offshoring innovation to emerging markets: organizational control and informal ... ·...

Offshoring innovation to emerging markets:Organizational control and informalinstitutional distance

Michael A Sartor andPaul W Beamish

Ivey Business School, Western University, London,Canada

Correspondence:Michael A Sartor, Ivey Business School,Western University, 1255 Western Road,London, Canada N6G 0N1.Tel: +1 519-281-6122

Received: 28 March 2013Revised: 8 May 2014Accepted: 28 May 2014Online publication date: 21 August 2014

AbstractThe literature on innovation offshoring has focused on the dichotomous choicebetween two distinct investment strategies – captive offshoring and outsourcedoffshoring. We use the concept of organizational control to investigate howdifferences in the informal institutions that prevail in the home and host countriesinfluence multinational enterprise (MNE) strategy (or, the organizational controldecision) with respect to subsidiaries established to offshore innovation. Whilethe relationship between formal institutions and MNE strategy has been thesubject of considerable academic scrutiny, less is known about the role ofinformal institutions. We propose that the type of uncertainty precipitated byinformal institutions is critical to understanding the strategic behavior of foreign-investing MNEs. We hypothesize that an MNE’s organizational control over asubsidiary will be contingent upon the type of informal institutional uncertaintyencountered by the subsidiary. More specifically, we disaggregate the informalinstitutions construct and develop three new, more explicit, latent constructs –behaviorally-oriented informal institutions (BOII), technology-oriented informal insti-tutions (TOII) and demand-oriented informal institutions (DOII). Our theory positsthat while an increase in BOII distance will precipitate a preference for greaterorganizational control, heightened TOII and DOII distances will induce theopposite outcome – a preference for lower levels of organizational control.Journal of International Business Studies (2014) 45, 1072–1095. doi:10.1057/jibs.2014.36

Keywords: informal institutions and uncertainty; informal institutional differences; foreignmarket entry; emerging markets/countries/economies; country risk; innovation and R&D

INTRODUCTIONMultinational enterprises (MNEs) have increasingly engaged inthe practice of offshoring innovation (or, foreign market-basedinnovation) (Bertrand & Mol, 2013), particularly in emerging mar-kets. The growing prevalence of the phenomenon is surprisingbecause emerging markets have generally been regarded as havingweak intellectual property (IP) rights protection systems (Zhang, Li,Hitt, & Cui, 2007). Investing successfully in emerging markets hasroutinely been complicated by concerns regarding technology leak-age or appropriability hazards (Pisano, 1989). MNEs that choose todevelop their IP abroad are faced with the incessant challenge ofdetermining how to protect these intangible assets. Notwithstand-ing the presumed difficulties associated with offshoring innovation,

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a number of explanations have been proposed forthis growing trend, including cost savings (Zhao,2006), the need for new product and process innova-tions (Nieto & Rodríguez, 2011), access to globaltalent pools (Lewin, Massini, & Peeters, 2009), andproximity to growth markets (Govindarajan &Ramamurti, 2011). Efforts to formulate theory thatcan be used to explain how MNEs choose to executethese strategic offshore investments have focusedprimarily on delineating two distinct approaches –

captive offshoring (in which the MNE engages ininnovation activities through its own subsidiary inan offshore market) and offshore outsourcing (inwhich the MNE fully outsources innovation activ-ities to an independent foreign supplier) (Kedia &Mukherjee, 2009).Notwithstanding these advances, our understand-

ing of emerging market-based innovation continuesto be underdeveloped (Asakawa & Som, 2008;Demirbag & Glaister, 2010) for two principle rea-sons. First, scholars have suggested that the currenttheoretical framework lacks robustness because itconceptualizes innovation offshoring as a dichoto-mous choice. Here captive offshoring generallydescribes a fully internalized or integrated model ofoffshoring, while offshore outsourcing representsa fully externalized or non-integrated model. Inresponse, researchers have proposed that a morenuanced range of strategies are being employed byMNEs that engage in innovation offshoring ( Jahns,Hartmann, & Bals, 2006; Nieto & Rodríguez, 2011).Second, scholars have argued that greater attentionneeds to be given to the impact of institutional-levelfactors on the strategic investment decisions ofMNEs that choose to offshore innovation (Kedia &Mukherjee, 2009). In fact, institutional uncertaintyhas been argued to provide a natural startingpoint for explaining the strategic decisions of MNEsthat engage in emerging market-based innovation(Demirbag & Glaister, 2010). Scholars have tradi-tionally formulated theory pertaining to MNE stra-tegies under conditions of heightened institutionaluncertainty by leveraging two constructs developedto facilitate institutional analysis (North, 1990). For-mal institutions are written laws, rules and regula-tions. Informal institutions are norms of behavior,codes of conduct, practices and conventions. Whilethe impact of formal institutions, such as IP rightsprotection systems and FDI restrictions, on thegovernance of these subsidiary investments is well-established (Gomes-Casseres, 1990; Hagedoorn,Cloodt, & Van Kranenburg, 2005; Zhao, 2006), farless is known about the role of informal institutions.

We address the aforementioned limitations in theinnovation offshoring literature in two ways. First,we use the concept of organizational control and,second, we investigate how institutional uncertaintyprecipitated by differences in the informal institu-tions that prevail in the home and host marketsimpact the organizational control decisions of MNEsthat engage in emerging market-based innovation.We define organizational control as the degree towhich an MNE integrates an offshore subsidiarythrough its equity investment and partnering deci-sions. In doing so, we endeavor to garner a morefine-grained understanding of the range of foreignentry strategies employed by MNEs that engage inemerging market-based innovation.Against this backdrop, we leverage the tenets of

transaction cost theory (TCT) to elaborate an uncer-tainty-based conceptualization of informal institu-tions. To date, two key challenges have limited thepredictive insights generated by research that hasfocused on the taxonomy of institutions (formal vsinformal). First, unlike formal institutions, the infor-mal institutions construct has not been rigorouslyconceptualized (Estrin & Prevezer, 2011). Second,the relative lack of theory pertaining to informalinstitutions has resulted in a wide range ofapproaches being employed to incorporate the con-struct into research studies. Scholars that havesought to incorporate informal institutions into theirstudies have tended to operationalize the constructeither very broadly, using one of the various culturaldistance measures that are routinely employed ininternational business research, or very narrowly,using a study-specific range of indicators as a mea-sure of the construct (Galang, 2012). As a conse-quence, the informal institutions construct has notbeen extensively integrated into mainstream strat-egy theories or studies of institutions (Estrin &Prevezer, 2011). This is regrettable because scholarshave argued that some of the most significant differ-ences between countries can be attributed to differ-ences in informal institutions (Bruton, Ahlstrom, &Puky, 2009). A country’s informal institutions createexpectations and a shared understanding withrespect to the behavior that can be anticipatedwithin that country (Peterson & Thomas, 2007).Given that institutional distance is a major sourceof uncertainty for MNEs (Feinberg & Gupta, 2009;Santangelo & Meyer, 2011), more pronounced dif-ferences in the informal institutions that prevailwithin the home and host country markets willresult in heightened uncertainty for the foreign-investing MNE (Makhija & Stewart, 2002).

Offshoring innovation to emerging markets Michael A Sartor and Paul W Beamish1073

Journal of International Business Studies

A central premise of our work is that the type ofuncertainty precipitated by informal institutionaldifferences is a significant determinant of the strate-gic behavior (or, the organizational control decisions)of MNEs that engage in innovation offshoring.Accordingly, we develop theory that can be used toconceptualize informal institutions and their influ-ence on MNE strategy by building upon the long-established typology of uncertainties in TCT (Crook,Combs, Ketchen, & Aguinis, 2013; Geyskens,Steenkamp, & Kumar, 2006). We propose that infor-mal institutions can be associated with at least threeimportant types of uncertainty – behavioral uncer-tainty, technological uncertainty and demand uncer-tainty. We disaggregate the informal institutionsconstruct and introduce three new, more explicitconstructs – behaviorally-oriented informal institutions(BOII), technology-oriented informal institutions (TOII)and demand-oriented informal institutions (DOII). Ourtheory posits that where the difference in BOIIbetween the home and host markets is greater, MNEsthat offshore innovation to emerging markets willexercise greater organizational control over these sub-sidiary investments. Conversely, where TOII andDOII distance are more pronounced, these sameMNEs will prefer to relax their organizational controlover their subsidiary investments. Given that thethree types of uncertainty are assumed to existcontemporaneously (Khanna & Palepu, 1997), wealso develop theory and investigate the interactioneffects between BOII, TOII and DOII. We test ourtheory against the entry decisions associated with157 subsidiary investments made in 15 emergingmarkets during a nine-year period. The results yieldsupport for several of the predictions proffered byour theory and buttress the general proposition thatinformal institutions may affect the entry strategies ofMNEs (Meyer, Estrin, Bhaumik, & Peng, 2009).Our work makes two key contributions. First, we

advance understanding with respect to how MNEsstructure their offshore innovation subsidiaries bymoving beyond the strict dichotomous choicebetween captive and outsourced offshoring (Nieto& Rodríguez, 2011). To do so, we use the concept oforganizational control to provide a finer-grained viewinto the foreign entry strategies that MNEs executeto facilitate these investments. Second, we contri-bute to institution-based international strategy scho-larship by refining the conceptualization of informalinstitutions. In doing so, we provide a more nuancedtheoretical framework that can be used to incorpo-rate considerations of informal institutions intostrategy-focused research (Cantwell, Dunning, &

Lundan, 2010) and bolster efforts to generate moregeneralizable research results (Estrin & Prevezer,2011).

LITERATURE REVIEW

Organizational Control and Offshoring InnovationExtant theory pertaining to how MNEs offshoreinnovation has focused primarily on the distinctionbetween captive offshoring (in which the MNEengages in innovation activities through its ownsubsidiary in an offshore market) and offshore out-sourcing (in which the MNE fully outsources inno-vation activities to an independent foreign supplier)(Kedia & Mukherjee, 2009). However, researchershave begun to speculate that the broad spectrum ofinstitutional environments encountered by MNEsthat offshore their innovation to emerging markets(Demirbag & Glaister, 2010) might be precipitatinga richer mix of strategic responses than the dicho-tomous choice (captive vs outsourcing) that hasbeen elaborated to date (Nieto & Rodríguez, 2011;Su, Akkiraju, Nayak, & Goodwin, 2009). Consistentwith this perspective, Jahns et al. (2006) suggest thata wide range of contractual, legal and operationalarrangements are being employed by MNEs toimplement their offshoring strategy.In studying the strategy of MNEs that engage in

innovation offshoring, we leverage the researchtradition established by Doz and Prahalad (1984,1981) whose concept of strategic control providedthe theoretical foundation for subsequent concep-tual advances pertaining to organizational control inthe international joint venture literature (Chen,Paik, & Park, 2010; Yan & Gray, 2001). In doing so,we build on Rangan and Drummond’s (2011) recentassertion that the notion of strategic organizationalcontrol merits further development in the globalstrategy literature. To date, TCT has been one of thepredominant theoretical lenses employed to studysubsidiary control in international business research(Brock, Shenkar, Shoham, & Siscovick, 2008). How-ever, the theory has traditionally conceptualizedcontrol in terms of a firm’s choice between dis-crete governance modes (Williamson, 1985). Morerecently, scholars have begun to recognize that firmsare executing a wider array of strategic choices thatexist “along a make/buy continuum” (Parmigiani,2007: 285). International business scholars haveincreasingly shared this perspective. As examples,while Barden, Steensma, and Lyles (2005: 160)have argued that “control is more sophisticated thanthe one dimensional construct often assumed (in the



literature),” Li and Li (2010: 1552) have advocated“a finer-grained analysis of MNEs’ ownership strate-gies.” Control has been defined by Yan and Gray(2001: 397) to include “the mechanisms a partneremploys to ensure that the venture conforms to itsinterests.” Efforts to explain how firms respond toenvironmental uncertainties (Miller, 1992) andinstitutional pressures (Oliver, 1991) have yieldedtheory which proposes that the strategic responsesof firms can be characterized as varying in terms ofthe degree of control that the firm exercises. Scholarshave argued that an MNE’s control over a foreignsubsidiary investment is diminished when it dele-gates discretion to a host-country’s equity partners,suppliers and employees (Rangan & Drummond,2011). Consistent with this theory, MNEs have beenfound to exert greater control over their foreignsubsidiaries through the retention of equity(Malhotra & Gaur, 2014; Zhao, Luo, & Suh, 2004)and through their partnering decisions (Makino &Beamish, 1998).The extensive body of research that has investi-

gated the relationship between formal institutionsand MNE strategy (Hagedoorn et al., 2005; Zhao,2006) has reinforced the longstanding belief thatwhen formal institutions are more underdevelopedin the host market, MNEs will exert tighter controlover foreign subsidiaries that are established forthe purpose of engaging in innovation (Roth &Morrison, 1992). We extend this line of inquiry byfocusing on informal institutions. However, a centralthesis underpinning our work is that the degree oforganizational control that an MNE exercises withrespect to a foreign market-based innovation invest-ment will be contingent upon the type of informalinstitutional uncertainty precipitated by institu-tional differences between the home and hostmarkets.

Informal InstitutionsInstitutions include both the written rules and thenorms of behavior that humans implement toreduce uncertainty (North, 1990). However, institu-tions can also be a source of uncertainty and risk forinternationalizing MNEs, particularly when theseinstitutions are substantially different from the insti-tutions encountered in the home country (Eden &Miller, 2004). Prior research has established that firmstrategies and institutional environments are inter-dependent in emerging markets (Luo, 2007). Giventhat written rules, laws and regulations, or formalinstitutions, are explicit and can be easily measured,these institutions have been subject to considerable

scrutiny in the extant literature which has resultedin a robust theoretical conceptualization of the con-struct (Meyer & Peng, 2005).While informal institutions have traditionally

been given considerably less theoretical and empiri-cal attention than formal institutions, some scholarshave endeavored to incorporate the informal institu-tions construct into their work. Informal institu-tions have been argued to exert both direct andmoderating effects upon several aspects of an MNE’sforeign entry strategy (Bevan, Estrin, & Meyer, 2004;Schwens, Eiche, & Kabst, 2011; Yiu & Makino,2002). Nonetheless, the informal institutions con-struct has not been as rigorously conceptualized asformal institutions have been (Estrin & Prevezer,2011). This is not surprising. Scholars from business,law and political science have concurred that infor-mal institutions are significantly more difficult thanformal institutions to conceptualize (Bernstein &Hannah, 2008; Goodliffe & Hawkins, 2006; Luo &Deng, 2009). Consistent with this observation, North(1990: 36) has conceded that “it is much easier todescribe and be precise about the formal rules thatsocieties devise than to describe and be precise aboutthe informal ways by which human beings havestructured human interaction.” As a consequence ofthe more limited theoretical development surround-ing the informal institutions construct, researchershave employed a wide range of approaches whenoperationalizing and measuring the construct. A firstapproach has involved focusing on the role of formalinstitutions, to the exclusion of informal institutionsaltogether. Understandably, informal institutionshave proven to be a challenging construct for scholarsworking at the intersection between institutionaltheory and TCT because economic theory “runs intopredictable trouble accounting for something as elu-sive as… the domain of ongoing social relationships”(Nee, 1998: 85).As a second approach, scholars who have included

informal institutions in their studies have frequentlyemployed a broad operationalization of the con-struct, choosing to incorporate the variable usingcultural distance as a proxy for informal institutions(Galang, 2012). A principle challenge associatedwith this approach is that cultural distance hasbeen critiqued as being a less relevant driver ofmanagerial decision-making than perceptionsregarding the host market’s institutional environ-ment (Xu & Shenkar, 2002). In fact, Singh (2007b:424) has argued that “an institutional perspectiveoffers a more complete … measurement of nationaldifferences and environmental complexity than a



cultural perspective.” An added challenge associatedwith this approach is that cultural distance is a time-invariant construct (Hofstede, 2001). While manyresearchers have presumed that informal institu-tions are constant, prior work has suggested that thismay not be a valid assumption (Meyer & Peng,2005). In fact, in developing theory that expounds adynamic view of institutions and emphasizes theinterplay between changes in informal institutionsand formal institutions, Cantwell et al. (2010: 578)conclude that “institutional distance does not sim-ply equate to cultural distance.”A third approach has focused more narrowly,

employing different measures to operationalizespecific informal institutions, such as corruption(Galang, 2012). While the insights generated by thisthird approach have bolstered comprehension of thedistinction between formal and informal institu-tions operating in host markets, an unintendedconsequence of the practice has been to fosterinequivalence (Zhao et al., 2004) between the var-ious measures of a particular informal institution.This can pose implications for the generalizability offindings and the development of theory related toinformal institutions.A natural consequence of the routine application

of these divergent approaches is that they havegenerated inconsistent empirical findings. We illus-trate this trend in Table 1 by summarizing the resultsassociated with a small sample of studies that haveemployed at least one of these approaches to inves-tigate the relationship between informal institutionsand expatriate deployment which has been concep-tualized by some scholars as one strategy that anMNE can use to exert control over its foreign sub-sidiaries (Caligiuri & Stroh, 1995; Shay & Baack,2004). We do not critique the results associated withthe studies in Table 1. Instead, the disparate findingsare intended to demonstrate that theory is needed toestablish conceptual boundary conditions withinand around the informal institutions construct inorder to faciliate a more orderly development oftheory pertaining to the construct. Prior inconsis-tent empirical findings that have resulted from thecurrent theoretical foundation have garnered impor-tant theoretical consequences. Most notably, theinformal institutions construct has not been exten-sively integrated into mainstream strategy theoriesor studies of institutions (Estrin & Prevezer, 2011).This is a regrettable outcome given that informalinstitutions constitute a significant componentwithin the broader system of host market institu-tions (Bae & Salomon, 2010).

The Typology of Uncertainties: Behavioral andEnvironmentalIn addition to asset specificity and frequency, uncer-tainty constitutes one of the three attributes oftransactions that can precipitate an increase intransaction costs and influence the strategic beha-vior of MNEs (Williamson, 1985). Uncertainty is ameasure of the unpredictability of future outcomesand has been conceptualized in terms of behavioraluncertainty and environmental uncertainty (Crooket al., 2013). Behavioral uncertainty is the uncertaintyrelated to a transaction partner’s behavior (Griffith,Harmancioglu, & Droge, 2009: 218), whereas envir-onmental uncertainty is the perceived inability topredict the organization’s external environment.Environmental uncertainty includes both techno-logical uncertainty (the inability to fully comprehendaspects of the technological environment) (Song &Montoya-Weiss, 2001) and demand uncertainty (theinability to forecast the amount and type of outputsthat will be required in the marketplace) (Miller,1992). Notably, extant theory holds that heightenedbehavioral uncertainty will precipitate the oppositeoutcome with respect to governance choice whencompared with the effects of heightened technologi-cal uncertainty and demand uncertainty. While anincrease in technological and demand uncertaintieswill prompt firms to prefer hybrids over hierar-chies, under conditions of heightened behavioraluncertainty, firms will prefer vertical integration(Geyskens et al., 2006).Given institutional theorists’ concern with the

role of institutions in defining and protecting prop-erty rights, TCT has assumed a prominent positionin institutional analysis. A core tenet of institutionaltheory is that institutions bring order to economicexchange (North, 2005). However, institutions thatmake property rights less secure have the effect ofincreasing transaction costs (North, 1990). In emer-ging markets and transition economies, institutionsare a prime determinant of the size of transactioncosts (Murrell, 2005). While Williamson (1985: 56)contends that asset specificity is “the big locomo-tive” of TCT, Ménard and Shirley (2005) have arguedthat informal and formal institutions might be asimportant as asset specificity in influencing thechoice of governance structure. They implicitly sug-gest that institutional uncertainty is a significantforce in shaping the characteristics of exchange.Institutional distance is a major source of uncer-

tainty that influences the strategic behavior of MNEs(Feinberg & Gupta, 2009; Santangelo & Meyer,2011). Informal institutions have been identified as



a prominent origin of some of the most significantdifferences between countries (Bruton et al., 2009).A country’s informal institutions (norms, codes ofconduct, practices and conventions) create expecta-tions and a shared understanding with respect to thebehavior that can be anticipated within that country(Peterson & Thomas, 2007). More pronounced dif-ferences in the informal institutions that prevailwithin the home and host country markets willgarner heightened uncertainty for the foreign-investing MNE (Makhija & Stewart, 2002).

Given that we theorize that the type of uncertaintyprecipitated by these informal institutional differ-ences is a significant determinant of an MNE’sstrategic behavior, TCT’s taxonomy of uncertaintiesprovides an appropriate foundation upon which toerect a more nuanced, theoretically grounded con-ceptualization of informal institutions. Building onNorth’s (1990) definition of informal institutions(norms of behavior, codes of conduct, practices andconventions that guide social relations and businessactivities), we leverage the predominant typology of

Table 1 An overview of the approaches used to study the relationship between informal institutions and expatriate staffing

Study (Dependent variable) Independent variables Findings

Boyacigiller (1990)a

(Proportion of US nationals in aforeign branch’s workforce).

Formal institution (political risk)and cultural distance.

1. Weaker formal institutions predict a larger ratio of USnationals in the subsidiary.

2. An increase in cultural distance predicts a larger ratio ofUS nationals in the subsidiary.

Ando & Paik (2012)b

(Ratio of parent country nationals tototal subsidiary employees).

Institutional distance (formal/regulative) and cultural distance.

1. An increase in formal institutional distance predicts asmaller ratio of parent country nationals in thesubsidiary.

2. An increase in cultural distance predicts a smaller ratioof parent country nationals in the subsidiary.

Mezias & Mezias (2010)c

(Use of parent country nationals(expatriates) vs use of host countrynationals in the subsidiaryworkforce).

Conceptual paper: Informalinstitution (corruption).

Summary of propositions: Under conditions of heightenedhost market corruption, sociologically based theoriespredict increased use of host country nationals in thesubsidiary’s workforce, while economic-based theoriespredict increased use of parent country nationals(expatriates).

Gaur, Delios, & Singh (2007)c

(Percentage of expatriate parentcountry nationals in the subsidiaryworkforce).

Formal (regulative) institutionaldistance, informal (normative)institutional distance andcultural distance.

1. An increase in formal (regulative) institutional distancepredicts a larger ratio of parent country nationals in thesubsidiary.

2. An increase in informal (normative) institutionaldistance predicts a larger ratio of parent countrynationals in the subsidiary.

3. An increase in cultural distance predicts a smaller ratioof parent country nationals in the subsidiary.

Xu, Pan, & Beamish (2004)c

(Ratio of Japanese expatriates tototal employees in the foreignsubsidiary).

Formal (regulative) institutionaldistance, informal (normative)institutional distance andcultural distance.

1. An increase in formal (regulative) institutional distancepredicts a smaller ratio of parent country nationals inthe subsidiary.

2. An increase in informal (normative) institutionaldistance predicts a smaller ratio of parent countrynationals in the subsidiary.

3. An increase in cultural distance does not predict theratio of parent country nationals in the subsidiary.

aIncorporates formal (regulative) institutions to the exclusion of informal (normative) institutions.bIncorporates informal institutions using one of the various measures of cultural distance.cIncorporates a study-specific, multi-item measure of informal (normative) institutions.



uncertainties employed by TC theorists (behavioraluncertainty, technological uncertainty and demanduncertainty) to ground our theoretical disaggregationof the informal institutions construct into threemore explicit latent constructs. We define BOII asthe norms of behavior, practices and conventionsthat influence the exercise of managerial discretion.TOII are the norms of behavior, practices and con-ventions that influence the development and use oftechnologies. DOII are the norms of behavior, prac-tices and conventions that precipitate demand forgoods and services in the marketplace. Home andhost markets are characterized by unique institu-tional environments (Xu & Shenkar, 2002). Wepropose that while behavioral uncertainty arises fromthe extent to which BOII differ in the home and hostmarkets, technological uncertainty and demand uncer-tainty each arise from the extent to which TOII andDOII respectively differ between the home and hostcountry markets.

THEORYAND HYPOTHESES DEVELOPMENTA central premise of our work is that the type ofuncertainty engendered by BOII, TOII and DOIIinformal institutional differences respectively is animportant determinant of an MNE’s strategic beha-vior. This is because the predominant costs precipi-tated by behavioral uncertainty will be different fromthose precipitated by environmental uncertainties(technological and demand). Our efforts build uponNorth’s (1990: 43) recommendation that scholarsleverage TCT to advance comprehension of informalinstitutions because “although informal institutionsare not directly observable … the actual costs oftransacting provide indirect evidence of informalconstraints.” More specifically, while heightenedbehavioral uncertainty can be expected to increasethe costs of safeguarding IP assets from potentiallyopportunistic partners and employees (Dyer, 1997),heightened environmental uncertainties (technologicaland demand) can increase the MNE’s informationcosts and production costs associated with creatingnew IP assets (Atuahene-Gima & Li, 2004; Prashant,Harbir, & Howard, 2000). Consequently, the mech-anisms through which behavioral uncertainty andenvironmental uncertainty (both technological anddemand) will impact upon an MNE’s strategy (or,organizational control decisions) will be distinct. Tosummarize our theory in advance: we propose thatan increase in behavioral uncertainty, resulting fromincreased BOII distance, will predict an MNE’s pre-ference for increased organizational control becausethe MNE will focus on minimizing the potential

costs of opportunism. Conversely, an increase intechnological uncertainty or demand uncertainty,resulting from increased TOII and DOII distancesrespectively, will predict an MNE’s preference forreduced organizational control because the MNE willfocus on minimizing information and productioncosts through learning. Our theory is consistent withconceptual work by Verbeke (2003) who proposesthat an MNE’s strategic decisions are predicatedupon a consideration of both the firm’s need tominimize costs associated with opportunism, inaddition to the firm’s need to learn.

BOII and Organizational ControlNational informal institutions dictate the kinds oforganizational activity that are permissible (Dikova,Sahib, & Van Witteloostuijn, 2010). Informal insti-tutions shape the manner in which firms conducttheir business (Meyer & Peng, 2005), as well asinfluencing the exercise of managerial discretionand behavior by imposing constraints on managers’actions (Hambrick & Abrahamson, 1995). Con-straints on managerial discretion are a function ofthe degree to which a proposed course of managerialaction is regarded as objectionable (Crossland &Hambrick, 2011). A proposed course of managerialaction will be characterized as objectionable if itcontravenes accepted business practices, conven-tions, norms of behavior and codes of conduct inthe local market (Crossland & Hambrick, 2007).These accepted business practices constitute normsthat “specify how things should be done and deline-ate what a society perceives as acceptable behavior”(Estrin, Baghdasaryan, & Meyer, 2009: 1181). Thebehavior of local firms and managers with respect tobusiness practices and property rights, including IPassets, are guided by the beliefs, norms and attitudesthat prevail in the local market (Schotter &Teagarden, 2012; Yang, 2005). When these hostmarket beliefs, norms and attitudes differ from thosethat exist in the MNE’s home market, then beha-vioral uncertainty will increase. This is because theMNE will be less familiar with the expected behaviorof managers in the host country and the MNE willfind it more difficult to understand and predict thebehavior that can be anticipated with respect to its IPassets within that country (Peterson & Thomas,2007). Trust is predicated on informal institutions(Dikova et al., 2010). The perceived likelihood of IPappropriation is contingent upon home–host coun-try differences in the state of informal institutionssuch as behavioral norms (North, 1990).



Under conditions of heightened behavioral uncer-tainty and in the presence of highly specific assets,appropriation risks are perceived to be greater whichheightens the safeguarding costs incurred by thefirm (Williamson, 1985). As such, when BOII dis-tance is more pronounced, a foreign-investing MNEcan be expected to execute strategic decisions thatsupport its efforts to minimize the costs of opportu-nistic behavior. Scholars have argued that behavioraluncertainty should motivate an MNE to pursueincreased control over its subsidiary investmentsdue to the prospect of lower transaction costs asso-ciated with direct control (Brouthers & Brouthers,2003). Tighter control over subsidiary investmentshas been argued to attenuate the costs associatedwith monitoring the behavior of host market equitypartners (Luo, 2007). If more extensive behavioralmonitoring is anticipated as necessary, then anMNEis more likely to adopt strategies that focus onincreasing its oversight of the subsidiary (Gaur,Delios, & Singh, 2007). Accordingly, we hypothesizethat,

Hypothesis 1: Foreign-investing MNEs will exer-cise more organizational control over subsidiaryinvestments when the BOII distance between thehome and host countries is greater.

TOII, DOII and Organizational ControlFor MNEs engaged in innovation offshoring, techno-logical uncertainty and demand uncertainty will beclosely intertwined (Atuahene-Gima & Li, 2004)because the development of new innovations thatcan satisfy consumers in the market will be based ona profound understanding of both the technologicalenvironment and consumption behavior (Di Minin,Zhang, & Gammeltoft, 2012). Our theory proposesthat when a host market’s TOII or DOII are perceivedto be different from those found in the MNE’s homemarket, a foreign-investing MNE will encounterheightened technological uncertainty and demanduncertainty respectively upon entering into theforeign market.Proponents of the social shaping of technology

perspective maintain that the design and implemen-tation of technologies are precipitated by a widerange of social factors, in addition to the traditionaleconomic and technical considerations (Williams &Edge, 1996). The ongoing practices of social actorswho interact with these technologies constitutetechnological norms (Jones & Karsten, 2009). Con-sistent with this perspective, we propose that theTOII prevailing in a host market reflect the degree to

which technologically focused constituents in thehost country’s private and public sectors are engagedin activities designed to facilitate the development,transfer and growth of knowledge and technology inthe host country. Relatedly, the demand for newinnovations in a community emerges from theinteraction between new technologies and currentsocial practices in the course of working, learningand communicating (Orlikowski, 2000). Innovationdiffusion researchers have found that the diffusionof demand for new innovations is largely a socialprocess in which non-adopters in a market imitateadopters as a result of communication between thegroups (Dutta & Roy, 2005). Social ties and socialinteraction tend to accelerate the diffusion of newinnovations (Trkman, Jerman Blazic, & Turk, 2008).Ongoing social and economic practices that areshaped by the interests and values of a market’sconstituents further stimulate the demand for newinnovations (Orlikowski & Iacono, 2001).Extant research has revealed that MNEs from less

technologically advanced countries experience tech-nological and demand uncertainties upon enteringinto more technologically advanced foreign markets(Di Minin et al., 2012; Su, 2013). Similarly, MNEsfrom more technologically advanced countries alsoexperience technological and demand uncertaintieswhen entering into less technologically advancedforeign markets (Immelt, Govindarajan, & Trimble,2009). In both cases, the technological disparitybetween the home and host markets breeds uncer-tainty because the MNE is entering into a market inwhich it may be neither able to fully comprehendaspects of the prevailing technological environment,nor able to forecast the amount and type of innova-tion outputs required in the marketplace. Collec-tively, the observations of Di Minin et al. (2012)and Immelt et al. (2009) suggest that technologicaluncertainty and demand uncertainty will be lower for aforeign-investing MNE when the home and hostmarkets are more similar in terms of technologicaladvancement and in terms of demand for newinnovations.The inability to comprehend the technological

environment prevailing in the host market has beenidentified as an important obstacle inhibiting theefforts of developed-market MNEs to successfullydesign and sell new products and services in emer-ging markets (Tong & Li, 2008). Experience hassuggested that, when compared with the productsand services that are available to consumers indeveloped markets, customers in emerging marketsare demanding “decent performance at an ultralow



cost – a 50% solution at a 15% price” (Govindarajan,2012; Immelt et al., 2009: 57). As such, underconditions of heightened technological and demanduncertainties, identifying customer needs anddesigning products or services to satisfy those needsbecomes more complex (Song & Montoya-Weiss,2001). When technological and demand uncertain-ties are greater, innovation performance will beadversely affected by increased costs (Brown &Eisenhardt, 1995). Innovation and new productdevelopment under conditions of heightened tech-nological and demand uncertainties require moreiterative effort (Eisenhardt & Tabrizi, 1995) andforeign-investing firms risk becoming locked intoirrelevant or outmoded innovations (Geyskenset al., 2006). Failed efforts to source and producerelevant new knowledge can adversely impact thefinancial performance and survival of a firm(Mudambi & Tallman, 2010). Under conditions ofheightened TOII or DOII distances, we anticipate thatthe strategic decisions of foreign-investing MNEswill reveal a greater concern for the magnitude ofpotential costs associated with unproductive inno-vation efforts and getting locked into irrelevant oroutmoded innovations.MNEs that endeavor to engage in the development

of new innovations for host market consumersrequire access to knowledge that is tacit and noteasily codified (Makhija & Ganesh, 1997). An impor-tant strategy that can be employed to increase thelikelihood of innovation success is to draw uponothers’ experience and learn quickly (Brown &Eisenhardt, 1995). In order to more fully compre-hend the technological environment and the mar-ketplace for goods and services in foreign countries,MNEs have been found to employ local growthteams that engage partners and employees from thehost market who can not only teach the MNE aboutthe local technological environment, but also howto design, produce and sell products and servicesfor value-conscious customers (Govindarajan &Ramamurti, 2011; Sarkar, 2011). These practices areconsistent with extant theory which suggests thatwhen more tacit, process-related knowledge isrequired to generate new innovations, firms thatlack this knowledge will rely on more sociallyoriented mechanisms to enhance their learning(Makhija & Ganesh, 1997; Teagarden & Schotter,2013; Turner & Makhija, 2006). Immelt et al. (2009)document General Electric’s (GE) substantial invest-ment in R&D to develop a medical device for dis-tribution in emerging markets and its initial inabilityto find buyers for the device. Subsequent efforts to

engage a local joint venture (JV) partner helped thecompany to understand that its initial innovationefforts had been misguided. GE had failed to fullycomprehend the fact that medical environments inemergingmarkets are better-suited to low-tech appli-cations. This oversight resulted in the companyinitially developing technologically sophisticated,feature-rich devices, rather than the low-cost, porta-ble devices for which demand existed in the hostmarket. The development of the relationship withthe local JV partner positioned GE to become morefamiliar with the host country’s technological envir-onment and to design more suitable products forlocal consumers.Consequently, MNEs that engage in foreign mar-

ket-based innovation require access to country-specific knowledge (Belderbos & Heijltjes, 2005),particularly where this knowledge helps to attenuatethe uncertainty bred by heightened TOII and DOIIdistances. Under conditions of heightened TOII andDOII distances, MNEs will engage in foreign entrystrategies that are designed to position the firm togarner a better understanding of the host market’stechnological environment and its marketplace forgoods and services. While MNEs are often rich intechnology, they may be poor in their comprehen-sion of the host country. Achieving deep marketpenetration must be preceded by efforts to develop amore robust familiarity with customers’ needs. Host-country partners can be expected to contributecountry-specific knowledge and offer the MNE anopportunity to broaden the scope of the firmby introducing new, context-specific information(Beckman, Haunschild, & Phillips, 2004). This canhelp mitigate the costs associated with developingnew products and services. As such, we hypothe-size that,

Hypothesis 2: Foreign-investing MNEs will exer-cise less organizational control over subsidiaryinvestments when the TOII distance between thehome and host countries is greater.

Hypothesis 3: Foreign-investing MNEs will exer-cise less organizational control over subsidiaryinvestments when the DOII distance between thehome and host countries is greater.

Interaction EffectsWe have theorized that heightened BOII distancewill precipitate a preference for increased organiza-tional control as the MNE focuses on minimizingthe costs of safeguarding new IP assets against



opportunistic behavior, whereas heightened TOIIand DOII distances will lead to a preference for lessorganizational control as the MNE focuses on learningin order to minimize the information and produc-tion costs associated with generating new innova-tions in the host market. Behavioral, technologicaland demand uncertainties are pervasive in emergingmarkets (Khanna & Palepu, 1997). Notwithstandingthe simultaneous existence of these distinct types ofuncertainty, we are aware of no theory that predictsthe effects of the interaction between these uncer-tainties. However, in positing an evolutionary viewof the MNE and its strategic behavior, Verbeke(2003: 503) has argued that an MNE’s strategicdecisions are not static. Instead, he proposes that anMNE’s focus on learning vs protecting againstopportunism undergoes “an effective co-evolutionover time of these two critical parameters.”We applythis temporal perspective to the trade-off betweenlearning and protecting against opportunism in ourstudy of the foreign entry strategy (or, organizationalcontrol decision) of MNEs that invest in emergingmarkets for the purposes of engaging in innovation.At the point of foreign entry, the MNE faces

significant liabilities associated with its foreignness(Zaheer & Mosakowski, 1997) and with informalinstitutional differences. As a result, the MNE’sinability to fully comprehend the technologicalenvironment will be limited (technological uncer-tainty). This will also be true of its ability to forecastthe amount and type of innovation outputs that willbe required in the marketplace (demand uncertainty).Conversely, at the point of foreign entry, the MNEhas not created a substantial inventory of new IPassets because the innovation activities have not yetbegun. Consequently, while behavioral uncertaintywill still be a concern for the MNE at the point offoreign entry because the MNE can be expected tohave transferred some existing IP assets to the newsubsidiary investment (Zhao, 2006), technologicaland demand uncertainties will pose greater concernsfor the MNE. As such, in evaluating the comparativeeffects of behavioral, technological and demanduncertainties precipitated by increased BOII, TOIIand DOII distances respectively, we anticipate thatthe effects of heightened TOII and DOII distances willbe more pronounced sources of uncertainty thanBOII distance at the point of foreign entry. Consistentwith Verbeke’s (2003) evolutionary view of theMNE, we expect that the MNE’s need to learn (inorder to minimize information and production costsresulting from technological and demand uncertainties)will predominate over its need to minimize the

potential costs associated with the safeguarding IPassets against opportunism.Even though an MNE’s decision to relax its organi-

zational control over the subsidiary investment inorder to attenuate the costs associated with technolo-gical and demand uncertaintiesmay increase anMNE’sexposure to behavioral uncertainty, implementingthis strategy reveals that the MNE anticipatesthat the benefits associated with reducing its techno-logical and demand uncertainties will offset thecosts associated with increased behavioral uncertainty(Beckman et al., 2004). The initial structure of emer-ging market-based investments made by com-panies such as Microsoft (Tong & Li, 2008) and GE(Govindarajan & Ramamurti, 2011) for the purposesof engaging in innovation support this perspective.As such, we anticipate that although theMNE will beprimarily concerned with TOII and DOII distances atthe point of foreign entry, the firm’s concernsregarding behavioral uncertainty in the future whenIP assets are accumulating in the foreign subsidiarywill exert a moderating effect upon the negativerelationships between organizational control and eachof TOII distance and DOII distance. Accordingly, wehypothesize that,

Hypothesis 4: An MNE’s preference for less orga-nizational control under conditions of heightenedTOII distance is weakened when the BOII distancebetween the home and host countries is greater.

Hypothesis 5: An MNE’s preference for less orga-nizational control under conditions of heightenedDOII distance is weakened when the BOII distancebetween the home and host countries is greater.

Technological uncertainty resulting from increasedTOII distance and demand uncertainty resultingfrom increased DOII distance are closely related(Atuahene-Gima & Li, 2004). We have theorized thatboth TOII and DOII distances increase informationand production costs by making it more difficult forthe MNE to comprehend the technological environ-ment and to forecast the type and amount of newinnovations required in the marketplace. Techno-logical uncertainty has been argued to precipitateincreased costs associated with understanding notonly the nature of the technological environment,but also the nature of customer demands and needs(Di Minin et al., 2012). As such, we expect that anincrease in TOII distance andDOII distancewill have acompounding effect on an MNE’s preference for lessorganizational control in its subsidiary investment.Accordingly, we hypothesize that,



Hypothesis 6: An MNE’s preference for less orga-nizational control under conditions of heightenedTOII distance is strengthened when the DOII dis-tance between the home and host countries isgreater.

METHODS

Data Sources, Dependent Variable and FocalIndependent VariablesWe tested our hypotheses by investigating the orga-nizational control decisions of 157 subsidiaries thatwere identified by the parent MNEs as being foundedfor the purposes of engaging in R&D activities/knowledge-sourcing (Almeida, 1996; Gupta, Tesluk,& Taylor, 2007; Singh, 2007a). The focal subsidiarieswere established in 15 emerging market countries1

during a nine-year period. Information pertaining tothese investments was gathered from the 2001−2009editions of the Kaigai Shinshutsu Kigyou Souran, acompendium of Japanese global FDI that has beenshown to be close to the population of foreignaffiliates of public and private Japanese companies(Hennart, 1991; Yamawaki, 1991).Despite the fact that innovation offshoring has

been routinely conceptualized as a dichotomouschoice (captive vs outsourced), scholars have proposedthat a broader range of configurations should beinvestigated ( Jahns et al., 2006; Nieto & Rodríguez,2011). We sought to operationalize the organiza-tional control variable as a continuous dependentvariable which would measure the degree to whichanMNE integrates an offshore subsidiary through itsequity investment and partnering decisions. Extanttheory holds that an MNE is able to integrateand exert control over its subsidiary investmentsthrough a variety of mechanisms, including itsequity ownership position (Zhao et al., 2004) andits decision to invest with partners who share thesame national background (Makino & Beamish,1998; Rangan & Drummond, 2011). In order tooperationalize organizational control as a multidimen-sional construct (Chen, Park, & Newburry, 2009;Chen et al., 2010; Yan & Gray, 1994, 2001), weincorporated two continuous variables: the focalMNE’s proportionate share of total equity in thesubsidiary investment and the proportionate shareof total equity in the subsidiary investment that washeld by all home-country ( Japanese) partners.2

The three focal informal institutions constructswere theoretically grounded on North’s (1990) con-ceptualization of informal institutions (norms of

behavior, codes of conduct, practices and conven-tions that guide social relations and businessactivities) and on TCT’s typology of uncertainties(behavioral, technological and demand). To developmeasures for the BOII, TOII and DOII constructs, weselected items from the International Institute forManagement Development’s World CompetitivenessYearbooks (WCY). The WCY collects survey data oninternational business executives’ perceptions withrespect to the institutions that prevail in countriesworldwide. Based on our theory, a range of indica-tors was selected from the WCY surveys and sub-jected to factor analysis. Ultimately, two indicatorswere found to be related to our theoretical concep-tualization of each of the three latent constructs(BOII, TOII and DOII).

BOIIA country’s standards of business conduct and thereputation of its firms contribute to the prevailinginformal institutional environment (Dikova et al.,2010). Reputation is based on the prior behavior offirms and it guides expectations with respect to thefuture behavior of firms (Bitektine, 2011). As such,the reputation of firms is assumed to be representa-tive of their typical behavior (Uzzi, 1996). Parkhe(1998: 233) has noted that “reputation creates trustby imposing self-restraint on actions, as a companystrives to preserve and protect (the reputation) that ithas painstakingly built.” Accordingly, we used mea-sures of the differences in the reputation of man-agers in the home and host countries with respect toissues of managerial credibility and ethical practicesas an indication of the differences in prevailing BOII.When these differences are more pronounced, weexpect that MNEs will experience heightened uncer-tainty with respect to the perceived likelihood of IPappropriation.

TOIIPrior research has identified a number of socialfactors that contribute to stimulating the develop-ment of new technologies. These social factorsinclude practices with respect to technological coop-eration between firms (Hagedoorn, 1993) and inter-organizational knowledge transfer activities (Grant& Baden-Fuller, 2003). In fact, collaborative practicesthat generate new technologies and innovation canprecipitate further technological spillovers (D’Este &Patel, 2007). Building on this work, we assume thatgreater TOII differences will be indicated by differ-ences in home and host market inter-organizationalknowledge transfer capabilities and differences in



the extent of technological cooperation betweenfirms.

DOIIThe demand for undiscovered innovations is diffi-cult to measure given that consumers in the marketcannot yet be aware of the new innovations. How-ever, given that the diffusion of new innovationsis precipitated by social processes (Dutta & Roy,2005), scholars have proposed that the adoption ofinnovation artifacts (such as hardware, software,etc.) is indicative of the diffusion of innovations(Orlikowski & Iacono, 2001). More widespreadbroadband access and adoption in a market has beenfound to be associated with heightened employmentand demand for new innovations (Lee & Chan-Olmsted, 2004). Accordingly, in order to measureDOII, we employed indicators pertaining to percapita broadband adoption and full-time R&D work-ers per capita. Where differences in broadband adop-tion and R&D employment practices between thehome and host country are more pronounced, weexpect that MNEs will encounter heighteneddemand uncertainty for new innovations. Our logicis consistent with prior research that sought to

operationalize demand uncertainty in terms of newproduct activity and R&D expenditures (Rosson &Ford, 1982).Table 2 reports the CFA results and the factor

loadings for all four of the latent constructs.

Reliability and validity of measuresAn assessment of internal consistency (compositereliability) was based upon Fornell & Larcker’s (1981)measure. The results revealed that the measures ofinternal consistency for organizational control (0.93),BOII (0.90), TOII (0.82) and DOII (0.92) all exceededthe 0.70 guideline required to establish internalconsistency (Nunnally & Bernstein, 1994). In termsof convergent validity, Fornell and Larcker’s (1981)average variance extracted (AVE) measure was calcu-lated for the organizational control (0.87), BOII (0.82),TOII (0.70) and DOII (0.85) constructs, all of whichexceeded the 0.50 cutoff required for the AVE toprovide evidence of satisfactory convergent validity.In terms of unidimensionality, we concluded thatthe four factor model fit the data, given that the fitindices all satisfy the requisite 0.90 benchmarks(GFI=0.95, NFI=0.94, IFI=0.96, CFI=0.96, TLI=0.91), and the chi-square ratio (3.07) was adequate

Table 2 Confirmatory factor analysis resultsa for the organizational control, BOII, TOII and DOII constructs

Latent constructs and associated items Factorloading

Organizational control CR = 0.93, AVE = 0.87

Focal MNE equity share The focal MNE’s proportionate share of equity in the subsidiaryinvestment.

0.93

Equity share of all home country partners The proportionate share of equity in the subsidiary investment held byall home country partners.

0.94

Behaviorally-oriented informal institutions (BOII) CR = 0.90, AVE = 0.82Prevalence of ethical practices Ethical practices (0 = are never implemented in companies, 10 = are

always implemented in companies).0.89

Credibility of managers The credibility of managers in society is (0 = weak, 10 = strong). 0.92

Technology-oriented informal institutions (TOII) CR = 0.82, AVE = 0.70Technological cooperation practices Technological cooperation (0 = is lacking between companies, 10 = is

common between companies).0.97

Knowledge transfer practices Knowledge transfer between companies and universities (0 = is lacking,10 = is highly developed).

0.68

Demand-oriented informal institutions (DOII) CR = 0.92, AVE = 0.85Broadband adoption Number of broadband subscribers per 1000 inhabitants. 0.92Full-time R&D personnel per capita employedin businesses

Full-time R&D workers per 1000 inhabitants employed in businesses. 0.92

aModel fit: GFI = 0.95, NFI = 0.94, IFI = 0.96, CFI = 0.96, TLI = 0.91, χ2 ratio = 3.07.CR: composite reliability (internal consistency), AVE: average variance extracted.



(Hinkin, 1995; Jackson, Wall, Martin, & Davids,1993; Marsh & Hocevar, 1985).

Discriminant validityWe employed the method specified by Fornell andLarcker (1981) to assess discriminant validity. Thesquare root of the AVE for the organizational control(0.94), BOII (0.91), TOII (0.84) and DOII (0.92) con-structs all exceeded the correlations between eachof the latent construct pairings. Furthermore, thesquare root of the AVE values for each construct alsoexceeded the correlation between each latent con-struct and every other variable included in theregression models, a finding which further supportsthe discriminant validity of all four latent constructs(Farrell, 2010; Fornell & Larcker, 1981; Hair, Black,Babin, Anderson, & Tatham, 2006). The results ofthe discriminant validity analysis are reported in thecorrelation matrix (Table 3). Based on these results,we concluded that the organizational control, BOII,TOII and DOII constructs all exhibited adequatediscriminant validity.

Control Variables and Estimation MethodGiven that our theory focuses on uncertainty, a coretenet of TCT, we controlled for asset specificity(Williamson, 1985). While parent-level R&D oradvertising intensity ratios are routinely employedin transaction cost research to control for assetspecificity at the subsidiary level, our sample lackedthe data needed to compute these ratios for asufficient number of firms. As such, we controlledfor asset specificity using the subsidiary’s capitalintensity. The intensity of an MNE’s capital invest-ment in a subsidiary has been recognized as asuitable proxy for the specific nature of the assetsembedded by the MNE in the subsidiary investment(Henisz, 2000; Masten, Meehan, & Snyder, 1989).This is particularly true of subsidiaries that areactively engaged in innovation efforts, given thatprior research has found that a firm’s R&D intensityis closely associated with its capital structure(O’Brien, 2003). Our approach is also consistent withprior work that has measured asset specificity interms of the level of dedicated assets associated witha subsidiary investment (Brouthers & Brouthers,2003). We measured capital intensity as the ratio ofthe subsidiary’s capitalization to the MNE’s totalsales (Henisz, 2000). Profitability was measured usingthe parent’s return on sales (Kotabe & Swan, 1994).Uncertainty reduction theory (Berger & Calabrese,1975) holds that uncertainty can be reducedthrough interaction and exchange over time. Given

that our sample is only constituted by observationspertaining to the subsidiaries’ year of foreign entry,we needed to incorporate a time-related variable intoour analyses in order to account for the possibilitythat uncertainty had been reduced for some MNEsthrough the passage of time and the accumulation ofexperience in the host country. Accordingly, prioryears host market experience was measured as theparent MNE’s total number of subsidiary years ofexperience in the host market accumulated prior tothe entry that occurred in our sample. In doing so,we were able to account for the fact that MNEs withmore previous experience in the host countries weremore likely to have developed the knowledge and tohave accumulated the experience needed to be ableto predict the future status of informal institutions.3

Extant research in the domain of innovation off-shoring provides further support for this controlvariable. Scholars have found that prior experiencein the host country is a determinant of an MNE’sstrategic behavior when offshoring innovation, pri-marily because these host countries are characterizedby distinct institutional environments (Demirbag &Glaister, 2010). In the same vein, any MNEs thatwere parents to more than one of the subsidiaries inour sample could be expected to have a uniqueperspective on the uncertainty that they mightencounter when offshoring innovation to emergingmarkets. Some of these MNEs might perceive thatheightened uncertainty will be associated withhaving multiple subsidiaries engage in emergingmarket-based innovation. Conversely, these MNEsmight also perceive lower levels of uncertainty, as aresult of the experience associated with establishingmultiple subsidiaries. Either way, these MNEs mightexperience a different degree of uncertainty relativeto those MNEs that only established one of thesubsidiaries in our sample. As such, we included anadditional variable (MNE with multiple subsidiaries) tocontrol for this possibility.4 A subsidiary that wasassociated with an MNE that was parent to morethan one subsidiary was coded as “1” and “0” if thesubsidiary was the only subsidiary associated with itsparent MNE. A dummy variable (industry) wasemployed to control for industry effects by distin-guishing between manufacturing industry subsidi-aries and non-manufacturing subsidiaries because afirm’s industry status as a manufacturing entity hasbeen found to predict its foreign-entry strategies(Brouthers & Brouthers, 2003).We also included control measures with respect to

the formal institutional environment and the culturalenvironment. IP rights protection and political risk



have been found to be consistently significant pre-dictors of equity share, entry mode and partneringdecisions (Delios & Henisz, 2003; Gomes-Casseres,1990). Our measures for both variables were derivedfrom the WCY surveys. Higher values for each vari-able indicate, respectively, stronger IP rights protec-tion and lower risk of political instability. Culturaldistance has also been found to predict a firm’sforeign entry decisions (Kogut & Singh, 1988). Wecalculated cultural distance using Kogut and Singh’s(1988) cultural distance measure and Hofstede’s(2001) scores.Skewed covariates (profitability, experience and

capital intensity) were log transformed prior to test-ing our hypotheses (Tabachnick & Fidell, 2007). Ourregression models were estimated using hierarchicallinear modeling (HLM) which has been argued toyield more precise coefficient estimates than ordin-ary least squares (OLS) regression in internationalbusiness research (Peterson, Arregle, & Martin,2012). Hierarchical relationships can be said to existwhere firm-level outcomes are predicted by firm-level and country-level variables (Hitt, Beamish,Jackson, & Mathieu, 2007). Hierarchical data struc-tures are implicitly ignored in the context of OLSregression (Hoffmann, Griffin, & Gavin, 2000).Accordingly, multilevel or hierarchical models canbe used in an effort to estimate variance at multiplelevels simultaneously. This approach to modelingfacilitates the explicit recognition and investigationof data structures characterized by the existence ofrelationships that span different levels of analysis.HLM enables researchers to partition multiple levelsof variance in the outcome variable, while maintain-ing the appropriate level of analysis for the indepen-dent variables (Hoffmann et al., 2000). While someof the countries in our sample hosted a smallernumber of subsidiary investments than other coun-tries, hierarchical regression modeling can use unba-lanced samples constituted by different numbers ofobservations per group (Peterson et al., 2012), withas few as one or two observations per country (Bell,Ferron, & Kromrey, 2008). Prior to executing themodels that investigated the interaction effects(Hypotheses 4, 5 and 6), we centered the BOII, TOIIand DOII distance variables in Models 5, 6 and 7(Aiken & West, 1991).

RESULTSTable 3 reports the correlation matrix and descrip-tive statistics for our study’s sample. Some of thecountry-level variables in our study exhibited highcorrelations which was expected because a hostTa

ble

3Descriptiv

estatistic

san

dco

rrelations

Varia

ble

Mean

s.d.

12

34

56

78

910

11

1Organ

izationa

lcon

trol

0.76

0.30

0.94

2Cap

italinten

sity

(log)

−2.77

1.09

−0.12

†

3Profita

bility(lo

g)0.11

0.03

−0.11

†−0.01

4Prioryearsho

stmarketex

perie

nce(lo

g)1.12

0.77

−0.06

−0.31

***

0.11

†

5MNEwith

multip

lesubsidiarie

s−

−−0.04

−0.07

0.04

0.28

***

6Indu

stry

−−

−0.20

***

0.17

**0.02

−0.02

0.03

7Po

liticalrisk

6.03

1.49

0.09

0.17

*0.05

−0.04

−0.04

−0.07

8Intellectua

lprope

rtyrig

htsprotectio

n5.41

1.23

0.24

***

−0.03

0.00

−0.02

0.01

−0.19

***

0.50

***

9Culturald

istanc

e3.69

0.89

−0.01

−0.01

−0.05

0.09

−0.02

−0.04

0.11

†0.22

***

10BO

IIdistan

ce0.28

1.03

−0.02

−0.07

−0.09

−0.04

0.05

0.02

−0.52

***

−0.58

***

−0.29

***

0.91

11TO

IIdistan

ce1.25

0.92

−0.26

***

0.01

−0.01

−0.01

−0.04

0.20

***

−0.56

***

−0.69

***

−0.25

***

0.59

***

0.84

12DOIIdistan

ce22

.96

44.70

−0.11

*0.15

*−0.10

†−0.02

0.11

*0.01

−0.17

**−0.37

***

0.03

0.46

***

0.37

***

0.92

†p<0.10

,*p<0.05

,**p<0.01

,***

p<0.00

1.Allaretw

o-tailedtests.

Note:Th

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tstheAV

Evalues

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lcon

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(0.87),

BOII(0.82),T

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hetestof

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forthe

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(0.94),B

OII(0.91),T

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latent

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market’s institutions are interdependent and gener-ally share common variance (Holmes Jr, Miller, Hitt,& Salmador, 2013). Nonetheless, we concluded thatmulticollinearity was not a problem in our modelsgiven that the highest variance inflation factor (VIF)score in any of the regression models (3.36) wassubstantially less than the maximum VIF of 10which is recommended for regression analyses ininternational strategy research (Reuer & Leiblein,2000). Table 4 presents the results of the tests ofour six hypotheses pertaining to the relationshipbetween organizational control and the uncertainty-based measures of informal institutional distance(BOII, TOII and DOII).We present a base model (Model 1) in Table 4 that

excludes the effects of the BOII, TOII and DOIIdistance variables, along with models that includethese main effects (Models 2–4), as well as theinteraction effects between BOII, TOII and DOII(Models 5–7). While Hypothesis 1 was not supportedby the results of Model 2 ( χ2=0.14, p>0.05), theresults presented in Model 3 ( χ2=6.08, p<0.05)which tests Hypothesis 2 and Model 4 ( χ2=4.12,p<0.05) which tests Hypothesis 3 were consistentwith our theory. We found that MNEs exercised lessorganizational control when establishing subsidi-aries to offshore their innovation under conditionsof heightened TOII distance ( β=−0.16, p<0.01) andDOII distance ( β=−0.21, p<0.01). As such, bothHypotheses 2 and 3 were supported.The results reported in Model 6 ( χ2=10.58,

p<0.05) with respect to the interaction effect inHypothesis 5 supported our theory that an increasein BOII distance would attenuate an MNE’s prefer-ence for less organizational control under conditionsof heightened DOII distance ( β=0.19, p<0.05).Notably, Model 6 is the best fitting model in ourstudy in terms of the reduction in model devianceover the base Model 1 (Δ deviance=10.58). Simi-larly, considering the Akaike information criterion(AIC), Model 6 can also be regarded as the best modelbecause it has the lowest AIC (104.43) and thesecond lowest Bayesian information criterion (BIC)(128.51), both of which are less than the AIC(109.01) and BIC (130.96) associated with the basemodel (Model 1) which excludes the effects of thefocal independent variables (BOII, DOII and theinteraction effect) (Arregle, Miller, Hitt, & Beamish,2013; Burnham & Anderson, 2004). Figure 1 illus-trates the interaction effect (Aiken & West, 1991;Dawson, 2014) between BOII distance and DOIIdistance on organizational control. The figure sug-gests that although MNEs prefer to exercise less

organizational control in emerging markets charac-terized by heightened DOII distance, this preferenceis diminished as BOII distance increases. We testedthe interaction effect between BOII and TOII dis-tances upon organization control (Model 5:χ2=5.99, p>0.05), and between TOII and DOII dis-tances on organizational control (Model 7: χ2=9.34,p<0.05), but the interaction terms were not signifi-cant in these models. Thus while the interactioneffect in Hypothesis 5 was supported, Hypotheses 4and 6 were not supported.In summary, in terms of the reduction in AIC and

BIC, as well as the statistically significant reductionin deviance, Models 3, 4, 6 and 7 represent animprovement over the base Model 1. Therefore allfour models provide a better explanation than thebase model for the organizational control decisionsof firms that offshore their innovation investmentsto emerging markets under conditions of increasedinformal institutional distance.5

DISCUSSION AND CONCLUSIONS

Organizational ControlHeightened interest in innovation offshoring, parti-cularly in emerging markets, has precipitated agrowing body of research (Vives, Asakawa, &Svejenova, 2010). Notwithstanding the considerableadvances with respect to this phenomenon, scholarshave advocated expending more effort studyingthe organizational implications associated withestablishing these subsidiaries (Govindarajan &Ramamurti, 2011; Griffith et al., 2009). More speci-fically, researchers have begun to note that the broadspectrum of institutional environments encoun-tered by MNEs that offshore their innovation(Demirbag & Glaister, 2010) is precipitating a richermix of strategic responses than the dichotomouschoice (captive vs outsourcing) that has been elabo-rated to date (Nieto & Rodríguez, 2011). The widearray of contractual, legal and operational arrange-ments that are being employed by MNEs toimplement their offshoring strategy supports thisperspective ( Jahns et al., 2006). Consequently, amore nuanced understanding of the range of strate-gies being employed by MNEs that engage in inno-vation offshoring is needed (Nieto & Rodríguez,2011).Consistent with Rangan and Drummond’s (2011)

recent assertion that the notion of strategic organi-zational control merits further attention in theglobal strategy literature, we proposed that whenMNEs establish subsidiaries in emerging markets for



Table 4 Results of HLM regression analyses of informal institutional distances (BOII, TOII and DOII) on organizational control

Variables Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7

(base) BOII TOII DOII BOII * TOII BOII * DOII TOII * DOII

Intercept 0.87(0.15)*** 0.97(0.31)* 1.63(0.27)*** 0.64(0.11)*** 1.38(0.29)** 0.37(0.26) 1.09(0.25)**

Capital intensity (log) −0.02(0.02) −0.02(0.02) −0.03(0.02) −0.02(0.02) −0.03(0.02) −0.03(0.02) −0.02(0.02)Profitability (log) −0.49(0.81) −0.47(0.82) −0.37(0.82) 0.06(0.83) −0.33(0.82) −0.03(0.81) −0.22(0.82)Prior years host market experience (log) −0.01(0.03) −0.01(0.03) −0.03(0.04) −0.01(0.04) −0.03(0.04) −0.01(0.03) −0.01(0.04)MNE with multiple subsidiaries −0.06(0.06) −0.06(0.06) −0.08(0.06) −0.10(0.06) −0.08(0.06) −0.09(0.06) −0.08(0.06)Industry dummy −0.12(0.06)† −0.12(0.06)† −0.13(0.05)* −0.11(0.05)† −0.13(0.04)* −0.11(0.05)† −0.12(0.05)*Intellectual property rights protection 0.02(0.02) 0.01(0.02) −0.03(0.02) 0.04(0.02)* −0.02(0.02) 0.04(0.02)* 0.00(0.02)Political risk 0.00(0.02) −0.01(0.03) −0.04(0.02)† 0.00(0.01) −0.03(0.03) 0.02(0.02) −0.03(0.02)Cultural distance −0.05(0.02)* −0.06(0.03)† −0.08(0.02)** −0.03(0.02) −0.08(0.03)* −0.01(0.03) −0.06(0.02)*BOII distance −0.03(0.07) 0.01(0.06) 0.11(0.07)TOII distance −0.16(0.05)** −0.15(0.07)† −0.10(0.06)DOII distance −0.21(0.06)** −0.27(0.07)** −0.16(0.07)†

BOII distance * TOII distance 0.01(0.03)DOII distance * BOII distance 0.19(0.07)*TOII distance * DOII distance 0.06(0.08)

Variance inflation factor range 1.04–1.39 1.04–2.74 1.04–2.23 1.04–1.97 1.05–3.36 1.06–2.97 1.05–2.68Model deviance 47.01 46.87 40.93 42.89 41.02 36.43 37.67χ2 of Δ deviancea 0.14 6.08 * 4.12 * 5.99 10.58 * 9.34 *AIC 109.01 110.87 104.93 106.90 109.02 104.43 105.67AICb 4.58 6.44 0.50 2.47 4.59 0.00 1.24BIC 130.96 133.53 127.59 129.55 133.10 128.51 129.75aCompared to Model 1 (base).bAIC Model I – minimum AIC†p < 0.10, * p < 0.05, ** p < 0.01, *** p < 0.001n = 157.All are two-tailed tests. Standard errors are in parentheses.

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the purpose of engaging in innovation, they may bemore concerned with organizational control thanthey are with the choice between a fully captive orfully outsourced strategy. We defined organizationalcontrol as the degree to which an MNE integrates anoffshore subsidiary through its equity investmentand partnering decisions. In doing so, we couchedour work within the body of extant theory that hasconceptualized control both in terms of the typesof control (Chen et al., 2009, 2010; Rangan &Drummond, 2011), as well as in terms of the deci-sions through which control is derived (strategic,operational and structural) (Child & Yan, 1999; Yan& Gray, 2001). Our work coalesces closely relatedstrands of research which have held that an MNE isable to integrate and exert control over its subsidiaryinvestments through a variety of mechanisms,including its equity ownership over the subsidiary(Zhao et al., 2004) and its partnering decisions(Makino & Beamish, 1998; Rangan & Drummond,2011). In doing so, we offer a finer-grained view intothe wide array of foreign entry strategies that MNEsexecute to offshore innovation.An extensive body of research has investigated the

relationship between formal institutions and MNEstrategy (Hagedoorn et al., 2005; Zhao, 2006). Thiswork has reinforced the long held belief that whenformal institutions are more underdeveloped in thehost market, MNEs will exert tighter control overforeign subsidiaries that are established for the pur-pose of engaging in innovation (Roth & Morrison,1992). We have extended this line of inquiry by

focusing on informal institutions. However, ourwork is distinct from the prior scholarship thatfocused on formal institutions. A central thesisunderpinning our research is that the degree oforganizational control that an MNE exercises whenit establishes a subsidiary for the purpose of enga-ging in innovation offshoring will be contingentupon the type of institutional uncertainty precipi-tated by informal institutional differences betweenthe home and host markets.

Informal Institutions (BOII, TOII and DOII)While scholars’ understanding of the relationshipbetween host market formal institutions and MNEstrategy has matured considerably, comprehensionof the influence of informal institutions on MNEstrategy remains far less developed (Meyer & Peng,2005). We have proposed that, unlike formal institu-tions, informal institutions have not been concep-tualized as rigorously (Estrin & Prevezer, 2011;Sauerwald & Peng, 2013) which has resulted in awide range of approaches being employed to incor-porate the construct. As we illustrated in Table 1,scholars that have sought to incorporate informalinstitutions into their studies have tended to oper-ationalize the construct either very broadly, usingone of the cultural distance measures that are routi-nely employed in international business research, orvery narrowly, using a study-specific range of indica-tors as a broad measure of the construct (Galang,2012). Consequently, the construct has not beenextensively integrated into mainstream strategytheories or institutional studies (Estrin & Prevezer,2011). This is concerning because informal insti-tutions have been characterized as being moreimportant than formal institutions in regulatingeconomic exchange in emerging economies (Peng,2003; Teagarden & Schotter, 2012).Given the central role of construct development in

theory-building scholarship (Suddaby, 2010), effortsto develop a more fine-grained conceptualization ofan existing construct constitute an opportunity toadvance theory (Venkatraman, 2008; Vergne, 2011).Institutional distance is well-established in the inter-national strategy literature as a source of uncertaintyconfronting foreign-investing MNEs (Santangelo &Meyer, 2011). We have suggested that informal insti-tutions can be conceptualized as a source of differenttypes of institutional uncertainty – behavioral, tech-nological and demand. Our theory proposed thatinformal institutions could be expected to exertdisparate impacts on MNE strategy, depending uponthe type of uncertainty involved. This is because the

00.10.20.30.40.50.60.70.80.9

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Low DOII High DOII

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Low BOIIHigh BOII

Figure 1 Interaction effect of BOII and DOII distances on orga-nizational control.Notes: High BOII and low BOII refer to BOII distance one stan-dard deviation above and below the mean BOII. Likewise, highDOII and low DOII refer to DOII distance one standard deviationabove and below the mean value. DOII rescaled 10−1.



predominant costs precipitated by behavioral uncer-tainty should be different from those precipitated byenvironmental uncertainties (technological anddemand). More specifically, while heightened beha-vioral uncertainty should be expected to increase thecosts of safeguarding IP, heightened environmentaluncertainties (technological and demand) mightincrease the MNE’s information costs and produc-tion costs associated with creating new IP assets.Consequently, the mechanisms through whichbehavioral uncertainty and environmental uncertainty(both technological and demand) should impact uponan MNE’s strategy (or, organizational control deci-sions) could be distinct.While BOII distance did not exert a significant

impact on the organizational control decisions ofthe firms in our study, we did find that an increase intechnological uncertainty and demand uncertainty,resulting from increased TOII and DOII distancesrespectively, predicted an MNE’s preference forreduced organizational control, a strategy which isdesigned to facilitate the MNE’s efforts to minimizeinformation and production costs by learning aboutthe host country’s marketplace for goods and ser-vices from host-country partners.As a preliminary illustration of the utility of our

theory, we return to Table 1 and juxtapose ourconceptualization of informal institutions againstthe work of both Gaur et al. (2007) and Xu, Pan,and Beamish (2004) in an attempt to reconcile theirresults. On the surface, the findings of these twostudies appear to contradict one another, a commonpredicament in extant research that investigates theeffects of informal institutions. While Gaur et al.(2007) found that an increase in informal institu-tional distance predicted an increase in expatriateintensity, Xu et al. (2004) found the opposite result –increased informal institutional distance resulted inreduced expatriate usage. Prior research has concep-tualized expatriate intensity as one strategy that canbe used by an MNE to exert control over its foreignsubsidiary investments (Caligiuri & Stroh, 1995;Shay & Baack, 2004). A closer analysis of bothstudies reveals that while Gaur et al. (2007) focus oninformal institutions that garner behavioral uncer-tainty, Xu et al.’s (2004) operationalization of infor-mal institutions is more closely related to demanduncertainty. More specifically, Gaur et al.’s (2007)measure of informal institutions was constituted byindicators such as the degree of bureaucracy and theprevalence of corruption. These indicators couldreasonably be expected to lead to an increase in thedegree of behavioral uncertainty perceived by the

MNE. Conversely, Xu et al.’s (2004) measure ofinformal institutions provides an indication of thedegree of demand uncertainty fostered by informalinstitutions, incorporating indicators such as theamount of attention that firms devote to productdesign, customer satisfaction and employee training,each of which could be expected to either precipitateor attenuate customer demand.The contrasting results reported in the Gaur et al.

(2007) and Xu et al. (2004) studies suggest that morenuanced theory is needed to conceptualize informalinstitutions. Absent such theory, researchers maycontinue to employ disparate approaches towardsthe construct, which risks the possibility that con-flicting findings will continue to be reported. As such,we have endeavored to clarify theoretical boundaryconditions within and around the informal institu-tions construct. More specifically, we have proposedthat conceptualizing informal institutions in terms ofthe different types of uncertainty that they garner canultimately contribute to a more orderly developmentof theory pertaining to informal institutions in theinternational business literature by providing a theo-retical framework to guide scholars’ efforts to incor-porate the construct into their studies. In turn, ourtheory creates an opportunity for scholars to acceler-ate the integration of informal institutions intomain-stream strategy theories (Estrin & Prevezer, 2011).Finally, institutionally focused research that

leverages the tenets of TCT routinely assumes thatuncertainty matters only in the presence ofhighly specific assets (Williamson, 1985). We haveextended these insights by investigating the interac-tion effects associated with informal institutionsthat produce distinct types of uncertainty (beha-vioral, technological and demand) in the presenceof high asset specificity. Our efforts are consistentwith international business scholarship which hasproposed that, rather than focusing upon singlemanifestations of uncertainty, scholars should con-trast the effects associated with different types ofuncertainty in their theory-building efforts (Cuypers& Martin, 2009; Miller, 1993). Indeed, the failure todiscern between different types of informal institu-tional uncertainty poses the risk of muting itsnuanced impact on firm strategy (Milliken, 1987).For example, in examining the simultaneous effectsof the distinct types of uncertainty, we found thatalthough MNEs that engage in foreign market-basedinnovation respond to higher levels of DOII distanceby relaxing organizational control over these sub-sidiary investments, this effect is moderated as BOIIdistance increases. These findings were consistent



with our theory which proposes that at the point offoreign entry, MNEs will make organizational con-trol decisions that are designed to minimize theinformation and production costs associated withtheir innovation endeavors. Prior research has sug-gested that learning from constituents in the localmarket can support an MNE’s efforts to minimizethese costs when innovating in the host market.However, our findings with respect to the moderat-ing effect of BOII distance also support our theorythat MNEs are mindful of the need to minimize thecosts of safeguarding IP assets that they expect willsubsequently accrue in the subsidiary after the pointof foreign entry. This cost minimizing objective canbe achieved by retaining greater organizational con-trol over the subsidiary investment.

Managerial ImplicationsWright, Filatotchev, Hoskisson, and Peng (2005: 6)have argued that “it seems impossible to do well inemerging economies without an understanding ofhow formal and informal institutions affect firms.”Owing to the general weakness of formal institutionsin emerging economies, informal institutions havebeen recognized as assuming a more prominent rolethan formal institutions in the regulation of economicexchange (Peng & Heath, 1996). Our research assistsmanagers to understand how informal institutionsaffect their firms. We proposed that informal institu-tions could trigger distinct strategic responses fromMNEs and that these responses can be associated withdifferent types of uncertainty precipitated by informalinstitutional differences between the home and hostmarkets. As such, in developing the firm’s foreignentry strategy, it is imperative for managers to identifywhich type of uncertainty poses a more significantconcern for the MNE. Engaging in this exercise willassist managers to execute organizational controldecisions in a manner that positions the subsidiary toweather the type of uncertainty that will be mostrelevant to the MNE’s investment objectives.

Limitations and Future DirectionsOur work does include some limitations. First, weemploy a sample of firms from a single homecountry. While this can help to minimize the impactof differences between multiple home countriesupon the dependent variables in a study (Hillman &Wan, 2005), future work should seek to confirm ourfindings using a sample of non-Japanese subsidiaries.Second, our study focuses on developedmarket firmsentering into emerging markets (China in particular)for the purpose of engaging in innovation. Recent

work with respect to R&D investments by emergingmarket firms in Europe has questioned whether aseparate model of R&D internationalization isneeded to understand the nature of investments thatoriginate in emerging markets and terminate indeveloped markets (Di Minin et al., 2012). As such,future work should test our theory using a sample ofemerging market firms investing in both developedmarkets and other emerging market countries. Theseefforts could provide an opportunity to establishadditional boundary conditions with respect to boththe informal institutions construct and the phenom-enon of foreign market-based innovation. Further,while our study operationalized the organizationalcontrol dependent variable in terms of the focalMNE’s proportionate share of total equity in thesubsidiary investment and the proportionate shareof total equity in the subsidiary investment that washeld by all home-country (Japanese) partners, priorresearch has recognized the importance of expatriatedeployment as an additional strategy that MNEsemploy to exercise control over foreign subsidiaryinvestments (Caligiuri & Stroh, 1995; Shay & Baack,2004). As such, future research should explore alter-nate approaches to measuring organizational control,with particular attention being given to efforts toincorporate a consideration of the MNE’s expatriatedeployment strategy. Finally, while our measures ofBOII, TOII and DOII are relevant to our study’scontext, alternate measures of our theory’s con-structs should be explored and applied within otherresearch contexts, particularly given that our mea-sure of BOII and its interaction with TOII generatednon-significant effects. To extend our theoreticalframework further, the formal institutions constructshould also be disaggregated using the same typol-ogy of uncertainties. This would allow scholars toexplore the multiple interaction effects both withinthe formal and informal institutions constructs andacross both types of institutions. Both are researchundertakings that could contribute to advancingthe research agenda dedicated to exploring the co-evolution of institutions and organizations (Cantwellet al., 2010; Holmes Jr et al., 2013; North, 2005).An important theoretical imperative has moti-

vated our conceptual efforts with respect to informalinstitutions. Management scholars have increas-ingly advocated the need to investigate the co-evolution of formal institutions, informal institu-tions and organizations (Cantwell et al., 2010;Holmes Jr et al., 2013), a line of research inquiry thathas been championed extensively by institutionaltheorists (Ménard & Shirley, 2005; North, 2005).



The failure to develop a more nuanced conceptuali-zation of informal institutions threatens to inhibitthe progress of this important research agenda andothers that employ the construct. Our theory, whichfocuses on conceiving informal institutions in termsof the type of uncertainty that they engender hasbeen developed to guide scholars’ efforts to concep-tualize the construct and to reduce reliance uponoverly broad, time-invariant concepts such as cul-tural distance to incorporate informal institutionsinto research studies. In doing so, we build uponrecent institutional scholarship which emphasizesthe non-ergodic nature of uncertainty (North, 2005).The concept of non-ergodic uncertainty implies thatthe manifestations of uncertainty that firms encoun-ter over the course of time change because institu-tions evolve (Cantwell et al., 2010). As such, ourconceptualization of informal institutions may pro-vide a more enduring theoretical framework withwhich to incorporate informal institutional distanceinto institutionally based research.

ACKNOWLEDGEMENTSOur sincere thanks to Area Editor Paula Caligiuri andtwo anonymous JIBS reviewers for providing construc-tive and valuable input during the review process. Wealso acknowledge the insightful comments and feed-back of Andreas Schotter, Shige Makino and NorihikoTakeuchi.

NOTES1The number of subsidiary investments in each host

country is indicated in brackets: Brazil (2), Chile (1),China (86), Czech Republic (2), Hong Kong (10),Hungary (1), India (4), Indonesia (4), South Korea (21),Malaysia (2), Philippines (1), Poland (1), Singapore (9),South Africa (1) and Thailand (12). Host countries were

identified as “emerging markets” based upon TheEconomist’s designation. Their definition has been usedby Michigan State University’s Center for InternationalBusiness Education and Research (CIBER) which haspublished an annual Market Potential Index for EmergingMarkets since 1996.

2Given that expatriate deployment (often opera-tionalized using the subsidiary’s expatriate intensity or,the ratio of expatriate employees to total subsidiaryemployees) has also been recognized in the literature asa strategy employed by MNEs to exercise control oversubsidiary investments (Caligiuri & Stroh, 1995; Shay &Baack, 2004), we executed additional regression modelsas robustness tests in which the organizational controldependent variable was constituted by three indicators –the focal MNE’s proportionate share of total equity in thesubsidiary investment, the proportionate share of totalequity in the subsidiary investment that was held by allhome-country ( Japanese) partners and the subsidiary’sexpatriate intensity (log). The results of these robustnessanalyses are reported in the Results section.

3We thank an anonymous Reviewer for bringing thisdynamic and control variable to our attention.

4We thank an anonymous Reviewer for suggestingthis control variable.

5We also executed regression models as robustnesstests in which the organizational control dependentvariable was constituted by three indicators – the focalMNE’s proportionate share of total equity in thesubsidiary investment, the proportionate share of totalequity in the subsidiary investment that was held byall home-country (Japanese) partners and the subsi-diary’s expatriate intensity (log). While the signs of thecoefficients in these models were generally consistentwith our theory, the results generated by thesemodels were not as strong as the results presented inTable 4.

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ABOUT THE AUTHORSMichael A Sartor is a PhD Candidate at the IveyBusiness School, Western University. He received hisJD from Osgoode Hall Law School, York Universityand his MBA from the Ivey Business School, WesternUniversity. His research focuses on global strategy,foreign direct investment, emerging economies andthe institutional environment of foreign markets.

Paul W Beamish holds the Canada Research Chairin International Business at the Ivey BusinessSchool, Western University, London, Canada. Heserved as Editor-in-Chief of JIBS from 1993 to 1997,and is a Fellow of the Royal Society of Canada,Academy of International Business, and Asia PacificFoundation. His research focuses on FDI, joint ven-tures, emerging markets and activities of the multi-national enterprise.

Accepted by Paula Caligiuri, Area Editor, 28 May 2014. This article has been with the authors for two revisions.



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