The effect of Environmental Dynamism on the Relationship between International Diversification and Firm Performance

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The effect of Environmental Dynamism

on the Relationship between

International Diversification and Firm

Performance

University of Groningen

August 2012

Written by Harm Robben

Supervised by: A.N. Kiss

Co-assessor: Dr. D.H.M. Akkermans

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University of Groningen | Abstract. 2

Abstract.

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University of Groningen | Table of Contents 3

Introduction ... 5

Literature Review ... 10

Resource Based View (RBV) ... 11

Stage models of Internationalization ... 13

Transaction cost / Internalization theories (TCI) ... 14

Multinational Network Hypothesis (MNH) ... 15

I-P and the environment. ... 17

Hypothesis development ... 20

Research Design ... 24

Sample description ... 24 Dependent variable ... 26 Independent variables ... 26 Control variables ... 29

Data Analysis Technique ... 30

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University of Groningen | Table of Contents 4

List of Tables

Table 1: Summary of Variables………28

Table 2: Summary Statistics………..31

Table 3: Regression Results………33

Table 4: Dynamism values (Appendix 3)………51

Table 5: Full Regression Results (Appendix 4)………52

List of Figures

Figure 1: NACE Rev. 2 Structure (Appendix 1)……….……….47

Figure 2: Excerpt Annual report Man SE (Appendix 2)……….………..49

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University of Groningen | Introduction 5

Title: The effect of Environmental

Dynamism on the Relationship between

International Diversification and Firm

Performance.

Introduction

One of the most researched themes in the area of International Business research is the study of the international diversification – performance (I-P) relationship (Chao & Kumar, 2010; Ruigrok, Amann & Wagner, 2007). Research that involves the I-P relationship has resulted in a wide variety of conclusions about the shape and direction of the relation, moderating variables and areas for future research (Bausch & Krist, 2007; Contractor, Kundu & Hsu, 2003; Datta, Rajagopalan & Rasheed, 1991; Glaum & Oesterle, 2007; Hitt Tihanyi, Miller & Conely, 2006; Lu & Beamish, 2004; Purkayastha, Manolova & Edelman, 2012). Nonetheless these papers are proof of the importance of the I-P theme in the International Business field of research.

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positive relationship (mainly during the 1970’s). Later during the 1980’s and 1990’s recognition came that internationalization also bears the risk of failure and the strictly positive relation changed to results that proved that there is no relationship, a linear positive or negative relation and an U-shaped or inverted U-shaped relation (see Contractor et al, 2003 for a complete overview). This accumulated knowledge on the I-P relation shows that little consensus has been established about the direction and shape of the relationship. The explanation for the lack of consensus has been sought after in the firm characteristics (Brock & Yaffe, 2008; Dastidar, 2009), the measurement inconsistencies (Cardinal, Miller & Palich, 2011; Wiersema & Bowen, 2011) and the proposition made by Hennart (2007) that there is no theoretical connection between internationalization and performance and that therefore all prior results are based on luck (Cardinal et al., 2011).

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The occurrence of the 2007/2008 worldwide financial crisis and the questions this raises have led to the recognition of the fact that there are no empirical investigations that analyze what happens to the I-P relationship in a turbulent or dynamic environment. The recent financial crisis is not unique, but by far the largest the world has ever seen. Due to the enormous impact of the crisis some researchers take the opportunity to use the crisis as a natural experiment to reexamine commonly accepted relations in economy and at the business level (Bezemer, 2011; Kuppuswamy & Villalonga, 2010; Rudolph & Schwetzler, 2011). By doing so two recent studies have found that diversified corporations are valued higher in times of crisis (Kuppuswamy & Villalonga, 2010; Rudolph & Schwetzler, 2011). Where these researches show that the valuation of diversified corporations increases the question remains whether the performance of these firms increases as well. For that reason this paper will examine whether or not the environmental dynamism caused by the 2007/2008 financial crisis has a moderating influence on the international diversification – performance relationship. So in response to the earlier introduced gap, in this paper I will answer the following research question:

Research question: What is the moderating effect of environmental dynamism on the internationalization – performance relationship?

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What is the theoretical relation between international diversification and performance? Why is the environmental dynamism expected to have a moderating influence on the I-P relation?

In the empirical section of this paper I will test the theoretical relations derived from the literature. The goal of the empirical section is to measure the effect of international diversification on a sample of firms and statistically measure the effect of environmental dynamism. In this section the following questions will be answered:

What is the shape and direction of the relation between international diversification and performance?

What is the effect of environmental dynamism on the relation between international diversification and firm performance?

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University of Groningen | Introduction 9 Relevance:

The answers to the earlier raised questions are relevant for both theoretical and practical reasons. Primarily this paper responds to the lack of knowledge about what happens to the I-P relation in a turbulent environment and thereby adds to the current literature on the subject. By adding a context related variable to the I-P relation this paper follows recent articles which attempt to enhance our understanding of the effect of internationalization (Elango & Sethi, 2007; Jong de et al., 2010; Ruigrok et al., 2007). As mentioned earlier this ads to the complexity of the subject and should not be seen as an attempt to create a comprehensive model which includes all variables that are of influence on the I-P relation. By focusing strictly on one new variable, namely the environmental dynamism, this paper is expected to add an explanation for the performance created by internationalization under very specific circumstances. By doing so this paper has practical relevance as well. Based on the results, managers are able to determine the appropriate strategy in times of environmental turbulence. If the environmental turbulence has a positive moderating effect on the I-P relation it might be worth the additional investment of increased international diversification. The opposite might be true as well; when the moderating effect is negative, decreasing international diversification can be a more appropriate corporate strategy. The relevance of these results should be applicable to many types of environmental turbulence, so not only that created by a global financial crisis, but also the dynamism often found in developing markets.

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University of Groningen | Literature Review 10

Literature Review

The following chapter will present an overview of theories related to the subject of firm internationalization and performance. When conducting research on this topic it becomes apparent that the terminology in prior research is inconsistent. The relation between internationalization and performance has been investigated under the title of: global market

diversification, multinationality, geographic diversification, international expansion and globalization (Brock & Yaffe, 2008; Hitt et al., 2006) to name a few examples. To prevent any

misinterpretation about the topic of this review and research, the term international diversification in this review refers to: a firm’s expansion beyond the borders of its home country, across different countries or geographical regions (Capar & Kotabe, 2003; Hitt et al., 2006). This definition includes internationalization through exports as well as through FDI regardless of the entry mode chosen. Based on this definition I was able to include all appropriate theoretical bases for the internationalization and performance relationship.

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Although each theory takes a different approach to explain the I-P relationship there are some commonalities as well. First, all theories are similar in the incorporation of market failures. Each theory indicates that firms benefit from international diversification because these firms are able to benefit from market failures (Lu & Beamish, 2004). This indication means that if all national markets where perfectly operating markets there would be no benefit in international diversification. Second, all the theories take a different approach in explaining the same concept, namely the balance between the costs and benefits of internationalization. All the theories recognize that the performance benefits derived from internationalization are a result of the costs and benefit trade-off and that the performance therefore varies with the level of internationalization of the firm. The following section will present a brief review of each of these theories and will especially focus on the explanation these theories have for the reason why firms internationalize and why internationalized firms have superior performance.

Resource Based View (RBV)

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that accrues to the firm specific resources. More specifically Hymer (1976) has indicated that with higher international involvement a firm has higher levels of tangible and intangible resource exploitation, and therefore is expected to have a higher performance (Bartlett & Ghoshal, 1989; Hsu & Pereira, 2006; Porter, 1990; Teece, 1986).

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linear relation between international diversification and performance (Cardinal, Miller & Palich, 2011; Goerzen & Beamish, 2003).

Stage models of Internationalization

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characteristic. In this stage of internationalization the positive balance between costs and benefits is expected to weaken do to an increase in market entry costs (Assaf, Josiassen, Ratchford & Barros, 2012; Johanson & Vahlne, 2009).

The benefits a firm is able to derive from international diversification, based on the stage model have to do with gathering information from a wider market base (Assaf et al., 2012; Hsu & Pereira, 2006; Lu & Beamish, 2004; Ruigrok & Wagner, 2003). According to Hennart (2007) it is hard to defend the point that international firms benefit from R&D operations and knowledge from abroad, because most of the R&D expenses within firms are still made in the home country and as a consequence most of the patents resulting from R&D efforts are also secured in the home markets. The internationalized firms do however gather experience from their international operations and have easier access to foreign market information (Baek, 2004; Bausch & Krist, 2007; Brock & Yaffe, 2008; Hitt et al., 2006; Kim, Hwang & Burgers, 1993; Ruigrok & Wagner, 2003)

Transaction cost / Internalization theories (TCI)

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foreign operations the firm will be able to better leverage its intangible assets and as a result it creates a competitive advantages not available to domestic firms (Baek, 2004; Buckley & Casson, 1976; Hennart, 1982 & 2007; Hitt et al., 2006; Mathur et al., 2004). In line with this logic is also the theoretical assumption that the more internationalized a firm is the better it will be able to leverage these intangible assets. Within the TCI theories there is however a threshold level of international diversification after which the costs of internalizing one more foreign operation become to outweigh the benefits (Goerzen & Beamish, 2003). This threshold is based on the costs of control, which is closely related to the agency theory as well, which will increase with each additional operation that needs to be controlled within the firm (Baek, 2004; Bausch & Krist, 2007 Capar & Kotabe, 2003; Elango & Sethi, 2007; Freund, Trahan & Vasudevan, 2007; Goerzen & Beamish, 2003; Lu & Beamish, 2004; Purkayastha et al., 2012; Reeb, Kwok & Baek, 1998). The threshold level of international diversification is not the same for every firm as this is dependent on the firms’ capacity to control its operations and the ability to adapt its control mechanisms to the amount of operations it has to control (Contractor et al., 2007; Lu & Beamish 2004; Ruigrok et al., 2007). Based on the TCI theories the shape of the I-P relation is expected to resemble the ∩-shape, which is indicative of the initial benefits of internationalization whit the inclusion of a threshold after which the performance decreases.

Multinational Network Hypothesis (MNH)

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1990; Chung, Lu & Beamish, 2008; Johanson & Vahlne, 2009). The creation of multinational networks is theorized to be driven by market imperfections and the firms’ ability to benefit from increased leverage on its intangible assets (Doukas, Pantzalis & Kim, 1999).

Based on this view of the firm the corporation is expected to benefit from arbitrage possibilities (Contractor, 2003; Dastidar, 2009; Lu & Beamsih, 2004), risk reduction (Amit & Livnat, 1988; Contractor, 2007; Hund, Monk & Tice, 2010; Kim et al., 1993; Lu & Beamish, 2004; Rugman, 1976; Reeb et al., 1998) and cross-subsidization (Berger & Ofek, 1995; Brock & Yaffe, 2008; Kim & Mathur, 2008; Kwok & Reeb, 2000; Reeb et al., 1998). Each of these benefits has its source in the flexibility created by the existence of the internationally diversified firm. In light of the MNH a higher level of international diversity is related to a higher level of flexibility and therefore better performance. The MNH does however also recognize the control issues related to the complexity of operations within a large multinational network. The balance between benefits and costs in this theoretical background is therefore based on the offsetting effect of the increased flexibility and the increased complexity of the firm.

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Krist, 2007; Chao & Kumar, 2010; Jong de, Phan & van Ees, 2010). I will do the same and research the moderating effect of environmental turbulence on the I-P relationship. The following section will therefore elaborate on the theoretical grounds for including the environment in this study.

I-P and the environment

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The characteristics of the home country environment which are currently included in I-P research do not coffer the whole spectrum of environmental influences that have been identified in research literature. The theoretical approaches to understanding the environment’s effect on organizations are diverse but do revolve around the industry structure or the task environment of the firm (Rosenbusch, Rauch & Bausch, 2011; Sharfman & Dean, 1991). The industry structure theory is closely related to the work of Porter (1990) and studies the effect of industry characteristics on a firm’s performance (Dess & Beard, 1984; Rosenbusch et al., 2011). The industry based perspective has been criticized as being too much of an aggregation to represent the environmental effects (Dess & Beard, 1984; Rosenbusch et al., 2011). For that reason the task environment of the firm (the organizations interaction with customers, competitors, suppliers, and other stakeholders) is considered to be a more appropriate base for environmental analysis (Rosenbusch et al., 2011). The analysis of the task environment is commonly based on the combination of three constructs developed by Dess and Beard (1984); these constructs are environmental munificence, complexity and dynamism.

Munificence. Environmental munificence refers to the resource availability in a firm’s

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country of origin effect, mainly operationalized through the market size (Bobillio et al., 2010; Elango & Sethi, 2007; Rasheed, 2005; Rosenbusch et al., 2011; Wan & Hoskisson, 2003).

Complexity. The heterogeneity and concentration of environmental elements is referred to

as the environmental complexity (Boyne & Meier, 2009; Dess & Beard, 1984; Rasheed, 2005; Rosenbusch et al., 2011). More specifically the complexity of an environment refers the amount and diversity of information, knowledge, resources, and capabilities needed to successfully operate in an environment (Rosenbusch et al., 2011). As a consequence the environmental complexity is reflected in the perceived uncertainty and greater information processing requirements by management (Dess & Beard, 1984). Additionally the increase in structural complexity of the environment (for instance through internationalization) also increases the need for strategic activity (Dess & Beard, 1984; Rosenbusch et al., 2011).

Dynamism. The construct of environmental dynamism refers to the level of turbulence

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University of Groningen | Hypothesis development 20

the aftermath of the 9-11 terrorist attack (Li, Tallman & Ferreira, 2005) and the effect of hurricane Katrina (Boyne & Meier, 2009). A dynamic environment is often linked to the flexibility of a firm (Mascarenhas, 1985; Rosenbusch et al., 2011; Zhang, 2006). More flexible firms are better able to cope with dynamic environments, and through that logic the environmental dynamism is also related to internationalization and performance as internationalized firms are considered to be more flexible (Baek, 2004; Kogut, 1985).

These three elements together are considered to be a good approximation of the firm’s environment (Dess & Beard, 1984; Rosenbusch et al., 2011), but there is relatively little literature that relates these measures of the environment to the I-P relationship (Kuivalainen, Sundqvist, Purumalainen & Cadogan, 2004). In this research I am specifically looking for the effect of environmental instability on the I-P relationship. The environmental instability is fully captured in the construct of environmental dynamism and more precisely the turbulence as described above. Therefore I will take the dynamism construct and link that to the I-P relationship. In the methodology section I will discuss the operationalization of this construct. However, first the following section presents the hypothesis development.

Hypothesis development

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The I-P relationship has recently been characterized as being S-shaped (Contractor, 2007; Lu & Beamish, 2004; Ruigrok et al., 2007; Thomas & Eden, 2004). This S-shaped relation is a recent revolution which unites seemingly contradictory prior research results in a new three staged model (Contractor, 2007; Lu & Beamish, 2004; Ruigrok et al., 2007; Thomas & Eden, 2004). The three stages of the S-curve theory are discussed below.

The first of these stages represents a low degree of international diversification and the stage theory of internationalization and the MNH offer a theoretical reasoning for an initial decrease in performance. This reasoning is based on high initial costs at the market entry due to the liability of foreignness and limited initial benefits (Bausch & Krist, 2007; Contractor, 2007; Dastidar, 2009; Hennart, 2007; Hitt et al., 2006; Johanson & Vahlne, 2009; Lu & Beamish, 2004; Thomas & Eden, 2004) The length of this stage depends on many factors like the home and host country conditions and the adaptability of the firm (Contractor, 2007).

The second stage is characterized by moderate degrees of international diversification and a positive performance slope. This positive balance between the costs and benefits is related to the RBV and a direct result of a firm’s utilization of its access to cheaper resources; the economies of scale and scope; benefits of synergies; knowledge acquired from earlier foreign expansion; and the internalization of transaction costs (Contractor, 2007; Contractor et al., 2003; Lu & Beamish, 2004; Ruigrok et al., 2007; Thomas & Eden, 2004). The length of this second stage in the S-shaped theory depends on a firm’s ability to organize its operations and to adapt its organization to the increased complexity of its international operations.

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that higher levels of international diversification are expected to increase the performance until a certain threshold level after which the additional cost of increases in international diversification are expected to outweigh the additional benefits (Baek, 2004; Bausch & Krist, 2007 Capar & Kotabe, 2003; Elango & Sethi, 2007; Goerzen & Beamish, 2003; Lu & Beamish, 2004; Reeb et al., 1998). This switch in the balance between benefits and costs is caused by the increased complexity of operations in any additional foreign markets. The complexity is based on the cultural distance which becomes more complicated by the number of foreign markets a firm is operating in. Additionally the complexity increases with the coordination of geographically dispersed markets (Lu & Beamish, 2004; Ruigrok et al., 2007). Based on these three stages I expect the relation between DOI and performance to be non- linear which leads to the following hypothesis:

H1: The relationship between international diversification and performance will be non- linear, with a negative slope at low degrees of international diversification, positive slope at moderate

degrees of international diversification and a negative slope at high degrees of international diversification.

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These reasons are mainly related to the network characteristics of the firm as explained in the MNH. The MNH explains the advantages of the internationalized firms based on the increased flexibility created by the firms’ international operations (Baek, 2004; Bartlett & Ghoshal, 1990; Chung, Lu & Beamish, 2008; Johanson & Vahlne, 2009; Kogut, 1985). According to this theory the increased flexibility offers firm specific advantages, like arbitrage possibilities, cross-subsidization and risk reduction by income stability, in stable environments. I argue that in a dynamic environment the benefits attributable to these advantages increase, because the flexibility is a natural defense mechanism against adverse results in parts of the organization (Amit & Livnat, 1988; Contractor, 2007; Hund et al., 2010; Kim, Hwang & Burgers, 1993; Lu & Beamish, 2004; Rugman, 1976; Reeb et al., 1998).

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University of Groningen | Research Design 24

environments at this level of international diversification, but the value of these benefits are much higher in dynamic environments than in a stable environment. These expectations result in the following hypothesis.

H2. Environmental dynamism moderates the relationship between geographic diversification and firm performance in such a way that higher degrees of international diversification will have

higher performance levels in environmentally dynamic times.

Research Design

In order to draw conclusions on the influence of environmental dynamism on the internationalization – performance relationship this research will utilize quantitative research methods. The research will be based on a sample of German firms for which firm data was gathered over a period from 2005 till 2011. This period includes the effects of the financial crisis which lead to environmental dynamism. In the following sections I will discuss the sample selection, variable operationalization and data analysis.

Sample description

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overview of the industry classifications is included in appendix 1). The data for this sample of firms has been collected using the Orbis database and the firm’s annual reports.

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generalization. In this research the moderating variable of interest is that of the occurrence of environmental turbulence, therefore I control for the effect of the country of origin.

Dependent variable

Firm Performance: ROA

I will use the return on assets (ROA) ratio as the performance measure, which is in line with most of the other research on the DOI performance relation (Bobillo et al., 2010; Contractor et al., 2003; Ruigrok et al., 2007). The ROA will be measured as the pre-tax income divided by the total assets multiplied with 100 (Ruigrok et al., 2007).

Independent variables

Internationalization

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Environmental dynamism

The environmental dynamism measure I will apply in this research is based on the seminal work by Dess and Beard (1984). As explained in the previous sections the construct of the firms environment is operationalized through three variables (munificence, dynamism and complexity) (Boyd, 1990 & 1995; Dess& Beard, 1984; Keats & Hitt, 1988; Sharfman & Dean, 1991). As I try to isolate the effect environmental dynamism has on the I-P relationship I will only utilize the measures that operationalize the dynamism variable.

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The operationalization of the environmental dynamism has been performed in many different ways (Boyd 1990 & 1995; Keats & Hitt, 1988; Sharfman & Dean, 1991), but is generally based on the measures introduced by Dess & Beard (1984), as these measures have proven to withstand critical evaluation (Boyd, 1990).

In this paper I will utilize a small adaptation from the original measure proposed by Dess & Beard (1984). These adaptations are necessary for several reasons. First, the data for all separate industries in the German economy was not complete which makes is impossible to copy the exact measures used in the Dess & Beard (1984) study. Additionally the original measures focus on the industry level environment of the firm, where I am interested in how the national economy affects the firm performance. To resolve this issue I decided to perform the Dess & Beard measures on a national level of analysis, which means that instead of using the industry level value of shipments I used the aggregate value of production for the entire German economy, and the same level of aggregation for the price-cost margin, the total employment and the value added. Secondly the original measures included a variable for technological development within the industry. As the measure on an industry basis was not possible due to the data limitations the inclusion of the variable for technological change was impossible as well. This means that the environmental dynamism measure I apply measures only the economic unpredictable change for the German economy as a whole. In relation to the purpose of this research this measure is able to estimate exactly those aspects of environmental dynamism that I am interested in.

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Where

y = value of production, price-cost margin, total employment or gross value added. t = year, and

α = residual

For the actual calculations of the dynamism variable I will follow Boyd (1988) who calculates the value for any given year, based on the preceding 5 years. For example, the values for 2007 are based on the regression over the period 2003-2007. The values that are summed up to form the dynamism variable are based on the calculation of . An overview of all discussed values is available in appendix three.

Control variables

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expenses to net sales. Finally there will be controls for the age of the firm, product

diversification (Baek, 2004; Goerzen & Beamish, 2003) and industry (Capar & Kotabe, 2003;

Contractor et al., 2003; Goerzen & Beamish, 2003; Ruigrok et al., 2007). An overview of all variables, the operationalization and the data sources is presented in table 1. The summary statistics for the variables described above are presented in table 2.

Table 1

Variable Definition Abbreviation Data Source

Dependent variable

Firm Performance Return on Assets = pre-tax income / total assets * 100

ROA Orbis

Independent variable

Internationalization DOI = Foreign Sales percentage times the Foreign Assets percentage

DOI Annual reports

Moderating variable

Environmental dynamism

See appendix 3 DYN Eurostat

Control variables

Size Natural Log of Number of employees SIZE Orbis

Leverage Liquidity ratio LIQ Orbis

Intangibles R&D expenses / net sales R&D Orbis

Age Date of incorporation AGE Orbis

Product diversification Difference between subsidiary 2 digit SEC-code and company 2 digit SEC code.

DIV Dummy Orbis

Industry Companies 2 digit SEC-code IND Dummy Orbis

Data Analysis Technique

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time-University of Groningen | Research Design 31

series and cross-sectional data points to enable statistical analysis of the relations between the different variables introduced before. Preliminary analysis indicated the existence of outliers which were removed from further analysis resulting in a dataset of 455 firm year observations.

In respect to the regression analysis of panel data there are several options from which to choose the most appropriate analysis technique. Depending on the homogeneity among the cross-sectional data groups the pooled regression, fixed effects model or random effects model is considered to be the most appropriate technique. The results of the pooled OLS regression analysis showed low standard errors indicating a relatively homogenous cross-sectional data panel. Additionally the Durbin-Watson scores resulting from the pooled OLS regression are indicative of negligible levels of autocorrelation, which indicates no need for further complicating the analysis. Based on these considerations the pooled OLS regression is an appropriate technique for analyzing the panel dataset created for this research. Additionally utilizing the pooled OLS regression is similar to techniques applied by Thomas and Eden (2004) and Ruigrok, Amann and Wagner (2007) who also investigate the I-P relationship with panel data analysis.

The OLS regression analysis will be performed by using the SPSS statistics program and testing the following general regression function:

ROA = β1 SIZE + β2 LIQ + β3 R&D + β4 AGE + β5 DIV Dummy + β6INS + β7DOI + β8 DOI2 + β9DOI3 + β10 (DOI*DYN) + β11 IND Dummy’s + α

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University of Groningen | Results 32

well. Additionally to this data adaptation the continuous variables will also be standardized with the goal to make interpretation of the coefficients easier. The results of the regression analysis are presented in table 3, which does not include the results for the industry dummy variables in order to conserve space. The full table including the industry dummy variables is included in appendix 4.

Table 2

Descriptive Statistics and Correlations (N= 455).

The significance levels are represented as follows: ** = 1% significance level, * = 5% significance level

Results

The intercorrelations among the set of predictor variables included in the summary statistics indicate that there is no sign of multicollinearity. Additionally table 2 shows that the average firm in the sample operates at an internationalization level of .32, which indicates a left sided bias on the internationalization continuum. The firms included in the sample do however cover the full range of internationalization with a minimum value of 0 and a maximum of .95. The dynamism measure has an average score of .029 for which there are relatively little results which I can compare this to. Looking at the original article by Dess andBeard (1984) who measured a

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Table 3

The table reports the results of 5 regression models with the t-values in brackets (N= 455). The significant results are presented as follows: *** = 1% significance level; **= 5% significance level * = 10% significance level. The variables that are marked with a * show standardized coefficients.

Independent Variables Model 1 Model 2 Model 3 Model 4 Model 5

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minimum dynamism score of -1.246 and a maximum of 3.527, this level of dynamism would be just inside the top 20 of the dynamic industries they measured (total of 52 industries included in their research). As such the German economy between 2007 and 2011 should be described as a relatively stable economy. The correlations in table 2 also confirm the general notions that older and larger firms are more internationalized (Hennart, 2007), which can be based on the positive correlations between the degree of internationalization and both the age and the size of the firm. These figures also support the decision to include the firm size, liquidity, R&D expenditure, firm age and product diversification in the regression analysis as control variables.

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University of Groningen | Discussion 35

a positive effect on a firm’s performance. The second hypothesis is represented by model 5, which includes the interaction variable between internationalization and environmental dynamism. The results do not significantly support hypothesis 2. Where the coefficient is correctly signed, indicating that the effect international diversification has on firm performance becomes more positive in periods with a more dynamic environment; the non-significance of this coefficient obliges to reject the second hypothesis. To sum up, the results presented in table three confirms the existence of an S-shaped relation between internationalization and firm performance, but is unable to significantly support the notion that the attributes ascribed to internationalization are of higher value when environmental dynamism increases.

Discussion

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Additionally the context of these findings, and especially the country of origin effect, needs to be taken into account. The same is naturally true for the support found for the S-curve hypothesis, which I will discuss first.

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larger market with similar institution and cultures is expected to have the same effect (Ruigrok et al., 2007). Based on these factors the German market has a different profile from the Japanese, American and Swiss market, and as such the generalizability of the S-curve hypothesis increases. Additionally this research adds to the generalizability by including a new control variable into the S-curve measurements. The results are also significant when controlling for environmental dynamism, which suggests that even in dynamic environments there is support for the S-curve hypothesis. In light of these results future research should research the S-curve hypothesis in highly dynamic environments like developing markets and other developed markets enduring a financial crisis.

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safe to say that the results presented in this research are not proof that supports the second hypothesis developed in this research they are interesting enough to prompt further research. In the following section I will discuss the implications that can be based on this research and the limitations that where incorporated in the research design.

Implications

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first attempt to incorporate environmental dynamism into the I-P relationship. The theory developed for this purpose, as based on Dess and Beard (1984), is new to the I-P research. Also new is the stability measurement I apply to interact with the level of international diversification. There is very little business research that includes economic measures for environmental stability. The results show that the dynamism measure can significantly influence firm performance; however future research is needed to further develop the measure and test its applicability to different environments / economies and different time frames, as discussed above. The research I have performed also has several practical implications. Knowing the effect of international diversification on firm performance and knowing what this means in times of environmental dynamism is valuable information to management teams operating newly internationalizing and internationally diverse firms. This research implies that it is beneficial to operate an international diverse firm and that these benefits increase in times of environmental dynamism. Additionally the results indicate that when controlling for environmental dynamism the shape of the I-P relationship remains the same, which is valuable to management as it makes the development of an internationalizing corporation more predictable. Several subjects for future research have already been mentioned and I expect that this future research can reinforce the practical implications suggested above.

Limitations

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University of Groningen | Conclusion 40

sample represents a bias towards newly internationalizing firms and firms who operate at relatively low levels of international diversification. Nonetheless the results support the S-curve hypothesis. Still it can be expected that the statistics show different results for analysis of a sample of firms that are evenly distributed or that might have a right sided bias. Secondly the sample size consisting of 94 German firms and a total of 455 firm year observation might be considered relatively small. A bigger sample size could result in more reliable results and cause a more even distribution of the degree of internationalization. Finally I already discussed the context relatedness of the interaction results; however I want to reiterate that the choice for the German market could be interpreted as a limitation to this research. Other economies with more dynamic environments could produce more support for the hypothesis in this research, which could be a starting point for future research.

Conclusion

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University of Groningen | References 41

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University of Groningen | Appendix 1 47

Appendix 1

Industry Classification

The overview presented in figure .. is produced by the European Union and offers a broad overview of the Industry and divisions included in the NACE Rev. 2 classification system which was also applied to the companies included in the sample of this research.

Figure 1

Source: European Commission (2008), NACE Rev. 2 – Statistical classification of economic activites in the European Community. Luxembourg: Office for Official Publications of the European Communities. 363 pp.

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Appendix 2

Data gathering methodology

The data on the foreign sales percentage and foreign assets percentage used to calculate the degree of international diversification was done manually by finding the needed figures in the separate firm’s annual reports. The calculations where performed based on the revenue data as reported by the firms included in the sample. The formula’s used to calculate this data where:

FSTS = 1 – (German Revenue / Total Revenue) * 100 FATA = 1 – (German Assets / Total Assets) *100

For an example of these figures and the way they are presented in the annual reports I refer to figure 2 presented in this appendix

On some occasion the firm changed its reporting methods within the timeframe I am interested in. For some companies this meant that the reporting on the business segment Europe, which included Germany changed into a two separate segments being Germany and Rest of Europe. In these occasions I would still only be interested in the segment reporting for the segment Germany over the entire period, so to enable the data gathering for German segment I have calculated the percentage value of the German segment in relation to the Total Europe segment for the periods in which these segments where reported on separately and use this percentage to calculate the German segment for the periods in which the company would only report on the Europe segment. This technique was applied to complete the data for 5 out of the 94 firms in the sample. The formula’s used to calculate these values are as follows:

German % = German segment / (German segment + Rest of Europe segment) The FSTS and FATA calculation would then be as follows:

FSTS = 1 – ((German % * Europe revenue) / Total revenue) FATA = 1 – ((German % * Europe assets) / Total assets)

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Figure 2

An excerpt from the annual report of Man SE. The picture shows the Segment information by region as reported in the annual report of Man SE (year 2011, page 168)

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Figure 3

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Appendix 3

Table 4

The table reports the separate dynamism values which have been used to compute the dynamism value used in this paper. The reported standard errors are based on the following equation:

, Where

y = value of production, price-cost margin, total employment or gross value added. t = year, and

α = residual

2007 2008 2009 2010 2011

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Appendix 4

Table 5

The table reports the results of 5 regression models with the t-values in brackets (N= 455). The significant results are presented as follows: *** = 1% significance level; **= 5% significance level * = 10% significance level. The variables that are marked with a * show standardized coefficients.

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