Management International Review

, Volume 53, Issue 4, pp 555–577 | Cite as

Dual-Option Subsidiaries and Exit Decisions During Times of Economic Crisis

  • Chris Changwha Chung
  • Seung-Hyun Lee
  • Jeoung-Yul Lee
Research Article

Abstract

  • This study examines the dual implications of dual-option subsidiaries on exit decisions during times of economic crisis. Retaining dual-option subsidiaries in crisis-stricken countries means leaving a shadow option open for future growth once a crisis ends. However, MNCs may encounter problems pursuing either option due to challenges in managing dual-option subsidiaries with clashing strategic mandates.

  • The equivocal nature of dual-option subsidiaries points to the possibility of another factor playing an important moderating role in exit decisions—subsidiary performance—which has been rarely considered in the MNC real options literature. Our primary argument is that lower subsidiary performance increases the influence of shadow option value embedded in dual-option subsidiaries.

  • Analyzing a sample of 703 Korean overseas manufacturing subsidiaries in Asian countries, we find that when profitability falls, subsidiaries with dual options are less likely to be exited than those with single options.

Keywords

Within-country growthAcross-country flexibilityDual optionsSubsidiary exitEconomic crisis 

Introduction

Real options theory explains two different types of foreign direct investment (Belderbos and Zou 2009; Kogut and Kulatilaka 1994a). According to a within-country growth option perspective, multinational corporations (MNCs) use foreign subsidiaries to test host country potential and create growth options (Brouthers and Dikova 2010; Fisch 2011; Kogut 1991; Kulatilaka and Perotti 1998; Li and Li 2010; Tong et al. 2008; Xu et al. 2010). According to an across-country flexibility option perspective, MNCs can enhance operational flexibility by shifting value chain activities across multinational networks in response to changing conditions in individual countries (Allen and Pantzalis 1996; Chung et al. 2008; Fisch and Zschoche 2012; Driouchi and Bennett 2011; Lee and Makhija 2009a; Rangan 1998; Tang and Tikoo 1999). Most real options studies focus on either within-country growth-driven or across-country flexibility-driven subsidiaries, and therefore pay insufficient attention to subsidiaries embedded with both options; in this paper we will refer to these as dual-option subsidiaries. We argue that from the MNC top management standpoint, some MNC subsidiaries might not be seen as either within-country growth-driven or across-country flexibility-driven. Potentially a third kind, dual-option subsidiaries might be another type of subsidiary that MNC top management may have in mind in making decisions on the fate of each subsidiary.

The lack of attention to dual-option subsidiaries has resulted in a significant gap in the literature, since the majority of MNC-affiliated subsidiaries operating in two or more countries (including an MNC’s home country) have potential to take advantage of both within-country growth and across-country flexibility options (Belderbos and Zou 2007; Chung et al. 2010). For example, Chung et al. (2010) argue that MNC subsidiaries can have both within-country growth and across-country operational flexibility options, with the first based on a host country’s economic growth potential and the second emphasizing operational flexibility among affiliated subsidiaries within a multinational network.

In this paper we investigate the implications of dual-option subsidiaries for host country exit decisions. Most real options research has focused on investment initiation decisions (e.g., Brouthers and Dikova 2010; Cuypers and Martin 2010; Li and Li 2010; Tong and Li 2011). The question of whether firms use real options logic when considering reasons for salvaging an investment has received much less attention (Li et al. 2007). Exit decision research is important because many entry decisions can be characterized as mistakes (Vivarelli and Santarelli 2007), resulting in considerable weeding-out activity as firms abandon individual overseas investments (Bartelsman et al. 2005). According to Boddewyn (1979), one of every two foreign subsidiaries added to an MNC network is abandoned. Similar foreign entry-to-foreign exit ratios have been reported by Padmanabhan (1993) for UK MNCs; Barkema et al. (1996) for Dutch MNCs; and Benito (1997) for Norwegian MNCs.

Our study context—economic crisis—helps establish a boundary condition under which one option has greater value over another. During such periods, a dramatic downturn in a local economy can make a location unattractive for MNCs motivated to exploit within-county growth, while at the same time creating a low-cost manufacturing opportunity for MNCs capable of exploiting the operational flexibility embedded in their multinational networks (Chung et al. 2010; Lee and Song 2012). Exit decisions for dual-option subsidiaries are more complex due to their dual implications: Retaining such subsidiaries preserves options for future growth in local markets once a crisis period passes, therefore dual-option subsidiaries are less likely to be exited because of the value associated with a shadow within-country growth option. However, some MNCs find it difficult to pursue either option due to conflicts between the strategic mandates of dual-option subsidiaries. Such conflicts may increase the odds of exiting a dual-option subsidiary.

The equivocal nature of dual-option subsidiaries points to the possibility of another factor playing an important moderating role in exit decisions: Subsidiary performance. The international business literature clearly states that the most important reason for subsidiary exit is unsatisfactory performance (Benito 2005; Rugman 1979), yet subsidiary performance is rarely incorporated into MNC real options research. We therefore compare the likelihood of subsidiary exit changes as a function of performance level between dual- and single-option subsidiaries. A real options approach is most appropriate when other quantifiable benefits are negligible (O’Brien and Folta 2009; Tiwana et al. 2007). When subsidiary performance is strong, the option value of continuing in a host country is negligible because MNCs are unlikely to exit profitable subsidiaries. However, when subsidiary performance is weak and when easily quantifiable benefits of retention are absent, the option value of persistence should become more influential. In this paper we will describe our proposal that the shadow option value embedded in dual-option subsidiaries becomes more influential when subsidiary performance is weak. In other words, when profitability is low, dual-option subsidiaries are less likely to be exited than those pursuing a single option.

Theory and Hypothesis Development

Much of past real options research has focused on MNC flexibility at the corporate level, therefore insufficient attention has been paid to individual subsidiaries compared to aggregate subsidiary operations. Real options researchers have tended to assume that MNC subsidiaries are more or less equal because they belong to the same parent firm, and have therefore treated them as if their individual real options orientations do not affect MNC flexibility (Allen and Pantzalis 1996; Tang and Tikoo 1999). It is only recent that real options researchers have started examining the role of each subsidiary in its contribution to the MNC flexibility (Fisch and Zschoche 2012; Lee and Song 2012). For example, Fisch and Zschoche (2012) examine the impact of MNC subsidiaries’ country uncertainties on new subsidiary establishment. Lee and Song (2012) examine an interrelationship among MNC subsidiaries in such way that production increase in a particular subsidiary would be associated with production decrease in another. While these studies look into the role of each MNC subsidiary in the whole MNC subsidiary network, still these studies do not look into the real options orientation of each MNC subsidiary.

Each subsidiary’s real options orientation is based on its path-dependent strategic assignment (Kogut and Kulatilaka 1994b; Rangan 1998). MNCs interested in penetrating host country markets make subsidiary localization their priority in order to establish better fits with market preferences (Monteiro et al. 2008; Ozsomer and Gencturk 2003; Roth and Morrison 1990). In comparison, compatibility with other subsidiaries is a priority for MNCs interested in improving coordination within their global production networks (Allen and Pantzalis 1996; Chung et al. 2013; Kogut and Kulatilaka 1994a; Tang and Tikoo 1999). While this strategy might be viewed as cumbersome during normal times (Chung et al. 2008), it can provide significant benefits when a local market collapses. However, among subsidiaries established for within-country growth purposes, host market difficulties increase the odds of being exited (Benito and Welch 1997; Borde et al. 1998; Kogut 1991).

Real options theory is based on the idea that in times of uncertainty, opportunities to wait before making an irreversible decision have value; traditional net present value criteria fail to consider this flexibility benefit (Dixit 1992; Fisch 2011; Li and Li 2010). For an MNC that has established a subsidiary in a host country, uncertainty and sunk costs may give rise to an option value embedded in a delayed decision to exit (Dixit 1989; Chung and Beamish 2005a). If an MNC can delay its exiting decision so as to determine if the benefits of exiting cover the sunk costs of the investment, then the ability to wait has value (Pindyck 1991). The usual subsidiary exit decision threshold therefore increases beyond conventional net present value (Dixit and Pindyck 1994). If the benefit of abandoning a subsidiary exceeds this higher threshold, the subsidiary exit option is immediately exercised; otherwise the MNC is more likely to stay in a local market longer than expected under traditional net present value criteria. Under real options logic, an MNC will be reluctant to exit a local market in an uncertain environment due to the irreversible loss of any possibility to recoup its investment should local conditions improve.

A shadow option is a latent option that remains after an initial option is exercised (Bowman and Hurry 1993; Myers 1984). Dual-option subsidiaries are less likely than across-country flexibility-driven subsidiaries to be abandoned, since maintaining such subsidiaries means retaining a shadow option for growth after a crisis period is over. Thus, a dual-option subsidiary may exercise its across-country flexibility option during an economic crisis, but return to a within-country growth emphasis when the host country recovers. Another way to state this is that for dual-option subsidiaries, an across-country option provides preferential access to future within-country option opportunities (Bowman and Hurry 1993). Erikson (2002) and Hurry et al. (1992) argue that exercising the first option should be regarded as the purchase of a shadow option. For example, exercising an across-country operational flexibility option gives an MNC with dual-option subsidiaries the right, but not the obligation, to exercise the shadow within-country growth option once uncertainty is resolved. Based on this rationale, our first hypothesis is expressed as:

Hypothesis 1a

During times of economic crisis, subsidiaries with dual options are least likely to be exited, followed by subsidiaries with either across-country flexibility or within-country growth options, in that order.

However, real options research reminds us that flexibility has costs (Bowman and Moskowitz 2001; Chung et al. 2013; Driouchi and Bennett 2011; Kogut 1989) and that MNC subsidiaries retaining dual options may not be able to exercise either one. For example, an MNC subsidiary that tries to simultaneously satisfy local preferences and coordinate production with subsidiaries in other countries may not achieve maximum results in either situation. In addition, while divesting a subsidiary during an economic crisis may be a viable option from a real options perspective (McGrath 1999; Lee et al. 2007), the presence of a shadow option may influence MNCs to wrongly maintain subsidiaries with very uncertain futures (Adner and Levinthal 2004). As Kogut (1989, p. 388) observes, “having the potential to exercise flexibility is a far cry from having the management system to do it.” Poor organizational design and incorrect behavioral considerations can present problems for MNCs that have dual options (Barnett 2008; Busby and Pitt 1997; Driouchi and Bennett 2011)—for instance, they may be stuck at an in-between point, unable to successfully exercise either one (Dess and Davis 1984). In some situations, the value of combined options can be lower than when each option is pursued independently (Vassolo et al. 2004).

Furthermore, due to localization pressure, the possibility exists of dual-option subsidiaries developing strategies that are very different from those used by across-country option subsidiaries. Rangan (1998), Reuer and Leiblein (2000), Driouchi and Bennett (2011) perceive the potential lack of compatibility among MNC network subsidiaries and residual differences in administrative styles as reasons why MNCs are less operationally flexible than they should be. In a similar vein, Collis (1991, p. 53) argues that “administrative heritage will lead firms to maintain production configurations that do not optimize production costs.” In addition, if conflicting purposes associated with dual options result in substantially higher costs, then the value of keeping dual option subsidiaries falls. This explains Rangan’s (1998) argument that real options flexibility investments must be analyzed in terms of opportunity costs. When those opportunity costs reach a certain level, it is best to divest dual-option subsidiaries during times of economic crisis.

These factors explain why dual-option subsidiaries are more likely to be exited than those limited to the across-country option. However, dual-option subsidiaries are still less likely to be exited than subsidiaries limited to the within-country growth option because they can extract some operational flexibility benefits via global production networks when local markets collapse. A competing hypothesis to H1a is therefore proposed as:

Hypothesis 1b

During times of economic crisis, across-country flexibility-driven subsidiaries are least likely to be exited, followed by dual-option subsidiaries and within-country growth-driven subsidiaries, in that order.

The equivocal nature of dual-option subsidiaries points to the possibility of another factor playing a moderating role in exit decisions. According to the international business literature, the most basic reason for exiting a subsidiary in a host country is unsatisfactory performance (Benito 2005; Rugman 1979). However, performance has rarely been considered in the MNC real options literature. We argue that unsatisfactory performance increases the likelihood of within-country growth-driven subsidiaries being exited compared to across-country flexibility-driven or dual-option subsidiaries. Within-country growth-driven subsidiaries are in the worst position because they cannot flexibly use resources from other subsidiaries in their MNC networks (Birkinshaw et al. 2000). Poor local market demand can exacerbate existing performance problems for within-country growth-driven subsidiaries, thus increasing the potential for divestiture. In contrast, during times of economic crisis, across-country flexibility-driven subsidiaries and dual-option subsidiaries are better positioned to show their value in terms of exchange rate depreciation, lower factor costs, and other favorable trade conditions (Chung et al. 2010; Jacque and Vaaler 2001).

Comparing poorly performing dual-option and across-country flexibility-driven subsidiaries, we propose that dual-option subsidiaries are less likely to be exited. According to the real options literature, an options approach is most salient when other quantifiable benefits are negligible (Tiwana et al. 2007). When subsidiary performance is high, the option value of persisting in a host country becomes immaterial, since it is highly unlikely that an MNC will shut down a profitable subsidiary. However, when performance is low and the benefits of keeping a subsidiary are difficult to quantify, the option value of persistence becomes much more influential (O’Brien and Folta 2009).

The value of a subsidiary is the sum of the value of current assets, the value of current discounted expected future cash flows, plus the option value (Fisch 2011; Myers 1984). If the expected cash flows are large, then the real option value will not affect the decision to exit, as the expected cash flows are sufficient to keep the subsidiary alive. However, if cash flows are small or negative, real option value may just tip the balance between exit and survival. Despite performance problems, dual-option subsidiaries still have a latent shadow (within-country growth) option (Bowman and Hurry 1993), an advantage that provides incentives to retain subsidiaries with dual options during times of economic crisis. Poorly performing across-country flexibility-driven subsidiaries do not have this advantage. We therefore propose that the lower the subsidiary performance, the greater the influence of shadow option value embedded in dual-option subsidiaries, making them less likely than across-country flexibility-driven subsidiaries to be exited:

Hypothesis 2

Among poorly performing subsidiaries, those with dual options are less likely to be exited than those with a single option—specifically, across-country flexibility-driven and within-country growth-driven subsidiaries, in that order.

Methodology

Data and Sample

We used multiple data sources to collect information about MNCs and their foreign subsidiaries. Three primary sources for foreign subsidiary data were the Korean Ministry of Strategy and Finance (KMSF) database, WISEfn (a database of publicly traded Korean firms), and the Korea Listed Companies Association. In addition, we gathered further information on foreign subsidiaries from each MNC’s homepage, LEXIS/NEXIS, company information in the Munwha Daily Newspaper, and the Korea Information Service (KIS) website.In light of our setting—the 1997 Asian economic crisis—we narrowed our sample to Korean MNCs’ subsidiaries in Asia. We selected the 1997–2001 observation period for two reasons. First, the crisis started in 1997, and its effects were felt for several years (UNCTAD 2000). Second, MNCs are generally conservative in their exit decisions due to the difficulties of re-entry (Chung and Beamish 2005a). We therefore wanted to observe a sufficiently long time period to capture the true impacts of the crisis on exit decisions, and to prevent a potentially serious right-censoring problem. We also recognized that foreign subsidiaries in manufacturing, service, and trade industries may not perform the same way during times of economic crisis. To reduce confounding potential across different industry types, we followed the well-established real options practice of focusing on manufacturing subsidiaries (Allen and Pantzalis 1996; Belderbos and Sleuwaegen 2005).

After compiling a sample of Korean overseas manufacturing subsidiaries, we matched parent firm data with WISEfn, KIS- (Korea Information Service) Value, and the Korea Listed Companies Association. We then matched host country information from the World Development Indicator of the World Bank Group to the compiled data. The final sample consisted of 703 manufacturing subsidiaries of 479 Korean MNCs operating in 14 Asian countries. After testing Hypotheses 1a and 1b based on the full sample, we split the full sample into two sub-samples to compare the exit likelihood of poorly-performing subsidiaries with that of well-performing subsidiaries (i.e., Hypothesis 2). Based on the cut-off criterion of break-even, we split the full sample into a sample of high return on assets (ROA) group (369 subsidiaries) and a sample of low ROA group (334 subsidiaries).

Variables

Dependent Variable

We operationalized subsidiary exit (Dxt) as the withdrawal of a subsidiary from a host country (Benito 1997, 2005; Li 1995; Torneden 1975), taking a value of 1 if subsidiary x was exited at time t and 0 otherwise. Observations were either continued until the subsidiary was exited, or right-censored at the end of 2001 if Dxt = 0 for subsidiary x throughout the time period. During the observation period, 305 (10 %) of the subsidiaries in our full sample were exited, 146 (9 %) of the subsidiaries in a split sample of high ROA group were exited, and 159 (11 %) of the subsidiaries in a split sample of low ROA group were exited.

Independent Variables

We operationalized across-country flexibility-driven subsidiaries, within-country growth-driven subsidiaries and dual-option subsidiaries based on the percentage of across-country (versus within-country) intra- and inter-firm sales. On one dimension, a foreign subsidiary may have sales to its affiliates in the home, host, and third countries (i.e., intra-firm sales) and unrelated companies in the home, host, and third countries (i.e., inter-firm sales) (Lee and Song 2012). On the other dimension, a subsidiary may have sales to its affiliates and unrelated companies within the host country (i.e., within-country sales) and those outside the host country (i.e., across-country sales). Given the focus of the present paper, our operationalization is based on the dimension of across-country versus within-country sales rather than that of intra-firm versus inter-firm sales. An across-country flexibility-driven subsidiary can have some within-country sales in the host country. A within-country growth-driven subsidiary can also have some across-country sales outside the host country. As such, we do not arbitrarily categorize different types of subsidiaries based on categorical dummy variables but instead locate them in the continuous spectrum based on the percentage of across-country (versus within-country) intra- and inter-firm sales. On the continuous spectrum, within-country growth-driven, dual-options, and across-country flexibility-driven subsidiaries can be located in a meaningful order as shown in Fig. 1a.

Fig. 1

The predicted shape of relationship between the percentage of across-country (versus within-country) intra- and inter-firm sales and exit likelihood

The purpose of the present paper is not to measure exact percentage cut-off points between the three different types of subsidiaries but to compare the exit likelihoods of different subsidiaries whose across-country (versus within-country) sales percentages vary in a meaningful order on the continuous spectrum. Given the purpose of the paper, what is really important is the shape of the relationship between the percentage of across-country (versus within-country) intra- and inter-firm sales and exit likelihood. Depending on the shape of the relationship, we can test the competing hypotheses proposed in the paper (i.e., Hypotheses 1a and 1b). H1a proposes that subsidiaries with dual options are least likely to be exited, followed by across-country flexibility-driven subsidiaries and within-country growth-driven subsidiaries, in that order. In this case, we test a curvilinear (more specifically, right-tilted U-shaped) relationship between the percentage of across-country (versus within-country) sales and exit likelihood as shown in Fig. 1b. On the left side of the figure, within-country growth-driven subsidiaries whose across-country sales are less than the other two types are most likely to be exited. In the middle, as across-country sales increase, dual-option subsidiaries are less likely to be exited than within-country ones but still more likely to be exited than across-country ones. On the right side of the figure, across-country flexibility-driven subsidiaries are more likely to be exited than dual-option subsidiaries but still less likely to be exited than within-country growth-driven subsidiaries. As such, the exit likelihoods of across-country flexibility-driven subsidiaries stay below those of within-country growth-driven subsidiaries.

On the other hand, H1b proposes that across-country flexibility-driven subsidiaries are least likely to be exited, followed by dual-option subsidiaries and within-country growth-driven subsidiaries, in that order. In this case, we propose a linear and negative-slope relationship between the percentage of across-country (versus within-country) sales and exit likelihood as shown in Fig. 1c. In the left side of the figure, within-country growth-driven subsidiaries whose across-country sales are less than the other two types are most likely to be exited. In the right side of the figure, across-country flexibility-driven subsidiaries whose across-country sales are more than the other two types are least likely to be exited. In the middle, dual-option subsidiaries whose across-country sales are in-between are less likely to be exited than within-country ones but more likely to be exited than across-country ones.

As shown by the competing hypotheses, dual-option subsidiaries have dual implications for exit decisions. The equivocal nature of dual-option subsidiaries points to the possibility that subsidiary performance may be a critical factor influencing exit decisions. As such, we investigated change in exit likelihood between dual- and single-option subsidiaries with the split samples based on the financial performance level of the subsidiary. We used each subsidiary’s return on assets (ROA) to measure the financial performance of the subsidiary, and split the full sample based on the cut-off criterion of break-even (i.e., 0 %).

Control Variables

We controlled for a set of factors that are also expected to influence subsidiary exit. First, we controlled for country-level variables. Using the World Bank data, we incorporated the direct effect of economic crises by including change in gross domestic product (GDP) in host countries. We also incorporated the economic condition of home country. To reflect economic conditions in Korea, we measured the extent of GDP decline/growth. Further, we controlled for annual per capita GDP for both host and home countries. We controlled for the cultural distance between Korea and each host country based on Kogut and Singh’s (1988) index. We controlled for the political stability/risk of each host country using the BERI (Business Environment Risk Intelligence) political risk index—a higher score means less political problems. Various manufacturing industries were controlled for using the Korean equivalent of a two-digit Standard Industry Classification code. Eighteen manufacturing industries were controlled for.

At the MNC level, we controlled for the financial conditions of parent firms using their debt-to-equity ratio levels. Also, intangible assets have traditionally been viewed as influencing the international activity patterns of parent firms. We controlled for the effects of intangible assets by using measures of advertising intensity (advertising expenditures as a percentage of total sales) and R&D intensity (R&D expenditures as a percentage of total sales). We also controlled for MNC size, which was measured as the log of total assets of the MNC. Further, we controlled for the international experience (in years) of the MNC.

Alternative explanations at the subsidiary level were also controlled for. There may be an alternative possibility that subsidiaries may dramatically alter their within-country and across-country trade activities to deal with an economic crisis. According to the real options literature, real options are developed through a path-dependent process since current options derive from the previous strategic choices made and the corresponding subsidiary development path (Rangan 1998). In other words, the strategic orientation behind subsidiary operation has a sticky implication for the option development of the subsidiary (Kogut and Kulatilaka 1994b). Because of cost issues such as a high cost of switching from within-country to across-country orientations, subsidiaries do not generally change their within-country/across-country trade activities “dramatically” (Rangan 1998). Nevertheless, to preempt any potential room of this alternative explanation, we controlled for change in the across-country (versus within-country) intra- and inter-firm sales of subsidiaries.

We also incorporated a subsidiary’s ROA because subsidiary performance was a crucial determinant for divestment decisions (Benito 2005). Further, we made attempts to capture the effect of subsidiary size to control for liabilities of smallness or structural inertia. Subsidiary size was measured in terms of the total assets of a subsidiary. We controlled for the effects of human resource strategies by incorporating the ratio of Korean expatriates working at a subsidiary (i.e., expatriates as a percentage of total number of subsidiary employees). Finally included was a dummy variable indicating whether a subsidiary in a crisis-stricken country was wholly owned or part of a joint venture (Chung and Beamish 2005b).

Statistical Analysis

Since the majority of subsidiaries were not exited by the end of the observation period, utilizing right-censored cases was considered essential to our research (Allison 1984; Efron 1974). We therefore used semi-parametric event history models to investigate subsidiary exit hazards. Since the hazard distribution function for subsidiary exit during a period of economic crisis is a priori unknown, we fitted a Cox semi-parametric model that was not based on an a priori assumption regarding the nature or shape of the hazard function (Cox 1972; Cox and Oakes 1984).

Correlations across exit decisions were likely, given that a parent firm often had multiple foreign subsidiaries. To adjust for this problem, we used Huber and White estimators in the semi-parametric event history models when estimating variance in the random contributions of unobserved factors (Therneau and Grambsch 2000).

Results

Summary statistics and correlation matrices for the variables are presented in Table 1 (full sample), Table 2 (a split sample of high ROA subsidiaries) and Table 3 (a split sample of low ROA subsidiaries). Pearson statistics were calculated for correlations between two continuous variables, biserial statistics were calculated for correlations between a dichotomous and continuous variable, and tetrachoric statistics for correlations between two dichotomous variables. Results from variance inflation factor and tolerance level tests confirmed the absence of multicollinearity.

Table 1

Means, standard deviations, and correlations for full sample

 

Variables

Mean

S.D.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

1.

Subsidiary exit

0.10

0.31

1.00

                 

2.

Home country GDP growth

3.93

6.47

− 0.01

1.00

                

3.

Home country GDP per capita

10,738.97

781.05

− 0.06

− 0.04

1.00

               

4.

Host country GDP growth

4.07

4.48

− 0.13

− 0.07

0.32

1.00

              

5.

Host country GDP per capita

6,389.04

11,204.93

− 0.15

0.02

− 0.03

0.48

1.00

             

6.

Cultural distance

1.97

0.91

0.11

0.03

− 0.09

− 0.44

− 0.40

1.00

            

7.

Political risk/stability

56.07

8.53

− 0.08

0.00

− 0.03

− 0.2

0.34

0.37

1.00

           

8.

Advertising intensity

1.80

5.47

− 0.01

− 0.01

− 0.03

− 0.06

0.05

0.05

0.09

1.00

          

9.

R&D intensity

1.99

5.69

− 0.01

− 0.01

− 0.03

− 0.04

0.06

0.04

0.07

0.18

1.00

         

10.

Parent size

22.59

0.68

− 0.03

− 0.05

0.22

0.05

0.02

− 0.06

0.05

0.12

0.11

1.00

        

11.

Parent debt-to-equity ratio

− 17.18

88.40

0.01

0.02

0.01

− 0.02

0.02

0.00

0.00

0.00

0.00

0.00

1.00

       

12.

International experience

7.53

2.60

− 0.02

− 0.02

0.37

0.33

0.19

− 0.04

− 0.09

0.00

0.00

0.08

0.01

1.00

      

13.

Subsidiary size

16.64

2.43

− 0.25

0.09

− 0.01

− 0.23

0.16

0.04

0.02

0.03

0.06

0.10

0.02

0.19

1.00

     

14.

Expatriate ratio

0.14

0.25

− 0.12

0.07

− 0.11

− 0.26

0.30

0.27

0.22

0.01

0.00

0.00

− 0.04

0.02

− 0.07

1.00

    

15.

Entry mode: WOS (1) vs. JV (0)

0.76

0.43

− 0.02

0.03

0.07

− 0.09

0.15

0.12

0.13

− 0.01

− 0.01

0.04

− 0.01

0.08

− 0.03

0.11

1.00

   

16.

Subsidiary ROA

− 6.57

53.99

− 0.39

0.00

0.04

0.09

− 0.11

− 0.07

− 0.06

0.00

0.00

0.02

− 0.07

0.01

0.20

− 0.08

− 0.05

1.00

  

17.

Change in across-country (versus within-country) intra- and inter-firm sales

10.77

10.36

− 0.03

− 0.04

0.18

− 0.08

0.07

− 0.01

− 0.03

0.28

0.16

0.27

− 0.00

0.21

0.13

0.03

0.05

0.00

1.00

 

18.

Percentage of across-country (versus within-

country) intra- and inter-firm sales

38.72

42.40

− 0.07

0.02

0.02

0.12

− 0.17

− 0.14

− 0.07

0.01

0.01

− 0.07

− 0.00

0.03

0.06

− 0.04

0.10

0.04

0.06

1.00

Correlations with an absolute value greater than 0.045 are significant at the 0.05 level

Correlations with industry fixed effects are not shown

Table 2

Means, standard deviations, and correlations for high ROA group

 

Variables

Mean

S.D.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

1.

Subsidiary exit

0.09

0.30

1.00

                 

2.

Home coutnry GDP growth

3.97

6.52

− 0.01

1.00

                

3.

Home country GDP per capita

10,856.92

794.28

− 0.06

− 0.05

1.00

               

4.

Host country GDP growth

4.15

4.57

− 0.03

− 0.07

0.28

1.00

              

5.

Host country GDP per capita

6,514.72

11,360.45

− 0.04

0.01

0.02

0.46

1.00

             

6.

Cultural distance

1.95

0.90

0.02

0.00

− 0.05

− 0.43

− 0.40

1.00

            

7.

Political risk/stability

55.72

8.73

− 0.00

− 0.03

0.04

− 0.14

0.33

0.37

1.00

           

8.

Advertising intensity

1.97

7.59

− 0.02

− 0.01

− 0.01

− 0.05

0.06

0.05

0.11

1.00

          

9.

R&D intensity

2.19

7.89

− 0.02

− 0.01

− 0.01

− 0.03

0.07

0.04

0.09

0.19

1.00

         

10.

Parent size

22.64

0.65

− 0.06

− 0.06

0.23

0.04

0.05

− 0.07

0.10

0.11

1.10

1.00

        

11.

Parent debt-to- equity ratio

− 233.53

121.19

0.01

0.03

0.01

− 0.02

0.02

0.01

0.00

− 0.00

− 0.01

− 0.00

1.00

       

12.

International experience

7.66

2.59

− 0.05

− 0.01

0.37

0.37

0.23

0.01

− 0.06

0.01

0.01

0.14

0.02

1.00

      

13.

Subsidiary size

17.22

2.24

− 0.33

0.09

− 0.06

− 0.23

0.16

0.04

0.03

0.03

0.06

0.12

0.02

0.16

1.00

     

14.

Expatriate ratio

0.13

0.24

− 0.09

0.08

− 0.07

− 0.26

0.32

0.28

0.24

0.00

0.00

− 0.00

− 0.05

0.06

− 0.07

1.00

    

15.

Entry mode: WOS (1) vs. JV (0)

0.74

0.44

− 0.05

0.02

0.07

− 0.07

0.16

0.13

0.15

− 0.01

− 0.02

0.05

− 0.01

0.07

− 0.05

0.15

1.00

   

16.

Subsidiary ROA

6.21

30.18

− 0.26

− 0.03

0.01

− 0.03

0.03

0.03

0.01

− 0.02

− 0.00

− 0.00

− 0.18

0.02

0.12

0.02

− 0.09

1.00

  

17.

Change in across-country (versus within-

country) intra- and inter-firm sales

11.38

11.17

− 0.05

− 0.01

0.16

− 0.13

0.12

0.00

0.01

0.40

0.13

0.29

− 0.00

0.27

0.18

0.04

0.05

− 0.01

1.00

 

18.

Percentage of across- country (versus within- 

country) intra-  and inter- firm sales

38.30

41.92

− 0.03

0.04

0.01

0.08

− 0.14

− 0.13

− 0.08

0.02

0.02

− 0.07

0.03

0.05

0.10

− 0.02

0.07

0.02

0.06

1.00

Correlations with an absolute value greater than 0.045 are significant at the 0.05 level

Correlations with industry fixed effects are not shown

Table 3

Means, standard deviations, and correlations for low ROA group

 

Variables

Mean

S.D.

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

1.

Subsidiary exit

0.11

0.31

1.00

                 

2.

Home coutnry GDP growth

3.90

6.38

− 0.01

1.00

                

3.

Home country GDP per capita

10,624.63

778.21

− 0.06

− 0.04

1.00

               

4.

Host country GDP growth

3.99

4.41

− 0.23

− 0.07

0.34

1.00

              

5.

Host country GDP per capita

6,259.24

11,078.69

− 0.26

0.03

− 0.08

0.49

1.00

             

6.

Cultural distance

2.00

0.91

0.20

0.05

− 0.12

− 0.43

− 0.42

1.00

            

7.

Political risk/stability

56.42

8.30

− 0.16

0.03

− 0.10

− 0.14

0.35

0.37

1.00

           

8.

Advertising intensity

1.63

1.46

− 0.05

− 0.00

− 0.19

− 0.05

0.12

0.11

0.09

1.00

          

9.

R&D intensity

1.81

1.52

− 0.05

− 0.00

− 0.18

− 0.03

0.13

0.09

0.07

0.17

1.00

         

10.

Parent size

22.55

0.71

− 0.00

− 0.04

0.21

0.04

0.01

− 0.05

0.00

0.36

0.32

1.00

        

11.

Parent debt-to-equity ratio

199.62

30.36

0.03

− 0.02

0.00

− 0.02

0.01

-0.02

0.01

0.11

0.11

0.02

1.00

       

12.

International experience

7.39

2.61

− 0.02

− 0.03

0.36

0.37

0.15

− 0.08

− 0.12

− 0.01

− 0.02

0.01

0.01

1.00

      

13.

Subsidiary size

16.02

2.48

− 0.19

0.09

− 0.00

− 0.03

0.18

0.05

0.02

0.08

0.10

0.05

0.03

0.21

1.00

     

14.

Expatriate ratio

0.15

0.26

− 0.14

0.05

− 0.15

− 0.29

0.28

0.25

0.20

0.02

0.02

0.01

− 0.02

− 0.01

− 0.07

1.00

    

15.

Entry mode: WOS (1) vs. JV (0)

0.78

0.42

− 0.01

0.03

0.08

− 0.26

0.13

0.10

0.10

0.04

0.04

0.05

− 0.02

0.10

0.02

0.07

1.00

   

16.

Subsidiary ROA

− 19.36

65.79

− 0.44

0.02

0.03

0.15

− 0.18

− 0.12

-0.09

0.00

− 0.01

0.00

0.01

− 0.01

0.18

− 0.12

− 0.02

1.00

  

17.

Change in across-country (versus within-

country) intra- and inter-firm sales

10.14

9.43

− 0.00

− 0.06

0.19

− 0.04

0.03

− 0.02

− 0.08

0.18

0.29

0.25

0.02

0.15

0.07

0.02

0.05

− 0.01

1.00

 

18.

Percentage of across-country (versus within-

country) intra- and inter-firm sales

39.17

42.92

− 0.12

− 0.01

0.04

0.17

− 0.20

−0.15

− 0.07

− 0.05

− 0.06

− 0.06

− 0.02

0.00

0.03

− 0.05

0.13

0.06

0.07

1.00

Correlations with an absolute value greater than 0.045 are significant at the 0.05 level

Correlations with industry fixed effects are not shown

Empirical results for the full sample are shown in Table 4. In Model 1 we included control variables only. In Model 2, we introduced the linear term of across-country (versus within-country) intra- and inter-firm sales percentage in order to test the linear and negative-slope relationship between across-country sales percentage and exit likelihood proposed in H1b. In Model 3, we added the squared term of across-country (versus within-country) intra- and inter-firm sales percentage in order to test the curvilinear and U-shaped relationship between across-country sales percentage and exit likelihood proposed in H1a.

Table 4

Empirical results of Cox proportional hazard models for full sample

 

Full sample

Model 1

Model 2

Model 3

β

S.E.

β

S.E.

β

S.E.

Home coutnry GDP growth

− 0.101*

(0.045)

− 0.103*

(0.049)

− 0.113*

(0.049)

Home country GDP per capita

− 0.003***

(0.000)

− 0.003***

(0.000)

− 0.003***

(0.000)

Host country GDP growth

− 0.368***

(0.029)

− 0.366***

(0.030)

− 0.366***

(0.030)

Host country GDP per capita

− 0.0007***

(0.0001)

− 0.0007***

(0.0001)

− 0.0007***

(0.0001)

Cultural distance

0.277*

(0.130)

0.302*

(0.131)

0.303*

(0.131)

Political risk/stability

− 0.044***

(0.012)

− 0.043***

(0.012)

− 0.043***

(0.012)

Advertising intensity

− 0.101

(0.141)

− 0.107

(0.144)

− 0.112

(0.145)

R&D intensity

− 0.010

(0.024)

− 0.006***

(0.001)

0.0004***

(0.0001)

Parent size

− 0.500***

(0.116)

− 0.673***

(0.105)

− 0.673***

(0.105)

Parent debt-to-equity ratio

0.0005

(0.0004)

0.0005

(0.0004)

0.0004

(0.0004)

International experience

− 0.300***

(0.033)

− 0.298***

(0.033)

− 0.298***

(0.033)

Subsidiary size

− 0.256***

(0.022)

− 0.251***

(0.022)

− 0.249***

(0.023)

Expatriate ratio

− 0.599**

(0.192)

−0.612***

(0.192)

− 0.606**

(0.192)

Entry mode: WOS (1) vs. JV (0)

− 0.187

(0.147)

− 0.221

(0.148)

− 0.219

(0.148)

Change in across-country (versus within-country) intra- and inter-firm sales

− 0.006

(0.004)

− 0.006

(0.004)

− 0.006

(0.004)

Subsidiary ROA

− 0.004***

(0.0004)

− 0.004***

(0.0004)

− 0.004***

(0.0004)

Industry dummy

Included

 

Included

 

Included

 

Percentage of across-country (versus within-

country) intra- and inter-firm sales

  

− 0.002

(0.002)

− 0.007

(0.008)

Percentage of across-country (versus within-country) intra- and inter-firm sales2

    

0.00004

(0.0001)

Number of observations

3,082

3,082

3,082

Number of failures

305

305

305

Wald χ2

1,008.403***

1,013.336***

1,013.743***

p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001

In Model 2, the negative coefficient of the linear term of across-country sales percentage suggests that there may be a linear and negative-slope relationship between across-country sales percentage and exit likelihood, but the result is not statistically significant. Therefore, H1b is not supported. In Model 3 in which we added the squared term of across-country sales percentage, the negative coefficient of the linear term and the positive coefficient of the squared term indicate that there may be a curvilinear and U-shaped relationship between across-country sales percentage and exit likelihood, but the results are not statistically significant. Thus, H1a is not supported either. In the full sample, neither H1a nor H1b is supported.

The above inclusive results suggest that there may be another critical factor influencing the relationship between across-country sales percentage and exit likelihood. As such, we split the full sample into a sample of high ROA subsidiaries and that of low ROA subsidiaries, and then examined the relationship between across-country sales percentage and exit likelihood in each sample. Empirical results for the sample of high ROA subsidiaries are shown in the section A of Table 5. In Model 4 we included control variables only. In Model 5, we incorporated the linear term of across-country sales percentage to see if there is a linear and negative-slope relationship between across-country sales percentage and exit likelihood. In Model 6, we added the squared term of across-country sales percentage to see if there is a curvilinear and U-shaped relationship between across-country sales percentage and exit likelihood. Empirical results for the sample of low ROA subsidiaries are shown in the section B of Table 5. For Models 7–9 in the section B of Table 5, we followed the same procedure used in Models 4–6.

Table 5

Empirical results of Cox proportional hazard models for split samples

 

Section A: high ROA group

Section B: low ROA group

Model 4

Model 5

Model 6

Model 7

Model 8

Model 9

β

S.E.

β

S.E.

β

S.E.

β

S.E.

β

S.E.

β

S.E.

Home coutnry GDP growth

− 0.109

(0.066)

− 0.122

(0.071)

− 0.133

(0.071)

− 0.086

(0.063)

− 0.077

(0.067)

− 0.088

(0.067)

Home country GDP per capita

− 0.003***

(0.000)

− 0.003***

(0.000)

− 0.003***

(0.000)

− 0.003***

(0.000)

− 0.003***

(0.000)

− 0.003***

(0.000)

Host country GDP growth

− 0.245***

(0.058)

− 0.261***

(0.059)

− 0.261***

(0.060)

− 0.437***

(0.041)

− 0.433***

(0.041)

− 0.432***

(0.042)

Host country GDP per capita

− 0.0004*

(0.0002)

− 0.0005*

(0.0002)

− 0.0005*

(0.0002)

− 0.0008***

(0.0001)

− 0.0008***

(0.0001)

− 0.0008***

(0.0001)

Cultural distance

0.278

(0.215)

0.225

(0.216)

0.226

(0.216)

0.334†

(0.177)

0.399*

(0.182)

0.409*

(0.182)

Political risk/stability

− 0.012

(0.025)

− 0.018

(0.025)

− 0.018

(0.025)

− 0.087***

(0.017)

− 0.088***

(0.017)

− 0.086***

(0.017)

Advertising intensity

− 0.526*

(0.262)

− 0.604*

(0.259)

− 0.604*

(0.259)

− 0.205

(0.263)

− 0.234

(0.286)

− 0.214

(0.289)

R&D intensity

− 0.119†

(0.061)

− 0.003

(0.002)

− 0.0003**

(0.0001)

− 0.047

(0.038)

− 0.010***

(0.002)

− 0.0005***

(0.0001)

Parent size

− 0.455*

(0.201)

− 0.499**

(0.183)

− 0.496**

(0.184)

− 0.491**

(0.166)

− 0.384*

(0.159)

− 0.395*

(0.160)

Parent debt-to-equity ratio

0.0001

(0.0005)

0.0004

(0.0015)

0.0003

(0.0016)

0.0003

(0.0004)

0.0001

(0.0004)

0.0001

(0.0004)

International experience

− 0.271***

(0.076)

− 0.247***

(0.077)

− 0.247***

(0.077)

− 0.282***

(0.045)

− 0.275***

(0.045)

− 0.275***

(0.045)

Subsidiary size

− 0.081*

(0.038)

− 0.069†

(0.039)

− 0.068†

(0.039)

− 0.170***

(0.031)

− 0.160***

(0.031)

− 0.150***

(0.032)

Expatriate ratio

− 0.158

(0.332)

− 0.085

(0.331)

− 0.084

(0.331)

− 0.561*

(0.260)

− 0.610*

(0.261)

− 0.588*

(0.261)

Entry mode: WOS (1) vs. JV (0)

− 0.470*

(0.236)

− 0.586*

(0.245)

− 0.588*

(0.246)

− 0.293

(0.193)

− 0.243

(0.194)

− 0.261

(0.195)

Change in across-country (versus within-country) intra- and inter-firm sales

− 0.010

(0.008)

− 0.011

(0.008)

− 0.011

(0.008)

− 0.008

(0.005)

− 0.007

(0.005)

− 0.007

(0.005)

Subsidiary ROA

− 0.143***

(0.008)

− 0.145***

(0.009)

− 0.145***

(0.009)

− 0.004***

(0.0004)

− 0.004***

(0.0005)

− 0.004***

(0.0005)

Industry dummy

Included

 

Included

 

Included

 

Included

 

Included

 

Included

 

Percentage of across-country (versus within-

country) intra−  and inter-firm sales

  

− 0.005*

(0.002)

− 0.029**

(0.010)

  

− 0.011***

(0.002)

− 0.053***

(0.012)

Percentage of across-country (versus within-

country) intra- and inter-firm sales2

    

0.0001

(0.0001)

    

0.0005***

(0.0001)

Number of observations

1,619

1,619

1,619

1,463

1,463

1,463

Number of failures

146

146

146

159

159

159

Wald χ2

465.718***

465.819***

467.036***

586.725***

592.993***

595.680***

p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001

In Model 6 (a sample of high ROA subsidiaries), the negative linear term of across-country sales percentage is statically significant (β = − 0.029; p < 0.01) but the positive squared term of across-country sales percentage is not statistically significant (β = 0.0001; ns). On the other hand, in Model 9 (a sample of low ROA subsidiaries), both the negative linear term of across-country sales percentage (β = − 0.053; p < 0.001) and the positive squared term of across-country sales percentage (β = 0.0005; p < 0.001) are statically significant. These results indicate that a linear and negative-slope relationship between across-country sales percentage and exit likelihood is salient in the sample of high ROA subsidiaries, whereas a curvilinear and U-shaped relationship between across-country sales percentage and exit likelihood is salient in the sample of low ROA subsidiaries.

Based on the empirical results obtained, we illustrated the relationship between across-country sales percentage and exit likelihood for high ROA subsidiaries in Fig. 2. Figure 2 shows a linear and negative-slope relationship between across-country sales percentage and exit likelihood. In the left side of Fig. 2, within-country growth-driven subsidiaries whose across-country sales are less than the other two types are most likely to be exited. In the right side of Fig. 2, across-country flexibility-driven subsidiaries whose across-country sales are more than the other two types are least likely to be exited. In the middle of Fig. 2, dual-option subsidiaries whose across-country sales are in-between are less likely to be exited than within-country growth-driven subsidiaries but more likely to be exited than across-country flexibility-driven subsidiaries.

Fig. 2

High ROA subsidiaries: the actual shape of relationship between across-country sales percentage and hazard rate based on the empirical result of Cox hazard model

In Fig. 3, we illustrated the relationship between across-country sales percentage and exit likelihood for low ROA subsidiaries. Figure 3 shows a right-tilted U-shaped relationship between across-country sales percentage and exit likelihood. Starting from the left side of Fig. 3, within-country growth-driven subsidiaries whose across-country sales are less than the other two types are most likely to be exited. As across-country sales increase in the middle of Fig. 3, dual-option subsidiaries are less likely to be exited than within-country growth-driven subsidiaries but still more likely to be exited than across-country flexibility-driven subsidiaries. In the right side of Fig. 3, the right-tilted U-shaped relationship suggests that across-country flexibility-driven subsidiaries are more likely to be exited than dual-option subsidiaries but still less likely to be exited than within-country growth-driven subsidiaries. As such, the exit likelihood of across-country flexibility-driven subsidiaries stays below that of within-country growth-driven subsidiaries but still above that of dual-option subsidiaries.

Fig. 3

Low ROA subsidiaries: the actual shape of relationship between across-country sales percentage and hazard rate based on the empirical result of Cox hazard model

Results from a comparison of dual-option subsidiaries and across-country flexibility-driven subsidiaries indicate a greater exiting likelihood for dual-option subsidiaries when both types are profitable. However, when performance level decreases below break-even, dual-option subsidiaries are less likely to be exited than across-country flexibility-driven subsidiaries. Combined, these results support H2.

Discussion and Conclusion

Past real options studies have focused on either the within-country growth (Brouthers and Dikova 2010; Fisch 2011; Kogut 1991; Kulatilaka and Perotti 1998; Li and Li 2010; Tong et al. 2008; Xu et al. 2010) or across-country flexibility option perspective (Allen and Pantzalis 1996; Chung et al. 2008; Driouchi and Bennett 2011; Lee and Makhija 2009a, 2009b; Rangan 1998; Tang and Tikoo 1999), generally overlooking the dual implications of dual-option subsidiaries despite their significant presence in MNC networks. In this paper we examined the dual implications of dual-option subsidiaries on exit decisions during times of economic crisis. While it is easy to understand why within-country growth-driven subsidiaries are most likely to be divested when local markets collapse (Chung et al. 2010), it is difficult to predict what will happen in a scenario involving dual-option and across-country flexibility-driven subsidiaries. Maintaining dual-option subsidiaries in crisis-stricken countries means leaving a shadow option open for future growth after the crisis subsides (Bowman and Hurry 1993; Erikson 2002; Hurry et al. 1992; Myers 1984). However, due to challenges in managing conflicting interests in dual-option subsidiaries, MNCs may find it difficult to pursue either option (Barnett 2008; Busby and Pitt 1997; Driouchi and Bennett 2011; Reuer and Leiblein 2000). Accordingly, we failed to find any significant difference in exit likelihoods between dual-option and across-country flexibility-driven subsidiaries.

The inconclusive nature of our dual- and across-country option subsidiary findings suggests the involvement of another factor—subsidiary performance. While cited as one of the most important factors influencing subsidiary exit decisions in the international business literature (Rugman 1979), the moderating role of subsidiary performance is under-examined in the MNC real options literature. According to our results, across-country flexibility-driven subsidiaries were less likely to be exited than dual-option subsidiaries when both were profitable, suggesting that the cost-saving positions of across-country flexibility-driven subsidiaries were better aligned with the strategic requirements of MNCs during the crisis period. However, lack of profitability in across-country flexibility-driven subsidiaries did not necessarily put them in better positions compared to dual-option subsidiaries. Poorly performing dual-option subsidiaries are generally less likely than poorly-performing across-country flexibility-driven subsidiaries to be exited because they have greater value in terms of their within-country growth shadow option (Bowman and Hurry 1993; Erikson 2002).

Our finding that dual-option subsidiaries have greater option value than across-country flexibility-driven subsidiaries when a lack of profitability is involved suggests that the shadow option value of dual-option subsidiaries increases during times of uncertainty. When subsidiaries are profitable, there is less need to think about future potential value because current value already provides a strong incentive to maintain them. However, the fates of financially unsound subsidiaries may be decided by the presence of a shadow option (O’Brien and Folta 2009). Future option value gains prominence when other quantifiable benefits such as profitability are negligible (Tiwana et al. 2007). The value of a subsidiary is the sum of the value of current assets, the value of current discounted expected future cash flows, plus the option value (Chung et al. 2013; Fisch 2010). If the expected cash flows are large, then the real option value will not affect the decision to exit, as the expected cash flows are sufficient to keep the subsidiary alive. However, if cash flows are small or negative, real option value may just tip the balance between exit and survival (Bowman and Hurry 1993). That is, when performance is low and when easily quantifiable benefits of keeping a subsidiary in a host country evaporate, its future option value gains influence when deciding its fate. Keeping dual-option subsidiaries alive means having growth options in a local market once the crisis ends.

Regarding managerial implications, awareness of how past investment decisions and strategic orientations affect specific subsidiaries during crises can provide managers with a priori insight. Although operational flexibility is normally considered an adaptive and reactive response to environmental change, MNC subsidiaries may use their operational flexibility to proactively redefine market uncertainties. The real options perspective helps MNC managers battle with, capitalize on, and even befriend the uncertainty that is a constant factor in today’s global economy. During times of uncertainty, the fate of a subsidiary is determined by a mix of current and future options value. Therefore, making quick decisions to exit all subsidiaries experiencing financial trouble can have detrimental consequences. During times of uncertainty, exit decisions should be based on option valuation, including considerations of shadow option value.

It should be noted that keeping options open may not be a cure-all strategy. Especially when a subsidiary is in good standing in its performance, this logic of keeping latent shadow (within-country growth) option may not apply (Bowman and Hurry 1993). However, keeping future options open might be beneficial when a subsidiary is ailing from performance problems. This is why O’Brien and Folta (2009) and Tiwana et al. (2007) argue that considering potential future option value becomes more important when other quantifiable benefits such as profitability are negligible. In this sense, when it comes to the divestment decisions of MNC subsidiaries, managers may have to think of at least two things at the same time, subsidiary performance and keeping latent shadow option. Unless both of them are considered at the same time, mangers may make a blunder of mistakenly forgoing potential future gains by divesting all poorly performing subsidiaries.

Our findings are based on a sample of Korean MNCs’ overseas subsidiaries in Asia. As such, there might be an ‘Asian or Korean MNC’ effect since they are more likely to have a long-term view compared to their Western (American and European) counterparts. This may limit the generalizability of the findings of this study. However, this sample does provide a counterpoint to the dominant view in the literature based on Western multinational firms. For the development of MNC real options theory, such an alternative view point is valuable.

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Copyright information

© Springer Fachmedien Wiesbaden 2012

Authors and Affiliations

  • Chris Changwha Chung
    • 1
  • Seung-Hyun Lee
    • 2
  • Jeoung-Yul Lee
    • 3
  1. 1.Department of International Business, Korea University Business SchoolKorea UniversitySeoulKorea
  2. 2.Department of Organizations, Strategy and International Management, School of ManagementUniversity of Texas at DallasRichardsonUSA
  3. 3.Department of International Business, College of Business ManagementHongik UniversitySejongKorea

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