1
Business in conflict zones: Ethnic ties as
a driver for success
MSc International Business and Management, Semester 2A 2018 Master Thesis
Author:
Hendrik Ramke (S2727064); Email: h.ramke@student.rug.nl Supervisor:
Dr. S. Gubbi: Email: s.r.gubbi@rug.nl
Faculty of Economics and Business University of Groningen
Duisenberg Building, Nettelbosje 2, 9747 AE Groningen, Netherlands P.O. Box 800, 9700 AV Groningen, Netherlands
2 Abstract
3 Table of Content
1. Introduction 4
2. Literature Review 7
2.1 Business in intra- and interstate conflict 8
2.2 Subsidiary performance in conflict zones 10
2.3 Ethnic ties 12
2.4 Intra- and interstate conflicts and subsidiary performance 13
2.5 Moderating role of ethnic ties 13
2.6 Conceptual model 15
3. Methodology 16
3.1 Data collection 16
3.2 Sample 17
3.3 Variables and measurement 18
3.3.1 Dependent variable 18
3.3.2 Independent variables 19
3.3.3 Moderator ethnic ties 19
3.3.4 Control variables 19
3.3.5 Analysis 20
4. Empirical results 21
4.1 Assumptions of multiple regression analysis 21
4.1.1 Violation of assumptions 22
4.2 Multiple regression analysis 23
4.2.1 Hierarchical multiple regression 23
4.2.2 Moderation analysis 24
5. Conclusion 29
5.1 Discussion of results 29
5.2 Limitations and future research 31
5.3 Managerial implications 32
References 34
4 1. Introduction
The Heidelberg Institute for International Conflict Research (HIIK) recorded 385 violent and non-violent conflicts worldwide in 2017 making business in conflict zones a current topic that arouses more and more attention. Researchers commonly distinguish between intrastate conflicts and interstate conflicts (Banfield, Haufler, Lilly, 2015; Small, Singer, 1982; Regan, 1996; Pettersson, Wallensteen, 2015). Intrastate conflicts include civil wars as well as regional and intercommunal conflicts within the territory of a country (Dixon, Sarkees, 2015). This type of conflicts results in a strong fragmentation of the society into separate groups that shut themselves off based on ethnic and religious differences (Sambanis, 2004; Collier, Hoeffler, 2004; Gurr, 1994). Interstate conflicts are conflicts arising between two or more countries and rather lead to internal coherence and solidarity among the society. These conflicts root in territorial disputes or state rivalry and are fed by expansionist ambitions (Mousseau, 1998; Kocs, 1995; Hensel, 1998; Carment, 1993).
Recent waves of globalization, liberalization and privatization led to multinational companies (MNCs) significantly extending their proliferation across the globe. Thereby, developing areas are more extensively targeted in order to exploit presumed higher returns on investment and thus to strengthen a company’s global position. However, nowadays developing countries are increasingly affected by conflicts. Consequently, an increasing amount of foreign subsidiaries is exposed to host country intrastate and interstate conflicts. Research shows that conflict zones do significantly negatively affect subsidiary performance (Rettberg, 2004; Anderson et al., 2010; Abadie, Gardeazabal, 2003; Oh, Oetzel, 2011; Branzei, Abdelnour, 2010; Czinkota, Knight, Liesch, Steen, 2010). Thus, subsidiaries of foreign MNCs more often face severe challenges of maintaining efficiency, legitimacy and functioning operations affecting their performance in conflictual host countries (Jamali, Mirshak, 2009).
5 collaboration and continuous dialogue and consultation (Anderson et al., 2010; Gladwin, Walter, 1980; Bennett, 2001). This approach found that traditional ‘western’ business concepts do not properly work in conflict zones and are not appropriate to uncover the hidden potential of conflict zones. Driving on social identity theory, this thesis further refines this stream of literature by assuming that the applicability as well as success of extensive cooperation in conflict zones is dependent on the existence of ethnic ties between the foreign subsidiary and the society of the conflictual location. Thereby it is inferred that ethnic group belongingness in those locations is an important factor potentially prohibiting the needed high levels of interaction between foreign subsidiary and local actors due to ethnic incongruences. Consequently, in order to be economically viable in conflict zones, foreign subsidiaries appear to need the appropriate ‘ethnic equipment’ embodying similar general paradigms in order to assure access to key locals and effective interaction. It is argued that ethnic ties between the foreign subsidiary and the prevalent ethnic lines in the conflict zone positively moderate the negative relationship between intrastate conflicts and foreign subsidiary performance due to strong society fragmentation and the resulting in-group favoritism. This moderation effect is not expected to be present in locations dominated by interstate conflicts as the connected societies are rather united do not isolate themselves from each other. Ethnic ties thereby are defined as informal social or personal networks encompassing characteristics such as shared tongue, national origin, ethnic group or region of birth (Zaheer, Lamin, Subramani, 2009). Potential factors limiting the success of the strong coordination approach in conflict zones, such as ethnic ties, have been mostly neglected in recent IB research and thus are worth examining. The resulting research question is:
How do ethnic ties between the home and host location affect a foreign firm’s subsidiary’s performance in conflict zones?
6 emerging market firms as it yields important insights that can strengthen their ability to effectively perform in conflict zones in the future.
7 2. Literature Review
The literature dealing with business in conflict zones is rather fragmented and ambiguous. Most literature argues that companies operating in conflictual host countries, face substantial risk that negatively affects performance in those foreign areas. However, while some streams of literature classify these performance-reducing risks as insuperable, other studies propose specific risk-mitigating factors and strategies in order to overcome the resulting challenges and to be successful in conflict zones.
2.1 Business in intra- and interstate conflict zones
8 tensions among the population rather fragmenting the society than uniting it. However, assigning an ethnic label to all intrastate conflicts is not convenient and might misrepresent the actual situation in reality (Rupesinghe, 1987). Therefore, in order to capture intrastate conflicts, a more general definition of intrastate conflicts by Banfield, Haufler and Lilly (2005, p.17) is used. It describes intrastate conflict areas as those ‘countries that are in, emerging from, or at risk of violent conflict, being expressed either as civil wars or at more localized levels.’. Further, this thesis extends the definition as only countries plagued by armed intrastate conflicts resulting in at least 25 battle-related deaths are considered. This threshold might be less than those generally used but it is appropriate with regard to excluding minor coups, riots and demonstrations. Also, it ensures that the captured intrastate conflicts already reached a serious level of intensity so that the probability of further escalation is reasonably high (Small, Singer, 1982; Regan, 1996). For a matter of clarification, the severe fighting of the IS (Islamic State) against the regime and other rebel groups in Syria and the connected emergence of Syrian insurgents constitute strong forms of intrastate conflicts (Pettersson, Wallensteen, 2015).
9 disputes the threat or use of force, either militarized or not, is explicitly directed to harm the property or territory of a certain state (Jones, Bremer, Singer, 1996). The Iran-Iraq or Ethiopia-Eritrea wars depict extremely fatal examples of interstate conflicts (Lacina, Gleditsch, 2005). In this thesis, the definition of Pettersson and Wallensteen (2015) regarding interstate conflicts is applied. It classifies countries to be plagued by interstate conflicts if they are in armed conflict with one or more other countries. Again, this definition is enlarged as this paper only considers interstate conflicts that yield at least 25 battle-related deaths. As a consequence, non-crucial interstate disputes potentially distorting the results are excluded.
2.2 Subsidiary performance in conflict zones
There is an extensive number of distinct definitions referring to subsidiary performance in the existing literature. A lot of these definitions estimate performance on the basis of financial outcomes such as return on assets (ROA), return on equity (ROE), net income, sales or profits (Griffin, Mahon, 1997). Consequently, this thesis defines foreign subsidiary performance as the subsidiary’s financial profitability in the host country. It is commonly accepted that a foreign subsidiary’s performance is heavily dependent on its ability to effectively obtain resources from its environment (Lawrence, Lorsch, 1967; Pfeffer, Salancik, 1978). More precisely, an organization’s performance is determined by its ability to extract new knowledge from the environment through close inter-firm relationships (Powell, Kogut, Smith-Doerr, 1996). Embedded inter-organizational ties and the resulting lower uncertainty in close relationships improve inventory control and costs (Trevelen, 1987; Landeros, Monczka, 1989). Also, through close relationships, an environments’ resource heterogeneity becomes increasingly feasible which enhances the possibility of value creation through specific combinations of resources and activities. In that way, the range of opportunities gets widened (Hakansson, Snehota, 1995; Blankenburg Holm, Eriksson, Johanson, 1996).
10 economic instability makes business conduction extremely precarious. A lack of legal frameworks as well as an infrastructure that might be damaged or even purposefully vandalized make it inherently difficult to put in place legally enforceable contracts. Moreover, companies located in conflictual areas face a severe shortage of skilled people due to most employees being rather averse to endanger their safety in those locations. Additionally, various recent conflicts are bound to diffusing trends of economic stagnation, unequal wealth distributions or governmental corruption. The result is a highly dysfunctional economic environment impacted by weak institutions, corruption, poverty and income inequality, which facilitates further dispersal of violent conflicts such as wars, rebellions, revolutions or terrorism (Davies, 1996). These aspects, in turn, lead to foreign firms incurring additional costs when operating in conflictual areas, for instance extra security costs, higher insurance premiums or further costs of identifying alternative suppliers (Oh and Oetzel, 2017). In Colombia, as an illustration, companies are increasingly affected by violent conflicts since the early 1990s. Frequent kidnappings, blackmail and an extensive destruction of the infrastructure involving communication towers, utilities and roads led to massive disruptions. These disruptions in combination with exploding security costs drove companies in Colombia into serious threats of bankruptcy (Rettberg, 2004).
However, conflict zones might also be beneficial to foreign firms’ performance as they constitute environments that may be highly demanding but at the same time embody sparse foreign competition due to their complexity. Conflict zones are thus on the one hand highly challenging environments that might exacerbate or even prevent effective functioning of foreign subsidiaries. On the other hand, when attempted properly, they also bury valuable potential that can be
transformed into a competitive advantage which improves performance.
11 in conflict zones are urged to establish stable bonds with a variety of actors in order to compensate the dysfunctional conflictual environment (Oh and Oetzel, 2017). These studies identify the nature of a company’s business strategy as the main factor in order to mitigate the negative influence of conflicts on performance in conflict prone locations. Conflict zones are riddled with wars, either civil or cross-border, as well as with riots, well-marked outlawry and an absence of legal frameworks. Hence, the establishment of legally enforceable contracts can be highly challenging or even impracticable. Consequently, firms entering those areas need to blur their organizational boundaries and efficiently connect to locals to form trustworthy partnerships in order to compensate for insurgency. Various MNCs entering conflict zones act as an exogenous body to the society and regard themselves as separate entities (Jamali, Jirshak, 2009). However, according to Schouten (2007), MNCs are not able to operate efficiently with a neutral stance. Partnering up with locals and in that way making the complex market nuances of the turbulent environment more feasible is at the core of successfully establishing a sustainable strategy in conflictual areas (Anderson et. al, 2010). Thereby, subsidiary behavior in conflict prone areas needs to be based upon collaboration and integration involving high levels of compromise and sharing. In that way, severe conflicts can be resolved leading to both opposing parties obtaining satisfaction through win-win outcomes (Gladwin, Walter, 1980). Dialogue and consultation as well as collective action thereby serve as efforts to more entirely understand the underlying drivers and reasons for violence and to enhance the insights into particular conflicts prevalent in the respective locations (Bennett, 2001). Companies in conflict zones thus need to extend their business model by going beyond mere transactional partnerships. Thereby, foreign companies entering conflictual areas are compelled to discard their ‘foreigner-status’ and rather be recognized as ‘one of us’.
2.3 Ethnic ties
12 perspective, ethnic ties simplify the exchange of highly valuable information and in that way are able to subserve economic goals (Burt, 1997). Further, ethnic ties can become effective governance mechanisms in order to prevent opportunistic behavior and contract violations, especially in locations where contract enforcement is weak or infrastructures are instable (Xin, Pearce, 1996). More precisely, in locations where contracts need to be self-enforcing, the membership in the host country’s predominant ethnic group broadens the portfolio of cooperative strategies that can be applied (La Ferrara, 2003). According to Fearon and Laitin (1996), interethnic cooperation is heavily influenced by the degree of congruency between the parties involved. Applying a social matching model, they conclude that ethnic conflicts at the individual level spirals throughout the whole ethnic group. Hence, foreign subsidiaries and the embedded potentially distinct ethnicity may prevent efficient operation within conflict zones.
13 diverse groups of ethnicity and religion, reaching agreements and solving economic differences becomes increasingly difficult (Huntington, 1997).
2.4 Intra- and interstate conflicts and subsidiary performance
Drawing from the literature reviewed, it is assumed that both, intrastate and interstate conflicts do negatively affect a foreign subsidiary’s performance in the host location. This assumption has already been confirmed by other researchers (e.g. Oh and Oetzel, 2017; Rettberg, 2004; Davies, 1996; Anderson et al., 2010). Further, Abadie and Gardeazabal (2003) investigated the economic effects of conflicts by reference to the cease-fire in the Basque Country and concluded a negative relationship between host country conflicts and foreign companies’ performance. More recently, Oh and Oetzel (2011) observed an intense reduction of the number of subsidiaries in conflict zones as a response to the appearance of terrorist attacks. Branzei and Abdelnour (2010) and Czinkota, Knight, Liesch and Steen (2010) investigated severe cases of terrorism in developing countries and the connected threats and impacts and examined to what extent extreme conflicts such as terrorism influence international business. Therefore, these negative relationships are taken for granted and are not actually tested within this thesis. They serve as a baseline in order to be able to analyze the moderation effect of ethnic ties on these relationships.
2.5 Moderating role of ethnic ties
14 cooperation subsidiaries are able to establish in conflict zones in order to improve financial performance is capped due to ethnic groups shutting themselves off in eras of severe conflict. For that reason, ethnic ties can be assumed to facilitate business operations in a conflictual environment as they potentially decrease the level of ethnic discrepancy between the foreign subsidiary and the local community. However, the impact of ethnic ties on the performance of a foreign subsidiary in a conflict prone location seems to differ according to whether interstate or intrastate conflicts are predominant.
According to Turner, Brown and Tajfel (1979), a strong group identity affects individual behavior and thus creates in-group enhancement by preferring the in-group instead of the outgroup leading to in-group favoritism and discrimination against the outgroup. Hence, it can be assumed that foreign subsidiaries embodying distinct ethnicity relative to the conflict zone’s prevalent ethnic groups, face severe difficulties to get into contact with locals. This disadvantage seems to be critical in conflict zones plagued by intrastate conflicts. Intrastate conflicts prohibit the occurrence of a coherent national group belongingness due to internal tensions among the population. Rather, the society is fragmented into various groups that strongly separate themselves from each other on the basis of ethnic, religious or ideological differences. As a result, establishing close relationships with local actors in intrastate conflict zones becomes increasingly difficult, if not even impossible. Correspondingly, foreign subsidiary performance suffers. Therefore, ethnic ties are presumed to have a high potential for fostering foreign business conduction and ultimately improving a subsidiary’s performance in conflict zones plagued by intrastate conflicts:
H1a: Ethnic ties weaken the negative relationship between intrastate conflicts and foreign subsidiary performance.
15 H1b: Ethnic ties do not weaken the negative relationship between interstate conflicts and foreign subsidiary performance.
Hypothesis 1b assumes that the moderator ethnic ties does not have any impact on the dependent variable. Testing a so-called null-hypothesis differs from the standard practice. Theory usually guides the hypothesis in a specific direction. The approach of testing a null-hypothesis is frequently dismissed saying that null-hypotheses are typically rejected whereas its acceptance would yield considerable bias in the results (Greenwald, 1975). In line with this argumentation is Rozeboom (1960) stating that the null-hypothesis significance test method’s fundamental error lies in falsely believing that a scientific investigation builds on a decision rather than on an extensive cognitive evaluation. However, Gallistel (2009) describes null-hypotheses as being not only simple but also precise and thus important to explain theory evaluations. Further, when applied reasonably, null-hypothesis testing can be an effective and helpful method with regard to the interpretation of data (Nickerson, Raymond, 2000). Literature thus neither clearly refuses nor completely legitimizes the testing of a null-hypothesis. With regard to the theory leading to hypothesis 1b in this thesis, however, applying an alternative approach indicating a specific direction of the moderation effect would potentially distort the obtained results. Therefore, this thesis will test the null-effect.
2.6 Conceptual Model
Taking together the pre-mentioned hypotheses, the following conceptual model can be created:
16 3. Methodology
Within this section, a detailed overview of the research methodology of this study will be provided. More precisely, the variables and the applied measurements, the sampling strategy as well as data collection will be explained. Further, methods serving the statistical analysis will be elucidated.
3.1 Data collection
Conflict prone areas and their corresponding conflictual countries were identified through various data sources. The Uppsala Conflict Data Program (UCDP) is used as a database for international intrastate conflicts. It is argued to be among the most comprehensive sources of conflict-related data worldwide (Anderton, Carter, 2011). The UCDP/PRIO Armed Conflicts dataset includes intrastate wars as well as sub-war conflicts at the country-level until 2016. More precisely, it includes intrastate conflicts where the exertion of armed force results in at least 25 battle-related deaths in a calendar year (Gleditsch et al., 2002). Further, the UCDP Non-State Conflicts dataset shows intrastate conflicts between two organized groups, neither of which is the government of a state (Sundberg, Ralph, Eck, Kreutz, 2012). Lastly, the UCDP One-sided Violence dataset was used in order to obtain intrastate conflicts in form of intentional attacks on civilians either by governments or by formally organized armed groups (Eck, K. Hultman, L. Hultman, 2007). After having filtered the data for potential overlaps and double-mentioning, a substantial number of countries plagued by intrastate conflicts in the period from 2000 until 2016 was obtained. Concerning interstate conflicts, data from the Correlates of War Project was analyzed. Through the Militarized Interstate Dispute dataset by Kenwick, Lane, Ostick an Palmer (2013), countries plagued by interstate disputes in the same period were identified. In order to obtain a coherent dataset, the same fatality threshold was applied meaning that only those interstate conflicts were considered that led to 25 or more battle-related deaths in a calendar year.
17 suitable to effectively compare companies internationally (Bureau van Dijk (BvD)). The sample companies’ annual reports as well as websites turned out to be inapplicable sources of subsidiary data due to consolidation efforts frequently disguising the financial data of foreign subsidiaries.
Regarding the identification of ethnic ties between the French subsidiaries and the corresponding conflict countries, databases such as eurostats and worldbank, which are highly extensive data sources containing comprehensive real-world statistics, and the International Migration Report 2016 are used. Together, these data sources were screened in order to identify recent migration flows and the resulting change of ethnic mix in the respective sample locations. Regarding colonization, the ICOW Colonial History data set is used drawn from the Issue Correlates of War (ICOW) project by P. Hensel. It contains data on former colonization and the nationality of the corresponding past colonial rulers.
Two control variables and their measures were obtained through the ORBIS database as well. It includes all the necessary information and financial figures regarding the control variables foreign subsidiary size and parent company size. Data related to the control variable ‘economic status’ was gathered through the World Bank’s database.
3.2 Sample
18 period of intra- and interstate conflicts and the year of the financial information is legitimate and does not distort the results. This is due to the fact that ethnic identity is not only determined by present conflicts but also by collective memories of past traumas from conflicts (Frankl, 1992; Rothman, 1997; Volkan, 1998). Recent studies have outlined that for each independent variable or predictor, at least 10 events should be incorporated (Harrel, Lee, Mark, 1996; Laupacis, Sekar, Stiell, 1997; Concato, Peduzzi, Holford, Feinstein, 1995; Peduzzi, Concato, Feinstein, 1995). However, a sample of 20 foreign subsidiaries appeared to be by far too small in order to obtain generalizable results. Hence, a more comprehensive number of French subsidiaries was chosen as sample size is positively related to explanatory power (Hair, Black, Babin, Anderson, 1998). Hence, the sample size is far extending the minimal requested number of events. More specifically, after having deleted those French firms with foreign subsidiaries in countries that are not plagued by conflicts as well as those firms where the financial data of the subsidiary itself or of the parent company were incomplete, a sample containing 231 French foreign subsidiaries in 24 distinct countries was obtained. These countries are India, Algeria, Botswana, Ghana, Senegal, Morocco, Philippines, Tunisia, Sri Lanka, Sierra Leone, Pakistan, Nigeria, Mexico, Liberia, Lebanon, Jordan, Israel, Indonesia, Egypt, Ivory Coast, Colombia, Cameroon, Burkina Faso, Brazil. The sample thus touches various major regions in the world, meaning Asia, the Middle East, South America and Africa. The companies incorporated in the sample operate in a large variety of industries, enhancing the generalizability of the results.
3.3 Variables and measurement
3.3.1 Dependent variable
The dependent variable within this study is labeled foreign MNC subsidiaries’ performance and refers, as mentioned above, to the foreign MNC financial performance.
19 the ROEs and ROAs of subsidiaries in conflictual areas. Therefore, net income is used as an indicator in order to measure subsidiary performance. This procedure is in accordance with prior research (see e.g. Dossi and Patelli, 2010).
3.3.2 Independent variables
The two independent variables within this study are interstate conflicts and intrastate conflicts. As mentioned earlier, intrastate conflicts embody conflicts arising within the officially recognized territory of a state such as civil wars and inter-communal conflicts whereas interstate conflicts are rather evoked by territorial disputes, state rivalry as well as interstate ethnic conflicts. These two variables are measured at the country-level. Hence, countries embodying interstate and intrastate conflicts are identified. Combining the UCDP datasets and the COW datasets, the number of intra- and interstate conflicts in the various countries in the dataset were analyzed. Thereby, all intra- and interstate conflicts arising since 2000 were taken into account. In that way, it was assured that the recorded conflicts are not a one-time phenomenon. This method guaranteed that the countries later chosen within the sample are severe conflict areas. Further this procedure served the sufficient gathering of data concerning interstate-conflicts since these are much less apparent than intrastate conflicts.
3.3.3 Moderator ethnic ties
20 3.3.4 Control variables
In order to ensure accuracy of this study, several factors and their potential impacts need to be excluded by controlling for their effects.
First, it needs to be controlled for the economic status of the distinct host countries. Thereby, it is controlled for a country-level effect: market size. It is measured through gross domestic product (GDP) of the various countries in the year 2016. This procedure is in accordance with previous subsidiary performance analysis (Getachew, Beamish, 2017). Corresponding data is gathered through the ORBIS database on GDP (in current mUS$) of the diverse national accounts.
Second, it needs to be controlled for parent firm size. Larger firms are more probably associated with economies of scale enhancing their efficiency relative to the inputs required (Watson, Wooldridge, 2005). Hence, subsidiaries that are affiliates of rather large parent companies might be significantly more well-equipped concerning capabilities and key resources than subsidiaries of medium-sized firms which might makes them advantageous in terms of coping with the appearing challenges in conflict zones independent of the existence of ethnic connections. It is controlled by using the annual turnover in the year 2016.
Third, on the subsidiary-level, the size of the subsidiary is controlled. Subsidiary size was observed to influence subsidiary performance (Moulton, Thomas, 1993). It is controlled by the annual turnover of the subsidiary in the year 2016.
It is noticed that a dependent variable such as subsidiary performance yields much more potential control variables that can be included into the analysis. However, within this thesis only the three mostly encountered control variables will are incorporated as an automatic or blind inclusion of control variables in multiple regressions might lead to bias contaminating the results (Spector, Brannick, 2011).
3.3.5 Analysis
21 In order to be able to use this type of statistical analysis, according to Field (2009), various assumptions are imperative. First, outliers that are significantly biasing the model need to be detected and removed to make the results valid. Secondly, to ensure that the dependent variable is linearly related to any predictor variable, linearity needs to be tested between the predictor and the dependent variable. Next, the values of the residuals have to be independent and the variance of the residuals have to be constant. Otherwise, there would be heteroscedasticity due to unequal variances leading to rather uneven outcomes according to Field (2009). Lastly, multicollinearity between the independent variables needs to be precluded to ensure that the individual effects of the independent variables is visible. Data transformation can serve as an appropriate tool in case of violation of any of the assumptions. Regarding the moderation effect, a moderation analysis was conducted in order to test the interaction effect of the moderator ‘ethnic ties’. The moderation analysis was executed using ‘Process’, an additional statistical tool created by Andrew Hayes. By integrating it into the SPSS program, it yields several advantages against a manual moderation computation in SPSS such as the automatic calculation of the interaction-term (Field, 2009). In order to uphold robustness of the analysis, statistical bootstrapping was applied to minimize bias and at the same time to enhance the validity of the model. In detail, bootstrapping ‘estimates the properties of the sampling distribution from the sample data’ (Field, 2009, p. 638). Thereby, the method takes the sample as a population and creates smaller samples. In that way, bias resulting from non-normality can be erased. In other words, due to bootstrapping, the results of the multiple regression analysis are not dependent on statistical assumptions (Field, 2009; Hair et al., 1998).
4. Empirical Results
The following section incorporates the empirical results of the statistical analysis. More precisely, it contains the execution and findings of the various assumption tests as well as the outcomes of the hierarchical multiple regression analysis and the moderation analysis.
4.1 Assumptions of Multiple Regression Analysis
22 could be identified in the dataset. This finding was further supported by the obtained values of the Mahalanobis Distance confirming the initial results of the Cook’s Distance. In order to test for linearity, SPSS offers visual tools, such as a scatter plot or proper statistical tests. More precisely, linearity is tested by analyzing the significance for linearity as well as the deviation from linearity. Thereby, each independent variable and the dependent variable is analysed through an ANOVA table including the required values. The results indicated a non-linear relationship beyond the linear component with regard to both, the relationship between intrastate conflicts and subsidiary performance as well as the relationship between interstate conflicts and subsidiary performance. Unfortunately, data transformation did not yield the desired improvements. Concerning the assumption of normality, there was some degree of kurtosis observable in the obtained histogram indicating a non-normal distribution of values. Regrettably, data transformation using logarithm or square root, as suggested by Hair, Black, Babin, Anderson and Tatham (1998), did not normalize the distribution significantly. Multicollinearity, meaning the correlation of the independent variables, was tested through the Variance Inflation Factor (VIF) as this method is assumed to be more accurate than a correlation matrix (Field, 2009). The results showed that there is no multicollinearity apparent between the two predictors. Further, the values of the Durbin-Watson statistic indicated an increasingly stronger positive correlation between the values of the residuals violating the assumption that the values of the residuals have to be independent. Lastly, regarding heteroscedasticity, the obtained scatter plot did not show a funneled distribution indicating that there is no heteroscedasticity existing. More extensive descriptions of the statistical procedures as well as the SPSS output tables and graphs, can be found in the Appendix under ‘Assumptions of Multiple Regression Analysis’.
4.1.1 Violation of assumptions
23 determine the negative peculiarity of the relationship and to be able to draw inferences from the moderation regression following the multiple regression analysis. Additionally, the method of bootstrapping will be applied throughout the main analysis which is said to reduce potential bias resulting from assumption violations. In this way, the effects of bias from assumption violation can be reduced or even neutralized (Field, 2009).
4.2 Multiple Regression analysis
24 4.2.1 Hierarchical Multiple Regression
Table 7 presents a correlation matrix on all the variables used in the model. The correlations between all variables in the model are low and thus multicollinearity was not a concern. As mentioned already in the previous section, a collinearity diagnostic was run on all the variables using the variance inflation factor (VIF) method. The calculated VIF scores for all the variables are below 5, indicating that multicollinearity is not an issue.
Variables Mean SD 1 2 3 4 5 6 Subsidiary size 615.59 1230.91 PC Size 95720.15 57838.94 0,236 Hostmarket GDP 1181293.55 1000178.06 0,047 0,524 Intrastate conflicts 40.23 29.02 -0,034 0,456 0,765 Interstate conflicts Subsidiary Performance 11.12 0.90 6.213 5.56 0.136 0.43 0,516 -0,083 0.616 0.42 0.773 -0.198 -0.253
Table 7: Correlation coefficients
Table 8 presents the results of the tests. The analysis resulted in 2 models. The first including only the control variables and the second adding the two predictor variables. There are two different models within the output table of the hierarchical multiple regression. Thereby, model 1 embodies the control variables Parent Company Size, Subsidiary Size and Host Country Status (consisting of host market GDP in current mUSD) whereas model 2 adds the predictor variables. Inferring from the above table, the following interpretations can be drawn:
25 After having included the independent variables, the value of the Rsq raises to 16.50%, indicating that the predictors add a significant impact to the explanation in the variation.
Independent variables
Model 1 Model 2
Subsidiary size 0.000 0.000
PC Size -1.611E-5* -6.048E-6
Host market GDP 7.031E-7 2.769E-6** Intrastate conflicts -0.064** Interstate conflicts -0.250** R² 0.023 0.165 R² change 0.023 0.143 F-value 1.748 8.907** N 231 231
Table 7: Results hierarchichal multiple regression (coefficients) *p<0.05 **p<0.01
26 2009). According to that, in case a population would have been the basis for this model instead of a sample, it would explain 1.80% less of the variance of the dependent variable.
The F-value shows whether the model fits the overall data. Analyzing this value, one can suggest that model 1 does not significantly enhance the explanatory power regarding Subsidiary Performance since the p-value is larger than 0.05. However, when looking at model 2, it is observable that this model significantly increased the ability to predict Subsidiary Performance with a F-value which is higher than 1 and also highly significant with a p-value of 0.00. As a result, model 2 can be assumed to present a statistically significant predictor of Subsidiary Performance.
Thus, model 2 is emphasized as it was determined to be statistically significant. Looking at the b-value of Intrastate Conflicts, a b-value of -0.064 can be observed with a p-b-value of 0.007 indicating that a change in one unit of Intrastate Conflicts comes along with a significant decrease of -0.064 in Subsidiary Performance. Correspondingly, Interstate conflicts exhibit a b-value of -0.250 (p=0.007), meaning that this predictor also has a significant negative influence on Subsidiary Performance. Concerning the control variables, Host Market GDP shows a positive effect on Subsidiary Performance whereas Parent Company Size shows a negative effect on the dependent variable. However, only the impact of Host Market GDP is significant (p=0.000). The control variable Subsidiary Size does not have any effect on the dependent variable with a b-value of 0.00.
4.2.2 Moderation Analysis
27
Ethnic ties x Colonization
Low levels of ET -0,0583**
Medium levels of ET
High levels of ET -0,0012
Ethnic ties x French migrant stock
Low levels of ET -0,0485*
Medium levels of ET -0,0361**
High levels of ET -0,0137*
Ethnic ties x Host market migrant stock
Low levels of ET -0,0474*
Medium levels of ET -0,0839**
High levels of ET -0.1511**
Table 11: Results moderation analysis (Intra) *p<0.05 **p<0.01
28 Turning now to the moderator French Migrant Stock, it can be seen that the values in terms of the proportion of the respective foreign host market nationality within the French population are significant at all three levels (p<0.05). The relationship between intrastate conflicts and foreign subsidiary performance is more negative in case of low levels of the moderator (b=-0,0485) and less negative at high levels of the moderator (b=-0,0137). Hence, the negative relationship between the predictor and the dependent variable is significantly weakened by high migration levels into France.
The last component of the moderator Ethnic Ties is Host Market Migrant Stock. By interpreting the results, it is evident that the relationship between intrastate conflicts and foreign subsidiary performance is significantly negative at all three levels of the moderator. However, is can be observed that this relationship is less negative for low levels of the moderator (b=-0,0474) than for high levels of the moderator (b=-0,1511). It means that high levels of French migration to the respective host countries do significantly strengthen the negative relationship between Intrastate Conflicts and Subsidiary Performance.
Table 12 contains the outcomes of the three distinct regressions regarding the moderation effects of each component of the moderator with regard to interstate conflicts.
Ethnic ties x Colonization
Low levels of ET -0,3602**
Medium levels of ET
High levels of ET -0,0044
Ethnic ties x French migrant stock
Low levels of ET -0,3133**
Medium levels of ET -0,1893**
High levels of ET 0,0355
Ethnic ties x Host market migrant stock
29
Medium levels of ET -0,2740**
High levels of ET -0,3932**
Table 12: Results moderation analysis (Inter) *p<0.05 **p<0.01
Next, the moderation effect of Colonization on the relationship between Interstate Conflicts and the dependent variable is tested. When there was no former colonization (low levels), the relationship between the predictor and the dependent variable is negative (b=-0,3602). In case of former colonization (high levels), the coefficient is not statistically significant meaning that it is not significantly different from zero. Consequently, when Colonization obtains the value 1, the negative relationship between the predictor and the dependent variable is weakened.
Regarding the French Migrant Stock, the relationship between interstate conflicts and foreign subsidiary performance is observed to be negative at low levels of the moderator (b=-0,3133). This negative relationship becomes less strong and even turns positive at high levels of the moderator (b=0,0355). However, this value is not significant meaning that the coefficient is not significantly different from zero. Hence, when the proportion of the respective foreign host market nationality in the French population is high, the negative relationship between Interstate Conflicts and Subsidiary Performance is weakened.
Regarding host market migrant stock, it is observable that the relationship between interstate conflicts and foreign subsidiary performance is less negative at low levels of the moderator (b=-0,2092) than at high levels of the moderator (b=-0,3932). Hence, high proportions of French migrants in the various host country populations significantly strengthen the negative relationship between Interstate Conflicts and Subsidiary Performance.
5. Conclusion
30 5.1 Discussion of Results
The main purpose of this thesis was to investigate whether Ethnic Ties positively moderate the negative relationship between the predictors Intrastate Conflicts and Interstate Conflicts and the dependent variable Subsidiary Performance. Thereby, the moderation effect was predicted to be significant with regard to the predictor Intrastate Conflicts and not significant with regard to the predictor Interstate Conflicts. The baseline assumption was a negative relationship between the predictors and the dependent variable as already confirmed by prior literature. Such a relationship was found within the present sample so that the main objective of moderation testing could be adequately executed. Potential bias resulting from assumption violations was neutralized by applying ‘bootstrapping’ within the two main analyses. Consequently, the subsequent moderation regression could be accurately executed and interpreted. The moderator Ethnic Ties was measured through three components, namely former colonization between France and the respective host country, the French migrant stock and the host country’s migrant stock.
The results show that the presence of former French colonization has a positive impact and thus weakens the negative relationship between Intrastate Conflicts and Subsidiary Performance. The same impact was observed with regard to the relationship between the predictor interstate conflicts and foreign subsidiary performance which is in contrast with the initial prediction.
31 performance and thus rather exacerbate business conduction in terms of subsidiary performance in intrastate conflict zones. When considering Interstate Conflicts, it seems as if high levels of migration flows from France into the various host countries do positively impact subsidiary performance in locations where interstate conflicts are present as they weaken the negative relationship between interstate conflicts and foreign subsidiary performance.
Taken together, it can be inferred that the hypotheses 1a and 1b have partly been confirmed. Regarding Colonization, hypothesis 1a is confirmed as the presence of former colonial ties weakened the negative relationship between the predictor Intrastate Conflicts and the dependent variable. However, hypothesis 1b is contrasted as former colonization also weakens the relationship between interstate conflicts and foreign subsidiary performance.
High levels of French Migrant Stock exhibited significant moderation effects weakening the main relationship between both predictors and the dependent variable. Thus hypothesis 1a is validated and hypothesis 1b is contrasted.
Lastly, concerning Host Market Migrant Stock, hypothesis 1a was not confirmed as high levels of French migration into the respective host countries strengthened the negative relationship between intrastate conflicts and foreign subsidiary performance. With regard to the predictor Interstate Conflicts, high levels of French migration into the respective host countries weakened the negative relationship between interstate conflicts and foreign subsidiary performance. Hence, hypothesis 1b was also not confirmed.
As a result, it can be concluded that Ethnic Ties can be classified as being helpful regarding the successful business conduction in conflict prone areas not only where intrastate conflicts are present but also where interstate conflicts do arise.
5.2 Limitations and Future Research
32 to neutralize potential resulting bias, the data might not be perfectly non-biased. Adapting the sample in terms of size or characteristics might serve as a solution for this issues in the future. Also, regarding the sample, consistent information about subsidiaries in various conflict areas were hard to obtain. Thus, the sample might be biased as a great proportion of the subsidiaries comes from Morocco and India as there was the complete data obtainable within these locations. Future research might have access to more sophisticated and complete database except from the Orbis database and thus might use samples that are to a higher degree fragmented with regard to the conflictual host locations.
Further, in order to more accurately test the moderation effect of colonization on subsidiary performance in conflict areas, the unique characteristics of the former colonization need to be considered. In that way, future research might clarify whether the hostility aspect of colonization did influence the analysis within this thesis and thus distorted the results.
Lastly, the database ‘Correlates of War’ by Sorokin, Wright and Richardson was used in order to determine the number of interstate conflicts apparent in the various locations. This database only includes interstate disputes that have been militarized. However, according to Jones, Bremer and Singer (1996), there are also so-called ‘serious’ interstate disputes that not necessarily got militarized such as confrontations regarding energy investments or resource allocation. The ‘Militarized Interstate Disputes’ database of the Correlates of War project do not incorporate those interstate disputes and thus might have biased this thesis’ results. Future research might identify another database incorporating both types of interstate conflicts to enhance the accuracy and generalizability of results.
5.3 Managerial and practical implications
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41 APPENDIX
Appendix 1: Results of assumption testing Outliers
Through the creation of a new variable within the dataset with a threshold of 1, outliers can be determined. In case, the new variable embodies values that exceed the threshold of 1.00, it can be suggested that outliers are present. Correspondingly, if the new variable only generates values clearly below 1.00, the dataset does not exhibit any outliers that potentially bias the results. Within the analysed dataset, all values of the new variable score below 1.00, indicating the absence of any outliers. Further, the Mahalanobis Distance was used in order to support this outcome. This statistical tool likewise tests for the presence of any multivariate outliers. Similarly, it creates a new variable. However, according to Field (2009), thresholds are not constant and might vary with a change of numbers of predictors and sample size. Hence, it was imperative to generate another variable containing the probability of each value to be an outlier with regard to the Mahalanobis variable. This was done by comparing the Mahalanobis values to a Chi-Square distribution. As a result, values that score below 0.001 are assumed to be outliers. By applying this method, no outliers were identified which supports the initial results of the Cook’s distance.
Linearity
In order to test for linearity, SPSS offers visual tools, such as a scatter plot or proper statistical tests. More precisely, linearity is tested by analyzing the significance for linearity as well as the deviation from linearity. Thereby, each independent variable and the dependent variable is analysed through an ANOVA table including the required values. Initially, when testing the independent variable Intrastate Conflicts, the following results were received:
42
Within Groups 5093.196 211 24.138
Total 7107.093 230
Table 1: ANOVA Table Subsidiary Performance – Intrastate conflicts
As observable in the table above, the test for linearity between Subsidiary Performance and Intrastate Conflicts has a significance value smaller than the threshold of 0.05, indicating that there is a linear relationship between the two variables. However, the test for deviation from linearity also exhibits a significance value < 0.05, which means that there is a non-linear relationship in addition to the linear component. Hence, the variable Intrastate Conflicts is transformed by taking the logarithm. The outcomes of the transformation are presented in the following table:
Table 2: ANOVA Table Subsidiary Performance – Intrastate conflicts (log)
Even after the transformation, the significance value for the deviation from linearity is still <0.05, indicating a non-linear relationship beyond the linear component. Thus the assumption of linearity is violated. Applying the same test for linearity with regard to the predictor Interstate Conflicts, the following results were obtained:
43 Table 3: ANOVA Table Subsidiary Performance – Interstate conflicts
The significance value of linearity between the independent variable Interstate Conflicts and the dependent variable Subsidiary Performance is < 0.05. Unfortunately, the significance value for the deviation from linearity between the two variables also scores below 0.05, indicating a non-linear relationship in addition to the linear component between Interstate Conflicts and Subsidiary Performance as well, violating the assumption of linearity. Using data transformation in form of logarithm did not positively affect the significance values (Table XXX)
ANOVA Table Sum of Squares Df Mean Square F Sig. Subsidiary_Performa nce_NetIncome mUSD * Log2_Inter Between Groups (Combined) 1867.329 13 143.641 5.821 .000 Linearity 778.287 1 778.287 31.538 .000 Deviation from Linearity 1089.042 12 90.754 3.678 .000 Within Groups 5231.641 212 24.678 Total 7098.970 225
Table 4: ANOVA Table Subsidiary Performance – Interstate conflicts (log)
Within the multiple regression analysis, the robustness method ‘bootstrapping’ will be applied which is able to strongly reduce bias when assumptions are violated according to Field (2009). In that way, the generation of valid results can still be uphold. However, with regard to the subsequent interpretation of the results, one needs to be careful.
44 Normality
The assumption of normality is checked through the creation of a histogram. In order for the values to not be unnormally distributed, the graph needs to be skewed in a symmetrical manner. Additionally, the curve should be balanced meaning it should neither be strongly peaked nor flat. The obtained histogram shows a distribution which can be regarded as relatively normal with respect to the level of skewness. However, kurtosis of the distribution seems to be an issue as the curve is peaked meaning that there is some degree of positive kurtosis (leptokurtic). Several studies consider data transformation and more precisely the use of the logarithm or square root as appropriate methods in order to solve kurtosis problems (Hair, Black, Babin, Anderson, Tatham, 1998; Field, 2009). Unfortunately, both of these transformations did not lead to the desired normalization of distribution. Consequently, bootstrapping will be applied within the main analysis. In that way, kurtosis bias will be avoided since this method does not presume normality. Although the observable gaps within the generated histogram could indicate potential outliers, this was already precluded within the outlier testing section through the Cook’s Distance and Mahalanobis Distance. Thus, it can be inferred that the residuals appear to be normally distributed.
45 Figure 2: Histogram transformed variables (log)
