manufactur-ing integration (for H1), technology diversity (forH2), and forward self-citations (for H3). For man-ufacturing integration, the BEA collects informa-tion on product transfers to and from both parentsand affiliates. This measure includes both inter-mediate and final products (and does not breakthis information down). I created my measure byaggregating information on the product inflowsand outflows to and from affiliated operations inother countries. I then scaled this measure by totalsubsidiary sales. (More specifically, I created aratio of the sum of total exports to the parentfirm, plus total imports from the parent firm, plustotal exports to other third-country affiliates, anddivided that number by the total sales of the for-eign operation to examine product integration.)

To examine the knowledge diversity that is thefocus of the second hypothesis, I used Hall et al.’s(2001) measure of originality—which is essen-tially a measure of technological diversity consid-ering backward patent citations. This measure canbe defined as:

Originality Index = 1 −n∑

j

s2ij

where sij refers to the proportion of citations madeto patents in technology class j. Higher originality

4 To clarify, those patents that are not categorized as collab-orative often include more than one inventor—however, theyhave all inventors from the same country and, therefore, do notinvolve multicountry collaborations.

measures indicate more diffuse backward citationsof technology classes, implying that a wider arrayof technologies are being utilized in the innovation(Hall et al., 2001; Jaffe et al., 1993). I weightedthis measure by the average originality measure forall patents in the same primary technology class.

To analyze subsequent development of knowl-edge for the third hypothesis, I examined the ratioof forward self-citations to total citations. Citedpatents are a technological antecedent of the citingpatent (Jaffe and Trajtenberg, 2002), and I consid-ered future MNC patents that cite the focal patentto be extending and further developing this firmknowledge.

Foreign operation and MNC control variables

R&D has been widely used as a measure offirm investment in knowledge assets (Berry andSakakibara, 2006; Buckley and Casson, 1976;Morck and Yeung, 1991), and the BEA collectsdata on the R&D expenditures for each foreignaffiliate and parent firm. I created time-varyingmeasures of foreign operation R&D intensity bydividing total country R&D expenditure by totalcountry sales in each foreign country operation.I also created a measure of parent firm R&Dintensity by dividing total U.S. R&D expendituresby total U.S. sales. In addition, I included eitherthe count of prior year patents (in the HECKPROBresults) or a stock measure of prior country patentsby the foreign operation in the host country (inthe MLOGIT results). I included the log of totalcountry operations to control for the size of foreignoperations in the specific foreign country. I alsoincluded the log of MNC worldwide assets.

I also controlled for product and geographicdispersion differences across firms. I include theproduct diversity (Palepu, 1985) of each firm tocapture the technological diversity of a firm anduse a Herfindahl-type index that considers salesacross three-digit SIC codes. I used the followingformula to calculate this variable:

Product Diversity =∑

i=1

Pi ∗ ln (1/Pi )

where P is the proportion of the firm’s sales withinthe each i th three-digit SIC code. I also includeda measure of the parent firm R&D intensity (mea-sured as U.S. R&D expenditures divided by U.S.



sales) to capture product market differences. Sim-ilar to the inclusion of a firm’s product diversity,I included each firm’s geographic dispersion andcalculated a Herfindahl-type index that considershow dispersed firm assets are across all of thefirm operations. This measure is defined as:

Geographic Dispersion = 1 −n∑

I=1

(Xi)2

where n is the number of countries (including thehome country), and x is the share of each countryin the firm’s total assets. This index ranges fromzero (minimum dispersion—all assets in onecountry) to one (when assets are evenly dividedacross the n countries). I also controlled for theproduct lines of foreign operation. I calculatedthe percent of foreign operation sales that are inthe same main three-digit industry as the parentfirm’s main industry. Main parent firm industryis defined as the industry with the highest sales inthe United States.

For country controls, I include several variablesthat can impact the attractiveness of doing R&Din that location. Several studies have shown manycountry level variables to significantly influenceforeign R&D locations (Alcacer and Chung, 2007;Ambos and Ambos, 2009; Berry, 2006; Chung andYeaple, 2008), and I incorporate many of thesehost country location attributes. I start by includingthe log of gross domestic product (GDP) to proxyfor host country size and the lagged difference inGDP per capita to capture growth in each country.Geographic distance can impact performancebecause it may be difficult to oversee and conductbusiness activities in distant countries, and Iinclude a measure of the geographic distance ofthe host country to the United States. These time-varying variables come from the World Bank’sWorld Development Indicators (WDI). I includeda control for political risk in each country usingHenisz’s (2000) PolConV time-varying values forpolitical constraints faced by political actors in thepolicy environment in the country. I also includeda measure of openness, captured by inward for-eign direct investment (FDI) as a percent of GDP(from the WDI). In my HECKPROB, I include ameasure to capture the knowledge distance acrossthe United States and the host country. Thismeasure comes from Berry, Guillen, and Zhou(2010) and is based on the difference in the total

number of patents per population and number ofscientific articles per population across countries.In the MLOGIT estimation (where the dependentvariable is specific to one patent), I captured thestrength of host country knowledge in the technol-ogy class of the new foreign patent itself. I usedpatent inventor country and main ICL technologyclass data to calculate the percent of worldwidepatents in each technology class that is generatedin the host country of the foreign operation in eachyear. I used patent stocks for both the numeratorand denominator for this variable, calculatedusing a 15 percent depreciation rate (Hall, Jaffe,and Trajtenberg, 2005). I also included a measureto capture cultural distance across the UnitedStates and each host country in the HECKPROBmodels. This measure comes from Berry et al.(2010) and uses World Values Surveys time-varying data to approximate Hofstede’s culturalvalues.5

I also controlled for differences in the protec-tions for firm intellectual property across countries.I used Park’s (2008) updated index of patent pro-tection (from the original Ginarte and Park, 1997,index). This measure incorporates the unweightedsum of separate scores for coverage, member-ship in international treaties, duration of protec-tion, enforcement mechanisms, and restrictions. Iconsidered several other proxies to capture this,including Zhao’s (2006) dummy variable basedon a consolidation of separate indices, includingKaufmann et al.’s (1999) Rule of Law index, theU.S. Trade Representative’s Special 301 Prior-ity Watch List, producing similar results to thosereported below. In addition, the results are thesame whether I use a one- or three-year lag, and Ireport the one-year lagged results below.

Tables 1 and 2 describe each variable andprovide summary statistics and correlations for allvariables. In all of my models below, I use laggedvalues for all independent variables and includethree-digit industry and year dummies.

METHODS

To examine my hypotheses, I used both firm-and patent-level estimations. To examine my first

5 Though the inclusion of this culture measure reduces thesample size in the HECKPROB results reported below, itsinclusion does not alter the results for my main independentvariables.


878 H. Berry

Table 1. Summary statistics (mean and S.D.) and correlations

1 2 3 4 5 6 7 8 9

1. R&DIntensity 0.007 (0.03) 1.02. Manufacturing integration 0.22 (0.13) 0.28 1.03. Patent originality 1.0 (0.52) 0.02 0.04 1.04. Patent SelfCitesRatio 0.11 (0.08) −0.02 0.02 −0.01 1.05. CoreSales 0.66 (0.44) 0.01 0.09 −0.03 0.06 1.06. Sales 10.71 (2.20) 0.34 −0.14 −0.03 0.05 0.22 1.07. GeoDispersion 0.52 (0.18) −0.06 −0.01 −0.01 0.03 0.14 0.30 1.08. ProductDiversification 0.74 (0.53) −0.03 0.02 0.01 0.06 −0.28 0.07 −0.04 1.09. ParR&DIntensity 0.03 (0.05) 0.03 −0.11 −0.05 −0.08 0.04 −0.13 −0.07 −0.25 1.010. MNCNewPatents 18.65 (128.3) −0.01 0.06 −0.01 0.21 0.18 0.28 0.19 0.03 −0.1011. LogWWAssets 15.59 (1.89) −0.08 −0.04 0.01 0.05 0.01 0.41 0.12 0.22 −0.2312. LogGeoDist 8.81 (0.55) 0.02 −0.10 −0.01 −0.13 −0.07 −0.01 0.24 −0.18 −0.0113. LogGDP 26.40 (1.44) −0.09 −0.05 −0.06 −0.02 0.01 0.24 0.10 0.22 0.0614. PolConV 0.76 (0.19) 0.01 0.05 0.01 0.04 −0.04 −0.01 −0.14 0.18 0.0115. CountryTechKnowledge 0.44 (0.06) 0.08 0.03 0.05 −0.02 0.03 −0.19 −0.09 −0.26 0.0116. KnowledgeDist 20.6 (11.04) 0.06 0.17 −0.01 −0.32 −0.10 −0.04 0.21 −0.17 −0.0417. CulturalDist 13.9 (7.3) 0.01 −0.05 0.02 −0.25 −0.09 −0.04 0.06 −0.24 −0.0318. Openness 0.04 (0.22) 0.05 −0.00 0.02 −0.15 0.09 −0.08 0.06 −0.38 0.0619. IPIndex 4.01 (0.22) −0.04 0.01 −0.01 0.01 0.04 0.09 −0.03 0.10 0.1120. GDPCapGrowth 0.02 (0.11) −0.04 −0.06 −0.02 0.03 0.04 −0.04 0.07 0.03 0.07

11 12 13 14 15 16 17 18 19 20

11 LogWWAssets 0.20 1.012 LogGeoDist −0.30 −0.06 1.013. LogGDP 0.10 0.05 0.06 1.014. PolConV 0.11 0.03 −0.32 0.0415. CountryTechKnowledge −0.06 0.06 −0.06 0.3316. KnowledgeDist −0.04 −0.09 0.38 0.14 0.30 1.017. CulturalDist −0.19 0.02 0.41 −0.26 −0.43 −0.31 1.018 Openness −0.13 −0.11 0.28 −0.22 −0.28 0.32 0.05 1.019 IPIndex 0.18 0.02 −0.26 0.24 0.22 −0.12 −0.13 −0.35 1.020 GDPCapGrowth 0.10 −0.02 −0.08 −0.03 −0.11 0.14 −0.01 −0.02 −0.08 1.0

hypothesis, I used a HECKPROB model at the firmlevel of analysis. I have concerns about the unob-servable “knowledge strategy” of my MNCs (asforeign R&D expenditures represent only 11 per-cent of total R&D expenditures by these firms).Some MNCs may not consider foreign markets atall in their knowledge activities, and I incorpo-rate a first-stage equation with foreign R&D asthe dependent variable to limit this selection bias.I use a variation of Heckman’s selection modelcapable of estimating binary outcomes in both theselection and estimation equations. The bivariatePROBIT model with sample selection (HECK-PROB) produces a series of coefficients that havebeen adjusted to account for firms doing R&D inthe host country. These models are jointly esti-mated by using full information maximum likeli-hood estimation. I included industry fixed effects

and year fixed effects in all analyses. I also clus-tered by the parent-country operation.

It is necessary in Heckman-style models toinclude a unique variable that predicts the outcomein the selection equation but not in the estimationequation. The exclusion restriction I included isthe extent of import penetration into the UnitedStates, which is measured as the ratio of foreignimports to U.S. domestic shipments using datafrom Schott (2004). A higher share of imports intothe U.S. domestic market suggests that foreignfirms have advanced capabilities to compete withU.S. firms. This would lead to increasing pres-sures to become more competitive across foreignmarkets, which is likely to require increasingattention to differences across markets (thoughhigher local R&D expenditures) by U.S. firms(Hutzschenreuter and Grone, 2009). I would notexpect foreign competitor import penetration in the



Table 2. Description of variables (sources)

Dependent variables 0/1 in HECKPROB, 1 = foreign operation has new foreign patents (broken down toinclude multicountry collaborative patents and noncollaborative patents)

For MLOGIT: Three categories of foreign patents:1—all inventors from one foreign country2—multicountry patents with U.S. and foreign inventors (par-sub)3—multicountry patents with foreign inventors (sub-sub)

(All dependent variables come from the USPTO data.)Independent variablesManufacturing integrationt1 For each foreign operation, lagged exports and imports with parent and other firm

operations divided by total sales (BEA data)Patent originality For each foreign patent, Hall et al.’s (2001) originality measure to capture the diversity

of cited technology classes. This measure has been weighted by the averageoriginality measure for all patents in the firm’s primary technology class (USPTO)

Patent self-citation ratio For each foreign patent, the ratio of forward citations to total citations (USPTO)R&D intensityt-1 For each foreign operation, lagged R&D expenditures divided by total sales (BEA data)Log salest-1 For each foreign operation, lagged log of total sales (BEA data)Parent R&D intensityt-1 Lagged parent firm R&D expenditures in the United States divided by its U.S. sales

(BEA data)Core industry salest-1 For each foreign operation, lagged percent of sales that are in the main three-digit

manufacturing industry of the U.S. parent firm (BEA data)Geographic dispersiont-1 For the MNC, lagged Herfindahl-type index that calculates how dispersed a firm’s assets

are across all country operations (see text for formula). Zero would be no geographicdispersion (BEA data)

Product diversificationt-1 For the MNC, a Herfindahl-type index that calculates how dispersed a firm’s sales areacross three-digit SIC codes (see text for formula). Zero is no product diversity (BEAdata)

MNC sizet-1 Lagged log of a firm’s total U.S. and foreign assets (BEA data)MNC new patentst-1 In HECKPROB: Lagged count of new MNC patents (USPTO)MNC patents in countryt-1 In MLOGIT: Lagged count of all prior country patents by the foreign operation in that

host country (USPTO)Log geographic distancet-1 Log of host country distance to United States (WDI data)Log GDPt-1 Lagged log of GDProduct of host country (WDI data)GDP/Cap growtht-1 Lagged first difference in GDP per capita for host country (WDI data)Opennesst-1 Lagged inward FDI as a percent of GDP (WDI data)IP index Ginarte and Park’s index of patent rights, incorporating coverage, membership in

international treaties, duration of protection, enforcement mechanisms, andrestrictions. (Park, 2008, provides updated data to the Ginarte and Park, 1997, index.)

POLCONVt-1 Henisz’ PolconV index of political constraints (Henisz, 2000)Cultural distancet-1 In HECKPROB: Lagged cultural distance using World Values Surveys time-varying data

to approximate Hofstede’s cultural values (from Berry et al., 2010)Knowledge distancet-1 In HECKPROB: Lagged knowledge distance between the United States and the host

country, based on the total number of patents by total population and number ofscientific articles by total population (from Berry et al., 2010)

Country tech knowledget-1 In MLOGIT: For each foreign patent, the lagged percent of total patents (to worldwidepatents) in the same technology class that originate from that host country in that yearusing first inventor country assignment (USPTO–NBER data)

ForeignImportPenUSt-1 In HECKPROB: The lagged extent of import penetration into the United States,measured as the ratio of foreign imports to U.S. domestic shipments using data fromSchott (2004)

United States to have a significant impact on U.S.firm foreign-invented patents, but rather to have amore limited impact on localization and adaptationof existing firm products and imports. There is asignificant difference in model fit when I includeimport penetration in the first stage. Inclusion ofthis variable in my patent estimation confirms that

it does not have a significant relationship withfirm foreign patenting. To examine how productintegration affects collaborative patenting by firms,I ran separate models predicting multicountrypatents and single country patents.

To examine my second and third hypotheses,I used a multinomial logit (MLOGIT) model (at


880 H. Berry

the foreign patent level of analysis) to analyzesignificant differences across collaborative andnoncollaborative foreign patents. To categorize thepatents of firms, I considered the proportion ofcountry inventors on each firm patent and brokemy sample into three categories: (1) noncollabo-rative single country foreign patents; (2) collab-orative multicountry patents with U.S. inventors(parent-subsidiary collaborations); and (3) collab-orative multicountry patents with no U.S. inventors(subsidiary-subsidiary collaborations). A Hausmantest to check for the independence of irrelevantalternatives (IIA) assumption in MLOGIT modelsiteratively drops one option and tests whether thecoefficients significantly change. The results fromthis test (and separately run Small-Hsiao tests)show that the three categories are independent ofeach other. In an MLOGIT model, the probabilitiesof occurrence of each option are normalized withrespect to one of them, usually the one that occursmost frequently in a given sample. In the currentsample, noncollaborative single country foreigninventor patents occur most frequently, and theyare the base category. I continue to use industryfixed effects, year fixed effects, and cluster by theparent country. I also include a lagged stock ofcountry patents by the MNC in the host countryof the foreign operation.

For robustness, I also perform a zero-inflatednegative binomial (ZINB) model to be able tocontrol for the decision to patent in foreign coun-tries. Although not reported below, the outcomeequation results were very similar across theHECKPROB and ZINB analyses. In addition, I rannegative binomial models with firm fixed effectsand probit models with random effects and, again,

though not reported below, the results for each ofthese are similar to the results reported below formy main variables of interest.

RESULTS

Before discussing the empirical results, it isinteresting to consider some of the trends inthe combined BEA and USPTO dataset. Forexample, at the foreign operation level, 1,464(9%) have patents and 3,159 (19%) do R&D.This translates into 46 percent of the foreignoperations of firms doing R&D also generatingpatents, suggesting that about half of the foreignoperations of U.S. MNCs that do R&D alsogenerate new patents. This corresponds withKuemmerle’s (1999) finding that 45 percent of theforeign R&D labs in his sample were establishedfor knowledge augmentation, with the remainderbeing done for home base exploiting of parent firmknowledge (by modifying products to suit localmarkets, for example).

Table 3 shows longitudinal trends for themain variables of this study. The first rowshows that overall foreign patenting has beenincreasing over the time period. The second, third,and fourth rows reveal different trends acrosscollaborative and noncollaborative patenting byU.S. MNCs and shows a significant increase inthe proportion of multicountry patenting by U.S.MNCs over the 1989–2004 time period. By 2004,the collaborative patent categories make up morethan one-third of all new foreign patents, andthis table shows that this growth has been drivenby increases in parent-subsidiary collaborations.

Table 3. Trend analysis for main foreign operation and foreign patent variables

Average

Variable 1989 2004 Longitudinal trend

U.S. MNC average number of foreign patents 1.48 2.38 0.23** (2.54)Noncollaborative patents (same foreign country inventor patents)

proportion0.77 0.64 −0.18*** (−3.38)

Collaborative patent with U.S. inventors (parent-subsidiary patents)proportion

0.21 0.32 0.34** (2.48)

Collaborative patents with foreign inventors (subsidiary-subsidiarypatents) proportion

0.02 0.03 NS

Manufacturing integration 0.24 0.32 0.23** (2.31)

NS = not significant. Longitudinal trend is calculated as the coefficients of a linear trend measure in fixed effects panel regressionswith time trend as the only predictor. T -stats are in parentheses.Significance level (two-sided): *< 10%; **< 5%; ***< 1%.



Table 3 also shows that both foreign affiliate R&Dintensity and product transfers have been risingover this time period.

Table 4 reports results from the HECKPROBmodel. This model reports impact of manufactur-ing integration on multicountry collaborative inno-vation conditional on firms doing foreign R&D,thus controlling for unobserved firm heterogeneityregarding firm propensities to engage in foreignR&D. The correlation between the error term inthe outcome model and the error term in the selec-tion model (rho) is significantly different from zeroacross each column, confirming the necessity ofthe selection model.

The first column in Table 4 shows the results forall new firm foreign patenting, while the secondand third columns break out firms with new mul-ticountry collaborative patents and single country(noncollaborative) patents. In the first hypothesis, Iargued that multicountry knowledge generation ismore likely in foreign operations that have higherproduct integration with home country operations.The results show that product integration has asignificant impact on multicountry collaborativepatents (column two), but not on single countryforeign patents (column three), and Z−tests (Pater-noster et al., 1998) confirm that there is a sig-nificant difference between the coefficients acrossthese two samples (p < 0.01). Hypothesis 1 thusreceives support in the HECKPROB model.

The controls in the HECKPROB model behavemostly as expected. Prior patenting has the largestmarginal effect across all of the coefficients inevery model. R&D intensity in the foreign oper-ation is significant and positive. Both the size ofthe foreign operation and the size of the coun-try are positive and significant, reinforcing priorfindings that larger foreign operations and largercountries play an important role in the foreigninvestment strategies of firms. The geographic dis-persion of MNCs is also positive and significant,though the product diversity of MNCs is not sig-nificant (though it is negative). Not too surpris-ingly, foreign patents are generally more likely tocome from countries that have more stable policies(more policy constraints) and have better intellec-tual property protections.

Table 5 shows results at the foreign patentlevel of analysis. Coefficients in MLOGIT modelsexpress how much the given variables influencethe probability relative to the base case. Here,

the base case is foreign single country (or non-collaborative) patents. This means that the coeffi-cients reveal statistical differences across the coef-ficients from the category under consideration andthe base case. The first column of Table 5 showsthe results comparing parent-subsidiary multicoun-try collaboration and the second column showsthe results for subsidiary-subsidiary multicountrycollaboration. Marginal effects for each of thesecomparisons are reported in columns 3 and 4,respectively. I also report the marginal effectsfor the comparison between the parent-subsidiarymulticountry collaborations with the subsidiary-subsidiary multicountry collaborations in the fifthcolumn.

The first and second columns in Table 5,(which compare parent-subsidiary collaborationswith noncollaborative patents [category 2 ver-sus category 1] and subsidiary-subsidiary col-laborations with noncollaborative patents [cate-gory 3 versus category 1], respectively), showthat product integration is positive and statisti-cally significant, providing support for the logicin the first hypothesis. Both parent-subsidiaryand subsidiary-subsidiary multicountry collabora-tions come from foreign operations with signifi-cantly higher manufacturing integration than non-collaborative foreign patents. The odds ratios arereported in brackets, and these show that the oddsof a collaborative parent-subsidiary multicountrypatent relative to a single country noncollabo-rative patent are 2.34 times greater for foreignoperations with a one standard deviation increasein manufacturing integration. The correspondingincrease is 1.56 for subsidiary-subsidiary multi-country patents. There is no significant differenceacross parent-subsidiary and subsidiary-subsidiarycollaborations.

The second hypothesis predicted that multicoun-try collaborative innovations are more likely todraw from a wider base of technological knowl-edge than single country innovations. The mainvariable of interest in the second hypothesis isHall et al.’s (2001) originality index, which usesbackward citations to measure the technologicaldiversity of the patent. (As noted above, thisindex has been weighted by the average origi-nality index for the primary technology class.)Columns 1 and 2 in Table 5 show that bothparent-subsidiary and subsidiary-subsidiary mul-ticountry collaborations have significantly higher


882 H. Berry

Table 4. HECKPROB results: multicountry and single country foreign patent generation

Dependent variable: 0/1, in (1), 1 = has new foreign patents; in (2), 1 = has new multicountry collaborative patents;in (3), 1 = has new single country foreign patents

Model All foreign patents (2) Multicountry (3) Single country

H1: Manufacturing integrationt-1 0.21* 0.37* 0.10(2.81) (5.21) (0.92)[0.06] [0.09] [0.02]

R&D intensityt-1 2.91* 1.99* 3.02*(4.11) (2.73) (4.05)[0.24] [0.21] [0.28]

Salest-1 0.07** 0.03 0.11*(2.42) (1.41) (2.80)[0.06] [0.04] [0.10]

Core industry sales percentt-1 −0.02 0.16* −0.06(−1.39) (2.44) (−1.14)[−0.02] [0.04] [−0.01]

Parent R&D intensityt-1 0.47** 0.85* 0.41(2.16) (2.84) (1.32)[0.14] [0.08] [0.11]

MNC new patentst-1 0.01* 0.01* 0.01*(4.95) (4.76) (4.89)[1.55] [0.74] [1.62]

Geographic dispersiont-1 −0.17 0.35** −0.72*(−1.26) (2.19) (−2.86)[−0.02] [0.03] [−0.09]

Product diversificationt-1 −0.09 −0.04 −0.10**(−2.56) (−1.44) (−2.43)[−0.03] [−0.01] [−0.03]

MNC sizet-1 0.10 0.04 0.10(1.46) (.30) (1.13)[0.03] [0.02] [0.03]

Geographic distancet-1 0.01 −0.01* 0.02(1.18) (−2.02) (1.41)[0.01] [−0.01] [0.01]

Log GDPt-1 0.09* 0.16* 0.08(3.72) (4.93) (1.58)[0.03] [0.04] [0.01]

IP indext-1 0.28* 0.29* 0.18(3.45) (3.48) (1.78)

[−0.04] [−0.06] [−0.04]GDP/Cap growtht-1 0.02* 0.02* 0.01**

(3.33) (3.51) (2.01)[0.01] [0.01] [0.01]

Knowledge distancet-1 −0.01*** −0.01*** −0.01***(−3.46) (−3.55) (−3.35)[−0.01] [−0.01] [−0.01]

PolConVt-1 0.60* 0.39 0.68*(2.48) (1.59) (2.59)[0.05] [0.03] [0.06]

Cultural distancet-1 −0.01** −0.02** −0.01(−2.05) (−3.15) (−1.82)[−0.01] [−0.02] [−0.01]

Opennesst-1 1.32** 1.89* −0.47(2.06) (3.86) (−0.71)[0.41] [0.27] [−0.23]

Constant −2.31* −2.81* −1.79**(−3.12) (−3.94) (−2.04)



Table 4. Continued

Dependent variable: 0/1, in (1), 1 = has new foreign patents; in (2), 1 = has new multicountry collaborative patents;in (3), 1 = has new single country foreign patents

Model All foreign patents (2) Multicountry (3) Single country

Selection equation: dependent variable:0/1, 1 = R*D Expenditures > 0

Manufacturing integrationt-1 0.11** 0.12** 0.11**(2.11) (2.17) (2.09)

Salest-1 0.13* 0.13* 0.12*(4.85) (4.85) (4.31)

Parent R&D intensityt-1 0.22** 0.22** 0.23**(2.04) (2.03) (2.03)

Geographic dispersiont-1 0.15** 0.19** 0.12(1.98) (2.19) (1.66)

Product diversificationt-1 0.06** 0.06** 0.02(2.01) (1.98) (1.41)

MNC sizet-1 0.11* 0.12* 0.07**(2.45) (2.86) (2.01)

Log GDPt-1 0.11* 0.11* 0.11*(4.91) (4.92) (4.91)

IP indext-1 −0.02* −0.02* −0.02*(−2.87) (−2.89) (−2.87)

GDP/Cap growtht-1 0.02* 0.02* 0.02*(3.28) (3.26) (3.26)

Knowledge distancet-1 −0.01* −0.01* −0.01*(−3.46) (−3.55) (−3.35)

Cultural distancet-1 −0.01** −0.01** −0.01**(−2.05) (−1.96) (−2.02)

PolConVt-1 −0.01* −0.01** −0.01*(−3.84) (−2.06) (−3.77)

Opennesst-1 −0.48 −0.47 −0.51(−0.71) (−0.72) (−0.96)

Foreign import penetration in USt-1 2.96* 2.95* 2.94*(4.03) (3.98) (4.01)

Rho/alpha 0.33* 0.33* 0.37*(4.62) (4.62) (4.68)

Log likelihood −7640.6 −7248.1 −6278.6Industry dummies Yes Yes YesYear dummies Yes Yes YesClustered by firm-country Yes Yes YesNumber of observations 9434 9434 9434

All models include robust standard errors. Test of independent equations for HECKPROB: (1) χ2 = 21.95***; (2) χ2 = 8.74***; (3)χ2 = 6.21***. [Marginal Effects] in HECKPROB model are conditioned on the selection equation.Significance level (two-sided): *< 10%; **< 5%; ***< 1%.

technological diversity than single country for-eign patents. The odds ratios show that parent-subsidiary multicountry patent relative to a singlecountry noncollaborative patent have a 1.21 timeshigher technological diversity. The correspondingincrease is 1.17 for subsidiary-subsidiary multi-country patents. There is no significant differenceacross parent-subsidiary and subsidiary-subsidiarycollaborations.

Finally, the third hypothesis argued that mul-ticountry collaborative innovations are morelikely to be further developed within MNCsthan single country foreign innovations. Thishypothesis receives support for parent-subsidiarymulticountry collaborations only. Table 5 showsthat the self-citation ratios for parent-subsidiarycollaborations are positively and significantly


884 H. Berry

Table 5. MLOGIT results for multicountry and single country foreign patent generation

Dependent variable: 1 = single country foreign patent (sub only); 2 = multicountry patent with U.S. inventors(par-sub); 3 = multicountry patent with foreign inventors (sub-sub)

Coefficients, comparing Marginal effects, comparing

Model comparison: 2 with 1 3 with 1 2 with 1 3 with 1 2 with3

H1: Manufacturing integrationt−1 0.09*** 0.06** [2.34]*** [1.56]** [1.21](2.49) (2.01)

H2: Originality indext-1 0.47*** 0.39*** [1.21]*** [1.17]** [1.04](3.49) (2.81)

H3: Self-citation ratiot-1 0.55*** 0.08 [1.73]*** [1.19] [1.59]**(3.60) (0.78)

R&D intensityt-1 −0.03 −0.06 [0.94] [0.81] [1.43](−0.97) (−1.45)

Salest-1 −0.12*** −0.15*** [0.78]*** [0.71]*** [1.05](−3.64) (−3.51)

Parent R&D intensityt-1 −1.15 −1.27 [0.93] [0.88] [0.92](−0.43) (−1.39)

Core industry salest-1 0.42*** 0.26** [1.26]*** [1.14]** [1.04](2.96) (2.24)

MNC patents in countryt-1 −0.01*** −0.01* [0.87]*** [0.73]* [0.95](−2.83) (−1.72)

MNC geographic dispersiont-1 1.33*** 1.65*** [1.22]*** [1.35]*** [.91](2.31) (3.04)

MNC product diversityt-1 0.11 0.01 [1.08] [1.01] [1.05](0.95) (0.15)

MNC sizet-1 0.16*** 0.21*** [1.11]*** [1.18]* [1.03](2.82) (3.14)

Geographic distancet-1 −0.29** −0.35** [0.87]** [0.84]** [1.03](−2.04) (−2.11)

Log GDPt-1 −0.01 −0.12** [0.96] [0.93]** [1.11](−1.01) (−2.12)

Country patent knowledget-1 0.32 0.24 [1.07] [1.04] [1.01](0.88) (0.67)

Political distancet-1 −0.74 0.17 [0.95] [0.97] [0.93](−1.53) (0.29)

IP indext-1 0.03 −0.38 [1.02] [0.91] [1.11](0.52) (−1.49)

Opennesst-1 −0.12 −0.08 [0.78] [0.86] [0.94](−1.03) (−0.54)

GDP/Cap growtht-1 0.01 0.01 [1.01] [1.02] [0.97](0.31) (0.41)

Constant 1.42 2.45**(1.09) (2.21)

Log likelihood −7994Industry and year dummies YesClustered by firm-country YesNumber of observations 19,813

All models include robust standard errors.Significance level (two-sided): **< 5%; *< 1%.

different from both subsidiary-subsidiary collab-orations and noncollaborative patents. The oddsratios show that parent-subsidiary multicountrypatents relative to a single country noncollabora-tive patent have a 1.73 times higher self-citationratio. The last column shows that parent-subsidiary

multicountry patents have a 1.59 times higherself-citation ratio than subsidiary-subsidiarymulticountry patents.

In the MLOGIT models, I included the stock ofa firm’s patents in the host country. This variable issignificant and negative for both parent-subsidiary



and subsidiary-subsidiary collaborations, whichsuggests that U.S. MNCs are more likely to docollaborative patenting when they have fewer for-eign patents in the host country. The technol-ogy class country patent knowledge variable ispositive, but not significant, suggesting that hostcountry technological capabilities have a similarimpact across all three categories of patents. Othervariables that are significantly different include thesize of foreign operations and the geographic dis-persion of MNCs. The foreign operations that docollaborative patents tend to be smaller than thosethat do noncollaborative patents while the MNCstend to be larger, and those operations that dosubsidiary-subsidiary collaborations tend to comefrom smaller countries. In addition, the resultsshow that multicountry collaborative patents tendto come from foreign operations with higher salesin the main product line of the parent firm.

Finally, theory would suggest that foreign opera-tions are likely to go from more basic product inte-gration to knowledge collaboration. However, onecould argue that foreign operations may becomemore integrated after those operations start doingmore collaborative foreign patenting. Given thatMNCs tend to be very reluctant to internationalizetheir R&D (R&D is the last value chain activitythat firms take abroad, and only 11 percent of U.S.MNCs’ R&D expenditures are done in foreignmarkets on average), it is unlikely that these for-eign collaborations are driving manufacturing inte-gration. In addition, if this were driving the presentresults, I would not expect to see significant differ-ences across the parent-subsidiary collaborationsand the subsidiary-subsidiary collaborative patentsin terms of subsequent usage. This suggests thatthe current lagged structure is appropriate, withthe results showing a significant effect from man-ufacturing integration to knowledge collaboration.

DISCUSSION AND IMPLICATIONS

Although extant research has long argued that firmabilities to share, integrate, and generate knowl-edge across their operations play a key role indriving both international expansion and perfor-mance (Gupta and Govindarajan, 2000; Kogut andZander, 1992, 1993; Szulanski, 1996) and despitethe fact that several studies have documented a risein multicountry collaborations (Guellec and vanPottelsberghe de la Potterie, 2001; OECD, 2004;

Yamin and Otto, 2004), there hasn’t yet been suf-ficient examination of the factors that can enableMNCs to achieve this type of global innovation. Inaddition, extant research has not tended to analyzehow the outcomes from shared knowledge genera-tion differ from other types of firm innovation (forexceptions, see Haas and Hansen, 2007; Hansen,1999; Henderson and Clark, 1990), limiting ourunderstanding of whether or how multicountry col-laborative innovations may differ from other firminnovations. Further, while multinational corpora-tions are in unique positions to access diverse setsof technical inputs across their operations from avariety of country locations, the mere possessionof knowledge-based advantages does not by itselfguarantee that a firm will be able to exploit or aug-ment the sources of this advantage in their foreignoperations (Ambos and Ambos, 2009; Martin andSalomon, 2003). Just as transferring knowledgecannot be taken for granted (Kogut and Zander,1993), not all firms will be able to combine knowl-edge from different source locations to generatenovel innovations.

This paper extends our understanding of com-binative knowledge generation within MNCs byconsidering how more basic relationships thatcome from cross-border manufacturing integra-tion can lead to higher level relationships thatinvolve multicountry collaborations on innova-tion. Building on the knowledge-based view ofthe firm and the foreign knowledge-seeking lit-eratures, I argue that communication channels,common knowledge, and increased visibility thatcome from manufacturing integration can enableforeign operations to play increasingly importantroles in innovation processes, and the results showthat more basic relationships that have been estab-lished through integrated manufacturing can leadto collaboration on innovation. In so doing, thispaper emphasizes the importance of evolving andpath-dependent parent-affiliate relations in both theforeign knowledge sourcing strategies of firms andthe successful realization of combinative capabili-ties for MNCs.

This paper contributes to our understanding ofhow both strong and weak ties provide benefitsto MNCs in terms of accessing diverse knowl-edge that resides across their operations. Extantliterature examining the influence of social inter-actions on creativity has highlighted a tensionbetween the benefits that strong and weak ties canproduce for firms (Fleming et al., 2007). While


886 H. Berry

strong ties allow for better tacit knowledge trans-fer (Hansen, 1999; Reagans and McEvily, 2003),weak ties have been shown to provide access tononredundant and more diverse knowledge (Burt,2004; Hansen, 1999). When foreign operationsare working on similar product lines and produc-ing firm products or component parts, the strongrelationships through which tacit knowledge isexchanged across these operations can also pro-vide access to foreign ideas that can be integratedwith existing firm knowledge to generate new pro-duction processes or products for firms. Thesemanufacturing ties thus incorporate the beneficialaspects of both strong and weak social interac-tions across geographically distant firm operationsby allowing for the exchange of tacit and diverseknowledge.

This paper also shows how collaborative inno-vations differ from other foreign patents in termsof technological diversity and subsequent usage.Bartlett and Ghoshal (1989) asserted over 20 yearsago that firms that operate in a variety of coun-try environments are exposed to multiple stimulithat provide them learning opportunities to developunique competencies from those found at home.In this view, one of the key advantages of inter-national expansion is its greater opportunity togenerate more diverse innovations. The data usedin this paper reveal that an increasing share ofU.S. firms’ foreign innovations are multicountrycollaborative innovations and that these innova-tions are based on a wider pool of knowledge thansingle foreign country patents, and more likely tobe used in subsequent innovations than other for-eign patents. These results suggest that these moretechnologically diverse patents serve as internalspringboards (Chung and Yeaple, 2008) for firms.By combining knowledge from different countryoperations, MNCs exploit knowledge from differ-ent source locations (Phene and Almeida, 2008),reinforcing the idea that these firms are gain-ing competitive advantages that other firms willhave difficulty replicating (Gupta and Govindara-jan, 2000; Kogut and Zander, 1993; Martin andSalomon, 2003).

The results also show some unanticipated find-ings. For example, there is a significant differencein the self-citation ratio of parent-subsidiarycollaborations versus subsidiary-subsidiary col-laborations. While increased visibility and highquality interactions (Hansen and Haas, 2001) canlimit tendencies toward isolation (Monteiro et al.,

2008), the results in this paper suggest that theU.S. parent firms play a dominant role in determin-ing when collaborative innovations will be usedin subsequent innovations. Foreign manufacturingoperations that are integrated with their parentfirm are often dependent on the parent for inputsinto their production processes, which gives thehome country operations leverage in determiningthe changing role of those foreign operations. Inaddition, the trends in Table 3 show that parent-subsidiary collaborations are driving the significantincrease in multicountry patenting within U.S.MNCs (with subsidiary-subsidiary increasing at alower rate). This suggests that headquarters mayplay an important role in determining when collab-orative knowledge is undertaken. At a minimum,it suggests that the involvement of U.S. inventorsplays a critical role in pushing and extending mul-ticountry collaborative knowledge further withinthe firm. Future research could certainly explorethe role of home country inventors in knowledgeextension and subsequent development withinthe firm.

For managers, these results suggest that manu-facturing integration across firm operations createties that can enable firms to achieve collaborativeinnovations that combine diverse knowledge.Though several academic studies highlight theimportance of knowledge integration and recombi-nation, there are fewer studies that show how firmsarrive at knowledge integration and recombinationacross their operations. This paper finds that bybuilding manufacturing connections across oper-ations that work on different aspects of the firmproducts, MNCs may be able to overcome prob-lems associated with the “not invented here” syn-drome or from organizational groupthink. Thoughintrafirm, cross-border product transfers withinMNCs account for about one-third of all worldtrade (UNCTAD, 2004; Zeile, 1997), the impli-cations of manufacturing integration on MNCs isunderresearched (Bernard et al., 2009). Of course,the results in this study by no means suggest thatmulticountry innovations will automatically hap-pen for all firms who invest in intrafirm manu-facturing integration. Intrafirm cooperation acrossmanufacturing activities and across manufactur-ing and innovation activities is likely to requiremanagerial oversight and incentives. However, theresults in this paper suggest that this cooperationacross manufacturing and R&D activities is bothoccurring and providing competitive advantages in



the forms of more diverse technological innova-tions for U.S. MNCs.

Relevant to managers and academics alike, thispaper documents the growing importance of mul-ticounty collaborations by U.S. MNCs. Over thepast two decades, the proportion of multicountrycollaborations has grown from one-fifth to one-third of all foreign patents by U.S. MNCs. Thispaper thus examines an important phenomenon ininnovation that is being used by more and moreMNCs as they manage their knowledge assets andwork toward generating new innovations acrosstheir operations. Thus, this study highlights theknowledge benefits that MNCs can achieve fromintegrated manufacturing activities.

There are limitations to this study. First, as withall studies on innovation, there is no perfect wayto assess innovation by firms. Though patents arewidely used in research to capture innovative out-puts (Jaffe and Trajtenberg, 2002), they certainlydo not capture all innovation. Second, the empir-ical analysis is limited to U.S. MNCs. While thedata from the BEA contain the most comprehen-sive information available on the worldwide oper-ations of U.S. firms, the results may not general-ize beyond U.S. MNCs. Alternate and additionalmeasures of both inputs and outputs and otherdatasets are certainly warranted to further ourunderstanding of the issues explored in this paper.Finally, while I have access to very rich data onthe operations of U.S. MNCs, I do not know whenemployees might be assigned to other locations. Inthis paper, I have used the patent inventor locationsto determine when multicountry patenting occurs.I cannot determine whether firm employees moveduring a project but still report their home coun-try on the patent. Future research could certainlyexplore this limitation to better understand howemployee movement within MNCs impacts bothknowledge sharing and generation.

Overall, this paper emphasizes the importanceof manufacturing relations in the global innovationstrategies of MNCs while documenting changingpatterns in the foreign patenting of U.S. MNCs.While single country foreign patents still consti-tute the majority of new foreign patenting by U.S.MNCs, the trends in this paper show significantincreases in the proportion of multicountry collab-orations in the global innovations of these firms.Though foreign knowledge offers firms the poten-tial for new knowledge creation, this paper focuses

on conditions that can help firms to achieve col-laborative and combinative knowledge generation.It also provides evidence that these collabora-tive innovations not only bring together morediverse knowledge, but also that this combinedknowledge is used in subsequent innovations bythese firms.

ACKNOWLEDGEMENTS

The statistical analysis of firm-level data on U.S.multinational companies was conducted at theBureau of Economic Analysis (BEA) United StatesDepartment of Commerce under arrangements thatmaintain legal confidentiality requirements. I thankBill Zeile and Ray Mataloni for helpful discussionson the BEA data. I also thank associate editorKulwant Singh, Phil Anderson, Mauro Guillen,Vit Henisz, Aseem Kaul, Bruce Kogut, and anony-mous referees for helpful comments on earlier ver-sions of this paper, and Juan Alcacer for help withmatching firm names across the BEA and USPTOdata. Views expressed in this paper do not reflectthose of the BEA or the United States Departmentof Commerce. Finally, this paper was writtenduring my time as an ASA/NSF/BEA fellow at theBEA, and I gratefully acknowledge that funding.

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