the diffusion of foreign divestment from burma · dissolve its joint venture with pepsi-cola...

Strategic Management JournalStrat. Mgmt. J., 35: 1032–1052 (2014)

Published online EarlyView 11 July 2013 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/smj.2147

Received 5 June 2012 ; Final revision received 26 April 2013

THE DIFFUSION OF FOREIGN DIVESTMENTFROM BURMA

SARAH A. SOULE,1* ANAND SWAMINATHAN,2 and LASZLO TIHANYI31 Stanford Graduate School of Business, Stanford, California, U.S.A.2 Goizueta Business School, Emory University, Atlanta, Georgia, U.S.A.3 Mays Business School, Texas A&M University, College Station, Texas, U.S.A.

We examine variation in the rate of divestment by multinational firms from Burma. We argue thatin addition to a set of firm-level characteristics known to impact divestment decisions, firms arealso influenced by characteristics of their home country and the divestment patterns of others.Using data on firms operating in Burma during 1996–2002, we model these multiple influenceson firms to divest. Our results show that beyond firm-level concerns, firms divest in responseto the political characteristics of their home country, including protest, the level of politicalfreedom, and transparency of institutions. We also find that the centrality of their home countryin the network of intergovernmental organizations impacts divestment patterns in interestingways. Copyright 2013 John Wiley & Sons, Ltd.

INTRODUCTION

Foreign divestment is a significant corporate-leveldecision that involves the sale of international sub-sidiaries, closure of foreign plants, and exit fromforeign markets. Despite the importance of thetopic, we know relatively little about the factorsleading firms to divest their foreign investments(Berry, 2013; McDermott, 2010). While previ-ous research finds that firms typically divest theiroperations to improve performance (see reviewin Berry, 2013), scholars of corporate strategyincreasingly consider divestment as a critical ele-ment of complex resource allocation decisions,including investments into new (foreign) sub-sidiaries, product diversification, and research anddevelopment (Hoskisson, Johnson, and Moesel,1994; Markides, 1995).

Keywords: divestment; Burma; social movements; diffu-sion; politics*Correspondence to: Sarah A. Soule, Stanford Graduate Schoolof Business, 655 Knight Way, Knight Management Center,Stanford, CA 94305, U.S.A. E-mail: [email protected]

Copyright 2013 John Wiley & Sons, Ltd.

Resource allocation decisions by means ofdivestment are likely the result of changes infirm preferences and environmental conditions thathad originally motivated firms to invest in aforeign market. However, there may be a host ofadditional factors that firms and their managersconsider when they decide to exit a foreign market.In particular, several scholars have suggested thatfirms may divest of foreign holdings for politicalreasons and/or because they are pressured to doso by their stakeholders (Berry, 2013; Boddewyn,1983; Kaempfer, Lehman, and Lowenberg, 1987;Kobrin, 1980; Lansing and Kuruvilla, 1988; Singerand van der Walt, 1987; Soule, 2009). Othershave found that divestment decisions are not madein a vacuum; rather, divestment decisions diffusebetween similar organizations (Soule, 1995).

The idea that firms may divest for reasonsbeyond concerns about profit and performance iscompelling to scholars interested in how firmsrespond to political conditions and/or stakeholdersand how firms respond to the actions of other firms,especially during uncertainty (Hiatt and Sine, inpress). However, the extant empirical literature on

Divestment from Burma 1033

this question has suffered for several reasons, allclosely related to the fact that obtaining data onfirm divestiture is notoriously difficult, in large partbecause firms are reluctant to share informationon their divestment patterns for the reason thatdivestment is seen as a type of failure (Hamiltonand Chow, 1993; McDermott, 2010). First, mostempirical treatments of divestment have examinedcompanies from only one home country (e.g.,Benito, 1997; Berry, 2013; Henisz and Delios,2004).1 Thus, we know little about how variationin home country factors influences divestment.Second, few studies compare firms across multipleindustries (see review in McDermott, 2010). Thus,it is difficult to know if firms operating in certainindustries are more or less likely to divest and,if so, if this varies by home or host countrycharacteristics. Finally, most empirical treatmentsfocus on only one set of explanatory factors at atime; that is, the effect of stakeholder pressures ondivestment (e.g., Soule, 2009), or the effect of hostcountry political factors on divestment (Heniszand Delios, 2004), or the diffusion of divestment(Soule, 1995).

While there is still much to be admired inthe existing literature, we propose a more com-prehensive approach to the topic of firm divest-ment, and we obtain data that allow us speak tosome of the unanswered questions in the liter-ature. Specifically, we examine firm divestmentfrom Burma2 from 1996 to 2002. Using event his-tory data on 449 multinational firms (housed in 32different countries) that had investments in Burma,we show that, controlling for a combination offirm characteristics, home country political char-acteristics and diffusion pressures influenced thesefirms’ decisions about whether or not to withdrawfrom Burma during this period. The divestmentprocess, like most firm decisions about controver-sial subjects, is highly contested and plays out

1 In other words, the typical research design examines thedivestment patterns of Japanese (e.g., Henisz and Delios, 2004)or Norwegian (e.g., Benito, 1997) or American (e.g., Berry,2013) companies doing business in some number of hostcountries.2 Note that in 1989, the Burmese military changed the nameof the country to Myanmar. The name change is consideredcontroversial because it is seen as less inclusive of minoritiesand was also never formally approved by any legislative bodyin Burma. Moreover, the US (along with Ireland and the UnitedKingdom) has not adopted the name change. Thus, in this paperwe follow the convention of the US Government and of otheracademics (e.g., Schock, 1999) and use ‘Burma’ rather thanMyanmar.

at multiple levels (Schneiberg and Soule, 2005).After describing our empirical context, we developseveral hypotheses about a firm’s rate of divest-ment from Burma. We then describe our researchdesign and interpret the results of our statisticalanalyses. Our results highlight the importance ofattention to the complicated reality of corporatedecision-making processes—a reality that is notdetermined solely by attention to corporate profitsand performance. In fact, our results indicate thata firm’s home country political character matters agreat deal to divestment decisions, as does a firm’srelationships to other firms.

FIRM DIVESTMENT FROM BURMA

On May 17, 2012, Secretary of State HillaryClinton announced that the United States waslifting sanctions that, for decades, had barred USinvestment in Burma, an action that was criticizedby many human rights activists and organizationsbut that was soon followed by the relaxation ofsanctions by the EU, Japan, Canada, and Australia(Myers, 2012).3 This action was prompted by the2011 election of a new president in Burma, UThein Sein and the fact that Aung San Suu Kyiand members of her opposition party (the NationalLeague for Democracy) had finally been allowed tooccupy seats in the Burmese Parliament. In short,it would appear that Burma is in the midst of adeep political transition—most would argue, forthe better.

Prior to this recent turn of events in Burma,the country was considered by most to be apariah state, with a terrible record of humanrights abuses during the 1962–2011 period ofmilitary rule. The list of human rights abusesthat the military government was accused of inthe 1962–2011 period ranged from censorship totorture, from forced labor to physical surveillance,from ethnic cleansing to rape, from extrajudicialkillings to slavery, from restrictions on religion toconscripting children into the military (e.g., Marlayand Ulmet, 2001; White, 2004). These and other

3 Note that the new policy does not end American governmentalsanctions against Burma; rather it grants license to Americancompanies to do business in the country via suspendingenforcement of the sanctions. In fact, the sanctions will remainon the books as ‘an insurance policy’ in the event that thecountry’s political transition stalls (Myers, 2012).

Copyright 2013 John Wiley & Sons, Ltd. Strat. Mgmt. J., 35: 1032–1052 (2014)DOI: 10.1002/smj

1034 S. A. Soule, A. Swaminathan, and L. Tihanyi

abuses were brought to wide international attentionin 1988 with the massive, nationwide, student-led, pro-democracy uprising (Schock, 1999, 2005).While the demonstrations and rallies associatedwith the uprising were brutally repressed, theypaved the way for the multiparty legislativeelections in 1990, in which the National Leaguefor Democracy (NLD) won 83% of parliamentaryseats. Despite this landslide victory, the militaryjunta refused to give up their power. They insteadplaced Aung San Suu Kyi under house arrest,where she remained sporadically until the end of2010.

Before many nation states instituted economicsanctions against Burma, investing in the countrywas quite common, and there were good reasonsfor this. Doing business in Burma provided firmswith access to natural resources with limitedlocal or international competition. Additionally,operating in Burma provided access to inexpensivelabor to firms that were willing to employ workersfrom a labor pool that was notoriously under-educated and under-skilled. If firms were willingto deal with the military government, they likelyrealized above average profits and were able tosatisfy the interests of their shareholders.

Yet, there were several risks involved in invest-ing in Burma during this period. Firms investingin Burma had contracts with the corrupt govern-mental elite, which in addition to controlling thepolitical system also controlled the formal econ-omy.4 In practice, this meant that the Burmeseregulations on foreign investment, import–exportprocedures, licensing, and so on were all subjectto change at the whim of government elites. Aswell, it meant that paying ‘tea money’(bribes) togovernment officials was common.

Additionally, operating in Burma also entailedrisks to a firm’s reputation because of the globalmovement condemning the nation for its doc-umented human rights abuses described above.Because the government in Burma was known forits heavy repression of dissidents, few people inBurma dared to oppose the government’s policies,thus a chief strategy of this global movement wasto target multinational firms in their home coun-tries with the goal of encouraging them to pull theirinvestments out of Burma. One effect of protest

4 http://www.icftu.org/displaydocument.asp?Index = 991222320&Language = EN [24 April 2012].

directed at firms doing business in Burma was todamage the image and credibility of these firms(Danaher and Mark, 2003).5 This is reflected inthe comments of Karel Vuurestee, the chairmanof Heineken on the day of his company’s divesti-ture from Burma: ‘Since then [when the companyentered Burma] the public opinion and issues sur-rounding this market have changed to a degreethat could have an adverse effect on our brand andcorporate reputation’ (quoted in Usborne, 1996).

Given these risks, it is not surprising thatmany multinational firms from several countriesdecided to divest their Burmese holdings in the late1990s and 2000s. However, there was substantialvariation in the rate of divestment of thesefirms. For example, in 1997, PepsiCo decided todissolve its joint venture with Pepsi-Cola ProductsMyanmar after facing sharp criticism for its tiesto Thein Tun, the PepsiCo franchise-owner inBurma who had been accused of supporting thegovernment’s brutal repression of the Burmesepro-democracy movement (Cooper, 1997). Thedecision to pull out of Burma came after themobilization of an organized social movementthat included encouraging Michael Jackson toend his PepsiCo sponsorship, targeting Harvardand other universities that had campus diningcontracts with PepsiCo, and an organized Internet‘corporate campaign’ against PepsiCo’s because ofits involvement in Burma (Cooper, 1997; Danaherand Mark, 2003; Manheim, 2004).6

PepsiCo’s decision to sever financial ties toBurma, like the decisions of J Crew Clothing,Motorola, Apple, and many other multinationalfirms, was hailed as a victory by human rightsactivists across the globe. However, PepsiCo’sdecision and the decisions of these other firmswere certainly not representative of the actionsof all firms with business ties to Burma (InvestorResponsibility Research Center, 2002a, b). Forexample, a particularly recalcitrant firm wasUnocal, a former US oil and gas company,which consistently refused to bow to pressuresfrom activist groups. Unocal was involved inthe construction of a 416-mile long natural gas

5 For research on how organizational image motivates organiza-tional strategy and action, see Dukerich, Golden, and Shortell(2002) and Whetten and Mackey (2002). For research on howsocial activism, specifically, can harm firms’ reputations, seeKing and Soule (2007) and King (2008).6 In 2012, PepsiCo Inc., reached a deal with Diamond Star todistribute its products in Burma once again (Barta, 2012).



pipeline between Burma and Thailand. Duringthe initial phase of construction, Burmese militarytroops were deployed to protect workers. Thesetroops were accused of raping, killing, andtorturing the workers (Spar and La Mure, 2003).Not surprisingly, Unocal became the target ofa concerted campaign to get the company towithdraw from Burma, but it refused to do so.

In this paper, we ask the broad question of whatfactors influence a firm’s decision to divest fromcountries, testing our arguments on firms investedin Burma. In the following section, we present ourcentral argument, that a firm’s decision to divestits operations from countries that face internationalsanctions is simultaneously influenced by severalcontextual factors. Specifically, we extend previ-ous divestment literature on firm-level determi-nants by developing hypotheses on how the char-acteristics of the home country in which the firmis embedded and pressures from other firms thathave already divested their operations may moti-vate firms to leave Burma.

THEORY AND HYPOTHESES

There are a number of reasons why multinationalfirms divest operations in other countries (e.g.,Berry, 2013).7 First, at a most basic level, firmsdivest operations because of performance andprofit concerns (Berry, 2013; Duhaime and Grant,1984; Gleason, Mathur, and Singh, 2000; Hamiltonand Chow, 1993; Hryckiewicz and Kowalewski,2011; Montgomery and Thomas, 1988; Sachdev,1976). In an early review of the literature, Bod-dewyn (1979: 22) notes that financial consider-ations ‘predominate when it comes to explain-ing divestment’ and that these considerations canstem from ‘poor performance of the subsidiaryor division, the inability of the parent companyto sustain further losses, or the lack of capitalto finance the modernization or expansion neces-sary to survive’. Others suggest that divestment ismotivated by market and production cost-reductionopportunities in foreign subsidiaries (Berry, 2013).Additional firm-level characteristics that influ-ence divestment include firm size and scope of

7 While it may be tempting to assume that these reasons aresimply the flipside of the reasons for foreign direct investment ,it is clear that this is not the case. For research on the reasonsfor foreign direct investment, see Knickerbocker (1974) andNachum and Zaheer (2005).

the firms’ international operations (Benito, 1997;Berry, 2013; Lee and Caves, 1998; Li, 1995;Mariotti and Piscitello, 1999; Mata and Portugal,2000).8 Based on this literature, the analysis belowincludes measures of firm size, firm performance,and firm scope of international involvement.

While a substantial body of literature finds sup-port for the claim that divestment decisions aremade because of lagging profits and missed busi-ness opportunities, firms often make divestmentdecisions when their performance is high or whenthey are able to continue to realize business oppor-tunities in foreign markets. Because firms withforeign operations and subsidiaries must grapplewith the political environment of the host country,some scholars have found that firms will foregoprofits when the political situation in a host countryis sufficiently unstable or risky (e.g., Berry, 2013;Henisz and Delios, 2001; Henisz and Macher,2004; Henisz, Zelner, and Guillen, 2005; Hiatt andSine, in press).

In addition to the political character of thehost country, firms must also grapple with thepolitical character of their own home country(Holburn and Zelner, 2010; Li and Resnick, 2003;Schollhammer and Nigh, 1984). In particular, firmsare frequently targeted by protest, demonstrations,corporate campaigns, and boycotts in an effort toget them to divest of holdings in countries withpoor human rights records (Soule, 2009; Spar andLa Mure, 2003). Additionally, home countries varyconsiderably on their level of political stability andtransparency.

Finally, in addition to a firm’s own financialconsiderations and the political character of thehost and home countries, firms also monitorwhat other firms are doing and often followsuit. For example, Shaver, Mitchell, and Yeung(1997) argue that firms learn about foreign directinvestment from other, more experienced firmsand often make critical decisions based on whatother firms do. Reid and Toffel (2009) reportsimilar spillover effects in their study of corporatedisclosure of climate strategies. They find thatshareholder resolutions filed against a single firmresult in changes in other firms’ practices withinthe same industry. And, Soule (1995) argues that

8 For empirical treatments that also examine industry-leveleconomic factors and the effect of interfirm competition onfinancial considerations, see Martin, Swaminathan, and Mitchell(1998) and Guillen (2003).



divestment decisions by universities were drivenby diffusion processes.

The model of divestment that we present herebuilds on previous work on diffusion of behavioramong multinational firms and the influence of thepolitical environment on international strategies.Our model focuses on the political character ofthe home country (e.g., protests, level of politicalfreedom, and transparency of transactions) andinterorganizational effects based on the firm’ssize, internationalization, and the membershipof the firm’s home country in economic andsocial intergovernmental organizations (IGOs).9

We discuss each of these in turn in more detail.

Home country effects

In addition to firm performance, size, and otherfirm-level characteristics studied in the previousliterature, we suggest that the political characterof a firm’s home country could also influenceforeign divestment decisions.10 The developmentof political institutions in a country, in general,provides the environment in which firms makedecisions about the scope and organization oftheir foreign operations (Garcıa-Canal and Guillen,2008; Guler and Guillen, 2010; Holburn andZelner, 2010; Schollhammer and Nigh, 1984;Siegel, Licht, and Schwartz, 2008). Given this,we offer three hypotheses relating the politicalcharacter of a firm’s home country to its likelihoodof divestment from a country that is subject tointernational sanctions.

First, protests, a form of social activism, in thehome country should influence a firm’s divest-ment decision. When activists target firms, theymay not only increase the firms’ costs of doingbusiness, but may alter their competitive posi-tion (King and Soule, 2007; Reid and Toffel,2009). For example, Hiatt, Sine, and Tolbert(2009) find that activism can delegitimize organi-zations by promoting behavioral norms, pressuringchanges in regulations, and educating the public.

9 In addition to these foci of our model, we also include measuresof firm size, firm performance, and firm scope of internationalinvolvement, in keeping with the past research on divestment.10 While most of the literature on foreign divestment focuseson the political environment of the host country, we hold thatconstant by focusing on a single host country (Burma) andinstead focus on variation in the political environment of homecountries.

Social activism, thus, likely has strategic implica-tions (Baron, 2001; Siegel and Vitaliano, 2007).The movement against corporate financial ties toBurma involved student, labor, human rights, andenvironmental organizations, all of which sharedthe common goal of reducing the flow of resourcesfrom foreign investors to Burma with the ulti-mate goal of pressuring the local government tocease their documented human rights abuses. Toaccomplish this goal, organizations such as theFree Burma Coalition (FBC) targeted multinationalcorporations known to produce goods in Burmawith protest demonstrations and boycotts (Soule,2009; Spar and La Mure, 2003). While the FBCwas founded in the United States, similar advocacyorganizations were also active in other countriesand, like the FBC, attempted to pressure firms todivest their Burma-related holdings (Cooper, 1997;Manheim, 2001).

Several accounts of the movement directed atfirms with financial ties to Burma have concludedthat many firms did, in fact, bow to the pressuresof the movement. For example, Spar and La Mure(2003) note that by 2002 several US based firms(including Costco, Wal-Mart, and Levi-Strauss)had divested their Burmese holdings because ofthe divestment movement. Anecdotal accounts ofvarious divesting companies point to the real pos-sibility that they divested their Burmese opera-tions because of activist pressures. For example,Christopher Sinclair, the Chief of Pepsi in the mid-1990s, said (when referring to Pepsi’s decisionprocess), ‘Obviously pressure from consumers andshareholders is what we’ll respond to’ (OklahomaCity Journal Record , 1996). Thus, we expect thatfirms from home countries with documented anti-Burma protest events will be quicker to divest thanfirms from home countries with no documentedactivism. Hence we hypothesize

H1: Anti-Burma protest in the home countryof a firm will increase the likelihood of thefirm’s divestment from Burma .

Second, we expect that the general politicalconditions in the home country will influencethe propensity of divestment from Burma (Hol-burn and Zelner, 2010; Li and Resnick, 2003;Schollhammer and Nigh, 1984). In politically freeand open countries, citizens can influence whattheir governments do and thus can have a voice



in how governments regulate firms. Multinationalfirms headquartered in these countries are likelyto consider the opinion of a wider range of con-stituents, in addition to the preferences of theirshareholders, when they operate in foreign loca-tions targeted by international sanctions and con-cerns. Political freedom allows citizens to expresstheir concerns about the worldwide practices ofmultinationals that are headquartered in their coun-try. They can push legislation through their electedrepresentatives to limit profit motives in interna-tional operations and ban corporate practices insideand outside the borders of their country. In con-trast, activists in countries with limited politicalfreedom often face political and civil violence asconsequences of their actions. The lack of opportu-nities to express concern in uncertain and unstablepolitical environments does not motivate firms tochange their existing corporate practices. In addi-tion to the limited influence by citizens, lack ofpolitical freedom in a country prevents the emer-gence of new ventures that can present alternativesto existing corporate practices. For example, intheir study of new ventures in Colombia, Hiattand Sine (in press) find that an environment withpolitical and civil violence decreases the benefitsof strategic planning and survival of new organi-zations. Therefore,

H2: Political freedom in the home country ofa firm will increase the likelihood of the firm’sdivestment from Burma .

Third, we expect that firms from countries withhigher levels of transparency in their public trans-actions will be quicker to divest from Burmafor two different reasons. First, better and moretransparent institutions in a firm’s home coun-try may help firms to seek opportunities in moresophisticated markets, and withdraw from countryenvironments with underdeveloped institutions andcomplex government bureaucracy (Garcıa-Canaland Guillen, 2008; Holburn and Zelner, 2010).Moreover, business opportunities in more sophisti-cated markets are largely unavailable to firms fromcountries with high levels of corruption. The oper-ations of firms in such countries therefore may belimited to underdeveloped markets, such as Burma.Second, a high level of transparency in dealingwith government officials in a firm’s home countrylikely increases the conflict between the headquar-ters and the subsidiary management in Burma.

Bribery and strong ties to the government are oftenconditions for success in the local subsidiary oper-ations of multinational firms. While such practicesmight be acceptable to firms from countries char-acterized by high corruption, they likely will not betolerated by firms operating under more transpar-ent institutional conditions in their home countries.

H3: Higher level of transparency in publictransactions in the home country of a firmwill increase the likelihood of the firm’sdivestment from Burma .

Interorganizational effects

Inherent in our discussion above is that firms areassumed to be discrete entities whose actions areinfluenced exclusively by their own characteristicsand the characteristics of their home countries.Certainly, in a world increasingly characterized bya variety of relations between organizations locatedin disparate corners of the world, it makes sensethat these firms affect one another in real ways.This does not mean that the above approachesare unimportant; rather it means that a firm’sdecisions are affected not only by the focal firm’scharacteristics and by the character of its homecountry, but also by the actions of other firms.

Why would the actions of other firms affectwhat a particular firm does with respect to divest-ment? During times of uncertainty, organizationslook outward to others and model their behaviorafter important referents in a quest for legitimacy(DiMaggio and Powell, 1983). Important referentsmight be those organizations to which a focal orga-nization is directly connected through joint mem-bership in associations or through shared boardmembers and personnel, or those regarded as supe-rior or successful (Briscoe and Safford, 2008; Han,1994; Haveman, 1993; Scott, 1995) or similar onsome culturally constructed dimension (Schneibergand Soule, 2005; Soule, 1997; Soule and Earl,2001; Soule and Zylan, 1997; Strang and Soule,1998). Such accounts provide a plausible explana-tion for why firms may influence one another viamonitoring and imitation, but we turn to diffusiontheory to help us understand the process by whichthis happens (Strang and Soule, 1998). Relationalmodels of diffusion hold that information flowsbetween actors through their direct networkrelations, thus the rate of diffusion should be



higher when actors are in direct and frequent con-tact. But, scholars have also noted that actors aresometimes indirectly connected through commonmembership in a social category, a phenomenonStrang and Meyer (1993) call ‘cultural linkage’

In addition to specifying how divestment mayflow between directly and indirectly connectedfirms, diffusion theory also allows us to considerimportant asymmetries in the diffusion process.Diffusion theory specifies that actors (in ourcase, firms with investment in Burma) in someenvironments are more ‘susceptible’ (that is, theyare more likely to be influenced by previousadopters of an action), while others are more‘infectious’ (that is, their adoption behavior ismore likely to influence others). Thus, when weconsider the effects that firms have on other firms,it is important to recognize that not all firms shouldbe treated the same. Some firms’ actions may bemore likely to spur others to act, while other firmsmay be more likely to jump on the bandwagonof divestment (Briscoe and Safford, 2008; Rao,Greve, and Davis, 2001). These insights lead usto several hypotheses regarding interfirm effectsof divestment behavior.

First, firms are more likely to be responsive orsusceptible to the divestment behavior of otherfirms to the extent that divestment involves lowtransaction costs or in cases where they are con-cerned about negative spillovers on their reputation(Spar and La Mure, 2003). Specifically, we expectthat the level of embeddedness of the firms’ homecountry in intergovernmental organizations (IGOs)will affect the level of susceptibility of firms to thediffusion of divestment. IGO connectedness hasbeen shown to promote trade (Ingram, Robinson,and Busch, 2005), peace (Pevehouse and Russett,2006) and democracy (Torfason and Ingram, 2010)among countries. In spreading global policies andpractices, IGOs act as a coordination mechanismthat allows countries to learn about each other’schoices and emulate models that are available tothem (Dobbin, Simmons, and Garrett, 2007).

We believe that a country’s membership andactive participation in IGOs influence not onlynational policies but also the behavior of firmsbased in that country. We hypothesize that firmsfrom home countries that are more central in thenetwork of economic IGOs will be less susceptibleto divestment, whereas firms from home countriesthat are more central in the network of social IGOswill be more susceptible to divestment pressures.

Our expectation is based on the premise thateconomic and social IGOs operate under differentsets of norms, emphasizing economic growth andsocial welfare respectively. On the one hand,firms from home countries that are more centralin the network of economic IGOs may valuethe location opportunities that Burma can offer,including natural resources and low labor costand, thus, are expected to be less susceptible topressures for divestments by other firms. Firmsfrom home countries that are more central in thenetwork of social IGOs, on the other hand, may bemore susceptible to divestment pressures, owing totheir better understanding of and sensitivity to thedeteriorating social conditions in Burma. Thus,

H4: Firms from home countries that are morecentral in the network of economic IGOs willbe less susceptible to other firms’ divestmentactions from Burma .

H5: Firms from home countries that are morecentral in the network of social IGOs will bemore susceptible to other firms’ divestmentactions from Burma .

In addition to the hypotheses regarding suscep-tibility of some firms, we expect that larger firmsand firms with more international experience maybe more infectious; that is, their actions may bemore likely to be copied by others, than the actionsof smaller and less experienced firms. Becausethey employ more people and account for largerpercentages for their countries’ production, largerfirms tend to gain high status and be regardedas examples as corporate success by other firms.Actions of larger firms may also be more news-worthy, due to their worldwide market share andspending on advertising. When these firms decideto divest from a country, like Burma, their actionmay convey special and costly information aboutan uncertain market. Additionally, others may wishto emulate the strategies of more experienced com-panies in international markets, especially in timesof uncertainty (Lieberman and Asaba, 2006; Raoet al., 2001; Shaver et al., 1997). The actions ofthese more experienced firms regarding specificuncertain markets are more contagious becausethey have the ability to transfer their experi-ence from other similar markets in their broader



portfolio of international operations. Their divest-ment from Burma can be particularly newsworthyto less experienced firms that do not want to losepublic support by staying too long in an uncertainmarket.

H6: Divestment from Burma by larger firmswill diffuse to other firms .

H7: Divestment from Burma by more interna-tionally diversified firms will diffuse to otherfirms .

Finally, we hypothesize that divestment fromBurma more likely diffuses within subcommuni-ties of firms that are similar in some respect.When Heineken considered the divestment of itsBurmese operations, it was responding not onlyto concerns in its home country, the Netherlands,but it was also following a similar decision madeby a key competitor. Their decision ‘came onlya day after its Danish competitor, Carlsberg, alsorevealed that it would be pulling out of Burmarather than face the risk of an international boy-cott of its products’ (Usborne, 1996). The highlevel of uncertainty in the business environment ofBurma makes it particularly important for firms tomodel their behavior after other similar firms theyregard as successful (Briscoe and Safford, 2008;DiMaggio and Powell, 1983; Soule, 1997; Strangand Meyer, 1993; Strang and Soule, 1998.)

While there are different ways to define similar-ity of firms, firm size and level of internationaliza-tion may be particularly relevant characteristics inforeign divestment decisions. When they considertheir exit from Burma, larger firms may modeltheir behavior after the actions of other large firms,while smaller firms may be less visible, there-fore their actions may not provide helpful cuesfor larger firms’ divestment decisions. Similarly,firms that have a great deal of international expe-rience may look for insights from the strategies ofother similar firms. While their own broader inter-national experience exposes these firms to differentpolitical regimes and institutional environments,divestment from Burma by other firms with exten-sive international experience may send an impor-tant additional signal to them. Therefore, we posit:

H8: Divestment from Burma will diffusewithin a subcommunity of firms that aresimilar in size.

H9: Divestment from Burma will diffusewithin a subcommunity of firms that aresimilar in their international diversification .

DATA AND METHODS

Dependent variable

As noted above, we have collected data on 449firms, from 32 countries, that had business ties toBurma between 1996 and 2002.11 The dependentvariable in our analyses is a time-varying dichoto-mous measure for each firm-year, which is coded1 when a firm divested its Burmese holdings in agiven year (and is otherwise coded as 0). Thesedata come from quarterly publications by theInvestor Responsibility Research Center (IRRC)on multinational firm investments in Burmabetween 1996 and 2002 (see Appendix A). IRRC’squarterly publications provide an exhaustive list offirms with Burma investments until 2002 with vari-ations in size, industry, and national origin. As acheck on the reliability of these data, we exam-ined lists compiled by other organizations mon-itoring investments in Burma, including GlobalUnions (http://www.global-unions.org/burma/ [7March 2012]) and Irrawaddy Publishing Group, anexile group of Burmese citizens.12 We found thelists to be comparable.

We only analyze the divestment of firms withinvestments in Burma because these are the onlyfirms that are at risk of divesting. Our goal isto advance a theory of firm exit from Burmabased on those firms that had investments inthis country. We recognize that this may limitthe generalizability of findings to other firm

11 We are not immune to the data acquisition issues describedearlier. In fact, it was data availability that led us this particulartime period, rather than a longer period (which would havebeen ideal). This necessarily means that our data are subjectto both left and right censoring. With respect to left censoring(the more serious of these two issues), we believe that 1996is the right starting point, since 1995 was the most criticalyear in the international movement against Burma (Danaher andMark, 2003; Soule, 2009). This was the year in which AungSan Suu Kyi was first released from house arrest, the year inwhich the Free Burma Coalition initially mobilized (organizingthe ‘International Day to Free Burma’ in October) and the year inwhich Beyond Rangoon was released. All of these events drewinternational attention to Burma, and pressures on companies todivest grew in response (including efforts by US shareholders tosubmit resolutions for consideration in the 1996 proxy season).12 Irrawaddy’s list is no longer posted online but is availablefrom the authors.



populations because we do not know if thosefirms that had investments in Burma during thisperiod were substantively different from all otherfirms. To determine if there is bias in the sampleselection, we would need information on all firmsat risk of investing in Burma (i.e., the worldwideset of multinational firms operating in the 1990s).Unfortunately, this is not feasible; thus our resultsshould be understood as applying only to thefirms with investments in Burma in 1996.13

Statistical model and independent variables

As the preceding discussion makes clear, webelieve that firms’ decisions to divest their opera-tions in Burma were affected by the character ofthe firm, the character of the home country of thefirm, and interorganizational pressures to do so.To incorporate all of these influences in a singlemodel, we use the additive form of the heteroge-neous diffusion model , which has been discussedelsewhere in detail (Greve, Strang, and Tuma,1995; Strang and Soule, 1998; Strang and Tuma,1993). This event history model is represented as:

rn (t) = exp(a ′xn

) + exp(β ′vn

)

∑

s∈τ(t)

exp(γ ′ws + δ′zns

)

In this model, n refers to those firms that havenot yet divested and s refers to those that havealready done so. Here,

• xn is a vector of variables describing n’s intrinsicpropensity to divest.

• vn is a vector of variables describing n’ssusceptibility to contagion or diffusion.

• ws is a vector of variables describing theinfectiousness of s.

• zns is a vector of variables describing theproximity of n and s (in other words, theinfectiousness of s for a specific n, or thesusceptibility of n for a specific s).

The sources of our data for the variables thatare entered into each of the vectors are describedin detail in Appendix B. We estimate these modelsusing RATE 3.3 (Tuma, 1996).

13 We are unaware of divestment studies that have been ableto use the Heckman approach conditioning on entry behavior,presumably for the reasons we describe above.

Independent variables: firm characteristics

To capture firm-level effects found to be importantin previous research, we use the propensity vector(xn) and a set of variables measuring the character-istics of firms that might influence their decisionsto divest. We include measures of firm-level char-acteristics as controls in the propensity vector aswe would in a traditional event history model. For-eign direct investment (FDI) is a dummy variablethat measures a firm’s level of commitment to itsBurmese operations. FDI, in general, indicates alasting interest by the investor through higher than10% ownership stake and effective voice in themanagement of the local operation (InternationalMonetary Fund, 1993). This variable is coded 1in years when the investment is a FDI and 0 oth-erwise (e.g., nonequity investment). We measurefirm size by the yearly logarithm of total sales.Firm performance is measured (yearly) by returnon assets (ROA) weighted by industry sector ROA,a standard measure of profitability used in theliterature (e.g., Nickerson and Silverman, 2003).Using industry-adjusted ROA allows for a moreaccurate comparison of firm performance acrossdifferent industries. Our measure of internation-alization captures two important motivations forinternational expansion: access to foreign marketsand ownership of foreign operations. Firm interna-tionalization is a composite of foreign sales as apercentage of total sales and foreign assets as a per-centage of total assets, measured yearly (Tallmanand Li, 1996; Tihanyi et al., 2003). Finally, weinclude dummy variables for industries, includingmining, financial institutions, utilities, manufactur-ing, services, information, transportation, and retailand trade.

Independent variables: home countrycharacteristics

Whereas firms clearly are influenced by their ownfinancial analyses of whether or not divestmentis a beneficial strategy, we argue that they arealso affected by the political context of the homecountries in which they are embedded. To capturethese effects, we also include a number of differentcountry-level variables, measured annually, in thepropensity vector.14

14 Our data structure also lends itself to Hierarchical LinearModeling (HLM), since we have firms embedded in countries.



The first country-level variable is a time-varyingdummy variable that is coded 1 in years in whichthere was at least one documented anti-Burmaprotest event in the home country of the firms inour sample, and is included to test H1. These datawere coded from the archives at www.ibiblio.org,which is the home to one of the largest free collec-tions of newspapers (among other documents) onthe Internet. Trained research assistants searchedfor articles and press releases from around theworld using keyword search strings includingeither Burma or Myanmar, a particular year,and a set of keywords about protest demonstra-tions (e.g., Burma + protest + 1996, Myanmar +protest + 1997, Burma + demonstration + 1998).Such searches netted a number of different kindsof documents, ranging from newspaper articles, topress releases from various companies and fromthe FBC, to public listserv comments, to folkmusic lyrics, to opinion/editorial pieces. One typeof document that was helpful to us is the ‘BurmaAlert’, which was an online periodical publishedby the Associates to Develop Democratic Burma.This publication included brief discussions of var-ious kinds of Burma-related news from around theworld, including discussion of protest events sur-rounding human rights abuses in that country. Weasked research assistants to select first any news-paper article on protest related to Burma from ibib-lio.org or to locate the original newspaper articleon such protest, as described in the various issuesof ‘Burma Alert’. Then, the assistants read each ofthe articles and coded when and where a protestevent took place. From this information, we wereable to construct our time-varying dummy variablefor protest in a given country-year. We recognizethat this measure of protest is rather crude; how-ever, given that we are examining protest in 32countries spanning 1996–2002, there is not a morefeasible way to measure protest in these countries.

We also include an index of the level of politicalfreedom in the country, which is constructed byFreedom House, to test H2. The index is based onthe ratings of political rights in a country fromthe 1996–2002 editions of the Freedom of theWorld Survey. It measures political rights in three

We ran our basic model including all of the measures we includein our propensity vector using HLM (GLLAMM in Stata) andfound the results to mirror those presented below. Because weare also interested in modeling diffusion effects, we opted to usethe additive heterogeneous diffusion model discussed in the text.

main areas, including electoral process, politicalpluralism and participation, and functioning ofgovernment (http://www.freedomhouse.org/reports[May 1, 2012]). The index is measured on a 1–7point scale. We reverse-coded the original scalefor ease of interpretation, such that in our study, 7represents the highest level of political freedomand 1 represents the lowest level of politicalfreedom in a country.

Our third country-level variable is the level oftransparency (or lack of corruption) in a givencountry, which is included to test H3. This variableis measured by the Corruption Perception Indexcompiled by Transparency International. The indexis a composite of surveys of country analysts andbusiness people from multiple institutions world-wide, such as the Economist Intelligence Unit,IMD International, World Bank, World EconomicForum, and others. The values of the index rangefrom 1 to 10, where 1 = low transparency (highcorruption) and 10 = high transparency (low cor-ruption).

Finally, we include three additional country-level variables to control for the possibility thatfirms located in countries with strong ties to Burmawill be less likely, all things considered, to divest.Specifically, we include measures of the extentof the home country’s trade with Burma, diplo-matic relations with Burma, and investment inBurma. Data on trade with Burma were mea-sured by the trade flows (e.g., export and import)between Burma and the firm’s home country.These were collected from The Correlates of WarTrade Project dataset (Barbieri and Keshk, 2012;Barbieri, Keshk, and Pollins, 2009). We collecteddiplomatic relations (a dummy variable for diplo-matic representation), and country investment inBurma data (country FDI flow) from The Corre-lates of War Diplomatic Exchange dataset (Bayer,2006) and Worldbank and UNCTAD sources.

Independent variables: interfirm effects

Susceptibility

The susceptibility vector ( vn) lets us examine howcharacteristics of firms that have not yet divestedmight render such firms more open or vulnerableto influence by others. This vector measurespotential adopters’ susceptibility to divestment bycreating, in effect, an interaction term betweenthe cumulative number of divesting firms and



the firm-level characteristic of interest. Whilewe do not offer any specific hypotheses, weinclude two firm characteristics, size and level ofinternationalization, in the susceptibility vector.

We include two measures of network ties in thesusceptibility vector to test H4 and H5. We mea-sure a country’s yearly mean number of economicand social ties to other countries via shared mem-berships in intergovernmental organizations. Weexpect that centrality in the economic and socialIGO networks reflect country-level business andsocial pressures that influence the decision to con-tinue doing business in Burma. These data comefrom Ingram, Robinson, and Busch (2005) whoused the time-varying listing of IGOs and theirmembers from 1816 to 2001 provided by Peve-house, Nordstrom, and Warnke (2003) to constructa time-varying affiliation matrix of connectednessbetween two countries.

Infectiousness

The infectiousness vector (ws) captures the asym-metries of the interfirm influence in the diffusion.This vector allows us to examine the characteris-tics of firms that are more likely copied by othersduring their divestment from Burma. In this vector,we include firm size (H5) and internationalization(H6).

Proximity

The proximity vector (zns) captures a differentaspect of interfirm influence by examining howthe actions of firms in a particular category affectthe actions of other firms also in that category. Wefirst use the proximity vector to examine whetherdivestment was more likely to diffuse withinsubcommunities of firms that are similar in size(H8) or have the same level of internationalization(H9). We also include two additional controlvariables in the proximity vector, based on resultsrecently reported by Reid and Toffel (2009), whichshowed evidence of diffusion between firms in thesame industry. Industry groups in these modelsare based on the United Nations InternationalStandard Industrial Classification (ISIC) codes ofthe sample firms’ primary industries, but becauseof missing data, we create two different measures:one including all firms, even those that could notbe classified and one that only includes firms thatcould be classified.

RESULTS

Table 1 presents descriptive statistics on and acorrelation matrix of the variables. Our analysisof divestment in Burma is presented in Tables 2and 3.

The models in Table 2 include covariates onlyin the propensity vector and should be understoodas one would analyze a traditional event historymodel of the effects of a set of variables on therate of divestment in the absence of contagion.15

The results of all models in Table 2 suggest thatfirm-level characteristics have a limited effect ondivestment decisions. However, looking across themodels, we see that firms in the mining and financeindustries have higher rates of divestment thanthose in other industries.

All models in Table 2 show support for twoof our three hypotheses about how a firm’s homecountry characteristics impact firm decisions aboutdivestment from Burma. We find support for ourargument that protest activity in the home countryimpacts firm-level decisions regarding divestmentfrom Burma (H1). Firms from home countriesin which anti-Burma protests had occurred in agiven year were more than twice as likely to exitBurma as firms from home countries that did notexperience any protest activity (the multiplier ofthe baseline exit rate, Model 1, is given by exp(0.734) = 2.08). This finding lends support to thosewho have argued that protest can impact firm-leveldecisions (Soule, 2009).

We do not, however, find support for ourargument that a home country’s level of politicalfreedom would increase the rate of divestmentby firms therein. While marginally significant inModels 1 and 3 (and in the expected direction),the country’s level of political freedom does notsignificantly impact the rate of divestment of firm’stherein.

We do find support for our argument that thelevel of transparency in a given home countrywill impact firms’ decisions about divestment. Forexample, the coefficient in Model 5 shows thatfirms from home countries with the highest level(9.7) of transparency observed in our data are morethan seven times as likely to divest from Burmaas firms from the home countries with the lowest

15 We obtained similar results using discrete time event historyanalysis, using xtlogit in Stata. These results are available uponrequest from the first author.



Tabl

e1.

Des

crip

tive

stat

istic

san

dco

rrel

atio

ns(n

=2,

723)

Var

iabl

eM

ean

SD1

23

45

67

89

1011

1213

1415

1617

1819

2021

1.D

ives

tmen

t0.

050.

221.

002.

FDI

0.52

0.50

−0.0

51.

003.

Firm

’ssa

les

(log

)7.

921.

84−0

.01

−0.1

61.

004.

Firm

’spe

rf.

1.85

1.84

0.00

0.00

0.06

1.00

5.Fi

rm’s

inte

rnat

.70

.50

25.2

10.

01−0

.08

0.15

0.00

1.00

6.M

inin

g0.

070.

250.

050.

090.

00−0

.06

0.01

1.00

7.Fi

nanc

ial

inst

.0.

110.

310.

010.

200.

040.

01−0

.06

−0.0

91.

008.

Util

ities

0.01

.10

0.01

−0.0

30.

030.

030.

02−0

.03

−0.0

31.

009.

Man

ufac

turi

ng0.

340.

470.

00−0

.30

0.14

−0.0

60.

15−0

.19

−0.2

5−0

.07

1.00

10.

Serv

ices

0.08

0.27

−0.0

20.

13−0

.17

−0.0

3−0

.02

−0.0

8−0

.10

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3−0

.21

1.00

11.

Info

rmat

ion

0.05

0.21

0.01

0.10

−0.0

10.

26−0

.01

−0.0

6−0

.08

−0.0

2−0

.16

−0.0

61.

0012

.T

rans

port

atio

n0.

080.

27−0

.02

0.00

−0.0

10.

02−0

.02

−0.0

8−0

.10

−0.0

3−0

.21

−0.0

8−0

.06

1.00

13.

Ret

ail

and

trad

e0.

070.

250.

01−0

.10

0.02

−0.0

10.

00−0

.07

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0−0

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−0.1

9−0

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−0.0

6−0

.08

1.00

14.

Prot

est

inco

untr

y0.

850.

360.

05−0

.15

0.06

0.01

0.05

0.04

−0.0

80.

000.

050.

02−0

.02

−0.0

20.

071.

0015

.Po

l.fr

eedo

m6.

251.

400.

07−0

.30

0.28

−0.0

10.

150.

06−0

.09

0.05

0.14

−0.0

70.

04−0

.14

0.08

0.19

1.00

16.

Tra

nspa

renc

yIn

t.7.

141.

780.

06−0

.16

0.04

0.00

0.14

0.01

−0.0

10.

050.

08−0

.01

0.01

−0.0

60.

070.

050.

401.

0017

.E

con.

IGO

ties

17.2

62.

250.

01−0

.16

0.25

−0.0

10.

110.

01−0

.15

0.04

0.11

−0.0

3−0

.06

−0.0

6−0

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0.16

0.47

0.01

1.00

18.

Soc.

IGO

ties

9.38

1.40

0.05

−0.1

90.

170.

020.

150.

08−0

.05

0.04

0.08

0.00

−0.0

2−0

.07

0.03

0.24

0.46

−0.1

30.

811.

0019

.T

rade

with

Bur

ma

223.

7426

6.63

−0.0

50.

18−0

.14

−0.0

2−0

.22

−0.1

20.

02−0

.06

−0.0

80.

03−0

.08

0.04

0.01

−0.1

8−0

.54

0.21

−0.3

7−0

.62

1.00

20.

Bur

ma

dipl

.re

l.0.

170.

370.

010.

70−0

.07

0.05

0.11

0.07

0.08

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−0.0

30.

02−0

.02

−0.1

2−0

.14

0.00

−0.0

70.

020.

14−0

.33

1.00

21.

Cou

ntry

inve

st.

40.5

665

.27

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0.02

0.05

−0.0

70.

050.

04−0

.11

0.00

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0.03

−0.0

2−0

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−0.2

10.

35−0

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−0.2

20.

46−0

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1.00

22.

Indu

stry

grou

p25

.71

25.9

40.

000.

19−0

.06

0.10

−0.0

4−0

.21

0.51

0.03

−0.4

30.

480.

280.

260.

22−0

.03

−0.1

0−0

.09

−0.1

0−0

.05

0.00

0.00

0.04



Table 2. Firm divestment from Burma, 1996–2002

(1) (2) (3) (4) (5)

Intercept −5.684* −5.395* −5.697* −5.567* −5.492*

(0.900) (1.032) (0.953) (0.898) (1.029)FDI −0.348‡ −0.341‡ −0.348‡ −0.351‡ −0.347‡

(0.197) (0.198) (0.197) (0.197) (0.198)Firm’s total sales (log) −0.077‡ −0.073 −0.077‡ −0.073 −0.068

(0.045) (0.046) (0.045) (0.045) (0.045)Firm’s performance −0.0006 −0.0008 −0.0006 −0.001 −0.0004

(0.013) (0.013) (0.012) (0.013) (0.012)Firm’s internationalization −0.0002 −0.0007 −0.0002 −0.0001 −0.0001

(0.004) (0.004) (0.004) (0.004) (0.004)

Mining 0.960* 0.930* 0.961* 0.917* 0.900*

(0.340) (0.345) (0.342) (0.342) (0.346)

Financial institutions 0.797* 0.790* 0.798* 0.803* 0.825*

(0.345) (0.345) (0.346) (0.344) (0.347)Utilities 0.647 0.615 0.647 0.707 0.681

(0.748) (0.750) (0.748) (0.749) (0.752)Manufacturing 0.267 0.264 0.267 0.233 0.229

(0.280) (0.280) (0.280) (0.281) (0.281)Services 0.143 0.133 0.143 0.116 0.090

(0.424) (0.424) (0.424) (0.424) (0.426)Information 0.680 0.655 0.680 0.699 0.660

(0.436) (0.439) (0.436) (0.437) (0.441)Transportation 0.111 0.106 0.111 0.110 0.102

(0.443) (0.443) (0.443) (0.443) (0.444)Retail and trade 0.357 0.360 0.355 0.336 0.303

(0.383) (0.383) (0.384) (0.383) (0.386)

Protest in country 0.734* 0.729* 0.732* 0.730* 0.688‡(0.353) (0.352) (0.354) (0.352) (0.355)

Political freedom in country 0.199‡ 0.150 0.199‡ 0.150 0.080(0.105) (0.138) (0.105) (0.112) (0.144)

Transparency International Index 0.160* 0.174* 0.160* 0.192* 0.233*

(0.069) (0.073) (0.070) (0.074) (0.091)Trade with Burma — −0.0003 — — −0.0004

— (0.0006) — — (0.0006)Diplomatic relations with Burma — — 0.010 — 0.224

— — (0.239) — (0.292)Country investment in Burma — — — −0.002 −0.002

— — — (0.002) (0.002)Number of spells 2723 2723 2723 2723 2723Number of events 135 135 135 135 135Chi-square 44.38* 44.66* 44.38* 45.92* 46.62*

Degrees of freedom 17 18 18 18 20

Standard errors are in parentheses. ‡p < 0.10; *p < 0.05 (two-tailed test).

level (1.2) of political freedom ((exp (0.233 ×9.7)/exp (0.233 × 1.2) = 7.25).

Models 3–5 in Table 2 include the threeadditional country-level variables designed to tapthe extent of the home country’s relationships withBurma: trade with Burma, diplomatic relationswith Burma, and country investment in Burma.None of these additional variables affected the rateof divestment from Burma.

In addition to the character of a firm’s homecountry, it is critical to examine patterns of

diffusion and different types of influence generatedfrom other firms. Table 3 presents models designedto test these interfirm effects.

On these dimensions, robust findings withrespect to susceptibility of firms are shown inModels 1 through 3 in Table 3. We find thatfirms from home countries that are central ineconomic IGO networks are less susceptible toinfluence by the divestment activity of other firms;however, home country centrality in social IGOnetworks increases the susceptibility of firms to



Table 3. Diffusion of firm divestment from Burma, 1996–2002

(1) (2) (3)

Propensity (α):Intercept −20.250* −19.290* −22.06

(6.394) (7.102) (16.04)FDI −0.386 −0.415 −0.287

(0.314) (0.307) (0.365)

Firm’s total sales (log) −0.179* −0.173* −0.170*

(0.070) (0.070) (0.080)Firm’s performance 0.006 0.006 0.003

(0.016) (0.017) (0.020)

Firm’s internationalization 0.012* 0.012* 0.013*

(0.005) (0.005) (0.006)Mining 0.790 0.960‡ 1.364

(0.481) (0.510) (0.839)Financial institutions 0.380 0.401 0.880

(0.524) (0.529) (0.871)Utilities 0.779 0.756 1.464

(0.912) (0.922) (1.177)Manufacturing −0.267 −0.245 0.250

(0.413) (0.417) (0.795)Services −0.201 −0.197 0.307

(0.674) (0.684) (0.991)Information 0.957‡ 0.969‡ 1.559‡

(0.554) (0.556) (0.905)Transportation −12.77 −26.52 −21.04

(4055) (943100) (54170)Retail and trade −0.313 −0.289 —

(0.640) (0.645) —Protest in country 1.309‡ 1.278‡ 1.486

(0.755) (0.733) (0.931)

Political freedom in country 1.415* 1.329* 1.865(0.580) (0.628) (1.934)

Transparency International Index 0.745* 0.696‡ 0.517(0.337) (0.372) (0.385)

Trade with Burma 0.003* 0.003‡ 0.003(0.0015) (0.0017) (0.002)

Diplomatic relations with Burma 0.540 0.512 0.117(0.577) (0.577) (0.640)

Country investment in Burma −0.004 −0.003 −0.005(0.003) (0.003) (0.004)

Susceptibility (β):Intercept −85.360 −188.10 −137.50

(1,669) (148,100) (4,475)Country economic ties via IGOs −0.406* −0.403* −0.410*

(0.140) (0.141) (0.138)

Country social ties via IGOs 0.716* 0.712* 0.712*

(0.232) (0.234) (0.219)Firm’s total sales (log) 0.240 0.116 0.639

(0.250) (0.347) (0.528)Firm’s internationalization −13.550 −0.745 −1.570

(521) (6745) (162)Infectiousness (γ ):Firm’s total sales (log) 1.625 0.208 2.200

(33.06) (3884) (88.68)Firm’s internationalization 13.900 1.657 2.169

(521) (6,868) (163.3)



Table 3. (Continued)

(1) (2) (3)

Proximity (δ):Firm’s total sales (log) 0.255 0.132 −0.816‡

(0.187) (0.373) (0.430)Firm’s internationalization −13.54 −0.727 −1.555

(521) (6,745) (162)Industry group (incl. unclassified) — 0.803 —

— (1.709) —Industry group B (excl. unclassified) — — 0.849

— — (0.745)Number of spells 2723 2723 2145Number of events 135 135 116Chi-square 72.98* 72.75* 70.04*

Degrees of freedom 28 29 28

Standard errors are in parentheses. ‡p < 0.10, *p < 0.05 (two-tailed test).

the divestment behavior of other firms. Theseresults provide support for both H4 and H5 bysuggesting that country-level networks based oneconomic and social ties, by design, carry differentnorms that emphasize economic growth and socialwelfare respectively.

With respect to infectiousness, to our surprise,neither of our two hypotheses (H6 and H7) wassupported. The actions of more internationallyexperienced and larger firms were more infectiousthan the actions of other firms, but these differ-ences were not statistically significant. Divestmentdecisions by such firms did not set off a cascadeof divestment by other firms.

With respect to diffusion or proximity, we donot find support for either H8 or H9. Firms didnot appear to look to similarly sized firms (asmeasured by their total sales), nor did they lookto firms with similar levels of internationalization.

Models 2 and 3 in Table 3 estimate an alternativeexplanation: that divestment from Burma diffusedwithin industry subgroups, as has been shown byReid and Toffel (2009). In Model 2, we includeall firms, even if the firm could not be classifiedinto an ISIC industry subgroup; and in Model 3, werestrict the analysis to firms that could be classifiedinto an ISIC industry subgroup. Regardless ofwhich measure we use, we find no evidence thatdivestment decisions diffused between firms in thesame industry.

Finally, it is interesting to note in Models 1and 2 (Table 3), that firm-level characteristics aresignificant and consistent with past research. Inaddition, these more fully specified models provide

support for H2—firms from home countries withgreater political freedom are more likely to divesttheir Burmese operations.

DISCUSSION AND CONCLUSIONS

This paper contributes to the literature on divest-ment by examining the integrated influence ofhome country characteristics and interorganiza-tional effects. First, our focus on relational factors,in addition to home country factors, is importantbecause of the asymmetry between the decisionsinvolving foreign direct investment and divest-ment. That is, firms may not only divest foreignoperations because of financial considerations orunrealized business opportunities but because ofpolitical conditions, pressures by their differentstakeholders, and actions of members in their rele-vant reference groups. The case of divestment fromBurma suggests that these nonfirm-specific consid-erations may be even more important for firms thantheir profit and other business opportunities.

Second, our examination of the influence ofthe home country environment contributes to agrowing body of literature on the institutionaldeterminants of multinational firm behavior (e.g.,Garcıa-Canal and Guillen, 2008; Holburn andZelner, 2010). In this spirit, we find that firms fromcountries with higher levels of political freedomand transparency have a greater propensity todivest their Burmese operations. These resultssuggest that home country political characteristics,in addition to traditional business considerations,



may be meaningful determinants of internationaldivestment (McDermott, 2010).

Third, in this study, we show that commonalitiesin the political environment of nation states such ascommon membership in economic and social IGOsact as mechanisms for the diffusion of firms’ exitfrom a given country. While we emphasize theinformation and learning benefits of a country’scentrality in IGO networks, it is also possiblethat a country’s position in IGO networks reflectspublic opinion (Burstein, 1998) or the preferencesof elites. The centrality of the home country in thenetwork of economic IGOs diminished a firm’ssusceptibility to the divestment activity of otherfirms, whereas home country centrality in thesocial IGO network enhanced susceptibility. Theseresults indicate that cost–benefit analyses of howa particular decision might affect a firm should besensitive to factors external to the firm itself.

Fourth, our study also contributes to the liter-ature at the nexus of organizational studies andsocial movements (e.g., Hiatt et al., 2009; Soule,2009) by focusing on multinational firms, and theeffects of movements thereon. In particular, thepresent study illustrates how private politics inhome countries can affect corporate actions inother countries, indirectly through diffusion pro-cesses. Most research on private politics focuseson the direct impact of activism on corporateresponses within particular geographic spheres.That is, there are few studies that examine thefurther-reaching and indirect effects of activismon nonproximate firms via processes of diffusionand scale shift (Soule, 2009, 2013). An importantimplication of this is that social movement activitycan matter to firm-level decisions, either directlyvia protest or indirectly as firms’ divestment deci-sions spread to others.

Finally, the literature at the nexus of organi-zational studies and social movements has beenkeenly aware of the influence of both the corpo-rate and the political opportunity structure on theoutcomes of protest and social movement activ-ity (see reviews in King and Pearce, 2010; Soule,2009; Soule and Olzak, 2004). Our attention tothe impact of the country level political environ-ment is an important contribution to this litera-ture in that we are able to compare across manycountries’ unique political opportunity structures,while also controlling for elements of the corporate

opportunity structure, to assess how these impactfirm-level decisions.16

Future research

It seems reasonable to conclude with some sug-gestions for future research. First, we begin witha general call for more research on foreign divest-ment from countries with uncertain political envi-ronments or ones that are subject to internationalsanctions. As firms from many countries are com-peting for resources, increased efficiency, or mar-ket opportunities around the world, they have beeninvesting in countries with higher political risksin increasing numbers. This development, cou-pled with the eagerness of the political elites ofless developed and emerging countries to attractforeign direct investment, has led to some sce-narios in which firms have suffered significantdamages to their reputation or lost substantialinvestments. Researchers interested in these topicsmay study many host country locations, includingCuba, Syria, Venezuela, and several countries ofSub-Saharan Africa.

Second, as strategy scholars begin to recognizethe importance of political activities (includingsocial movements) and movement scholars beginto recognize that firms are increasingly importanttargets of protests and boycotts, it is critical forboth fields to pay careful attention to the other(Baron, 2001; Baron and Diermeier, 2007; Daviset al., 2008; Eesley and Lenox, 2006; Hiatt et al.,2009; Soule, 2009). For example, we call onscholars to think of ways to develop measures ofprotest and other social movement activities thatare important for decision makers in the firm. Find-ing reliable protest data from multiple countriesover a number of years for this research has beena challenge, as we describe above. Researchersstudying divestment in other country environmentsmay be able to collect data on relevant protests ina smaller number of countries using QualitativeComparative Analysis (Ragin, 2000).

Third, interesting contributions can be made byintegrating strategy and social movement researchin the study of foreign direct investment anddivestment in countries with weak political insti-tutions. As a recent study by Hiatt and Sine

16 We are grateful to an anonymous reviewer for these twotheoretical insights.



(in press) shows, new ventures struggle for theirsurvival in Colombia owing to local political andcivil violence. While multinational firms enteringthis and other similar institutional environmentslikely face similar difficulties, it would be interest-ing to investigate the extent to which their actionsare influenced by local collective actions. Anotherinteresting area for future research is the influenceof IGO networks on firm strategies in countrieswhere the rule-of-law is absent. Specifically, IGOnetworks may serve as substitutes in countries withunderdeveloped institutions.

Fourth, we call for additional research on theinterfirm effects on divestment or the adoptionof other firm strategies in their internationaloperations. Firm decisions are often made byconsidering the decisions and actions of other firms(Greve, 1995, 1996; Soule, 1997). Studying howthese decisions diffuse, thus, can reveal new andinteresting insights about firm behavior. While wedid not find any evidence that the divestmentrate was driven by similarity to other firms,this may be due to our period of observationwhen there was little uncertainty about Burmabeing a pariah nation state subject to sanctionsand protest activity. We encourage researchersto collect longitudinal datasets to model moreprecisely the diffusion of the adoption of differentstrategies in international business.

Fifth, we encourage research on changing firmstrategies regarding foreign investment into coun-tries that face international sanctions. Firms thatrespond to private politics in their home countryby leaving a foreign location may return laterwhen sanctions are lifted. However, there mightbe variation across firms, industries, and countriesin re-entry strategies. For example, Coca-Cola hasresponded to the recent easing of internationaleconomic sanctions against Burma by exportingto the country first. PepsiCo, at the same time,has signed an agreement to distribute its productsvia Diamond Star, a local conglomerate firm(Barta, 2012). Other multinational competitorsfrom different countries may follow differentre-entry strategies depending on the institutionaldevelopment of and collective activism in theirhome countries and their former ties to thepolitical elite in Burma.

In conclusion, our study on the diffusion offirm divestment from Burma adds to an increasingbody of research on foreign divestment. Theresults reported in this paper provide evidence

that firms, in addition to their own characteristics,also consider the political character of their homecountry, and the actions of other firms whendeciding whether to divest their foreign operations.These results have important implications for firmmanagers, organizers of social movements, andpolicy makers in home and host countries. Wehope these results also provide some interestingpoints of departure for a continuing investigationof foreign divestment activity.

ACKNOWLEDGEMENTS

The authors would like to thank Brayden King,Vit Henisz, Jesper Sørensen, and John Meyer forcomments on an earlier draft of this paper and PaulIngram for providing the IGO network data usedin the study.

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APPENDIX A FIRMS OPERATING IN BURMA 1996–2002

Home country Number of firms with Burma FDI Number of divestments

Australia 6 2Austria 1 0Bangladesh 1 0Belgium 2 0Brunei 1 0Canada 16 8China 6 1Denmark 3 1Finland 1 0France 21 1Germany 33 4Hong Kong 12 2India 3 1Indonesia 4 0Ireland 1 1Israel 1 0



Appendix A. (Continued)

Home country Number of firms with Burma FDI Number of divestments

Italy 7 2Japan 60 10Laos 1 1Malaysia 18 1Netherlands 12 6Pakistan 1 0Philippines 1 0Singapore 33 5South Africa 2 1South Korea 9 2Sweden 4 2Switzerland 9 1Taiwan 2 0Thailand 23 4United Kingdom 27 10United States 128 69Total 449 135

Source: Investor Responsibility Research Center (IRRC) 1996–2002.

APPENDIX B VARIABLES INCLUDED IN PAPER.

Variables Data sources Coverage

Divestment from Burma Investor Responsibility ResearchCenter (IRRC) publications

Quarterly data on 449firms, 1996–2002

Foreign Direct Investment IRRC publications 1996–2002 (firm)Firm’s total sales Compustat, Compact Disclosure,

Thomson One Banker1996–2002 (firm)

Firm’s performance Compustat, Compact Disclosure,Thomson One Banker

1996–2002 (firm)

Firm’s level ofinternationalization

Compustat, Thomson One Banker,proxy statements

1996–2002 (firm)

Industry Compustat, Compact Disclosure,Thomson One Banker

1996–2002 (industry)

Political freedom in country Freedom House 1996–2002 (country)Protest in country www.ibiblio.org 1996–2002 (country)Transparency International Index Transparency International 1996–2002 (country)Country’s mean number of ties

to others via IGOsIngram, Robinson, and Busch (2005);

Pevehouse, Nordstrom, and Warnke(2003)

1996–2002 (country)

Trade with Burma The Correlates of War Project TradeDataset (Barbieri and Keshk, 2012;Barbieri, Keshk, and Pollins, 2009)Worldbank, UNCTAD

1996–2002 (country)

Diplomatic relations with Burma The Correlates of War DiplomaticExchange Dataset (Bayer, 2006)

1996–2002 (country)

Country investment in Burma ASEAN, Worldbank, UNCTAD 1996–2002 (country)


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